| 1 |
Anesthesia for CT.Scan of Brain |
1300 BDT |
| 2 |
Anesthesia for CT.Scan of Brain + EEG |
2500 BDT |
| 3 |
Anesthesia for CT.Scan of Brain+PNS/Orbit |
2000 BDT |
| 4 |
Anesthesia for CT.Scan of Ear+MRI of Ear |
2500 BDT |
| 5 |
Anesthesia for CT.Scan of Ear+MRI of Ear+Echo |
3000 BDT |
| 6 |
Anesthesia for CT.Scan of Joint(Shoulder/Hip/Knee/Ankle etc) |
1500 BDT |
| 7 |
Anesthesia for CT.Scan of Upper/Lower Abdomen |
1500 BDT |
| 8 |
Anesthesia for CT.Scan of Whole Abdomen |
1500 BDT |
| 9 |
Anesthesia for MRI of Brain |
1500 BDT |
| 10 |
Anesthesia for MRI of Brain + EEG |
2500 BDT |
| 11 |
Anesthesia for MRI of Joint(Shoulder/Hip/Knee/Ankle etc) |
1500 BDT |
| 12 |
Anesthesia for MRI of Upper/Lower Abdomen |
1500 BDT |
| 13 |
Anesthesia for MRI of Whole Spine |
3000 BDT |
| 14 |
AP Spine 2 (Two) side measurement of bone densitometer (Dexa Scan)(2203) |
3000 BDT |
| 15 |
CBCT - Airway Analysis |
2000 BDT |
| 16 |
CBCT - Both Jaw |
6000 BDT |
| 17 |
CBCT - ENT Imaging |
9000 BDT |
| 18 |
CBCT - Full Face |
7000 BDT |
| 19 |
CBCT - Middle Ear (Double) |
4000 BDT |
| 20 |
CBCT - Middle Ear (Single) |
2500 BDT |
| 21 |
CBCT - Sinus |
4500 BDT |
| 22 |
CBCT -Single Jaw |
3500 BDT |
| 23 |
CBCT -Single Quadrant |
3000 BDT |
| 24 |
CBCT -Single Tooth |
2500 BDT |
| 25 |
CBCT -TMJ (Close & Open Mouth) |
3000 BDT |
| 26 |
CBCT -TMJ (Close Mouth) |
2000 BDT |
| 27 |
Cephalometric View |
450 BDT |
| 28 |
Choanogram (Nasal) |
2000 BDT |
| 29 |
Cine MRI of Cysternogram |
9000 BDT |
| 30 |
CT Angio Abdomenal Vessel |
14000 BDT |
| 31 |
CT Angio of Aortogram |
14000 BDT |
| 32 |
CT Angio of Brain |
10000 BDT |
| 33 |
CT Angio of Brain & Neck Vessel |
15000 BDT |
| 34 |
CT Angio of Cardiac |
14000 BDT |
| 35 |
CT Angio of Liver / Three Phase Liver |
14000 BDT |
| 36 |
CT Angio of Neck Vessels |
10000 BDT |
| 37 |
CT Angio of Peripheral Lower Limbs |
15000 BDT |
| 38 |
CT Angio of Peripheral Upper Limbs |
15000 BDT |
| 39 |
CT Angio of Pulmonary Vessel |
14000 BDT |
| 40 |
CT Angio of Renal |
14000 BDT |
| 41 |
CT Cisternography / Cistetnogram |
12000 BDT |
| 42 |
CT Enterography |
12000 BDT |
| 43 |
CT Guided FNAC-1 |
4000 BDT |
| 44 |
CT Guided FNAC-2 |
4000 BDT |
| 45 |
CT Nesopharunx |
6000 BDT |
| 46 |
CT Oesophagus |
6000 BDT |
| 47 |
CT Scan of Base of the Skull |
6000 BDT |
| 48 |
CT Scan of Ears |
6000 BDT |
| 49 |
CT Scan of Left Ankle |
6000 BDT |
| 50 |
CT Scan of Left Ear/Mastoid |
6000 BDT |
| 51 |
CT Scan of Left Elbow Joint |
6000 BDT |
| 52 |
CT Scan of Left Foot |
6000 BDT |
| 53 |
CT Scan of Left Hip Joint |
6000 BDT |
| 54 |
CT Scan of Left Knee Joint |
6000 BDT |
| 55 |
CT Scan of Left Leg |
6000 BDT |
| 56 |
CT Scan of Left Shoulder Joint |
6000 BDT |
| 57 |
CT Scan of Left Thigh |
6000 BDT |
| 58 |
CT Scan of Left Wrist Joint |
6000 BDT |
| 59 |
CT Scan of Orbits |
6000 BDT |
| 60 |
CT Scan of Right Ankle |
6000 BDT |
| 61 |
CT Scan of Right Elbow Joint |
6000 BDT |
| 62 |
CT Scan of Right Foot |
6000 BDT |
| 63 |
CT Scan of Right Hip Joint |
6000 BDT |
| 64 |
CT Scan of Right Knee Joint |
6000 BDT |
| 65 |
CT Scan of Right Leg |
6000 BDT |
| 66 |
CT Scan of Right Mastoid |
6000 BDT |
| 67 |
CT Scan of Right Shoulder Joint |
6000 BDT |
| 68 |
CT Scan of Right Thigh |
6000 BDT |
| 69 |
CT Scan of Right Wrist Joint |
6000 BDT |
| 70 |
CT Supra-renalgland |
6000 BDT |
| 71 |
CT Urography |
14000 BDT |
| 72 |
Dental film - One film |
150 BDT |
| 73 |
Dental film - Three film |
450 BDT |
| 74 |
Dental film - Two film |
300 BDT |
| 75 |
Digital Micturating Cysto Urethrogram ( M.C. U ) |
2500 BDT |
| 76 |
Digital 24 Hrs. late Film for Barium Follow through |
400 BDT |
| 77 |
Digital 24 Hrs. late Film for I.V.U. |
400 BDT |
| 78 |
Digital Ba-meal study of small bowel Ileo-caecal gut with spot film of Ileo-caecal gut |
2000 BDT |
| 79 |
Digital Ba-meal study of Stomach, Duodenum, Follow through(G.I. Tract) |
2000 BDT |
| 80 |
Digital Ba-meal study of Stomach,Duodenum & Followthrough of small gut & Ileo-caecal gut |
2000 BDT |
| 81 |
Digital Barium enema of colon (large gut) Double contrast |
2500 BDT |
| 82 |
Digital Barium meal study of Ileo-caecal gut and appendix |
2000 BDT |
| 83 |
Digital Barium meal study of Stomach, Duodenum |
2000 BDT |
| 84 |
Digital Barium meal study of Stomach, Duodenum (Double contrast) |
2000 BDT |
| 85 |
Digital Barium meal study of Stomach, Duodenum & Hiatus Hernia |
2000 BDT |
| 86 |
Digital Barium meal study of Stomach, Duodenum including (G.I. Tract) |
2000 BDT |
| 87 |
DIgital Barium Swallow of Oesophagus |
2000 BDT |
| 88 |
Digital Barium Swallow of Oesophagus including Hiatus Hernia |
2000 BDT |
| 89 |
Digital Cologram/Loopogram (Barium enema) through colostomy opening |
2500 BDT |
| 90 |
Digital Fluoroscopy of chest to see movement of diaphragm with one spot film |
500 BDT |
| 91 |
Digital O.C.G. (Oral Cholecystography) |
1500 BDT |
| 92 |
Digital Retrograde Pyelography (Urography) |
2000 BDT |
| 93 |
Digital Retrograde Urethrogram (RGU) |
2500 BDT |
| 94 |
Digital Retrograde Urethrogram with Antegrade cystogram |
2000 BDT |
| 95 |
Digital Retrograde Urethrogram with MCU |
2500 BDT |
| 96 |
Digital X - Ray of Flexion and Extension |
800 BDT |
| 97 |
Digital X-Ray Extra film |
400 BDT |
| 98 |
Digital X-Ray for 100% (One Film) |
400 BDT |
| 99 |
Digital X-Ray for 100% (Three Films) |
1200 BDT |
| 100 |
Digital X-Ray for 100% (Two Films) |
800 BDT |
| 101 |
Digital X-Ray of Both Ankle joint Lateral view |
400 BDT |
| 102 |
Digital X-Ray of Both Shoulder joint Lateral view |
800 BDT |
| 103 |
Digital X-Ray of .................. |
400 BDT |
| 104 |
Digital X-Ray of Abdomen Erect Posture AP & Lat. View |
1200 BDT |
| 105 |
Digital X-Ray of Abdomen Erect Posture Including Diaphragm (Child) |
400 BDT |
| 106 |
Digital X-Ray of Acoustic meatus perorbital view |
400 BDT |
| 107 |
Digital X-Ray of Atlanto axial joint OM view |
400 BDT |
| 108 |
Digital X-Ray of Atlanton Axial O.M & Lateral View ( B / V ) |
800 BDT |
| 109 |
Digital X-Ray of Ba-enema of colon Single contrast of child to examin Hirscha. |
2000 BDT |
| 110 |
Digital X-Ray of Ba-Followthrough double contrast |
2000 BDT |
| 111 |
Digital X-Ray of Ba-meal of small intestine and follow thorough |
3000 BDT |
| 112 |
Digital X-Ray of Bone age ( Adult Clavicle & Pelvis) |
800 BDT |
| 113 |
Digital X-Ray of Bone Age (Child) |
800 BDT |
| 114 |
Digital X-Ray of Both Ankle Joint (B/V) |
800 BDT |
| 115 |
Digital X-Ray of Both Ankle Joint & Both Foot |
2000 BDT |
| 116 |
Digital X-Ray of Both Ankle Joint AP View |
400 BDT |
| 117 |
Digital X-Ray of Both Ankle Joint Lateral View |
400 BDT |
| 118 |
Digital X-Ray of Both Clavicle AP View |
400 BDT |
| 119 |
Digital X-Ray of Both Feet AP View |
400 BDT |
| 120 |
Digital X-Ray of Both feet both view |
800 BDT |
| 121 |
Digital X-Ray of Both Feet Lateral View |
400 BDT |
| 122 |
Digital X-Ray of Both foot (B/V) |
800 BDT |
| 123 |
Digital X-Ray of Both Hand (B/V) |
800 BDT |
| 124 |
Digital X-Ray of Both Hand AP View |
400 BDT |
| 125 |
Digital X-Ray of Both Hand B/V |
800 BDT |
| 126 |
Digital X-Ray of Both hand for bone age |
800 BDT |
| 127 |
Digital X-Ray of Both Hand Lateral View |
400 BDT |
| 128 |
Digital X-Ray of Both hand with wrist joint AP view |
400 BDT |
| 129 |
Digital X-Ray of Both Heel B/V |
800 BDT |
| 130 |
Digital X-Ray of Both heel lateral view for soft tissue |
400 BDT |
| 131 |
Digital X-Ray of Both hip joint (B/V) |
1200 BDT |
| 132 |
Digital X-Ray of Both hip joint Lat view |
800 BDT |
| 133 |
Digital X-Ray of Both Knee AP, Lat Rt & Lt. Oblique standing position |
2000 BDT |
| 134 |
Digital X-Ray of Both Knee Joint and Oblique View |
2000 BDT |
| 135 |
Digital X-Ray of Both Knee Joint and Skyline B/V |
1200 BDT |
| 136 |
Digital X-Ray of Both Knee Joint AP View |
400 BDT |
| 137 |
Digital X-Ray of Both Knee Joint AP View Standing Position |
800 BDT |
| 138 |
Digital X-Ray of Both Knee Joint B/V (Child) |
800 BDT |
| 139 |
Digital X-Ray of Both Knee Joint Lat. View |
400 BDT |
| 140 |
Digital X-Ray of Both Knee Joint skyline position |
400 BDT |
| 141 |
Digital X-Ray of Both Knee Joints(BV) AP & Lateral |
800 BDT |
| 142 |
Digital X-Ray of Both Leg AP View |
800 BDT |
| 143 |
Digital X-Ray of Both Leg with Ankle Joint in Standing Position |
1600 BDT |
| 144 |
Digital X-Ray of Both Mastoid AP oblique & Lateral Oblique view |
800 BDT |
| 145 |
Digital X-Ray of Both Shoulder AP & Axillary View |
2000 BDT |
| 146 |
Digital X-Ray of Both shoulder joint (B/V) |
1600 BDT |
| 147 |
Digital X-Ray of Both Shoulder joint AP View |
800 BDT |
| 148 |
Digital X-Ray of Both T.M. Joint open & close Mouth |
1600 BDT |
| 149 |
Digital X-Ray of Both Wrist AP View |
400 BDT |
| 150 |
Digital X-Ray of Both Wrist Lateral View |
400 BDT |
| 151 |
Digital X-Ray of C. Spine AP,Lat,Flexion,Extension,Neutral |
2000 BDT |
| 152 |
Digital X-Ray of Cervical One Oblique View |
400 BDT |
| 153 |
Digital X-Ray of Cervical spine AP & both lat view |
1200 BDT |
| 154 |
Digital X-Ray of Cervical spine AP & Both oblique View |
1200 BDT |
| 155 |
Digital X-Ray of Cervical spine AP & Lateral View (B/V) |
800 BDT |
| 156 |
Digital X-Ray of Cervical spine AP & One oblique View |
800 BDT |
| 157 |
Digital X-Ray of Cervical spine AP View Only |
400 BDT |
| 158 |
Digital X-Ray of Cervical spine AP, Lateral & Both oblique View |
1600 BDT |
| 159 |
Digital X-Ray of Cervical spine AP, Lateral & Left oblique View |
1200 BDT |
| 160 |
Digital X-Ray of Cervical spine AP, Lateral & Right oblique View |
1200 BDT |
| 161 |
Digital X-Ray of Cervical spine AP,Lat,Flexion,Extension, & Rt. oblique view |
2000 BDT |
| 162 |
Digital X-Ray of Cervical Spine B/V with Atlanto Axial Joint |
1200 BDT |
| 163 |
Digital X-Ray of Cervical Spine Both Lateral View |
800 BDT |
| 164 |
Digital X-Ray of Cervical Spine Both Oblique View |
800 BDT |
| 165 |
Digital X-Ray of Cervical spine flexion, extention and open mouth |
1200 BDT |
| 166 |
Digital X-Ray of Cervical spine Lateral & Both oblique View |
1200 BDT |
| 167 |
Digital X-Ray of Cervical spine Lateral & One oblique View |
800 BDT |
| 168 |
Digital X-Ray of Cervical spine Lateral View |
400 BDT |
| 169 |
Digital X-Ray of Cervical spine One Oblique View Only |
400 BDT |
| 170 |
Digital X-Ray of Cervico-dorsal spine (Cervico-Thoracic) spine AP & Lateral view |
800 BDT |
| 171 |
Digital X-Ray of Chest AP View (100% Equal Size) |
400 BDT |
| 172 |
Digital X-Ray of Chest AP, Rt. Letaral, Oblique View |
800 BDT |
| 173 |
Digital X-Ray of Chest apical lordotic & Lt. Lat view |
800 BDT |
| 174 |
Digital X-Ray of Chest Apical view |
400 BDT |
| 175 |
Digital X-Ray of Chest for Rib Left Side (Oblique View) |
400 BDT |
| 176 |
Digital X-Ray of Chest for Rib Right Side (Oblique View) |
400 BDT |
| 177 |
Digital X-Ray of Chest Inspiratory & Expiratory PA view |
800 BDT |
| 178 |
Digital X-Ray of Chest left lateral decubitus view |
400 BDT |
| 179 |
Digital X-Ray of Chest left lateral view |
400 BDT |
| 180 |
Digital X-Ray of Chest Lordotic View |
400 BDT |
| 181 |
Digital X-Ray of Chest P/A View (100% Equal Size) |
400 BDT |
| 182 |
Digital X-Ray of Chest PA & lateral view |
800 BDT |
| 183 |
Digital X-Ray of Chest PA & left lateral view |
800 BDT |
| 184 |
Digital X-Ray of Chest PA & right lateral view |
800 BDT |
| 185 |
Digital X-Ray of Chest PA with Sternum |
1050 BDT |
| 186 |
Digital X-Ray of Chest Penetrating Lateral View |
400 BDT |
| 187 |
Digital X-Ray of Chest Penetrating View |
400 BDT |
| 188 |
Digital X-Ray of Chest right lateral decubitus view |
400 BDT |
| 189 |
Digital X-Ray of Chest right lateral view |
400 BDT |
| 190 |
Digital X-Ray of Clavical (B/V) |
800 BDT |
| 191 |
Digital X-Ray of Coccyx Bone Both View |
800 BDT |
| 192 |
Digital X-Ray of Cone both Lat view of lumbo secral joint |
800 BDT |
| 193 |
Digital X-Ray of Cone down AP & Lat view |
800 BDT |
| 194 |
Digital X-Ray of Cone down Lateral View |
400 BDT |
| 195 |
Digital X-Ray of Dacrocystogram |
3000 BDT |
| 196 |
Digital X-Ray of Distal Cologram |
2500 BDT |
| 197 |
Digital X-Ray of Dorsal (Thoracic) spine AP & Lateral View |
800 BDT |
| 198 |
Digital X-Ray of Dorsal (Thoracic) spine AP View |
400 BDT |
| 199 |
Digital X-Ray of Dorsal (Thoracic) spine AP, Lateral & Both oblique View |
1600 BDT |
| 200 |
Digital X-Ray of Dorsal (Thoracic) spine AP, Lateral & One oblique View |
1200 BDT |
| 201 |
Digital X-Ray of Dorsal (Thoracic) spine Lateral View |
400 BDT |
| 202 |
Digital X-Ray of Dorsal spine AP, Lat & Both oblique view |
2000 BDT |
| 203 |
Digital X-Ray of Dorsal Spine both Lateral view |
800 BDT |
| 204 |
Digital X-Ray of Dorsal Spine both Oblique view |
800 BDT |
| 205 |
Digital X-Ray of Dorso lumber ( Thoraco-Lumber ) Spine AP View |
400 BDT |
| 206 |
Digital X-Ray of Dorso lumber (Thoraco-Lumber) spine (B/V) AP & Lateral View(874) |
800 BDT |
| 207 |
Digital X-Ray of Dorso Lumber (Thoraco-Lumber) Spine AP View |
400 BDT |
| 208 |
Digital X-Ray of Dorso lumber (Thoraco-Lumber) spine Lateral View |
400 BDT |
| 209 |
Digital X-Ray of Dorso Lumber Spine AP,Lat,Flexion,Extension,Neutral |
2000 BDT |
| 210 |
Digital X-Ray of Dorso-Lumbar spine both lateral view |
800 BDT |
| 211 |
Digital X-Ray of Dorso-Lumbar spine both oblique view |
800 BDT |
| 212 |
Digital X-Ray of Dorso-Lumber AP, Lat & Oblique View |
1600 BDT |
| 213 |
Digital X-Ray of Face |
400 BDT |
| 214 |
Digital X-Ray of Face AP & Lat. View |
800 BDT |
| 215 |
Digital X-Ray of Ferguson View |
800 BDT |
| 216 |
Digital X-Ray of Fistulogram |
2000 BDT |
| 217 |
Digital X-Ray of Fluroscopic Guided Marking of Disc Level |
400 BDT |
| 218 |
Digital X-Ray of Hysterosalpingography |
2000 BDT |
| 219 |
Digital X-Ray of I. A. M. Perorbital view |
400 BDT |
| 220 |
Digital X-Ray of I. V. U. |
2000 BDT |
| 221 |
Digital X-Ray of I. V. U. with late film |
3000 BDT |
| 222 |
Digital X-Ray of I. V. U. with M. C. U. |
2500 BDT |
| 223 |
Digital X-Ray of Invertogram |
400 BDT |
| 224 |
Digital X-Ray of Invertogram (Plain abdomen erect lateral with legs uo) |
400 BDT |
| 225 |
Digital X-Ray of Knee joint oblique view RT (ONE FILM) |
400 BDT |
| 226 |
Digital X-Ray of L/S spine Ap & Both Lat view |
1200 BDT |
| 227 |
Digital X-Ray of L/S spine AP,Lat,Flexion,Extension, & Rt. oblique view |
2000 BDT |
| 228 |
Digital X-Ray of L/S Spine Both Oblique View |
800 BDT |
| 229 |
Digital X-Ray of L/S Spine Left Oblique View |
400 BDT |
| 230 |
Digital X-Ray of L/S Spine Rt. Oblique View |
400 BDT |
| 231 |
Digital X-Ray of L/S, Spine both lateral view |
800 BDT |
| 232 |
Digital X-Ray of Left Ankle joint AP & Lateral view |
400 BDT |
| 233 |
Digital X-Ray of Left Clavicle AP & Lateral View |
800 BDT |
| 234 |
Digital X-Ray of Left Clavicle AP View |
400 BDT |
| 235 |
Digital X-Ray of Left Ear |
400 BDT |
| 236 |
Digital X-Ray of Left Elbow joint AP & Lateral view |
400 BDT |
| 237 |
Digital X-Ray of Left Elbow joint AP, Lat. & oblique view |
400 BDT |
| 238 |
Digital X-Ray of Left Foot AP & Oblique View (B/V) |
400 BDT |
| 239 |
Digital X-Ray of Left Forearm (Radius&Ulna) AP & Lat.View including Wrist joint |
400 BDT |
| 240 |
Digital X-Ray of Left Forearm(Radius&Ulna)AP &Lat.View inclu.Elbow &Wrist joint |
400 BDT |
| 241 |
Digital X-Ray of Left Hand AP & Lateral View |
400 BDT |
| 242 |
Digital X-Ray of Left Hand PA & Oblique View |
400 BDT |
| 243 |
Digital X-Ray of Left Heel (Calcaneum) Axial & Lateral View |
400 BDT |
| 244 |
Digital X-Ray of Left hip joint AP & Lateral View |
800 BDT |
| 245 |
Digital X-Ray of Left hip joint AP View |
400 BDT |
| 246 |
Digital X-Ray of Left hip joint Lateral View |
400 BDT |
| 247 |
Digital X-Ray of Left Hip joint oblique view |
400 BDT |
| 248 |
Digital X-Ray of Left Humerus (Arm) AP & Lat. View including Shoulder joint |
800 BDT |
| 249 |
Digital X-Ray of Left Humerus (Arm)AP &Lat.View including Shoulder &Elbow joint |
800 BDT |
| 250 |
Digital X-Ray of Left knee joint (B/V) AP & Lateral view |
400 BDT |
| 251 |
Digital X-Ray of Left knee joint AP, Lateral & Skyline view |
800 BDT |
| 252 |
Digital X-Ray of Left knee joint AP, Lateral, Skyline & Intercondylar view |
1200 BDT |
| 253 |
Digital X-Ray of Left Leg (Tibia & Fibula) including Knee & Ankle joint |
800 BDT |
| 254 |
Digital X-Ray of Left Leg including ankle joint AP & Lat view |
800 BDT |
| 255 |
Digital X-Ray of Left Leg including knee joint AP & Lat view |
800 BDT |
| 256 |
Digital X-Ray of Left lower jaw AP, Lat & Oblique view |
1200 BDT |
| 257 |
Digital X-Ray of Left Orbit AP & Lateral (Up & Down) |
800 BDT |
| 258 |
Digital X-Ray of Left Scapula AP & Lateral view with shoulder joint |
800 BDT |
| 259 |
Digital X-Ray of Left Scapula AP view |
400 BDT |
| 260 |
Digital X-Ray of Left shoulder joint AP View |
400 BDT |
| 261 |
Digital X-Ray of Left sub-mandibular gland lateral oblique view |
400 BDT |
| 262 |
Digital X-Ray of Left T.M. Joint open & close Mouth |
800 BDT |
| 263 |
Digital X-Ray of Left Thigh (femur) AP & Lateral view including Knee joint |
800 BDT |
| 264 |
Digital X-Ray of Left Thigh (femur) AP& Lateral view inclu.hip joint in one film |
800 BDT |
| 265 |
Digital X-Ray of Left Thigh (femur)AP& Lateral view inclu.Knee joint in one film |
800 BDT |
| 266 |
Digital X-Ray of Left Thigh (femur)AP& Lateral view including hip joint |
800 BDT |
| 267 |
Digital X-Ray of Left thumb (B/V) |
400 BDT |
| 268 |
Digital X-Ray of Left Thumb B/V |
400 BDT |
| 269 |
Digital X-Ray of Left Wrist joint AP, Lateral View & Oblique view |
400 BDT |
| 270 |
Digital X-Ray of Left Wrist Joint PA & Lateral View |
400 BDT |
| 271 |
Digital X-Ray of Lower Limb AP |
800 BDT |
| 272 |
Digital X-Ray of Lower Limb Lateral |
800 BDT |
| 273 |
Digital X-Ray of LS Spine AP,Lat,Flexion,Extension,Neutral |
2000 BDT |
| 274 |
Digital X-Ray of Lt. Arm AP & Lateral View |
800 BDT |
| 275 |
Digital X-Ray of Lt. Foot AP & Lat. View |
400 BDT |
| 276 |
Digital X-Ray of Lt. Foot including ankle joint (B/V) |
800 BDT |
| 277 |
Digital X-Ray of Lt. Foot including heel lat view |
400 BDT |
| 278 |
Digital X-Ray of Lt. Heel with Ankle AP and Lat View |
800 BDT |
| 279 |
Digital X-Ray of Lt. Index Finger AP & Lat View |
400 BDT |
| 280 |
Digital X-Ray of Lt. Knee Joint AP & Lat. View ( Standing Position) |
800 BDT |
| 281 |
Digital X-Ray of Lt. Knee Joint AP, Lat in weight bearing position |
800 BDT |
| 282 |
Digital X-Ray of Lt. Knee joint AP, Lat. & Intercondylar view |
800 BDT |
| 283 |
Digital X-Ray of Lt. Leg AP & Lateral view (Child) |
400 BDT |
| 284 |
Digital X-Ray of Lt. Little Finger AP & Lat View |
400 BDT |
| 285 |
Digital X-Ray of Lt. Middle Finger AP & Lateral View |
400 BDT |
| 286 |
Digital X-Ray of Lt. Patella Axial View |
400 BDT |
| 287 |
Digital X-Ray of Lt. Ring Finger AP & Lat View |
400 BDT |
| 288 |
Digital X-Ray of Lt. Shoulder Joint AP & Lateral View |
800 BDT |
| 289 |
Digital X-Ray of Lt. Shoulder joint AP, Lat. & oblique view |
1200 BDT |
| 290 |
Digital X-Ray of Lt. Shoulder Jt. AP,Lat,Abduction,Adduction |
2000 BDT |
| 291 |
Digital X-Ray of Lt. Shoulder Jt. AP,Lat,Internal & External rotation |
2000 BDT |
| 292 |
Digital X-Ray of Lt. Thight AP & Lateral view (Child) |
400 BDT |
| 293 |
Digital X-Ray of Lumber spine (B/V) AP & Lateral View |
800 BDT |
| 294 |
Digital X-Ray of Lumber Spine AP View |
400 BDT |
| 295 |
Digital X-Ray of Lumber Spine AP, Lat & Both Oblique View |
1600 BDT |
| 296 |
Digital X-Ray of Lumber Spine lateral view |
400 BDT |
| 297 |
Digital X-Ray of Lumbo Sacral Spine P/A view |
400 BDT |
| 298 |
Digital X-Ray of Lumbo secral lat & oblique view |
1200 BDT |
| 299 |
Digital X-Ray of Lumbo-sacral spine AP View |
400 BDT |
| 300 |
Digital X-Ray of Lumbo-sacral spine (B/V) AP & Lateral View |
800 BDT |
| 301 |
Digital X-Ray of Lumbo-sacral spine (B/V) PA & Lateral View |
800 BDT |
| 302 |
Digital X-Ray of Lumbo-sacral spine AP & Both oblique View |
1200 BDT |
| 303 |
Digital X-Ray of Lumbo-sacral spine Lateral View |
400 BDT |
| 304 |
Digital X-Ray of Lumbo-sacral spine PA, Lateral & Both oblique View |
1600 BDT |
| 305 |
Digital X-Ray of Lumbo-sacral spine PA, Lateral & One oblique View |
1200 BDT |
| 306 |
Digital X-Ray of Lumbo-Secral Spine Both Oblique View |
800 BDT |
| 307 |
Digital X-Ray of Mandible both lateral oblique view |
800 BDT |
| 308 |
Digital X-Ray of Mandible left lateral oblique view |
400 BDT |
| 309 |
Digital X-Ray of Mandible PA & both lateral oblique view |
1200 BDT |
| 310 |
Digital X-Ray of Mandible PA & left lateral oblique view |
800 BDT |
| 311 |
Digital X-Ray of Mandible PA & right lateral oblique view |
800 BDT |
| 312 |
Digital X-Ray of Mandible PA view |
400 BDT |
| 313 |
Digital X-Ray of Mandible right lateral oblique view |
400 BDT |
| 314 |
Digital X-Ray of Mastoid AP oblique & Lateral Oblique view left side |
800 BDT |
| 315 |
Digital X-Ray of Mastoid AP oblique & Lateral Oblique view right side |
800 BDT |
| 316 |
Digital X-Ray of Mastoid Towens View(S) |
400 BDT |
| 317 |
Digital X-Ray of Mastoid Towne`s View(S837) |
400 BDT |
| 318 |
Digital X-Ray of Mastoid Townes (B/V) |
800 BDT |
| 319 |
Digital X-Ray of Mastoid Townes & Stenverse View |
800 BDT |
| 320 |
Digital X-Ray of Maxilla, Left Lateral oblique view |
400 BDT |
| 321 |
Digital X-Ray of Maxilla, Right Lateral oblique view |
400 BDT |
| 322 |
Digital X-Ray of Micturating Cystogram |
2500 BDT |
| 323 |
Digital X-Ray of Mortise view (one film) |
400 BDT |
| 324 |
Digital X-Ray of Myelogram |
3000 BDT |
| 325 |
Digital X-Ray of Nasal Bones both lateral view |
400 BDT |
| 326 |
Digital X-Ray of Nasopharynx lateral view for soft tissues/adenoid |
400 BDT |
| 327 |
Digital X-Ray of Neck AP & Lateral View |
800 BDT |
| 328 |
Digital X-Ray of Neck lateral view for soft tissue/Nasopharynx |
400 BDT |
| 329 |
Digital X-Ray of Neck of Cervical Ribs |
400 BDT |
| 330 |
Digital X-Ray of Nephro Urethrogram (Normal) |
2500 BDT |
| 331 |
Digital X-Ray of Nephrostogram |
2500 BDT |
| 332 |
Digital X-Ray of Occlusal view for lower jaw (Mandible) |
500 BDT |
| 333 |
Digital X-Ray of Occlusal view for upper jaw |
500 BDT |
| 334 |
Digital X-Ray of Occlusal view of maxilla |
500 BDT |
| 335 |
Digital X-Ray of Optic foramen |
400 BDT |
| 336 |
Digital X-Ray of P. T. C. |
1500 BDT |
| 337 |
Digital X-Ray of P.N.S. O/M & Lateral view |
800 BDT |
| 338 |
Digital X-Ray of P.N.S. O/M view |
400 BDT |
| 339 |
Digital X-Ray of Pelvis AP & Both Hip joint Letaral View |
1200 BDT |
| 340 |
Digital X-Ray of Pelvis AP & Lateral View with Both hip joint |
1200 BDT |
| 341 |
Digital X-Ray of Pelvis AP View ( Frog-Leg Position-Adult) |
500 BDT |
| 342 |
Digital X-Ray of Pelvis AP View ( Frog-Leg Position-Child) |
400 BDT |
| 343 |
Digital X-Ray of Pelvis AP with Both hip joint AP View |
800 BDT |
| 344 |
Digital X-Ray of Pelvis Both Oblique view |
800 BDT |
| 345 |
Digital X-Ray of Pelvis erect lat view for CPD |
800 BDT |
| 346 |
Digital X-Ray of Pelvis erect posture |
500 BDT |
| 347 |
Digital X-Ray of Pelvis Erect Posture (CPD) |
500 BDT |
| 348 |
Digital X-Ray of Pelvis Lateral View |
400 BDT |
| 349 |
Digital X-Ray of Pelvis with both hip joint AP view (Child) |
400 BDT |
| 350 |
Digital X-Ray of Pericathetar Urethogram(X781) |
2500 BDT |
| 351 |
Digital X-Ray of Phonogram |
2000 BDT |
| 352 |
Digital X-Ray of Plain Abdomen AP & Lat. View |
1200 BDT |
| 353 |
Digital X-Ray of Plain Abdomen AP View |
500 BDT |
| 354 |
Digital X-Ray of Plain Abdomen AP View (Child) |
400 BDT |
| 355 |
Digital X-Ray of Plain Abdomen Erect & Supine View |
800 BDT |
| 356 |
Digital X-Ray of Plain Abdomen Erect View including Diaphragm |
500 BDT |
| 357 |
Digital X-Ray of Plain Abdomen in Supine View |
600 BDT |
| 358 |
Digital X-Ray of Plain Abdomen Lateral View |
500 BDT |
| 359 |
Digital X-Ray of Plain KUB (Children below 10 yrs) one film |
400 BDT |
| 360 |
Digital X-Ray of Plain KUB AP & Lateral View |
1200 BDT |
| 361 |
Digital X-Ray of Plain KUB AP View |
500 BDT |
| 362 |
Digital X-Ray of Plain KUB AP View and Lumber Spine lat-View |
1200 BDT |
| 363 |
Digital X-Ray of Plain KUB Erect View (Standing) |
500 BDT |
| 364 |
Digital X-Ray of Retrograde Urethro Cystogram |
2500 BDT |
| 365 |
Digital X-Ray of Right Ankle joint AP & Lateral view |
400 BDT |
| 366 |
Digital X-Ray of Right Clavicle AP & Lateral View |
800 BDT |
| 367 |
Digital X-Ray of Right Clavicle AP View |
400 BDT |
| 368 |
Digital X-Ray of Right Elbow joint AP & Lateral view |
400 BDT |
| 369 |
Digital X-Ray of Right Elbow joint AP, Lat. & oblique view |
400 BDT |
| 370 |
Digital X-Ray of Right Foot AP & Oblique View (B/V) |
400 BDT |
| 371 |
Digital X-Ray of Right Forearm (Radius&Ulna) AP & Lat.View including Elbow joint |
400 BDT |
| 372 |
Digital X-Ray of Right Forearm (Radius&Ulna) AP & Lat.View including Wrist joint |
400 BDT |
| 373 |
Digital X-Ray of Right Forearm(Radius&Ulna)AP &Lat.View inclu.Elbow &Wrist joint |
400 BDT |
| 374 |
Digital X-Ray of Right Hand AP & Lateral View |
400 BDT |
| 375 |
Digital X-Ray of Right Hand PA & Oblique View |
400 BDT |
| 376 |
Digital X-Ray of Right Heel (Calcaneum) Axial & Lateral View |
400 BDT |
| 377 |
Digital X-Ray of Right hip joint AP & Lateral View |
800 BDT |
| 378 |
Digital X-Ray of Right hip joint AP View |
400 BDT |
| 379 |
Digital X-Ray of Right hip joint Lateral View |
400 BDT |
| 380 |
Digital X-Ray of Right Humerus (Arm) AP & Lat. View including Shoulder joint |
800 BDT |
| 381 |
Digital X-Ray of Right Humerus(Arm)AP &Lat.View including Shoulder&Elbow joint |
800 BDT |
| 382 |
Digital X-Ray of Right knee joint (B/V) AP & Lateral view |
400 BDT |
| 383 |
Digital X-Ray of Right knee joint AP, Lateral & Skyline view |
800 BDT |
| 384 |
Digital X-Ray of Right knee joint AP, Lateral, Skyline & Intercondylar view |
1200 BDT |
| 385 |
Digital X-Ray of Right Leg (Tibia & Fibula) including Knee & Ankle joint |
800 BDT |
| 386 |
Digital X-Ray of Right Leg including ankle joint AP & Lat view |
800 BDT |
| 387 |
Digital X-Ray of Right Leg including knee joint AP & Lat view |
800 BDT |
| 388 |
Digital X-Ray of Right S/C joint AP & Oblique view |
800 BDT |
| 389 |
Digital X-Ray of Right Scapula AP & Lateral view with shoulder joint |
800 BDT |
| 390 |
Digital X-Ray of Right Scapula AP view |
400 BDT |
| 391 |
Digital X-Ray of Right shoulder joint AP View |
400 BDT |
| 392 |
Digital X-Ray of Right sub-mandibular gland lateral oblique view |
400 BDT |
| 393 |
Digital X-Ray of Right T.M. Joint open & close Mouth |
800 BDT |
| 394 |
Digital X-Ray of Right Thigh (femur) AP & Lateral view including hip joint |
800 BDT |
| 395 |
Digital X-Ray of Right Thigh (femur) AP & Lateral view including Knee joint |
800 BDT |
| 396 |
Digital X-Ray of Right Thigh (femur) AP&Lateral view inclu. Knee joint in 1 film |
800 BDT |
| 397 |
Digital X-Ray of Right thumb (B/V) |
400 BDT |
| 398 |
Digital X-Ray of Right Thumb B/V |
400 BDT |
| 399 |
Digital X-Ray of Right Wrist joint AP, Lateral View & Oblique view |
400 BDT |
| 400 |
Digital X-Ray of Right Wrist Joint PA & Lateral View |
400 BDT |
| 401 |
Digital X-Ray of Rt. Arm AP & Lateral View |
800 BDT |
| 402 |
Digital X-Ray of Rt. Foot AP & Lat. View |
400 BDT |
| 403 |
Digital X-Ray of Rt. Foot including ankle joint (B/V) |
800 BDT |
| 404 |
Digital X-Ray of Rt. Foot including heel lat view |
400 BDT |
| 405 |
Digital X-Ray of Rt. Heel with Ankle AP and Lat View |
800 BDT |
| 406 |
Digital X-Ray of Rt. Index Finger AP & Lat View |
400 BDT |
| 407 |
Digital X-Ray of Rt. Knee Joint AP & Lat View (Standing Position) |
800 BDT |
| 408 |
Digital X-Ray of Rt. Knee Joint AP, Lat & both oblique view in standing position |
2000 BDT |
| 409 |
Digital X-Ray of Rt. Knee Joint AP, Lat in weight bearing position |
800 BDT |
| 410 |
Digital X-Ray of Rt. Knee joint AP, Lat. & Intercondylar view |
800 BDT |
| 411 |
Digital X-Ray of Rt. Leg AP & Lateral view (Child) |
400 BDT |
| 412 |
Digital X-Ray of Rt. Little Finger AP & Lat View |
400 BDT |
| 413 |
Digital X-Ray of Rt. Middle Finger AP & Lateral View |
400 BDT |
| 414 |
Digital X-Ray of Rt. Middle finger AP, Lat view |
400 BDT |
| 415 |
Digital X-Ray of Rt. Orbit AP & Lateral (Up & Down) |
800 BDT |
| 416 |
Digital X-Ray of Rt. Patella Axial View |
400 BDT |
| 417 |
Digital X-Ray of Rt. Ring Finger AP & Lat View |
400 BDT |
| 418 |
Digital X-Ray of Rt. Shoulder AP, Lat & Oblique view |
1200 BDT |
| 419 |
Digital X-Ray of Rt. Shoulder Joint AP & Lateral View |
800 BDT |
| 420 |
Digital X-Ray of Rt. Shoulder Jt. AP,Lat,Aboduction,Adaction |
2000 BDT |
| 421 |
Digital X-Ray of Rt. Shoulder Jt. AP,Lat,Internal & External rotation |
2000 BDT |
| 422 |
Digital X-Ray of Rt. Thigh AP & Lateral view (Child) |
400 BDT |
| 423 |
Digital X-Ray of S. I. Joint (B/V) |
800 BDT |
| 424 |
Digital X-Ray of S. I. Joint Both oblique view |
800 BDT |
| 425 |
Digital X-Ray of S. I. Joint PA view |
400 BDT |
| 426 |
Digital X-Ray of Sacro-Coccygeal spine AP & Lateral View |
800 BDT |
| 427 |
Digital X-Ray of Sacro-Coccygeal spine Lateral View |
400 BDT |
| 428 |
Digital X-Ray of Scaphoid view for wrist joint |
400 BDT |
| 429 |
Digital X-Ray of Scapula Lateral View |
400 BDT |
| 430 |
Digital X-Ray of Scapula Oblique View |
400 BDT |
| 431 |
Digital X-Ray of Scoliogram (one film) |
500 BDT |
| 432 |
Digital X-Ray of Scoliogram AP & LATERAL VIEW(S1176) |
1200 BDT |
| 433 |
Digital X-Ray of Sinugram |
2000 BDT |
| 434 |
Digital X-Ray of Sinus (PNS) |
400 BDT |
| 435 |
Digital X-Ray of Skiagram |
1000 BDT |
| 436 |
Digital X-Ray of Skull AP & Lateral view |
800 BDT |
| 437 |
Digital X-Ray of Skull AP Rt. and Lt. Lat view |
1200 BDT |
| 438 |
Digital X-Ray of Skull AP View |
400 BDT |
| 439 |
Digital X-Ray of Skull base of the skull |
400 BDT |
| 440 |
Digital X-Ray of Skull for Sella Turcica/Pituitary Fossa Cone down view |
400 BDT |
| 441 |
Digital X-Ray of Skull for Sella Turcica/Pituitary Fossa Lateral view |
400 BDT |
| 442 |
Digital X-Ray of Skull for sinuses (P.N.S. O/M) |
400 BDT |
| 443 |
Digital X-Ray of Skull for Sinuses (PNS O/M View) |
400 BDT |
| 444 |
Digital X-Ray of Skull Lateral view |
400 BDT |
| 445 |
Digital X-Ray of Skull Left Lat view |
400 BDT |
| 446 |
Digital X-Ray of Skull PA & Lateral view |
800 BDT |
| 447 |
Digital X-Ray of Skull Right Lat view |
400 BDT |
| 448 |
Digital X-Ray of Skull silla tursica both view |
400 BDT |
| 449 |
Digital X-Ray of Skull Townes View |
400 BDT |
| 450 |
Digital X-Ray of Skull Transorbital PA view for internal auditory canal |
400 BDT |
| 451 |
Digital X-Ray of Skull with Mandible AP view |
400 BDT |
| 452 |
Digital X-Ray of Spinal colum B/V |
1600 BDT |
| 453 |
Digital X-Ray of Sternum AP & Lateral View |
800 BDT |
| 454 |
Digital X-Ray of Sternum AP, Lat & Oblique View |
1200 BDT |
| 455 |
Digital X-Ray of Sternum Lateral View |
400 BDT |
| 456 |
Digital X-Ray of Sternum Oblique & lateral View |
800 BDT |
| 457 |
Digital X-Ray of Sternum Oblique View |
400 BDT |
| 458 |
Digital X-Ray of Styloid Process B/V |
800 BDT |
| 459 |
Digital X-Ray of Submento vertical view |
400 BDT |
| 460 |
Digital X-Ray of T-Tube Choloagiography |
2500 BDT |
| 461 |
Digital X-Ray of Tendo Achilies/Tendo Calcaneum (Only Lateral View) |
400 BDT |
| 462 |
Digital X-Ray of Trans Orbital Patrus view |
400 BDT |
| 463 |
Digital X-Ray of Upper Limb AP |
800 BDT |
| 464 |
Digital X-Ray of Upper Limb Lateral |
800 BDT |
| 465 |
Digital X-Ray of Whole Spine |
2400 BDT |
| 466 |
Digital X-Ray of Wrist Joints to Assess Bone Age |
400 BDT |
| 467 |
Digital X-Ray of Zygomatic, arches |
400 BDT |
| 468 |
Douche Charge |
200 BDT |
| 469 |
Dual Femur measurement of bone densitometer (Dexa Scan) |
1500 BDT |
| 470 |
Extra Film Charge-2(Per<EMAIL_ADDRESS>|
1000 BDT |
| 471 |
Extra Film Charge-3(Per<EMAIL_ADDRESS>|
1500 BDT |
| 472 |
Extra Film Charge-4(Per<EMAIL_ADDRESS>|
2000 BDT |
| 473 |
Extra Film Charge-5(Per<EMAIL_ADDRESS>|
2500 BDT |
| 474 |
Extra Film Charge-6(Per<EMAIL_ADDRESS>|
3000 BDT |
| 475 |
Extra Film Charge(Per Film) |
500 BDT |
| 476 |
FNAC CT |
2000 BDT |
| 477 |
Forearm measurement of bone densitometer (Dexa Scan) |
1500 BDT |
| 478 |
Lateral Spine (LVA) of bone densitometer (Dexa Scan)(2205) |
2000 BDT |
| 479 |
Loopgram / Cologram Child |
2500 BDT |
| 480 |
Low dose CT. Scan of Chest Screening |
4000 BDT |
| 481 |
Mammography of Both Breast |
2000 BDT |
| 482 |
Mammography of Left Breast |
1000 BDT |
| 483 |
Mammography of Right Breast |
1000 BDT |
| 484 |
mp MRI of Prostate |
9000 BDT |
| 485 |
mp MRI of Urinary Bladder Mass |
9000 BDT |
| 486 |
MR of Peripharal Angio Lower Limbs |
12000 BDT |
| 487 |
MR of Peripharal Angio Upper Limbs |
12000 BDT |
| 488 |
MR Renal Angiography |
7000 BDT |
| 489 |
MR Urography |
9000 BDT |
| 490 |
MRA of Brain |
7000 BDT |
| 491 |
MRA of Neck |
7000 BDT |
| 492 |
MRCP |
9000 BDT |
| 493 |
MRCP With CT Scan |
9000 BDT |
| 494 |
MRI of Brain |
7000 BDT |
| 495 |
MRI & MRA of Neck |
9000 BDT |
| 496 |
MRI & MRS of Brain |
9000 BDT |
| 497 |
MRI & MRV of Brain |
9000 BDT |
| 498 |
MRI And MRA of Brain |
9000 BDT |
| 499 |
MRI Enterography |
18000 BDT |
| 500 |
MRI of Dorsal Spine With Screening Whole Spine |
7000 BDT |
| 501 |
MRI of Adreenal Glands |
7000 BDT |
| 502 |
MRI of Both Breast Screening |
9000 BDT |
| 503 |
MRI of Brachial Plexux |
9000 BDT |
| 504 |
MRI of Brain & Orbits |
9000 BDT |
| 505 |
MRI of Breast |
14000 BDT |
| 506 |
MRI of Cervical Spine |
7000 BDT |
| 507 |
MRI of Cervical Spine With Screening Whole Spine |
7000 BDT |
| 508 |
MRI of Chest |
9000 BDT |
| 509 |
MRI of Dorsal Spine |
7000 BDT |
| 510 |
MRI of Dorso - Lumbar Spine |
14000 BDT |
| 511 |
MRI of DWIBS |
10000 BDT |
| 512 |
MRI of Ears |
7000 BDT |
| 513 |
MRI of HBS |
9000 BDT |
| 514 |
MRI of Kidneys |
9000 BDT |
| 515 |
MRI of KUB |
14500 BDT |
| 516 |
MRI of Left Ankle Joint |
9000 BDT |
| 517 |
MRI of Left Arm |
9000 BDT |
| 518 |
MRI of Left Ear |
7000 BDT |
| 519 |
MRI of Left Elbow Joint |
9000 BDT |
| 520 |
MRI of Left Foot |
9000 BDT |
| 521 |
MRI of Left Forearm |
9000 BDT |
| 522 |
MRI of Left Hand |
9000 BDT |
| 523 |
MRI of Left Hip Joint |
9000 BDT |
| 524 |
MRI of Left IAC |
7000 BDT |
| 525 |
MRI of Left Knee Joint |
9000 BDT |
| 526 |
MRI of Left Leg |
9000 BDT |
| 527 |
MRI of Left Mastoid |
7000 BDT |
| 528 |
MRI of Left Shoulder Joint |
9000 BDT |
| 529 |
MRI of Left Thigh |
9000 BDT |
| 530 |
MRI of Left Wrist Joint |
9000 BDT |
| 531 |
MRI of Lower Abdomen |
9000 BDT |
| 532 |
MRI of Lumbar Spine With Screening Whole Spine |
7000 BDT |
| 533 |
MRI of Lumbo-Sacral Spine |
7000 BDT |
| 534 |
MRI of Neck |
9000 BDT |
| 535 |
MRI of Nesopharmax |
9000 BDT |
| 536 |
MRI of Orbits |
9000 BDT |
| 537 |
MRI of P. N. S. |
9000 BDT |
| 538 |
MRI of Pelvis |
9000 BDT |
| 539 |
MRI of Perfusion of Brain |
7000 BDT |
| 540 |
MRI of Right Ankle Joint |
9000 BDT |
| 541 |
MRI of Right Arm |
9000 BDT |
| 542 |
MRI of Right Elbow Joint |
9000 BDT |
| 543 |
MRI of Right Foot |
9000 BDT |
| 544 |
MRI of Right Forearm |
9000 BDT |
| 545 |
MRI of Right Hand |
9000 BDT |
| 546 |
MRI of Right Hip Joint |
9000 BDT |
| 547 |
MRI of Right IAC |
7000 BDT |
| 548 |
MRI of Right Knee Joint |
9000 BDT |
| 549 |
MRI of Right Leg |
9000 BDT |
| 550 |
MRI of Right Mastoid |
7000 BDT |
| 551 |
MRI of Right Shoulder Joint |
9000 BDT |
| 552 |
MRI of Right Thigh |
9000 BDT |
| 553 |
MRI of Right Wrist Joint |
9000 BDT |
| 554 |
MRI of Sella & Perisellar/ Pituitary Region |
7000 BDT |
| 555 |
MRI of T.M Joint / Face |
9000 BDT |
| 556 |
MRI of Tongue |
9000 BDT |
| 557 |
MRI of Upper Abdomen |
9000 BDT |
| 558 |
MRI of Whole Abdomen |
18000 BDT |
| 559 |
MRI of Whole Body |
30000 BDT |
| 560 |
MRI of Whole Spine |
21000 BDT |
| 561 |
MRI Tractography |
7000 BDT |
| 562 |
MRI Whole Spine for Bony Metastasis |
9000 BDT |
| 563 |
MRS of Brain |
7000 BDT |
| 564 |
MRV of Brain |
7000 BDT |
| 565 |
OPG |
450 BDT |
| 566 |
OPG (Open & Close ) |
450 BDT |
| 567 |
PORTABLE XRAY ABDOMEN AP |
800 BDT |
| 568 |
PORTABLE XRAY C/S SPINE BV |
1000 BDT |
| 569 |
PORTABLE XRAY CXR AP |
800 BDT |
| 570 |
PORTABLE XRAY CXR AP & OBLIQUE |
1200 BDT |
| 571 |
PORTABLE XRAY CXR OBLIQUE |
800 BDT |
| 572 |
PORTABLE XRAY FEMUR AP & LATERAL |
1000 BDT |
| 573 |
PORTABLE XRAY L/S SPINE AP & LATERAL |
1200 BDT |
| 574 |
PORTABLE XRAY LEG AP & LATERAL |
800 BDT |
| 575 |
PORTABLE XRAY PELVIS AP |
800 BDT |
| 576 |
PORTABLE XRAY SKULL AP & LATERAL |
1200 BDT |
| 577 |
Sialogram Lefl sub mandibular gland & duct (Digital) |
2500 BDT |
| 578 |
Sialogram Left parotid gland |
2500 BDT |
| 579 |
Sialogram right parotid gland |
2500 BDT |
| 580 |
Sialogram right sub mandibular gland & duct (Digital) |
2500 BDT |
| 581 |
Single Femur Measurement of bone densitometer (Dexa Scan) |
1500 BDT |
| 582 |
Spiral CT Scan Base of Skull |
6000 BDT |
| 583 |
Spiral CT Scan of Adrenal Glands |
6000 BDT |
| 584 |
Spiral CT Scan of Brain |
4000 BDT |
| 585 |
Spiral CT Scan of Brain & .............. |
7000 BDT |
| 586 |
Spiral CT Scan of Brain & Orbit/P.N.S. |
7000 BDT |
| 587 |
Spiral CT Scan of Cervical Spine |
6000 BDT |
| 588 |
Spiral CT Scan of Chest (HRCT) |
6000 BDT |
| 589 |
Spiral CT Scan of Chest/Lungs |
6000 BDT |
| 590 |
Spiral CT Scan of Dorsal/Thoracic Spine |
6000 BDT |
| 591 |
Spiral CT Scan of Face |
6000 BDT |
| 592 |
Spiral CT Scan of HBS/Liver |
6000 BDT |
| 593 |
Spiral CT Scan of Kidnys |
6000 BDT |
| 594 |
Spiral CT Scan of KUB |
12000 BDT |
| 595 |
Spiral CT Scan of KUB (Screening) |
10000 BDT |
| 596 |
Spiral CT Scan of Lower Abdomen |
6000 BDT |
| 597 |
Spiral CT Scan of Lumbo Secral Spine |
6000 BDT |
| 598 |
Spiral CT Scan of Neck |
6000 BDT |
| 599 |
Spiral CT Scan of P. N. S. |
6000 BDT |
| 600 |
Spiral CT Scan of Pelvis With 3D |
6000 BDT |
| 601 |
Spiral CT Scan of Pituitary Gland |
6000 BDT |
| 602 |
Spiral CT Scan of Upper Abdomen |
6000 BDT |
| 603 |
Spiral CT Scan of Whole Abdomen |
12000 BDT |
| 604 |
Venography of Both LIMB |
10000 BDT |
| 605 |
Venography of Left LIMB |
5000 BDT |
| 606 |
Venography of one LIMB |
5000 BDT |
| 607 |
Venography of Right LIMB |
5000 BDT |
| 608 |
Venography of Two LIMB |
10000 BDT |
| 609 |
Vesico Ureteric Reflux |
2000 BDT |
| 610 |
Whole body scan of bone densitometer (Dexa Scan) |
3000 BDT |


TuteOne Plus Two Kit
A hearty and a warm welcome to TuteOne!
We are extremely overwhelmed to welcome you to TuteOne when you are at the tip of your toes and getting ready for the most valuable and most challenging time period of their academic career. Our vision is to deliver a highly effective student-centric coaching; to create optimistic and inspirational minds.
We wish to take you one step ahead to success.
With deep respect, We would like to conclude with Dr. APJ Abdul Kalam Sir’s quote “If you want to shine like a sun, first burn like a sun.”
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Divergence Operator, $\nabla \cdot \mathbf{f} $
Divergence is a vector operator that describes the quantity of a vector field at each point.
It is the volume density of outward flux of a vector field at an infinitesimal volume around a point.
This leads to another way of understanding divergence:
Imagine a point $(x_A,y_A)$ in the vector field, which has a vector output assigned to it.
If $\nabla \cdot \mathbf{f}(x_A,y_A) \neq 0$, as we move along an
infinitesimal distance parallel to the direction of the vector at the point (that is $\mathbf{f}(x_A,y_A))$,
there is a change in the magnitude of the output vector, which is the field strength. If divergence is positive, the field strength
increases as we move in the direction of the vector at $(x_A,y_A)$. If divergence is negative, the field strength
decreases as we move in the direction of the vector at the point.
Visualisation Guide
- A vector field is shown on the right. This field has a constant divergence value as indicated.
- Note that the field does not look like a "source" or "sink".
However, the field strength still changes along the x-direction, which indicates a non-zero divergence.
As you move along a direction parallel to the vector field at any point,
there is a change in the magnitude of the vector field. We can imagine this as if field lines are created or destroyed as we move along.
- Adjust the slider until the value of divergence is zero.
Note that the length of the arrows in the field are constant; there is no creation or destruction of field lines.
Hence, this is a divergence-free field.


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| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
DbLoaderDelegate defines API that allows to control the behavior of DbLoader during the database reverse-engineering. Delegate is also notified of the progress of reverse-engineering.
| Method Summary | |
void |
dbEntityAdded(DbEntity ent)
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void |
dbEntityRemoved(DbEntity ent)
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void |
objEntityAdded(ObjEntity ent)
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void |
objEntityRemoved(ObjEntity ent)
|
boolean |
overwriteDbEntity(DbEntity ent)
Returns true to tell DbLoader that it is OK to overwrite DbEntity that already exists in the model. |
void |
setSchema(DbEntity ent,
java.lang.String schema)
Deprecated. Since 1.1 this method is not used by DbLoader. Suppressing schema during reverse-engineering has undesired consequences, such as incorrectly reengineered relationships. |
| Method Detail |
public boolean overwriteDbEntity(DbEntity ent) throws CayenneException
CayenneException
public void dbEntityAdded(DbEntity ent)
public void dbEntityRemoved(DbEntity ent)
public void objEntityAdded(ObjEntity ent)
public void objEntityRemoved(ObjEntity ent)
public void setSchema(DbEntity ent, java.lang.String schema)
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--- title: "Week 11 Lab -- GLMM" author: "Drew Tyre" date: "2020-10-28" output: html_document: fig_caption: TRUE weight: 803111 ---
The first dataset we’ll look at is from Zuur et al. (2009); the data are from Vicente et al. (2005) who looked at the distribution and faecal shedding patterns of 1st stage larvae of Elaphostrongylus cervi in red deer. Here we’re interested in the presence and absence of larvae in deer as functions of size (length in cm), sex, and farm identity.
library(tidyverse)
library(NRES803)
library(lme4)
data(ecervi)
head(ecervi)
The average number of larvae in a fecal sample is highly skewed to the right – many zeros but also some very large values.
hist(ecervi$Ecervi, xlab = "Number of L1 E. cervi", main = "")
The response variable is continuous, so we need to do some data manipulation in order to get presence/absence data. This is one way to handle highly skewed data like this. While we’re doing that, we’ll make sure sex is categorical and center the length variable to improve convergence, and make the intercept directly interpretable as the probability of presence for an average size deer.
ecervi <- ecervi %>% mutate(Ecervi.pa = Ecervi > 0, fSex = factor(Sex, labels = c("Male",
"Female")), cLength = Length - mean(Length))
ggplot(ecervi, aes(x = cLength, y = Ecervi)) + geom_point() + facet_wrap(~fSex)
One issue that can affect a binomial model is called “complete seperation”. This arises when one predictor is a “perfect” predictor of presence or absence. There is a value above which there are only presences and below which there are only absences. The plot above suggests that won’t be an issue with our fixed effects, but there could be farms that are perfectly affected or unaffected.
with(ecervi, table(Farm, Ecervi.pa))
There are 3 farms with either all positive or all negative observations. We won’t worry about that for now, but we will want to look for problems with that later.
As always, start with a global model to check residuals. The global model here has the interaction of sex and length. We clearly have a repeated measures design, so we will start with a mixed model using Farm as the random effect. It is also possible that the effects of sex and length could vary by farm.
M0 <- glmer(Ecervi.pa ~ fSex * cLength + (1 + fSex * cLength | Farm), data = ecervi,
family = binomial)
summary(M0)
That model fails to converge, or at least is reporting some issues with the “singular fit” message. Asking for the sex by length interaction to vary among farms is probably too much given there are some farms with relatively few observations. Looking at the summary, especially the random effects estimates, it is clear that the scaling between Sex and Length is very different. A 1 cm change in length is a much smaller change than a change from male to female. This kind of discrepancy can make it harder for a model to converge. If I rescale Length by dividing through with the standard deviation the coefficients for those two variables will be closer, and this can help with convergence. I will also change the contrasts on Sex to “sum to zero” contrasts, which has a similar beneficial effect to centering a continuous variable.
ecervi <- ecervi %>% mutate(csLength = cLength/sd(Length))
contrasts(ecervi$fSex) <- contr.sum(2)
M0 <- glmer(Ecervi.pa ~ fSex * csLength + (1 + fSex * csLength | Farm), data = ecervi,
family = binomial)
summary(M0)
Still fails to converge. OK, let’s try the next simplest model, leaving out the interaction in the random effect.
M0 <- glmer(Ecervi.pa ~ fSex * csLength + (1 + fSex + csLength | Farm), data = ecervi,
family = binomial)
summary(M0)
That works! Let’s check the two simpler models that allow either fSex or csLength to vary across farms.
M0a <- glmer(Ecervi.pa ~ fSex * csLength + (1 + csLength | Farm), data = ecervi,
family = binomial)
summary(M0a)
M0b <- glmer(Ecervi.pa ~ fSex * csLength + (1 + fSex | Farm), data = ecervi, family = binomial)
summary(M0b)
The first model converges fine, the second one has issues with a “singular fit” again. If you look closely at the summary for M0b
, you can see that the variance of the fSex
random effect is nearly 0, and the correlation with the intercept is 1.00. I suspect the issue is with some farms having only males.
with(ecervi, table(Farm, fSex))
Yes, there are several. This might cause issues later, but ignore for now.
Check residuals for both.  A bit of digging around in source code followed and I fixed the underlying qres.binom so it works with S4 instead of S3 objects.
qres.binom <- function(glmer.obj) {
p <- fitted(glmer.obj)
y <- glmer.obj@resp$y
if (!is.null(glmer.obj@resp$weights))
n <- glmer.obj@resp$weights else n <- rep(1, length(y))
y <- n * y
a <- pbinom(y - 1, n, p)
b <- pbinom(y, n, p)
u <- runif(n = length(y), min = a, max = b)
qnorm(u)
}
residM0a$qr <- qres.binom(M0a)
ggplot(residM0a, aes(x = .fitted, y = qr)) + geom_point() + geom_smooth() + geom_hline(yintercept = 0,
linetype = 2)
ggplot(residM0a, aes(x = csLength, y = qr)) + geom_point() + geom_smooth() + geom_hline(yintercept = 0,
linetype = 2)
probs <- c(0.25, 0.75)
y <- quantile(residM0a$qr, probs, names = FALSE, na.rm = TRUE)
x <- qnorm(probs)
slope <- diff(y)/diff(x)
int <- y[1L] - slope * x[1L]
ggplot(residM0a, aes(sample = qr)) + geom_qq(size = rel(4)) + geom_abline(intercept = int,
slope = slope, linetype = 2, size = 2)
ggplot(residM0a, aes(x = .fitted, y = sqrt(abs(qr)))) + geom_point() + geom_smooth() +
geom_hline(yintercept = 1)
Those all look fine. If you rerun qres.binom()
you’ll notice that the plots look different. These residuals are “randomized”, meaning that they are drawn randomly from the distribution of the residuals, not the actual fixed values themselves. So they do fluctuate. Pay most attention to the confidence envelope – if there is a flat line everywhere inside the envelope, any fluctuations up and down can be ignored.
So we have identified the global models and checked that they are adequate. Next we need to make up a set of models and identify the best ones using \(AIC_c\). We need to build the set with all possible random effects, and all possible fixed effects models. The number of variables is small, so this will be a reasonable thing to do.
fe <- c("1", "fSex", "csLength", "fSex + csLength", "fSex * csLength")
re <- c("(1 | Farm)", "(1 | Farm) + (0 + fSex | Farm)", "(1 | Farm) + (0 + csLength | Farm)",
"(1 | Farm) + (0 + fSex | Farm) + (0 + csLength | Farm)", "(1 + fSex | Farm)",
"(1 + csLength | Farm)", "(1 + csLength + fSex | Farm)")
forms <- expand.grid(LHS = "Ecervi.pa ~", fe = fe, re = re)
models <- forms %>% mutate(RHS = paste(fe, re, sep = "+"), model = paste(LHS, RHS),
fits = map(model, ~glmer(as.formula(.x), data = ecervi, family = binomial)))
A few of those models failed to converge. Figuring out which ones is a bit involved. Reading documentation for merMod objects there is a slot for information on the optimization, and a bit of experimenting determined that I could check for the object lme4 to have length > 0.
models <- mutate(models, converged = !map_lgl(fits, ~length(.x@optinfo$conv$lme4) >
0))
which(!models$converged)
Now we’re ready to see which models are the best, keeping a wary eye out for those models that had convergence issues.
library(MuMIn)
library(pander)
pander(model.sel(models$fits))
One difference from the “regular” linear mixed model with normal error distributions is that we don’t have to switch off REML estimation to compare models with different fixed effects. glmer()
is already using maximum likelihood for everything.
And here are the final estimates.
summary(models$fit[[30]])
Next we want to make some plots of the effects so we can interpret what is going on. First we’ll create some new data and go from there as we have in the past. The additional wrinkle is that we have to think about what we want predict to do with the random effects. The first option is to look at the “population average” response, which we do by setting re.form=~0
.
topmod <- models$fit[[30]]
lr = range(ecervi$csLength)
nd <- expand.grid(csLength = seq(lr[1], lr[2], length = 20), fSex = factor(levels(ecervi$fSex)))
nd$pp = predict(topmod, newdata = nd, type = "response", re.form = ~0)
# ggplot(nd, aes(x=csLength, y=pp, col=fSex, group=Farm:fSex)) +
# geom_line(alpha=0.5) + ylab('Probability of E. cervi infection') +
# geom_line(aes(x=csLength, y=pp, col=fSex), data=nd, inherit.aes = FALSE,
# size=2) + geom_rug(aes(x=csLength), data=filter(ecervi, Ecervi.pa),sides='t',
# inherit.aes = FALSE) + geom_rug(aes(x=csLength), data=filter(ecervi,
# !Ecervi.pa),sides='b', inherit.aes = FALSE)
ggplot(nd, aes(x = csLength, y = pp, col = fSex)) + geom_line() + xlab("Centered and scaled Length") +
ylab("Probability of E. cervi infection") + geom_rug(aes(x = csLength), data = filter(ecervi,
Ecervi.pa), sides = "t", inherit.aes = FALSE) + geom_rug(aes(x = csLength), data = filter(ecervi,
!Ecervi.pa), sides = "b", inherit.aes = FALSE)
These lines represent the effect of length and sex for a typical farm.
glm()
, i.e. ignoring the variation between farms. Compare and contrast the results that you get, both the magnitude and direction of the coefficients, as well as their relative standard errors.There is a significant and on-going debate about how best to do inference with this sort of model. One way around the debate is to use parametric bootstrapping to estimate things like the standard errors of the predictions and confidence intervals on the coefficients. lme4
has a premade function to get confidence intervals on the coefficients. WARNING this line of code will take > 20 minutes to run. Forget about these unless you’ve got alot of time.
# returns a matrix with estimates plus confidence intervals for all fixed and
# random effects parameters
topmod.CI <- confint(topmod, method = "boot", oldNames = FALSE)
topmod.CI
This function draws random samples of the random effects and the i.i.d. errors, generates a simulated response based on those error values, and then re-estimates the model. The confidence limits are based on the quantiles of the distribution of parameter estimates generated from 500 simulations. If fitting the original model takes a couple seconds, this routine will take 500 times as long to complete! You will also probably see warnings about convergence failures – all this reminds us that we’re out on the bleeding edge of computational statistics here.
Profile intervals are also good, slow, but not as bad as bootstrap.
topmod.profCI <- as.data.frame(confint(topmod, method = "profile", oldNames = FALSE)) # profile limits
topmod.WaldCI <- as.data.frame(confint(topmod, method = "Wald", oldNames = FALSE))
# get rid of rownames
rownames(topmod.profCI) <- NULL
rownames(topmod.WaldCI) <- NULL
# and change names to include type of CI
names(topmod.profCI) <- c("Profile_CI2.5", "Profile_CI97.5")
names(topmod.WaldCI) <- c("Wald_CI2.5", "Wald_CI97.5")
topmod.CI <- tidy(topmod) # from broom.mixed
# add the profile intervals -- confint() uses a different order from tidy()
topmod.CI <- cbind(topmod.CI, topmod.profCI[c(4:7, 1, 3, 2), ], topmod.WaldCI[c(4:7,
1, 3, 2), ])
topmod.CI <- gather(topmod.CI, type_level, limit, contains(".5"))
# now split type_level up
topmod.CI <- separate(topmod.CI, type_level, into = c("type", "level"), sep = "_")
# OMG I need the 2.5 and 97.5 values in seperate columns!
topmod.CI <- spread(topmod.CI, level, limit)
# that messed up the order of the rows, but looks like it all worked.
ggplot(topmod.CI, aes(x = term, y = estimate, fill = type)) + geom_bar(stat = "identity",
position = "dodge") + geom_errorbar(aes(ymin = CI2.5, ymax = CI97.5), position = "dodge")
It can be hard to see what is going on unless you use the “zoom” to make this plot large enough for the term names to not overlap. So the intervals for the intercept and sex effects are pretty close to the “simple” Wald intervals. The intervals for csLength and the interaction are longer with profile intervals, but at least they still exclude zero. In addition, the profile method gives us intervals on the variance parameters as well.
The reason it is hard to get confidence intervals on predictions is because of the uncertainty in the variance parameters, which can be substantial. The sd of the csLength random effect includes zero, for example. This makes sense, as the differences among the top 3 models were all in the random effects.
The basic idea is best illustrated with a figure showing how the log-likelihood of a model changes as one of the parameter values is changed.
# get a profile for the fixed effect csLength
lengthProf <- profile(topmod, which = "csLength")
library(lattice)
xyplot(lengthProf, absVal = TRUE)
The x-axis on that figure are values of the coefficient csLength. The y-axis is a measure of the change in deviance as the coefficient is moved away from the maximum likelihood estimate (the peak at the bottom). The vertical and horizontal lines indicate 50%, 80%, 90%, 95%, and 99% confidence intervals. As the parameter value moves away from the MLE, the model’s log-likehood gets worse. Particular points along that profile correspond to different critical points on chisquare distribution with one degree of freedom.


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It's DogeCars
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Nissan GTR The updated Nissan GT-R has the same twin-turbocharged 3,799 cc (3.8 L; 231.8 cu in) V6 VR38DETT engine but increased the engine output to 421 kW (572 PS; 565 hp) at 6,400 rpm and 633 N⋅m (467 lbf⋅ft) at 3,200–5,800 rpm. The transmission system is also refined to shift the gears smoothly and quieter than before.
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We always prefer to retain trees where possible, however when removal is required you can be assured that we can remove your trees safely and efficiently, with the area left spotlessly clean after the job is complete. Our arborists can also advise you on the expected ongoing viability of your trees, and relevant regulations or laws that apply to your tree, so you can plan ahead, and ensure that all the boxes are ticked.
You may wish to consider removing your tree if it is:
ACT Tree Felling specialise in pruning trees, it is a service we take pride in being able to provide at the highest level.
There are many benefits to pruning a tree correctly and we always prune to the highest industry standards, complying with Australian Standard for pruning of amenity trees (AS4373), ACT Tree Protection Act 2005 and any other relevant standards.
With an understanding of tree biology and the variance of species characteristics. Correct pruning can reduce the wind resistance of your trees, lessening the chance of branch failure.
Your trees may benefit from pruning if they have:
Pruning can also:
Dead wooding is the process of selectively removing the dead, dying and diseased branches from trees. Removing the deadwood from your tree can increase the aesthetic appeal of your tree and reduce the likelihood of dead branches falling.
With almost 40 years’ experience working in the tree industry in Canberra, ACT Tree Felling has developed a reputation as the best local business for removal of difficult, large and/or dangerous trees. We are the preferred providers for the Australian National Botanic Gardens, where we are often contracted to remove difficult to access, large trees in sensitive environments where no damage to other plants is acceptable.
We will organise all aspects of the project to ensure these difficult jobs are completed in the safest method possible, sometimes involving traffic management and the use of cranes.
We have strict Work Health and Safety Policies internally and comply with all relevant legislation to ensure a safe work site for all our staff, clients and members of the public.
We are fully equipped with the most advanced tree care equipment to ensure the job is completed professionally, safely and efficiently.
All home owners in the ACT are required by law to ensure their trees are clear from power and house service lines. Sometimes trees growing too close to power lines can cause blackouts, create safety hazards such as fires, and increase the risk of electrocution.
Our staff are trained and accredited to the highest level to work around live power lines, so most of the time we will not require a power outage to achieve required clearance from the powerlines. In cases where a power outage is required, we will arrange the whole process for you in cooperation with EvoEnergy.
You can rest assured that we are:
Trees are very beneficial to our environment and can add significant monetary and amenity value to our homes, places of work and communities. They may also have sentimental value for some customers, who may wish to retain their trees at all costs.
However sometimes trees with multiple trunks (co-dominant stems), can have less structural integrity than optimal and ‘failure’ at this type of branch union can occur.
Other defected unions or tree parts can have a higher than average likelihood of failure. ACT Tree Felling can inspect your trees, assess them for any structural weakness and then recommend if bracing may assist in the retention of your tree assets and what the most appropriate type of cable or bracing system for your situation. The result? You can retain the trees you love and have peace of mind knowing that you have done all you can to minimise any associated risk.
There are three major reasons for cable and bracing:
Tree stumps can be unsightly, obtrusive and hazardous. Stump grinding is the most efficient and cost-effective solution to removing unwanted stumps from your property, to prevent re-growth and the spread of tree disease.
Stumps can become:
We also offer a wood chipping service where we can put all your branches/cuttings through our chipper, then either take away the mulched material or leave on-site for you to apply to your garden.
Applying mulch to your trees and garden looks great, retains soil moisture, slows down the weeds and can add nutrition to your plants and trees. Mulch is also great for trees in decline, as it aids recovery from stress, injury or disease.
ACT Tree Felling can supply quality mulch at a fantastically cheap rate, to locations throughout Canberra and Queanbeyan so please give us a call and we can get you onto our popular waiting list.
If you are worried about your tree’s structural integrity, health, condition, life expectancy, falling or overhanging limbs or something else that just doesn’t look quite right, a detailed tree inspection via consultation with one of our Consulting Arborists will help ease your mind.
Our consultation will identify key issues or concerns in relation to your tree, giving you verbal advice in an easy-to-understand manner.
Need something in writing?
We can provide either brief field notes to outline the basic details of your tree/s and situation or alternatively a full tree report formatted and referenced to be utilised for engagement with third parties (such as ACAT, Tree Protection Unit, ACTPLA or Body Corporate Committees).
The consultant will be a member of Arboriculture Australia and bound by the Code of Ethics of the Association.
These qualifications ensure that our team of consultants will be able provide clear and concise advice in the following areas:
If you are planning tree removal or tree pruning that requires council approval, we can prepare and submit the application on your behalf, and if necessary, provide supporting documentation and a tree report to go along with the application.


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A letter will be randomly selected. Type a word for each of the 4 different categories that starts with that letter. The player that gets most correct words in the least amount of time wins!
Score:
The letter is...


3 types derived from PipelineWriter
Microsoft.PowerShell.Commands.Utility (1)
commands\utility\trace\TraceExpressionCommand.cs (1)
332
internal class TracePipelineWriter :
PipelineWriter
System.Management.Automation (2)
utils\IObjectWriter.cs (1)
124
internal class DiscardingPipelineWriter :
PipelineWriter
utils\ObjectWriter.cs (1)
17
internal class ObjectWriter :
PipelineWriter
33 references to PipelineWriter
System.Management.Automation (33)
engine\ExecutionContext.cs (3)
726
internal
PipelineWriter
ExternalSuccessOutput { get; set; }
731
internal
PipelineWriter
ExternalErrorOutput { get; set; }
736
internal
PipelineWriter
ExternalProgressOutput { get; set; }
engine\hostifaces\LocalPipeline.cs (2)
1104
private
PipelineWriter
_oldExternalErrorOutput;
1105
private
PipelineWriter
_oldExternalSuccessOutput;
engine\hostifaces\Pipeline.cs (1)
359
public abstract
PipelineWriter
Input { get; }
engine\hostifaces\pipelinebase.cs (1)
218
public override
PipelineWriter
Input
engine\Pipe.cs (2)
80
internal
PipelineWriter
ExternalWriter
94
private
PipelineWriter
_externalWriter;
engine\pipeline.cs (4)
35
private
PipelineWriter
_externalSuccessOutput;
36
private
PipelineWriter
_externalErrorOutput;
1489
internal
PipelineWriter
ExternalSuccessOutput
1519
internal
PipelineWriter
ExternalErrorOutput
engine\remoting\client\remotepipeline.cs (1)
296
public override
PipelineWriter
Input
engine\remoting\commands\InvokeCommandCommand.cs (6)
1665
List<
PipelineWriter
> removeCollection = new List<
PipelineWriter
>();
1667
foreach (
PipelineWriter
writer in _inputWriters)
1680
foreach (
PipelineWriter
writer in removeCollection)
2032
private readonly List<
PipelineWriter
> _inputWriters = new List<
PipelineWriter
>();
engine\remoting\commands\newrunspacecommand.cs (4)
439
PipelineWriter
writer = _stream.ObjectWriter;
705
PipelineWriter
writer = _stream.ObjectWriter;
839
PipelineWriter
writer = _stream.ObjectWriter;
1247
PipelineWriter
writer = _stream.ObjectWriter;
engine\runtime\CompiledScriptBlock.cs (1)
1040
var
oldExternalErrorOutput = context.ExternalErrorOutput;
utils\ObjectStream.cs (8)
146
internal abstract
PipelineWriter
ObjectWriter { get; }
489
private
PipelineWriter
_writer = null;
721
internal override
PipelineWriter
ObjectWriter
725
PipelineWriter
writer = null;
731
_writer = new ObjectWriter(this) as
PipelineWriter
;
1557
private
PipelineWriter
_writer;
1779
internal override
PipelineWriter
ObjectWriter
1789
_writer = new PSDataCollectionWriter<T>(this) as
PipelineWriter
;


nethack
`Prev `__
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`Next `__
--------------
**nethack**: /net´hak/, n.
[Unix] A dungeon game similar to `*rogue* <../R/rogue.html>`__ but more
elaborate, distributed in C source over `*Usenet* <../U/Usenet.html>`__
and very popular at Unix sites and on PC-class machines (nethack is
probably the most widely distributed of the freeware dungeon games). The
earliest versions, written by Jay Fenlason and later considerably
enhanced by Andries Brouwer, were simply called ‘hack’. The name changed
when maintenance was taken over by a group of hackers originally
organized by Mike Stephenson. There is now an official site at
`http://www.nethack.org/ `__. See also
`*moria* <../M/moria.html>`__, `*rogue* <../R/rogue.html>`__,
`*Angband* <../A/Angband.html>`__.
--------------
+----------------------------+----------------------------+-------------------------------+
| `Prev `__ | `Up <../N.html>`__ | `Next `__ |
+----------------------------+----------------------------+-------------------------------+
| netdead | `Home <../index.html>`__ | netiquette |
+----------------------------+----------------------------+-------------------------------+


Construction works on 2nd Niger Bridge 28% complete – Julius Berger
by Okechukwu NnodimOkechukwu Nnodim, Abuja
Global construction giant, Julius Berger, has put the percentage of construction works so far completed on the Second Niger Bridge at approximately 28 per cent.
It also released pictures showing how far work has progressed on the bridge that connects Delta and Anambra states.
In a report dated November 15, 2019, on progress made at the project site, which was obtained on Friday in Abuja, the firm stated that the scope of works comprise of 1.6km long River Niger Bridge and 10.3km highway inclusive Owerri interchange and toll station.
The report stated that the letter of award for the project was issued on July 25, 2018, and the contract was signed on August 14, 2018.
Work commenced on the project site on September 1, 2018, while the contract period was captured in the report as 42 months.
It was also learnt that the total manpower on the site was 1,201, as the firm stated that work was going on at the site.


Bajaj Finance to launch QIP next week: Sources
The size of the QIP is reportedly about Rs 8,500 crore and its price band is likely to be between Rs 3,810–3,900 per share.
by Moneycontrol NewsBajaj Finance will look to issue its qualified Institutional placement (QIP) next week, according to a CNBC-TV18 flash.
The size of the QIP is reportedly about Rs 8,500 crore and its price band is likely to be between Rs 3,810–3,900 per share. Five to six domestic and foreign bankers have been appointed for the issue of the QIP.
Bajaj Finance posted a net profit growth of 63 percent year-on-year (YoY) on robust loan growth, better margins, controlled expenses and lower taxes in the second quarter of FY20.
Close
The business performance of Bajaj Finance continues to be strong despite macro headwinds such as slowing growth, tight liquidity and rising competition.Special Thursday Expiry on 10th 7th Nov
Early Closure to The Great Diwali Discount. Last Chance to get Moneycontrol PRO for a year @ Rs. 289/- only
Coupon code: DIWALI


How do I get what I want? What do I have to do and in what order?
These are the questions to get ahead and demolish the competition, right?
And what are you willing to do? Will you step on someone? Will you step on a friend?  What obstructions in your path are you willing to eradicate with no sympathy whatsoever?
If you’re going to get what you want with more than just dumb luck, you certainly will have to be finding out the answers to these questions. Honesty is key and mistakes, I understand, will be severely punished with sharp learning curves.
In other words, there is no half-assing it. There is no try. You go in, you better do it ruthlessly.
And lo — some people do.
–
Speaking of doing it right and living it up, the boy and his boys are really doing it right in the Central European part of this globe. Sure, they’ll come back saddened to be reminded that they’re Americans, and that life will not then be what it once was. But for now, it’s all it CAN be, as they say, and no one, not the Haight entourage or the ‘lou boys are doing it as well as these kids because they have the advantage of multi-national travel in addition to the fun. Fabulous work gentlemen.
Bring me back some absinthe and we’ll party like hobbits over squash.
–
Monday night was weird. Yes, there were people dressed up in strange garments and asking for free stuff but that’s because it was all hallow’s eve. We tell all the children to go forth and hoard as much chocolate as they can from perfect strangers. And while we’re confusing them with lessons conflicting with the norm, we should tell them to cross the streets without looking, take off their seat belts and take up smoking. That’d go over well.
But that’s not why it was weird.
Engulfed in work in the past few days, I find it increasingly hard to actually get home. Work follows me with a deviousness I cannot escape these days. While the folks were enjoying the company of our height and age-challenged neighbors, I was (and I’m not even joking), solving inverse logic truth tables by hand in between creeping the hell out of trick-or-treaters.
“What’s you’re costume of?” The kids would ask.
“I’m an IT consultant. Scary, right?” Total confusion on their faces. “ETHERNET!” I yelled at the short blond one, and I’m pretty sure I saw him flinch. His did didn’t laugh.
“Here, kid, take some candy and…NO, DON’T TOUCH THAT.”
“Sorry to scare you but your kid was reaching for an inverse truth table and that’s just like an apple with a razor blade in it but without the apple.”
I didn’t get many return visitors. I did, however, enjoy turning the fog machine on occasionally spraying the older kids with a hose when they got too close to my jack-o-lantern. But the scary thing is that I was using my degree.
Weird, eh?
Stay in school kids, and don’t take candy from that handsome Professor Snape over in the crazy lady’s house…yeah, the one with the bad-ass jack-o-rockin’-lanterns.


This is Words and Buttons Online — a collection of interactive #tutorials, #demos, and #quizzes about #mathematics, #algorithms and #programming.
Imagine there is something wrong with the water pressure in your house. You have to call the plumber service. They say that there is a guy, who is honest, and capable, and has a PhD in plumbing, but… He doesn’t speak English well. He came from Tajikistan and only speaks fluent Tajik. But it just so happens that you studied Tajik in college, so you say that they send the guy immediately.
When he arrives, you describe the problem (in Tajik), and he gets to work. Soon enough he finds the problem and tries to report it to you, apparently waiting for a reaction. But for some reason he doesn’t use Tajik to report it, he uses English. Which… He doesn’t really know. If you reply (in Tajik) that you don’t understand, he will not switch to Tajik; he will only repeat the same phrase louder.
Which doesn’t help to build a dialog at all.
Nobody knows why he consistently chooses to reply in the language he doesn’t speak well instead of his own. That you do, by the way. It is absurdly irritating, but that’s just how the things work. It’s how they have always been. What he means makes perfect sense in his own tongue, but what he speaks aloud is basically a bad English mixed with professional jargonisms and Tajik obscenities.
This feels somehow like this.
|
Tamserpo [CC BY-SA 3.0 or GDFL], from Wikimedia Commons
Ok, it isn’t about plumbing anymore. It never was about plumbing. It’s about how we communicate with the machine. A programming language is something we use to tell it what to do, but the machine tries to speak back in English when something gets wrong. Computers don’t speak English well, although they are good at processing formal languages. And presumably, the one who writes in a formal language should be able to read it back without a problem. Wouldn’t it be better, if the compiler or interpreter responds in the same language it gets its commands in?
So far the only languages I know that report errors in itself are Erlang, Elixir, and Ocaml. If you know more, please let me know.
Here’s a simple example from “Programming Erlang”:
1> Point = {point, 10, 45}. 2> {point, C, C} = Point. =ERROR REPORT==== 28-Oct-2006::17:17:00 === Error in process <0.32.0> with exit value: {{badmatch,{point,10,45}},[{erl_eval,expr,3}]} |
The string in bold is the error message, the rest is just a preamble from the interpreter. Indeed, it isn’t entirely convenient for the casual reader. You have to know Erlang to read its errors. But since you still need to know Erlang to write the code that causes them, it’s fine.
The alternatives are much worse. With informal and non-standardized error messaging you have to know not only the programming language itself but its error messaging Pidgin as well. Every C++ practitioner can confirm that reading STL messages is an art by itself. It takes knowledge, patience, determination, and occasionally a crystal ball to build a firm understanding of a reported problem.
For instance, the error message from above reads as “sorry, I can’t print out an element for you, because its type doesn’t have a << operator.”
Normally, the language is something you can build a dialog in. Programming languages are an unlucky exemption. Historically, it was more important to tell a computer what to do rather than the opposite. When you write a small single-threaded program you can hope that there will be no errors whatsoever so you don’t really need a reporting at all. Error reporting is viewed as an auxiliary feature.
Erlang, however, aims at building highly complex distributed systems. Errors are not only most likely to happen, they are inherent to the nature of the domain. Everything that could go wrong eventually will. And you better have a decent reporting language for that.
The very fact that you can have a dialog, meaning writing code and receiving errors in the same language, makes Erlang not only programming but a true computer language.
| Index #programming | ← there's more. |
+
So You Think You Know C (free book) + Geometry for Programmers (paid book) + Github & RSS |


I must confess: I love cabbage. It goes well with any number of dishes, nutritious, has a wonderful green color, and comes in many variates. I am still skeptikal about green smoothies, and have profound dislike for the current Kale love. My forefathers grew Repolho before any hipster donned its first cap!
Cabbage is a serious matter for me. Anyway, I got hold of this recipe and though it was a interesting combination of salmon and Vegetable king, and the Dill vinagrette intrigued me.
Who am I kidding? I wanted a cabbage dish and there was not a lot of time to prepare it. This fitted the bill. It also turned out to have a wonderful flavor with the dill and lemon combining well with the cabbage.
Variations
- I have a Kumquat tree which happens to have fruits at the moment. I took a Kumquat and squeezed the juice on top of the salmon before sticking it in the oven for extra citrus flavor.
- The recipe states Dijon mustard, and I kept because it sounds fancy. In fact, I used the rest of an old Bautzen mustard jar.
- The original recipe had 2 types of cabbage, Kale and Savoy. The hipsters took all the Grühnkohl from the supermaket. No problem. It worked nicely with just the Savoy and it sounds frencher.
Source
This Martha Stewart book on our shelve for while and even though we made a few recipes, it seems underused. This recipe came from there and it was a hit, so hopefully there will be more to come.
- Servings: 4
- Prep Time: 15 mins
- Total Time: 35 mins
Ingredients
- Salmon: 4 fillets
- Savoy cabbage: 1 large head
- Dill: small bunch
- Lemon: 1, juice and zest
- Olive oil: 8 tablespoon
- Dijon mustard: 1 teaspoon
- Salt and pepper: to taste
Directions
- Heat the oven to 230ºc. Take the cabbage leaves, remove the hard steams and cut in thin slices. Put it in a roasting tray, drizzle with 2 tablespoons of olive oil, salt and pepper to taste, mixing it all. Put in the oven for 6 minutes. Once done, mix it all again, lay the salmon on top and season with salt and pepper. Roast everything for about 10 minutes.
- In a bowl mix the left-over olive oil (6 tablespoons), the chopped dill, mustard, and lemon juice and zest.
- Serve drizzling the vinaigrette on top of the salmon and cabbage.


Like a BIBFRAME Work, a BIBFRAME Instance is a RDF Resource subclass. A BIBFRAME Instance combines characteristics of both a FRBR Expression and Manifestation.
A BIBFRAME Instance has the following properties:
The BIBFRAME Instance is also the parent class for a number of different types of Instances listed below:
<http://bibcat.org/Instance/b96aa86c-2cfa-11e6-8471-005056c00008> a bf:Instance, bf:Print ; bf:instanceOf <https://lccn.loc.gov/12032828> ; bf:copyrightDate 1887 ; bf:provisionActivity [ a bf:Publication ; relator:pbl <http://id.loc.gov/authorities/names/n88002745> ] . <http://id.loc.gov/authorities/names/n88002745> a bf:Organization ; rdfs:label "Houghton, Mifflin and Company" .
BIBFRAME 2.0 does not currently have an audio instance type, so to represent an audio instance, the more general BIBFRAME Instance class is used.
<http://bibcat.org/Instance/058767d0-2d76-11e6-b2d3-ac87a3129ce6> a bf:Instance ; bf:carrier [ a bf:Carrier ; rdf:value "audio disc" ] ; bf:dimensions "12 in." ; bf:extent [ a bf:Extent ; rdf:value "3 sound discs" ] ; bf:instanceOf <https://lccn.loc.gov/85751262> ; bf:soundCharacteristic [ a bf:PlayingSpeed ; rdf:value "33 1/3 rpm" ] .
In this example, we will create two instances of our United Nations BIBFRAME Dataset, one for the XML format and the other for the CSV format.
<http://bibcat.org/Instance/ce342a40-2d7d-11e6-927b-ac87a3129ce6> a bf:Electronic ; bf:instanceOf <http://bibcat.org/Work/84330c68-2d7d-11e6-8b16-ac87a3129ce6> bf:digitalCharacteristic [ a bf:FileType ; rdf:value "XML" ], [ a bf:EncodingFormat ; rdf:value "application/xml" ], [ a bf:FileSize ; rdf:value "937 KB" ]; rdfs:label "XML download of Population by religion, sex, and urban/rural residence for 2011" . <http://bibcat.org/Instance/e68986ec-2db6-11e6-9e8a-005056c00008> a bf:Electronic ; rdfs:label "CSV download of Population by religion, sex, and urban/rural residence for 2011" ; bf:digitalCharacteristic [ a bf:EncodingFormat ; rdf:value "text/csv" ], [ a bf:FileType, rdf:value "Comma separated values" ], [ a bf:FileSize, rdf:value "213 KB" ]; bf:instanceOf <http://bibcat.org/Work/84330c68-2d7d-11e6-8b16-ac87a3129ce6> .
<http://bibcat.org/Instance/10e18ff4-2dba-11e6-9a7b-005056c00008> a bf:Instance ; bf:carrier [ a bf:Carrier ; rdf:value "videodisc" ] ; bf:instanceOf <http://tiger.coloradocollege.edu/record=b2348805> ; bf:note [ a bf:Note ; rdfs:label "Filmed in Egypt and the Sinai with one of the biggest sets ever constructed for a motion picture, this version tells the story of the life of Moses. Once favored in the Pharaoh's bousehold, Moses turned his back on a privileged life to lead his people to freedom" ; bf:noteType "summary" ] ; bf:videoCharacteristic [ a bf:VideoFormat ; rdf:value "DVD NTSC Region 1, widescreen enhanced for 16:0 TVs" ] .


Computer Science and Information Systems Faculty
The following is a list of Computer Science and Information Systems faculty. Please click on a faculty member's name for more information.
Department Chair
Il-Hyung Cho |
Faculty
Moe Bidgoli |
|
Il-Hyung Cho |
|
George Corser |
|
Poonam Dharam |
|
Scott James |
|
Aos Mulahuwaish |
|
Khandaker Abir Rahman |


Internal to Button module. Members should not be accessed by the application. More...
#include <Button.h>
Data Fields | |
| ClockP_Handle | clockHandle |
| Button_StateVariables | buttonStateVariables |
| Button_EventMask | buttonEventMask |
| Button_Callback | buttonCallback |
| uint32_t | debounceDuration |
| uint32_t | longPressDuration |
| uint32_t | doublePressDetectiontimeout |
| Button_Pull | buttonPull |
Internal to Button module. Members should not be accessed by the application.
| ClockP_Handle Button_Object::clockHandle |
Handle to clock used for timing
| Button_StateVariables Button_Object::buttonStateVariables |
State variables for handling the debounce state machine
| Button_EventMask Button_Object::buttonEventMask |
Event subscription mask for the button
| Button_Callback Button_Object::buttonCallback |
Callback function for the button
| uint32_t Button_Object::debounceDuration |
Debounce duration for the button in milliseconds(ms)
| uint32_t Button_Object::longPressDuration |
Long press duration is milliseconds(ms)
| uint32_t Button_Object::doublePressDetectiontimeout |
Double press detection timeout is milliseconds(ms)
| Button_Pull Button_Object::buttonPull |
Button pull(stored after reading from GPIO module)


Big sports events today
by TIMESOFINDIA.COMNEW DELHI: Here are the big sports events lined up for Sunday (November 3) that comprise action from India-Bangladesh first T20I and summit clashes of WTA Finals.
(All timings in IST)
1:15 am (Football - Serie A)
Torino vs Juventus (Juventus won 1-0)
1:30 am (Football - La Liga)
Real Madrid vs Real Betis (The match ended in a 0-0 draw)
6:30 am (Cricket - 2nd T20I)
New Zealand vs England (New Zealand won by 21 runs)
9:00 am (Cricket - 1st T20I)
Australia vs Pakistan (Match called off due to rain)
2:00 pm (Tennis - WTA Finals)
Kristina Mladenovic/Timea Babos vs Hsieh Su-wei/Barbora Strycova in women's doubles final
3:00 pm (Football - International Friendly)
India women vs Vietnam women
5:00 pm (Tennis - WTA Finals)
Ashleigh Barty vs Elina Svitolina in women's singles final
7:00 pm (Cricket - 1st T20I)
7:30 pm (Football - Premier League)
Crystal Palace vs Leicester City
7:30 pm (Football - Indian Super League)
8:30 pm approx (Badminton - SaarLorLux Open)
Lakshya Sen vs Hong Yang Weng (China) in men's singles final
10:00 pm (Football - Premier League)
Everton vs Tottenham
11:00 pm (Cricket - India Women tour of West Indies, 2nd ODI)
West Indies Women vs India Women


[1]
unsurprisingly lacked a bit of mediterranean flair , -lrb-/-lrb- especially the saucing for pasta dishes -rrb-/-rrb- .
[2]
very efficient and quiet aircon , hot water shower , but a bit slow in operation .


CrimPapers
Articles published on 15 June 2017
On 15 June 2017, 9 new articles were published in 2 journals.
Corrigendum
Negative Emotionality and Aggression in Violent Offenders: the Moderating Role of Emotion Dysregulation
Latent Profile Analysis of Psychopathic Traits Among Homicide, General Violent, Property, and White-Collar Offenders
Third-Person Perceptions, Hostile Media Effects, and Policing: Developing A Theoretical Framework For Assessing the Ferguson Effect
Race/ethnicity and Criminal Behavior: Neurohormonal Influences
Life History As the Appropriate Meta-Theory For Evaluating Group-Differences in Psychopathic Personality: A Comment on Lynn (2017)
Heart Rate, Serotonin Transporter Linked Polymorphic Region (5-Httlpr) Genotype, and Violence in An Incarcerated Sample
Giving the Devil His Due: Why Freedom of Inquiry in Science and Politics Is Inviolable
The Effect of Minority Threat on Risk Management and the “New Disciplinology” in Schools


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| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object org.apache.xpath.XPath
public class XPath
The XPath class wraps an expression object and provides general services for execution of that expression.
| Field Summary | |
|---|---|
private static boolean |
DEBUG_MATCHES
Set to true to get diagnostic messages about the result of match pattern testing. |
private FunctionTable |
m_funcTable
The function table for xpath build-in functions |
private Expression |
m_mainExp
The top of the expression tree. |
(package private) java.lang.String |
m_patternString
The pattern string, mainly kept around for diagnostic purposes. |
static int |
MATCH
Represents a match type expression. |
static double |
MATCH_SCORE_NODETEST
The match score if the pattern consists of just a NodeTest. |
static double |
MATCH_SCORE_NONE
The match score if no match is made. |
static double |
MATCH_SCORE_NSWILD
The match score if the pattern pattern has the form NCName:*. |
static double |
MATCH_SCORE_OTHER
The match score if the pattern consists of something other than just a NodeTest or just a qname. |
static double |
MATCH_SCORE_QNAME
The match score if the pattern has the form of a QName optionally preceded by an @ character. |
static int |
SELECT
Represents a select type expression. |
(package private) static long |
serialVersionUID
|
| Constructor Summary | |
|---|---|
XPath(Expression expr)
Construct an XPath object. |
|
XPath(java.lang.String exprString,
javax.xml.transform.SourceLocator locator,
PrefixResolver prefixResolver,
int type)
Construct an XPath object. |
|
XPath(java.lang.String exprString,
javax.xml.transform.SourceLocator locator,
PrefixResolver prefixResolver,
int type,
javax.xml.transform.ErrorListener errorListener)
Construct an XPath object. |
|
XPath(java.lang.String exprString,
javax.xml.transform.SourceLocator locator,
PrefixResolver prefixResolver,
int type,
javax.xml.transform.ErrorListener errorListener,
FunctionTable aTable)
Construct an XPath object. |
| Method Summary | |
|---|---|
void |
assertion(boolean b,
java.lang.String msg)
Tell the user of an assertion error, and probably throw an exception. |
boolean |
bool(XPathContext xctxt,
int contextNode,
PrefixResolver namespaceContext)
Given an expression and a context, evaluate the XPath and return the result. |
void |
callVisitors(ExpressionOwner owner,
XPathVisitor visitor)
This will traverse the heararchy, calling the visitor for each member. |
void |
error(XPathContext xctxt,
int sourceNode,
java.lang.String msg,
java.lang.Object[] args)
Tell the user of an error, and probably throw an exception. |
XObject |
execute(XPathContext xctxt,
int contextNode,
PrefixResolver namespaceContext)
Given an expression and a context, evaluate the XPath and return the result. |
XObject |
execute(XPathContext xctxt,
org.w3c.dom.Node contextNode,
PrefixResolver namespaceContext)
Given an expression and a context, evaluate the XPath and return the result. |
void |
fixupVariables(java.util.Vector vars,
int globalsSize)
This function is used to fixup variables from QNames to stack frame indexes at stylesheet build time. |
Expression |
getExpression()
Get the raw Expression object that this class wraps. |
javax.xml.transform.SourceLocator |
getLocator()
Get the SourceLocator on the expression object. |
double |
getMatchScore(XPathContext xctxt,
int context)
Get the match score of the given node. |
java.lang.String |
getPatternString()
Return the XPath string associated with this object. |
private void |
initFunctionTable()
initial the function table |
void |
setExpression(Expression exp)
Set the raw expression object for this object. |
void |
warn(XPathContext xctxt,
int sourceNode,
java.lang.String msg,
java.lang.Object[] args)
Warn the user of an problem. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
static final long serialVersionUID
private Expression m_mainExp
private transient FunctionTable m_funcTable
java.lang.String m_patternString
public static final int SELECT
public static final int MATCH
private static final boolean DEBUG_MATCHES
public static final double MATCH_SCORE_NONE
public static final double MATCH_SCORE_QNAME
public static final double MATCH_SCORE_NSWILD
public static final double MATCH_SCORE_NODETEST
public static final double MATCH_SCORE_OTHER
| Constructor Detail |
|---|
public XPath(java.lang.String exprString, javax.xml.transform.SourceLocator locator, PrefixResolver prefixResolver, int type, javax.xml.transform.ErrorListener errorListener) throws javax.xml.transform.TransformerException
exprString
- The XPath expression.locator
- The location of the expression, may be null.prefixResolver
- A prefix resolver to use to resolve prefixes to
namespace URIs.type
- one of SELECT
or MATCH
.errorListener
- The error listener, or null if default should be used.
javax.xml.transform.TransformerException
- if syntax or other error.public XPath(java.lang.String exprString, javax.xml.transform.SourceLocator locator, PrefixResolver prefixResolver, int type, javax.xml.transform.ErrorListener errorListener, FunctionTable aTable) throws javax.xml.transform.TransformerException
exprString
- The XPath expression.locator
- The location of the expression, may be null.prefixResolver
- A prefix resolver to use to resolve prefixes to
namespace URIs.type
- one of SELECT
or MATCH
.errorListener
- The error listener, or null if default should be used.
javax.xml.transform.TransformerException
- if syntax or other error.public XPath(java.lang.String exprString, javax.xml.transform.SourceLocator locator, PrefixResolver prefixResolver, int type) throws javax.xml.transform.TransformerException
exprString
- The XPath expression.locator
- The location of the expression, may be null.prefixResolver
- A prefix resolver to use to resolve prefixes to
namespace URIs.type
- one of SELECT
or MATCH
.
javax.xml.transform.TransformerException
- if syntax or other error.public XPath(Expression expr)
expr
- The Expression object.
javax.xml.transform.TransformerException
- if syntax or other error.| Method Detail |
|---|
private void initFunctionTable()
public Expression getExpression()
getExpression
in interface ExpressionOwner
public void fixupVariables(java.util.Vector vars, int globalsSize)
vars
- List of QNames that correspond to variables. This list
should be searched backwards for the first qualified name that
corresponds to the variable reference qname. The position of the
QName in the vector from the start of the vector will be its position
in the stack frame (but variables above the globalsTop value will need
to be offset to the current stack frame).public void setExpression(Expression exp)
setExpression
in interface ExpressionOwner
exp
- the raw Expression object, which should not normally be null.public javax.xml.transform.SourceLocator getLocator()
public java.lang.String getPatternString()
public XObject execute(XPathContext xctxt, org.w3c.dom.Node contextNode, PrefixResolver namespaceContext) throws javax.xml.transform.TransformerException
xctxt
- The execution context.contextNode
- The node that "." expresses.namespaceContext
- The context in which namespaces in the
XPath are supposed to be expanded.
javax.xml.transform.TransformerException
- thrown if
the error condition is severe enough to halt processing.
javax.xml.transform.TransformerException
public XObject execute(XPathContext xctxt, int contextNode, PrefixResolver namespaceContext) throws javax.xml.transform.TransformerException
xctxt
- The execution context.contextNode
- The node that "." expresses.namespaceContext
- The context in which namespaces in the
XPath are supposed to be expanded.
javax.xml.transform.TransformerException
- thrown if the active ProblemListener decides
the error condition is severe enough to halt processing.
javax.xml.transform.TransformerException
public boolean bool(XPathContext xctxt, int contextNode, PrefixResolver namespaceContext) throws javax.xml.transform.TransformerException
xctxt
- The execution context.contextNode
- The node that "." expresses.namespaceContext
- The context in which namespaces in the
XPath are supposed to be expanded.
javax.xml.transform.TransformerException
- thrown if the active ProblemListener decides
the error condition is severe enough to halt processing.
javax.xml.transform.TransformerException
public double getMatchScore(XPathContext xctxt, int context) throws javax.xml.transform.TransformerException
xctxt
- XPath runtime context.context
- The current source tree context node.
MATCH_SCORE_NODETEST
,
MATCH_SCORE_NONE
, MATCH_SCORE_OTHER
,
or MATCH_SCORE_QNAME
.
javax.xml.transform.TransformerException
public void warn(XPathContext xctxt, int sourceNode, java.lang.String msg, java.lang.Object[] args) throws javax.xml.transform.TransformerException
xctxt
- The XPath runtime context.sourceNode
- Not used.msg
- An error msgkey that corresponds to one of the constants found
in XPATHErrorResources
, which is
a key for a format string.args
- An array of arguments represented in the format string, which
may be null.
javax.xml.transform.TransformerException
- if the current ErrorListoner determines to
throw an exception.public void assertion(boolean b, java.lang.String msg)
b
- If false, a runtime exception will be thrown.msg
- The assertion message, which should be informative.
java.lang.RuntimeException
- if the b argument is false.public void error(XPathContext xctxt, int sourceNode, java.lang.String msg, java.lang.Object[] args) throws javax.xml.transform.TransformerException
xctxt
- The XPath runtime context.sourceNode
- Not used.msg
- An error msgkey that corresponds to one of the constants found
in XPATHErrorResources
, which is
a key for a format string.args
- An array of arguments represented in the format string, which
may be null.
javax.xml.transform.TransformerException
- if the current ErrorListoner determines to
throw an exception.public void callVisitors(ExpressionOwner owner, XPathVisitor visitor)
owner
- The owner of the visitor, where that path may be
rewritten if needed.visitor
- The visitor whose appropriate method will be called.
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(Bureaucryptocracy Principle)
Dont be afraid to challenge crypto choices!Never write your own crypto
Never write your own cryptoor otherwise said: If You're Typing the Letters A-E-S Into Your Code You’re Doing It Wrong
requests open
encrypt with AES
Cryptography is perilous because you get no feedback when you mess up
- Code always compiles
- No crypto tests in CI pipelines (except SAST to some extent)
cryptopals.comThe Right Way to learn about Cryptography is to start by learning how to break it
We do this unusual combination of algorithms so the attacker won't know how what exactly is done internallyfoto de la niña dando explicaciones
A cryptosystem should be secure even if everything about the system, except the key, is public knowledge
The Enemy knows the system
But the pen-test did not find any flaws in it
OK, if you think my choice of MGF1+SHA256(SHA1) is wrong do a PoC exploiting it
Anyone, from the most clueless amateur to the best cryptographer, can create an algorithm that he himself can't break.
The Enemy knows the system
Secret Prefix
sha = sha(secret + data)
Secret Suffix
sha = sha(data + secret)


Use addDataAsync() API to asynchronous load data from a given url, set callback to execute when onload of the data
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--- layout: page title: About header-img: "img/about-bg.png" ---
Mallory is a passionate and driven full stack engineer, multi-instrumentalist and writer who fronts the psych/indie/art rock band, The Grasping Straws and appears in other bands: Mischief Night, and Sensation Play. She enjoys being in the moment and learning new things. Follow along as she explores her curiosity in the world of tech, one concept at a time.