Bike racing unites the joy of riding a bike, the thrill of competition and pushing to be your best, the rewards of working together and sharing camaraderie with teammates, and combining fitness with skills and strategy. And there’s so much more. “What’s racing all about” is different for every woman. We have the top-flight women who best the field again and again, while also taking time to help guide and support others. We have back-of-the-packers who know they’ll never achieve glory in the traditional sense, but feel their own glory in getting out there and pushing through, and sharing that experience with women who become some of their closest friends. Some of us love the dirt, delighting in the unique (and often muddy) challenges of a cyclocross or mountain bike course. Some crave the speed and sun of the track. Some love the open road and the feel of the peloton. We share a willingness to work hard, and a strong desire to have fun at the same time. We also work together for the sake of the team -- particularly in road and track races, individual racers might have specific roles to play within a race to help boost those with the likeliest chances of winning. You may also find yourself working with women from other teams for parts of a road or track race -- that is, riding in a rotating paceline to share the burden of the pull and the benefits of the draft so that all have a better chance of advancing in the field. Many women who love their bikes but never thought of themselves as racers find great fulfillment once they’ve explored this world a little more.
Being on a racing team gives you a lot of benefits, and also carries some expectations of you. As a team member, you’re one of a consistent group of cyclists who can train together, usually with similar goals and timelines, and that makes the workouts more efficient and more fun. You can learn a lot from more experienced racers -- everything from bike handling skills to how to pin on race numbers or use rollers. Teams typically have at least one training ride per week during the fall and winter (and sometimes at other times of the year) and everyone needs to participate in many (not all) of those rides, as well as do additional training throughout the week. Teams may have clinics and workshops about topics such as hill climbing, nutrition and recovery and you’d be expected to attend as many of those as possible. Of course, teams are all about racing. You’ll be expected to race a certain number of times each year; the number varies by team. Some teams have racers in all four disciplines (road, mountain, cyclocross, track); others focus on one or two. Many teams engage in community involvement activities, and some sponsor races where you can either race or volunteer and learn more about the sport.
Sometimes team members know of a promising prospect and approach that person. Many other times, you make the first move by discussing your interest with a team and applying to join that team. (See below for more details.) Each team has different personalities and areas of emphasis. Check out the websites of all the teams, and chat with team members on the road, at events, or at the Meet the Team rides.
Definitely not! Although a team can be a great resource for learning the ropes, not everyone chooses to join one right away - it's fine to take your time, wait a season or two, and see who you click with on and off the bike. However, you'll want to have a group of folks you ride with on a regular basis - whether they're teammates or friends, riding with people who are more skilled than you is the best way to improve.
All bike racing requires a good level of physical fitness and strength. But you don’t have to be superhuman by any means. You’ll get more fit as you train with your team, for one thing. And, if you’re not one of the fastest kids on the block but you’re strong and agile, mountain bike or cyclocross racing could be great options for you. Some racers start out on the road, then try MTB or cyclocross and never look back because they enjoy the dirt so much. While you don’t have to be super-fast, you do need to be willing to work hard and participate fully in various team workouts, races and other activities.
Road bike races can involve some hills, and those can make the difference for some racers and their ability to stay in the pack (group). But some road races are flat, criteriums (short courses, usually in a town or city) don’t usually involve much of a climb, and track racing has no hills at all. Cyclocross can have some short, steep hills, and some have longer climbs, but they usually only make up a small part of a course, and cyclocross has other sorts of barriers (literally). Mountain bike racing often includes hills (as the name would imply), but these can be ridden at your pace, and there are plenty of places where you can make up any time lost on a climb.
Definitely not! We have racers from their teens to their late-60s, and every age in between. Many don’t start racing until their 40s or 50s and beyond, and many older racers easily outpace their younger competitors. Think about it in terms of your fitness, not your age. And experience can count for a lot!
Bike racing carries some risks, as does any form of bike riding (and many other athletic activities). In road and track races, you often ride in very close proximity to others and at a relatively high speed. This means different sorts of risks than, say, commuting through downtown Seattle. Serious accidents are relatively rare, but they can happen. Cyclocross and mountain bike races move at slower speeds and on dirt (or mud!) – falling can actually be fun and remind you of being a kid again - but as with any bike riding there’s a risk of injury in those disciplines too. Those who choose to race understand the risks, do what they can to minimize the risks, and believe that their joy in the sport is worth it.
Cost will vary by cycling discipline and the races you choose to do, and whether you choose to join a team (not required, but highly encouraged for the support and guidance you will receive). Expect to pay around $25 to $40, give or take, for each race you do, though some teams may reimburse part of those expenses. For road and track racing, you will need to buy a USA Cycling license ($70 per year; one-day licenses can be purchased for beginner categories at $xxx ) and WSBA membership ($25); this may be required for some mountain and cyclocross races also. If you join a cycling team you likely will have to pay team dues; amounts vary, so ask individual teams that you’re interested in. Teams will usually require that you buy a new kit (team jersey and shorts, plus if desired other pieces of team apparel) each year (that’s necessary because sponsors, which are highlighted on our kits, can vary from year to year). Depending on what types of races you do, you may have to drive or carpool some distance to races and those expenses typically aren’t reimbursed.
Racing and related training and team activities do require a significant time commitment, though in some cases it’s not much more than the time you’re already spending on your bike. Many racers do have busy jobs and heavy family commitments; it helps to have a family that’s enthusiastic about your racing. Some racers make it a family affair, with children or spouses/significant others who race or who attend races as supporters or spectators. To get a better feel for how racers juggle their various loves, chat with us at races or events (don’t be shy - racers love to talk about racing and their teams) or click the ASK WSBA link.
Generally, team rosters are set in October, after a series of Meet the Team and Introduction to Racing rides in late August through early October (check the calendar - http://www.wsbaracing.org/calendar.html - and this website for details as the time approaches.) If you’re getting interested in racing at some other time of the year, there are lots of things you can do to prepare.
You can start by clicking the ASK WSBA link to let us know of your background and interest, and we can get back to you with some specific ideas and more contact information. Otherwise, going to a race and talking with team members at races is a great way to get started (check the calendar). You don’t have to be on a team to race, though some overall skill and bike handling ability is necessary and for some races you will need at least a one-day USAC license (usually purchasable at the race). In the late spring and throughout the summer, you can take an intro track class at the velodrome (www.velodrome.org; see below for more details), then try some track racing, and get to know members of the various teams. CycleU (www.cycleu.com) offers many classes and bootcamps for road and cyclocross racing, including introductory sessions. For mountain biking you can usually just show up and register to race on the day but some may require registration in advance if numbers are limited – see the website for the race for details. There are no training pre-requisites but make sure you ask around to understand how hard a course may be. Beyond that, just riding your bike a lot and getting in good overall shape goes a long way.
USA Cycling divides racers into racing categories depending on their experience and proficiency, with Category 1 being the most experienced and fastest amateur racers. Beginning road, track and cyclocross racers always start as Cat 4s (women) and Cat 5 (men), and usually (but not always) have their own field in a race so they’re not grouped in with the more experienced and faster Cats 3, 2 and 1. If you finish well in a specified number of races, you can look to upgrade to Cat 3, and potentially later to Cats 2 and 1. In mountain bike races, the beginner category may be called “beginners” or, if it is sanctioned by USA Cycling, it is Category 3. For some races, racers may be able to “self-seed” or choose which category they race in.
Speed at any given time during a race can vary, depending on terrain, weather, tactics being employed, and other factors. The pace speeds up for at least part of the field during attacks and then slows a bit for recovery. Sometimes races start out slower than you’d expect; other times they’re fast from the outset. When you’re part of a peloton or working with one or more other riders, you get benefit of the draft and can ride faster with 30 percent less effort. Generally speaking, Cat 4 women’s races in Washington range from an average of 21 to 23 mph for the winner to around 18 mph.
In Washington state, the road season begins in late February or early March and lasts through early summer, with some criteriums continuing throughout the summer. Time trials tend to kick off the season, followed by road races and then criteriums (crits). Cat 4 fields for road races are typically 20 to 40 racers. A Cat 4 road race is usually 24 to 45 miles, typically in two or more loops of the same circuit. The degree of hilliness varies. Each race starts with what’s called a neutral rollout, in which everyone rides slowly together for a mile or so until the gun sounds and the race begins. The peloton stays generally together for the opening few miles, until attacks (one or more racers speeding up significantly for a short while as part of a tactic) begin and start breaking up the field. What happens after that varies depending on terrain and skill of each rider. Often the field gets broken into two or three or more smaller groups - and typically each of those groups works together even though each has competing teams represented. The pace, and attacks and other tactics, can ebb and flow throughout the race. Road races are held away from Seattle in places such as Mason Lake or Sequim, so a few hours of driving often is needed early in the morning. For more information: http://www.usacycling.org/how-to-start-racing-on-the-road.htm
A time trial is each individual racing against the clock - you start alone, not as part of the group, and you ride alone, and your finish is determined by your time. Racers start off at set intervals on a continuing basis, so you almost always can see other racers ahead of you, passing you, or returning from another direction on a loop. You can pass and be passed. A time trial in this area is around 10 miles, generally but not totally flat. A time trial is a good way to get your feet wet and work out some new-racer jitters - you can get a feel for all the necessary pre-race activities and warmups without being in the middle of a mass start. . You can use your usual road bike for a time trial - take off water bottle cages, light brackets, saddle bags and anything else weighty - but some people use a specially designed, more aerodynamic time trial bike.
A criterium, commonly called a crit, is shorter than a road race and involves many laps around a closed circuit of a mile or so in length. The total distance of each race isn’t known in advance; it’s determined as the race progresses. Racing time is around 25 to 40 minutes. There is some elevation, but much less than in a road race. Bike handling and corning skills play a big role, as does overall speed and strength. Local crits include one held in Volunteer Park in the Capitol Hill neighborhood and one in downtown Ballard -- and watching as a spectator can give you a great feel for what a race is all about. More informal crits are held every Thursday evening throughout the spring and summer at Seward Park.
A circuit race is like a criterium, but over a longer course, up to a couple of miles per lap.
A stage race combines several types of road racing - time trial, road, criterium, circuit - spread out over a weekend (sometimes longer). It challenges a road racer’s versatility; strategy also can play a big role.
Cyclocross -- often called ‘cross or CX -- is the fastest-growing cycling discipline in the U.S. and is known for its festive, spectator-friendly atmosphere, its accessibility for all sorts of bike riders, and of course its dirt and mud. Cyclocross is primarily a fall/winter sport, with races starting in September, and a great way to get off the couch when the weather gets less sunny! Races are frequently held in urban settings like parks or forested areas. There are several series in Washington, including MFG, Cross Revolution, and Inland series. Each series comprises of several races in different locations with different types of terrain and features. You can choose to race one or many of the series. Additionally there are independent races held throughout the season. Cyclocross is short and intense, lasting from 30 minutes to an hour depending on your category. A race involves multiple laps around a course of often varied surface types, and may include small barriers that you with obstacles that you either ride up and over, carry your bike over after dismounting. You may end up running parts of the course while carrying your bike. It’s short and intense, lasting from 30 minutes to an hour. Many racers who aren’t all that fast on the road can do well in CX if they have good overall strength. Most people race on a special cyclocross bike, though you could also start out with a mountain bike or a road bike with wider tires. CX bikes have more clearance around the tires for mud, the tires are wider and knobby, and the brakes are either cantilever or disc. XXXX ADD: Details about the Washington CX scene, where races are typically held, etc XXX For more information: USAC: http://www.usacycling.org/how-to-start-racing-cyclo-cross.htm. For local series information see www.mfgcyclocross.com, http://www.cross-revolution.com/, http://www.inlandnwcyclocross.com/ and the WSBA calendar for links to other local races.
In track racing, racers ride special track bikes - with a fixed gear and no brakes - in multiple laps around a banked-corner track known as a velodrome. These races are the shortest and most intense of the cycling disciplines, usually around two to five miles for women’s Cat 4. Track racing includes a number of different types of races, with exotic names such as the Miss ‘n’ Out, Snowball, Point-A-Lap and Keirin, and each session of Cat 4 racing usually involves three races of varying types and lengths. Strategy often plays a big role in track races; often it’s not the fastest woman who wins. Track racing improves your bike handling skills, spin, sprint, and overall speed and fitness. And, you learn how to stop without brakes (much easier than you might think). Unlike the other disciplines, track racing can be done only in dry conditions because the track is slippery when wet, so summer time is track time. In Washington, track racing happens at the Jerry Baker Memorial Velodrome in Redmond. The velodrome offers required classes and practice races to get you started, and you can rent a track bike there if you don’t have one. For more information: USAC: http://www.usacycling.org/how-to-start-track-racing.htm Jerry Baker Memorial Velodrome in Redmond: http://www.velodrome.org
The Mountain bike season starts in early March and runs until early fall. Races vary greatly in length, location, terrain and technical skill requirements. They can be as short as an hour, or upwards of 50 miles in length (known as “marathons” or “epics”). Most races usually are multiple laps of a marked course, with beginner racers doing fewer laps. In some races, particularly those that are more technical in nature, beginners may do an abbreviated course that avoids the hardest sections. A mountain bike is highly advised for this discipline, but you will see many types of mountain bikes out there, from full suspension (both the front and the back of the bike have shocks), to hard-tails (front shock only), to single-speeds (with only one gear) and other varieties. Cross-country races typically emphasize overall fitness, with the full race being timed (uphills, downhills and everything in between), and may include some steeper sections of the course, roots, rocks and logs to ride over or around, though these are usually limited in nature. Local races include the Budu race series, NW Epic Series, and NW Mountain Bike races. There are also independent races that happen throughout the season. Downhill races, as the name implies, are usually fast courses that go… well… downhill, usually via very direct routes and often feature large obstacles like drops and long rocky sections. Vehicles often shuttle riders (and their very heavy bikes) to the top of a run, much like a chair lift at a downhill ski resort. Enduro races fall somewhere in between. Racers are required to ride the whole course including the climbs, but only parts are timed (usually the downhill portions requiring bike handling skills). The Sturdy Dirty race, which is an all-womens race held at Tiger Mountain every June, is a good example of an enduro.


{% extends "layout/_layout.html" %} {% set page_title = 'Columns' %} {% block main %}
Columns in mw-grid has classes like ".mv_"
or [class*="ds_"]
. Default mw-grid has 5 breakpoints in SCSS object $devices
and their keys are CSS-class prefixes:
"mv_"
- for "mobile vertical" (like ".mv_12"
) up from 320px"mh_"
- for "mobile horizontal" (like ".mh_12"
) up from 576px"tb_"
- for "tablets" (like ".tb_12"
) up from 768px"mv_"
- for "desktops" (like ".ds_12"
) up from 1024px"hd_"
- for "hi definition" (like ".hd_12"
) up from 1366pxColumns number is set in SCSS var $columns
Columns gaps (left and right) is set in SCSS var $columns_gap


The Kenyan journey of creating makers continues yet again ,a year on after Oloo Martin setting that bar i alongside Bob carry the hurdle.
Currently I work as Workshop Technician at Gearbox Kenya Limited which is a one of a kind Hardware prototyping space based in Kenya where i get to practice and also educate interested makers within the community.
Previously I served as a FabOutreach Organising Secretary at the University of Nairobi's Science and Technology Park,Fablab.Where I organised and trained Kids Outreach Program alongside my fellow outreach members. Apart from that I took part in Maternal Newborn Child Health Care (MNCH) project (2014-2015) that was being housed within the very space hence my love for a fablab in solving community project started.


Maintaining data consistency between caches in a distributed Geode system is vital for ensuring its functional integrity and preventing data loss.
General Guidelines
Before Restarting a Region with a Disk Store, Consider the State of the Entire Region
Note: If you revoke a member’s disk store, do not restart that member with its disk stores—in isolation—at a later time.
Geode stores information about your persisted data and prevents you from starting a member with a revoked disk store in the running system. But Geode cannot stop you from starting a revoked member in isolation, and running with its revoked data. This is an unlikely situation, but it is possible to do:
- Members A and B are running, both storing Region data to disk.
- Member A goes down.
- Member B goes down.
- At this point, Member B has the most recent disk data.
- Member B is not usable. Perhaps its host machine is down or cut off temporarily.
- To get the system up and running, you start Member A, and use the command line tool to revoke Member B’s status as member with the most recent data. The system loads Member A’s data and you run forward with that.
- Member A is stopped.
- At this point, both Member A and Member B have information in their disk files indicating they are the gold copy members.
- If you start Member B, it will load its data from disk.
- When you start Member A, the system will recognize the incompatible state and report an exception, but by this point, you have good data in both files, with no way to combine them.
Understand Cache Transactions
Understanding the operation of Geode transactions can help you minimize situations where the cache could get out of sync.
Transactions do not work in distributed regions with global scope.
Transactions provide consistency within one cache, but the distribution of results to other members is not as consistent.
Multiple transactions in a cache can create inconsistencies because of read committed isolation. Since multiple threads cannot participate in a transaction, most applications will be running multiple transactions.
An in-place change to directly alter a key’s value without doing a put can result in cache inconsistencies. With transactions, it creates additional difficulties because it breaks read committed isolation. If at all possible, use copy-on-read instead.
In distributed-no-ack scope, two conflicting transactions in different members can commit simultaneously, overwriting each other as the changes are distributed.
If a cache writer exists during a transaction, then each transaction write operation triggers a cache writer’s related call. Regardless of the region’s scope, a transaction commit can invoke a cache writer only in the local cache and not in the remote caches.
A region in a cache with transactions may not stay in sync with a region of the same name in another cache without transactions.
Two applications running the same sequence of operations in their transactions may get different results. This could occur because operations happening outside a transaction in one of the members can overwrite the transaction, even in the process of committing. This could also occur if the results of a large transaction exceed the machine’s memory or the capacity of Geode. Those limits can vary by machine, so the two members may not be in sync.
Guidelines for Multi-Site Deployments
Optimize socket-buffer-size
In a multi-site installation using gateways, if the link between sites is not tuned for optimum throughput, it could cause messages to back up in the cache queues. If a queue overflows because of inadequate buffer sizes, it will become out of sync with the sender and the receiver will be unaware of the condition. You can configure the send-receive buffer sizes of the TCP/IP connections used for data transmissions by changing the socket-buffer-size attribute of the gateway-sender and gateway-receiver elements in the cache.xml
file. Set the buffer size by determining the link bandwidth and then using ping to measure the round-trip time.
When optimizing socket-buffer sizes, use the same value for both gateway senders and gateway receivers.
Prevent Primary and Secondary Gateway Senders from Going Offline
In a multi-site installation, if the primary gateway server goes offline, a secondary gateway sender must take over primary responsibilities as the failover system. The existing secondary gateway sender detects that the primary gateway sender has gone offline, and a secondary one becomes the new primary. Because the queue is distributed, its contents are available to all gateway senders. So, when a secondary gateway sender becomes primary, it is able to start processing the queue where the previous primary left off with no loss of data.
If both the primary gateway sender and all its secondary senders go offline and messages are in their queues, data loss could occur, because there is no failover system.
Verify That isOriginRemote Is Set to False
The isOriginRemote flag for a server or a multi-site gateway is set to false by default, which ensures that updates are distributed to other members. Setting its value to true in the server or the receiving gateway member applies updates to that member only, so updates are not distributed to peer members.


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Timely (and Stateful) Processing with Apache Beam
In a prior blog post, I introduced the basics of stateful processing in Apache Beam, focusing on the addition of state to per-element processing. So-called timely processing complements stateful processing in Beam by letting you set timers to request a (stateful) callback at some point in the future.
What can you do with timers in Beam? Here are some examples:
- You can output data buffered in state after some amount of processing time.
- You can take special action when the watermark estimates that you have received all data up to a specified point in event time.
- You can author workflows with timeouts that alter state and emit output in response to the absence of additional input for some period of time.
These are just a few possibilities. State and timers together form a powerful programming paradigm for fine-grained control to express a huge variety of workflows. Stateful and timely processing in Beam is portable across data processing engines and integrated with Beam’s unified model of event time windowing in both streaming and batch processing.
What is stateful and timely processing?
In my prior post, I developed an understanding of stateful processing largely by contrast with associative, commutative combiners. In this post, I’ll emphasize a perspective that I had mentioned only briefly: that elementwise processing with access to per-key-and-window state and timers represents a fundamental pattern for “embarrassingly parallel” computation, distinct from the others in Beam.
In fact, stateful and timely computation is the low-level computational pattern that underlies the others. Precisely because it is lower level, it allows you to really micromanage your computations to unlock new use cases and new efficiencies. This incurs the complexity of manually managing your state and timers - it isn’t magic! Let’s first look again at the two primary computational patterns in Beam.
Element-wise processing (ParDo, Map, etc)
The most elementary embarrassingly parallel pattern is just using a bunch of
computers to apply the same function to every input element of a massive
collection. In Beam, per-element processing like this is expressed as a basic
ParDo
- analogous to “Map” from MapReduce - which is like an enhanced “map”,
“flatMap”, etc, from functional programming.
The following diagram illustrates per-element processing. Input elements are squares, output elements are triangles. The colors of the elements represent their key, which will matter later. Each input element maps to the corresponding output element(s) completely independently. Processing may be distributed across computers in any way, yielding essentially limitless parallelism.
This pattern is obvious, exists in all data-parallel paradigms, and has a simple stateless implementation. Every input element can be processed independently or in arbitrary bundles. Balancing the work between computers is actually the hard part, and can be addressed by splitting, progress estimation, work-stealing, etc.
Per-key (and window) aggregation (Combine, Reduce, GroupByKey, etc.)
The other embarassingly parallel design pattern at the heart of Beam is per-key
(and window) aggregation. Elements sharing a key are colocated and then
combined using some associative and commutative operator. In Beam this is
expressed as a GroupByKey
or Combine.perKey
, and corresponds to the shuffle
and “Reduce” from MapReduce. It is sometimes helpful to think of per-key
Combine
as the fundamental operation, and raw GroupByKey
as a combiner that
just concatenates input elements. The communication pattern for the input
elements is the same, modulo some optimizations possible for Combine
.
In the illustration here, recall that the color of each element represents the key. So all of the red squares are routed to the same location where they are aggregated and the red triangle is the output. Likewise for the yellow and green squares, etc. In a real application, you may have millions of keys, so the parallelism is still massive.
The underlying data processing engine will, at some level of abstraction, use state to perform this aggregation across all the elements arriving for a key. In particular, in a streaming execution, the aggregation process may need to wait for more data to arrive or for the watermark to estimate that all input for an event time window is complete. This requires some way to store the intermediate aggregation between input elements as well a way to a receive a callback when it is time to emit the result. As a result, the execution of per key aggregation by a stream processing engine fundamentally involves state and timers.
However, your code is just a declarative expression of the aggregation operator. The runner can choose a variety of ways to execute your operator. I went over this in detail in my prior post focused on state alone. Since you do not observe elements in any defined order, nor manipulate mutable state or timers directly, I call this neither stateful nor timely processing.
Per-key-and-window stateful, timely processing
Both ParDo
and Combine.perKey
are standard patterns for parallelism that go
back decades. When implementing these in a massive-scale distributed data
processing engine, we can highlight a few characteristics that are particularly
important.
Let us consider these characteristics of ParDo
:
- You write single-threaded code to process one element.
- Elements are processed in arbitrary order with no dependencies or interaction between processing of elements.
And these characteristics for Combine.perKey
:
- Elements for a common key and window are gathered together.
- A user-defined operator is applied to those elements.
Combining some of the characteristics of unrestricted parallel mapping and per-key-and-window combination, we can discern a megaprimitive from which we build stateful and timely processing:
- Elements for a common key and window are gathered together.
- Elements are processed in arbitrary order.
- You write single-threaded code to process one element or timer, possibly accessing state or setting timers.
In the illustration below, the red squares are gathered and fed one by one to
the stateful, timely, DoFn
. As each element is processed, the DoFn
has
access to state (the color-partitioned cylinder on the right) and can set
timers to receive callbacks (the colorful clocks on the left).
So that is the abstract notion of per-key-and-window stateful, timely processing in Apache Beam. Now let’s see what it looks like to write code that accesses state, sets timers, and receives callbacks.
Example: Batched RPC
To demonstrate stateful and timely processing, let’s work through a concrete example, with code.
Suppose you are writing a system to analyze events. You have a ton of data coming in and you need to enrich each event by RPC to an external system. You can’t just issue an RPC per event. Not only would this be terrible for performance, but it would also likely blow your quota with the external system. So you’d like to gather a number of events, make one RPC for them all, and then output all the enriched events.
State
Let’s set up the state we need to track batches of elements. As each element comes in, we will write the element to a buffer while tracking the number of elements we have buffered. Here are the state cells in code:
new DoFn<Event, EnrichedEvent>() {
@StateId("buffer")
private final StateSpec<BagState<Event>> bufferedEvents = StateSpecs.bag();
@StateId("count")
private final StateSpec<ValueState<Integer>> countState = StateSpecs.value();
… TBD …
}
# State and timers are not yet supported in Beam's Python SDK.
# Follow https://issues.apache.org/jira/browse/BEAM-2687 for updates.
Walking through the code, we have:
- The state cell
"buffer"
is an unordered bag of buffered events. - The state cell
"count"
tracks how many events have been buffered.
Next, as a recap of reading and writing state, let’s write our @ProcessElement
method. We will choose a limit on the size of the buffer, MAX_BUFFER_SIZE
. If
our buffer reaches this size, we will perform a single RPC to enrich all the
events, and output.
new DoFn<Event, EnrichedEvent>() {
private static final int MAX_BUFFER_SIZE = 500;
@StateId("buffer")
private final StateSpec<BagState<Event>> bufferedEvents = StateSpecs.bag();
@StateId("count")
private final StateSpec<ValueState<Integer>> countState = StateSpecs.value();
@ProcessElement
public void process(
ProcessContext context,
@StateId("buffer") BagState<Event> bufferState,
@StateId("count") ValueState<Integer> countState) {
int count = firstNonNull(countState.read(), 0);
count = count + 1;
countState.write(count);
bufferState.add(context.element());
if (count > MAX_BUFFER_SIZE) {
for (EnrichedEvent enrichedEvent : enrichEvents(bufferState.read())) {
context.output(enrichedEvent);
}
bufferState.clear();
countState.clear();
}
}
… TBD …
}
# State and timers are not yet supported in Beam's Python SDK.
# Follow https://issues.apache.org/jira/browse/BEAM-2687 for updates.
Here is an illustration to accompany the code:
- The blue box is the
DoFn
. - The yellow box within it is the
@ProcessElement
method. - Each input event is a red square - this diagram just shows the activity for
a single key, represented by the color red. Your
DoFn
will run the same workflow in parallel for all keys which are perhaps user IDs. - Each input event is written to the buffer as a red triangle, representing the fact that you might actually buffer more than just the raw input, even though this code doesn’t.
- The external service is drawn as a cloud. When there are enough buffered
events, the
@ProcessElement
method reads the events from state and issues a single RPC. - Each output enriched event is drawn as a red circle. To consumers of this output, it looks just like an element-wise operation.
So far, we have only used state, but not timers. You may have noticed that there is a problem - there will usually be data left in the buffer. If no more input arrives, that data will never be processed. In Beam, every window has some point in event time when any further input for the window is considered too late and is discarded. At this point, we say that the window has “expired”. Since no further input can arrive to access the state for that window, the state is also discarded. For our example, we need to ensure that all leftover events are output when the window expires.
Event Time Timers
An event time timer requests a call back when the watermark for an input
PCollection
reaches some threshold. In other words, you can use an event time
timer to take action at a specific moment in event time - a particular point of
completeness for a PCollection
- such as when a window expires.
For our example, let us add an event time timer so that when the window expires, any events remaining in the buffer are processed.
new DoFn<Event, EnrichedEvent>() {
…
@TimerId("expiry")
private final TimerSpec expirySpec = TimerSpecs.timer(TimeDomain.EVENT_TIME);
@ProcessElement
public void process(
ProcessContext context,
BoundedWindow window,
@StateId("buffer") BagState<Event> bufferState,
@StateId("count") ValueState<Integer> countState,
@TimerId("expiry") Timer expiryTimer) {
expiryTimer.set(window.maxTimestamp().plus(allowedLateness));
… same logic as above …
}
@OnTimer("expiry")
public void onExpiry(
OnTimerContext context,
@StateId("buffer") BagState<Event> bufferState) {
if (!bufferState.isEmpty().read()) {
for (EnrichedEvent enrichedEvent : enrichEvents(bufferState.read())) {
context.output(enrichedEvent);
}
}
}
}
# State and timers are not yet supported in Beam's Python SDK.
# Follow https://issues.apache.org/jira/browse/BEAM-2687 for updates.
Let’s unpack the pieces of this snippet:
-
We declare an event time timer with
@TimerId("expiry")
. We will use the identifier"expiry"
to identify the timer for setting the callback time as well as receiving the callback. -
The variable
expiryTimer
, annotated with@TimerId
, is set to the valueTimerSpecs.timer(TimeDomain.EVENT_TIME)
, indicating that we want a callback according to the event time watermark of the input elements. -
In the
@ProcessElement
element we annotate a parameter@TimerId("expiry") Timer
. The Beam runner automatically provides thisTimer
parameter by which we can set (and reset) the timer. It is inexpensive to reset a timer repeatedly, so we simply set it on every element. -
We define the
onExpiry
method, annotated with@OnTimer("expiry")
, that performs a final event enrichment RPC and outputs the result. The Beam runner delivers the callback to this method by matching its identifier.
Illustrating this logic, we have the diagram below:
Both the @ProcessElement
and @OnTimer("expiry")
methods perform the same
access to buffered state, perform the same batched RPC, and output enriched
elements.
Now, if we are executing this in a streaming real-time manner, we might still have unbounded latency for particular buffered data. If the watermark is advancing very slowly, or event time windows are chosen to be quite large, then a lot of time might pass before output is emitted based either on enough elements or window expiration. We can also use timers to limit the amount of wall-clock time, aka processing time, before we process buffered elements.
Processing Time Timers
A timer in processing time (time as it passes while your pipeline is executing) is intuitively simple: you want to wait a certain amount of time and then receive a call back.
To put the finishing touches on our example, we will set a processing time
timer as soon as any data is buffered. We track whether or not the timer has
been set so we don’t continually reset it. When an element arrives, if the
timer has not been set, then we set it for the current moment plus
MAX_BUFFER_DURATION
. After the allotted processing time has passed, a
callback will fire and enrich and emit any buffered elements.
new DoFn<Event, EnrichedEvent>() {
…
private static final Duration MAX_BUFFER_DURATION = Duration.standardSeconds(1);
@TimerId("stale")
private final TimerSpec staleSpec = TimerSpecs.timer(TimeDomain.PROCESSING_TIME);
@ProcessElement
public void process(
ProcessContext context,
BoundedWindow window,
@StateId("count") ValueState<Integer> countState,
@StateId("buffer") BagState<Event> bufferState,
@TimerId("stale") Timer staleTimer,
@TimerId("expiry") Timer expiryTimer) {
boolean staleTimerSet = firstNonNull(staleSetState.read(), false);
if (firstNonNull(countState.read(), 0) == 0) {
staleTimer.offset(MAX_BUFFER_DURATION).setRelative());
}
… same processing logic as above …
}
@OnTimer("stale")
public void onStale(
OnTimerContext context,
@StateId("buffer") BagState<Event> bufferState,
@StateId("count") ValueState<Integer> countState) {
if (!bufferState.isEmpty().read()) {
for (EnrichedEvent enrichedEvent : enrichEvents(bufferState.read())) {
context.output(enrichedEvent);
}
bufferState.clear();
countState.clear();
}
}
… same expiry as above …
}
# State and timers are not yet supported in Beam's Python SDK.
# Follow https://issues.apache.org/jira/browse/BEAM-2687 for updates.
Here is an illustration of the final code:
Recapping the entirety of the logic:
- As events arrive at
@ProcessElement
they are buffered in state. - If the size of the buffer exceeds a maximum, the events are enriched and output.
- If the buffer fills too slowly and the events get stale before the maximum is reached, a timer causes a callback which enriches the buffered events and outputs.
- Finally, as any window is expiring, any events buffered in that window are processed and output prior to the state for that window being discarded.
In the end, we have a full example that uses state and timers to explicitly
manage the low-level details of a performance-sensitive transform in Beam. As
we added more and more features, our DoFn
actually became pretty large. That
is a normal characteristic of stateful, timely processing. You are really
digging in and managing a lot of details that are handled automatically when
you express your logic using Beam’s higher-level APIs. What you gain from this
extra effort is an ability to tackle use cases and achieve efficiencies that
may not have been possible otherwise.
State and Timers in Beam’s Unified Model
Beam’s unified model for event time across streaming and batch processing has
novel implications for state and timers. Usually, you don’t need to do anything
for your stateful and timely DoFn
to work well in the Beam model. But it will
help to be aware of the considerations below, especially if you have used
similar features before outside of Beam.
Event Time Windowing “Just Works”
One of the raisons d’etre for Beam is correct processing of out-of-order event data, which is almost all event data. Beam’s solution to out-of-order data is event time windowing, where windows in event time yield correct results no matter what windowing a user chooses or what order the events come in.
If you write a stateful, timely transform, it should work no matter how the surrounding pipeline chooses to window event time. If the pipeline chooses fixed windows of one hour (sometimes called tumbling windows) or windows of 30 minutes sliding by 10 minutes, the stateful, timely transform should transparently work correctly.
This works in Beam automatically, because state and timers are partitioned per key and window. Within each key and window, the stateful, timely processing is essentially independent. As an added benefit, the passing of event time (aka advancement of the watermark) allows automatic release of unreachable state when a window expires, so you often don’t have to worry about evicting old state.
Unified real-time and historical processing
A second tenet of Beam’s semantic model is that processing must be unified between batch and streaming. One important use case for this unification is the ability to apply the same logic to a stream of events in real time and to archived storage of the same events.
A common characteristic of archived data is that it may arrive radically out of order. The sharding of archived files often results in a totally different ordering for processing than events coming in near-real-time. The data will also all be all available and hence delivered instantaneously from the point of view of your pipeline. Whether running experiments on past data or reprocessing past results to fix a data processing bug, it is critically important that your processing logic be applicable to archived events just as easily as incoming near-real-time data.
It is (deliberately) possible to write a stateful and timely DoFn that delivers
results that depend on ordering or delivery timing, so in this sense there is
additional burden on you, the DoFn
author, to ensure that this nondeterminism
falls within documented allowances.
Go use it!
I’ll end this post in the same way I ended the last. I hope you will go try out Beam with stateful, timely processing. If it opens up new possibilities for you, then great! If not, we want to hear about it. Since this is a new feature, please check the capability matrix to see the level of support for your preferred Beam backend(s).
And please do join the Beam community at<EMAIL_ADDRESS>and follow @ApacheBeam on Twitter.


Michael Smerconish
Welcome to MichaelSmerconish.com
This domain is for sale. If you want to buy it, please email at.


{% extends 'layout.html' %} {% block pageTitle %} You are not eligible for help to get money off milk, food and vitamins {% endblock %} {% block content %}
You’re not eligible to get help to buy food and milk if:
{% endif %} {% if (data['ESA'] == "income") and (data['pregnant'] == "no") %}You’re not eligible to get help to buy food and milk if:
{% endif %}You might be eligible the get help to buy food and milk if:
Your biometric residence permit (BRP) or your online immigration status will say if you cannot claim public funds. You might also have a letter from the Home Office about it.
If you think you cannot claim public funds because of your immigration status, ask for an application form by emailing healthystartclaim@dhsc.gov.uk


{{comments post.id}}
{{email}} said:
{{body}}
{{#unless @last}}{{/unless}}
Be the first to leave a comment!
{{/each}}


sqlsrv_has_rows
(No version information available, might only be in Git)
sqlsrv_has_rows — Indicates whether the specified statement has rows
说明
bool sqlsrv_has_rows ( resource $stmt )
Indicates whether the specified statement has rows.
参数
stmt
A statement resource returned by sqlsrv_query() or sqlsrv_execute().
返回值
Returns TRUE if the specified statement has rows and FALSE if the statement
does not have rows or if an error occurred.
范例
Example #1 sqlsrv_has_rows() example
"dbName", "UID"=>"username", "PWD"=>
"password" )
$conn = sqlsrv_connect( $server, $connectionInfo );
$stmt = sqlsrv_query( $conn, "SELECT * FROM Table_1");
if ($stmt) {
$rows = sqlsrv_has_rows( $stmt );
if ($rows === true)
echo "There are rows.
";
else
echo "There are no rows.
";
}
?>
参见
• sqlsrv_num_rows() - Retrieves the number of rows in a result set
• sqlsrv_query() - Prepares and executes a query.


{% extends "layouts/base.html" %} {% load layout_extras %} {% load i18n %} {% block title %}{%trans "Permanent Identifier Creation Unavailable" %}{% endblock %} {% block heading %}{% content_heading _("Permanent Identifier Creation Unavailable") %}{% endblock %} {% block content %}
{% trans "You may not create any permanent identifiers because your account doesn't have any identifier types (shoulders) assigned to it." %}
{% url "ui_demo.simple" as url_demosimple %} {% comment %}Translators: Copy HTML tags over and only translate words outside of these tags i.e.:
TRANSLATE TEXT WRAPPED BY HTML TAGS
i.e.: PLEASE PRESERVE HTML TAGS {% endcomment %} {% blocktrans trimmed %}You may still create temporary identifiers with the demo identifierfunctionality.{% endblocktrans %}{% trans "If you have questions, you may " %} {% trans "contact us" %}.


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The Quick Version
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We expect participants to follow these rules at conference and workshop venues and conference-related social events.


| < Day Day Up > |
9.8. The Lisp ModesEmacs has three Lisp modes, listed here by their command names:
All three modes have the same basic functionality; they differ only in the support they give to running Lisp code. All three Lisp modes understand the basic syntax elements common to all language modes. In addition, they have various commands that apply to the more advanced syntactic concepts of S-expressions, lists, and defuns. An S-expression (or syntactic expression) is any syntactically correct Lisp expression, be it an atom (number, symbol, variable, etc.), or parenthesized list. Lists are special cases of S-expressions, and defuns (function definitions) are special cases of lists. Several commands deal with these syntactic concepts; you will most likely become comfortable with a subset of them. Table 9-11 shows the commands that handle S-expressions.
Since an S-expression can be a wide variety of things, the actions of commands that handle S-expressions are determined by where your cursor is when you invoke them. If your cursor is on a ( or on a space preceding one, the S-expression in question is taken to be the list that starts with that (. If your cursor is on some other character such as a letter or number (or preceding whitespace), the S-expression is taken to be an atom (symbol, variable, or constant). For example, suppose your cursor is in this position: (mary bob (dave (pete)) ed) If you type C-M-f, the cursor moves like this: (mary bob (dave (pete)) ed) That is, the cursor moves forward past the S-expression (dave (pete)), which is a list. However, say your cursor is positioned like this: (mary bob (dave (pete)) ed) When you type C-M-f, it moves here: (mary bob (dave (pete)) ed) In this case, the S-expression is the atom bob. The commands moving in lists are shown in Table 9-12.
As a mnemonic device, you can think of lists as analogous to lines and S-expressions as analogous to characters; thus, C-n and C-p appear in list motion commands, whereas C-f and C-b appear in S-expression motion commands. C-M-n and C-M-p work similarly to C-M-f and C-M-b, respectively, except that you must position the cursor so that there is a list in front or back of it to move across—that is, there must be an opening or closing parenthesis on, after, or before the cursor. If there is no parenthesis, Emacs signals an error. For example, if your cursor is positioned like this: (fred bob (dave (pete)) ed) and you type C-M-n, Emacs complains with the message: Containing expression ends prematurely However, if your cursor is here: (fred bob (dave (pete)) ed) the "next list" is actually (dave (pete)), and the cursor ends up like this if you type C-M-n: (fred bob (dave (pete)) ed) The commands for moving up or down lists enable you to get inside or outside them. For example, say your cursor is here: (fred bob (dave (pete)) ed) typing C-M-d moves the cursor here: (fred bob (dave (pete)) ed) This is the result because fred is the next level down after its enclosing list. Typing C-M-d again has this result: (fred bob (dave (pete)) ed) You are now inside the list (dave (pete)). At this point, typing C-M-u does the opposite of what C-M-d does: it moves the cursor back and outside of the two lists. But if you type M-x up-list Enter, you will move forward as well as out, resulting in this: (fred bob (dave (pete)) ed) The commands for defuns listed in Table 9-13 are more straightforward.
These commands work properly only when the (defun that starts the current function is at the beginning of a line. 9.8.1 Indentation in Lisp ModesThe Lisp modes provide "flashing" of matching left parentheses; if the matching parenthesis is outside of the current window, the line it is on appears in the minibuffer. The Lisp modes also provide indentation via the Tab key and C-j for newline-and-indent (except in Lisp interaction mode, described later in this chapter). The indentation style supported by the Lisp modes "knows" a lot about Lisp keywords and list syntax; unfortunately, it is not easily customized.[12]
Here is an example, a Lisp equivalent of the "times" C function shown earlier in the chapter, that illustrates the indentation style: (defun times (x y) (let ((i 0) (result 0)) (while (< i x) (setq result (+ result y) i (1+ i))) result)) The basic indentation value is 2; this value is used whenever code on the next line goes down a level in nesting. For example, the body of the function, after the line containing defun, is indented by 2. The (while... and result)) lines are indented by 2 with respect to the let because they are the body of the block let introduces. Things like defun, let, and while are function calls, even though they act like keywords. The indentation convention for function calls is that if there are arguments on lines after the line where the function name and first argument appear, the additional arguments line up with the first one. In other words, this has the form: (function-name arg1 arg2 arg3 ...) The multiple arguments to setq in the preceding function provide another example of this. However, the indentation of the line (result 0) shows that something a bit different happens with lists that are not function calls. The list in question is actually ((i 0) (result 0)), which is a list with two elements (both of which are also lists). The indentation style supported by the Lisp modes lines up these two elements. Even though keyword-like terms such as let and while are actually function calls, the Lisp modes "understand" these functions to the extent that special indentation conventions are set up for them. For example, if we were to put the condition for the while-loop on a separate line and press Tab to indent it properly, the result would be: (while (< i x) (setq result (+ result y) i (1+ i))) Similar things happen with if and cond control structures; Chapter 11 contains properly indented examples. Another remark about indentation conventions: the Lisp modes are geared toward a style in which multiple right parentheses are put on the same line immediately following each other, instead of on separate lines. For example, the line i (1+ i))) contains right parentheses that close off the 1+ function, the setq, and the while respectively. If you prefer, you can put your closing parentheses on separate lines, but if you press Tab to indent them, they won't line up properly with their matching open parentheses; you have to indent them manually. In addition to the Tab and C-j commands for indentation, the Lisp modes support the command C-M-q (for indent-sexp), which indents every line in the S-expression just following the cursor. You can use this command, for example, to indent an entire function definition: just put the cursor right before the defun and type C-M-q. 9.8.2 Comments in Lisp ModesComments in the Lisp modes are handled by the universal comment command M-;, which indents out to comment-column (or, if there is text at that column, one space past the last character), inserts a semicolon, and puts the cursor just past it. If you want a comment to occupy an entire line (or to start anywhere other than at comment-column), you must move to where you want the comment to start and type the semicolon yourself. Note that if you press Tab on any line that contains only a comment, the comment moves out to comment-column. To get around this, use two or more semicolons; doing so causes Tab to leave the comments where they are. The Lisp modes also support the other comment commands discussed earlier in the chapter, including M-j to extend a comment to another line and M-x kill-comment Enter to get rid of a single-line comment. These features are common to all three Lisp modes; next, we discuss the features unique to each. 9.8.3 Emacs Lisp Mode DifferencesEmacs Lisp mode was designed to be used with code meant to run within Emacs itself, so it facilitates running the code you type. Lisp is an interpreted (as opposed to purely compiled) language, so it is possible to blur the line between the write and run/debug phases of Lisp programming; Emacs Lisp mode takes some advantage of this opportunity, whereas Lisp interaction mode goes even further, as we'll see later. In Emacs Lisp mode, the command C-M-x (eval-defun) picks up the function definition around or after the cursor and evaluates it, meaning that it parses the function and stores it so that Emacs "knows" about the function when you invoke it. Emacs Lisp mode also includes the command M-Tab (for lisp-complete-symbol),[13] which performs completion on the symbol (variable, function name, etc.) preceding the cursor, as described in Chapter 14. Thus, you can type the shortest unambiguous prefix for the symbol, followed by M-Tab, and Emacs tries to complete the symbol's name for you as far as it can. If it completes the symbol name, you can go on with whatever you are doing. If it doesn't, you haven't provided an unambiguous prefix. You can type more characters (to disambiguate further), or you can type M-Tab again, and a help window showing the choices pops up. Then you can type more characters and complete the symbol yourself, or you can try for completion again.
9.8.4 Lisp Mode DifferencesLisp mode (as opposed to Emacs Lisp mode) is meant for use with Lisp processors other than the Emacs Lisp interpreter. Therefore it includes a couple of commands for interfacing to an external Lisp interpreter. The Lisp mode command C-c C-z (run-lisp) starts up your system's Lisp interpreter as a subprocess and creates the *lisp* buffer (with an associated window) for input and output.[14] If a Lisp subprocess already exists, C-c C-z uses it rather than creating a second one. You can send function definitions to the Lisp subprocess by putting the cursor anywhere within a function's definition and using C-M-x, which in this case stands for lisp-send-defun. This procedure causes the functions you define to become known to the Lisp interpreter so that you can invoke them later.
9.8.5 Working with Lisp FragmentsEmacs Lisp mode is probably the best thing to use if you are editing entire files of Emacs Lisp code, for example, if you are programming your own mode (as described in Chapter 11) or modifying an existing one. However, if you are editing "little" pieces of Lisp code (for example, making additions or modifications to your .emacs file), Emacs has more powerful features you can use that further blur the line between writing and running code. <IP_ADDRESS> Commands for evaluating a line of LispThe first of these is the command M-: (for eval-expression). This command enables you to type a one-line Lisp expression of any kind in the minibuffer; the expression is evaluated, and the result is printed in the minibuffer. This is an excellent, quick way to check the values of Emacs variables and to experiment with "internal" Emacs functions that aren't bound to keys or that require arguments. You can use the symbol completion command M-Tab while you are using eval-expression. Unfortunately (or fortunately, depending on your point of view), Emacs doesn't normally let you use eval-expression. If you try pressing M-:, you will see the message loading novice . . . in the minibuffer. Then a window pops up with a message on the order of, "You didn't really mean to type that, did you?" You get three options: press Space to try the command only once, y to try it and enable it for future use with no questions asked, or n to do nothing. If you want to use eval-expression, type y. This command actually results in the following line being put in your .emacs file: (put 'eval-expression 'disabled nil) If you are a knowledgeable Lisp programmer, you will understand that this addition sets the property disabled of the symbol eval-expression to nil. In other words, Emacs considers certain commands to be verboten to novice users and thus allows commands to be disabled. If you want to skip this entire procedure and just use eval-expression, simply put the above line in your .emacs file yourself (make sure you include the single quotes). Another feature that helps you exercise Emacs Lisp code is C-x C-e (for eval-last-sexp). This command runs the line of Lisp that your cursor is on and prints its value in the minibuffer. C-x C-e is handy for testing single lines of code in an Emacs Lisp file. <IP_ADDRESS> Using Lisp interaction modeAn even more powerful feature is Lisp interaction mode. This is the mode the default buffer *scratch* is in. Filenames with no suffixes normally cause Emacs to go into Lisp interaction mode, though you can change this using the variable auto-mode-alist, described earlier in this chapter and in more detail in Chapter 10. You can also put any buffer in Lisp interaction mode by typing M-x lisp-interaction-mode Enter; to create an extra Lisp interaction buffer, just type C-x b (for switch-to-buffer), supply a buffer name, and put it in Lisp interaction mode. Lisp interaction mode is identical to Emacs Lisp mode except for one important feature: C-j is bound to the command eval-print-last-sexp. This command takes the S-expression just before point, evaluates it, and prints the result in the buffer. To get the usual newline-and-indent functionality attached to C-j in other modes, you must press Enter, followed by Tab. Remember that an S-expression is any syntactically valid expression in Lisp. Therefore, you can use C-j in Lisp interaction mode to check the values of variables, enter function definitions, run functions, and so on. For example, if you type auto-save-interval and press C-j, the value of that variable (300 by default) appears. If you type a defun and press C-j after the last right parenthesis, Emacs stores the function defined (for future invocation) and prints its name; in this case, C-j is similar to C-M-x (for eval-defun) except that the cursor must be after (as opposed to before or in the middle of) the function being defined. If you invoke a function, Emacs evaluates (runs) the expression and responds with whatever value the function returns. C-j in Lisp interaction mode gives you an excellent way to play with, incrementally develop, and debug Emacs Lisp code, and since Emacs Lisp is "true" Lisp, it is even useful for developing some bits of code for other Lisp systems. |
| < Day Day Up > |


3/7/2018: Portland, Oregon
3/13/2018: Seattle, Washington
4/21/2018: Eugene, Oregon
March of the Zapotec and real people of Holland
No No No
The Flying Cup Club


| Week | Day | Guest(s) | Purpose of Visit |
|---|---|---|---|
| 2 | 14 | Ram Pothineni and Nidhhi Agerwal | To celebrate iSmart Shankar movie success. |
| 3 | 21 | Vennela Kishore | To promote Manmadhudu 2 movie in which the host Akkineni Nagarjuna is lead actor. |
| 6 | 42 | Ramya Krishnan | Entered the house for the Eviction Process. |
| 7 | 49 | Nani | To promote Gang Leader movie. |
| 8 | 56 | P. V. Sindhu and Pullela Gopichand | To celebrate 2019 BWF World Championships victory. |
| 9 | 60 | Family members of Housemates | To take part in a Task to meet their family member. |
| 63 | Varun Tej | To promote Gaddalakonda Ganesh movie. | |
| 12 | 79 | Akkineni Nagarjuna | Entered the house on the Occasion of Vijayadashami festival. |
| 13 | 86 | Krithika (Vithika's Sister); Masuma (Ali's Wife); Ganguly (Siva Jyothi's Husband) |
Entered the house as a part of "BB Hotel" Luxury Budget Task Guests. |
| 87 | Revathi, Arjun & Lakshana (Baba Bhaskar's Family); Rajya Laxmi (Varun's Grandmother); Sudha Rani (Rahul's Mother); Latha (Sreemukhi's Mother) |
||
| 90 | Pooja (Varun's Sister); Rama Krishna Rathod (Sreemukhi's Father); Swapna (Siva Jyothi's Sister); Anantha Laxmi (Vithika's Mother); Anchor Ravi (Ali's Friend); Singer Noel Sean (Rahul's Friend); Shobana (Baba Bhaskar's Sister) |
To take part in a Task to predict the 5 Finalist of the season. | |
| 14 | 98 | Vijay Deverakonda, Tharun Bhascker Dhaassyam, Abhinav Gomatam and Naveen George Thomas | To promote Meeku Maathrame Cheptha movie. (Only Vijay entered the house) |
| 15 | 99 | Suma Kanakala | Entered the house on the Occasion of Deepavali festival. |
| 103 | Subhash & Phani Kumar | Entered the house as winners of content in HELO App. | |
| All Evicted Housemates | Entered the house to encourage the Finalists. | ||
| 105 | Raashi Khanna, Maruthi Dasari | To escort Ali Reza (Fourth Runner-up). | |
| Srikanth, Catherine Tresa | To escort Varun Sandesh (Third Runner-up). | ||
| Anjali | To escort Baba Bhaskar(Second Runner-up). | ||
| Nidhhi Agerwal, Anurag Kulkarni | Performed on the occasion of Grand Finale. | ||
| Chiranjeevi | To present the trophy to the winner. |


What is EQ and why is it important?
EQ stands for Emotional Quotient, though it is more commonly referred to as Emotional Intelligence. Emotions are an intangible aspect of our lives and because of this it can be really tricky to understand them. Emotional Intelligence is the ability to discriminate between your feelings, and use the information they give you as a guide in your thinking and actions.In the tech industry, it is very common to work with many different people. Strong EQ is a key element in anybody who wants to be a leader - it is one of the defining factors that "distinguishes outstanding leaders from those judged as average." (Kemper 1999)
How do we cultivate EQ?
First, we need to understand that EQ is a skill, and just like any other skill, requires practice and maintenance. Practice, combined with a concept called neuroplasticity (the ability of our brain to change based on what we are thinking, doing, and paying attention to), allows anyone to improve these skills.Training Methods
- Attention Training Also known as mindfulness, attention training is practiced by holding your attention on one thing. Mindfulness is the practice of watching the breath, and also watching your 'self', i.e. watching your attention, and being aware when it slips away from the breath.
- Conscious Listening Similarly to mindfulness, this practice is about paying attention. The focus of your attention in conscious listening, is on what another person is saying. It is a great exercise to listen and loop what someone is saying - consciously listen without interrupting, and once the person is done speaking, repeat back to them what you heard them say. The idea is not to make any comments or input on what was heard - simply repeat it back. Repeat this process until the speaker is happy with the listeners understanding of what was said.
- Journaling This is about getting accustomed to noticing cognitions and emotions, and being able to write about them. At first it may be difficult, but the goal is to be able to write non-stop for 20 minutes a day. There are many benefits to journaling; not only will it help you understand your self and your emotions, but it deregulates stress and frees the creative side of your brain up!


Most real-world systems have to deal with multiple clients simultaneously. In a typical multithreaded implementation of such a system, different threads will handle different clients. Logging is especially well suited to trace and debug complex distributed applications. An approach to differentiate the logging output of one client from another is to instantiate a new separate logger for each client. However this promotes the proliferation of loggers and increases the management overhead of logging.
A lighter technique is to uniquely stamp each log request initiated from the same client interaction.
Log4net supports different types of contextual logging and contexts with different scopes.
Contextual data can be set in different scopes. These contexts have progressively narrower visibility. In the logging event itself the values from all of the contexts are combined together such that values specified in a lower scoped context hide values from a higher context.
| Scope | Type | Description |
|---|---|---|
| Global | log4net.GlobalContext | The global context is shared by all threads in the current AppDomain. This context is thread safe for use by multiple threads concurrently. |
| Thread | log4net.ThreadContext | The thread context is visible only to the current managed thread. |
| Logical Thread | log4net.ThreadLogicalContext | The logical thread context is visible to a logical thread. Logical threads can jump from one managed thread to another. For more details see the .NET API System.Runtime.Remoting.Messaging.CallContext. |
| Event | log4net.Core.LoggingEvent | Each event captures the current contextual state at the time the event is generated. Contextual data can be set on the event itself. This context is only visible to the code generating the event itself. |
The log4net contexts store properties, i.e. name value pairs. The name is a string the value is any object. A property can be set as follows:
log4net.GlobalContext.Properties["name"] = value;
If properties with the same name are set in more than one context scope then the value in the narrowest scope (lower down in the list above) will hide the other values.
The property values are stored as objects within the LoggingEvent. The PatternLayout supports rendering the value of a named property using the %property{name} syntax. The value is converted to a string by passing it to the log4net.ObjectRenderer.RendererMap which will locate any custom renderer for the value type. The default behavior for custom types is to call the object's ToString() method.
An active property value is one who's value changes over time.
For example, imagine a custom type that implemented the ToString() method to return the number of bytes allocated by the runtime garbage collector.
public class GCAllocatedBytesHelper { public override string ToString() { return GC.GetTotalMemory(true).ToString(); } }
An instance of this type can be added to the log4net.GlobalContext during application startup:
log4net.GlobalContext.Properties["GCAllocatedBytes"] = new GCAllocatedBytesHelper();
Once this property is set in the context all subsequent logging events will have a property called GCAllocatedBytes. The value of the property will be an instance of the GCAllocatedBytesHelper type. When this value is rendered to a string by calling the ToString method the current number of bytes allocated by the garbage collector will be returned and included in the output.
Sometimes simple key value pairs are not the most convenient way of capturing contextual information. A stack of information is a very convenient way of storing data especially as our applications tend to be stack based.
The ThreadContext and LogicalThreadContext also support storing contextual data in a stack. The stack is stored in context property, therefore stacks have names and more than one stack can exist in the same context. A property value set in a narrower context would override a stack with the same property name set in a wider scoped context.
The stack supports Push and Pop methods. As more contextual data is pushed onto the stack the stack grows. When the stack is rendered all the data pushed onto the stack is output with the most recent data to the right hand end of the string.
As the stack is just an object stored in the context properties it is also rendered using the same PatternLayout syntax: %property{name}. Where name is the name of the stack.
Calls the the stack's Push and Pop methods must be matched up so that each push has a corresponding pop. The Push method also returns an IDisposable object that will perform the required pop operation when it is disposed. This allows the C# using syntax to be used to automate the stack management.
using(log4net.ThreadContext.Stacks["NDC"].Push("context")) { log.Info("Message"); }
The INFO level log has a stack stored in its NDC property. The top item in the stack is the string context. The using syntax ensures that the value context is popped off the stack at the end of the block.
The using syntax is recommended because it removes some work load from the developer and reduces errors in matching up the Push and Pop calls, especially when exceptions can occur.
The NDC (Nested Diagnostic Context) exists for compatibility with older versions of log4net. This helper class implements a stack which is stored in the thread context property named NDC.
The MDC (MappedDiagnostic Context) exists for compatibility with older versions of log4net. This helper class implements a properties map which is mapped directly through to the thread context properties.
To illustrate this point, let us take the example of a web service delivering content to numerous clients. The web service can build the NDC at the very beginning of the request before executing other code. The contextual information can be the client's host name and other information inherent to the request, typically information contained in cookies. Hence, even if the web service is serving multiple clients simultaneously, the logs initiated by the same code, i.e. belonging to the same logger, can still be distinguished because each client request will have a different NDC stack. Contrast this with the complexity of passing a freshly instantiated logger to all code exercised during the client's request.
Nevertheless, some sophisticated applications, such as virtual hosting web servers, must log differently depending on the virtual host context and also depending on the software component issuing the request. Log4net supports multiple logger repositories. This would allow each virtual host to possess its own copy of the logger hierarchy. Configuring multiple logger hierarchies is beyond the scope of this document.


this should only be called by a Puppet::Type::Component resource now and it should only receive an array
# File lib/puppet/transaction.rb, line 232 def initialize(catalog, report = nil) @catalog = catalog @report = report || Puppet::Transaction::Report.new("apply", catalog.version, catalog.environment) @event_manager = Puppet::Transaction::EventManager.new(self) @resource_harness = Puppet::Transaction::ResourceHarness.new(self) @prefetched_providers = Hash.new { |h,k| h[k] = {} } end
Copy an important relationships from the parent to the newly-generated child resource.
# File lib/puppet/transaction.rb, line 67 def add_conditional_directed_dependency(parent, child, label=nil) relationship_graph.add_vertex(child) edge = parent.depthfirst? ? [child, parent] : [parent, child] if relationship_graph.edge?(*edge.reverse) parent.debug "Skipping automatic relationship to #{child}" else relationship_graph.add_edge(edge[0],edge[1],label) end end
# File lib/puppet/transaction.rb, line 221 def add_dynamically_generated_resources @catalog.vertices.each { |resource| generate_additional_resources(resource) } end
# File lib/puppet/transaction.rb, line 428 def add_resource_status(status) report.add_resource_status status end
Add some additional times for reporting
# File lib/puppet/transaction.rb, line 35 def add_times(hash) hash.each do |name, num| report.add_times(name, num) end end
Are there any failed resources in this transaction?
# File lib/puppet/transaction.rb, line 42 def any_failed? report.resource_statuses.values.detect { |status| status.failed? } end
Find all of the applied resources (including failed attempts).
# File lib/puppet/transaction.rb, line 61 def applied_resources report.resource_statuses.values.collect { |status| catalog.resource(status.resource) } end
Apply all changes for a resource
# File lib/puppet/transaction.rb, line 47 def apply(resource, ancestor = nil) status = resource_harness.evaluate(resource) add_resource_status(status) event_manager.queue_events(ancestor || resource, status.events) unless status.failed? rescue => detail resource.err "Could not evaluate: #{detail}" end
Find all of the changed resources.
# File lib/puppet/transaction.rb, line 56 def changed? report.resource_statuses.values.find_all { |status| status.changed }.collect { |status| catalog.resource(status.resource) } end
# File lib/puppet/transaction.rb, line 147 def eval_generate(resource) return false unless resource.respond_to?(:eval_generate) raise Puppet::DevError,"Depthfirst resources are not supported by eval_generate" if resource.depthfirst? begin made = resource.eval_generate.uniq return false if made.empty? made = Hash[made.map(&:name).zip(made)] rescue => detail resource.log_exception(detail, "Failed to generate additional resources using 'eval_generate: #{detail}") return false end made.values.each do |res| begin res.tag(*resource.tags) @catalog.add_resource(res) res.finish rescue Puppet::Resource::Catalog::DuplicateResourceError res.info "Duplicate generated resource; skipping" end end sentinel = Puppet::Type.type(:whit).new(:name => "completed_#{resource.title}", :catalog => resource.catalog) # The completed whit is now the thing that represents the resource is done relationship_graph.adjacent(resource,:direction => :out,:type => :edges).each { |e| # But children run as part of the resource, not after it next if made[e.target.name] add_conditional_directed_dependency(sentinel, e.target, e.label) relationship_graph.remove_edge! e } default_label = Puppet::Resource::Catalog::Default_label made.values.each do |res| # Depend on the nearest ancestor we generated, falling back to the # resource if we have none parent_name = res.ancestors.find { |a| made[a] and made[a] != res } parent = made[parent_name] || resource add_conditional_directed_dependency(parent, res) # This resource isn't 'completed' until each child has run add_conditional_directed_dependency(res, sentinel, default_label) end # This edge allows the resource's events to propagate, though it isn't # strictly necessary for ordering purposes add_conditional_directed_dependency(resource, sentinel, default_label) true end
Evaluate a single resource.
# File lib/puppet/transaction.rb, line 78 def eval_resource(resource, ancestor = nil) if skip?(resource) resource_status(resource).skipped = true else resource_status(resource).scheduled = true apply(resource, ancestor) end # Check to see if there are any events queued for this resource event_manager.process_events(resource) end
This method does all the actual work of running a transaction. It collects all of the changes, executes them, and responds to any necessary events.
# File lib/puppet/transaction.rb, line 93 def evaluate add_dynamically_generated_resources Puppet.info "Applying configuration version '#{catalog.version}'" if catalog.version relationship_graph.traverse do |resource| if resource.is_a?(Puppet::Type::Component) Puppet.warning "Somehow left a component in the relationship graph" else resource.info "Starting to evaluate the resource" if Puppet[:evaltrace] and @catalog.host_config? seconds = thinmark { eval_resource(resource) } resource.info "Evaluated in %0.2f seconds" % seconds if Puppet[:evaltrace] and @catalog.host_config? end end Puppet.debug "Finishing transaction #{object_id}" end
# File lib/puppet/transaction.rb, line 111 def events event_manager.events end
# File lib/puppet/transaction.rb, line 115 def failed?(resource) s = resource_status(resource) and s.failed? end
Does this resource have any failed dependencies?
# File lib/puppet/transaction.rb, line 120 def failed_dependencies?(resource) # First make sure there are no failed dependencies. To do this, # we check for failures in any of the vertexes above us. It's not # enough to check the immediate dependencies, which is why we use # a tree from the reversed graph. found_failed = false # When we introduced the :whit into the graph, to reduce the combinatorial # explosion of edges, we also ended up reporting failures for containers # like class and stage. This is undesirable; while just skipping the # output isn't perfect, it is RC-safe. --daniel 2011-06-07 suppress_report = (resource.class == Puppet::Type.type(:whit)) relationship_graph.dependencies(resource).each do |dep| next unless failed?(dep) found_failed = true # See above. --daniel 2011-06-06 unless suppress_report then resource.notice "Dependency #{dep} has failures: #{resource_status(dep).failed}" end end found_failed end
A general method for recursively generating new resources from a resource.
# File lib/puppet/transaction.rb, line 199 def generate_additional_resources(resource) return unless resource.respond_to?(:generate) begin made = resource.generate rescue => detail resource.log_exception(detail, "Failed to generate additional resources using 'generate': #{detail}") end return unless made made = [made] unless made.is_a?(Array) made.uniq.each do |res| begin res.tag(*resource.tags) @catalog.add_resource(res) res.finish add_conditional_directed_dependency(resource, res) generate_additional_resources(res) rescue Puppet::Resource::Catalog::DuplicateResourceError res.info "Duplicate generated resource; skipping" end end end
Prefetch any providers that support it, yo. We don’t support prefetching types, just providers.
# File lib/puppet/transaction.rb, line 278 def prefetch(provider_class, resources) type_name = provider_class.resource_type.name return if @prefetched_providers[type_name][provider_class.name] Puppet.debug "Prefetching #{provider_class.name} resources for #{type_name}" begin provider_class.prefetch(resources) rescue => detail Puppet.log_exception(detail, "Could not prefetch #{type_name} provider '#{provider_class.name}': #{detail}") end @prefetched_providers[type_name][provider_class.name] = true end
# File lib/puppet/transaction.rb, line 259 def prefetch_if_necessary(resource) provider_class = resource.provider.class return unless provider_class.respond_to?(:prefetch) and !prefetched_providers[resource.type][provider_class.name] resources = resources_by_provider(resource.type, provider_class.name) if provider_class == resource.class.defaultprovider providerless_resources = resources_by_provider(resource.type, nil) providerless_resources.values.each {|res| res.provider = provider_class.name} resources.merge! providerless_resources end prefetch(provider_class, resources) end
# File lib/puppet/transaction.rb, line 424 def relationship_graph @relationship_graph ||= Relationship_graph_wrapper.new(catalog.relationship_graph,self) end
# File lib/puppet/transaction.rb, line 432 def resource_status(resource) report.resource_statuses[resource.to_s] || add_resource_status(Puppet::Resource::Status.new(resource)) end
# File lib/puppet/transaction.rb, line 244 def resources_by_provider(type_name, provider_name) unless @resources_by_provider @resources_by_provider = Hash.new { |h, k| h[k] = Hash.new { |h, k| h[k] = {} } } @catalog.vertices.each do |resource| if resource.class.attrclass(:provider) prov = resource.provider && resource.provider.class.name @resources_by_provider[resource.type][prov][resource.name] = resource end end end @resources_by_provider[type_name][provider_name] || {} end
Is the resource currently scheduled?
# File lib/puppet/transaction.rb, line 437 def scheduled?(resource) self.ignoreschedules or resource_harness.scheduled?(resource_status(resource), resource) end
Should this resource be skipped?
# File lib/puppet/transaction.rb, line 442 def skip?(resource) if missing_tags?(resource) resource.debug "Not tagged with #{tags.join(", ")}" elsif ! scheduled?(resource) resource.debug "Not scheduled" elsif failed_dependencies?(resource) # When we introduced the :whit into the graph, to reduce the combinatorial # explosion of edges, we also ended up reporting failures for containers # like class and stage. This is undesirable; while just skipping the # output isn't perfect, it is RC-safe. --daniel 2011-06-07 unless resource.class == Puppet::Type.type(:whit) then resource.warning "Skipping because of failed dependencies" end elsif resource.virtual? resource.debug "Skipping because virtual" elsif resource.appliable_to_device? ^ for_network_device resource.debug "Skipping #{resource.appliable_to_device? ? 'device' : 'host'} resources because running on a #{for_network_device ? 'device' : 'host'}" else return false end true end
Generated with the Darkfish Rdoc Generator 2.


Mega Man
The Blue Bomber
Mega Man has appeared in many forms over the years
Mega Man, known as Rockman in Japan, is a video game franchise created by Capcom, starring the robot character Mega Man, or one of his many counterparts. Mega Man, released for the Nintendo Entertainment System in 1987, was the first in a series of over 50 games on multiple systems. By March 2015, the series had sold about thirty million copies worldwide.
The classic Mega Man series consists of ten main games, a spin-off, Mega Man & Bass, as well as all Game Boy, Sega Genesis, Sega Game Gear and other console games featuring the original design of Mega Man. The classic series is considered to be the origin of the story, with Mega Man being the first installment, and continuing with ten direct sequels. Chronologically after Mega Man 8 comes Mega Man & Bass, followed by Mega Man 9 and Mega Man 10.
Mega Man has also been featured in many comics and manga in Japan, although few have been localized in North America.
According to GamesRadar, the Mega Man games were the first to feature a non-linear "level select" option. This was a stark contrast to both linear games (like Super Mario Bros.) and open world games (like The Legend of Zelda and Metroid). GamesRadar credits the "level select" feature of Mega Man as the basis for the non-linear mission structure found in most open-world, multi-mission, sidequest-heavy games, including modern games like Grand Theft Auto, Red Dead Redemption and Spider-Man: Shattered Dimensions. In Street Fighter: Assassin's Fist tenth episode "Raging Demon", Ryu and Ken were seen playing Mega Man 2 from a gift from Ken's father.
Overall, the character of Mega Man has been well received by critics. IGN called him an icon of Capcom. Nintendo Power listed Mega Man as their fourth favourite hero, citing his ability to steal weapons from downed Robot Masters. Mega Man was also listed as the best robot in video games by many sources such Joystick Division, UGO Networks, and Complex. GameDaily ranked him as the best Capcom character of all time. UGO Networks listed Mega Man as one of their best heroes of all time, and called him "one of the most iconic video game heroes of all time". He was included in GameSpot's "All Time Greatest Video Game Hero" contest and reached the "Elite Eight" round before losing to Mario. In a Famitsu poll done in February 2010, Mega Man was voted by readers as the twenty-second most popular video game character. The 2011 Guinness World Records Gamer's Edition lists Mega Man as the 23rd most popular video game character. In 2012, GamesRadar ranked him as the 12th "most memorable, influential, and badass" protagonist in games.
For more information about Mega Man, view his Wikipedia Page


The U Coding BootCamp Sample Github Pages
We will continue styling this is in the future
The Awesome button


Performs adjustments of a user-supplied independence loglikelihood function using a robust sandwich estimator of the parameter covariance matrix, based on the methodology in Chandler and Bate (2007) <doi:10.1093/biomet/asm015>. This can be used for cluster correlated data when interest lies in the parameters of the marginal distributions or for performing inferences that are robust to certain types of model misspecification. Functions for profiling the adjusted loglikelihoods are also provided, as are functions for calculating and plotting confidence intervals, for single model parameters, and confidence regions, for pairs of model parameters. Nested models can be compared using an adjusted likelihood ratio test.
| Version: | 1.1.1 |
| Depends: | R (≥ 3.3.0) |
| Imports: | graphics, methods, numDeriv, stats, utils |
| Suggests: | knitr, rmarkdown, sandwich, testthat |
| Published: | 2018-11-28 |
| Author: | Paul J. Northrop [aut, cre, cph], Richard E. Chandler [aut, cph] |
| Maintainer: | Paul J. Northrop <p.northrop at ucl.ac.uk> |
| BugReports: | http://github.com/paulnorthrop/chandwich/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://github.com/paulnorthrop/chandwich |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | chandwich results |
| Reference manual: | chandwich.pdf |
| Vignettes: |
Introducing chandwich: Chandler-Bate Sandwich Loglikelihood Adjustment |
| Package source: | chandwich_1.1.1.tar.gz |
| Windows binaries: | r-devel: chandwich_1.1.1.zip, r-release: chandwich_1.1.1.zip, r-oldrel: chandwich_1.1.1.zip |
| OS X binaries: | r-release: chandwich_1.1.1.tgz, r-oldrel: chandwich_1.1.1.tgz |
| Old sources: | chandwich archive |
Please use the canonical form https://CRAN.R-project.org/package=chandwich to link to this page.


title('MIT SMS (BETA)') ->header('MIT SMS (BETA)'); $page->content_begin(); ?>
=$sms_announcement?>
Get info on MIT people, shuttles and classes via text message using the new MIT SMS Service (currently in BETA).
Just text your request to 648338 ('MITEDU') and we'll text back the information you need.
For keywords and tips, text "help" to 648338 ('MITEDU')
The MIT SMS Service includes People Directory, Shuttle Schedule, Stellar, Events Calendar, Emergency Info and 3Down.
This service is free from MIT, but carrier charges may apply.
$page->content_end() ?>


BREAKING: Court upholds Ojezua as Edo APC Chairman
by https://www.facebook.com/CheerfulpraiseOsagie Otabor, Bénin
An Edo State High Court has directed that Barr. Anselm Ojezua be recognised as State Chairman of the All Progressives Congress (APC) in Edo state.
It granted an order of interim injunction directing that the status quo as at 10th of November, 2019 with regards to the chairmanship of the All Progressives Congress bê maintained.
The court presided over by Justice O. Oviawe said the status quo be maintained pending the hearing and determination of the Motion on Notice praying for an order of interlocutors injunction.
Justice O Oviawe granted the order in the suit filed by Anselm Ojezua, Kenneth Asekhema and Dr. Aisosa Amadasun.
Defendants in the suit are Col. David Imuse (rtd) Lawrence Okah and Mallam Lanre Issa-Onilu.
Ojezua was last week removed from office after eleven out of the 16 member State Working Committee signed a removal notice on him as state chairman of the party.
However, three out of the eleven members have denounced their signatories on the document.
In the suit, Ojezua sought for interim injunction directing that the status quo as at 10th November 2019 with regards to the chairmanship of the All Progressive Congress, Edo State chapter, be maintained by the parties.
Deriving ruling, Justice Oviawe said, “I have come to a determination that this application for an order of interim injunction finds merit.
“I am satisfied that there is a substantial issue to be tried at the hearing. In line with the authorities and being satisfied as to the urgency of this application, the application is hereby granted as prayed.
“Accordingly, an order of interim injunction is hereby granted directing that the status quo as at 10/11/19 with regards to the chairmanship of the All Progressives Congress, Edo State chapter, be maintained pending the hearing and determination of the Motion on Notice praying for an order of interlocutory injunction.”
Justice Oviawe adjourned till Thursday, December 5th, 2019 for hearing and determination of the motion for interlocutory injunction.
It was gathered that the Ojezua who was present at the APC NEC meeting in Abuja was allowed entry based on the court ruling.


teller-android / com.levibostian.teller.repository / OnlineRepository / RefreshResult / SkippedReason / CACHE_NOT_TOO_OLD
CACHE_NOT_TOO_OLD
CACHE_NOT_TOO_OLD
Cache exists but, it's not too old yet. Call refresh with force = true
to perform a refresh manually.


A hierarchical, multivariate, continuous (and discrete) time dynamic modelling package for panel and time series data, using stochastic differential equations. Contains a faster frequentist set of functions using OpenMx for single subject and mixed-effects (random intercepts only) structural equation models, or a hierarchical Bayesian implementation using Stan that allows for random effects and non-linearity over all model parameters. Allows for modelling of multiple noisy measurements of multiple stochastic processes, time varying input / event covariates, and time invariant covariates used to predict the parameters.
| Version: | 2.7.6 |
| Depends: | R (≥ 3.4.0), Rcpp (≥ 0.12.16), OpenMx (≥ 2.3.0) |
| Imports: | rstan (≥ 2.17.1), rstantools (≥ 1.5.0), plyr, tools, data.table, Matrix, datasets, stats, graphics, grDevices, parallel, shiny, MASS, methods, utils, corrplot, mvtnorm, DEoptim, KernSmooth |
| LinkingTo: | StanHeaders (≥ 2.17.0), rstan (≥ 2.17.1), BH (≥ 1.66.0-1), Rcpp (≥ 0.12.16), RcppEigen (≥ <IP_ADDRESS>.0) |
| Suggests: | knitr, testthat |
| Published: | 2018-11-20 |
| Author: | Charles Driver [aut, cre, cph], Manuel Voelkle [aut, cph], Han Oud [aut, cph] |
| Maintainer: | Charles Driver <driver at mpib-berlin.mpg.de> |
| License: | GPL-3 |
| URL: | https://github.com/cdriveraus/ctsem |
| NeedsCompilation: | yes |
| SystemRequirements: | GNU make |
| Citation: | ctsem citation info |
| Materials: | README NEWS |
| In views: | Psychometrics |
| CRAN checks: | ctsem results |
| Reference manual: | ctsem.pdf |
| Vignettes: |
Continuous time structural equation modelling with ctsem Introduction to Hierarchical Continuous Time Dynamic Modelling with ctsem |
| Package source: | ctsem_2.7.6.tar.gz |
| Windows binaries: | r-devel: ctsem_2.7.6.zip, r-release: ctsem_2.7.6.zip, r-oldrel: ctsem_2.7.6.zip |
| OS X binaries: | r-release: ctsem_2.7.6.tgz, r-oldrel: ctsem_2.7.6.tgz |
| Old sources: | ctsem archive |
Please use the canonical form https://CRAN.R-project.org/package=ctsem to link to this page.


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