class: center, middle, inverse, title-slide # An introduction to economic geography ## EK Ricardian models and hat algebra ### Ivan Rudik ### Cornell Dyson --- exclude: true ```r options(htmltools.dir.version = FALSE) knitr::opts_hooks$set(fig.callout = function(options) { if (options$fig.callout) { options$echo <- FALSE } knitr::opts_chunk$set(echo = TRUE, fig.align="", message = FALSE, warning = FALSE) options }) ``` --- # Roadmap 1. The economics of space 2. A simple Eaton Kortum Model 3. Exact hat algebra to solve counterfactuals --- # The economics of space Capturing space is hard for similar reasons as to why capturing time is hard: lots of states / interactions -- Historically, very little serious treatment of space -- .hi-blue["Spatial Impossibility Theorems"] tell us that there's no competitive equilibrium outcome with transport of goods and positive transport costs if space is homogeneous (utilities and production technologies are the same) - Factor mobility perfectly substitutes for trade, never incur the trade cost --- # Spatial models With spatial models we are now going to allow for: - heterogeneity across space - trade + frictions - migration + frictions - agglomeration economies - dispersion forces (congestion) Basically, more consideration of general equilibrium effects --- # Spatial models These new approaches generally are considered a part of .hi[economic geography:] the explicit consideration of space -- Exogenous location-specific characteristics matter -- Endogenous agglomeration and dispersion forces matter -- Increasingly important in trade and urban, lots of conceptual/methodological parallels to IO but with a GE twist -- Often combines granular data (census blocks, households, cell-level) with a theoretical equilibrium model to simulate counterfactuals --- # Spatial models: macro-ish These features allow us to better understand the impacts of things like: - the costs of sea level rise (Desmet et al. 2021) - climate change and the food problem (Nath 2021) - climate and agricultural adaptation (Costinot, Donaldson, Smith 2016) - the geography of environmental regulation (Hollingsworth, Jaworski, Kitchens, and Rudik, 2021) - the climate adaptation value of migration (Cruz and Rossi-Hansberg 2021) --- # Spatial models: micro These features better allow us to understand the impacts of things like: - the social value of public transit (Severen 2021) - amenity endogeneity (Almagro and Dominguez-Ilno, 2021) - the value of density in Berlin (Ahlfeldt et al. 2015) - the impact of Amazon HQ2 (Dingel and Tintelnot 2021) --- # Simple set up: a model of market access We're going to start off with a simple .hi[market access] / .hi-blue[gravity] model -- The model and code are derived from Donaldson and Hornbeck (2016) -- It is a version of the widely-used Eaton and Kortum (2002) Ricardian model <!-- -- --> <!-- Standard trade models are all isomorphic: same aggregate outcomes despite different microfoundations --> <!-- - EK --> <!-- - Melitz --> <!-- - Armington --> <!-- - Krugman --> --- # Simple set up: a model of market access Here's what we are going to do: 1. Develop the static model 2. Show how to use .blue[exact hat algebra] to simulate counterfactuals without data on time-invariant exogenous variables (Dekle et al. 2008) - Tomorrow's paper uses .blue[dynamic hat algebra] (Caliendo et al. 2019) -- .hi[New computational piece here:] we will be solving for things up to a .blue[normalization], we won't necessarily be able to get the levels of all variables --- # Households `\(L_i\)` households are in location `\(i = 1,\dots,N\)` -- Households supply labor inelastically, and are perfectly mobile across locations (easy to relax) -- Household utility is `$$U(C_i) = C_i$$` --- # Households Household utility is `$$U(C_i) = C_i$$` -- Each industry produces a continuum of varieties `\(\omega \in [0,N]\)` (important for the production side) such that `\(C_i\)` is a .pink[constant elasticity of substitution] aggregate of the varieties with elasticity `\(\sigma\)` -- With the CES assumption, we have the .pink[price index] in location `\(i\)` is: `$$P_i = \left(\int_0^N P(\omega)^{1-\sigma}d\omega \right)^{\frac{1}{1-\sigma}}$$` --- # Households: equilibrium utility and wages The consumer's indirect utility is given by their .pink[real wage:] `$$V_{i} = \frac{w_{i}}{P_{i}}$$` .hi[In equilibrium what must be true about the spatial distribution of V?] -- Indirect utility is equalized across locations `\(\dots\)` Why? -- With perfectly mobile labor, indirect utility is equalized in equilibrium and wages `\(w_i\)` satisfy: `$$w_i = \bar{U} P_i$$` --- # Firms Firms maximize profits and take prices as given -- For each location, `\(z_{i}(\omega)\)` is .hi[efficiency] -- This is the quantity of variety `\(\omega\)` that can be produced using one unit of labor and capital in location `\(i\)` --- # Firms: EK assumption We assume that `\(z_{i}(\omega)\)` is a random variable distributed according to the Frechet distribution (Eaton and Kortum, 2002): `$$F_{i}\left(z\right) = \exp\left[-T_{i} \left(z\right)^{-\theta}\right]$$` -- This distributional assumption is what will buy us tractability in our model later --- # Firms: EK assumption `$$F_{i}\left(z\right) = \exp\left[-T_{i} \left(z\right)^{-\theta}\right]$$` -- `\(\theta > 1\)` is the trade elasticity parameter common across all locations and measures the level of intra-industry heterogeneity -- Smaller `\(\theta\)` `\(\rightarrow\)` more dispersion `\(\rightarrow\)` more heterogeneity `\(\rightarrow\)` stronger .blue[comparative advantage] effects -- `\(T_{i}\)` measures fundamental productivity -- Larger values of `\(T_{i}\)` shifts the distribution to the right and corresponds to larger .blue[absolute advantage] --- # Firms: Production technology Perfectly competitive firms use labor, capital, and .pink[Cobb-Douglas] technologies to produce different varieties of goods -- Total output in location `\(i\)` is given by `\(Y_i = z_i(\omega) L_i^\gamma K_i^{1-\gamma}\)` -- `\(\gamma\)` is the labor share and `\(r_i\)` is the rental rate of capital -- Capital is perfectly mobile so `\(r_i = r\)` for all `\(i\)` -- The input cost of producing variety `\(\omega\)` in location `\(i\)` is: `$$c_i = {(w_i)}^\gamma {(r)}^{1-\gamma}$$` --- # Firms: Trade and prices Trade costs are .pink[iceberg] -- Delivering 1 unit of the good from `\(j\)` to `\(i\)` requires shipping `\(\tau_{ij} \geq 1\)` units where `\(\tau_{ii} = 1\)`, this represents the costs of shipping/trade -- The price of a good from `\(j\)` in `\(i\)` is then: `$$P_{ij}(\omega) = \frac{1}{z_i(\omega)}c_i \tau_{ij} = \frac{1}{z_i(\omega)}{(w_i)}^\gamma {(r)}^{1-\gamma} \tau_{ij}$$` -- Buyers purchase from the lowest-cost provider so the price in `\(i\)` is: `$$P_i(\omega) = \min_{j}\left\{P_{ij}(\omega), j=1,\dots,N \right\}$$` --- # Firms: Trade and prices `\(P_{ij}(\omega)\)` and the Frechet assumption on `\(z\)` give us a distribution of prices faced by `\(i\)` from `\(j\)` sellers `\(G_{ij}(p)\)`: `$$Pr[P_{ij} \leq p] \equiv G_{ij}(p) = 1 - F_{j}\left(\frac{1}{p}{(w_i)}^\gamma {(r)}^{1-\gamma} \tau_{ij}\right)$$` -- The lowest price for a variety in `\(i\)` takes on the minimum across all countries `\(j\)` giving us the distribution for prices in `\(i\)` of varieties that `\(i\)` actually buys `\(G_n(p)\)`: `$$Pr[P_i \leq p] \equiv G_i(p) = 1 - \prod_{j=1}^N [1- G_{ij}(p)]$$` --- # Firms: Trade and prices We then get our final expression for the distribution of prices in `\(i\)`: `$$G_i(p) = 1 - \exp(-\Phi_i p^\theta) \quad \text{where} \quad \Phi_i = \sum_{j=1}^N T_j (c_j \tau_{ij})^{-\theta}$$` -- `\(\Phi_i\)` summarizes how prices in `\(i\)` are governed by: - Fundamental productivity in all `\(j\)` - Input costs in all `\(j\)` - Trade barriers with all `\(j\)` -- What does the distribution look like in autarky or with frictionless trade? --- # Firms: Prices Two key properties of `\(G_i(p)\)`: 1. The probability that `\(j\)` is the lowest-cost seller in `\(i\)` is: `$$\pi_{ij} = \frac{T_j (c_j \tau_{ij})^{-\theta}}{\sum_{h=1}^N T_h (c_h \tau_{ih})^{-\theta}} \qquad \approx \text{ logit shares}$$` -- <!-- 2. Prices are independent of sources: sellers adjust on the extensive margin by selling more or fewer goods --> <!-- -- --> 2. The ideal price index in `\(i\)` is `\((\sigma < 1+ \theta)\)`: `$$P_i = \gamma \Phi_i^{-1/\theta}$$` --- # Firms: Prices With a bit of math we can solve for the .pink[ideal price index] as a function of input costs and parameters: `$$P_{i} = \kappa \left(\sum_{n=1}^N T_{n} \left[{(w_n)}^\gamma \tau_{in} \right]^{-\theta} \right)^{-1/\theta}$$` which is the cost of 1 unit of utility in location `\(i\)`, `\(\kappa\)` is a constant --- # Firms: Trade `$$P_{i} = \kappa \left(\sum_{n=1}^N T_{n} \left[{(w_n)}^\gamma \tau_{in} \right]^{-\theta} \right)^{-1/\theta}$$` Notice `\(P_i\)` is increasing in sellers' trade costs `\(\tau_{in}\)` and input costs `\(w_n\)`, and decreasing in productivity `\(T_n\)` -- `\({(P_{i})}^{-\theta}\)` is often called consumer market access `\((CMA_i)\)` and captures location `\(i\)`'s access to cheaper products --- # Firms: Trade Next, define a new variable, .pink[expenditure shares:] the share of `\(i\)`s total expenditures on products from location `\(j\)`: `\(\lambda_{ij}\)` -- Expenditure shares `\(\equiv\)` probability of being the lowest-cost seller: `$$\lambda_{ij} = \frac{T_{j} \left( {(w_j)}^\gamma \tau_{ij}\right)^{-\theta}}{\sum_{h=1}^N T_{h} \left( {(w_h)}^\gamma \tau_{ih}\right)^{-\theta}}$$` --- # Firms: Trade .hi[Bilateral trade expenditures] of location `\(i\)` on goods from location `\(j\)` are `\(X_{ij}\)` where: `$$\lambda_{ij} = \frac{X_{ij}}{\sum_{h=1}^N X_{ih}} = \frac{X_{ij}}{X_{i}}$$` -- and we can show that: `$$X_{ij} = \kappa T_{j} Y_i\left(\frac{ {(w_j)}^\gamma \tau_{ij}}{{P_{i}}}\right)^{-\theta}$$` `\(i\)` purchases more products from `\(j\)` if the costs of products from `\(j\)` are lower, `\(i\)` is richer, `\(j\)` is more productive --- # Exact hat algebra How do we solve this model? Suppose we want to know the effect of a change in productivity `\(\hat{T_j} = \frac{T^c_j}{T_j}\)` -- Hats denote changes in a variable from factual to counterfactual -- It turns out it's relatively easy to solve these models in terms of .hi[changes] -- Representing the model in changes is nice because it will difference out time-invariant variables -- In this simple model trade costs are the time-invariant variable --- # Exact hat algebra First, labor income `\(w_i L_i = \gamma Y_i\)` can be written as a function of the sum of expenditures by `\(j\)` on products from `\(i\)` `$$w_i L_i = \gamma \sum_{j=1}^N \lambda_{ji} w_j L_j$$` -- RHS is spending by all locations `\(j\)` on `\(i\)`s products --- # Exact hat algebra `$$\lambda_{ij} = \frac{T_{j} \left( {(w_j)}^\gamma \tau_{ij}\right)^{-\theta}}{\sum_{h=1}^N T_{h} \left( {(w_h)}^\gamma \tau_{ih}\right)^{-\theta}}$$` `$$w_i L_i = \gamma \sum_{j=1}^N \lambda_{ji} w_j L_j$$` Suppose we have a productivity shock `\(\hat{T}_j\)`, and that `\(\hat{\tau}_{ij} = \hat{L} = 1\)` -- What we are going to do is manipulate these two expressions into .pink[hat form] --- # Exact hat algebra Let's start with the counterfactual labor market clearing condition: `$$w^c_i L^c_i = \gamma \sum_{j=1}^N \lambda^c_{ji} w^c_j L^c_j$$` -- `\(\lambda^c_{ji} w^c_j L^c_j\)` is just how much `\(j\)` spends on products from `\(i\)` so that: `$$w^c_i L^c_i = \gamma \sum_{j=1}^N X^c_{ji}$$` --- # Exact hat algebra Next let's put labor income into hat form: -- `$$\hat{w}_i \hat{L}_i = \frac{w^c_i L^c_i}{w_i L_i} = \gamma \sum_{j=1}^N \frac{X^c_{ji}}{w_i L_i} = \gamma \sum_{j=1}^N \frac{X^c_{ji}}{w_i L_i}\frac{X_{ji}}{X_{ji}} = \gamma \sum_{j=1}^N \frac{X_{ji}}{w_i L_i} \hat{X}_{ji}$$` The change in income due to `\(\hat{T}_j\)` is given by the change in bilateral expenditures, as well as the .pink[factual/observed] income and bilateral expenditures which are just data --- # Exact hat algebra Now let's look at the counterfactual expenditure shares: `$$\lambda^c_{ij} = \frac{T^c_{j} \left( {(w^c_j)}^\gamma \tau_{ij}\right)^{-\theta}}{\sum_{h=1}^N T^c_{h} \left( {(w^c_h)}^\gamma \tau_{ih}\right)^{-\theta}}$$` And remember that trade costs .hi[do not] change in this example -- Next, put it in hat form --- # Exact hat algebra `$$\hat{\lambda}_{ij} = \frac{\lambda^c_{ij}}{\lambda_{ij}} = \frac{\frac{T^c_{j} \left( {(w^c_j)}^\gamma \tau_{ij}\right)^{-\theta}}{T_{j} \left( {(w_j)}^\gamma \tau_{ij}\right)^{-\theta}}}{\frac{\sum_{h=1}^N T^c_{h} \left( {(w^c_h)}^\gamma \tau_{ih}\right)^{-\theta}}{\sum_{h=1}^N T_{h} \left( {(w_h)}^\gamma \tau_{ih}\right)^{-\theta}}} = \frac{\hat{T}_{j} \left( {(\hat{w}_j)}^\gamma\right)^{-\theta}}{\frac{\sum_{h=1}^N T^c_{h} \left( {(w^c_h)}^\gamma \tau_{ih}\right)^{-\theta}}{\sum_{h=1}^N T_{h} \left( {(w_h)}^\gamma \tau_{ih}\right)^{-\theta}}} = \frac{\hat{T}_{j} \left( {(\hat{w}_j)}^\gamma\right)^{-\theta}}{\hat{P_i}^{-\theta}}$$` The change in expenditure shares is given by the changes in productivity, wages, and prices -- We still need to solve for `\(\hat{P}^{-\theta}_i\)` --- # Exact hat algebra We can do so with the price index expression: `$$P_{i} = \kappa \left(\sum_{j=1}^N T_{j} \left[{(w_j)}^\gamma \tau_{ij} \right]^{-\theta} \right)^{-1/\theta}$$` Which gives us: `$$\hat{P}_{i}^{-\theta} = \frac{\left(\sum_{j=1}^N T^c_{j} \left[{(w^c_j)}^\gamma \tau_{ij} \right]^{-\theta} \right)}{\left(\sum_{h=1}^N T_{h} \left[{(w_h)}^\gamma \tau_{ih} \right]^{-\theta} \right)}$$` --- # Exact hat algebra Next we make a few (potentially odd) substitutions -- Since `\(j\)` is not in the denominator, we can treat the denominator as a constant and move it inside the sum over `\(j\)`: `$$\hat{P}_{i}^{-\theta} = \sum_{j=1}^N \frac{\left(T^c_{j} \left[{(w^c_j)}^\gamma \tau_{ij} \right]^{-\theta} \right)}{\left(\sum_{h=1}^N T_{h} \left[{(w_h)}^\gamma \tau_{ih} \right]^{-\theta} \right)}$$` --- # Exact hat algebra Next., multiply and divide each term in the sum by the .pink[factual] productivity and wage terms in order to start working toward hat expressions: `$$\hat{P}_{i}^{-\theta} = \sum_{j=1}^N \left[\frac{\left(T^c_{j} \left[{(w^c_j)}^\gamma \tau_{ij} \right]^{-\theta} \right)}{\left(\sum_{h=1}^N T_{h} \left[{(w_h)}^\gamma \tau_{ih} \right]^{-\theta} \right)} \frac{T_j \left[w_j^\gamma\right]^{-\theta}}{T_j \left[w^\gamma_j\right]^{-\theta}} \right]$$` --- # Exact hat algebra We can then switch out the factual and counterfactual terms up top: `$$\hat{P}_{i}^{-\theta} = \sum_{j=1}^N \left[\frac{\left(T_{j} \left[{(w_j)}^\gamma \tau_{ij} \right]^{-\theta} \right)}{\left(\sum_{h=1}^N T_{h} \left[{(w_h)}^\gamma \tau_{ih} \right]^{-\theta} \right)} \frac{T^c_j \left[{(w^c_j})^\gamma\right]^{-\theta}}{T_j \left[w^\gamma_j\right]^{-\theta}} \right]$$` and this gives us: `$$\hat{P}_{i}^{-\theta} = \sum_{j=1}^N \left[\lambda_{ij} \hat{T}_j \left(\hat{w}_j^\gamma\right)^{-\theta} \right]$$` The change in prices is just data and other hat variables --- # Exact hat algebra Here's the three sets of equations again, they are all in terms of changes or data, so we do not need to solve for model fundamentals: `$$\hat{w}_i \hat{L}_i = \gamma \sum_{j=1}^N \frac{X_{ji}}{w_i L_i} \hat{X}_{ji}$$` `$$\hat{\lambda}_{ij} = \frac{\hat{T}_{j} \left( {(\hat{w}_j)}^\gamma\right)^{-\theta}}{\hat{P_i}^{-\theta}}$$` `$$\hat{P}_{i}^{-\theta} = \sum_{j=1}^N \left[\lambda_{ij} \hat{T}_j \left(\hat{w}_j^\gamma\right)^{-\theta} \right]$$` --- # Exact hat algebra Given `\(\hat{T}_i\)` we need to identify `\(\hat{w}_i, \hat{L}_i, \hat{P}_{i}, \hat{\lambda}_{ij}\)` -- This is `\(3N+N^2\)` variables, the previous set of 3 equations is only `\(2N+N^2\)` -- Need another `\(N\)` equations to identify the change in equilibrium -- These `\(N\)` equations are: `$$\frac{\hat{w_i}}{\hat{P}_i} = \frac{\hat{w_j}}{\hat{P}_j} = \widehat{\bar{U}} \,\,\, \forall i,j$$` and `$$\hat{L} = 1$$` --- # Exact hat algebra `$$\hat{P}_{i}^{-\theta} = \sum_{j=1}^N \left[\lambda_{ij} \hat{T}_j \left(\hat{w}_j^\gamma\right)^{-\theta} \right]$$` along with the change in equilibrium requirement that: `$$\frac{\hat{w_i}}{\hat{P}_i} = \widehat{\bar{U}} \,\,\, \forall i$$` allows us to iterate and solve for `\(\hat{w}_i\)` up to a normalization --- # Exact hat algebra `$$\hat{\lambda}_{ij} = \frac{\hat{T}_{j} \left( {(\hat{w}_j)}^\gamma\right)^{-\theta}}{\hat{P_i}^{-\theta}}$$` then lets us solve for `\(\hat{\lambda}_{ij}\)` given `\(\hat{P}_i\)` and `\(\hat{w}_j\)` -- Last we need expenditures and labor using the first condition: `$$\hat{w}_i \hat{L}_i = \gamma \sum_{j=1}^N \frac{X_{ji}}{w_i L_i} \hat{X}_{ji}$$` --- # Exact hat algebra `$$\hat{w}_i \hat{L}_i = \gamma \sum_{j=1}^N \frac{X_{ji}}{w_i L_i} \hat{X}_{ji}$$` Expenditures by `\(i\)` `\(X_i\)` will be equal to labor income so we have that: `$$\hat{X}_i = \gamma \sum_{j=1}^N \frac{X_{ji}}{w_i L_i} \hat{X}_{ji}$$` -- The definition of expenditure shares gives us: `$$\hat{\lambda}_{ij} = \frac{\hat{X}_{ij}}{\hat{X}_i}$$` --- # Exact hat algebra Combine these two to get: `$$\frac{\hat{X}_{ih}}{\hat{\lambda}_{ih}} = \gamma \sum_{j=1}^N \frac{X_{ji}}{w_i L_i} \hat{X}_{ji}$$` which is a set of `\(n\)` equations and `\(n\)` unknown `\(\hat{X}_{ji}\)` for any `\(h\)` we choose -- We have solved for all the unobserved hat terms given some change in productivity `\(\hat{T}_i\)` -- With these we can simulate any change in productivity, and the only two model parameters we needed to take a stand on were `\(\gamma\)` and `\(\theta\)`


@main("You're all set") {
That's it! You should now see a folder "Dropbox/Apps/Webhooks-Java".
Dropbox/Apps/Webhooks-Java
Put Markdown files (with the extension .md) in that folder and watch them get converted!
.md


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OCILIB (C and C++ Driver for Oracle)
4.5.1
|
OCILIB supports local and global transactions.
Local transactions are implicit within connection objects and there is no specific call or programming step for using it.
In order to control changes made in the database:
OCILIB supports a feature called 'Auto Commit' that performs an implicit and automatic commit call after every execute call
OCILIB supports them by :
Functions | |
| OCI_EXPORT boolean OCI_API | OCI_Commit (OCI_Connection *con) |
| Commit current pending changes. More... | |
| OCI_EXPORT boolean OCI_API | OCI_Rollback (OCI_Connection *con) |
| Cancel current pending changes.  More... | |
| OCI_EXPORT OCI_Transaction *OCI_API | OCI_TransactionCreate (OCI_Connection *con, unsigned int timeout, unsigned int mode, OCI_XID *pxid) |
| Create a new global transaction or a serializable/read-only local transaction. More... | |
| OCI_EXPORT boolean OCI_API | OCI_TransactionFree (OCI_Transaction *trans) |
| Free current transaction. More... | |
| OCI_EXPORT boolean OCI_API | OCI_TransactionStart (OCI_Transaction *trans) |
| Start global transaction. More... | |
| OCI_EXPORT boolean OCI_API | OCI_TransactionStop (OCI_Transaction *trans) |
| Stop current global transaction. More... | |
| OCI_EXPORT boolean OCI_API | OCI_TransactionResume (OCI_Transaction *trans) |
| Resume a stopped global transaction. More... | |
| OCI_EXPORT boolean OCI_API | OCI_TransactionPrepare (OCI_Transaction *trans) |
| Prepare a global transaction validation. More... | |
| OCI_EXPORT boolean OCI_API | OCI_TransactionForget (OCI_Transaction *trans) |
| Cancel the prepared global transaction validation. More... | |
| OCI_EXPORT unsigned int OCI_API | OCI_TransactionGetMode (OCI_Transaction *trans) |
| Return global transaction mode. More... | |
| OCI_EXPORT unsigned int OCI_API | OCI_TransactionGetTimeout (OCI_Transaction *trans) |
| Return global transaction Timeout. More... | |
| OCI_EXPORT boolean OCI_API OCI_Commit | ( | OCI_Connection * | con | ) |
#include <ocilib.h>
Commit current pending changes.
| con | - Connection handle |
Referenced by ocilib::Connection::Commit().
| OCI_EXPORT boolean OCI_API OCI_Rollback | ( | OCI_Connection * | con | ) |
#include <ocilib.h>
Cancel current pending changes.
| con | - Connection handle |
Referenced by ocilib::Connection::Rollback().
| OCI_EXPORT boolean OCI_API OCI_SetAutoCommit | ( | OCI_Connection * | con, |
| boolean | enable | ||
| ) |
#include <ocilib.h>
Enable / disable auto commit mode.
The auto commit mode allows commit changes after every executed SQL order
| con | - Connection handle |
| enable | - Enable (TRUE) or disable (FALSE) |
Referenced by ocilib::Connection::SetAutoCommit().
| OCI_EXPORT boolean OCI_API OCI_GetAutoCommit | ( | OCI_Connection * | con | ) |
#include <ocilib.h>
Get current auto commit mode status.
| con | - Connection handle |
Referenced by ocilib::Connection::GetAutoCommit().
| OCI_EXPORT OCI_Transaction* OCI_API OCI_TransactionCreate | ( | OCI_Connection * | con, |
| unsigned int | timeout, | ||
| unsigned int | mode, | ||
| OCI_XID * | pxid | ||
| ) |
#include <ocilib.h>
Create a new global transaction or a serializable/read-only local transaction.
| con | - Connection handle |
| timeout | - Time that a transaction stays inactive after being stopped |
| mode | - Transaction mode |
| pxid | - pointer to a global transaction identifier structure |
Referenced by ocilib::Transaction::Transaction().
| OCI_EXPORT boolean OCI_API OCI_TransactionFree | ( | OCI_Transaction * | trans | ) |
#include <ocilib.h>
Free current transaction.
| trans | - Connection handle |
Referenced by ocilib::Transaction::Transaction().
| OCI_EXPORT boolean OCI_API OCI_TransactionStart | ( | OCI_Transaction * | trans | ) |
#include <ocilib.h>
Start global transaction.
| trans | - Connection handle |
Referenced by ocilib::Transaction::Start().
| OCI_EXPORT boolean OCI_API OCI_TransactionStop | ( | OCI_Transaction * | trans | ) |
#include <ocilib.h>
Stop current global transaction.
| trans | - Connection handle |
Referenced by ocilib::Transaction::Stop().
| OCI_EXPORT boolean OCI_API OCI_TransactionResume | ( | OCI_Transaction * | trans | ) |
#include <ocilib.h>
Resume a stopped global transaction.
| trans | - Global transaction handle |
Referenced by ocilib::Transaction::Resume().
| OCI_EXPORT boolean OCI_API OCI_TransactionPrepare | ( | OCI_Transaction * | trans | ) |
#include <ocilib.h>
Prepare a global transaction validation.
| trans | - Global transaction handle |
Referenced by ocilib::Transaction::Prepare().
| OCI_EXPORT boolean OCI_API OCI_TransactionForget | ( | OCI_Transaction * | trans | ) |
#include <ocilib.h>
Cancel the prepared global transaction validation.
| trans | - Global transaction handle |
Referenced by ocilib::Transaction::Forget().
| OCI_EXPORT unsigned int OCI_API OCI_TransactionGetMode | ( | OCI_Transaction * | trans | ) |
#include <ocilib.h>
Return global transaction mode.
| trans | - Global transaction handle |
Referenced by ocilib::Transaction::GetFlags().
| OCI_EXPORT unsigned int OCI_API OCI_TransactionGetTimeout | ( | OCI_Transaction * | trans | ) |
#include <ocilib.h>
Return global transaction Timeout.
| trans | - Global transaction handle |
Referenced by ocilib::Transaction::GetTimeout().


Engineering Java 7’s Dual-Pivot Quicksort Using MaLiJAn
Based on the analysis of instruction counts (see details in my master’s thesis) one should expect that asymmetric pivot sampling improves YBB Quicksort. In this paper we empirically investigate this hypothesis in Java.
In fact, Vladimir Yaroslavskiy made the observation that asymmetry might help already in 2010, when he experimented with YBB Quicksort. In this mailing list post he asked for explanations why from 5 sample elements, exactly the smallest and third smallest elements perform best, and in particular better than the tertiles (second and forth smallest).
Dmytro Sheyko’s answer goes in the right direction: asymmetries in the partitioning algorithm may lead to improvements with asymmetric pivots. The details of his explanation are not correct because of simplifying assumptions; he closes with:
Of course, these consideration does not apply to the real DPQ completely. This is because in real DPQ every item is not compared with pivots in well defined order and real DPQ contains numerous special cases, which make it harder to analyze.
Still, we could finally give this analysis: [conference paper] / [full paper].
While we can confirm savings in the number of executed Java Bytecode instructions, running times show a peculiar pattern:
There seem to be two types of inputs, where running time is either in the lower (faster) part or in the upper (slower) part, depending on the class of the input. We investigate this phenomenon in detail and trace it to Java’s just-in-time (JIT) compiler.
With regard to the initial hypothesis, we have to conclude that any potential speedup is dwarfed by these JITter effects.
MaLiJAn
For the experiments we used our self-made tool MaLiJAn, the Maximum Likelihood Java Analyzer (I know, great name).
It decomposes a given Java program into its control-flow graph and injects counting instructions at the beginning of each basic block (i.e. each node in that graph). From these basic-block execution counters determined on given data, MaLiJAn tries to extrapolate behavior for any input size. That step has to remain a heuristic, of course, but for many typical algorithms and inputs we tried, it worked quite reasonably.
Finally, MaLiJAn computes expected costs from these extrapolations, based on user-specified cost measures, which assign a constant cost contribution to each execution of a basic block.
The theoretical basis of MaLiJAn is described in this article; it is also sketched in the appendix of this paper, where we extend MaLiJAn to approximate average running times for executing a single basic block.
Relation to Other Papers
We could confirm some of the empirical findings of this paper analytically.


Coding Standards
These standards for code formatting and documentation must be followed by anyone contributing to Fuel. Any contributions that do not meet these guidelines will not be accepted.
File Formatting
Closing PHP Tag
Files containing only PHP code should always omit the closing PHP tag (?>). This prevents many of the elusive white screens of death.
Indentation
All indentation should be done using real tabs, NOT spaces.
Line Endings
Line endings should be Unix-style LF.
File Naming
All file names must be all lower case. No exceptions.
Encoding
Files should be saved with UTF-8 encoding and the BOM should not be used.
Naming Conventions
Namespaces
All core classes must be under the Fuel namespace. You can use sub-namespaces, but they must fall under the Fuel namespace:
namespace Fuel;
namespace Fuel\Controller;
namespace Fuel\Session;
If for some reason you need to include multiple namespaces in the same file, you must use curly braces around the entire namespace. However, we strongly discourage this, and it should not be used.
namespace Fuel
{
class Foo {
// Code here
}
}
namespace Fuel\Bar
{
class Hello {
// Code here
}
}
Classes
Class names must underscores to separate words. You should never use CamelCase (except in very rare cases). Each word in the class name should begin with a capital letter.
The underscores in the class names will be replaced by a directory separator during autoloading and that used as the file path. Here is an example:
namespace Fuel;
// ------------------------------------------------------------------------
class Session {
}
namespace Fuel;
// ------------------------------------------------------------------------
class Session_Cookie extends Session_Driver {
}
This would result in the following file path:
core/classes/fuel/session.php
core/classes/fuel/session/cookie.php
Methods
Like class names, method names should use underscores to separate words, not CamelCase. Method names should also be all lower case. Protected and private methods should be prefixed with an underscore to enhance code readability.
class Session {
public static function get_flash($name, $data)
{
// Some code here
}
}
class View {
// Array of global view data
protected static $_global_data = array();
protected static function capture($view_filename, array $view_data)
{
// Some code here
}
}
Variables
Variable names should be concise, and contain only lower case letters and underscores. Loop iterators should be short, preferably a single character.
$first_name
$buffer
for ($i = 0; $i < $max; $i++)
Constants
Constants follow the same guide lines as variables, with the exception that constants should be all upper case.
MY_CONSTANT
TEMPLATE_PATH
TEXT_DEFAULT
Keywords
Keywords such as true, false, null, as, etc should be all lower case, as upper case is reserved for constants.
$var = true;
$var = false;
$var = null;
foreach ($array as $key => $value)
public function my_function(array $array)
function my_function($arg = null)
Control Structures
The structure keywords such as if, for, foreach, while, switch should be followed by a space as should parameter/argument lists and values. Braces should be placed on a new line, and break should have the same tab as its case.
if ($arg === true)
{
//do something here
}
elseif ($arg === null)
{
//do something else here
}
else
{
//catch all do something here
}
foreach ($array as $key => $value)
{
//loop here
}
for ($i = 0; $i < $max; $i++)
{
//loop here
}
while ($i < $max)
{
//loop here
}
switch ($var)
{
case 'value1':
//do something here
break;
default :
//do something here
break;
}
Comparisons, Logical operators
Comparing function/method returns and variables should be type aware, for example some functions may return false, and when comparing this return the type sensitive operators such as === or !==. Additionally, use of and or or is preferred over && or || for readability. In some cases this cannot be avoided and the use of && or || as its required may be used.
if ($var === false and $other_var == 'some_value')
if ($var === false or false === my_function())
White Space
Indentation
Tab (not soft tabs) indentation is required.
Class/Interface Declarations
Class/interface declarations have the opening brace on the same line:
class Session {
}
Function/Method Declarations
The function/method opening brace must always begin on a new line and have the same indentation as its structure.
class Session {
public static function get_flash($name, $data)
{
// Some code here
}
}
Variables
When initializing variables do not do them on a single line. To enhance code readability these should each be on a separate line.
$var = ''; //do each on its own line
$other_var = ''; //do each on its own line
Brackets and Parenthesis
No space should come before or after the initial bracket/parenthesis. There should not be a space before closing bracket/parenthesis.
$array = array(1, 2, 3, 4);
$array['my_index'] = 'something';
for ($i = 0; $i < $max; $i++)
Concatenation
String concatenation should not contain spaces around the joined parts
//yes
$string = 'my string '.$var.' the rest of my string';
//no
$string = 'my string ' . $var . ' the rest of my string';
Operators
$var = 'something';
if ($var == 'something') //space before and after operator
$var++; // no space before
++$var; //no space after
$var = $some_var + $other_var; //space before and after operator


[gecode-users] Advisor on a ViewArray and index of assigned variable
Christian Schulte
cschulte at kth.se
Tue Nov 10 21:03:24 CET 2015
Hi,
No, this is not at all feasible as I tried to explain: the view has (and hence the advisor) has no idea that the view is stored in a view array. Think of it as follows: the view might be stored in different arrays by different propagators. So how could the view and hence the advisor know which array we talk about?
Cheers
Christian
--
Christian Schulte, <http://www.gecode.org/~schulte> www.gecode.org/~schulte
Professor of Computer Science, KTH, <mailto:cschulte at kth.se> cschulte at kth.se
Expert Researcher, SICS, <mailto:cschulte at sics.se> cschulte at sics.se
From: users-bounces at gecode.org [mailto:users-bounces at gecode.org] On Behalf Of Valentin Lemière
Sent: Tuesday, November 10, 2015 05:20 PM
To: cschulte at kth.se
Cc: users at gecode.org
Subject: Re: [gecode-users] Advisor on a ViewArray and index of assigned variable
Hi,
I see, thanks for your answer.
When an Advisor is used on a BoolView it stores the type of assignment in the delta, which can be accessed with BoolView::one and ::zero.
But couldn't an Advisor, when applied to a ViewArray, store the index in the delta and then access it with ViewArray::index?
With the index I can get the assigned value but not the other way around.
It's not the case right now I understand, but do you think this is something feasible?
Regards,
Valentin
_____
De: "Christian Schulte" <cschulte at kth.se <mailto:cschulte at kth.se> >
À: "Valentin Lemière" <valentin.lemiere at unicaen.fr <mailto:valentin.lemiere at unicaen.fr> >, users at gecode.org <mailto:users at gecode.org>
Envoyé: Lundi 9 Novembre 2015 20:20:51
Objet: RE: [gecode-users] Advisor on a ViewArray and index of assigned variable
Hi,
An advisor subscribes to a particular variable implementation through a view hence, the only information that is available by default is which advisor is executed and what is the delta.
Additional information – such as the position of an advisor in a view array – must be explicitly stored in the advisor, there is no way around it.
Cheers
Christian
--
Christian Schulte, <http://www.gecode.org/~schulte> www.gecode.org/~schulte
Professor of Computer Science, KTH, <mailto:cschulte at kth.se> cschulte at kth.se
Expert Researcher, SICS, <mailto:cschulte at sics.se> cschulte at sics.se
From: users-bounces at gecode.org <mailto:users-bounces at gecode.org> [mailto:users-bounces at gecode.org] On Behalf Of Valentin Lemière
Sent: Monday, November 9, 2015 04:56 PM
To: users at gecode.org <mailto:users at gecode.org>
Subject: [gecode-users] Advisor on a ViewArray and index of assigned variable
Hello everyone,
I am a PhD. student and I am currently looking at Gecode to see if it'll fit my needs.
I need to implement a global constraint on a large number of boolean variables. So I have extended from NaryPropagator with a view of type BoolView.
When a variable is assigned, the propagator infers some knowledge and may assign other variable(s).
To get the required information, I added an Advisor to each variable, storing its index; so I can get it in the advise method and provide it to the propagator.
But this technique is too slow and creates too much advisors.
So I tried adding an Advisor directly to the ViewArray; the advise function is correctly called and I can still get whether the variable was assigned a zero or a one with the delta.
But I don't get the index information to find the actual assigned variable.
I looked for a static method of ViewArray to convert the delta to this information but couldn't find one.
Can an Advisor on a ViewArray get the index of the assigned variable?
Or is there another way to deal with a large number of variables other than an Advisor per variable?
Regards,
Valentin
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generate random id based on template string. Default template string is 'xxxxxxxx-xxxx-1xxx-1xxx-xxxxxxxxxxxx'.
Template rules very simple:
base - it's a string for creating id. Rewrite only special characters
N - Rewrite to random Number
H - Rewrite to random hex numder
S - Rewrite to random english symbol
X - Rewrite to any from "N","H","S"
(String?)
:
[
default: 'XXXXXXXX-XXXX-1XXX-1XXX-XXXXXXXXXXXX'
]
String
:
uid();
uid('XXX-4NNN-dummy-SSS');
Humanized time string. This method is very sensitive to the correctness of the input arguments
String
:
uid._time('-', new Date() );
Humanized date string. This method is very sensitive to the correctness of the input arguments
String
:
uid._date('-', new Date() );
Humanized date+time string. Safe method.
(Date?)
:
[
default: new Date()
]
- instance of Date constructor
(String?)
:
[
default: ' - '
]
- Separator character for output date
(String?)
:
[
default: ' \s '
]
- Separator character for output bitwin date and time
(String?)
:
[
default: ' : '
]
- Separator character for output time
String
:
uid.time();
uid.time( new Date() );
uid.time( new Date(), '-', ':', '-');
hash based on time in 36 numerical system by default
(Date?)
:
[
default: new Date()
]
- instance of Date constructor
(Number)
[
bit
]
:
[
default: 36
]
- expect number 2-36
String
:
hash string
uid.th();
uid.th(null, 4);
uid.th(new Date(), 10);
generate uuid (xxxxxxxx-xxxx-Mxxx-Nxxx-xxxxxxxxxxxx) based on time, reserved characters and random symbols
(String?)
[
default: random english symbol ( uid('S') )
]
(String?)
[
default: random number ( uid('N') )
]
(Date?)
[
default: new Date()
]
- date of guid generation
String
:
uid.guid();
uid.guid('M', 0, new Date() );
defination on platforms (both variants on platform like Electron)
bower i --save s-uid
npm i --save s-uid
window.uid || window['s-uid'] // in browser
var uid = require('s-uid') // in Node.js


I am an experienced software engineer skilled in Java, Golang, Python and C with 5+ years of experience. I have worked as a Software Developer at Cisco and Whatfix. Currently I am a Software Development Engineer at Amazon working on a confidential greenfield project. My career interest lies in Distributed Systems and scaling software systems.
Project: ASR903
Project: Unified Computing System Manager (UCSM)
Developed a tool to perform Automation and Regression Testing for HTML5 and JAVA based Graphical User Interface (GUI) using xnee, shell scripts and tcl/tk to test the user interface under real world circumstances. The tool takes a snapshot of the system while performing tests to help identify the errors along with the memory usage of the system represented using a bar graph. The tool also sends auto generated emails to the team containing a report for review.
Worked on Elementary GIS and Speech Processing to build a database of latitudes and longitudes of all the villages in India using Google Maps API by writing a shell script. As a part of Speech Processing I trained and tested a model for a small vocabulary of words using the CMUSphinx Tool to automate audio transcription.
Currently working towards building a Sharded Fault Tolerant Key Value Datastore built using Raft consensus algorithm using Golang.
Developed an Expense Tracking Application using technologies like Spring Boot, React, MongoDB, Docker and Docker Compose.
Developed a routing protocol based on Distance Vector Routing using Bellman Ford Algorithm using python and mininet which runs continuously and responds to change in weights/cost between links to update the routing table.
Developed an Iterative DNS Resolver for A, MX and NS queries which also supports DNSSec validation.
Developed a Windows Desktop Application in Microsoft AppFest 2013 held in the college using C# and XAML to help kids learn alphabets and numbers. Selected among the top 25 Apps in the AppFest.
Built a web based tool in final year of college using ASP.Net to help employees track tasks assigned to them and supervisors to track the tasks assigned by them.
Implemented a bookstore software in the final year of college. I was involved right from Software Requirement Specification, Analysis and Design of classes and the relationship between them using UML diagrams in IBM Rational Rose to implementation using ASP.Net.
Apart from being a software developer, I enjoy most of my time being outdoors. I am an avid traveller and a thrill seeker, I have enjoyed being catapulted into the sky at 200kmph in reverse bungee to paragliding from a cliff 8000ft above sea level.
When forced indoors, I follow a number of comedy and thriller genre movies and television shows, I am an aspiring chef, and spend a large amount of my free time exploring the latest technology advancements such as machine learning, blockchain and supplimenting my interest with MOOCs on such topics.


Chances are prescription and over-the-counter pharmaceuticals sitting in people’s medicine cabinets right now will someday find their way into water supplies. Most will get there when we excrete them or unused pills are flushed down the toilet. Others will seep into groundwater from meds tossed in landfills. These chemicals have been found in hundreds of rivers and lakes across the country, including each of the Great Lakes, and in the drinking water of 46 million Americans. Along the Chicago lakefront, scientists have found everything from antibiotics to pain relievers to caffeine.  But they have already had impacts on fish and other wildlife.
You can help by taking unwanted medicines to collection programs. Your pills will be incinerated, which poses less threat to the environment. Since 2003, Chicago and nearby suburbs have been hosting one-day collection events. Permanent drop-off sites at five police stations across the city also make it possible for residents to rid their medicine cabinets of unwanted pharmaceuticals anytime. The city’s permanent program alone keeps thousands of pounds of medication out of Lake Michigan and area rivers each year.


Chairman's Club donates $70K to those in need
by WVLT NewsKNOXVILLE, Tenn. (WVLT) — People in need around east Tennessee are getting more than $70,000 dollars in donations.
The chairman's club is gathered in Neyland Stadium, handing out donations last night.
It's a group of 100 men and their families trying to make a difference.
Recipients include Sangri La Therapeutic Academy of Writing, Joy of Music, Emerald Youth, Freedom School, UT Medical Neonatal and Shop with a Cop.


Filter
Downloads
Spam list
Router
DNS sniff
Remove selected
Add AP bssid
Add STA mac
Add from input
Set filter
WIFI CAP
IP CAP
AP scanner
STA MAC sniffer
MAC filter
Router config
Router sniffer
Set spam list
Download file
AP SSID:
AP password:
AP mac:
STA SSID:
STA password:
STA hostname:
STA mac:
Set configuration


About TFTPy
TFTPy is a pure Python implementation of the Trivial FTP protocol.
I wrote it because the VoIP company that I work for uses TFTP to pull firmware loads for our sets, and at times when this doesn't work we use a Windows-based diagnostic tool to troubleshoot the connection.
As all of the computers in my home run some flavour of Linux or FreeBSD, this tool wasn't much use to me, so I started one of my own. I decided to use Python since it's comfortable and available for the platforms that I care about, and was surprised to not find a pre-existing TFTP library for it. So, I wrote one, and here it is. It's not 1.0 yet, but downloading is production-ready IMHO, as some of the people using it tell me.
Features
At this time, it supports the following RFCs:
- 1350 The TFTP Protocol, revision 2 (octet mode only)
- 2347 TFTP Option Extension
- 2348 TFTP Blocksize Option
- 2349 TFTP Timeout Interval and Transfer Size Options (just the tsize option right now)
Future Plans
I do have plans for this code before a 1.0 release, including the following:
- Full RFC 1350 compliance, including netascii mode (I could care less about "mail" mode).
- Symmetric UDP support. I don't know of an RFC for this but it's a no-brainer for NAT traversal. In this mode the server should always respond on the port that the RRQ was sent to, so stateful firewalls will permit the response.
- Documentation!
The Code
You can find the latest release at the SourceForge Project Page, as a source tarball. It should also be in PyPi, so you can use easy_install if you prefer.
The latest code though is always on the master branch in Github. I did use SVN in SourceForge for a while, but after discovering Git I couldn't go back. To clone the repository, run the following command using git
git clone git://github.com/msoulier/tftpy.gitPatches welcome, even if I can't guarantee response time. You can of course send me the url of a public git repository to pull from as well.
The Github project page is right here.
Support
SourceForge doesn't make the mailing list easy to find, so here is a direct link if you'd like to join.
Feel free to email me with any questions, or contact me through github.
To submit a bug report, please use the issue tracker in the Github project page. I've shut down the trackers at sourceforge for now.
Documentation
I am working on some documentation via the Sphinx project. The current ones are here.
Last updated: May 10, 2010.


Cristiano Ronaldo to be evaluated before Juventus' clash with Atletico
by BeSoccerMaurizio Sarri is hopeful Cristiano Ronaldo will return for Juventus when Atletico Madrid visit Turin in the Champions League.
Cristiano Ronaldo has trained with Juventus and will be evaluated ahead of Tuesday's Champions League clash with Atletico Madrid, Maurizio Sarri has confirmed.
The Portugal striker sat out the unconvincing 3-1 win at Atalanta over the weekend as he continues to contend with a knee injury.
However, Ronaldo is seemingly in line to feature in the Group D contest against Atleti, an opponent the former Real Madrid star has scored 25 times against in his prolific career.
"Yesterday he did the training sessions with his team-mates," Sarri said. "He seems to be growing [stronger]. We will evaluate it between today and tomorrow to see if we have solved it, but the fact that yesterday he did all the training with his team-mates is very positive. I think and hope there will be no repercussions."
Ronaldo's relationship with Sarri has been under the microscope in recent weeks, mainly due to the coach's decision to haul off his star forward in two straight matches when Juve were chasing a win prior to the international break.
The second of those games, a 1-0 victory over AC Milan, saw Ronaldo head straight down the tunnel and reportedly leave the stadium before the match had finished.
However, Sarri insists all is well between the duo and he has no objection to players showing frustration when being substituted.
Featured links
- The latest football transfers news and rumours
- Neymar or Mbappé? Zidane choose
- Kante explains why he turned down PSG
- What Cristiano said about Messi to his Man Utd teammates
"My relationship with Cristiano is good," he added.
"If a player who has won so much is angry about being substituted it means he still has a lot of motivation and this is something positive.
"It is 25 years I have seen players get angry over substitutions."
Sarri, who confirmed Matthijs de Ligt and Federico Bernardeschi will also be evaluated before the game with Atleti, also explained why he does not foresee Ronaldo, Gonzalo Higuain and Paulo Dybala lining up in the same XI any time soon.
"Playing Paulo, Gonzalo and Cristiano all together is difficult because of their characteristics, but all three know how to play really well and are comfortable with each other," he said.
"We have three strong strikers for two places. None of the three can play 65 games as seen in the early part of the season. Everyone will find a place."
Juve have already qualified for the knockout phase of the Champions League but know a win over Atleti will secure top spot in Group D.
"Right now I'm seeing the team play excellently in flashes and I would like to see some more continuity in certain aspects, but we must take into account the characteristics of the players," Sarri said.
"We certainly have room for improvement. Against Atleti we can't worry about what they are going to do. They are a difficult team to face but we must think about how important first place in the group is."


const model = new HostedModel({
url: 'https://my-model.hosted-models.runwayml.cloud/v1',
token: 'my-secret-token', # token is only required for private models
})
Return info about the input/output spec provided by the model. Makes a GET request to the /v1/info route of a hosted model under the hood.
Returns true
if this model is awake, false
if it is still waking up.
See Awake, Awakening, and Awake in the
Hosted Models docs.
Run the model on your input and produce an output. This is how you "run" the model.
An object containing input parameters to be sent to the model. Use the info method to get the correct format for this object, as each model expects different inputs.
Returns a promise that will resolve once the model is awake. This method is never required, as info and query will always return results eventually, but it can be useful for managing UI if you want to postpone making info and query requests until you know that they will resolve more quickly.
// This is pseudo code
const model = new HostedModel({
url: 'https://my-model.hosted-models.runwayml.cloud/v1',
token: 'my-secret-token', # token is only required for private models
})
// Enter some loading state in the UI.
loading(true)
await model.waitUntilAwake() // This method is never required, but can sometimes be useful
loading(false)
while (true) {
const input = getSomeInput()
const output = await model.query(input)
doSomething(output)
}
waitUntilAwake The rate that this function will poll the hosted model endpoint to check if it is awake yet.
 This is the main interface provided by this package. Exposes two main methods for interfacing with a model.
info()
query(input)
Exposes two helper methods for checking the "awake" status of a hosted model.
isAwake()
waitUntilAwake()


Find out more abut an exciting campaign at Leeds Art Gallery.
10 February – 28 August 2017
Take a free tour!
21 January - 31 December 2017


| When a Com port is active, the
Menu text will change to the active port number. If the selected port
does not have the Mini_CT communicating or the port is not valid, the
Com port text will change to Com:XX. On start up, the program searches for a serial port with an attached Mini_CT. This may take several seconds to locate. The same is true when selecting a port manually. Wait a few seconds for the program to respond. |


QModbusResponse Class
QModbusResponse is a container class containing the function code and payload that is stored inside a Modbus ADU. More...
| Header: | #include <QModbusResponse> |
| qmake: | QT += serialbus |
| Since: | Qt 5.8 |
| Inherits: | QModbusPdu |
| Inherited By: |
Public Functions
| QModbusResponse() = default | |
| QModbusResponse(const QModbusPdu &pdu) | |
| QModbusResponse(FunctionCode code, const QByteArray &data = QByteArray()) | |
| QModbusResponse(FunctionCode code, Args... data) |
- 11 public functions inherited from QModbusPdu
Static Public Members
| int | calculateDataSize(const QModbusResponse &response) |
| int | minimumDataSize(const QModbusResponse &response) |
| void | registerDataSizeCalculator(FunctionCode fc, CalcFuncPtr calculator) |
- 1 static public member inherited from QModbusPdu
Related Non-Members
| QDataStream & | operator>>(QDataStream &stream, QModbusResponse &pdu) |
Additional Inherited Members
- 1 protected function inherited from QModbusPdu
Detailed Description
QModbusResponse is a container class containing the function code and payload that is stored inside a Modbus ADU.
A typical Modbus response can looks like this:
QModbusResponse response(QModbusResponse::ReadCoils, QByteArray::fromHex("02cd01"));
Note: When using the constructor taking the QByteArray
, please make sure to convert the containing data to big-endian byte order before creating the request.
The same response can be created like this, if the values are know at compile time:
quint8 payloadInBytes = 2, outputHigh = 0xcd, outputLow = 0x01; QModbusResponse response(QModbusResponse::ReadCoils, payloadInBytes, outputHigh, outputLow);
Member Function Documentation
[default]
QModbusResponse::QModbusResponse()
Constructs an invalid QModbusResponse.
QModbusResponse::QModbusResponse(const QModbusPdu &pdu)
Constructs a copy of pdu.
QModbusResponse::QModbusResponse(FunctionCode code, const QByteArray &data = QByteArray())
Constructs a QModbusResponse with function code set to code and payload set to data. The data is expected to be stored in big-endian byte order already.
QModbusResponse::QModbusResponse(FunctionCode code, Args... data)
Constructs a QModbusResponse with function code set to code and payload set to data. The data is converted and stored in big-endian byte order.
Note: Usage is limited quint8
and quint16
only. This is because QDataStream
stream operators will not only append raw data, but also e.g. size, count etc. for complex types.
[static]
int QModbusResponse::calculateDataSize(const QModbusResponse &response)
Calculates the expected data size for response, based on the response's function code and data. Returns the full size of the response's data part; -1
if the size could not be properly calculated.
See also minimumDataSize and registerDataSizeCalculator.
[static]
int QModbusResponse::minimumDataSize(const QModbusResponse &response)
Returns the expected minimum data size for response based on the response's function code; -1
if the function code is not known.
[static]
void QModbusResponse::registerDataSizeCalculator(FunctionCode fc, CalcFuncPtr calculator)
This function registers a user-defined implementation to calculate the response data size for function code fc. It can be used to extend or override the implementation inside QModbusResponse::calculateDataSize().
The CalcFuncPtr
is a typedef for a pointer to a custom calculator function with the following signature:
int myCalculateDataSize(const QModbusResponse &pdu);
Related Non-Members
QDataStream &operator>>(QDataStream &stream, QModbusResponse &pdu)
Reads a pdu from the stream and returns a reference to the stream.
Note: The function might fail to properly stream PDU's with function code QModbusPdu::Diagnostics or QModbusPdu::EncapsulatedInterfaceTransport because of the missing size indicator inside the PDU. In particular this may happen when the PDU is embedded into a stream that doesn't end with the diagnostic/encapsulated request itself.


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boost::container::flat_set —
template<typename T, typename Pred, typename Alloc> class flat_set { public: // types typedef tree_t::key_type key_type; typedef tree_t::value_type value_type; typedef tree_t::pointer pointer; typedef tree_t::const_pointer const_pointer; typedef tree_t::reference reference; typedef tree_t::const_reference const_reference; typedef tree_t::key_compare key_compare; typedef tree_t::value_compare value_compare; typedef tree_t::iterator iterator; typedef tree_t::const_iterator const_iterator; typedef tree_t::reverse_iterator reverse_iterator; typedef tree_t::const_reverse_iterator const_reverse_iterator; typedef tree_t::size_type size_type; typedef tree_t::difference_type difference_type; typedef tree_t::allocator_type allocator_type; typedef tree_t::stored_allocator_type stored_allocator_type; // construct/copy/destruct flat_set(const Pred & = Pred(), const allocator_type & = allocator_type()); template<typename InputIterator> flat_set(InputIterator, InputIterator, const Pred & = Pred(), const allocator_type & = allocator_type()); template<typename InputIterator> flat_set(ordered_unique_range_t, InputIterator, InputIterator, const Pred & = Pred(), const allocator_type & = allocator_type()); flat_set(const flat_set< T, Pred, Alloc > &); flat_set(flat_set &&); flat_set& operator=(const flat_set &); flat_set& operator=(flat_set &&); // public member functions key_compare key_comp() const; value_compare value_comp() const; allocator_type get_allocator() const; const stored_allocator_type & get_stored_allocator() const; stored_allocator_type & get_stored_allocator() ; iterator begin() ; const_iterator begin() const; const_iterator cbegin() const; iterator end() ; const_iterator end() const; const_iterator cend() const; reverse_iterator rbegin() ; const_reverse_iterator rbegin() const; const_reverse_iterator crbegin() const; reverse_iterator rend() ; const_reverse_iterator rend() const; const_reverse_iterator crend() const; bool empty() const; size_type size() const; size_type max_size() const; void swap(flat_set &) ; std::pair< iterator, bool > insert(const value_type &) ; std::pair< iterator, bool > insert(value_type &&) ; iterator insert(const_iterator, const value_type &) ; iterator insert(const_iterator, value_type &&) ; template<typename InputIterator> void insert(InputIterator, InputIterator) ; template<class... Args> iterator emplace(Args &&...) ; template<class... Args> iterator emplace_hint(const_iterator, Args &&...) ; iterator erase(const_iterator) ; size_type erase(const key_type &) ; iterator erase(const_iterator, const_iterator) ; void clear() ; void shrink_to_fit() ; iterator find(const key_type &) ; const_iterator find(const key_type &) const; size_type count(const key_type &) const; iterator lower_bound(const key_type &) ; const_iterator lower_bound(const key_type &) const; iterator upper_bound(const key_type &) ; const_iterator upper_bound(const key_type &) const; std::pair< const_iterator, const_iterator > equal_range(const key_type &) const; std::pair< iterator, iterator > equal_range(const key_type &) ; size_type capacity() const; void reserve(size_type) ; };
flat_set is a Sorted Associative Container that stores objects of type Key. flat_set is a Simple Associative Container, meaning that its value type, as well as its key type, is Key. It is also a Unique Associative Container, meaning that no two elements are the same.
flat_set is similar to std::set but it's implemented like an ordered vector. This means that inserting a new element into a flat_set invalidates previous iterators and references
Erasing an element of a flat_set invalidates iterators and references pointing to elements that come after (their keys are bigger) the erased element.
flat_set
public
construct/copy/destructflat_set(const Pred & comp = Pred(), const allocator_type & a = allocator_type());
Effects: Constructs an empty flat_map using the specified comparison object and allocator.
Complexity: Constant.
template<typename InputIterator> flat_set(InputIterator first, InputIterator last, const Pred & comp = Pred(), const allocator_type & a = allocator_type());
Effects: Constructs an empty map using the specified comparison object and allocator, and inserts elements from the range [first ,last ).
Complexity: Linear in N if the range [first ,last ) is already sorted using comp and otherwise N logN, where N is last - first.
template<typename InputIterator> flat_set(ordered_unique_range_t, InputIterator first, InputIterator last, const Pred & comp = Pred(), const allocator_type & a = allocator_type());
Effects: Constructs an empty flat_set using the specified comparison object and allocator, and inserts elements from the ordered unique range [first ,last). This function is more efficient than the normal range creation for ordered ranges.
Requires: [first ,last) must be ordered according to the predicate and must be unique values.
Complexity: Linear in N.
flat_set(const flat_set< T, Pred, Alloc > & x);
Effects: Copy constructs a map.
Complexity: Linear in x.size().
flat_set(flat_set && mx);
Effects: Move constructs a map. Constructs *this using x's resources.
Complexity: Construct.
Postcondition: x is emptied.
flat_set& operator=(const flat_set & x);
Effects: Makes *this a copy of x.
Complexity: Linear in x.size().
flat_set& operator=(flat_set && mx);
Effects: Makes *this a copy of x.
Complexity: Linear in x.size().
flat_set
public member functionskey_compare key_comp() const;
Effects: Returns the comparison object out of which a was constructed.
Complexity: Constant.
value_compare value_comp() const;
Effects: Returns an object of value_compare constructed out of the comparison object.
Complexity: Constant.
allocator_type get_allocator() const;
Effects: Returns a copy of the Allocator that was passed to the object's constructor.
Complexity: Constant.
const stored_allocator_type & get_stored_allocator() const;
stored_allocator_type & get_stored_allocator() ;
iterator begin() ;
Effects: Returns an iterator to the first element contained in the container.
Throws: Nothing.
Complexity: Constant.
const_iterator begin() const;
Effects: Returns a const_iterator to the first element contained in the container.
Throws: Nothing.
Complexity: Constant.
const_iterator cbegin() const;
Effects: Returns a const_iterator to the first element contained in the container.
Throws: Nothing.
Complexity: Constant.
iterator end() ;
Effects: Returns an iterator to the end of the container.
Throws: Nothing.
Complexity: Constant.
const_iterator end() const;
Effects: Returns a const_iterator to the end of the container.
Throws: Nothing.
Complexity: Constant.
const_iterator cend() const;
Effects: Returns a const_iterator to the end of the container.
Throws: Nothing.
Complexity: Constant.
reverse_iterator rbegin() ;
Effects: Returns a reverse_iterator pointing to the beginning of the reversed container.
Throws: Nothing.
Complexity: Constant.
const_reverse_iterator rbegin() const;
Effects: Returns a const_reverse_iterator pointing to the beginning of the reversed container.
Throws: Nothing.
Complexity: Constant.
const_reverse_iterator crbegin() const;
Effects: Returns a const_reverse_iterator pointing to the beginning of the reversed container.
Throws: Nothing.
Complexity: Constant.
reverse_iterator rend() ;
Effects: Returns a reverse_iterator pointing to the end of the reversed container.
Throws: Nothing.
Complexity: Constant.
const_reverse_iterator rend() const;
Effects: Returns a const_reverse_iterator pointing to the end of the reversed container.
Throws: Nothing.
Complexity: Constant.
const_reverse_iterator crend() const;
Effects: Returns a const_reverse_iterator pointing to the end of the reversed container.
Throws: Nothing.
Complexity: Constant.
bool empty() const;
Effects: Returns true if the container contains no elements.
Throws: Nothing.
Complexity: Constant.
size_type size() const;
Effects: Returns the number of the elements contained in the container.
Throws: Nothing.
Complexity: Constant.
size_type max_size() const;
Effects: Returns the largest possible size of the container.
Throws: Nothing.
Complexity: Constant.
void swap(flat_set & x) ;
Effects: Swaps the contents of *this and x. If this->allocator_type() != x.allocator_type() allocators are also swapped.
Throws: Nothing.
Complexity: Constant.
std::pair< iterator, bool > insert(const value_type & x) ;
Effects: Inserts x if and only if there is no element in the container with key equivalent to the key of x.
Returns: The bool component of the returned pair is true if and only if the insertion takes place, and the iterator component of the pair points to the element with key equivalent to the key of x.
Complexity: Logarithmic search time plus linear insertion to the elements with bigger keys than x.
Note: If an element it's inserted it might invalidate elements.
std::pair< iterator, bool > insert(value_type && x) ;
Effects: Inserts a new value_type move constructed from the pair if and only if there is no element in the container with key equivalent to the key of x.
Returns: The bool component of the returned pair is true if and only if the insertion takes place, and the iterator component of the pair points to the element with key equivalent to the key of x.
Complexity: Logarithmic search time plus linear insertion to the elements with bigger keys than x.
Note: If an element it's inserted it might invalidate elements.
iterator insert(const_iterator position, const value_type & x) ;
Effects: Inserts a copy of x in the container if and only if there is no element in the container with key equivalent to the key of x. p is a hint pointing to where the insert should start to search.
Returns: An iterator pointing to the element with key equivalent to the key of x.
Complexity: Logarithmic search time (constant if x is inserted right before p) plus insertion linear to the elements with bigger keys than x.
Note: If an element it's inserted it might invalidate elements.
iterator insert(const_iterator position, value_type && x) ;
Effects: Inserts an element move constructed from x in the container. p is a hint pointing to where the insert should start to search.
Returns: An iterator pointing to the element with key equivalent to the key of x.
Complexity: Logarithmic search time (constant if x is inserted right before p) plus insertion linear to the elements with bigger keys than x.
Note: If an element it's inserted it might invalidate elements.
template<typename InputIterator> void insert(InputIterator first, InputIterator last) ;
Requires: i, j are not iterators into *this.
Effects: inserts each element from the range [i,j) if and only if there is no element with key equivalent to the key of that element.
Complexity: N log(size()+N) (N is the distance from i to j) search time plus N*size() insertion time.
Note: If an element it's inserted it might invalidate elements.
template<class... Args> iterator emplace(Args &&... args) ;
Effects: Inserts an object of type T constructed with std::forward<Args>(args)... if and only if there is no element in the container with key equivalent to the key of x.
Returns: The bool component of the returned pair is true if and only if the insertion takes place, and the iterator component of the pair points to the element with key equivalent to the key of x.
Complexity: Logarithmic search time plus linear insertion to the elements with bigger keys than x.
Note: If an element it's inserted it might invalidate elements.
template<class... Args> iterator emplace_hint(const_iterator hint, Args &&... args) ;
Effects: Inserts an object of type T constructed with std::forward<Args>(args)... in the container if and only if there is no element in the container with key equivalent to the key of x. p is a hint pointing to where the insert should start to search.
Returns: An iterator pointing to the element with key equivalent to the key of x.
Complexity: Logarithmic search time (constant if x is inserted right before p) plus insertion linear to the elements with bigger keys than x.
Note: If an element it's inserted it might invalidate elements.
iterator erase(const_iterator position) ;
Effects: Erases the element pointed to by position.
Returns: Returns an iterator pointing to the element immediately following q prior to the element being erased. If no such element exists, returns end().
Complexity: Linear to the elements with keys bigger than position
Note: Invalidates elements with keys not less than the erased element.
size_type erase(const key_type & x) ;
Effects: Erases all elements in the container with key equivalent to x.
Returns: Returns the number of erased elements.
Complexity: Logarithmic search time plus erasure time linear to the elements with bigger keys.
iterator erase(const_iterator first, const_iterator last) ;
Effects: Erases all the elements in the range [first, last).
Returns: Returns last.
Complexity: size()*N where N is the distance from first to last.
Complexity: Logarithmic search time plus erasure time linear to the elements with bigger keys.
void clear() ;
Effects: erase(a.begin(),a.end()).
Postcondition: size() == 0.
Complexity: linear in size().
void shrink_to_fit() ;Effects
Throws: If memory allocation throws, or T's copy constructor throws.
Complexity: Linear to size().
iterator find(const key_type & x) ;
Returns: An iterator pointing to an element with the key equivalent to x, or end() if such an element is not found.
Complexity: Logarithmic.
const_iterator find(const key_type & x) const;
Returns: A const_iterator pointing to an element with the key equivalent to x, or end() if such an element is not found.
Complexity: Logarithmic.s
size_type count(const key_type & x) const;
Returns: The number of elements with key equivalent to x.
Complexity: log(size())+count(k)
iterator lower_bound(const key_type & x) ;
Returns: An iterator pointing to the first element with key not less than k, or a.end() if such an element is not found.
Complexity: Logarithmic
const_iterator lower_bound(const key_type & x) const;
Returns: A const iterator pointing to the first element with key not less than k, or a.end() if such an element is not found.
Complexity: Logarithmic
iterator upper_bound(const key_type & x) ;
Returns: An iterator pointing to the first element with key not less than x, or end() if such an element is not found.
Complexity: Logarithmic
const_iterator upper_bound(const key_type & x) const;
Returns: A const iterator pointing to the first element with key not less than x, or end() if such an element is not found.
Complexity: Logarithmic
std::pair< const_iterator, const_iterator > equal_range(const key_type & x) const;
Effects: Equivalent to std::make_pair(this->lower_bound(k), this->upper_bound(k)).
Complexity: Logarithmic
std::pair< iterator, iterator > equal_range(const key_type & x) ;
Effects: Equivalent to std::make_pair(this->lower_bound(k), this->upper_bound(k)).
Complexity: Logarithmic
size_type capacity() const;
Effects: Number of elements for which memory has been allocated. capacity() is always greater than or equal to size().
Throws: Nothing.
Complexity: Constant.
void reserve(size_type count) ;
Effects: If n is less than or equal to capacity(), this call has no effect. Otherwise, it is a request for allocation of additional memory. If the request is successful, then capacity() is greater than or equal to n; otherwise, capacity() is unchanged. In either case, size() is unchanged.
Throws: If memory allocation allocation throws or T's copy constructor throws.
Note: If capacity() is less than "count", iterators and references to to values might be invalidated.


Namespace netDxf.Objects
Classes
Group
Represents a group of entities.
GroupEntityChangeEventArgs
ImageDefinition
Represents an image definition.
Layout
Represents a layout.
MLineStyle
Represents as MLine style.
MLineStyleElement
Represent each of the elements that make up a MLineStyle.
MLineStyleElementChangeEventArgs
PlotSettings
Represents the plot settings of a layout.
RasterVariables
Represents the variables applied to bitmaps.
UnderlayDefinition
Represents an underlay definition.
UnderlayDgnDefinition
Represents a DGN underlay definition.
UnderlayDwfDefinition
Represents a DWF underlay definition.
UnderlayPdfDefinition
Represents a PDF underlay definition.
Structs
PaperMargin
Represents the unprintable margins of a paper.
Enums
DictionaryCloningFlags
Duplicate record cloning flag (determines how to merge duplicate entries).
ImageDisplayQuality
Image display quality (screen only).
MLineStyleFlags
Flags (bit-coded).
PlotFlags
Defines the plot settings flag.
PlotPaperUnits
Plot paper units.
PlotRotation
Plot rotation
PlotType
Defines the portion of paper space to output to the media.
ShadePlotMode
Defines the shade plot mode
ShadePlotResolutionMode
Defines the shade plot resolution mode.
SupportedImageFormats
Supported image formats.
UnderlayType
Defines the different underlay documents available.


Before Change
// Set the ticks on the axis object.
self.ax.set_yticks([]) // Clear the yaxis labels / ticks
self.ax.set_xticks(np.linspace(-1,1,11))
After Change
// l_xlim and u_xlim are lower and upper limits of the x-axis,
// set according to our calculated maximum and minimum silhouette score along with necessary padding
l_xlim = max(-1, min(-0.1, round(min(self.silhouette_samples_) - 0.1, 1)))
u_xlim = min(1, round(max(self.silhouette_samples_) + 0.1, 1))
self.ax.set_xlim([l_xlim, u_xlim])
// The (n_clusters_+1)*10 is for inserting blank space between
// silhouette plots of individual clusters, to demarcate them clearly.


The user-service module contains the following methods.
The following protection mechanisms are configured for the admin-service module.


Welcome to Jaira Velasco's Travel and Tour!
Originating City
Destination City
Price
Duration
Calgary
Los Cabos
$1667 per adult
5 Days
Havana
$1289 per adult
Barcelona
$3249 per adult
London
$3207 per adult
Rome
$3439 per adult
Submit form using GET method:
Name:
E-mail address:
Departure date:
Destination city:
Number of passengers:
Submit
Submit form using POST method:
Name:
E-mail address:
Departure date:
Destination city:
Number of passengers:
Submit


Since 2017, Allegheny Cereal has been cooking up an inventive and tasty assortment of granola flavors that can't be found on supermarket shelves. Established in Pittsburgh's historic Deutschtown neighborhood, we source high-quality local ingredients whenever possible.
Our granola is made with love in small batches. We are always experimenting and adding new flavors, so check back often to see what's in store.


| Package | com.sibirjak.angara.sequence |
| Interface | public interface IPagedSequence extends ISequence, ILoaderItem, IProgressInfo, flash.events.IEventDispatcher, org.as3commons.collections.framework.IIterable |
| Implementors | PagedSequence |
A resource loader added to a paged sequence will be automatically paused.
| Method | Defined by | ||
|---|---|---|---|
|
activateLoaders(index:uint, numItems:uint):void
Resumes all loaders in the specified range and pauses all
other currently waiting loaders.
| IPagedSequence | ||
|
add(resourceLoader:IResourceLoader, weight:uint = 0):void
Adds a new resource loader to the sequence.
| ISequence | ||
|
clear():void
Stops all loaders and removes all loader references from the sequence.
| ISequence | ||
|
pause():void
Marks the item to be ignored by subsequent loader manager queue pulling operations.
| ILoaderItem | ||
|
remove(resourceLoader:IResourceLoader):void
Removes a loader from a sequence.
| ISequence | ||
|
resume():void
Marks a prior paused item to be eligible for loader manager queue polling
operations.
| ILoaderItem | ||
|
stop():void
Immediately stops loading of the item or its containing items.
| ILoaderItem |
| activateLoaders | () | method |
public function activateLoaders(index:uint, numItems:uint):void
Resumes all loaders in the specified range and pauses all other currently waiting loaders.
Parametersindex:uint — The index of the first resource loader.
|
|
numItems:uint — The number of loaders to be resumed.
|


--- layout: post title: asp.net and IIS follow-up tags: [iis, asp.net] ---
Following my article on asp.net hosting, Dave writes about this document that I could’ve used and have less investigation to do should have I found it. Great complementary content to my article. My favorite piece of Dave’s post? “The real eye opener in the article for me was…”. Now I’m happy as I know at least one person found something useful for their job. Benjamin told me, quite insightfully, that I needed to market my content better. And I think I have a beginning of it!
From julien, I’m also going to review it as soon as I get out of illness and conferencing about the code access security, the partial trust execution under .net 1.1 and how it is built. Thanks for reviewing and giving me your comments Julien! And yes, as soon as I come back from Amsterdam, I’ll finish my review on your Petshop SOA article. Sorry for the delay.
Time to bed. No, time to bed is way way past what I can afford. So off to grab a few hours of sleep. Will blog from the conference if it gets too boring! (That, and if I can get any wireless connection in my new hotel!)


Lorem ipsum dolor sit, amet consectetur adipisicing elit. Neque pariatur natus laboriosam ut sunt!
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How To Cut and Trim Video
The following command is used to trim video in FFmpeg. The stream copy enables to trim video without re-encoding and meanwhile keeps original quality for the output video.
`
.. code:: bash
ffmpeg -i input.mp4 -ss 00:01:23 -to 00:04:20 -c copy output.mp4
`
ffmpeg -i input.mp4 -ss 00:01:23 -to 00:04:20 -c copy output.mp4
-c copy trim via stream copy, which is fast and will not re-encode video.


Dinesh G
Coder
Problem Solver
shortcut finder
About Me
Learner & Free Thinker
Student - at BMSIT & Developer - by Intrest
Enthusiastic fresher pursuing engineering in the field of Computer Science in BMSIT college. I am self-motivated and I very much interested in coding. I am eager to learn new technologies and always think to make things simple. Passionate about implementing and launching new projects. Looking to start the career as an entry level software engineer.
- LocationBangalore, India
-<EMAIL_ADDRESS>- Phone+91-8892477491
- Skypedinesh G
- FacebookDinesh G
- Twitter@dinesh_G
-<EMAIL_ADDRESS>- Mozilla Reps ProfileDinesh G
- Telegram@dinesh_G
Resume
Education
2020
B.E- Computer Science Engineering
BMS Institute of technology and ManagementCGPA: 6.92
2016
XII
KLE S Nijalingappa collegePercentage: 82.67%
2014
X
Morning Star High SchoolCGPA: 89.6%
Experience
November 2019 - Present
Sudent at BMSIT
CSE Dept.Skills
Python
C
Java
HTML
CSS
php
JavaScript
Contact
Get in Touch
Get in Touch
Happy to Help.


Penpa+ Version 2.26.1 © 2020-2021
*Works only in Square Board Type, it also resets undo/redo. Answer checking if enabled, will only work with original grid size.
*Works only in Square Board Type, it also resets undo/redo. Ensure empty row/column before removing.
*Specify the location of the first cell of your sudoku grid and its size[optional]:


bit64: A S3 Class for Vectors of 64bit Integers
Package 'bit64' provides serializable S3 atomic 64bit (signed) integers.
These are useful for handling database keys and exact counting in +-2^63.
WARNING: do not use them as replacement for 32bit integers, integer64 are not
supported for subscripting by R-core and they have different semantics when
combined with double, e.g. integer64 + double => integer64.
Class integer64 can be used in vectors, matrices, arrays and data.frames.
Methods are available for coercion from and to logicals, integers, doubles,
characters and factors as well as many elementwise and summary functions.
Many fast algorithmic operations such as 'match' and 'order' support inter-
active data exploration and manipulation and optionally leverage caching.
| Version: |
0.9-7 |
| Depends: |
R (≥ 3.0.1), bit (≥ 1.1-12), utils, methods, stats |
| Published: |
2017-05-08 |
| Author: |
Jens Oehlschlägel |
| Maintainer: |
Jens Oehlschlägel <Jens.Oehlschlaegel at truecluster.com> |
| License: |
GPL-2 |
| URL: |
http://ff.r-forge.r-project.org/ |
| NeedsCompilation: |
yes |
| Materials: |
NEWS |
| CRAN checks: |
bit64 results |
Downloads:
Reverse dependencies:
| Reverse depends: |
LSPFP, RGoogleFit, rHealthDataGov, scidb |
| Reverse imports: |
antaresRead, boxr, CVXR, dplyr.teradata, fbRads, hdf5r, heims, nanotime, odbc, planor, RMariaDB, RPostgres, RSQLite, twitteR |
| Reverse suggests: |
ctmm, data.table, dataCompareR, dbplyr, dplyr, fst, h2o, MonetDBLite, otvPlots, rio, scales, writexl |
| Reverse enhances: |
csvread |
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=bit64
to link to this page.


Dr Babin is Practice Professor and Associate Director of the Engineering Entrepreneurship Program. On campus, Dr Babin is an advisor for the Wharton Venture Initiative Program (VIP) and an entrepreneurial fellow for the Weiss Tech House. He has significant entrepreneurial experience as a founder and Managing Director of Antiphony Partners LLC, a strategic consulting firm that helps companies create sustainable value through innovation.
On 11/22/19, M&T Innovation Fund held a Q&A panel with Dr Babin discussing the transition from a student entrepreneur to a professional entrepreneur, and the entrepreneurial opportunities available at Penn.
Q&A Panel in Larry Robbins House
Introduction.
There are lots of entrepreneurship opportunities available at Penn. Every school (except for the College) has some innovation or entrepreneurship program, in addition to co-curricular and extra-curricular opportunities. These include 12 accelerators on Penn’s campus to help students explore their ideas. That is a lot of intellectual horsepower!
How do you differentiate between these opportunities?
Differentiating opportunities has certainly been a historical challenge. However, some structure has developed in recent years. Some opportunities like Wharton VIP are exclusive to certain schools, while others like Weiss Tech House are student-run and open to the entire student body.
Let’s talk about successful Penn startups.
War-B: Worked on pricing with faculty members, they were members of VIP.
Zodiac: Outgrowth of Pete Fader in the Marketing department.
The best startups out of Penn take advantage of ALL of the resources provided to them. They apply to all the accelerators and look at the largest body of individuals for advice. Penn costs $75K/ year; the main value that you obtain is not from your classes, but rather the networks and facilities that you have access to.
Tangen Hall.
Tangen Hall is a student entrepreneurship hub that will finish construction in Fall 2020. All entrepreneurship facilities will move to Tangen Hall thereafter.
Most of the first floor will be a maker space (managed by SEAS) open to all students. A commercial kitchen and retail space for student businesses will also be present.
|
Even though students these days are more remotely-located, there is value to being concentrated in one area. For example, Dr Babin was once asked how to meet an engineer by a Wharton student! This issue will no longer persist as all students will have 24x7 access to the building.
Future VIP plans.
There is VIP in San Francisco, but not here for Penn alumni. That will be changed so that alumni and students can be better connected in the future.
Advice for getting co-founders.
You have to earn co-founders, and co-founders have to earn being with your startup.  Don’t be a “Whartonite Seeks Code Monkey”.
If you work on a class project with someone, that doesn’t entitle you to equity ownership if the idea becomes a company. Rather, your efforts entitle you to a better grade.
If someone chooses to work on the idea after a class ends, you should attract people by what value they can add as opposed to just splitting equity in some arbitrary proportion. The vision must come before the details; everyone must earn their equity.
Dr Babin often refers to Chapter 6 of The Founder’s Dilemma. The author argues that initially dividing up equity is easy and delusional; rather, everyone should earn the equity by contributing. Dead weight is futile.
Advice for planning your company timeline.
Always plan for 4 Years with a One Year Cliff. It is important to be transparent when dividing equity to avoid future resentment or conflict.
It is hard to develop student businesses because of rigorous courses. Further, students often assume that others must have the same idea. What is your perspective?
Let’s look at it less as horse-ahead-of-the-cart. If you ask the question: should I make a startup or get a job, you should get a job. If you are invested in your idea and are worried about it going away, then you should follow your startup.
What should we do about investors that look for more-experienced individuals?
Investors are more concerned about whether we will get tired of our startup as we are so young and often have different opportunities.
Some investors only look for grey hair-don’t pitch to them. But you can get over being young very quickly if you prove yourself.
User-testing among friends. Bias and very homogenous. How to find a good group for user-testing.
You can use social media to beta test for very little money. Almost everyone at Penn can arm-twist themselves to 100 users (friends to friends). However, you cannot get up to 5000 users by arm-twisting; direct sales are not feasible for scaling. Your product needs to generate positive word-of-mouth; your friends themselves cannot spread your idea if your idea isn’t up to scratch.
Never demo your product. Give it to your friend and let them figure out what to do. If they don’t get what to do, then you need to redesign your UI. This was Apple’s philosophy when developing the Macintosh and iPhone.
Laws and regulations.
Don’t break laws or do anything that can result in a call to the Dean or President. For example, Just 3D Print It was a Penn startup that 3D printed public models and resold them to consumers.
They also listed Dr Babin as an ambassador, despite never having spoken to him about this matter. Campus ambassador programs are very good, but one should exercise caution when adding someone to their startup.
Student-led organizations.
The problem with student-led organizations is that success is largely determined by the leader. Sometimes there is a good leader that elicits growth, and sometimes bad leaders hold back their organization.
What Weiss Fund does to mitigate this issue is overlap leaders. There is a senior running the Fund with a junior shadowing them. It has been working well for them over the past few years.
Thought on working on something ‘new’ vs collaborating.
Rather than pursuing an idea that is similar to an existing company, it is generally better to join the existing company and add value to them.
Is there a list of all Penn startups?
One thing that we are not good at Penn is centralization. While there is no centralized list, many accelerators have a list of their portfolio companies. M&T Innovation Fund has a list of our portfolio companies over the past 5 years. Weiss Fund has startup data for the past 6 years, VIP has startup data for the past 15 years. But there is definitely room for improvement.
If we were to assign every startup a unique key field, then we would be able to collect data on all their activity. But that requires funding and data support. If you want to work on the data side, contact Dr Babin.


She set off to search for a new pond that could serve, a place with no golf clubs and no AstroTurf. But every pond was empty, every well was dry, every tough was spoke for, yet still she had to try.
She traveled each road, and sought out every
route. But instead of finding home, poor Ness got the boot. And the reward for her
efforts, it was always this quip...
The rat said, "Only wee babies cry, chin up now, pip pip."
Nessie finally popped out. She'd reached the end of her rope. Where do you go, when there is no more hope? She stifled a whimper, and a lump in her throat. Chin up now, pip pip. She recited by rote.


Whats in it for you?
Benefits
Learn about the added benefits that come as part of your MVP distinction
Becoming an Sitecore MVP has a lot of benefits for you. Here are some highlights:
- Recognition as a global Sitecore expert and community leader
- Access to early product releases and privileged resources, including direct access to product teams and kick-off webinars
- Exclusive invitations to MVP discussion forums.
- Meet your regional Sitecore team and peers during regional MVP meetings
- Exclusive Invitation to the MVP Summit. The Summit is executive insight to product and company strategy with lots of networking and fun activities.
- Discount at Sitecore events SUGCON, Symposium
How to become a MVP
Hear from Tamas Varga, MVP Program Manager at Sitecore, on how you can become a MVP.


Do you want to delete this task?
By deleting this key, you will also delete all tasks and events using this key.


{% extends "./views/layout.html" %} {% block content %}
You can delete your account, but keep in mind this action is irreversible.


Lemon drops toffee tootsie roll gingerbread macaroon. Chocolate topping cotton candy cheesecake chocolate cake. Chupa chups caramels marzipan bonbon danish candy canes.
Dessert sugar plum muffin applicake applicake cheesecake wafer bonbon jelly beans. Icing donut marshmallow liquorice dessert chocolate bar tiramisu bear claw. Wafer tart muffin. Danish candy canes macaroon icing cake chupa chups candy jelly beans danish. Learn More →
Jujubes halvah lollipop toffee sweet cupcake jelly. Chupa chups chocolate carrot cake donut. Donut jelly beans cotton candy candy canes marshmallow. Soufflé biscuit gummi bears chocolate cake gummi bears pie. Learn More →
Candy lollipop gummi bears jujubes pie. Cake brownie toffee brownie apple pie sesame snaps donut carrot cake. Apple pie marshmallow pudding liquorice. Cotton candy halvah chupa chups cheesecake halvah applicake. Bear claw donut biscuit muffin toffee chocolate bar. Learn More →
Candy lollipop gummi bears jujubes pie. Cake brownie toffee brownie apple pie sesame snaps donut carrot cake. Apple pie marshmallow pudding liquorice. Cotton candy halvah chupa chups cheesecake halvah applicake. Learn More →
Brownie liquorice jelly. Macaroon pudding jelly beans pastry. Gummies sugar plum jelly-o. Biscuit lollipop faworki lollipop dessert donut cotton candy biscuit carrot cake. Marzipan faworki halvah liquorice tootsie roll. Cupcake icing jujubes wypas gummies biscuit pastry. Learn More →
Muffin sweet biscuit jujubes. Cake donut bear claw sweet roll soufflé lemon drops tootsie roll cookie halvah. Jelly beans cheesecake apple pie macaroon carrot cake macaroon applicake wypas caramels. Learn More →
Toffee sweet roll wypas jelly chocolate cake. Lemon drops jelly-o pudding fruitcake gingerbread sesame snaps tootsie roll lemon drops gingerbread. Dessert macaroon applicake tootsie roll gummies marzipan croissant chocolate. Croissant lollipop wypas pudding wypas. Dessert sweet roll caramels.


| Module | ActiveSupport::Cache::Strategy::LocalCache |
| In: |
/usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/cache/strategy/local_cache.rb
|
Caches that implement LocalCache will be backed by an in memory cache for the duration of a block. Repeated calls to the cache for the same key will hit the in memory cache for faster access.
Middleware class can be inserted as a Rack handler to use a local cache for the duration of a request.
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/cache/strategy/local_cache.rb, line 55 55: def middleware 56: @middleware ||= begin 57: klass = Class.new 58: klass.class_eval("class << self\ndef name\n\"ActiveSupport::Cache::Strategy::LocalCache\"\nend\nalias :to_s :name\nend\n\ndef initialize(app)\n@app = app\nend\n\ndef call(env)\nThread.current[:\#{thread_local_key}] = LocalStore.new\n@app.call(env)\nensure\nThread.current[:\#{thread_local_key}] = nil\nend\n", __FILE__, __LINE__ + 1) 59: klass 60: end 61: end
Use a local cache to front for the cache for the duration of a block.
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/cache/strategy/local_cache.rb, line 43 43: def with_local_cache 44: save_val = Thread.current[thread_local_key] 45: begin 46: Thread.current[thread_local_key] = LocalStore.new 47: yield 48: ensure 49: Thread.current[thread_local_key] = save_val 50: end 51: end


General working
Domain names
(automatically initialized)
- fasterized.com
- point to the platform by default (demo/preview mode)
- point to the platform or the origin if config exists
- fasterized.net
- always point to the platform
- fasterize.it
- point to the origin server
- s0.frz.io / s1.frz.io
- sharded domains that are used for static objects
- point to the platform or CDN
Other features
- URL versionning
- Mobile/tablet redirect
Broken page
- Test origin without Fasterize
- See detailed procedure on support site
Debug parameters
Use debug parameters in querystring
?frz-all=false
to disable all optimizations on a page
?frz-[rule]=false
to disable a rule on a page
?frz-[rule]-[option]=false
to disable a rule option on a page
?frz-persist-[rule]=false
to disable a rule for the session
- List of rules here
Unable to get client IP
- Used by analytics or fraud detection solutions
- Every request coming to origin servers have IP address of Fasterize servers
- Fasterize put client IP address in HTTP header
X-Forwarded-For
/True-Client-IP
- You must configure your tool to use these headers instead
- See details here
Error page: 'Couldn't find origin server...'
Images are degraded
Due to compression, some images (shaded colours for example) can be too heavily changed
- Exclude images from compression
- Exclude images globally
- Disable agressive PNG compression
- Increase compression quality
- Disable image compression
If Fasterize platform is down
.fasterized.com domain is bound to Cedexis and dynamic.
- Requests are automatically redirected to the origin servers
- You can see http://status.fasterize.com/ to follow the platform status live
For advanced users
frz-debug=true
enters debug mode
- unminified Fasterize scripts
- displays informations
- set the log level to DEBUG
- HTTP headers (
curl -X GET -I http://www.mysite.com
)
x-unique-id
useful to track a request
x-fstrz
to understand what happened to the request (see detailed meaning on this page)
And if you can't manage ...
Contact support at<EMAIL_ADDRESS>Contact support as well to:
- Inform of a global redesign
- Inform of a SSL certificate expiration
- Inform of a server migration


About Us
What is offercrunch.co.uk?
Offercrunch is a special offer aggregator. We look at the major retailers in the UK, find everything on offer and display it here for you.
How often is offercrunch updated?
Offercrunch is updated daily - we are working on updating the site more frequently so check back soon.
I have some feedback for the site
Why was the price different on the retailer's site?
On rare occasions the retailer will change the price before we have updated the site
I have a problem with the product I bought, what should I do?
Please contact the retailer you bought the product from
Are more product categories/retailers coming?
We are constantly adding extra retailers and have plans to add other categories in the future
Where are the icons on the homepage from?
Icons are by Housin Aziz and others at The Noun Project


Monday 23 July
hours:
work:
TSN Portal =>
Bugs 1129
Tuesday 31 July
hours:
- 12:00 AM => 2:00 AM
- 11:00 AM => 2:00 PM
work:
TSN Portal =>
Bugs 1144
Tuesday 7 August
hours:
work:
ASI Portal =>
Changesets 2736, 2737
Sunday 12 August
hours:
work:
ASI Portal =>
Bugs 1148, 1158
Monday 13 August
hours:
work:
ASI Portal =>
Bugs 1159


I’m currently a senior studying Computer Science at Virginia Tech’s College of Engineering.
I’ve had the pleasure of collaborating with great colleagues over the years, and I’m currently looking to work with a driven team looking to change the world one line of code at a time! You can take a look at my resume here!
In my free time, you can see me staying active at the gym, on a run, or on a wrestling mat! I love to game and hangout with my friends, and I’m always down to get a cup of coffee at any time. Check out what I’m up to with the links below!


{if condition = "$auth->check('shopro/wechat/menu/publish')"}
发布
{/if}
{if condition = "$auth->check('shopro/wechat/menu/edit')"}
编辑
{/if}
{if condition = "$auth->check('shopro/wechat/menu/copy')"}
复制
{/if}
{if condition = "$auth->check('shopro/wechat/menu/del')"}
删除
{/if}


It is fairly easy to roll your own template solution. You just need to traverse
the DOM and replaces string with a specific prefix and suffix, for instance
{{
and }}
with some other string.
Here is an example (make sure to show the developer console).
NodeList
and NamedNodeMap
. It can easily be changed
into for loops if support for IE6/7/8 is required.
NodeList.prototype.forEach = Array.prototype.forEach;
NamedNodeMap.prototype.forEach = Array.prototype.forEach;