How economists cite literature: citation analysis of two core Pakistani economic journals

Selected volumes of the Pakistan Development Review (PDR) and the Pakistan Economic and Social Review (PESR) were analysed to find the citation pattern of their articles. Eight volumes of each journal were selected, two volumes representing a decade. The results revealed that the PDR has been the most cited journal. The mean score of citations per article remained insignificantly different in the two core journals. More than 50 per cent of the citations from both journals were single-authored. More than 50 per cent of the citations were from non-journal sources, mainly books. Although citations from online sources were seen, it was a negligible number. About 47 per cent of the total citations of the PDR were up to five years old compared with the citations of the PESR, where only 25 per cent fell into this category. Most of the authors used foreign books as citations. There is a significant similarity in the top most cited journals in both cases. Most of the frequently cited journals were from the USA

Impact of computer training on professional library activities in Pakistan

Report on a survey of alumni of the Pakistan Library Association’s Computer Training Center in Lahore to determine the impact of the Certificate in Library Automation (CLA) on librarianship in Pakistan. The survey provided information on: the profile of the respondents; their participation in computer training before and after taking the CLA; the impact of their training on their success in job seeking; their access to and use of computers; their participation in library automation projects and other auto-mation related activities; and suggestions regarding further courses and the improvement of the Training Centre. The results showed that the courses were attended mainly by comparatively young professional librarians, most of whom were working in Lahore. Their computer training contributed a lot to their success in getting new jobs. Most of them had access to computer facilities in their offices and use them daily, and have participated significantly in automation activities in their libraries. Many also applied their computing knowledge in writing books, articles, delivering lectures and providing consultancy services. Many suggestions were made for improving the courses

Finding common support and assessing matching methods for causal inference

Doctor of PhilosophyDepartment of StatisticsMichael J. HigginsThis dissertation presents an approach to assess and validate causal inference tools to es- timate the causal effect of a treatment. Finding treatment effects in observational studies is complicated by the need to control for confounders. Common approaches for controlling include using prognostically important covariates to form groups of similar units containing both treatment and control units or modeling responses through interpolation. This disser- tation proposes a series of new, computationally efficient methods to improve the analysis of observational studies. Treatment effects are only reliably estimated for a subpopulation under which a common support assumption holds—one in which treatment and control covariate spaces overlap. Given a distance metric measuring dissimilarity between units, a graph theory is used to find common support. An adjacency graph is constructed where edges are drawn between similar treated and control units to determine regions of common support by finding the largest connected components (LCC) of this graph. The results show that LCC improves on existing methods by efficiently constructing regions that preserve clustering in the data while ensuring interpretability of the region through the distance metric. This approach is extended to propose a new matching method called largest caliper matching (LCM). LCM is a version of cardinality matching—a type of matching used to maximize the number of units in an observational study under a covariate balance constraint between treatment groups. While traditional cardinality matching is an NP-hard, LCM can be completed in polynomial time. The performance of LCM with other five popular matching methods are shown through a series of Monte Carlo simulations. The performance of the simulations is measured by the bias, empirical standard deviation and the mean square error of the estimates under different treatment prevalence and different distributions of covariates. The formed matched samples improve estimation of the population treatment effect in a wide range of settings, and suggest cases in which certain matching algorithms perform better than others. Finally, this dissertation presents an application of LCC and matching methods on a study of the effectiveness of right heart catheterization (RHC) and find that clinical outcomes are significantly worse for patients that undergo RHC

Antecedents of self-disclosure on social networking sites (SNSs): A study of Facebook users

Self-disclosure on social networking sites (SNSs) leads to social capital development, connectedness, and relationship building. Due to several benefits associated with this behavior, self-disclosure has become a subject of research over the last few years. The current study investigates the antecedents of self-disclosure under the lens of the technology acceptance model (TAM). The research is quantitative, and the data were collected from 400 Pakistani Facebook users with a variety of demographic characteristics. The partial least squares-structural equation model (PLS-SEM) analysis technique was employed to analyze the data. The study′s findings confirmed that perceived usefulness is a strong predictor of personal information sharing, and it along with other variables causes a 31% variation in self-disclosure behavior. However, trust (medium and social) mediates the relationship of perceived usefulness, privacy concerns, and self-disclosure behavior

A citation analysis of Pakistan Economic and Social Review

Selected volumes of Pakistan Economic and Social Review were analyzed to find out citation pattern of their articles. Eight volumes of the journal were selected representation two volumes from a decade. The results revealed that a peer local journal Pakistan Development Review has been the most cited journal in the cited literature under study. Sixty percent of the citations were single-authored. More than 50 percent of the citations were from non-journal sources maintly books. Although citations from onoine sources were seen but in a negligible number. The age of about 25 percent of the total citations was five years. Most of the authors used foreign books as citations. Most the greatly cited journals were from the USA

2-(4-Acetamido­benzene­sulfonamido)­benzoic acid

In the title compound, C15H14N2O5S, two similar mol­ecules comprise the asymmetric unit, which are linked by strong inter­molecular C—H⋯π inter­actions. Both mol­ecules are bent, with dihedral angles of 71.94 (16) and 74.62 (15)° between the benzene rings. An intra­molecular N—H⋯O hydrogen bond occurs in each mol­ecule. In the crystal, inter­molecular N—H⋯O and O—H⋯O hydrogen bonds link the mol­ecules into a three-dimensional network

Scalable Verification of GNN-based Job Schedulers

Recently, Graph Neural Networks (GNNs) have been applied for scheduling jobs over clusters, achieving better performance than hand-crafted heuristics. Despite their impressive performance, concerns remain over whether these GNN-based job schedulers meet users' expectations about other important properties, such as strategy-proofness, sharing incentive, and stability. In this work, we consider formal verification of GNN-based job schedulers. We address several domain-specific challenges such as networks that are deeper and specifications that are richer than those encountered when verifying image and NLP classifiers. We develop vegas, the first general framework for verifying both single-step and multi-step properties of these schedulers based on carefully designed algorithms that combine abstractions, refinements, solvers, and proof transfer. Our experimental results show that vegas achieves significant speed-up when verifying important properties of a state-of-the-art GNN-based scheduler compared to previous methods.Comment: Condensed version published at OOPSLA'2