Miracle-dz/UniFAR-FTUs huggingface dataset:
UCOM offline dataset-an urdu handwritten dataset generation

A benchmark database for character recognition is an essential part for efficient and robust development. Unfortunately, there is no comprehensive handwritten dataset for Urdu language that would be used to compare the state of the art techniques in the field of optical character recognition. In this paper, we present a new and publically available dataset comprising 600 pages of handwritten Urdu text written in Nasta’liq style in conjunction with detailed ground truth for the evaluation of handwritten Urdu character recognition. This dataset contains text lines written in Nasta’liq style by limited individuals on A4 size paper. The acquired data on page was scanned and text lines were segmented. UCOM database covers all Urdu characters and ligatures with different variation in addition to Urdu numeric data. We have considered that ligature consists of up to five characters in this dataset. The UCOM dataset can be used for handwritten character recogntition as well as writer identification. We proposed and evaluated the strength of Recurrent Neural Networks (RNN) on UCOM offline database sample text line.
Dynamic variability examination of frontogenesis: teleconnection of fronts and flood 2010

Approach for the detection of frontal activities with satellite imagery is proposed, based on the identification of cloud pattern, thermal gradient and water content of air masses using Meteosat-7 satellite imagery. Owing to highly variable nature of fronts, spatial shift occurring over 1.5 years are analysed. Full disc imagery of Meteosat-7 satellite is used for the analysis over vast geographical distribution of Eurasia. The study examined the fundamental characteristics of fronts and effects associated with fronts with the analysis for the flood event of 2010 in Pakistan. The results show seasonal as well as annual change in the range of lower and upper latitudinal limits of frontogenesis. Seasons of winter 2011 show an increase in speed whereas a decrease is observed in summer. The identification process has shown a frontal span over northern areas of Pakistan during flood event of 2010 accentuating the monsoonal rainfall intensity all over the country. The result of this analysis can be used to estimate the behaviour of the mid-latitudes global circulations. The anticipated outcome of this research study is the identification of abrupt nature of frontal processes.
An indoor self-localization algorithm using the calibration of the online magnetic fingerprints and indoor landmarks

Personal dead reckoning (PDR) localization technology can provide effective and critical assistance for public security, such as emergency rescue or anti-terror training in the indoor or underground environment without the need of deploying additional positioning infrastructure. However, the PDR suffers from the severe position error accumulation with time due to the inaccurate step length and moving direction estimation. To improve the self-positioning accuracy, this paper proposed a novel indoor self-localization algorithm using two kinds of automatic calibration methods, i.e., opportunistic magnetic trajectory matching and indoor landmark identification. Extensive experiments performed in two representative indoor environments, including an office building and a supermarket, demonstrate that the proposed self-localization algorithm can obtain an 80 percentile localization accuracy of 1.4m and 2m in the two representative indoor environments, respectively, which outperforms the art-of-the-state PDR algorithms.
Forward reachable sets: Analytically derived properties of connected components for dynamic networks

Abstract Formal analysis of the emergent structural properties of dynamic networks is largely uncharted territory. We focus here on the properties of forward reachable sets (FRS) as a function of the underlying degree distribution and edge duration. FRS are defined as the set of nodes that can be reached from an initial seed via a path of temporally ordered edges; a natural extension of connected component measures to dynamic networks. Working in a stochastic framework, we derive closed-form expressions for the mean and variance of the exponential growth rate of the FRS for temporal networks with both edge and node dynamics. For networks with node dynamics, we calculate thresholds for the growth of the FRS. The effects of finite population size are explored via simulation and approximation. We examine how these properties vary by edge duration and different cross-sectional degree distributions that characterize a range of scientifically interesting normative outcomes (Poisson and Bernoulli). The size of the forward reachable set gives an upper bound for the epidemic size in disease transmission network models, relating this work to epidemic modeling (Ferguson, 2000; Eames, 2004).
Automatic false positive canceling for indoor human detection

Humans are the most common mobile obstacles for an office robot. A robust human detector usually plays important roles in robots' perception phase. Especially, Tasks like dynamic path planning and obstacle avoidance have to employ such a detector to help make real-time decisions. Thus, an efficient human detector is meaningful for office robots. However, while deep learning based detectors are not always available in embedded applications, shallow model based ones suffer much from high false positive rates. In this paper, we present a novel approach that can automatically canceling most false positives from shallow detectors. This method regards the detection result as candidates. Then, an algorithm called rival penalized competitive learning is applied to evaluate the inner geometry relationship of each candidate. The one with low evaluation scores, which indicates possible false positives, will be discarded. Experiments show that this approach has the ability to decrease false positive rate of detectors running in office environment.
Teacher Pay and Teacher Quality

Can changes in teacher pay encourage more able individuals to enter the teaching profession? So far, studies of the impact of pay on the aptitude distribution of teachers have provided mixed evidence on the extent to which altering teacher salaries represents a feasible solution to the teacher quality problem. Using a unique dataset of test scores for everyone admitted into an Australian university between 1989 and 2003, I explore how changes in average pay or pay dispersion affect the decision to enter teacher education courses in the eight states and territories that make up Australia. A 1% rise in average teacher pay boosts the average aptitude of students entering teacher education courses by 0.8 percentile ranks, with the effect being strongest for those just above the median. I find some evidence that higher pay variance in teaching also boosts the aptitude of potential teachers.
Distributed primal-dual approximation algorithms for network design problems

We present a simple paradigm for efficient implementation of primal-dual approximation algorithms for several network design problems in the distributed environment. Our approximation ratios are the same as in the centralized primal-dual algorithms, and we establish that our message complexity is close to the best possible. Specifically, we show that the 2-approximation algorithm of [9] for covering an uncrossable set-family by a minimum cost set of edges can be implemented in distributed environment using O(nD) communication rounds and O(n log D) messages, where n is the number of nodes and D is the diameter of the communication network. In particular, within the same communication complexity we obtain: (i) A 2-approximation for Steiner Forest, Point to Point Connection, and T -Join. (ii) A 3-approximation for Survivable Network Design with requirements in {0, 1, 2}. (iii) An O(log k)-approximation for Steiner Network, for constant maximum requirement k. Even for Steiner Forest, the previous best known algorithm [11] had expected ratio O(log n), while using O(Sp log n) rounds and O(|E|S log n) messages, where S ≥ D is the “shortest path diameter” of the network, and p = O(n) is the number of groups in the instance. We also give a 2(k+1)-approximation algorithm for k-Connected Subgraph with metric costs that uses O(log log n) rounds and O(|E|) = O(n) messages, which is optimal. This improves the result of [12] where was given an O(k log n)-approximation algorithm that uses O(log n k ) rounds and O(nk log n k ) expected number of messages.
Adapting to Change in Healthcare: Aligning Strategic Intent and Operational Capacity

The concept of a stakeholder is commonplace in a business context. Participative— democratic communication refers to those organization-wide principles and practices that "represent" many relevant stakeholders in the decision making of work-related activities. One case in point is as follows: In May 2000, the Spartanburg Regional Healthcare System board of directors forced its CEO to resign, ending his 6-year tenure and the heated controversy of the previous 2 months. The former CEO focused primarily on strategic growth to the detriment of operations. Through participative-democratic practices, the interim CEO mended the damaged relations between the hospital administration, the community, and employee stakeholders in surfacing conflict to bolster operational efficiency. The current CEO attended to building stakeholder relationships and trust as a way to wed strategic growth and the organization's capacity to maintain it. Top executive managers and directly involved community political leaders helped in developing the participative-democratic communication principles set forth in this article. These core principles are (a) creating the space for new communicative interaction, (b) safeguarding a credible and open process, and (c) reclaiming suppressed views.
Factors Affecting the Effectiveness of eMentoring Program in Non-profit Organizations

eMentoring is a means of providing a guided mentoring relationship using online software or email as the primary means of communication. The use of eMentoring program involves careful matching of mentors and mentees. This research intends to empirically examine important factors affecting the effectiveness of eMentoring program in non-profit organizations, in particular, the role of matching in the adoption and success of eMentoring program. The research is ongoing at a mid-western US elementary school which has launched a successful eMentoring initiative for two years. The extended abstract here reports the literature review, hypotheses and methodology for our study.
Bioinformatics : Microarrays Analyses and Beyond

We have witnessed in the past years the rapid progresses in the human genome project and biotechnologies. These advances result in many complex datasets associated with indepth scientific knowledge, e.g., genome sequences of many species, microarray expression profiles of different cell lines, single nucleotide polymorphisms (SNPs) in the human genome, etc. These data together with their underlying scientific challenges spawn the new field of Bioinformatics, which sprawls many academic disciplines as well as the pharmaceutical industry, and create one of the most exciting times for all quantitative researchers. There is no doubt that statistics will be pivotal in this new field, but it remains a challenge to us statisticians whether we can play a leading role in this biology and informatics revolution. This is not just a challenge, in fact, but also a golden opportunity for our discipline.
Prevalence of Microalbuminuria in Older-Onset Diabetes

OBJECTIVE To examine the prevalence of microalbuminuria and the relationships of microalbuminuria to blood pressure and other risk factors. RESEARCH DESIGN AND METHODS Individuals diagnosed with diabetes at ≥30 yr of age either taking insulin (n = 435) or not taking insulin (n = 363), who were participants in the population-based Wisconsin Epidemiologic Study of Diabetic Retinopathy, were examined during 1984-1986. Random urine samples were collected and an agglutination inhibition test was used to determine the presence of microalbuminuria, which is defined as ≥0.03 g/L but <0.3 g/L. RESULTS The frequency of microalbuminuria was 29.2% in those individuals taking insulin and 22.0% in those not taking insulin. Microalbuminuria was significantly associated with the male sex, older age, higher systolic blood pressure, higher GHb, use of insulin, higher recent alcohol consumption, and a history of cardiovascular disease. CONCLUSIONS These findings suggest a relationship between controllable risk factors, blood pressure and GHb, and microalbuminuria in older-onset diabetic individuals.
Automated SubCellular Phenotype Classification : An Introduction and Recent Results

The genomic sequencing revolution has led to rapid growth in sequencing of genes and proteins, and attention is now turning to the function of the encoded proteins. In this respect, microscope imaging of a protein’s subcellular location is proving invaluable. High-throughput methods mean that it is now possible to capture images of hundreds of protein localisations quickly and relatively inexpensively, and hence genome-wide protein localisation studies are becoming feasible. However, to a large degree the analysis and localisation classification are still performed by the slow, coarse-grained and possibly biased process of manual inspection. As a step towards dealing with the fast growth in subcellular image data the Automated Sub-cellular Classification system (ASPiC) has been developed: a pipeline for taking cell images, generating statistics and classifying using SVMs. Here, the pipeline is described and correct classification rates of 93.5% and 86.5% on two 8-class subcellular localisation datasets are reported. In addition we present a survey of other important applications of cell image statistics. The complete image sets are being made available with the aim of encouraging further research into automated cell image analysis and classification.
Microsatellite loci in the tiger shark and cross-species amplification using pyrosequencing technology

The tiger shark (Galeocerdo cuvier) has a global distribution in tropical and warm temperate seas, and it is caught in numerous fisheries worldwide, mainly as bycatch. It is currently assessed as near threatened by the International Union for Conservation of Nature (IUCN) Red List. In this study, we identified nine microsatellite loci through next generation sequencing (454 pyrosequencing) using 29 samples from the western Atlantic. The genetic diversity of these loci were assessed and revealed a total of 48 alleles ranging from 3 to 7 alleles per locus (average of 5.3 alleles). Cross-species amplification was successful at most loci for other species such as Carcharhinus longimanus, C. acronotus and Alopias superciliosus. Given the potential applicability of genetic markers for biological conservation, these data may contribute to the population assessment of this and other species of sharks worldwide.
A learning market-maker in the Glosten–Milgrom model

This paper develops a model of a learning market-maker by extending the Glosten-Milgrom model of dealer markets. The market-maker tracks the changing true value of a stock in settings with informed traders (with noisy signals) and liquidity traders, and sets bid and ask prices based on its estimate of the true value. We empirically evaluate the performance of the market-maker in markets with different parameter values to demonstrate the effectiveness of the algorithm, and then use the algorithm to derive properties of price processes in simulated markets. When the true value is governed by a jump process, there is a two regime behaviour marked by significant heterogeneity of information and large spreads immediately following a price jump, which is quickly resolved by the market-maker, leading to a rapid return to homogeneity of information and small spreads. We also discuss the similarities and differences between our model and real stock market data in terms of distributional and time series properties of returns.
Live heap space analysis for languages with garbage collection

The peak heap consumption of a program is the maximum size of the live data on the heap during the execution of the program, i.e., the minimum amount of heap space needed to run the program without exhausting the memory. It is well-known that garbage collection (GC) makes the problem of predicting the memory required to run a program difficult. This paper presents, the best of our knowledge, the first live heap space analysis for garbage-collected languages which infers accurate upper bounds on the peak heap usage of a program's execution that are not restricted to any complexity class, i.e., we can infer exponential, logarithmic, polynomial, etc., bounds. Our analysis is developed for an (sequential) object-oriented bytecode language with a scoped-memory manager that reclaims unreachable memory when methods return. We also show how our analysis can accommodate other GC schemes which are closer to the ideal GC which collects objects as soon as they become unreachable. The practicality of our approach is experimentally evaluated on a prototype implementation. We demonstrate that it is fully automatic, reasonably accurate and efficient by inferring live heap space bounds for a standardized set of benchmarks, the JOlden suite.
Potent and Selective Triazole-Based Inhibitors of the Hypoxia-Inducible Factor Prolyl-Hydroxylases with Activity in the Murine Brain

As part of the cellular adaptation to limiting oxygen availability in animals, the expression of a large set of genes is activated by the upregulation of the hypoxia-inducible transcription factors (HIFs). Therapeutic activation of the natural human hypoxic response can be achieved by the inhibition of the hypoxia sensors for the HIF system, i.e. the HIF prolyl-hydroxylases (PHDs). Here, we report studies on tricyclic triazole-containing compounds as potent and selective PHD inhibitors which compete with the 2-oxoglutarate co-substrate. One compound (IOX4) induces HIFα in cells and in wildtype mice with marked induction in the brain tissue, revealing that it is useful for studies aimed at validating the upregulation of HIF for treatment of cerebral diseases including stroke.
Optimised Virtual Keyboards with and without Alphabetical Ordering - A Novice User Study

Optimised virtual keyboards are potentially efficient and fast for expert users, but they are difficult and slow for novice users due to the visual search requirement. Introducing structure and order to the layout may ease the visual searching process. By means of a Metropolis algorithm with an added alphabetical bias term to the Fitts-digraph energy function previously used (Zhai, Hunter, & Smith, 2000), we designed a keyboard layout with alphabetical ordering tendency with little movement efficiency cost. In contrast to previous efforts that failed to find any alphabetical ordering advantage, our experiment demonstrated that the alphabetical ordering created by our design method indeed improves novice users' performance and was preferred by most participants.
Effect of nebulised l- and d-arginine on exhaled nitric oxide in steroid naive asthma

BACKGROUND Nitric oxide (NO) is a product of the enzyme nitric oxide synthase (NOS) and is found in normal and asthmatic human airways. The administration ofl-arginine results in an increase in airway NO production in asthmatic subjects. This is thought to occur becausel-arginine is the substrate for NOS. However, studies in the systemic vasculature suggest that other mechanisms may be responsible. METHODS Eight patients with steroid naive asthma each received 2.5 g l-arginine, 2.5 g d-arginine, and 2.0% saline by ultrasonic nebuliser on separate days in a randomised, single blind manner. Exhaled NO was measured by chemiluminescence and spirometric tests were performed before and for 3 hours after each administration. The mean concentration of NO after exposure was calculated from the area under the curve. RESULTS l-arginine,d-arginine, and 2.0% saline induced a mean (95% CI) maximal bronchoconstriction of 11.9% (–1.7 to 25.4), 10.0% (2.8 to 17.2), and 8.5% (–2.5 to 19.5) of the starting forced expiratory volume in one second (FEV1), respectively. Exhaled NO declined in proportion to the degree of bronchoconstriction (r=0.60, p<0.01). Bronchoconstriction and the acute reduction in exhaled NO resolved within 15 minutes. The mean post-exposure concentration of NO was 15.75 parts per billion (ppb) after l-arginine, 15.16 ppb after d-arginine, and 12.74 ppb after 2.0% saline. The mean (95% CI) difference between l-arginine and placebo was 3.01 (0.32 to 5.7) ppb, between d-arginine and placebo 2.42 (0.10 to 4.74) ppb, and between l- and d-arginine 0.59 (–1.56 to 2.74) ppb. CONCLUSIONS Exhaled NO decreased with acute bronchoconstriction and returned to baseline with the resolution of bronchoconstriction. Exhaled NO increased following the administration of both l-arginine andd-arginine. Since NOS is stereospecific, this finding suggests that the increase in exhaled NO is not entirely mediated through an increase in NOS enzyme activity. We suggest that arginine may react in a non-stereospecific fashion with reactive oxygen species present in asthmatic airways.
The Genome-Sequenced Variant of Campylobacter jejuni NCTC 11168 and the Original Clonal Clinical Isolate Differ Markedly in Colonization, Gene Expression, and Virulence-Associated Phenotypes

ABSTRACT The genome sequence of the enteric bacterial pathogen Campylobacter jejuni NCTC 11168 (11168-GS) was published in 2000, providing a valuable resource for the identification of C. jejuni-specific colonization and virulence factors. Surprisingly, the 11168-GS clone was subsequently found to colonize 1-day-old chicks following oral challenge very poorly compared to other strains. In contrast, we have found that the original clinical isolate from which 11168-GS was derived, 11168-O, is an excellent colonizer of chicks. Other marked phenotypic differences were also identified: 11168-O invaded and translocated through tissue culture cells far more efficiently and rapidly than 11168-GS, was significantly more motile, and displayed a different morphology. Serotyping, multiple high-resolution molecular genotyping procedures, and subtractive hybridization did not yield observable genetic differences between the variants, suggesting that they are clonal. However, microarray transcriptional profiling of these strains under microaerobic and severely oxygen-limited conditions revealed dramatic expression differences for several gene families. Many of the differences were in respiration and metabolism genes and operons, suggesting that adaptation to different oxygen tensions may influence colonization potential. This correlates biologically with our observation that anaerobically priming 11168-GS or aerobically passaging 11168-O caused an increase or decrease, respectively, in colonization compared to the parent strain. Expression differences were also observed for several flagellar genes and other less well-characterized genes that may participate in motility. Targeted sequencing of the sigma factors revealed specific DNA differences undetected by the other genomic methods. These observations highlight the capacity of C. jejuni to adapt to multiple environmental niches, the likelihood that this adaptation involves genetic evolution, and provides the first whole-genome molecular exploration of the effect of laboratory culture and storage on colonization and virulence properties of this pathogen.