Miracle-dz/UniFAR-FTUs huggingface dataset:
User Assisted Data Structure Debugging and Verication

Data structures are one of the most important part of programming. Program faults lead tocorruption of runtime data structures of the program which lead to program failure or worse wrong output. Such kind of bugs are hard to debug using traditional debugging techniques. Specification based debugging techniques have been useful in solving such bugs with limited effectiveness. Debugging is one of the most costly part of software development process both in terms of time and man-power. On the other hand, verification compliments debuggingby providing guarantee of correctness. Therefore, automatic debugging and verificationtechniques greatly increase the productivity of the programmer. This dissertation concentrates on the techniques for debugging and verification of data-structures. Firstly, we propose an efficient and precise fault location framework for single threaded application. The framework includes a compact memory graph representation to store data structure evolution history, a specification language for user to simply specify data structure constraints and a precise fault location method. Secondly, we propose a linearizability verification technique for concurrent data-structures. Our verification technique is both sound and generic. We are able to verifymore concurrent data structures linearizable than any other state of the art linearizabilityverication technique.
mPneumonia: Development of an Innovative mHealth Application for Diagnosing and Treating Childhood Pneumonia and Other Childhood Illnesses in Low-Resource Settings

Pneumonia is the leading infectious cause of death in children worldwide. Each year, pneumonia kills an estimated 935,000 children under five years of age, with most of these deaths occurring in developing countries. The current approach for pneumonia diagnosis in low-resource settings—using the World Health Organization Integrated Management of Childhood Illness (IMCI) paper-based protocols and relying on a health care provider’s ability to manually count respiratory rate—has proven inadequate. Furthermore, hypoxemia—a diagnostic indicator of the presence and severity of pneumonia often associated with an increased risk of death—is not assessed because pulse oximetry is frequently not available in low-resource settings. In an effort to address childhood pneumonia mortality and improve frontline health care providers’ ability to diagnose, classify, and manage pneumonia and other childhood illnesses, PATH collaborated with the University of Washington to develop “mPneumonia,” an innovative mobile health application using an Android tablet. mPneumonia integrates a digital version of the IMCI algorithm with a software-based breath counter and a pediatric pulse oximeter. We conducted a design-stage usability field test of mPneumonia in Ghana, with the goal of creating a user-friendly diagnostic and management tool for childhood pneumonia and other childhood illnesses that would improve diagnostic accuracy and facilitate adherence by health care providers to established guidelines in low-resource settings. The results of the field test provided valuable information for understanding the usability and acceptability of mPneumonia among health care providers, and identifying approaches to iterate and improve. This critical feedback helped ascertain the common failure modes related to the user interface design, navigation, and accessibility of mPneumonia and the modifications required to improve user experience and create a tool aimed at decreasing mortality from pneumonia and other childhood illnesses in low-resource settings.
Wnt genes define distinct boundaries in the developing human brain: Implications for human forebrain patterning

Understanding the factors that govern human forebrain regionalization along the dorsal–ventral and left–right (L‐R) axes is likely to be relevant to a wide variety of neurodevelopmental and neuropsychiatric conditions. Recent work in lower vertebrates has identified several critical signaling molecules involved in embryonic patterning along these axes. Among these are the Wingless‐Int (WNT) proteins, involved in the formation of dorsal central nervous system (CNS) structures, as well as in visceral L‐R asymmetry. We examined the expression of WNT2b and WNT7b in the human brain, because these genes have highly distinctive expression patterns in the embryonic mouse forebrain. In the human fetal telencephalon, WNT2b expression appears to define the cortical hem, a dorsal signaling center previously characterized in mouse, which is also confirmed by BMP7 expression. In diencephalon, WNT2b expression is restricted to medial dorsal structures, including the developing pineal gland and habenular nucleus, both implicated in CNS L‐R asymmetry in lower organisms. At 5 weeks gestation, WNT7b is expressed in cerebral cortical and diencephalic progenitor cells. As the cortical plate develops, WNT7b expression shifts, demarcating deep layer neurons of the neocortex and the hippocampal formation. Spatial and temporal expression patterns show startling similarity between human and mouse, suggesting that the developmental roles of these WNT genes may be highly conserved, despite the far greater size and complexity of the human forebrain. J. Comp. Neurol. 474:276–288, 2004. © 2004 Wiley‐Liss, Inc.
Downregulation of miRNA-638 promotes angiogenesis and growth of hepatocellular carcinoma by targeting VEGF

The expression and function of microRNA-638 (miR-638) in hepatocellular carcinoma (HCC) remained unknown. Using the miRNA target prediction tools, we predicted that the vascular endothelial growth factor (VEGF) might be a direct target of miR-638. The aim of this study was to test the hypothesis that downregulation of miRNA-638 promotes angiogenesis and growth of HCC by targeting the VEGF signaling pathway. We found that miR-638 was significantly downregulated in HCC cells and clinical HCC specimens, and miR-638 levels were inversely correlated with tumor size, portal vein invasion and poor prognosis. Overexpression of miR-638 inhibited the processes of tumor angiogenesis in vitro and in vivo. The xenograft mouse model experiments showed miR-638 repressed tumor growth of HCC in vivo. Using a luciferase reporter assay, we identified VEGF as a direct target of miR-638. Subsequent investigation revealed that miR-638 expression was inversely correlated with VEGF expression in human HCC samples. Taken together, these results suggested that miR-638 is a novel therapeutic target for HCC and overexpression of miR-638 could suppress angiogenesis and tumor growth of HCC by inhibiting VEGF signaling.
Report of the Admission of Women to the U.S. Military Academy (Project Athena IV)

Abstract : This report provides a summary on the analysis of coeducation at West Point from June 1979 to June 1980. Included are highlights of individual research projects conducted to understand better the integration process. The document is organized into six parts. The first four parts relate to a specific concept for cadet development: military, physical, intellectual, and moral. The fifth part deals with cadet social development. The last part describes plans for future research on post-graduation performance and adjustment. The monograph concludes that women have been effectively integrated into the Corps of Cadets and all graduates are being prepared to lead in an Army which requires the integrated services of men and women.
Exome Sequencing to Detect Rare Variants Associated With General Cognitive Ability: A Pilot Study

Variation in human cognitive ability is of consequence to a large number of health and social outcomes and is substantially heritable. Genetic linkage, genome-wide association, and copy number variant studies have investigated the contribution of genetic variation to individual differences in normal cognitive ability, but little research has considered the role of rare genetic variants. Exome sequencing studies have already met with success in discovering novel trait-gene associations for other complex traits. Here, we use exome sequencing to investigate the effects of rare variants on general cognitive ability. Unrelated Scottish individuals were selected for high scores on a general component of intelligence (g). The frequency of rare genetic variants (in n = 146) was compared with those from Scottish controls (total n = 486) who scored in the lower to middle range of the g distribution or on a proxy measure of g. Biological pathway analysis highlighted enrichment of the mitochondrial inner membrane component and apical part of cell gene ontology terms. Global burden analysis showed a greater total number of rare variants carried by high g cases versus controls, which is inconsistent with a mutation load hypothesis whereby mutations negatively affect g. The general finding of greater non-synonymous (vs. synonymous) variant effects is in line with evolutionary hypotheses for g. Given that this first sequencing study of high g was small, promising results were found, suggesting that the study of rare variants in larger samples would be worthwhile.
Simulation of the nucleation of the precipitate Al3Sc in an Aluminum Scandium alloy using the kinetic Monte Carlo method

This paper describes the simulation of the phenomenon of nucleation of the precipitate Al3Sc in an Aluminum Scandium alloy using the kinetic Monte Carlo (kMC) method and the density-based clustering with noise (DBSCAN) method to filter the simulation data. To conduct this task, kMC and DBSCAN algorithms were implemented in C language. The study covers a range of temperatures, concentrations, and dimensions, going from 573K to 873K, 0.25% to 5%, and 50×50×50 to 100×100×100. The Al3Sc precipitation was successfully simulated at the atomistic scale. DBSCAN revealed to be a valorous aid to identify the precipitates. The achieved results are in good agreement with those reported in the literature, but we went deeper in the evaluation of the influence of all the simulation and analysis parameters.
Contextualized early failure characterization of cantilever snap assemblies

Failure detection and correction is essential in robust systems. In robotics, failure detection has focused on traditional parts assembly, tool breakage, and threaded fastener assembly. However, not much work has focused on classifying failure into various sub-modes. This is an important step in order to provide accurate failure recovery. Our work implemented a contextualized failure characterization scheme for cantilever snap assemblies. A rule based approach was used through which assemblies whose trajectories deviated from the normal approach trajectory were identified in the beginning of the task. We not only identified failure but also the failure type that occurred. The method identified exemplars that characterized salient features for specific deviations from the initial approach trajectory in the assembly task. A contact-state map was generated through sampling the contact space during training. Contextualized statistical measures were used to classify trials during the testing phase. Our work classified failure deviations with 88% accuracy. According to the statistic measures used, varying success was experienced in correlating failure deviation modes. Each case was analyzed using gaussian statistics and one and two standard deviations. Cases with trajectory deviations in one direction had {75%, 92%} accuracy, cases with deviations in two directions had {61%, 94%} accuracy, and cases with deviations in three directions had {69%, 100%} accuracy. Our work provides further insights into the early failure characterization of complex geometrical parts which will serve to implement failure recovery techniques in the face of significant and unexpected errors.
Kalman filter based system identification exploiting the decorrelation effects of linear prediction

In system identification one problem is the autocorrelation of the excitation signal which often crucially affects the adaptation process. This paper focuses on the Kalman filter based adaptation working in the frequency domain and the implication due to correlated signal input. Principle simulations and the introduction of a reference model indicate to which extent correlation take effect. The experimental results demonstrate that even though the Kalman approach already takes advantage from a certain level of inherent decorrelation, it also benefits from additional decorrelation. To address this issue, we derive a new realizable efficient structure combining the Kalman filter based adaptation with linear prediction techniques. The performance gains of the proposed approach are confirmed via experiments for an acoustic echo cancellation application for different scenarios.
Directional Antenna at Sink (DAaS) to prolong network lifetime in Wireless Sensor Networks

We investigate the effect of a directional antenna in wireless sensor networks from the perspective of network lifetime extension. Previous studies on wireless sensor networks have assumed only an omni-directional antenna model, since a directional antenna has been considered inappropriate for sensors due to size and cost constraints. In this sense, we propose to mount the directional antenna only on a designated gateway node, so called a sink, which has more energy and computational power to handle a large volume of data. With a directional antenna, the sink's communication range is extended and hence the number of neighbor nodes in the communication range increases. Since these neighbor nodes relay data toward the sink, they tend to deplete their energy more quickly than other nodes. Directional Antenna at Sink (DAaS) prolongs the network lifetime by increasing the number of neighbor nodes of the sink. To realize DAaS, we propose a sink beam pattern scheduling algorithm, which coordinates MAC layer wakeup/sleep schedules of the sink and the neighbor nodes according to the directional antenna's beam pattern schedule. The above scheduling algorithm minimizes the duty-cycle and hence saves more energy of the sink's neighbor nodes. Through extensive simulation experiments, we observe significant improvement of network lifetime with DAaS as the number of beam patterns increases.
A Robust Reinforcement Learning System Using Concept of Sliding Mode Control for Unknown Nonlinear Dynamical System

In this chapter, a novel control method using a reinforcement learning (RL) (Sutton and Barto (1998)) with concept of sliding mode control (SMC) (Slotine and Li (1991)) for unknown dynamical system is considered. In designing the control system for unknown dynamical system, there are three approaches. The first one is the conventional model-based controller design, such as optimal control and robust control, each of which is mathematically elegant, however both controller design procedures present a major disadvantage posed by the requirement of the knowledge of the system dynamics to identify and model it. In such cases, it is usually difficult to model the unknown system, especially, the nonlinear dynamical complex system, to make matters worse, almost all real systems are such cases. The second one is the way to use only the soft-computing, such as neural networks, fuzzy systems, evolutionary systems with learning and so on. However, in these cases it is well known that modeling and identification procedures for the dynamics of the given uncertain nonlinear system and controller design procedures often become time consuming iterative approaches during parameter identification and model validation at each step of the iteration, and in addition, the control system designed through such troubles does not guarantee the stability of the system. The last one is the way to use the method combining the above the soft-computing method with the model-based control theory, such as optimal control, sliding mode control (SMC), H∞ control and so on. The control systems designed through such above control theories have some advantages, that is, the good nature which its adopted theory has originally, robustness, less required iterative learning number which is useful for fragile system controller design not allowed a lot of iterative procedure. This chapter concerns with the last one, that is, RL system, a kind of soft-computing method, supported with robust control theory, especially SMC for uncertain nonlinear systems. RL has been extensively developed in the computational intelligence and machine learning societies, generally to find optimal control policies for Markovian systems with discrete state and action space. RL-based solutions to the continuous-time optimal control problem have been given in Doya (Doya (2000). The main advantage of using RL for solving optimal
POLLEN TRANSFER BY HUMMINGBIRDS AND BUMBLEBEES, AND THE DIVERGENCE OF POLLINATION MODES IN PENSTEMON

Abstract We compared pollen removal and deposition by hummingbirds and bumblebees visiting bird-syndrome Penstemon barbatus and bee-syndrome P. strictus flowers. One model for evolutionary shifts from bee pollination to bird pollination has assumed that, mostly due to grooming, pollen on bee bodies quickly becomes unavailable for transfer to stigmas, whereas pollen on hummingbirds has greater carryover. Comparing bumblebees and hummingbirds seeking nectar in P. strictus, we confirmed that bees had a steeper pollen carryover curve than birds but, surprisingly, bees and birds removed similar amounts of pollen and had similar per-visit pollen transfer efficiencies. Comparing P. barbatus and P. strictus visited by hummingbirds, the bird-syndrome flowers had more pollen removed, more pollen deposited, and a higher transfer efficiency than the bee-syndrome flowers. In addition, P. barbatus flowers have evolved such that their anthers and stigmas would not easily come into contact with bumblebees if they were to forage on them. We discuss the role that differences in pollination efficiency between bees and hummingbirds may have played in the repeated evolution of hummingbird pollination in Penstemon.
Systematic Review of Mutations in Pyrazinamidase Associated with Pyrazinamide Resistance in Mycobacterium tuberculosis Clinical Isolates

ABSTRACT Pyrazinamide (PZA) is an important first-line drug in the treatment of tuberculosis (TB) and of significant interest to the HIV-infected community due to the prevalence of TB-HIV coinfection in some regions of the world. The mechanism of resistance to PZA is unlike that of any other anti-TB drug. The gene pncA, encoding pyrazinamidase (PZase), is associated with resistance to PZA. However, because single mutations in PZase have a low prevalence, the individual sensitivities are low. Hundreds of distinct mutations in the enzyme have been associated with resistance, while some only appear in susceptible isolates. This makes interpretation of molecular testing difficult and often leads to the simplification that any PZase mutation causes resistance. This systematic review reports a comprehensive global list of mutations observed in PZase and its promoter region in clinical strains, their phenotypic association, their global frequencies and diversity, the method of phenotypic determination, their MIC values when given, and the method of MIC determination and assesses the strength of the association between mutations and phenotypic resistance to PZA. In this systematic review, we report global statistics for 641 mutations in 171 (of 187) codons from 2,760 resistant strains and 96 mutations from 3,329 susceptible strains reported in 61 studies. For diagnostics, individual mutations (or any subset) were not sufficiently sensitive. Assuming similar error profiles of the 5 phenotyping platforms included in this study, the entire enzyme and its promoter provide a combined estimated sensitivity of 83%. This review highlights the need for identification of an alternative mechanism(s) of resistance, at least for the unexplained 17% of cases.
Retrolental fibroplasia; incidence in different localities in recent years and a correlation of the incidence with treatment given the infants.

Retrolental fibroplasia (R. L. F.) is an ocular disease usually associated with prematurity and usually affecting both eyes. The most conspicuous diagnostic sign is the presence of a membrane, often vascularized, situated behind the crystalline lens. The presence of blood vessels in the membrane serves to differentiate retrolental fibroplasia from congenital cataract. The affected eye may be smaller than normal, the anterior chamber shallow and the ciliary body abnormally serrated. Secondary changes, such as synechiae, glaucoma and iritis, frequently develop. The disease is rarely, if ever, seen at birth but develops when the infant is between 1 and 5 months of age. It has been seen to start as a dilatation of the retinal vessels followed by exudative retinitis and subsequent retinal detachment.1 Retrolental fibroplasia was first associated with prematurity by Terry2in 1942. Since then there have been indications that the incidence has increased more in some
Interplay between plasma oxidative status, cortisol and coping styles in wild alpine marmots, Marmota marmota

SUMMARY Variation in how individuals cope behaviourally and physiologically with stressors is widespread and can have a significant impact on life-history traits and fitness. Individual coping styles are characterised by differential behavioural and adrenocortical reactivity to various challenges. As stress hormones can affect the production of reactive chemical species and the antioxidant status, individuals with different coping styles may differ also in oxidative status. Field studies on wild mammalian populations are few in number and none so far has simultaneously tested the relationship between coping style, adrenocortical reactivity and oxidative status in the same individuals. We measured individual variation in coping styles along a proactive-reactive continuum together with variation in baseline and stress-induced plasma oxidative damage, plasma non-enzymatic antioxidant capacity and cortisol in wild alpine marmots, Marmota marmota. Confirmatory path analysis revealed that different coping styles are accompanied by different baseline and stress-induced plasma oxidative statuses. Our findings also highlight the potential role of cortisol as a mediator of such differences.
A cloud security framework for a data centric WSN application

Data centric applications like remote healthcare application designed on a WSN-Cloud computing integrated architecture requires attention to its secure data management mechanism. A huge amount of data is generated in a health care application, which needs to be managed efficiently so that fast and reliable data communication and access can take place among the end users. In this research work we have proposed a flexible security model especially for data centric applications in cloud computing based scenario. This security model ensures data confidentiality, data integrity and fine grained access control to the application data. The objective of this work is to propose a secure framework to assist users at remote locations by considering the interoperability among different security solutions.