Miracle-dz/UniFAR-FTUs huggingface dataset:
Software Development using the Knowledge Insight Approach By Zehlam Menjoge

MENJOGE, ZEHLAM, Software Development using the Knowledge Insight Approach. (Under the direction of Dr. Thomas L. Honeycutt). Software development processes currently in use often result in the production of low-quality software. The earlier the properties such as quality, security, safety and reliability are addressed during the software development life cycle, the lower is the development cost and the greater is the probability that the end product functions with no unintended consequences. Unclear and inadequate requirements, unexpected problems during implementation, unwise decisions made in the beginning stages of the projects are some of the reasons, due to which changes may be required in the later stages of the project. A good software development model is one which accommodates changes, has the ability to adapt well to them and minimizes budget and schedule overruns. The Knowledge Insight Model (KIM) is an iterative software development process. It is flexible enough to accommodate changes at any point during the software development life cycle. KIM is also a higher abstraction of many of the existing software development processes. It consists of four related models, namely, the Framer, the Maker, the Sharer and the Finder. The Framer is responsible for planning the course of action to be taken and defining the strategies, activities and tasks that are required for developing software. The Maker creates a design from the plan formulated by the Framer, which isimplemented by the Finder. The Sharer defines the ways in which the activities of the Maker and the Finder can be tracked and monitored. In this way, it implements organized activity and separation of duties very effectively. The purpose of this thesis is to perform a comparative analysis of the Knowledge Insight Model with some other commonly used models, namely, the Waterfall Model, the Spiral model, the Rational Unified Process (RUP) and Extreme Programming (XP). These models are representatives of various classes of models. By studying each one of them, an understanding of the classes to which they belong, may be developed. The criteria for comparing them are based on the various aspects such as their structure and usability and the system’s products, property and success models. This analysis serves to evaluate KIM. The results of this analysis show that the KIM is very flexible. It is also suitable for use as a software development model when evolutionary prototyping is required for all sizes of projects. Software Development using the Knowledge Insight Approach
Neural responses to sanction threats in two-party economic exchange

Sanctions are used ubiquitously to enforce obedience to social norms. However, recent field studies and laboratory experiments have demonstrated that cooperation is sometimes reduced when incentives meant to promote prosocial decisions are added to the environment. Although various explanations for this effect have been suggested, the neural foundations of the effect have not been fully explored. Using a modified trust game, we found that trustees reciprocate relatively less when facing sanction threats, and that the presence of sanctions significantly reduces trustee's brain activities involved in social reward valuation [in the ventromedial prefrontal cortex (VMPFC), lateral orbitofrontal cortex, and amygdala] while it simultaneously increases brain activities in the parietal cortex, which has been implicated in rational decision making. Moreover, we found that neural activity in a trustee's VMPFC area predicts her future level of cooperation under both sanction and no-sanction conditions, and that this predictive activity can be dynamically modulated by the presence of a sanction threat.
Topic tracking with time granularity reasoning

Temporal information is an important attribute of a topic, and a topic usually exists in a limited period. Therefore, many researchers have explored the utilization of temporal information in topic detection and tracking (TDT). They use either a story's publication time or temporal expressions in text to derive temporal relatedness between two stories or a story and a topic. However, past research neglects the fact that people tend to express a time with different granularities as time lapses. Based on a careful investigation of temporal information in news streams, we propose a new strategy with time granularity reasoning for utilizing temporal information in topic tracking. A set of topic times, which as a whole represent the temporal attribute of a topic, are distinguished from others in the given on-topic stories. The temporal relatedness between a story and a topic is then determined by the highest coreference level between each time in the story and each topic time where the coreference level between a test time and a topic time is inferred from the two times themselves, their granularities, and the time distance between the topic time and the publication time of the story where the test time appears. Furthermore, the similarity value between an incoming story and a topic, that is the likelihood that a story is on-topic, can be adjusted only when the new story is both temporally and semantically related to the target topic. Experiments on two different TDT corpora show that our proposed method could make good use of temporal information in news stories, and it consistently outperforms the baseline centroid algorithm and other algorithms which consider temporal relatedness.
Stochastic models for document restructuration

Document (re)structuration consists in mapping documents coming from different sources, with different formats, onto a predefined semi-structured format. This generic problem appears in different applications settings like heterogeneous semi-structured databases querying, peer to peer systems, legacy document conversion, XML information retrieval. In the paper, we define the restructuration problem from a document centric perspective and identify the main problems raised by this new problematic. We then consider two restructuration instances: structuring flat documents and learning the correspondence between structured formats. We propose stochastic models for these two tasks and describe tests on a large XML document collection.
Evidence of a Pathway of Reduction in Bacteria: Reduced Quantities of Restriction Sites Impact tRNA Activity in a Trial Set

Occurring naturally along the genomes of many viruses and other pathogens, short palindromic restriction sites (<14bps) are often exploited by bacterial restriction enzymes as autoimmune defenses to end pathogen threats. These motifs may also appear in the host's genome where they are methylated so as not to attract restriction enzymes to the host's genetic material. Since these motifs in the host's genome may pose a significant danger, it is likely that their numbers have been reduced due to possible failures of methylation during evolutionary time. These palindromes are composed of bases likely containing information relating to codons used for protein translation. If palindromes are reduced in the genome, then its sequence composition making up the codons may also be found in reduced quantities. Furthermore, during translation codons are associated with tRNAs for protein fabrication which may also occur in reduced numbers. We suggest that a pathway of reduction that can be followed from the onset of these missing palindromes to the reduction (or absence) of specific tRNAs correlated to the codons from the palindromes. To create evidence for this pathway, we studied the bacterial genomes of Bacillus subtilis, Escherichia coli, Haemophilus influenzae, Methanococcus jannaschii, Mycoplasma genitalium, Synechocystis sp. and Marchantia polymorpha. Across these organisms, we applied statistical data from reduced palindromic populations (biological and non-relevant words) to regression models and performed an analysis of genomic tRNA presence from their compositions. We illustrate a pathway of reduction that extends from palindromes to tRNAs which may follow from evolutionary pressures concerning restriction site handling.
Added pilot semi-blind channel estimation scheme for OFDM in fading channels

An added pilot semi-blind (APSB) scheme used for channel identification of OFDM systems, which have been adopted for DAB and DVB-T, is proposed. This scheme uses pilot symbols that are added directly to the data symbols and hence does not require any additional bandwidth for its implementation. To remove the pilots, a two dimensional Wiener filter is used for the purpose of channel interpolation by using successive iterations. Although its complexity increases with additional iterations, the APSB scheme is found to compare favorably to existing blind schemes proposed for the OFDM system in terms of bit error rate and convergence.
An RND-Type Efflux System in Borrelia burgdorferi Is Involved in Virulence and Resistance to Antimicrobial Compounds

Borrelia burgdorferi is remarkable for its ability to thrive in widely different environments due to its ability to infect various organisms. In comparison to enteric Gram-negative bacteria, these spirochetes have only a few transmembrane proteins some of which are thought to play a role in solute and nutrient uptake and excretion of toxic substances. Here, we have identified an outer membrane protein, BesC, which is part of a putative export system comprising the components BesA, BesB and BesC. We show that BesC, a TolC homolog, forms channels in planar lipid bilayers and is involved in antibiotic resistance. A besC knockout was unable to establish infection in mice, signifying the importance of this outer membrane channel in the mammalian host. The biophysical properties of BesC could be explained by a model based on the channel-tunnel structure. We have also generated a structural model of the efflux apparatus showing the putative spatial orientation of BesC with respect to the AcrAB homologs BesAB. We believe that our findings will be helpful in unraveling the pathogenic mechanisms of borreliae as well as in developing novel therapeutic agents aiming to block the function of this secretion apparatus.
On the Linear Belief Compression of POMDPs: A re-examination of current methods

Belief compression improves the tractability of large-scale partially observable Markov decision processes (POMDPs) by finding projections from high-dimensional belief space onto low-dimensional approximations, where solving to obtain action selection policies requires fewer computations. This paper develops a unified theoretical framework to analyse three existing linear belief compression approaches, including value-directed compression and two non-negative matrix factorisation (NMF) based algorithms. The results indicate that all the three known belief compression methods have their own critical deficiencies. Therefore, projective NMF belief compression is proposed (P-NMF), aiming to overcome the drawbacks of the existing techniques. The performance of the proposed algorithm is examined on four POMDP problems of reasonably large scale, in comparison with existing techniques. Additionally, the competitiveness of belief compression is compared empirically to a state-of-the-art heuristic search based POMDP solver and their relative merits in solving large-scale POMDPs are investigated.
Development and Applications of the Copper-Catalyzed Azide-Alkyne Cycloaddition (CuAAC) as a Bioorthogonal Reaction

The emergence of bioorthogonal reactions has greatly broadened the scope of biomolecule labeling and detecting. Of all the bioorthogonal reactions that have been developed, the copper-catalyzed azide-alkyne cycloaddition (CuAAC) is the most widely applied one, mainly because of its relatively fast kinetics and high efficiency. However, the introduction of copper species to in vivo systems raises the issue of potential toxicity. In order to reduce the copper-induced toxicity and further improve the reaction kinetics and efficiency, different strategies have been adopted, including the development of diverse copper chelating ligands to assist the catalytic cycle and the development of chelating azides as reagents. Up to now, the optimization of CuAAC has facilitated its applications in labeling and identifying either specific biomolecule species or on the omics level. Herein, we mainly discuss the efforts in the development of CuAAC to better fit the bioorthogonal reaction criteria and its bioorthogonal applications both in vivo and in vitro.
Aberrant White Matter Microstructure in Children with 16p11.2 Deletions

Copy number variants (CNVs) of the chromosomal locus 16p11.2, consisting of either deletions or duplications, have been implicated in autism, schizophrenia, epilepsy, and other neuropsychiatric disorders. Since abnormal white matter microstructure can be seen in these more broadly defined clinical disorders, we used diffusion magnetic resonance imaging and tract-based spatial statistics to investigate white matter microstructural integrity in human children with 16p11.2 deletions. We show that deletion carriers, compared with typically developing matched controls, have increased axial diffusivity (AD) in many major central white matter tracts, including the anterior corpus callosum as well as bilateral internal and external capsules. Higher AD correlated with lower nonverbal IQ in the deletion carriers, but not controls. Increases in fractional anisotropy and mean diffusivity were also found in some of the same tracts with elevated AD. Closer examination with neurite orientation dispersion and density imaging revealed that fiber orientation dispersion was decreased in some central white matter tracts. Notably, these alterations of white matter are unlike microstructural differences reported for any other neurodevelopmental disorders, including autism spectrum disorders that have phenotypic overlap with the deletion carriers. These findings suggest that deletion of the 16p11.2 locus is associated with a unique widespread pattern of aberrant white matter microstructure that may underlie the impaired cognition characteristic of this CNV.
Semantic Place Labeling Using a Probabilistic Decision List of AdaBoost Classifiers

The success of mobile robots relies on the ability to extract from the environment additional information beyond simple spatial relations. In particular, mobile robots need to have semantic information about the entities in the environment such as the type or the name of places or objects. This work addresses the problem of classifying places (room, corridor or doorway) using mobile robots equipped with a laser range scan- ner. This paper compares the results of several AdaBoost algo- rithms (Viola-Jones AdaBoost, Gentle AdaBoost, Modest Ad- aBoost and Generalized AdaBoost for the place categorization) to train a set of classifiers and discusses these solutions. Since the problem is multi-class and these AdaBoosts provide only binary outputs, the AdaBoosts are arranged into Probabilistic Decision Lists (PDL), where each AdaBoost of the list gives a confidence value of each class. Then, Probabilistic Relaxation Labeling (PRL) is performed to smooth the classification re- sults. Moreover, heuristics for removing incorrect regions are proposed to reduce the classification error. Experimental re- sults suggest that PDL can be extended to several binary classi- fiers and show that PRL improves significantly the classification rates of the classifiers.
An Alternating Selection for Parallel Affine Projection Filters

We present a new structure for parallel affine projection (AP) filters with different step-sizes. By observing their error signals, the proposed alternating AP (A-AP) filter selects one of the two AP filters and updates the weights of the selected filter for each iteration. As a result, the total computations required for the proposed structure is almost the same as that for a single AP filter. Experimental results show that the proposed alternating selection scheme extracts the best properties of each component filter, namely fast convergence and small steady-state error.
Acute Psychosocial Stress Reduces Cell Survival in Adult Hippocampal Neurogenesis without Altering Proliferation

Factors modulating neurogenesis may contribute to the pathophysiology of affective disorders such as major depression. Environmental stressors in animal models have been proposed to alter neurogenesis, suggesting a mechanism for this contribution. The effect of an acute psychosocial stressor on either proliferation or survival (immediate, short term, and long term) was examined along with subsequent neuronal differentiation in the hippocampus of adult male Sprague Dawley rats. Subjects were exposed to a widely used social dominance paradigm that elicits behavioral and physiological responses to an acute psychosocial stressor. This social dominance paradigm may mimic human relational stress more realistically than laboratory stressors and provides a socially relevant model. We found that exposure to an acute psychosocial stressor at the time of cell generation resulted in a decreased number of newly generated cells in the hippocampus. By using sequential thymidine analog administration to provide temporal discrimination of DNA replication, we showed that short-term survival but not initial proliferation or immediate survival was altered in response to stress. Furthermore, we determined that stress experienced subsequent to proliferation also diminished long-term survival of cells. Thus, an acute episode of a social stress produces long-lasting effects on the incorporation of new hippocampal neurons by reducing their survival.
Selective Harmonic Elimination Technique for a CMLI with Unequal DC Sources

For a cascade multilevel inverter, switching angles at fundamental frequency are obtained by solving the selective harmonic elimination equations in such a way that the required fundamental voltage is obtained while eliminating certain lower order harmonic components. Due to nonlinear transcendental nature of these equations, there may exist simple, multiple or even no solution for a particular value of modulation index. In this article, an optimization based technique is implemented for solving the nonlinear transcendental equations producing all possible solutions. The objective function chosen is sum of square of harmonic components to be eliminated, and the solution (switching angles) is said to be obtained when the objective function is identically zero. The switching angles for different level of voltage unbalancing factors have been calculated for an 11level cascade multilevel inverter. Since the THD in the output voltage depends very much on the values of calculated switching angles, therefore, in this work, THD corresponding to different solution sets have been computed and compared for each set of voltage unbalancing factors. For the verification of computational results, MATLAB simulations on an 11-level CMLI using MATLAB/SIMULINK are carried out. It has been observed that the computational/analytical results are in close agreement with the simulated results hence verifying computational results.
Automated analysis of language production in aphasia and right-hemisphere damage: frequency and collocation strength

ABSTRACT Background: Reliance on formulaic language, i.e., holistically processed multiword chunks, is claimed to distinguish speakers with aphasia, speakers with right-hemisphere damage (RHD), and neurotypical controls (NC). Frequency and collocation strength of word combinations are indicators of formulaic language. Aims: We aimed to determine frequency and collocation properties of spoken production, as indicators of formulaic language, in people with aphasia, speakers with RHD and NC. Methods and Procedures: We used computerized methods to investigate spontaneous language in 40 speakers: 10 with fluent aphasia (fA), 10 with non-fluent aphasia (nfA), 10 with RHD, and 10 NC. Our analysis not only focused on frequency and collocation strength of grammatical combinations as markers of formulaic language (using the British National Corpus as reference), but also looked at word frequency, language fluency, proportion of content words, and measures of lexical and combinatorial diversity. Outcomes and Results: Both groups with aphasia differed from neurotypical speakers with regard to lexical features and word combinations. Their language was less fluent, less diverse at the word level, and, in the non-fluent group, contained a higher proportion of content words. Each aphasic group also differed significantly from controls with increased values on at least one marker of formulaic language. Speakers with RHD produced less-frequent combinations, which were more weakly collocated; however, these effects did not reach statistical significance. Conclusions: Our results show that formulaic language use distinguishes aphasic from other speakers and that differences can be tracked with an automated, corpus-based script that uses frequency and collocation variables. We present our study in the context of usage-based frameworks of language.
Elliptical shape and size approximation of a particle contour

The paper presents an approximation of the particle contour by means of an ellipse with equivalent moments of inertia along both axes perpendicular to each other. This method ensures higher accuracy of size approximation than circular and rectangular approximation methods. The proposed method can be applied to machine vision systems used for particle size distribution analysis. In this method, there are simultaneously determined two (instead of one) characteristic dimensions. From these two dimensions as a decisive criterion there is chosen the smaller one, because it has the greatest importance for the particle behavior of the grain in the screening process.
Quantification, Inequality, and the Contestation of School Closures in Philadelphia

Public education relies heavily on data to document stratified inputs and outcomes, and to design interventions aimed at reducing disparities. Yet despite the promise and prevalence of data-driven policies and practices, inequalities persist. Indeed, contemporary scholarship has begun to question whether and how processes such as quantification and commensuration contribute to rather than remediate inequality. Using the 2013 closure of 24 Philadelphia public schools as a case study, I employ a mixed-methods approach to illuminate quantification and commensuration as nuanced processes with contingent, dualistic, and paradoxical relationships to inequality. The quantified approach to selecting schools for closure predisposed poor and minority communities to institutional loss because academic underperformance, a key selection metric, was correlated with disadvantage. Paradoxically, academic performance measures, coupled with commensuration strategies, also enabled advocates to successfully overturn closure recommendations. I offer an evidentiary account of how quantification can perpetuate inequality, and I complicate prevailing understandings of quantification as a technology of power.
KooSHO: Japanese Text Input Environment based on Aerial Hand Writing

Hand gesture-based input systems have been in active research, yet most of them focus only on single character recognition. We propose KooSHO: an environment for Japanese input based on aerial hand gestures. The system provides an integrated experience of character input, Kana-Kanji conversion, and search result visualization. To achieve faster input, users only have to input consonant, which is then converted directly to Kanji sequences by direct consonant decoding. The system also shows suggestions to complete the user input. The comparison with voice recognition and a screen keyboard showed that KooSHO can be a more practical solution compared to the existing system.