Miracle-dz/UniFAR-FTUs huggingface dataset:
ON AN ORGANISATION IN MAURITIUS

Rework is a known vicious circle in software development since it plays a central role in the generation of delays, extra costs and diverse risks introduced after software delivery. It eventually triggers a negative impact on the quality of the software developed. In order to cater the rework issue, this paper goes in depth with the notion of rework in software development as it occurs in practice by analysing a development process on an organisation in Mauritius where rework is a major issue. Meticulous strategies to reduce rework are then analysed and discussed. The paper ultimately leads to the recommendation of the best strategy that is software configuration management to reduce the rework problem in software development.
Multi-Tier Networks for Citywide Damage Monitoring in a Natural Disaster

for disaster communications. The hybrid network named Sphinx [22] aims to achieve high throughput and low power consumption. Concurrently, it addresses fairness for resource allocation, and resilience for mobility. The mobile stations operate in two modes, one is a cellular mode, and the other is a peer-to-peer mode(Fig. 5). When a mobile station communi‐ cates with the others located in the same cell, all flows are served in the peer-to-peer mode in the initial state. In the event that a mobile station detects degradation of the throughput in the peer-to-peer mode, it requires BS to switch to the cellular mode. ‐
On integrals, Hamiltonian and metriplectic formulations of polynomial systems in 3D

We apply the Darboux integrability method to determine first integrals and Hamiltonian formulations of three dimensional polynomial systems; namely the reduced three-wave interaction problem, the Rabinovich system, the Hindmarsh-Rose model, and the oregonator model. Additionally, we investigate their Hamiltonian, Nambu-Poisson and metriplectic characters.
Genetic Polymorphism of UDP-Glucuronosyltransferase

Genetic polymorphism is referred to the discontinuous interspecies genetic variability among individuals having distinct alleles on a particular locus. Genetic polymorphism of genes encoding drug-metabolizing enzymes constitutes individual’s susceptibility to drugs, affirmed by having discrete allelic frequencies by the individual, strengthening the concept of precision medicine. To combat with toxic consequences of drugs, the polymorphic genes associated with xenobiotic metabolism must be studied. Up to 70% xenobiotic elimination is believed to be dependent on UDP-glucuronosyltransferase (UGT), an enzyme encoded by polymorphic UGT1A and UGT2B genes. Both bimodal and trimodal distribution patterns of UGT have been reported in various human populations studied. Genetic polymorphisms of UGT may even lead to truncated and shorter gene with grossly diminished enzymatic activity. The extent of phenotypic alteration inflicted by genetic polymorphisms depends on its nature and position on gene locus. The different isoforms of UGT superfamily differ from each other regarding substrate specificity and selectivity. The incidence of genetic polymorphisms and associated altered gene functions results in inter-individual variability in metabolic clearance and elimination of drugs. Hence, the critical interaction between genetics and biotransformation of drugs has recently been the focus of pharmacology research.
A JOINT CHANDRA AND SWIFT VIEW OF THE 2015 X-RAY DUST-SCATTERING ECHO OF V404 CYGNI

We present a combined analysis of the Chandra and Swift observations of the 2015 X-ray echo of V404 Cygni. Using a stacking analysis, we identify eight separate rings in the echo. We reconstruct the soft X-ray light curve of the 2015 June outburst using the high-resolution Chandra images and cross-correlations of the radial intensity profiles, indicating that about 70% of the outburst fluence occurred during the bright flare at the end of the outburst on MJD 57199.8. By deconvolving the intensity profiles with the reconstructed outburst light curve, we show that the rings correspond to eight separate dust concentrations with precise distance determinations. We further show that the column density of the clouds varies significantly across the field of view, with the centroid of most of the clouds shifted toward the Galactic plane, relative to the position of V404 Cyg, invalidating the assumption of uniform cloud column typically made in attempts to constrain dust properties from light echoes. We present a new XSPEC spectral dust-scattering model that calculates the differential dust-scattering cross section for a range of commonly used dust distributions and compositions and use it to jointly fit the entire set of Swift echo data. We find that a standard Mathis–Rumpl–Nordsieck model provides an adequate fit to the ensemble of echo data. The fit is improved by allowing steeper dust distributions, and models with simple silicate and graphite grains are preferred over models with more complex composition.
ERROR-FREE MILESTONES IN ERROR PRONE MEASUREMENTS BY DYLAN

A predictor variable or dose that is measured with substantial error may possess an error-free milestone, such that it is known with negligible error whether the value of the variable is to the left or right of the milestone. Such a milestone provides a basis for estimating a linear relationship between the true but unknown value of the error-free predictor and an outcome, because the milestone creates a strong and valid instrumental variable. The inferences are nonparametric and robust, and in the simplest cases, they are exact and distribution free. We also consider multiple milestones for a single predictor and milestones for several predictors whose partial slopes are estimated simultaneously. Examples are drawn from the Wisconsin Longitudinal Study, in which a BA degree acts as a milestone for sixteen years of education, and the binary indicator of military service acts as a milestone for years of service.
Sub-Epithelial Connective Tissue Graft to Increase the Volume of Residual Alveolar Bone in the Upper Anterior Sector and Fixed Rehabilitation with Zirconia

Background: The collapse of the alveolar ridge in an edentulous area in patients who will undergo oral rehabilitation impedes the harmonic relationship between pontic and ridge. To correct this type of defect there are several surgical techniques that aim to achieve soft tissue augmentation, allowing the conformation of an ideal profile with the use of a pontic. The aim was to demonstrate how the technique of tissue modification in an area with a class b defect of Allen allows the correction of aesthetics in the anterior dental sector. Case presentation: A 41-year-old Mexican woman. Extra and intraoral examination was performed, the dental treatment included connective tissue graft and rehabilitation with Zirconia. Conclusion: Surgery of residual alveolar ridge augmentation with connective tissue graft gives the patient favorable aesthetic results in the anterior area when it will be rehabilitated.
Nano-oxidation of silicon surfaces: Comparison of noncontact and contact atomic-force microscopy methods

Local oxidation lithography by atomic-force microscopy is emerging as a powerful method for nanometer-scale patterning of surfaces. Here, we perform a comparative study of contact and noncontact atomic-force microscopy (AFM) oxidation experiments. The comparison of height and width dependencies on voltage and pulse duration allows establishing noncontact AFM as the optimum local oxidation method. For the same electrical conditions, noncontact AFM oxides exhibit higher aspect ratios (0.04 vs 0.02). The smallness of the liquid meniscus in noncontact AFM oxidation produces smaller oxide widths. We also report a slower oxidation rate in contact AFM oxidation. We explain this result by introducing an effective energy barrier (∼0.14 eV) that includes the mechanical work done by the growing oxide against the cantilever (∼0.01 eV).
Complexity Efficient Decoder Design for Vehicular Communication

Vehicular communication is currently seen as a key technology for enabling safer and more comfortable driving. In the general effort to reduce the number of casualties and improve the traffic flow despite an increasing number of vehicles, this field has a promising future. IEEE 802.11p has been chosen as the standard for the Physical Layer (PHY) design for wireless vehicular communication. However, the channels encountered in such situations pose several challenges for reliable communications. Time and frequency selectivity caused by dispersive environments and high mobility lead to doubly-selective channels. The systems are expected to conduct proper operation, in spite of these disturbances. In this thesis, we focus on the design of receivers working on the PHY layer, with an emphasis on limited complexity. This poses high constraints on the algorithms, which already have to cope with the limited amount of information provided by the training sequences. The solutions considered all involve joint channel estimation and decoding, characterized by the use of an iterative structure. Such structures allow the channel estimation to benefit from the knowledge brought by the decoder, which ultimately decreases the error rate. Following a previous work, we use algorithms based on Minimum Mean Square Error (MMSE) or Maximum A Posteriori (MAP) estimation. These receivers were modified to operate on full frames instead of individual subcarriers, and various improvements were studied. We provide a detailed analysis of the complexity of the proposed designs, along with an evaluation of their decoding performance. The trade-offs between these two parameters are also discussed. A part of these analyses isused in [10]. Finally, we give an insight into some considerations which may arise when implementing the algorithms on testbeds.
Autonomously Determining the Parameters for SVDD with RBF Kernel from a One-Class Training Set

—The one-class support vector machine “support vector data description” (SVDD) is an ideal approach for anomaly or outlier detection. However, for the applicability of SVDD in real-world applications, the ease of use is crucial. The results of SVDD are massively determined by the choice of the regularisation parameter C and the kernel parameter σ of the widely used RBF kernel. While for two-class SVMs the parameters can be tuned using cross-validation based on the confusion matrix, for a one-class SVM this is not possible, because only true positives and false negatives can occur during training. This paper proposes an approach to ﬁnd the optimal set of parameters for SVDD solely based on a training set from one class and without any user parameterisation. Results on artiﬁcial and real data sets are presented, underpinning the usefulness of the approach.
Are Presolar Silicon Carbide Grains from Novae Actually from Supernovae?

We report Si, C, N, Mg-Al, Ca, and Ti isotopic data for three micron-sized presolar SiC grains from the Murchison meteorite. These grains have very low 12C/13C and 14N/15N ratios, similar to grains for which an origin in classical ONe novae has been previously ascribed. Isotopic signatures in one grain (28Si, 49Ti, and 44Ca excesses and a very high inferred 26Al/27Al ratio) indicate that it in fact formed in a supernova, not a nova. Similarly, a large 47Ti excess in another grain argues against a nova origin. The new data raise the question whether all grains previously attributed to novae might have in fact originated in Type II supernovae. The results also point to coupled synthesis of 13C and 15N in Type II supernovae.
Enhancing the Performance of Sentiment Analysis Supervised Learning Using Sentiments Keywords Based Technique

Sentiment Analysis (SA) and machine learning techniques are collaborating to understand the attitude of text writer, implied in particular text. Although, SA is an important challenging itself, it is very important challenging in Arabic language. In this paper, we are enhancing sentiment analysis in Arabic language. Our approach had begun with special pre-processing steps. Then, we had adopted sentiment keywords co-occurrence measure (SKCM), as an algorithm extracted sentiment-based feature selection method. This feature selection method had utilized on three sentiment corpora using SVM classifier. We compared our approach with some traditional methods, followed by most SA works. The experimental results were very promising for enhancing SA accuracy.
Signaler and Receiver Ages do not Affect Responses to RIchardson's Ground Squirrel Alarm Calls

Abstract Alarm calls alert receivers to the presence and/or nature of a predatory threat. Studies of alarm communication in Richardson's ground squirrels (Spermophilus richardsonii) have focused on juvenile signalers and receivers; however, adult and juvenile receivers may tailor their response to alarm calls based on different underlying signal parameters and attend differentially to alarm calls broadcast by adult versus juvenile signalers. To examine the potential influence of signaler and receiver age on the perception of response urgency, we presented free-living juvenile and adult S. richardsonii with alarm calls produced by juveniles and adults. Behavioral responses of call recipients were videotaped and analyzed to determine the influence of signaler and receiver age-class. No differences in vigilance response after juvenile- and adult-produced calls were detected for either adult or juvenile receivers. At the proximate level, the absence of any detectable difference in the acoustic attributes of juvenile- versus adult-produced calls may account for the lack of differential response. The absence of any age-dependent productional difference also is consistent with the recently advanced notion of young concealing information regarding their age in their alarm signals.
Space & Congruence Compression of Proofs

This work presents two methods for compression of formal proofs. Formal proofs are of great importance to modern computer science. They can be used to combine deductive systems. For example SAT solvers [11] are heavily used for all kinds of computations, because of their efficiency. A formal proof is a certificate of the correctness of the output of a SAT solver. Furthermore, formal proofs can provide information about the underlying problem. For example, Interpolants [37] and unsat cores can be extracted from proofs, as done in [33]. Typically problems tackled by automated systems are huge and so are the produced proofs. For example, [35] reports a 13 GB proof of one case of the Erdős Discrepancy Conjecture. With such proof sizes, computer systems reach their boundaries and that is why it is necessary to compress proofs. Our work presents two methods for proof compression. The first method removes redundancies in the congruence reasoning part of SMT proofs. Congruence reasoning deduces equalities from a set of input equations, using the four axioms reflexivity, symmetry, transitivity, and compatibility. We found that SMT solver often use an unnecessarily large set of input equations to deduce one particular equality. We present a novel explanation producing congruence closure algorithm and show that it produces shorter explanations than those we found in the benchmark proofs. By replacing long by short explanations, we construct a new, compressed proof. Furthermore, we prove that finding the shortest explanation is in general a NP-complete problem. The second method investigates the memory requirements of proofs. During processing a proof, not all parts of the proof have to be kept in memory at all times. Subproofs can be loaded into memory when needed and can be removed from memory again when they are not needed anymore. The traversal order in which subproofs are visited is essential to the maximum memory consumption during proof processing. We construct traversal orders with low memory requirements using two novel algorithms together with a collection of heuristics.
Selective biochemical labeling of C. jejuni cell-surface glycoconjugates

The display of cell-surface glycolipids and glycoproteins is essential for the motility, adhesion and colonization of pathogenic bacteria such as Campylobacter jejuni . Recently, the cell-surface display of C. jejuni glycoconjugates has been the focus of considerable attention, however, our understanding of the roles that glycosylation plays in bacteria still pales in comparison to our understanding of mammalian glycosylation. One of the reasons for this is that carbohydrate metabolic labeling, a powerful tool for studying mammalian glycans, is difficult to establish in bacterial systems and has a significantly more limited scope. Herein, we report the development of an alternative strategy that can be used to study bacterial cell-surface glycoconjugates. Galactose oxidase (GalO) is used to generate an aldehyde at C-6 of terminal GalNAc residues of C. jejuni glycans. This newly-generated aldehyde can be conjugated with aminooxy-functionalized purification tags or fluorophores. The label can be targeted towards specific glycoconjugates using C. jejuni mutant strains with N-glycan or lipooligosaccharides (LOS) assembly defects. GalO-catalyzed labeling of cell-surface glycoproteins with biotin, allowed for the purification and identification of known extracellular N-linked glycoproteins as well as a recently identified O-linked glycan modifying PorA. To expand the scope of the GalO reaction, live-cell fluorescent labeling of C. jejuni was used to compare the levels of surface exposed LOS to the levels of N-glycosylated, cell-surface proteins. While this study focuses on the GalO–catalyzed labeling of C. jejuni , it can in principle be used to evaluate glycosylation patterns and identify glycoproteins of interest in any bacteria.
Designing a Working Memory Capacity Test for Cognitive-Friendly Tangible Multimedia

A working memory capacity (WMC) test called “objects-span tri-tasks” is designed for preschoolers undergoing treatment using a new genre of multimedia, tangible multimedia, created by the authors. It tests the dual-functions of the preschoolers’ working memory (WM), namely storage and manipulation capacity, essential in supporting academic skills. The third task in the test is the overt setting of task engaging the long-term memory that supports the operation of WM. Tangible multimedia potentially enhances the WMC of preschoolers to a considerable extent because firstly, it uses tangible objects that are cognitively appropriate to the “preoperational” stage of preschoolers, and secondly, it simultaneously stimulates three main sensory channels, prescribed as equally crucial in knowledge acquisition in human memory theories. A pragmatic significance of the research is that it deepens the scope of multimedia research by looking into the aspect of cognitive structure which is rarely conducted in the multimedia realm. It also demonstrates an important step forward in multimedia research by relating WMC to the newly explored tangible multimedia, which could determine the real capability and value of such system. This paper starts off by discussing the underlying theories that contribute to the formation of the system and test, followed by its procedure, and a brief report of a case study.
Semi-Supervised Learning on Data Streams via Temporal Label Propagation

We consider the problem of labeling points on a fast-moving data stream when only a small number of labeled examples are available. In our setting, incoming points must be processed efficiently and the stream is too large to store in its entirety. We present a semi-supervised learning algorithm for this task. The algorithm maintains a small synopsis of the stream which can be quickly updated as new points arrive, and labels every incoming point by provably learning from the full history of the stream. Experiments on real datasets validate that the algorithm can quickly and accurately classify points on a stream with a small quantity of labeled examples.
Supervised Learning Model for Kickstarter Campaigns With R Mining

Web mediated crowd funding is a talented paradigm used by project launcher to solicit funds from backers to realize projects. Kickstarter is one such largest funding platform for creative projects. However, not all the campaigns in Kickstarter attain their funding goal and are successful. It is therefore important to know about campaigns’ chances of success. As a broad goal, authors intended in extraction of the hidden knowledge from the Kickstarter campaign database and classification of these projects based on their dependency parameters. For this authors have designed a classification model for the analysis of Kickstarter campaigns by using direct information retrieved from Kickstarter URLs. This aids to identify the possibility of success of a campaign.
Infinite Horizon Differential Games for Multiparameter Singularly Perturbed Systems

In this paper, we study the infinite horizon zerosum differential games for both standard and nonstandard multiparameter singularly perturbed systems. A composite approximation of the full-order linear feedback saddle-point solution is obtained by decomposing the full-order game problem into a slow game and two fast control problems. It is proven that such a composite approximation forms an O(||μ||) (near) saddle-point equilibrium of the full-order game, and the resulting value is O(||μ||2) over or below the exact value of the full-order game depending on the given game parameters. Keywords— Multiparameter, singular perturbation, differential games, saddle-point equilibrium.
A Tale of Two Cities: How WebView Induces Bugs to Android Applications

WebView is a widely used Android component that augments a native app with web browser capabilities. It eases the interactions between an app's native code and web code. However, the interaction mechanism of WebView induces new types of bugs in Android apps. Understanding the characteristics and manifestation of these WebView-induced bugs ($\omega \text{Bugs}$ for short) facilitates the correct usages of WebViews in Android apps. This motivates us to conduct the first empirical study on $\omega \text{Bugs}$ based on those found in popular open-source Android apps. Our study identified the major root causes and consequences of $\omega \text{Bugs}$ and made interesting observations that can be leveraged for detecting and diagnosing $\omega \text{Bugs}$. Based on the empirical study, we further propose an automated testing technique $\omega \text{Droid}$ to effectively expose $\omega \text{Bugs}$ in Android apps. In our experiments, $\omega \text{Droid}$ successfully discovered 30 unique and previously-unknown $\omega \text{Bugs}$ when applied to 146 open-source Android apps. We reported the 30 $\omega \text{Bugs}$ to the corresponding app developers. Out of these 30 $\omega \text{Bugs}$, 14 were confirmed and 7 of them were fixed. This shows that $\omega \text{Droid}$ can effectively detect $\omega \text{Bugs}$ that are of the developers' concern.
THREE CANDIDATE CLUSTERS AROUND HIGH REDSHIFT RADIO-LOUD SOURCES: MG1 J04426+0202, 3C 068.2, AND MS 1426.9+1052

We present near-infrared observations of the environments around three radio-loud sources (MG1 J0442+0202, 3C 068.2, and MS 1426.9 + 1052 ? > ) at redshifts z = 1.10, 1.57, and 1.83 (respectively) that are surrounded by near-infrared galaxy overdensities. Overdensities with respect to field counts were found to be significant up to 19σ, with 12 times the expected number of galaxies within the inner regions of the densest proto-cluster. Color–magnitude relations are constructed in Ks, J − Ks, with each candidate cluster exhibiting a feature consistent with the beginnings of a red sequence (RS). Galaxy models based on the redshift of the radio source are used to compare expected CMRs for a given formation epoch with the observed RS of each candidate, and are found to be consistent with an old ( z f > 5 ? > ) formation epoch for a few bright, red galaxies on the RS.