Miracle-dz/UniFAR-FTUs huggingface dataset:
Le réseau de distribution d’eau potable : un écosystème complexe lié à des enjeux de santé publique

L’emergence de pathogenes dans l’eau destinee a la consommation humaine represente une preoccupation majeure en matiere de sante publique pour les industriels et les pouvoirs publics concernes. Parmi ces pathogenes, certains sont d’origine fecale (Cryptosporidium, Campylobacter ou bien les rotavirus), alors que d’autres vivent dans l’environnent naturel (Legionella, Pseudomonas, Aeromonas ou bien les mycobacteries). Dans l’optique de mettre en place une analyse des risques lies a la presence de ces pathogenes, il est important d’accroitre nos connaissances sur l’ecologie de ces microorganismes et de developper des outils d’analyse afin de realiser une meilleure surveillance sanitaire. Par consequent, l’ecologie microbienne du reseau de distribution d’eau potable doit etre etudiee en detail, particulierement vis-a-vis des proprietes physiologiques et la diversite des especes microbiennes presentes, afin de mieux comprendre les interactions entre les especes communement rencontrees et celles pathogenes.
Impacts of Low Socio-economic Status on Educational Outcomes: A Narrative Based Analysis

Socioeconomic status (SES) is a metric used to compare a person’s social standing based on their income, level of education, and occupation. Students from low SES backgrounds are those whose parents have low income and have limited access to the resources and opportunities they need to aid their success. Researchers have studied many issues and solutions for students with low SES, and there is a lot of research going on in many fields, especially in the social sciences. Computer science, however, has not yet as a field turned its considerable potential to addressing these inequalities. Utilizing Natural Language Processing (NLP) methods and technology, our work aims to address these disparities and ways to bridge the gap. We built a simple string matching algorithm including Latent Dirichlet Allocation (LDA) topic model and Open Information Extraction (open IE) to generate relational triples that are connected to the context of the students’ challenges, and the strategies they follow to overcome them. We manually collected 16 narratives about the experiences of low SES students in higher education from a publicly accessible internet forum (Reddit) and tested our model on them. We demonstrate that our strategy is effective (from 37.50% to 80%) in gathering contextual data about low SES students, in particular, about their difficulties while in a higher educational institution and how they improve their situation. A detailed error analysis suggests that increase of data, improvement of the LDA model, and quality of triples can help get better results from our model. For the advantage of other researchers, we make our code available.
NAIST-NICT-TIT WMT22 General MT Task Submission

In this paper, we describe our NAIST-NICT-TIT submission to the WMT22 general machine translation task. We participated in this task for the English ↔ Japanese language pair.Our system is characterized as an ensemble of Transformer big models, k-nearest-neighbor machine translation (kNN-MT) (Khandelwal et al., 2021), and reranking.In our translation system, we construct the datastore for kNN-MT from back-translated monolingual data and integrate kNN-MT into the ensemble model. We designed a reranking system to select a translation from the n-best translation candidates generated by the translation system. We also use a context-aware model to improve the document-level consistency of the translation.
Synergistic Effects of Metformin and Cocoa Flavanol on Inflammatory and Oxidant Markers Induced by Carrageenan: Pathophysiological Approach

Background and Aim: The present study aims to evaluate the effects of metformin, cocoa flavanol and their combination as anti-inflammatory and antioxidant drugs. Methods: Forty adult male albino mice are divided into five groups: Control, Carrageenan (Cg), Cg Metformin (Met), Cg Cocoa and Cg Met Cocoa groups. Cg is used to induce the inflammation through injection of it in the paw of the hind leg and into the trunk of mice. Also, Met is applied intraperitoneally at the same time of Cg injection while Cocoa is received orally seven days before carrageenan injection. Biochemical estimation of inflammatory mediators (COX-2, PGE2, TNF-α, CRP) and selected oxidative stress markers (MDA, SOD, GSH) was performed. Results: This study elucidated the marvellous leverage of the metformin, cocoa flavanol and their combination as anti-inflammatory and antioxidant drugs, where metformin and Cocoa decreased all inflammatory mediators (COX-2, PGE2, TNF-α, CRP) with high significant (P<0.01) in comparing with Cg group. In addition, the level of MDA is decreased significantly (P<0.01), while the levels of SOD and GSH are increased significantly (P<0.01) in comparing with Cg group. Interestingly, their combination restored normal levels of the inflammatory mediators and the oxidative stress markers. Conclusion: I concluded that Met and cocoa are powerful anti-inflammatory substances and can ameliorate the oxidative stress that results from inflammation. Additionally, the mixture of them can retrieve the normal levels of all measured parameters.
Modeling and Design of Zero-Voltage-Switching Controller for Wireless Power Transfer Systems Based on Closed-Loop Dominant Pole

Zero-Voltage-Switching (ZVS) operation for a Wireless Power Transfer (WPT) system can be achieved by designing a ZVS controller. However, the performance of the controller in some industrial applications needs to be designed tightly. This paper introduces a ZVS controller design method for WPT systems. The parameters of the controller are designed according to the desired performance based on the closed loop dominant pole placement method. To describe the dynamic characteristics of the system ZVS angle, a nonlinear dynamic model is deduced and linearized using the small signal linearization method. By analyzing the zero-pole distribution, a low-order equivalent model that facilitates the controller design is obtained. The parameters of the controller are designed by calculating the time constant of the closed-loop dominant poles. A prototype of a WPT system with the designed controller and a five-stage multistage series variable capacitor (MSVC) is built and tested to verify the performance of the controller. The recorded response curves and waveforms show that the designed controller can maintain the ZVS angle at the reference angle with satisfactory control performance.
Pythagorean Picture Fuzzy Sets, Part 1- basic notions

Picture fuzzy set (2013) is a generalization of the Zadeh‟ fuzzy set (1965) and the Antanassov‟intuitionistic fuzzy set. The new concept could be useful for many computational intelligentproblems. Basic operators of the picture fuzzy logic were studied by Cuong, Ngan [10,11 ]. Newconcept –Pythagorean picture fuzzy set ( PPFS) is a combination of Picture fuzzy set with theYager‟s Pythagorean fuzzy set [12-14]. First, in the Part 1 of this paper, we consider basic notionson PPFS as set operators of PPFS‟s , Pythagorean picture relation, Pythagorean picture fuzzy softset. Next, the Part 2 of the paper is devoted to main operators in fuzzy logic on PPFS: picturenegation operator, picture t-norm, picture t-conorm, picture implication operators on PPFS.As aresult we will have a new branch of the picture fuzzy set theory.
Assessment of the Efficacy of a Mobile Phone–Delivered Just-in-Time Planning Intervention to Reduce Alcohol Use in Adolescents: Randomized Controlled Crossover Trial

Background Interventions to reduce alcohol use typically include several elements, such as information on the risks of alcohol consumption, planning for sensible drinking, and training of protective behavioral strategies. However, the effectiveness of these individual intervention elements within comprehensive programs has not been addressed so far, but it could provide valuable insights for the development of future interventions. Just-in-time interventions provided via mobile devices are intended to help people make healthy decisions in the moment and thus could influence health behavior. Objective The aim of this study was to test the proximal effects of a mobile phone–delivered, just-in-time planning intervention to reduce alcohol use in adolescents who reported recent binge drinking. The efficacy of this individual intervention element was tested within a comprehensive intervention program to reduce problem drinking in adolescents. Methods The study had an AB/BA crossover design, in which participants were randomly allocated to (1) a group receiving the planning intervention (A) in period 1 and assessment only (B) in period 2 or (2) a group receiving assessment only (B) in period 1 and the planning intervention (A) in period 2. The planning intervention included a text message to choose one of two predetermined if-then plans to practice sensible drinking with friends or when going out and a prompt to visualize the chosen plan. There was a washout period of at least 1 week between period 1 and period 2. Results Out of 633 program participants who recently binge drank, 136 (21.5%) were receptive in both periods of time and provided data on the proximal outcome, which was the number of alcoholic drinks consumed with friends or when going out. After the planning intervention, the number of alcoholic drinks consumed was approximately one standard drink lower compared with the finding without the intervention (P=.01). Conclusions A mobile phone–delivered, just-in-time, if-then planning intervention to practice sensible drinking with friends or when going out is effective in reducing alcohol consumption among adolescents who report recent binge drinking. Based on the relatively low percentage of participants with self-reported receptivity for the planning intervention, measures to increase the population impact of similar planning interventions should be implemented and tested in future trials. Trial Registration ISRCTN Registry ISRCTN52150713; http://www.isrctn. com/ISRCTN52150713
Nematodes and maize growth in Nigeria. II. Effects of some amendments on populations of Pratylenchus brachyurus and on the growth and production of maize (Zea mays) in Nigeria.

The use of nematicidal chemicals is perhaps the most reliable method for a quick and effective control of nematodes infesting crops. However, in Nigeria, it is unrealistic to recommend such chemicals to farmers because most nematicides are toxic to humans and require skilled labour for a successful application; they are also too costly and the increases in yields obtained by their use may not be sufficient to cover costs (Caveness, 1967). Yet, an ever increasing human population demands the growth of more food on continuosly restricted area of available arable land. Other methods must, therefore, be found which can ensure increased crop yields either by killing or reducing nematode pests. The use of soil amendments may offer such a possibility (Walker, 1969; Mankau and Das, 1969; Tomerlin et al., 1968). The present study describes a trial in which such organic amendments were used.
Lingua Custodia’s Participation at the WMT 2022 Word-Level Auto-completion Shared Task

This paper presents Lingua Custodia’s submission to the WMT22 shared task on Word Level Auto-completion (WLAC). We consider two directions, namely German-English and English-German.The WLAC task in Neural Machine Translation (NMT) consists in predicting a target word given few human typed characters, the source sentence to translate, as well as some translation context. Inspired by recent work in terminology control, we propose to treat the human typed sequence as a constraint to predict the right word starting by the latter. To do so, the source side of the training data is augmented with both the constraints and the translation context. In addition, following new advances in WLAC, we use a joint optimization strategy taking into account several types of translation context. The automatic as well as human accuracy obtained with the submitted systems show the effectiveness of the proposed method.
Effects of Feature Extraction Techniques on Classification of Turkish Texts

Feature extraction is the most important preprocessing step of text classification task. Effects of preprocessing techniques on text mining for English have been extensively studied. However, studies for Turkish are limited and generally belong to a specific problem domain. In this study, we investigate the effects of feature extraction techniques on four different Turkish text classification problems including news classification, spam e-mail detection, sentiment analysis, and author detection to show the differences and similarities among the problems. We also propose a new feature selection method to reduce feature space. The experimental analysis has showed that, stopword removal improves classification performance. However, stemming does not make any positive effect on classification accuracy. The most successful term weighting methods are tf and tf*idf . The proposed feature selection method improves classification performance and has higher accuracy than the well-known methods
Impact of Psychological Consequences on Poverty: An Evidence from Pakistan

The limitation and the complications which the economic agents are facing are studied in behavioral economics. The current study underhand is an attempt to explore the impact of psychological consequences on household incomes. The current study underhand used World Value Survey data for the years 2012-2014 for Pakistan. Simple Linear Regression analysis was used to measure the impact of psychological variables on the income of households in Pakistan. The results show that people with a more external locus of control positively affect their incomes, as they do believe in external factors like fate and luck for its success or failure. Creativity, loneliness, and positivity have a direct relation with income while mistrust and risk aversion have an inverse relation with income. Creative minds of individuals, freedom of choice to control their lives phenomenon have a strong, positive and significant association with income. Creativity at work increase income or regular work for just reward increase income. This means that the individuals who mistrust less are consequently quicker in taking economic decisions and would make investment planning that will lead to an increase in their income. A second estimated model of this study includes all socioeconomic variables which can determine the level of income. These variables cover a wide range of demographic and social variables. These socioeconomics variables are age, gender, level of education, number of children, marital status, interaction variable of marital status and age, a square of interaction variable of marital status and age, interaction variable of gender and age, a square of interaction variables of gender and age and dummies of the province. Results show that all these variables have a significant relation with income level. All the socioeconomic and demographic variables have a strong association with the level of income. It reveals that the dummy of marital status negatively influences the income, it means that an unmarried man can earn more than a married. This study suggested that policymakers should take initial steps to focus on human psychology while making efforts to reduce the poverty level.
The Social Construction of Online Fraud

This study critically examines how online retailers aim to differentiate between fraudulent and non-fraudulent customers by using digitally accessible data. Utilising social constructionism and actor-network theory as a theoretical framework, the study argues that online fraud is constructed through social practices as well as technological and organisational relations. This ongoing process involves several human and non-human actors embedded in heterogeneous networks, but the process is not neutral, and neither can the data used as the basis of fraud management be considered value-free. Big data has often been challenged as a neutral representation of reality, given that the collection and analysis thereof involve human biases, choices, selections and preferences. Consequently, the categories of risk assessment and manual fraud management practices represent these values. However, from a manual fraud review perspective, automated fraud management systems gain an object-like status and often remain unchallenged, and the choices and selections behind these implementations go unnoticed. Categorisations and fraud scorings are pre-giving when manual reviewers enter the risk assessment process and can only operate within existing norms and structures. Manual reviewers take a similar approach and make decisions using additional data sources such as Google and personal and professional websites while imposing their own preferences, biases and understandings, or accepting, rejecting or negotiating alternative realities proposed by other reviewers. It is also crucial how manual reviewers are able to enrol and mobilise other actors to take action in line with their own interests. The study shows that fraud assessment approaches create their own sense of normality and label those as suspicious or fraudulent who seem to deviate from the norm, thereby leading to the inclusion and exclusion of people. Furthermore, most fraud cases are not reported, which means that the vast majority remain unknown to the police, who then construct their own version of the crime.
A Veteran Science Teacher's Transitions to NGSS.

Curricular reforms in science education represent an opportunity for changes in instructional approaches with the intent of making learning and teaching more meaningful and effective. While beginning teachers may receive instruction on pedagogy aligned with adopted reforms, veteran teachers need support and development to implement instruction aligned with reforms. This qualitative case study focused on the transitions of a veteran, Grade 6 science teacher to implement instruction consistent with three-dimensional instruction outlined in the Next Generation Science Standards (NGSS Lead States, 2013). Themes that emerged through analyses of data included the desire and methods for developing pedagogical knowledge, collaborative supports for changing pedagogy, and resulting changes in pedagogy. Suggestions for further study include exploration of types of professional development that support changing pedagogy and a long-term study of teacher efficacy in three-dimensional instructional approaches outlined in NGSS (NGSS Lead States, 2013).
Regulation of Reactive Nitrogen Species (RNS) Metabolism and Resistance Mechanisms in Haemophilus influenzae : A Dissertation

Haemophilus influenzae encounters niches within the human host that are predicted to differ in availability of oxygen and reactive nitrogen species (RNS: nitrite and nitric oxide), which influence the environmental redox state. Previously reported data has indicated that an altered redox condition could serve as a signal recognized by H. influenzae to optimize its survival within host microenvironments. To elucidate the role of redox signaling in virulence, we examined regulation by the FNR homolog of H. influenzae , whose counterpart in E. coli has been reported to be a direct oxygen sensor and a regulator of genes responsible for RNS metabolism and resistance. Many members of the FNR regulon are subject to coordinated transcriptional control by NarP, a regulator in E. coli that is activated by cognate sensor NarQ in response to environmental nitrite. To study the regulatory activities of FNR and NarQ-NarP in H. influenzae , I targeted a gene predicted to be FNR-regulated, nrfA , which encodes nitrite reductase, a periplasmic cytochrome-c involved in anaerobic respiration. The fnr, narP and nrfA mutants were assayed for nitrite reduction, which implicated the roles of FNR, NarP and NrfA in RNS metabolism. Using Western blot detection of an epitope-tagged reporter protein fused to the endogenous nrf promoter (Pnrf-HA), I demonstrate that FNR and NarP, but not NarQ, are required for full activation of the nrf promoter. Additionally, Pnrf-HA expression increases as oxygen becomes depleted and decreases when exposed to high concentrations of nitrite, implying that the nrf promoter is modulated by environmental redox signals. FNR of E. coli has been implicated in regulation of resistance mechanisms to a reactive nitrogen species, nitric oxide (NO), which is produced by innate immune cells during infection as a host defense mechanism. A mutant lacking FNR is more sensitive to NO exposure and killing by activated macrophages than wild type H. influenzae after anaerobic pre-growth. Mutants of nrfA and narP have been tested and initial experiments have shown both mutants have a lesser NO sensitivity phenotype as compared to the fnr mutant, suggesting that other factors could be involved in FNR-mediated NO resistance in H. influenzae . Upon examination of potential factors that might be involved to this phenotype, we discovered FNR-regulated gene, ytfE , which contributes to defense against nitrosative stress. The fnr and ytfE mutants are more susceptible to killing by activated macrophages indicating that FNR regulation of ytfE might be important for in vivo infection.
Selection of Optimum Mother Wavelet Function for Turkish Phonemes

In this paper, we propose the selection of most suitable mother wavelet function for Turkish phonemes using discrete wavelet transform. The determination of most similar mother wavelet function to the signal has been a challenge in speech processing. The optimum mother wavelet function for Turkish phonemes have been determined by using quantitative measures which are energy and Shannon entropy, information theoretic measures which are joint entropy, conditional entropy, mutual information, and relative entropy from wavelet coefficients of the phonemes. In this study, 101 potential functions were investigated to determine the most appropriate mother wavelet. Experimental results show that the most appropriate wavelet functions for /c/ and /s/ phonemes which are unvoiced fricatives have been found as Bi-orthogonal 3.9 and Bi-orthogonal 5.5, respectively. By considering all the results, it is seen that the Bi-orthogonal 3.1 and Discrete Meyer wavelet functions are the most suitable mother wavelets for all other phonemes.