Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Detection of Depressive Users in Social Media

According to the World Health Organization, 350 million people worldwide sufferfrom depression. Detecting this trouble constitutes thus a challenge for personal and publichealth. Research in psychology has shown a strong correlation between the psychological stateof an individual and its language use. In this paper, we propose to leverage such linguisticfeatures to automatically detect depressive users on social media posts. Our approach is super-vised and relies on a set of features going from standard bag of words and surface features tomore linguistically informed features. This approach has been evaluated on Reddit social mediaposts and applied on two tasks: (a) Given user’s posts, detect whether the author is depressiveor not, (b) Given a user’s history of writings, early detect signs of depression. Our results showthat our approach is reliable on both tasks.
Diabetes and Subclinical Coronary Atherosclerosis

It is well known that diabetic patients have a high risk of cardiovascular events, and although there has been a tremendous effort to reduce these cardiovascular risks, the incidence of cardiovascular morbidity and mortality in diabetic patients remains high. Therefore, the early detection of coronary artery disease (CAD) is necessary in those diabetic patients who are at risk of cardiovascular events. Significant medical and radiological advancements, including coronary computed tomography angiography (CCTA), mean that it is now possible to investigate the characteristics of plaques, instead of solely evaluating the calcium level of the coronary artery. Recently, several studies reported that the prevalence of subclinical coronary atherosclerosis (SCA) is higher than expected, and this could impact on CAD progression in asymptomatic diabetic patients. In addition, several reports suggest the potential benefit of using CCTA for screening for SCA in asymptomatic diabetic patients, which might dramatically decrease the incidence of cardiovascular events. For these reasons, the medical interest in SCA in diabetic patients is increasing. In this article, we sought to review the results of studies on CAD in asymptomatic diabetic patients and discuss the clinical significance and possibility of using CCTA to screen for SCA.
Cruise Control of Phase Irrigation Motor Using SparkFun Sensor

Water Conservation and labor-saving is the key issue of irrigation in India. This Shot paper proposes an automatic irrigation control based on microcontroller and GSM technology. This wireless design provides high reliability. We have used SparkFunsoil moisture sensor SEN 13322 which is interfaced with RobokartAruduino Mega 2560 microcontroller. The soil information such as dry and wetness of the irrigation field is given to Elementz SIM 800 GSM module to an authorized wireless telephone from the remote area to the monitoring system based on smart sensor network. With the help of soil wet and dry information we are controlling the invento DC motor automatically with the help of sending message in smart phone.
An Investigation of an Acute Gastroenteritis Outbreak: Cronobacter sakazakii, a Potential Cause of Food-Borne Illness

Whole genome sequencing (WGS) has been widely used in traceability of food-borne outbreaks nowadays. Here, an interesting connection between Cronobacter sakazakii and food-borne acute gastroenteritis (AGE) was noticed. In October 2016, an AGE outbreak affecting 156 cases occurred in a local senior high school. Case-control study including 70 case-patients and 295 controls indicated a strong association between eating supper at school canteen of the outbreak onset and AGE, as revealed by the Odds Ratio (OR: 95.32). Six recovered Cronobacter strains were evaluated and compared using pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST) and WGS. A phylogenetic tree of whole genomic single nucleotide polymorphisms (wgSNPs) were generated to traceback the potential contamination source in this outbreak. C. sakazakii isolates S2 from a patient’s rectal swab and S4 from leftover food sample shared identical PFGE pattern and sequence type (ST73), and clustered tightly together in the SNP phylogenetic tree. C. sakazakii isolates S5 and S6 from food delivery containers were both ST4 but with different PFGE patterns. Cronobacter isolates S1 and S3 from two patients’ rectal swab were sequenced to be C. malonaticus and shared another PFGE pattern (ST567). The interesting feature of this study was the implication of C. sakazakii as a causative agent in food-borne AGE occurring in healthy adults, although C. sakazakii is considered as an opportunistic pathogen and generally affects neonates, infants and immunocompromised adults.
Mobile health technology adoption across generations: Narrowing the digital divide

Mobile health (m‐health) technologies offer many benefits to individuals, organizations, and health professionals alike. Indeed, the utilization of m‐health by older adults can foster the development of proactive patients, while also reducing financial burden and resource pressures on health systems. However, the potentially transformative influence of m‐health is limited, as many older adults resist adoption leading to the emergence of an age‐based digital divide. This study leverages protection motivation theory and social cognitive theory to explore the factors driving resistance among older adults. This mixed methods study integrates survey findings with insights from qualitative interviews to highlight that the m‐health digital divide is deepening due to older adults' perceived inability to adopt and their unwillingness to adopt stemming from mistrust, high risk perceptions, and strong desire for privacy. The paper contributes to the privacy and social inclusion literature by demonstrating that while many older adults have access to m‐health, they are currently excluded and require careful consideration by technology organizations and researchers. The study provides recommendations for narrowing the m‐health digital divide through inclusive design and educational efforts to improve self‐efficacy, develop privacy literacy, and build trust, thereby ensuring that older citizens are both capable and willing to adopt.
Conflict resolution for structured merge via version space algebra

Resolving conflicts is the main challenge for software merging. The existing merge tools usually rely on the developer to manually resolve conflicts. This is of course inefficient. We propose an interactive approach for resolving merge conflicts. To the best of our knowledge, this is the first attempt for conflict resolution of structured merge. To represent the possibly very large set of candidate programs, we propose an expressive and efficient representation by version space algebra. We also design a simple mechanism for ranking resolutions in the program space, such that the top-ranked resolution is very likely to meet the developer's expectation. We prototype our approach as a merge tool AutoMerge, and evaluate it on 244 real-world conflicts arising from 10 open-source projects. Results show great practicality of our approach.
Learning Scene Illumination by Pairwise Photos from Rear and Front Mobile Cameras

Illumination estimation is an essential problem in computer vision, graphics and augmented reality. In this paper, we propose a learning based method to recover low‐frequency scene illumination represented as spherical harmonic (SH) functions by pairwise photos from rear and front cameras on mobile devices. An end‐to‐end deep convolutional neural network (CNN) structure is designed to process images on symmetric views and predict SH coefficients. We introduce a novel Render Loss to improve the rendering quality of the predicted illumination. A high quality high dynamic range (HDR) panoramic image dataset was developed for training and evaluation. Experiments show that our model produces visually and quantitatively superior results compared to the state‐of‐the‐arts. Moreover, our method is practical for mobile‐based applications.
Semantic Clustering of Functional Requirements Using Agglomerative Hierarchical Clustering

Software applications have become a fundamental part in the daily work of modern society as they meet different needs of users in different domains. Such needs are known as software requirements (SRs) which are separated into functional (software services) and non-functional (quality attributes). The first step of every software development project is SR elicitation. This step is a challenge task for developers as they need to understand and analyze SRs manually. For example, the collected functional SRs need to be categorized into different clusters to break-down the project into a set of sub-projects with related SRs and devote each sub-project to a separate development team. However, functional SRs clustering has never been considered in the literature. Therefore, in this paper, we propose an approach to automatically cluster functional requirements based on semantic measure. An empirical evaluation is conducted using four open-access software projects to evaluate our proposal. The experimental results demonstrate that the proposed approach identifies semantic clusters according to well-known used measures in the subject.
Composable higher-order reactors as the basis for a live reactive programming environment

A live programming environment allows programmers to edit programs while they are running. This means that successive "edit steps" must not allow a programmer to bring the program in a form that does not make any sense to the underlying language processor (i.e., parser, compiler,.). Many live programming environments therefore rely on disciplined edit steps that are based on language elements such as objects, classes, and methods. Textual modifications to these elements are not seen as edit steps until some "accept" button is hit. Unfortunately, no such elements exist in current reactive languages. We present a new reactive language, called Haai, that is based on first-class higher-order reactors. Linguistically, Haai programs correspond to reactors or compositions of reactors. At run-time, reactors produce an infinite stream of values just like signals and behaviours in existing languages. Haai's live programming environment relies on textual modifications of entire reactors as its basic edit steps. Changing a reactor automatically updates all occurrences of that reactor in the reactive program, while it is running.
Benchmark Dose Modeling of In Vitro Genotoxicity Data: a Reanalysis

The methods of applied genetic toxicology are changing from qualitative hazard identification to quantitative risk assessment. Recently, quantitative analysis with point of departure (PoD) metrics and benchmark dose (BMD) modeling have been applied to in vitro genotoxicity data. Two software packages are commonly used for BMD analysis. In previous studies, we performed quantitative dose-response analysis by using the PROAST software to quantitatively evaluate the mutagenicity of four piperidine nitroxides with various substituent groups on the 4-position of the piperidine ring and six cigarette whole smoke solutions (WSSs) prepared by bubbling machine-generated whole smoke. In the present study, we reanalyzed the obtained genotoxicity data by using the EPA’s BMD software (BMDS) to evaluate the inter-platform quantitative agreement of the estimates of genotoxic potency. We calculated the BMDs for 10%, 50%, and 100% (i.e., a two-fold increase), and 200% increases over the concurrent vehicle controls to achieve better discrimination of the dose-responses, along with their BMDLs (the lower 95% confidence interval of the BMD) and BMDUs (the upper 95% confidence interval of the BMD). The BMD values and rankings estimated in this study by using the EPA’s BMDS were reasonably similar to those calculated in our previous studies by using PROAST. These results indicated that both software packages were suitable for dose-response analysis using the mouse lymphoma assay and that the BMD modeling results from these software packages produced comparable rank orders of the mutagenic potency.
The CLoTH Simulator for HTLC Payment Networks with Introductory Lightning Network Performance Results

The Lightning Network (LN) is one of the most promising off-chain scaling solutions for Bitcoin, as it enables off-chain payments which are not subject to the well-known blockchain scalability limit. In this work, we introduce CLoTH, a simulator for HTLC payment networks (of which LN is the best working example). It simulates input-defined payments on an input-defined HTLC network and produces performance measures in terms of payment-related statistics (such as time to complete payments and probability of payment failure). CLoTH helps to predict issues and obstacles that might emerge in the development stages of an HTLC payment network and to estimate the effects of an optimisation action before deploying it. We conducted simulations on a recent snapshot of the HTLC payment network of LN. These simulations allowed us to identify network and payments configurations for which a payment is more likely to fail than to succeed. We proposed viable solutions to avoid such configurations.
Verified three-way program merge

Even though many programmers rely on 3-way merge tools to integrate changes from different branches, such tools can introduce subtle bugs in the integration process. This paper aims to mitigate this problem by defining a semantic notion of conflict-freedom, which ensures that the merged program does not introduce new unwanted behaviors. We also show how to verify this property using a novel, compositional algorithm that combines lightweight summarization for shared program fragments with precise relational reasoning for the modifications. Towards this goal, our method uses a 4-way differencing algorithm on abstract syntax trees to represent different program versions as edits applied to a shared program with holes. This representation allows our verification algorithm to reason about different edits in isolation and compose them to obtain an overall proof of conflict freedom. We have implemented the proposed technique in a new tool called SafeMerge for Java and evaluate it on 52 real-world merge scenarios obtained from Github. The experimental results demonstrate the benefits of our approach over syntactic conflict-freedom and indicate that SafeMerge is both precise and practical.
The Quality Solution: The Stakeholder's Guide to Improving Health Care

The Quality Solution: The Stakeholder's Guide to Improving Health Care Nash DB, Goldfarb NI, eds. 321 pages. Sudbury, MA: Jones and Bartlett; 2006. $51.95. ISBN 0763727482. Order at www.jbpub. com. Field of medicine: Health care delivery. Format: Paperback book. Audience: Clinicians, medical students, health administrators, employers, and researchers seeking strategies for identifying, measuring, and improving health care. Purpose: In response to the Institute of Medicine's report, Crossing the Quality Chasm, The Quality Solution, the book attempts to frame quality health care by providing a guide for quality improvement tailored to the unique perspectives of key stakeholders. It offers a plan for bridging the quality chasmrecognizing that the chasm can be crossed at many points with a variety of mechanisms, ranging from incentives to technology. Content: In a well-organized and instructive manner, the book defines quality health care, its measurement, and ways in which it can be improved. The chapters are organized from the perspectives of health care stakeholders: consumers, payers, health care providers, and employers. On the basis of information found in each chapter, stakeholders can devise individual plans that, in total, will improve health care quality. All chapters have learning objectives and discussion points and end with a case study that illustrates key concepts and action plans. Highlights: The book is an excellent example of the whole being greater than the sum of its parts. It is refreshing from many different perspectives and offers something for nearly everyone interested in improving health care quality. Useful concrete examples are presented throughout the book, and the editors ensure a common lexicon, which facilitates understanding and move the reader toward an action plan. Limitations: Many health care quality improvement guides are written with a flavor of changing the system rather than blaming the individual. Yet, every conscientious physician is familiar with the feeling that stems from picking up a patient's chart and seeing a colleague's hurried scrawl. Like many other quality improvement initiatives, this book does not discuss how physicians can address quality with their peers. A systems solution will only get us part of the way there. Related readings: The Institute of Medicine report, Crossing the Quality Chasm: A New Health System for the 21st Century (National Academies Pr, 2001), and Kohn and colleagues' To Err Is Human: Building a Safer Health System (National Academies Pr, 2000). Reviewer: Cathy Bradley, PhD, Virginia Commonwealth University, Richmond, Virginia.
Locally Differentially Private Participant Recruitment for Mobile Crowdsourcing

Location-aware mobile crowdsourcing tasks like urban sensing always require exposing users' location, which lead to serious privacy breaches. In this poster, we propose a locally differentially private participants recruitment system to maximize spatial coverage of the mobile crowdsourcing task while preserving location privacy. Based on the mechanism of randomized response, our system preserves the privacy in a local way, which eliminates the need for a trusted server. With guaranteed location privacy protection, a heuristic algorithm is proposed to solve the maximum spatial coverage problem efficiently given the obfuscated reports. Extensive experiments on real-world user trajectories demonstrate the feasibility of our proposed system, which improves the spatial coverage by more than 10% on average compared with the state-of-the-art solutions.
Insights into the evolutionary dynamics of Neotropical biomes from the phylogeography and paleodistribution modeling of Bromelia balansae.

PREMISE OF THE STUDY Historical abiotic and biotic factors have strongly affected species diversification and speciation. Although pre-Pleistocene events have been linked to the divergence of several Neotropical organisms, studies have highlighted a more prominent role of Pleistocene climatic oscillations in shaping current patterns of genetic variation of plants. METHODS We performed phylogeographic analyses based on plastidial markers and modeled the current distribution and paleodistribution of Bromelia balansae (Bromeliaceae), an herbaceous species with a wide geographical distribution in South America, to infer the processes underlying its evolutionary history. KEY RESULTS Combined molecular and paleodistributional modeling analyses indicated retraction during the Last Glacial Maximum followed by interglacial expansion. Populations occurring in the semideciduous Atlantic Forest and the Cerrado formed two distinct genetic clusters, which have been historically or ecologically isolated since late Pliocene to early Pleistocene. Populations located in the transition zone had higher levels of genetic diversity, as expected by the long-term climatic stability in the region detected in our ecological niche models. CONCLUSIONS Our study adds important information on how herbaceous species have been affected by past climate in Central and Southeast Brazil, helping to disentangle the complex processes that have triggered the evolution of Neotropical biota.
Flavonoids as putative modulators of &Dgr;4‐, &Dgr;5‐, and &Dgr;6‐desaturases: Studies in cultured hepatocytes, myocytes, and adipocytes

This study was conducted to screen flavonoids for affecting expression of desaturases involved in omega-3 fatty acid synthesis and ceramide (CER) metabolism. To this end, cultured HepG2 hepatocytes, C2C12 myocytes, and 3T3-L1 adipocytes were treated with nontoxic concentrations of 12 selected flavonoids and expression of Δ4-, Δ5-, and Δ6-desaturases (DEGS1, FADS1, and FADS2, respectively) was determined. The flavonoids tested were more cytotoxic to HepG2 and 3T3-L1 than to C2C12 cells. In HepG2 cells, FADS1 was induced by quercetin and FADS2 expression was increased by daidzein, genistein, and pratensein treatment. DEGS1 was increased by apigenin, luteolin, orobol, and quercetin administration. In differentiated C2C12 cells, substances had no inducing effect or even lowered target gene expression. Pratensein induced both FADS1 and FADS2 in differentiated 3T3-L1 cells and DEGS1 was increased by treatment with apigenin, genistein, luteolin, orobol, and quercetin. In conclusion, pratensein may be an interesting test compound for further studies in vitro and in vivo on omega-3 synthesis since it induces its rate-limiting enzyme FADS2. Apigenin, luteolin, orobol, and quercetin induced DEGS1 and thereby possibly synthesis of proapoptotic CER in malignant HepG2 cells and 3T3-L1. In contrast, in benign C2C12 cells, they did not elevate mRNA steady state levels of DEGS1. That may partly explain the higher resistance of C2C12 cells against flavonoids compared to the other cell lines. By affecting tumor cells and nontumor cells differently, these flavonoids may be promising substances for further research regarding anticancer properties. © 2018 BioFactors, 44(5):485-495, 2018.
Food insecurity, financial priority, and nutrition literacy of university students at a mid-size private university

Abstract Objectives: The purpose of the study was to examine food insecurity in a mid-sized private Catholic university, taking into consideration students’ financial prioritization and nutrition literacy. Participants: Participants included 560 university undergraduate and graduate students in the fall of 2017. Methods: Measures assessed food insecurity, nutrition literacy, and financial prioritization. The USDA 6-question food insecurity screener and the New Vital Signs Food Label Instruments were utilized to measure food security and nutrition literacy. To measure financial priority, participants ranked nine items from highest to lowest priority. Results: Out of 560 university students, 35.8% of students were characterized as food insecure. Students who prioritized spending money on alcohol or tuition had higher odds of experiencing food insecurity. Conclusion: Prevalence of food insecurity may be as prevalent in private universities as in public universities. This warrants exploration to identify contributing factors and long-term solutions.
Revisiting CFR+ and Alternating Updates

The CFR+ algorithm for solving imperfect information games is a variant of the popular CFR algorithm, with faster empirical performance on a range of problems. It was introduced with a theoretical upper bound on solution error, but subsequent work showed an error in one step of the proof. We provide updated proofs to recover the original bound.