Miracle-dz/UniFAR-FTUs huggingface dataset:
Microbiological Diagnosis for Periodontal Diseases

Periodontitis, an infectious disease caused by bacteria, brings about destructive changes leading to loss of bone and connective tissue attachment (Williams, 1990). Several oral bacteria are considered to be possible pathogens in periodontitis (Darveau et al., 1997). In particular, the black-pigmented, Gram-negative anaerobic rods Porphyromonas gingivalis and Tannerella forsythia have been implicated as major pathogens in the etiology of this disease. These two species are frequently isolated together, implying the existence of an ecological relationship between these organisms (Darveau et al., 1997). Treponema denticola, a helical oral spirochete, has also been considered as a major pathogen in periodontitis (Darveau et al., 1997). Mixed infection with these three bacteria in periodontal sites is correlated strongly with the severity of adult periodontitis (Socransky & Haffajee, 1998). Socransky named this combination the “red complex” and found that these bacteria were most crucial for the progression of this disease (Socransky & Haffajee, 1998). Thus, the detection of these organisms provides essential information about the severity of periodontitis. Aggregatibacter actinomycetemcomitans is suspected to be the most probable causal factor for aggressive periodontitis in adolescents (Darveau et al., 1997). Although we cannot completely rule out the possibility of exogenous infection, periodontitis is thought to be primarily an endogenous infection caused by oral bacteria. Various systems for the detection of oral pathogens have been reported, but most are qualitative (Yoshida et al., 2005a; Yoshida et al., 2005b). Because periodontal pathogens exist not only in infected pockets but also in the healthy sulcus, qualitative detection is not suitable for the diagnosis of periodontitis. For this purpose, we have developed a quantitative detection system that uses real-time polymerase chain reaction (PCR) methodology (Yoshida et al., 2003a; Yoshida et al., 2003b ). The best time for the detection of oral bacteria remains unclear. When during the periodontal treatment process should a diagnostic system be used? Can a quantitative detection system be used for the initial diagnosis of periodontitis? Furthermore, periodontitis is influenced by multiple factors such as genetic, environmental, and lifestyle-related factors that complicate the determination of a microbial cut-off value for disease onset. The use of microbiological detection for the initial diagnosis of periodontitis is thus likely to be of limited value. Nevertheless, microbiological diagnosis is meaningful in evaluating the effects of periodontal therapy. During periodontal therapy, factors
A Fast Algorithm for Segmenting Defects on the Surface of QFN Packages

There are many different types of surface defects on semiconductor Integrated Chips (IC's) caused by various factors during manufacturing process, such as Scratch, Flash, Resin bleed, Melting and Void. These defects must be detected and classified by an inspection system for productivity improvement and effective process control. Among these defects, in particular, Resin bleed and Melting are the most difficult ones to classify accurately. The shape of Resin bleed and Melting defects are so similar that normally it is difficult to classify the Resin bleed and Melting. In this paper, we propose a new segmenting method and a set of features for detecting and classifying the Resin bleed and Melting defects.
FEATURE EXTRACTION ENCHANCEMENT IN USERS’ ATTITUDE DETECTION

The social network are the trendiest applications which are developed for sharing opinions about different topics or events e.g. Twitter. As a result, this kind of applications becomes abundant data source for NLP researchers to innovate and enhance techniques that can track users’ attitudes towards target event, topic or even another person. These users’ attitudes are playing a pivotal role for decision makers, so they can take an appropriate action towards users’ negative or positive reactions either. This paper focuses on users’ attitude detection based on new feature set and applies on different machine learning models that can monitor and enhance users’ attitude identification system. Annotated emotion tweets dataset and word emotion lexicon are used in training, building, and testing classification models.
Inductance dans son environnement : caractérisation des inductances planaires intégrées dans les conditions d'utilisation de l'électronique de puissance

Dans les applications de l’electronique de puissance, les inductances sont generalement utilisees avec des formes d’ondes triangulaire et rectangulaire. Dans ces conditions, les inductances ne peuvent pas etre caracterisees avec des formes d’ondes sinusoidales. Il existe dans la litterature plusieurs methodes de caracterisation des inductances. Aucune de ces methodes ne permet de caracteriser les composants magnetiques integres dans des conditions compatibles avec les formes d’onde de l’electronique de puissance. Une nouvelle methode de caracterisation en temps reel convenable aux composants magnetiques planaires integrees est developpee dans cette these. Le composant sous test est utilise dans un convertisseur DC-DC. A partir du courant i(t) et de la tension u(t) releves a ses bornes, il est possible de determiner la caracteristique φ(i) du composant. Connaissant le cycle d’hysteresis φ(i), les principaux parametres du composant tels que la valeur de l’inductance, le niveau de saturation du materiau magnetique, les pertes fer peuvent etre determinees. Il convient de preciser qu’apres l’enregistrement de u(t) et de i(t), un traitement des donnees approprie est effectue pour obtenir des signaux exploitables. L’approche a ete testee avec succes sur des inductances discretes et planaires integrees pour des frequences de mesure allant jusqu’au MHz. Nous avons ainsi montre que cette methode permet de relever des cycles mineurs jusqu’a la saturation du materiau magnetique et de tracer l’evolution de l’inductance en fonction de la composante continue du courant. Les resultats montrent que pour de tres faibles courants, on a des fortes valeurs de l’inductance qui sont quasiment constantes, en revanche a des courants moyens, l’inductance diminue fortement et a des forts courants, le circuit magnetique se sature et la valeur de l’inductance devient donc tres faible. Cette methode permet egalement d’etudier l’evolution des pertes fer dans les memes conditions d’utilisation que celles rencontrees en electronique de puissance
Birth Control Knowledge among Pharmacy Undergraduate Students in Vietnam: A Case Study and Situation Analysis

Aims: The main goal of this study is to define the factors that contribute to the knowledge, awareness, perceptions, and practice of birth control among pharmacy students at Lac Hong University (LHU) in Dong Nai Province. Subjects and Methods: A prospective cohort study was conducted among pharmacy students over 4 months from September to December 2017. Results: All respondents (n = 403) had heard of birth control methods. Nearly 90% of participants indicated that the male condom can protect against sexually transmitted diseases. Condoms are also the most common method of birth control. The mean knowledge and awareness scores of students were 4.52 ± 1.420 and 20.67 ± 4.06, respectively. The highest birth control knowledge score was 5.64 ± 0.996. Fifth-year students were the most knowledgeable about contraceptive use and had the highest mean knowledge score (4.82 ± 1.307). A significant association was found between marital status (P < 0.001), religion (P < 0.05), and mean knowledge of the respondents. Conclusions: Overall, the findings reflect that the majority of students at LHU had a poor understanding and awareness of contraception methods. Health education and awareness programs should be initiated for students to provide them with correct knowledge about contraception. The knowledge of these future health-care professionals will play an important role in improving public health.
Development of topological tools for the analysis of biological data

There is a growing need for unbiased clustering algorithms, ideally automated to analyze complex data sets. Topological data analysis (TDA) has been used to approach this problem. This recent field of mathematics discerns characteristic features of a space without relying on probabilistic approaches. It provides robust qualitative and quantitative assessments of the structure of data. Mapper, an algorithm of TDA, showed increased power over standard methods for complex data and overcame problems of noise. However, it relies on the selection of several parameters and is not well suited for small datasets. To overcome these problems, we have developed a topology-based clustering algorithm called Two-Tier Mapper (TTMap) to detect subgroups in global gene expression datasets and to identify their distinguishing features in a two groups comparison. First, TTMap discerns and adjusts for highly variable features in the control group and identifies outliers. Second, in order to obtain an individual appreciation of the differences with respect to the control group, a profile of deviation is computed for each test sample. Test samples are clustered according to two tiers creating a global and local network using a new topological algorithm based on Mapper, where all the parameters are carefully chosen or data-driven, avoiding any user induced bias. These choices render the algorithm theoretically stable. In particular when sample sizes are small, TTMap outperforms existing clustering methods in finding relevant subgroups, in stability on synthetic and biological datasets and in revealing more gene expression changes. Datasets from different sources can readily be combined into one analysis. Thus, TTMap can extract information from highly variable biological samples, and since an individual profile of deviation is established, it has potential for personalized medicine. The algorithm was developed as an open source R package deposited at the Bioconductor. Furthermore, two additional applications of topology were developed in order to find differences in gene expression through the menstrual cycle and cyclical patterns in gene expression related to hormone response.
Endogenous RhoG Is Rapidly Activated after Epidermal Growth Factor Stimulation through Multiple Guanine-Nucleotide Exchange Factors

In this article it is shown that EGF stimulation leads to rapid activation of RhoG through Vav GEFs and the GEF PLEKHG6. Importantly, different cellular responses induced by EGF are determined by the available GEFs. Furthermore, this article presents results showing that EGF-stimulated cell migration and EGFR internalization are regulated by RhoG.
Variations in contractile properties of rabbit single muscle fibres in relation to troponin T isoforms and myosin light chains.

1. The maximal velocity of shortening (Vmax), tension‐pCa relationships and the contractile and regulatory protein composition were determined in single, chemically skinned fibres from adult rabbit plantaris muscles. 2. Three groups of fibres were identified based on their protein compositions. One group had exclusively the slow‐type myosin heavy chain (MHC) and myosin light chains (LC) and had low velocities. Another group of fibres had mixtures of fast‐type and slow‐type MHCs and LCs and had intermediate shortening velocities. The third group of fibres had fast‐type myosin heavy and light chains and high velocities. 3. The low‐velocity fibres had a mean velocity (+/‐ S.E.M.) of 0.86 +/‐ 0.03 muscle lengths/s (ML/s) at 15 degrees C. The remaining fibres formed a continuum with respect to Vmax from 1.37 to 3.94 ML/s. These results indicate that a much greater diversity exists among single fibres from adult mammalian skeletal muscle than previously recognized. The intermediate‐ and high‐velocity fibres formed a continuum (from slow to fast) with respect to the amount of myosin light chain 3 (LC3). That is, Vmax increased with the relative LC3 content in single fibres in the intermediate‐ and high‐velocity groups in a quantitative, statistically significant manner. 4. Three isoforms of fast‐type troponin T were identified among the intermediate‐ and high‐velocity fibres. These fibres also contained fast‐type troponin C and troponin I. As was the case with the relative LC3 content, these fibres also formed a continuum with respect to the relative proportions of the three isoforms of fast‐type troponin T. It appears that different isoforms of troponin T are responsible for a slightly higher Ca2+ sensitivity of tension development in the high‐velocity fibres compared to the intermediate fibres. The continuum in troponin T isoform composition paralleled an increase in Vmax among these fibres. 5. The low‐velocity fibres had the highest Ca2+ sensitivity of the three groups and had exclusively the slow‐type isoforms of the regulatory proteins in the troponin complex. 6. The co‐ordinated variations in troponin T and LC3 compositions among the intermediate‐ and high‐velocity fibres are discussed as a possible means for the further differentiation of the contractile properties of the fibres in these two groups, beyond that provided by myosin heavy chain isoforms alone.
Peer Influence Via Instagram: Effects on Brain and Behavior in Adolescence and Young Adulthood.

Mobile social media often feature the ability to "Like" content posted by others. This study examined the effect of Likes on youths' neural and behavioral responses to photographs. High school and college students (N = 61, ages 13-21) viewed theirs and others' Instagram photographs while undergoing functional Magnetic Resonance Imaging (fMRI). Participants more often Liked photographs that appeared to have received many (vs. few) Likes. Popular photographs elicited greater activity in multiple brain regions, including the nucleus accumbens (NAcc), a hub of the brain's reward circuitry. NAcc responsivity increased with age for high school but not college students. When viewing images depicting risk-taking (vs. nonrisky photographs), high school students, but not college students, showed decreased activation of neural regions implicated in cognitive control.
A new mechanism for preventing HVM-Aware Malware

Hardware-based Virtual Machine (HVM), for its high efficiency and good simulation, has played an important role in the course of building honeypots and debuggers. But some malwares called HVM-Aware Malware can identify the virtualized environment which they are processing in and then stop themselves to avoid being analysed. One of the most efficient HVM-Aware technologies is called "Counter-Based Detection". It's a very risky challenge to HVM-based honeypots and debuggers. In this paper a new mechanism based on operation interception and return value distortion is presented to solve this problem, it can prevent HVM from being identified so that it can protect honeypots and debuggers very well. At last some experiments demonstrate the effectiveness and practicality of the mechanism.
Eating disturbances in the elderly: A geriatric-psychiatric perspective

The prevalence of malnutrition among older adults is increasing, leading to poor health outcomes and increased mortality. This review sheds light on the different etiologies of eating disturbances in the elderly and discusses assessment tools and treatment strategies. Older adults are found to be more prone to nutritional deficiencies and weight loss due to age related physiological and psychosocial changes, in addition to pathological medical and psychiatric disorders. The short form of the Mini Nutritional Assessment is considered the most commonly used screening tool in older persons. Individuals identified as malnourished or at high risk of malnutrition would benefit from comprehensive treatment plans according to the underlying etiology. Those involve environmental changes, oral nutritional supplements and ultimately pharmacotherapy.
Evaluation of supervisory control interfaces for mobile robot integration with tactical teams

As robotic systems become more sophisticated, they are increasingly called upon to accompany humans in high-stress environments. This research was conducted to support the integration of robotic systems into tactical teams operating in challenging and stressful environments. Robotic systems used to assist tactical teams will need to support some form of autonomy; these systems must be capable of providing operators supervisory control in cases of unpredictable real-time events. An evaluation of the relative effectiveness of three different methods of supervisory control of an autonomously operated mobile robot system was conducted: (1) hand gestures using a Microsoft Kinect, (2) an interactive Android application on a hand-held mobile device, and (3) verbal commands issued through a headset. These methods of supervisory control were compared to a teleoperated robot using a gamepad controller. The results from this pilot study determined that the touchscreen device was the easiest interface to use to override the robot's next intended movement (L2(3,23)=11.413, p=. 003, d=1.58) and was considered the easiest interface to use overall (L2(3,23)=8.078, p=. 044, d=. 93). The results also indicate that the touchscreen device provided the most enjoyable, satisfying, and engaging interface of the four user interfaces evaluated.
Generation and Characterization of a Breast Cancer Resistance Protein Humanized Mouse Model

Breast cancer resistance protein (BCRP) is expressed in various tissues, such as the gut, liver, kidney and blood brain barrier (BBB), where it mediates the unidirectional transport of substrates to the apical/luminal side of polarized cells. Thereby BCRP acts as an efflux pump, mediating the elimination or restricting the entry of endogenous compounds or xenobiotics into tissues and it plays important roles in drug disposition, efficacy and safety. Bcrp knockout mice (Bcrp−/−) have been used widely to study the role of this transporter in limiting intestinal absorption and brain penetration of substrate compounds. Here we describe the first generation and characterization of a mouse line humanized for BCRP (hBCRP), in which the mouse coding sequence from the start to stop codon was replaced with the corresponding human genomic region, such that the human transporter is expressed under control of the murine Bcrp promoter. We demonstrate robust human and loss of mouse BCRP/Bcrp mRNA and protein expression in the hBCRP mice and the absence of major compensatory changes in the expression of other genes involved in drug metabolism and disposition. Pharmacokinetic and brain distribution studies with several BCRP probe substrates confirmed the functional activity of the human transporter in these mice. Furthermore, we provide practical examples for the use of hBCRP mice to study drug-drug interactions (DDIs). The hBCRP mouse is a promising model to study the in vivo role of human BCRP in limiting absorption and BBB penetration of substrate compounds and to investigate clinically relevant DDIs involving BCRP.
Relational Learning Based Happiness Intensity Analysis in a Group

Pictures and videos from social events and gatherings usually contain multiple people. Physiological and behavioral science studies indicate that there are strong emotional connections among group members. These emotional relations among group members are indispensable to better analyzing individual emotions in a group. However, most of the existing affective computing methods focus on estimating the emotion of a single object only. In this work, we concentrate on estimating happiness intensities of group members while considering the reciprocities among them. We propose a novel facial descriptor that effectively captures happiness related facial action units. We also introduce two different structural regression models, Continuous Conditional Random Fields (CCRF) and Continuous Conditional Neural Fields (CCNF), for estimating emotions of group members. Our experimental results on HAPPEI dataset demonstrate the viability of proposed features and the two frameworks.
Resilience to a Cyber-Attack on the Automobile Industry: A Computable General Equilibrium Approach

The overall objective of this research is to improve risk management for cyber-threats among both private and public sectors through better understanding of the economic consequence of cyber-attacks and the benefits of various cyber resilience tactics in reducing these consequences. This is carried out in 3 stages: 1) estimation of direct effectiveness and costs of post-attack cyber resilience tactics; 2) adaptation of a state-of-the-art economic impact modeling approach to estimate cyber-attack consequences and resilience potential at both the microeconomic and macroeconomic levels; and 3) an empirical assessment of cyber-resilience in the U.S. Automobile Industry using the economic model to provide insights for decision makers to enhance resilience to cyber-attacks.
Associations between Familial Factor, Trait Conscientiousness, Gender and the Occurrence of Type 2 Diabetes in Adulthood: Evidence from a British Cohort

Objective To investigate social, familial, and psychological factors in influencing the occurrence of type 2 diabetes in adulthood. Method Some 17,415 babies born in Great Britain in 1958 and followed up at 7, 11, 33, and 50 years of age. The prevalence of type 2 diabetes at age 50 years was the outcome measure. Results Some 5,032 participants with data on parental social class, childhood cognitive ability tests scores at age 11 years, educational qualifications at age 33 years, personality traits, occupational levels, and type 2 diabetes (all measured at age 50 years) were included in the study. Available information also included whether cohort members’ parents or siblings had diabetes. Using logistic regression analyses, results showed that sex (OR=0.63: 0.42-0.92, p<.05), family history (OR=3.40: 1.76-6.55, p<.01), and trait conscientiousness (OR=0.76: 0.64-0.90, p<.001) were all significantly and independently associated with the occurrence of type 2 diabetes in adulthood. It appears that the occurrence of type 2 diabetes is greater among men than women (4.3% vs 2.5%). Conclusion Familial (genetic and non-genetic) and psychological factors are significantly associated with the prevalence of type 2 diabetes in adulthood.