Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of GSTT1 null, XPD 751 CC and XPC 939 CC genotypes with increased levels of genomic damage among hospital pathologists

Abstract Context: Hospital workers are at risk for genotoxic damage following occupationally exposure to xenobiotics. Pathologists are exposed to chemicals during their use in health care environments, particularly throughout inhalation of airborne agents, absorption through skin or contact with the patient’s body fluids. Objective: We evaluated the level of genomic damage in a sample of 61 hospital pathologists (occupationally exposed to antineoplastic drugs and sterilizing agents) and 60 control subjects. Materials and methods: Lymphocytes were analyzed by SCEs and CAs assays and genotyped for GSTT1, GSTM1, CYP1A1 Ile/Val, XPD (A751C) and XPC (A939C) gene polymorphisms. Results: Pathologists showed significantly higher frequencies of SCEs and CAs with respect to control subjects. GSTT1 null genotype was found to be associated with higher SCEs and CAs frequencies, whereas XPD 751 CC and XPC 939 CC genotypes only with a higher level of SCEs. Discussion and conclusions: The SCEs and CAs results are consistent with other published data, placing hospital workers as a category at risk for genotoxic damage caused by chronic exposure to xenobiotics. The higher levels of cytogenetic damage observed among GSTT1 null, XPD 751 and XPC 939 CC homozygote subjects confirm the importance of the genetic polymorphisms analysis associated to genotoxicological studies.
Detection of the Evil ring attack in wireless sensor networks using cross verification

In ad hoc networks and wireless sensor networks, several routing algorithms rely on the knowledge by the network nodes of their own geographic location and those of others. For cases where a node doesn't have its own positioning device (e.g., GPS), Alfaro et al. propose several algorithms that a node can run to determine its geographic position using position reports from neighbors. In this paper, we first present the evil ring attack, an attack on the geographic location algorithms of Alfaro et al. that misleads nodes about the true position of their neighbors. An attacker sends false reports with a position that sits on a circle centered at the victim's location and of a radius equal to the distance between the victim and attacker. The attack succeeds because the calculation of the distance between the victim and attacker is not affected despite this fake position. We then present and analyze an evil ring attack detection algorithm in which a position-unaware sensor node crosschecks the consistency of the information it collects from its neighbors with the information collected by other trusted neighbors. This algorithm detects the existence of neighbors running the evil ring attack. We propose a general distributed algorithm for a) localizing sensors in a wireless sensor network in the presence of some malfunctioning ones, and b) detecting such malfunctioning sensors.
Reasons for Fighting among Violent Female Adolescents: A Qualitative Investigation from an Urban, Midwestern Community

This qualitative study examines the self-reported reasons for fighting among female adolescents (N = 72). Data are drawn from brief intervention sessions addressing violent behavior and alcohol use. Young women age 14 to 18 (Mean = 16) were recruited in an urban emergency department (58.3% African American/Black, 31.9% White, and 9.7% other races/ethnicities). Participants identified multiple reasons that they engage in fights including self-protection/self-defense, enhancing social status and respect, safety (e.g., preventing future fights or sexual assaults), revenge/retaliation, social motivations (e.g., defending family or friends, fighting over romantic interests), coping, and enjoyment. Results provide insight into opportunities and challenges in developing interventions addressing aggression among female adolescents.
Influence of transverse deformation on resonant frequency of patch antenna

The strain sensor based on microwave patch antenna is presented to monitor structural strain. Theoretically, the resonant frequency of antenna is determined by both the length and the width of the antenna. When the antenna is stretched uniaxially, the resonant frequency of the antenna shifts mainly due to its length change in longitudinal direction. However, the effect of the transverse deformation due to Poisson effect on resonant frequency of the antenna is yet to be confirmed and evaluated. Two sets of experiments are prepared to study the effect. The resonant frequencies of 2.45GHz chipless patch antennas with fixed length and varying width are tested; and the 920MHz chipped patch antennas are attached to the surface of specimens with the stretching direction parallel to length direction of antennas and perpendicular to length direction, respectively. Both types of specimens are stretched under different levels of tension force to determine the sensitivity coefficient between resonant frequency shift and antenna strain. Both results show that the influence of the transverse deformation of antennas on resonant frequency can be neglected, and its resonance frequency has a good linear relationship with the longitudinal strain.
The mat sat on the cat: investigating structure in the evaluation of order in machine translation

We present a multifaceted investigation into the relevance of word order in machine translation. We introduce two tools, DTED and DERP, each using dependency structure to detect differences between the structures of machine-produced translations and human-produced references. DTED applies the principle of Tree Edit Distance to calculate edit operations required to convert one structure into another. Four variants of DTED have been produced, differing in the importance they place on words which match between the two sentences. DERP represents a more detailed procedure, making use of the dependency relations between words when evaluating the disparities between paths connecting matching nodes. In order to empirically evaluate DTED and DERP, and as a standalone contribution, we have produced WOJ-DB, a database of human judgments. Containing scores relating to translation adequacy and more specifically to word order quality, this is intended to support investigations into a wide range of translation phenomena. We report an internal evaluation of the information in WOJ-DB, then use it to evaluate variants of DTED and DERP, both to determine their relative merit and their strength relative to third-party baselines. We present our conclusions about the importance of structure to the tools and their relevance to word order specifically, then propose further related avenues of research suggested or enabled by our work. Candidate’s Declaration I, Martin McCaffery, hereby certify that this thesis, which is approximately 57, 000 words in length, has been written by me, and that it is the record of work carried out by me, or principally by myself in collaboration with others as acknowledged, and that it has not been submitted in any previous application for a higher degree. I was admitted as a research student in March 2013, and as a candidate for the degree of Doctor of Philosophy in June 2017; the higher study for which this is a record was carried out in the University of St Andrews between 2013 and 2017. Date . Signature of Candidate . Supervisor’s Declaration I hereby certify that the candidate has fulfilled the conditions of the Resolution and Regulations appropriate for the degree of Doctor of Philosophy in the University of St Andrews and that the candidate is qualified to submit this thesis in application for that degree. Date . Signature of Supervisor .
Role of Metal-Dependent Regulation of ESX-3 Secretion in Intracellular Survival of Mycobacterium tuberculosis

ABSTRACT More people die every year from Mycobacterium tuberculosis infection than from infection by any other bacterial pathogen. Type VII secretion systems (T7SS) are used by both environmental and pathogenic mycobacteria to secrete proteins across their complex cell envelope. In the nonpathogen Mycobacterium smegmatis, the ESX-1 T7SS plays a role in conjugation, and the ESX-3 T7SS is involved in metal homeostasis. In M. tuberculosis, these secretion systems have taken on roles in virulence, and they also are targets of the host immune response. ESX-3 secretes a heterodimer composed of EsxG (TB9.8) and EsxH (TB10.4), which impairs phagosome maturation in macrophages and is essential for virulence in mice. Given the importance of EsxG and EsxH during infection, we examined their regulation. With M. tuberculosis, the secretion of EsxG and EsxH was regulated in response to iron and zinc, in accordance with the previously described transcriptional response of the esx-3 locus to these metals. While iron regulated the esx-3 expression in both M. tuberculosis and M. smegmatis, there is a significant difference in the dynamics of this regulation. In M. smegmatis, the esx-3 locus behaved like other iron-regulated genes such as mbtB. In M. tuberculosis, both iron and zinc modestly repressed esx-3 expression. Diminished secretion of EsxG and EsxH in response to these metals altered the interaction of M. tuberculosis with macrophages, leading to impaired intracellular M. tuberculosis survival. Our findings detail the regulatory differences of esx-3 in M. tuberculosis and M. smegmatis and demonstrate the importance of metal-dependent regulation of ESX-3 for virulence in M. tuberculosis.
The gap between medical faculty’s perceptions and use of e-learning resources

ABSTRACT Background: e-Learning resources have become increasingly popular in medical education; however, there has been scant research on faculty perceptions and use of these resources. Objective: To investigate medical faculty’s use of e-learning resources and to draw on practical implications for fostering their use of such resources. Design: Approximately 500 full-time faculty members in 35 medical schools across the nation in South Korea were invited to participate in a 30-item questionnaire on their perceptions and use of e-learning resources in medical education. The questionnaires were distributed in both online and paper formats. Descriptive analysis and reliability analysis were conducted of the data. Results: Eighty faculty members from 28 medical schools returned the questionnaires. Twenty-two percent of respondents were female and 78% were male, and their rank, disciplines, and years of teaching experience all varied. Participants had positive perceptions of e-learning resources in terms of usefulness for student learning and usability; still, only 39% of them incorporated those resources in their teaching. The most frequently selected reasons for not using e-learning resources in their teaching were ‘lack of resources relevant to my lectures,’ ‘lack of time to use them during lectures,’ and ‘was not aware of their availability. ’ Conclusions: Our study indicates a gap between medical faculty’s positive perceptions of e-learning resources and their low use of such resources. Our findings highlight the needs for further study of individual and institutional barriers to faculty adoption of e-learning resources to bridge this gap.
Diffusion of Messages from an Electronic Cigarette Brand to Potential Users through Twitter

Objective This study explores the presence and actions of an electronic cigarette (e-cigarette) brand, Blu, on Twitter to observe how marketing messages are sent and diffused through the retweet (i.e., message forwarding) functionality. Retweet networks enable messages to reach additional Twitter users beyond the sender’s local network. We follow messages from their origin through multiple retweets to identify which messages have more reach, and the different users who are exposed. Methods We collected three months of publicly available data from Twitter. A combination of techniques in social network analysis and content analysis were applied to determine the various networks of users who are exposed to e-cigarette messages and how the retweet network can affect which messages spread. Results The Blu retweet network expanded during the study period. Analysis of user profiles combined with network cluster analysis showed that messages of certain topics were only circulated within a community of e-cigarette supporters, while other topics spread further, reaching more general Twitter users who may not support or use e-cigarettes. Conclusions Retweet networks can serve as proxy filters for marketing messages, as Twitter users decide which messages they will continue to diffuse among their followers. As certain e-cigarette messages extend beyond their point of origin, the audience being exposed expands beyond the e-cigarette community. Potential implications for health education campaigns include utilizing Twitter and targeting important gatekeepers or hubs that would maximize message diffusion.
Time-Dependent External Electric Field 2 III . Energy Injection and Equilibration

M. Ali-Akbari∗,1 Hajar Ebrahim†,2, 3 and S. Heshmatian‡4 Department of Physics, Shahid Beheshti University G.C. , Evin, Tehran 19839, Iran Department of Physics, University of Tehran, North Karegar Ave., Tehran 14395-547, Iran School of Physics, Institute for Research in Fundamental Sciences (IPM), P.O. Box 19395-5531, Tehran, Iran Department of Engineering Science, Buein Zahra Technical University, Buein Zahra, Qazvin, Iran
A Network Traffic Scheduler for a VoD Server on the Internet

Most of the Video on Demand (VoD) systems were designed to work in dedicated networks. However, there are some approaches that provide VoD service in nondedicated and best effort networks, but they adapt the media’s quality according to the available network bandwidth. Our research activities focus on VoD systems with high quality service on nondedicated networks. Currently, we have designed and developed, to integrate in the VoD server, a network manager that provides: total network control, network state information, and adaptation of the transmission rate in a TCP-Friendly way. The present work describes this network manager, named Network Traffic Scheduler (NTS), which incorporates a congestion control algorithm named "Enhanced Rate Adaptation Protocol" (ERAP). ERAP is an optimization of the well-known protocol denominated "Rate Adaptation Protocol" (RAP). Maintaining the basic behavior of RAP, ERAP increases the efficiency of the NTS by reducing the resources usage (of the server and the network). These components has been extensively evaluated by simulations and real tests in which the resource consumption and the performance were measured. This paper presents the advantages of using ERAP instead of RAP in a VoD server, and its viability to be integrated within the NTS in a VoD server on nondedicated networks.
Continuous Range Query Processing for Network Constrained Mobile Objects

In contrast to regular queries that are evaluated only once, a continuous query remains active over a period of time and has to be continuously evaluated to provide up to date results. We propose a method for continuous range query processing for different types of queries, characterized by mobility of objects and/or queries which follow paths in an underlying spatial network. The method assumes an available 2D indexing scheme for indexing spatial network data. An appropriately extended R∗-tree provides matching of queries and objects according to their locations on the network or their network routes. The method introduces an additional prerefinement step which generates main memory data structures to support efficient, incremental reevaluation of continuous range queries in periodically performed refinement steps.
Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification

Objective. Brain–computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. Approach. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. Main results. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. Significance. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.
Integration of human-computer interaction engineering issues into software process capability maturity models. (Intégration des questions d'ingénierie de l'interaction homme-machine dans les modèles d'aptitude et maturité de processus logiciel)

Software process capability maturity (SPCM) models are currently widely used in industry. To perform the practices defined in these models, software engineering approaches are applied. We also have experienced a large definition of methods, techniques, patterns, and standards for the analysis, design, implementation, and evaluation of interactive systems focusing on Human-Computer Interaction (HCI) issues. Nevertheless, it is well known that HCI approaches are not largely used in industry. In order to take advantage of the widespread use of SPCM models, this thesis proposes to integrate HCI issues (concepts of design, implementation, and evaluation of interactive systems) in the most known international SPCM model (CMMI-DEV – Capability Maturity Model Integration for Development) and in the Brazilian SPCM model (MR-MPS-SW – MPS for Software reference model). To that end, we have worked on (i) the identification of appropriate HCI approaches for each practice of the engineering advocated by these models, (ii) the evaluation and improvement of the identified HCI approaches with HCI experts, (iii) the validation of the proposition in an academic environment, and (iv) the conduction of two empirical studies about the perception of knowledge and use of HCI approaches in the industry. As a result, we got 14 categories of HCI approaches with examples of methods, techniques, patterns, and standards adequate to perform each practice of engineering activities of the both models when developing interactive systems. Moreover, the empirical study, in Brazilian industry, confirmed statistically that consultants of those SPCM models do not know and do not use HCI approaches as well as they know and use software engineering approaches.
A PHYSICALLY-MOTIVATED TRIODE MODEL FOR CIRCUIT SIMULATIONS

A new model for triodes of type 12AX7 is presented, featuring simple and continuously differentiable equations. The description is physically-motivated and enables a good replication of the grid current. Free parameters in the equations are fitted to reference data originated from measurements of practical triodes. It is shown, that the equations are able to characterize the properties of real tubes in good accordance. Results of the model itself and when embedded in an amplifier simulation are presented and align well.
An anomaly detection method to detect web attacks using Stacked Auto-Encoder

Network borne attacks are currently major threats to information security. Enormous efforts such as scanners, encryption devices, intrusion detection systems and firewalls have been made to mitigate these attacks. Web application firewalls use intrusion detection techniques to protect servers form HTTP traffic and, Machine learning algorithms have used based on anomaly detection in these firewalls. In this work, we proposed a method based on the deep neural network as feature learning method and isolation forest as a classifier. We compared this method with the methods does not include feature extraction models on CSIC 2010 data set. Additionally, we applied different activation function and learning for our deep neural network. Results show that deep models are more accurate than methods do not have feature extraction.
The Case for Adolescent HIV Vaccination in South Africa

AbstractDespite comprising 0.7% of the world population, South Africa is home to 18% of the global human immunodeficiency virus (HIV) prevalence. Unyielding HIV subepidemics among adolescents threaten national attempts to curtail the disease burden. Should an HIV vaccine become available, establishing its point of entry into the health system becomes a priority. This study assesses the impact of school-based HIV vaccination and explores how variations in vaccine characteristics affect cost-effectiveness.The cost per quality adjusted life year (QALY) gained associated with school-based adolescent HIV vaccination services was assessed using Markov modeling that simulated annual cycles based on national costing data. The estimation was based on a life expectancy of 70 years and employs the health care provider perspective.The simultaneous implementation of HIV vaccination services with current HIV management programs would be cost-effective, even at relatively higher vaccine cost. At base vaccine cost of US$ 12, the incremental cost effectiveness ratio (ICER) was US$ 43 per QALY gained, with improved ICER values yielded at lower vaccine costs. The ICER was sensitive to duration of vaccine mediated protection and variations in vaccine efficacy. Data from this work demonstrate that vaccines offering longer duration of protection and at lower cost would result in improved ICER values.School-based HIV vaccine services of adolescents, in addition to current HIV prevention and treatment health services delivered, would be cost-effective.
Targeting Technology to Increase Smallholder Profits and Conserve Resources: Experimental Provision of Laser Land-Leveling Services to Indian Farmers

With heterogeneous demand and consumption externalities, market segmentation and targeting can improve social welfare. We use a selective trial for laser land leveling (LLL) in India to understand such targeting strategies. We elicit farmer demand for and benefits from LLL services. LLL reduces groundwater extraction by 24%, with comparable fuel savings from reduced pumping. To leverage positive externalities, we combine farmer demand, LLL pumping effects, and service provider costs to evaluate the cost-effectiveness and other impacts of potential targeting strategies. A first-hour LLL discount—a second-degree price discrimination strategy—emerges as the most cost-effective targeting strategy for reducing groundwater extraction.