Miracle-dz/UniFAR-FTUs huggingface dataset:
Convincing Conversations: Using hypothetical versus non-hypothetical disengagement belief handling in a MI-based dialogue system for promoting a protein transition

The consumption of animal proteins has been associated with severe negative influences on health, the environment, and animal welfare. The aim of this study was to examine whether handling disengagement beliefs by providing non-hypothetical, evidence-based counterargumentation would lead to a bigger effect in the intention of omnivores to reduce their consumption of animal proteins than giving hypothetical, or what-if counterargumentation. A computer-delivered dialogue system was designed. The system applied theoretical insights from Motivational Interviewing and the Social Determination Theory. 159 respondents were randomly assigned to one of three versions of the intervention: two experimental conditions and one control group condition. The study had a pretest-posttest control group design. Analysis of the results revealed that hypothetical disengagement belief handling appeared to lead to a higher behavioural intention than non-hypothetical disengagement belief handling.
Revealing the Relationship between Smartphone Addiction and Academic Performance of Students: Evidences from Higher Educational Institutes of Pakistan

In this world of technology, smart phone has become a vital part in everyone’s life. This study aims to focus on the relationship between smartphone addiction and academic performance of students in higher education. Variables such as use of social networking sites, overuse of smart phone and Academic Performance (Grade Point Average and Time Management skills) were part of this research. Self-administered questionnaire was used to collect data from 360 students of two private universities in Rawalpindi, Pakistan. The target age group was 19-24 studying in Bachelors degree program. Data was analyzed through SPSS. Pearson correlation and multiple linear regression tests were applied. Results reveal that there is a negative relationship between smartphone addiction and academic performance. Moreover, it has been proved that students with good time management skills achieve high grades/GPAs than those who have poor time management skills due to involvement in different social networks (media) such as Facebook, Twitter and Instagram etc. It is suggested that students should spend their time wisely and use their smartphones for educational purposes. However, students need training, counseling and close monitoring to get benefits through smartphones’ use.
Towards Modular Algorithm Induction

We present a modular neural network architecture Main that learns algorithms given a set of input-output examples. Main consists of a neural controller that interacts with a variable-length input tape and learns to compose modules together with their corresponding argument choices. Unlike previous approaches, Main uses a general domain-agnostic mechanism for selection of modules and their arguments. It uses a general input tape layout together with a parallel history tape to indicate most recently used locations. Finally, it uses a memoryless controller with a length-invariant self-attention based input tape encoding to allow for random access to tape locations. The Main architecture is trained end-to-end using reinforcement learning from a set of input-output examples. We evaluate Main on five algorithmic tasks and show that it can learn policies that generalizes perfectly to inputs of much longer lengths than the ones used for training.
Variation of some physical properties of CuInS2 films by substrate temperature

Received: 21/Mar/2019, Accepted: 11/Apr/2019, Online: 30/Apr/2019 AbstractSpray pyrolysis is one of the most convenient, economical, inexpensive and simple methods for depositing large area semiconducting thin films. Semiconducting ternary CuInS2 thin films have been deposited onto the glass substrate by varying substrate temperature from 275 0 C, at the interval of 25 to 350 0 C by using aqueous solution of Cupric chloride, Indium trichloride and thiourea of 0.02 M and Seems to be one of the more important parameters affecting the physical properties of the semiconductor. The lattice parameter a and c at room temperature of the tetragonal unit cell were calculated for all these samples by Bruker AXS D8 Advance X-ray diffraction (XRD) techniques with Cu Kα (wavelength = 1.5418 Å) radiation.Conductivity of thin films determined by Four Probe method and hot probe technique wasdetermined to exhibit ptype conductivity. Due to temperature effect, shows the atoms are arrange regular in compound of these samples prepared at various temperatures 250, 300 and 350 0 C. As the films are not doped intentionally defect observed in intrinsic nature operative to be produced by Sulphur interstitials. Grain sizes were studied by Scanning Electron Microscope.
Genetic diversity and resistance profile of mycobacterial strains isolated in Senegal

Tuberculosis remains a major public health problem in Senegal. The aim of this study was to determine the resistance and molecular profiles of mycobacterial strains isolated over a four-year period in Senegal. Mycobacterial isolates worked on were obtained at the National Reference Laboratory of the National Antituberculosis Program (NAP) in Senegal. These strains were cultured on LowensteinJensen (LJ) medium or on LJ medium supplemented with pyruvate, between January 2011 and December 2014. Depending on the availability of reagents, the drug susceptibility tests were performed by the proportion method or molecular methods. Strains were characterized by spoligotyping. This study focused on 208 samples with 160 strains and 48 sputa. Antibiotic resistance testing was carried out on 151 samples among which 32 (21.2%) came from new patients and 119 (78.8%) from previously treated patients. Seventy (43.35%) MDR strains were detected. Spoligotyping were performed on 64 strains, essentially MDR strains which mostly belong to three families: T, Beijing and Cameroon. In Senegal, anti-tuberculosis drug resistance rates are very high among retreatment patients with a high percentage of MDR strains in patients with treatment failure. The strains belong to three main families: T superfamily, Beijing and Cameroon. Multidrug resistance compromises the effectiveness of tuberculosis treatment with a high risk of spread of these MDR strains in the community, hence, the importance of strengthening the fight against tuberculosis in general and MDR-TB in particular.
Development of an Engineered Geothermal System Exploration Methodology Using the Dixie Valley Geothermal Area, Nevada USA, as a Laboratory Calibration Site System

The Dixie Valley Geothermal Area, a Basin and Range type system, in central Nevada USA was chosen as the calibration site for development of an Engineered Geothermal system exploration methodology development due to its extensive body of geoscience data and information on the geothermal system and most importantly, well results in the public domain. It is also has the highest reported bottomhole temperature, 285°C, in the Basin and Range and the geothermal field is generating over 60 MWs of electrical power. The overall project study area was 2500km 2 with a calibration area (defined by the existing wellfield) of approximately 170km 2 . A baseline (existing data) analysis was conducted, and on this basis, baseline favorability maps were generated, from +1km above sea level (asl) to -4km asl at 0.5km intervals, for the three key Engineered Geothermal System (EGS) parameters of interest: rock type, temperature, and stress. Complimentary baseline trust ("confidence-in-the-data-used") maps were also created at the same scale to, among other things, indicate where additional data was required. Exploratory geostatistical data analysis was also conducted to determine the predictability of several key attributes of the system. To reduce data uncertainty and geophysical data and information non-uniqueness, new gravity, magnetotelluric, and ambient seismic noise data were collected to supplement the baseline data set. The enhanced data set (baseline + new data) were modeled and interpreted along with enhanced thermal modeling and enhanced geostatistical analysis. The outcome of both the baseline and enhanced data analysis are presented.
Surface Modification to Enhance the Properties of SA 210 Grade A1 boiler Steel by Friction Stir Processing

Friction stir processing (FSP) is used for localized modification and control of microstructure in nearsurface layers of processed metallic components for specific property enhancement. In the current investigation, FSP was developed on a boiler tube material namely SA 210 Grade A1 which is commonly used in high-temperature steam generating plants. The FSP was carried out at the rotation speed of 900 rpm with feed rate of 70 mm/min and threefold pass of 100 % overlap. The microstructure, mechanical properties were studied in detail. It was observed that after FSP the microstructure and the mechanical properties of the steel like microhardness, tensile strength, and yield strength improved. Thereafter, high-temperature corrosion behavior of the unprocessed and FSPed materials was investigated at 900°C for 50 cycles in Na2SO4-82%Fe2(SO4)3 molten salt environments. Weight-change measurements after each cycle were made to establish the kinetics of corrosion. The FSPed specimen showed higher corrosion resistance than the unprocessed steel.
Differences in Unemployment by Educational Attainment in the US and Europe: What Role for Skill-Bias Technological Change and Institutions?

This study is about differences in unemployment rate by educational attainment between the US and Europe over the past three decades. Apart from usual explanatory variables, like wage differentials between educational groups in the two regions, specific attention will be given to complementarities between capital and skilled labour. Increasing capital stock raises skilled wages more than unskilled wages, i.e. raises demand for skilled workers and hence leads to a relative fall in unemployment among high skilled. We find that this skilled biased technology effect is larger in the US than in Europe. European institutions favour wage equality but these also imply less incentives to migrate to higher education classes. This has a depressing effect on skilled labour supply. This means there is less mobility in the European labour market compared to the US, not just from a spatial but also from an educational perspective.
A Deep Belief Network Approach to Learning Depth from Optical Flow

It is well established that many living beings make use of motion information encoded in the visual system as a means to understand the surrounding environment and to assist with navigation tasks. In particular, a phenomenon referred to as motion parallax is known to be instrumental in the perception of depth when binocular cues are distorted or otherwise unavailable [6]. The key idea is that objects which are closer to a given observer appear to move faster through the visual field than those at a further distance. Due to this phenomenon, optical flow can be a very powerful tool for the decoding of spatial information. When exact data is available regarding the speed and direction of optical flow, recovering depth is trivial [1]. In general, however, sources of this information are unreliable, therefore a learning approach can come of great use in this domain. We describe the application of a deep belief network (DBN) to the task of learning depth from optical flow in videos. The network takes as input motion features generated by a hierarchical feedforward architecture of spatio-temporal feature detectors [4]. This system was developed as an extension of the HMAX model [12] and is inspired by the neurobiology of motion processing in the visual cortex. Our network is trained using a set of graphical scenes generated by a gaming engine, such that ground truth depth information is available for each video sequence. We show that, by using such a DBN, we are able to improve considerably over standard linear classifiers. In addition, we show that our results can be further improved by performing Markov random field smoothing on the output depth field map. Our findings suggest that cortex-like mechanisms are a conceivable tool for artificial vision systems that operate on video data.
Long-term Cost-effectiveness of Endoscopic vs Open Vein Harvest for Coronary Artery Bypass Grafting Oddershede,

Background: The greater saphenous vein is frequently used as a conduit for coronary artery bypass grafting (CABG). Previously, veins were most often harvested using open vein harvesting (OVH), however, endoscopic vein harvesting (EVH) techniques have become increasingly popular. Nevertheless, the long-term cost-effectiveness of EVH remains unknown. The present study estimated the long-term cost-effectiveness of EVH versus OVH for CABG. Methods: A Markov model was developed to estimate life-time costs (UK Pounds Sterling) and quality adjusted life-years (QALYs) with comparative results presented as incremental cost-effectiveness ratios (ICERs). Costs and probabilities of events in the OVH group were mainly drawn from a previously published study. Resource consumption and event probabilities in the EVH group were estimated using a meta-analysis to reflect the best available evidence. Parameter uncertainty was assessed using both one-way sensitivity analyses and probabilistic sensitivity analyses. Results: The life-time cost/QALY was £8219 rendering EVH cost-effective compared to OVH. Sensitivity analyses showed that EVH was cost-effective in 60.4% of simulations at a threshold of £30 000/QALY, reflecting a large uncertainty in the point estimate of the ICER. The main causes of uncertainty were the time-horizon and the event rates of major clinical events in the treatment groups. Conclusions: Current evidence indicates that EVH is cost-effective for harvesting saphenous vein segments for CABG compared to OVH. Further studies on long-term clinical outcomes are needed to reach a more precise costeffectiveness estimate.
Partial Simulation for Imitation Learning

Model-based imitation learning methods require full knowledge of the transition kernel for policy evaluation. In this work, we introduce the Expert Induced Markov Decision Process (eMDP) model as a formulation of solving imitation problems using Reinforcement Learning (RL), when only partial knowledge about the transition kernel is available. The idea of eMDP is to replace the unknown transition kernel with a synthetic kernel that: a) simulate the transition of state components for which the transition kernel is known (sr), and b) extract from demonstrations the state components for which the kernel is unknown (su). The next state is then stitched from the two components: s = {sr, su}. We describe in detail the recipe for building an eMDP and analyze the errors caused by its synthetic kernel. Our experiments include imitation tasks in multiplayer games, where the agent has to imitate one expert in the presence of other experts for whom we cannot provide a transition model. We show that combining a policy gradient algorithm with our model achieves superior performance compared to the simulation-free alternative.
ORNL SLICER 2: A NOVEL APPROACH FOR ADDITIVE MANUFACTURING TOOL PATH PLANNING

ORNL Slicer is the first software designed to generate machine instructions, or tool paths, from CAD files for large-scale 3D printing of metals and polymers. The software was revolutionary because it allowed for slicing of models reaching 20 feet long, generating millions of lines of G-Code in seconds. The structure of the first ORNL Slicer had limitations in its framework, which has led to the development of ORNL Slicer 2. In the second version of the slicer, the process is modularized with individual layers being divided into regions, smarter infill patterns, and traversals are generated based upon stress, thermal, and other models. The new software has also been structured to allow for slicing and reslicing based on machine feedback during the printing process.
Bilateral Lower Limb Lymphedema as the Only Sign of Kaposi Sarcoma in a Patient With Human Immunodeficiency Virus

We present a 35-year-old African American man with AIDSassociated Kaposi sarcoma with atypical bilateral lower limb lymphedema as the only sign of the disease during the 4-year follow-up. Lymphedema portrays a poor prognosis and represents an indication for chemotherapy in addition to antiretroviral therapy.
A Multi-Analytical study of Rock Paintings from Leandro 5 Megalithic Barrow, North-Weastern Portugal

The work was supported by UID/QUI/50006/2019 with funding from FCT/MCTES through national funds. Cesar Oliveira acknowledges Instituto de Ciencias e Tecnologias Agrarias e Agro-Alimentares, Porto (ICETA), for his contract under project NORTE-01-0145-FEDER-000011. This work was also developed under the project ‘Funerary and ceremonial practices between the Neolithic and the Bronze Age approached by archaeometry’ (ARQUEOM/Project-Sept2014).
Beyond Bourdieu, Foucault and Habermas: Review and Assessment of Critical Information Systems Research

This paper presents a literature review of critical information systems (IS) research. Specifically, it focuses on how IS researchers have responded to Myers and Klein’s (2011) call to consider critical approaches and theorists in addition Bourdieu, Foucault and Habermas. The review identifies and discusses three types of critical IS research “beyond Bourdieu, Foucault and Habermas”: work based on a) (other) critical grand social theories, b) postcolonialism and c) data-focused critical methods (i.e., Capabilities Approach, Critical Discourse Analysis, Critical Heuristics and Design, Frame Analysis and Phronetic Enquiry). Based on the literature review, the paper maps the landscape of critical approaches and theories and identify their origins. This analysis is helpful for IS researchers interested in conducting critical IS research by charting the range of critical research approaches beyond Bourdieu, Foucault and Habermas.
Curation Technologies for the Construction and Utilisation of Legal Knowledge Graphs

Under the umbrella of the European project LYNX we currently develop technologies for the construction of a legal knowledge graph and a corresponding system that makes use of this legal knowledge graph. The ﬁnal platform will eventually bundle a set of semantic services into a curation technology system, which is meant to assist users to process legal and regulatory content and data more efﬁciently and more effectively. In this paper we present an overview of the current state of the art with regard to semantic technologies and natural language processing approaches applied to the legal domain.
Exploring the Relationship Between Preschool Teacher Perceptions of Positive Teacher-Child Relationships and Classroom Practice

In 2015, it was estimated that 4 million children entered kindergarten without the necessary skills to succeed (U.S Department of Education, 2015). This academic and social deficit places children at a disadvantage which can be avoided when children are exposed to supportive learning environments characterized by positive relationships (Curby, et.al, 2009). The CLASS observation (Pianta, La Paro, & Hambre, 2008) classifies best practices in teacher-child interactions which are placed in dimensions within three major domains; emotional support, classroom organization, and instructional support. This research explores which dimensions teachers identify as important and the relationship with observed practices as identified by CLASS. Sixteen teachers ranked CLASS dimensions in order of importance followed by a CLASS observation and relationship between the two was examined. This study supports the idea that educators do practice the aspects of teacher-child interactions that they consider important, however a larger population sample is required to further this belief TEACHER PERCEPTIONS AND CLASSROOM PRACTICE 2
Discovering Motor Programs by Recomposing Demonstrations

In this paper, we present an approach to learn recomposable motor primitives across large-scale and diverse manipulation demonstrations. Current approaches to decomposing demonstrations into primitives often assume manually defined primitives and bypass the difficulty of discovering these primitives. On the other hand, approaches in primitive discovery put restrictive assumptions on the complexity of a primitive, which limit applicability to narrow tasks. Our approach attempts to circumvent these challenges by jointly learning both the underlying motor primitives and recomposing these primitives to form the original demonstration. Through constraints on both the parsimony of primitive decomposition and the simplicity of a given primitive, we are able to learn a diverse set of motor primitives, as well as a coherent latent representation for these primitives. We demonstrate, both qualitatively and quantitatively, that our learned primitives capture semantically meaningful aspects of a demonstration. This allows us to compose these primitives in a hierarchical reinforcement learning setup to efficiently solve robotic manipulation tasks like reaching and pushing.
STANDALONE 3D PRINTER WITH INTEGRATED 3D SCANNING

3D printers are now being used everywhere from simple prototyping to complex product creation. However, there still are a lot of hurdles to overcome for a much wider adaptation of such printers. One of the biggest problems is the difficulty in 3D model creation. It takes a lot of experience to create such models also, most of the 3D model creating software available today comes at a high price tag. To help with this, 3D scanners are available, but these scanners are sold separately and come at a high price. To solve these problems, a 3D printer with an integrated 3D scanning is proposed here.
PNEUMOCOCCAL CARRIAGE RATE IN CHILDREN AND THEIR ANTIMICROBIAL SUSCEPTIBILITY PATTERNS IN AN URBAN SET UP

INTRODUCTION: S.pneumoniae is the major cause of morbidity and mortality in India and abroad and carriage is the key to invasive disease. Carriage (20-60%) and invasive disease are more prevalent in children and in the elderly. Increased case fatality is due to the emergence of Penicillin and Multidrug Resistant S.pneumoniae worldwide. Penicillin has been the drug of choice for treatment of pneumococcal infections but the increasing number of reports of penicillin resistant pneumococci (PRP) throughout the world makes it essential to regionally determine the prevalence of PRP. MATERIALS AND METHODS: Nasopharyngeal swabs were collected from children between ≥ 3 months and ≤ 5 years of age attending paediatric immunization OPD in a medical college tertiary care hospital and research centre, Bengaluru, between December 2008 and August 2009 ( 8 months). S. pneumoniae were isolated based on colony morphology, Gram's staining, optochin sensitivity, and bile solubility. Antimicrobial susceptibility testing was carried out by Kriby-Bauer disc diffusion method for recommended commonly prescribed antibiotics. Oxacillin resistant strains denoting penicillin resistance were tested for Minimum inhibitory concentration for Penicillin G by Epsilometer test. RESULTS: 53 (27.89 %) S. pneumoniae were isolated from 190 nasopharyngeal swabs. 9 (16.98%) isolates have been intermediately penicillin resistant by E test. Only 5 (9.43%) and 34 (64.15%) isolates were sensitive to co-trimoxazole and tetracycline respectively. 51 isolates were susceptible to cefotaxime, 48 (90.56%) each were susceptible to erythromycin and ciprofloxacin. 25(47.19%) out of 53 isolates could be recovered at the end of one year stored in STGG medium at -20˚ C. Serogroup types 19, 10, 3, 14, 7, were common among the isolates. CONCLUSION: Carriage of S. pneumoniae is prevalent among young children in Bengaluru, which may predispose them to subsequent invasive pneumococcal diseases. There is decreased susceptibility to penicillin and other recommended antibiotics that may warrant appropriate culture and sensitivity testing during the management of invasive pneumococcal diseases and prescription of antibiotics in general.