Miracle-dz/UniFAR-FTUs huggingface dataset:
Medical Assisted Treatment of Opiate Dependence with Buprenorphine/Naloxon (Suboxone®) of Heroin Addicts in Prison Who Are Aging Penalties

Aim: To describe the treatment of opiate addicts who had to spend certain period in prison, after introduced in outpatient administering of substitution medicament Buprenorphine/Naloxon in Bosnia-Herzegovina. Methodology: We assessed 10 male opiate addicts aged 24.8±4.7 years. With presentation of clinical vignettes, authors described how opiate dependants with criminal past imprisoned in jail because of aging penalties avoided discontinuation of treatment after they were included in the Buprenorphine/Naloxon maintenance treatment program. This practice has been implemented in cooperation of Department of Psychiatry in Tuzla and Tuzla prison from 27 July 2009. Results: All opiate dependants described with clinical vignettes showed surprised with positive effects on overall outcomes of Buprenorphine/Naloxon after implementation of continual treatment in prison in cooperation with jail officers (nurse and guards). Also they were very satisfied with life quality during treatment in prison. Also jail officers, family members of dependant person showed satisfaction with achieved efficacy of Buprenorphine/Naloxon eider during aging penalties. Conclusion: Medically assisted treatment of opiate dependence with Buprenorphine/Naloxon for imprisoned addicts implemented as outpatient treatment with involvement of jail officers who were instructed in Buprenorphine/Naloxon daily administration, improved quality of life of treated opiate dependants, and quality of their relations in prison with others.
Inculturation of Liturgical Music in the Roman Catholic Church of Igbo Land: A Compositional Study

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Towards AI-assisted Healthcare: System Design and Deployment for Machine Learning based Clinical Decision Support

Over the last decade, American hospitals have adopted electronic health records (EHRs) widely. In the next decade, incorporating EHRs with clinical decision support (CDS) together into the process of medicine has the potential to change the way medicine has been practiced and advance the quality of patient care. It is a unique opportunity for machine learning (ML), with its ability to process massive datasets beyond the scope of human capability, to provide new clinical insights that aid physicians in planning and delivering care, ultimately leading to better outcomes, lower costs of care, and increased patient satisfaction. However, applying ML-based CDS has to face steep system and application challenges. No open platform is there to support ML and domain experts to develop, deploy, and monitor ML-based CDS; and no end-to-end solution is available for machine learning algorithms to consume heterogenous EHRs and deliver CDS in real-time. Build ML-based CDS from scratch can be expensive and time-consuming. In this dissertation, CDS-Stack, an open cloud-based platform, is introduced to help ML practitioners to deploy ML-based CDS into healthcare practice. The CDS-
Guest Editorial Neuroeconomics: A Neural Engineering Perspective

HE question of how we make, and how we should make, judgments and decisions has occupied thinkers for many centuries, with different disciplines approaching the problem with characteristically different techniques. A very recent approach, known as neuroeconomics, has the goal to integrate ideas from the fields of psychology, neuroscience, and economics in an effort to specify more accurate models of choice and decision. This special issue of “Neuroeconomics: Modeling and imaging the brain activity during economic transactions” is trying to include both the state-of-technique papers on the methodologies and models that it can be used in this field on humans. The scenario that comes out from the series of papers chosen from active authors in this new area of science is really interesting. From one side, there is the development of methodologies that allows estimate the brain activity during decision making tasks by using hemodynamic [1] or electromagnetic modalities [2], [3]. On the other side, there are contributions about theoretical [4] and practical aspects [5] of the application of neural engineering to the neuroeconomics. In particular, the paper of Grosenik et al. [1] faced with the attempt to classify sensory inputs in order to directly predict the behavioral output, by using the hemodynamic information related to the brain activity. They applied different machine learning algorithms to previously acquired data to examine the ability of functional magnetic resonance imaging (fMRI) activation in three regions—the nucleus accumbens (NAcc), medial prefrontal cortex (MPFC), and insula—to predict purchasing. Their goal was to improve spatiotemporal interpretability as well as classification accuracy. The use of electroencephalographic data was instead promoted in the context of prediction of particular memorization of TV advertising in the paper of Astolfi et al. [2]. There, the signs of brain activity related to the observation of TV ads were detected by using advanced statistical techniques. The techniques presented here shed new light on all thecortical networksandtheir behavior duringthememorization of TV commercials. Such techniques could also be relevant in neuroeconomics and neuromarketing for the investigation of the neural substrates subserving other decision making and recognition task. The use of EEG technology was also promoted in the paper of Bordaud et al. [3] for the study of the correlates of the brain electrical activity related to the exploratory behavior. In fact, decision making in an uncertain environment arises a conflict between two opposing needs: gathering infor
The monitoring of Verkhniy Kaban lake by rbcL gene of freshwater organisms using next-generation sequencing

Aim: The lake Verkhniy Kaban, along with the lakes Sredny Kaban and Nizhny Kaban, makes the part of the Kaban lake system. The lakes are located in the center of the large industrial city and experience anthropogenic load. According to the estimates of the Lake Kaban ecologists, they are related to polluted lakes. Materials and Methods: The sequencing of rbcL gene fragment sequences of the freshwater lake Verkhniy Kaban hydrobionts during autumn (2016) and summer (2017) sampling periods in FASTQ format is included in the international database on NCBI site with the following unique numbers: SRR7470846, SRR7459785, and SRR7463965. Results: The results of the analysis are given, and the water quality evaluation of the Verkhniy Kaban Lake (Kazan, Russia) is presented in the work on the basis of the rbcL gene of freshwater organisms by the method of new generation sequencing. The comparative analysis of metagenomic data shows that the majority of organisms of the Verkhniy Kaban Lake are grouped according to rbcL gene near b-mesosaprobic zone. The Verkhniy Kaban Lake can be characterized as contaminated with the water quality transitional to b-mesosaprobic one. Conclusions: The use of modern methods of molecular biology for the purpose of bioindication gives positive results and increases the effectiveness and reliability of water body ecological state evaluation. The obtained results are of great practical interest in the field of water body monitoring, in particular, and the environment as a whole.
Comparative Analysis of Collaborative Filtering Technique

Today it is almost impossible to retrieve information with a keyword search when the information is spread over several pages. The Semantic Web is an extension of the current web in which information is given well-defined meaning. Web personalization is the one application of semantic web usage mining. In this report we have explored comparison of various collaborative filtering techniques. Those techniques are memory based, model based and hybrid collaborative filtering. Our study shows that the performance of hybrid collaborative filtering technique is better than memory based and model based collaborative filtering technique. We have introduced normalization step, which will improve accuracy of traditional collaborative filtering techniques.
D-vector based speaker verification system using Raw Waveform CNN

In this paper, we propose a d-vector based speaker verification system in which rawaudio-CNN is used as a d-vector extractor instead of a conventional multi-layer perceptron. Because raw-audio-CNN takes raw wave signals as input, traditional acoustic feature extracting methods such as mel-frequency cepstral coefficient and mel-filterbank features are no longer needed. The results of experiments conducted show that raw-audio-CNN can successfully perform functions carried out by traditional acoustic feature extracting methods and outperforms traditional d-vector systems that utilize standard multi-layer perceptron with acoustic features.
Video quality assessment via gradient magnitude similarity deviation of spatial and spatiotemporal slices

Video quality assessment (VQA) has been a hot topic due to the rapidly increasing demands in related video applications. The existing state-of-art full reference (FR) VQA metric ViS3 uses adapted the Most Apparent Distortion (MAD) algorithm to capture spatial distortion first, and then quantifies the spatiotemporal distortion by spatiotemporal correlation and a HVS-based model from the spatiotemporal slices (STS) images. In this paper we argue that the STS images can provide enough information for measuring video distortion. Taking advantage of an effective and easy-applied FR image quality model GMSD, we propose to measure video quality by analysing the structural changes between the STS images of the reference videos and their distorted counterparts. This new VQA model is denoted as STS-GMSD. To further investigate the influence spatial dissimilarity, we also combine the frame-by-frame spatial GMSD factor with the STS-GMSD and propose another VQA model, named SSTS-GMSD. Extensive experimental evaluations on two benchmark video quality databases demonstrate that the proposed STS-GMSD outperforms the existing state-of-the-art FR-VQA methods. While STS-GMSD works all square with SSTS-GMSD, which validates that STS images contain enough information for FR-VQA model design.
In Vitro Effects of Brassinosteroids on the Growth and Antioxidant Enzyme Activities in Groundnut

This paper deals with the in vitro effects of brassinosteroids (BRs) on growth in the form of multiple shoots, chlorophyll content, Hill reaction activity (HRA), activities of catalase (CAT), peroxidase (POX), polyphenol oxidase (PPX), and ascorbate peroxidase (APX) in Arachis hypogaea L. genotypes (M-13 and PBS24030). In vitro impact of BR on shoot multiplication potential was found to be the best at 1 mL L−1 with BA (3 mg L−1) in both the cultivars. Flowering was observed in PBS24030 on the medium containing 2.0 mL L−1 BR with 3 mg L−1 BA. Rhizogenesis was noticed in the presence of BR alone. Total chlorophyll content and HRA were highest at 2.0 mL L−1 with BA in M-13 and 1.0 mL L−1 with BA in PBS24030. Antioxidant enzyme activities were increased in the presence of BR whether alone or in combination with BA in both the cultivars. However, progressive decline was observed in case of MDA content. The results obtained in the study clearly indicated not only the in vitro establishment of groundnut cultivars in the presence of BR alone and in combination with BA but also its effect on various growth promotory physiological parameters.
DISCUSSÃO E APLICAÇÃO DO PROTOCOLO THINK ALOUD EM PESQUISAS SOBRE PROCESSO DECISÓRIO

Este estudo propõe uma discussão sobre os aspectos conceituais do protocolo verbal think aloud, utilizando-se de aplicações práticas num processo de decisão individual. Este trabalho apoia-se na revisão dos estudos dos principais autores do protocolo, especialmente Ericsson e Simon (1993). Sobre a aplicação do think aloud, são apresentados exemplos cujas pesquisas utilizaram o método experimental, cujo objetivo era compreender como os indivíduos tomavam decisões com e sem o auxílio de Sistemas de Apoio à Decisão (SAD). Os resultados do primeiro experimento revelaram que o processo decisório, utilizando um SAD, assemelhou-se apenas para a ordem de escolha dos critérios no que tange ao processo de decisão humana. Os resultados do segundo experimento, quando o indivíduo usou o SAD, permitiram verificar a relação entre duas das quatro estratégias de decisão propostas por Todd e Benbasat (1991). Sem o auxílio do SAD, todas as estratégias de decisão foram identificadas. Acredita-se que as aplicações elucidadas possam servir de orientação para futuras pesquisas, não somente no campo de processo decisório, mas em outras áreas que possibilitam o uso do protocolo think aloud.
Betwixt and Between: A Pilot Study Exploring the Experiences of Clinical Educators Teaching in a Dispersed Model of Entry-Level Physiotherapy Curriculum

Education of the future healthcare workforce has long been a partnership between university and healthcare sectors, with students learning under the shared guidance of academics and clinicians. Traditionally, academics have taught in the classroom and clinicians have engaged students at the patient bedside. Using a phenomenologically-oriented approach, this pilot project explored the experiences of clinicians who team-taught a theoretical subject in a classroom environment. Purposeful sampling of physiotherapy staff within a metropolitan healthcare organisation was used. Six clinicians were recruited and, prior to teaching, completed a blended educational program about higher education teaching and learning. The clinicians taught classes of twenty students within new classroom spaces co-located at the healthcare organisation, with curricula provided by the university. Two semi-structured interviews were conducted with each clinician at the beginning and end of the allocated teaching period. Transcripts from the semi-structured interviews were analysed and four themes emerged. First, physiotherapists initially identified as clinicians not teachers, but their perceptions later broadened. Second, the intention of teaching was patient-focused. Third, the balancing of multiple roles resulted in challenges for the clinicians; and fourth, the experience involved new immersion in digital media. This work explores a different form of educator role – likened to a pracademic – and supports the need for considered approaches to teaching and links between theory/education and practice to meet the demands of modern healthcare and university learning.
Reducing message latency by making message passing transparent

The authors describe hardware to reduce message latency and hide message passing's existence on distributed memory multiprocessors. Existing message passing systems are visible to the programmer and require setup time for each message. The authors propose a system in which normal processor memory reads and writes cause a communications processor to send or receive messages as necessary to implement the read or write operation. To implement this a section of memory is typed, describing the actions needed when that memory is read or written. Communications processor setup commands provide tables giving the memory layout. This can include full/empty bit synchronization, counted writers synchronization, multiple recipients, broadcasting, and remote procedure call support. The authors provide a justification, a mechanism description, and a proposed hardware and software implementation outline. <<ETX>>
Implicações da época de colheita sobre a qualidade fisiológica de sementes de soja

A antecipacao e o atraso da colheita de sementes de soja tem sido objeto de estudo tanto nas areas de tecnologia de sementes quanto de melhoramento de plantas; em programas de tecnologia de sementes, a antecipacao da colheita possibilita a obtencao de sementes com maior qualidade fisiologica. Assim, objetivou-se com o presente trabalho avaliar o efeito da epoca de colheita sobre a qualidade fisiologica de sementes de soja. Dois ensaios foram conduzidos, um na safra 2013/14 e outro na 2014/15, em delineamento de blocos casualizados, com quatro repeticoes. Os tratamentos, em cada ensaio, foram: 1) colheita normal (CN) - sementes colhidas com 14% de umidade, sem aplicacao de dessecante; 2) colheita com dessecacao (CD) - sementes oriundas da dessecacao pre-colheita com paraquat + diuron, colhidas com 14% de umidade; 3) colheita antecipada (CA) - sementes colhidas com 17% de umidade; 4) colheita atrasada (CAT) - sementes colhidas 10 dias apos a colheita normal. A qualidade fisiologica das sementes foi avaliada pelo percentual de germinacao e vigor (teste de frio, envelhecimento acelerado, teste de tetrazolio, condutividade eletrica e comprimento de plântulas). O atraso de colheita em 10 dias reduziu o percentual de germinacao e vigor nas duas safras. A colheita com 17% de umidade proporcionou maior vigor pelos testes de frio (97 e 97%) e envelhecimento acelerado (97 e 93%) nas safras 2013/14 e 2014/15, respectivamente. Dessa forma, a colheita das sementes com 17% de umidade proporcionou maior qualidade fisiologica de sementes de soja, cultivar ND 6211 RR, nas duas safras agricolas.
Faster evolution and evolvability control of genetic algorithms using a Softmax Mutation method

We introduce a new mutation method in evolutionary algorithms called Softmax Mutation, based on a Gibbs or Boltzmann probability distribution. Comparative experimental runs with a traditional genetic algorithm showed it to be a better alternative to the standard blind genetic operator of random mutation. The advantages of this method are not restricted to its faster evolution (namely a three fold speed up). It also impacts positively on evolvability.
DIARY DATA SUBJECTED TO CLUSTER ANALYSIS OF INTAKE/OUTPUT/VOID HABITS WITH RESULTING CLUSTERS COMPARED BY CONTINENCE STATUS, AGE, RACE

Hypothesis / aims of study Clinicians attempt to reduce and interpret the multi-factorial information contained on a voiding diary by subjectively reducing the differing aspects into a single, unified pattern presumed to be associated with a particular bladder health state. This process, however, has relied on subjective rather than objectively driven analysis. We analyzed diary data, from both continent and incontinent women, to identify simple, discrete, patterns that emerge from the full spectrum of intake/output variables when subjected to a statistical data-driven process. We: 1) used cluster analysis to look for naturally occurring groupings, 2) described and labelled the resulting clusters, and 3) profiled the clusters by comparing them across variables commonly associated with bladder health but external to the cluster analysis variables.
The Relationship Between Body Mass Index and Sexual Dysfunction Among Women: A Meta-Analysis

Background: Sexualfunctionisanimportantindicatorof qualityof life,whichaﬀectsvariousaspectsof women’shealth,especially physicalhealth. Althoughsomeevidencesuggeststhatpeoplewithagreaterbodymassindexexperiencemoresexualdysfunction, this has continually been disputed. A meta-analysis was conducted to evaluate the relationship between these concepts more accu-rately. Methods: A meta-analysis on all published articles until October 2016 was conducted in Scopus, PubMed / Medline, Springer, Web of Knowledge, Science Direct, and Google scholar databases as well as SID and Magiran (Persian databases) using key words such as “Body Mass Index” AND “sexual dysfunction” AND women. Furthermore, the Random eﬀect model was used for statistical pooling. The heterogeneity of studies was evaluated using I 2 index. The data analysis was performed using Comprehensive Meta-Analysis software. Results: 9 eligible studies were included into the meta-analysis. The pooled results suggested an inverse association between body massindex(BMI)andsexualdysfunction(PooledCorrelation=-0.222;95% CI,-0.362-0.073). CochranQindexwasobtainedas73.574 (P < 0.001) and I 2 = 89.12% showed a high heterogeneity among the studies entered the meta-analysis. Conclusion: Aweakandinverserelationshipwasobservedbetweenbodymassindexandsexualdysfunction. Itseemstherelation-ship between these variables may be aﬀected by other numerous factors, which requires further investigation to be conﬁrmed.
Prediction with recurrent networks

The authors study extrapolation of time series using recurrent neural networks. They use the real-time recurrent learning algorithm introduced by R. J. Williams and D. Zipser (1989), both in the original form for first order nets and in a form for second order nets. It is shown that both the first order and the second order nets are able to learn to simulate the Mackey-Glass series. The prediction quality of the results is comparable to that from feedforward nets. <<ETX>>
Learning for Spoken Dialog Systems with Discriminative Graphical Models

A statistical spoken dialog system must keep track of what the user wants at any point during a dialog. The system has the ability to disambiguate in the presence of errors by maintaining probability distributions over possible dialog states. This thesis demonstrates that discriminative probabilistic graphical models can significantly improve the performance of the task of dialog state tracking, namely, predicting a user’s constraint that the user has specified so far during a dialog. One challenge for machine learning problems is when there is limited amount of available training data. In particular, learning for spoken dialog systems is hampered by the expense of collecting human-computer interactions. Insufficient training data can lead to overfitting with complex models and make the trained classifier vulnerable to unseen observations. In this thesis, parameter tying has been introduced as a new way to combat overfitting by learning generic weights on discriminative probabilistic graphical models. Each of the generic weights represents a group of parameters that share the same characteristic in discriminating between correct and incorrect labels. Essentially, the tied models ignore the specific identity of a value in the designed feature functions. With parameter tying, the learned model can generalize well to the unseen labels. Different variations of Conditional Random Fields (CRFs) are trained to perform the task of dialog state tracking. We also incorporate the detected user goal change information into the discriminative models to better capture the evolving user goals. With significantly