Miracle-dz/UniFAR-FTUs huggingface dataset:
Hepatitis B and C virus co-infection in Nigerian patients with HIV infection.

INTRODUCTION We set out to determine the seroprevalence of hepatitis B and hepatitis C viruses among human immunodeficiency virus infected individuals and its impact on pattern of presentation. METHODOLOGY A serological study for hepatitis B and hepatitis C viruses was performed on 260 HIV-positive individuals. These patients were tested for the presence of hepatitis B surface antigen and anti-hepatitis C virus (HCV) antibody. RESULTS Thirty (11.5%) patients tested positive for hepatitis B surface antigen, six (2.3%) tested positive for anti-hepatitis C virus antibody, four (1.5%) were positive for both hepatitis B surface antigen and anti-hepatitis C virus and the overall prevalence was 15.4% . Individuals younger than 40 years of age were more affected, and the odds ratio of a female being co-infected was 1.2, 25% versus 75% p value = 0.03. The prevalence of HIV and hepatitis co-infection rises with age except for hepatitis C. There was no significant difference in the mean levels of liver enzymes (AST, ALT) among the various groups. The groups differ significantly in their mean CD4 count: it was lowest for those co-infected with hepatitis B and hepatitis C; 106 cells/mm(3), 171 cells/mm(3) for those with HIV alone; and the highest value of 260 cells/mm(3) was obtained in those who tested positive for anti-HCV. Scarification marks and multiple blood transfusions were more common among those infected. There was no case of intravenous drug abuse identified. CONCLUSION This low frequency of HIV/HCV co-infection is probably due to the uncommon intravenous drug abuse in this population. Co-infection with hepatitis B virus is common among our HIV-infected patients and should be a major consideration in the initiation and choice of therapy.
MAP-based cross-language adaptation augmented by linguistic knowledge: from English to Chinese

Construction of a recognizer in a new target language usually involves collection of a comprehensive database in that language as well as manual annotation and model training. For rapid development of new language recognizer, we propose (1) substituting target language phoneme models by source language phoneme models trained previously; and (2) adapting target language phoneme models from source language phoneme models using maximum a posteriori method. Evaluations show that adaptation method results in an error reduction rate of 51% from using substitution, and an error reduction rate of 10% from language-dependent training. We also propose using data-driven method with linguistic knowledge, instead of heuristic rules, to align source language phonemes to target language phonemes, both for substitution and adaptation. Eva-lution shows that using linguistic rules brings a 2% increase in recognition rate.
Learning Cooperation In Repeated Games

In the eld of multi-agent systems, the study of coordination, cooperation and collaboration assumes a prominent position. Most of the research concerned with these issues concentrates on explicit negotiation between agents, on the investigation of settings in which global system goals have to be balanced with agents' individual goals or on the exploitation of real-world knowledge to determine eecient coordination strategies. We present a social learning and reasoning component as part of a layered learning agent architecture for iterated multi-player games, which is capable of implementing cooperative behaviour in societies of purely \sellsh" agents. This can be accomplished by learning about other agents' preferences, and by nding out how valuable other agents' actions are for the agent's own success. We claim that this is possible without any a priori knowledge of the underlying payoo matrices and without explicit communication between agents, and rst experiments yield promising results.
Classroom Quality, Classroom Composition, and Age at Entry: Experiences in Early Childhood Education and Care and Single and Dual Language Learners’ German Vocabulary

We examined independent and interactive links among three central characteristics of children’s experiences in early childhood education and care and the German receptive vocabulary of single language learners and dual language learners (DLLs). We allowed for possible differential effects depending on children’s language background. Our sample included 2,231 children (n = 1,555 single language learners, n = 371 DLLs from families in which German was frequently spoken, n = 305 DLLs from families in which German was less frequently spoken). Children attended 177 classrooms in 95 early childhood education and care centers and were 30 to 80 months old. We found that classroom process quality predicted German vocabulary only for DLLs with low exposure to German in the family. An earlier age at entry was linked to a larger German vocabulary for all children, but the link was stronger for DLLs from families with low exposure to German. Classroom composition did not predict German vocabulary.
On the Feasibility of Wireless Interconnects for High-throughput Data Centers

Data Centers (DCs) are required to be scalable to large data sets so as to accommodate ever increasing demands of resource-limited embedded and mobile devices. Thanks to the availability of recent high data rate millimeter-wave frequency spectrum such as 60GHz and due to the favorable attributes of this technology, wireless DC (WDC) exhibits the potentials of being a promising solution especially for small to medium scale DCs. This paper investigates the problem of throughput scalability of WDCs using the established theory of the asymptotic throughput of wireless multi-hop networks that are primarily proposed for homogeneous traffic conditions. The rate-heterogeneous traffic distribution of a data center however, requires the asymptotic heterogeneous throughput knowledge of a wireless network in order to study the performance and feasibility of WDCs for practical purposes. To answer these questions this paper presents a lower bound for the throughput scalability of a multi-hop rate-heterogeneous network when traffic generation rates of all nodes are similar, except one node. We demonstrate that the throughput scalability of conventional multi-hopping and the spatial reuse of the above bi-rate network is inefficient and henceforth develop a speculative 2-partitioning scheme that improves the network throughput scaling potentials. A better lower bound of the throughput is then obtained. Finally, we obtain the throughput scaling of an i.i. d. rate-heterogeneous network and obtain its lower bound. Again we propose a speculative 2-partitioning scheme to achieve a network with higher throughput in terms of improved lower bound. All of the obtained results have been verified using simulation experiments.
Penerimaan dan Pengetahuan Mahasiswa tentang Assessment for Learning

Assessment for learning (AfL) is considering the results of evaluation to rearrange better learning activities. One of assessments, formative assessment, is an information of development of students achievemnet in the learning activities. In addition, it is very usefull for redesign the next learning strategies to increase students capability, especially for teachers. So that, ability to conduct AfL is necessary for prospective teachers. This research is aimed to describe the approvement and understanding of prospective teacher to AfL. Survey, by using questionnare, is used in this research. Study objects were 59 students of Pendidikan Biologi Sebelas Maret University who enrolled in fourth semester. The data were analyzed qualitatively. The results showed that the most of students are realized the functions of assessment in the learning. Arround 67,8% of students stated that study plan can be changed based on the results of formative assessment. Meanwhile, 73,7% of students prefered written examination compared to the oral one and all of students are agree that every evaluation have to performe a feedback. Moreover, they are 69,5% and 74,6% of students decided on written and oral feedback respectively and the oral feedback is given by the teacher or lecturer. Then, all of students agree that feedback has some benefits to rise learning qualities. To conclude, the survey showed that students have approvement and understanding to the functions of AfL, kinds of assessment and feedback, and the subject of feedback. Prospective teacher needs more practice to use AfL and its application to reach the goals of learning
Cellular and molecular maturation in fetal and adult ovine calcaneal tendons

Processes of development during fetal life profoundly transform tendons from a plastic tissue into a highly differentiated structure, characterised by a very low ability to regenerate after injury in adulthood. Sheep tendon is frequently used as a translational model to investigate cell‐based regenerative approaches. However, in contrast to other species, analytical and comparative baseline studies on the normal developmental maturation of sheep tendons from fetal through to adult life are not currently available. Thus, a detailed morphological and biochemical study was designed to characterise tissue maturation during mid‐ (2 months of pregnancy: 14 cm of length) and late fetal (4 months: 40 cm of length) life, through to adulthood. The results confirm that ovine tendon morphology undergoes profound transformations during this period. Endotenon was more developed in fetal tendons than in adult tissues, and its cell phenotype changed through tendon maturation. Indeed, groups of large rounded cells laying on smaller and more compacted ones expressing osteocalcin, vascular endothelial growth factor (VEGF) and nerve growth factor (NGF) were identified exclusively in fetal mid‐stage tissues, and not in late fetal or adult tendons. VEGF, NGF as well as blood vessels and nerve fibers showed decreased expression during tendon development. Moreover, the endotenon of mid‐ and late fetuses contained identifiable cells that expressed several pluripotent stem cell markers [Telomerase Reverse Transcriptase (TERT), SRY Determining Region Y Box‐2 (SOX2), Nanog Homeobox (NANOG) and Octamer Binding Transcription Factor‐4A (OCT‐4A)]. These cells were not identifiable in adult specimens. Ovine tendon development was also accompanied by morphological modifications to cell nuclei, and a progressive decrease in cellularity, proliferation index and expression of connexins 43 and 32. Tendon maturation was similarly characterised by modulation of several other gene expression profiles, including Collagen type I, Collagen type III, Scleraxis B, Tenomodulin, Trombospondin 4 and Osteocalcin. These gene profiles underwent a dramatic reduction in adult tissues. Transforming growth factor‐ β~ 1 expression (involved in collagen synthesis) underwent a similar decrease. In conclusion, these morphological studies carried out on sheep tendons at different stages of development and aging offer normal structural and molecular baseline data to allow accurate evaluation of data from subsequent interventional studies investigating tendon healing and regeneration in ovine experimental models.
Incidence of multiple primary cancers and interval between first and second primary cancers

In this retrospective study, we aimed to clarify the risk of developing a second primary cancer and to determine the periods of high risk of second primary cancers. Subjects were all patients who had been diagnosed with a first primary cancer and registered with the Nagasaki Prefecture Cancer Registry between 1985 and 2007. We calculated the standardized incidence ratio (SIR) of second primary cancer according to site and years after diagnosis of the first primary cancer. A second primary cancer developed in 14 167 of 174 477 subjects (8.1%) during a median follow‐up of 1.8 years. The SIR of all cancer was 1.10 (95% confidence interval, 1.08–1.11). Some specific relationships were observed between sites with risk factors in common, such as smoking, drinking, and hormone status. The SIRs were relatively high after approximately 10 years for all sites, and trends differ among cancer sites. We showed that cancer patients are at higher risk of a second primary cancer than the general population. In respect of the risk of a second primary cancer, physicians should be alert for cancers that have risk factors in common with the first primary cancer.
Synthesizing type-safe compositions in feature oriented software designs using staged composition

The composition of features that interact with each other is challenging. Algebraic formalisms have been proposed by various authors to describe feature compositions and their interactions. The intention of feature compositions is the composition of fragments of documents of any kind to a product that fulfills users' requirements expressed by a feature selection. These modules often include code modules of typed programming languages whereas the proposed algebraic formalism is agnostic to types. This situation can lead to product code which is not type correct. In addition, types can carry semantic information on a program or module. We present a type system and connect it to an algebraic formalism thereby allowing automatic synthesis of feature compositions yielding well-typed programs.
Multiple Quantitative Trait Loci Mapping With Cofactors and Application of Alternative Variants of the False Discovery Rate in an Enlarged Granddaughter Design

The experimental power of a granddaughter design to detect quantitative trait loci (QTL) in dairy cattle is often limited by the availability of progeny-tested sires, by the ignoring of already identified QTL in the statistical analysis, and by the application of stringent experimentwise significance levels. This study describes an experiment that addressed these points. A large granddaughter design was set up that included sires from two countries (Germany and France), resulting in almost 2000 sires. The animals were genotyped for markers on nine different chromosomes. The QTL analysis was done for six traits separately using a multimarker regression that included putative QTL on other chromosomes as cofactors in the model. Different variants of the false discovery rate (FDR) were applied. Two of them accounted for the proportion of truly null hypotheses, which were estimated to be 0.28 and 0.3, respectively, and were therefore tailored to the experiment. A total of 25 QTL could be mapped when cofactors were included in the model—7 more than without cofactors. Controlling the FDR at 0.05 revealed 31 QTL for the two FDR methods that accounted for the proportion of truly null hypotheses. The relatively high power of this study can be attributed to the size of the experiment, to the QTL analysis with cofactors, and to the application of an appropriate FDR.
Work Group Inclusion: Test of a Scale and Model

We develop a theoretically based 10-item measure of work group inclusion comprised of two components (belongingness and uniqueness) and use this measure to empirically test the nomological network of work group inclusion developed by Shore et al. In Phase 1, we use two samples of full-time employees to develop and refine items as well as establish content validity. In Phase 2, we demonstrate convergent, discriminant, and incremental validity with both conceptually related and unrelated constructs. In Phase 3, we use data from an additional sample of employees and supervisors to test criterion-related validity and mediation by examining the multilevel relationships between inclusion and important antecedents and outcomes. Across the three phases of our study, the results demonstrate support not only for the factor structure, reliability, and validity of our work group inclusion measure but also for a theoretical model in which the construct of inclusion has important implications for individuals and organizations.
Improving Back-Propagation by Adding an Adversarial Gradient

The back-propagation algorithm is widely used for learning in artificial neural networks. A challenge in machine learning is to create models that generalize to new data samples not seen in the training data. Recently, a common flaw in several machine learning algorithms was discovered: small perturbations added to the input data lead to consistent misclassification of data samples. Samples that easily mislead the model are called adversarial examples. Training a "maxout" network on adversarial examples has shown to decrease this vulnerability, but also increase classification performance. This paper shows that adversarial training has a regularizing effect also in networks with logistic, hyperbolic tangent and rectified linear units. A simple extension to the back-propagation method is proposed, that adds an adversarial gradient to the training. The extension requires an additional forward and backward pass to calculate a modified input sample, or mini batch, used as input for standard back-propagation learning. The first experimental results on MNIST show that the "adversarial back-propagation" method increases the resistance to adversarial examples and boosts the classification performance. The extension reduces the classification error on the permutation invariant MNIST from 1.60% to 0.95% in a logistic network, and from 1.40% to 0.78% in a network with rectified linear units. Results on CIFAR-10 indicate that the method has a regularizing effect similar to dropout in fully connected networks. Based on these promising results, adversarial back-propagation is proposed as a stand-alone regularizing method that should be further investigated.
A PAPR reduction technique based on a constant envelope OFDM approach for fiber nonlinearity mitigation in optical direct-detection systems

In this paper, we propose a new peak-to-average power ratio reduction technique based on a constant envelope orthogonal frequency division multiplexing (CE-OFDM) approach to mitigate fiber induced nonlinearities in direct-detection optical OFDM (DDO-OFDM) systems. Simulation results show that the proposed 10 Gbps DDO-CE-OFDM system using 16-quadrature amplitude modulation (16-QAM), 2.66 GHz signal bandwidth, and different values of electrical phase modulation index outperforms DDO-OFDM systems as it increases the fiber nonlinearity tolerance in fiber links without optical dispersion compensation. The bit error rate of the proposed transmission scheme is decreased by a factor of 1000 if compared to conventional DDO-OFDM systems, for 10 dBm of optical input power and considering a span of 960 km of standard single-mode fiber.
Prevalence and Co-Occurrence of Substance Use Disorders and Independent Mood and Anxiety Disorders

Background Uncertainties exist about the prevalence and comorbidity of substance use disorders and independent mood and anxiety disorders. Objective To present nationally representative data on the prevalence and comorbidity of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM–IV) alcohol and drug use disorders and independent mood and anxiety disorders (including only those that are not substance induced and that are not due to a general medical condition). Design Face-to-face survey. Setting The United States. Participants Household and group quarters residents. Main Outcome Measures Prevalence and associations of substance use disorders and independent mood and anxiety disorders. Results The prevalences of 12-month DSM–IV independent mood and anxiety disorders in the U.S. population were 9.21 percent (95 percent confidence interval [CI], 8.78 percent–9.64 percent) and 11.08 percent (95 percent CI, 10.43 percent–11.73 percent), respectively. The rate of substance use disorders was 9.35 percent (95 percent CI, 8.86 percent–9.84 percent). Only a few individuals with mood or anxiety disorders were classified as having only substance-induced disorders. Associations between most substance use disorders and independent mood and anxiety disorders were positive and significant (p < .05). Conclusions Substance use disorders and mood and anxiety disorders that develop independently of intoxication and withdrawal are among the most prevalent psychiatric disorders in the United States. Associations between most substance use disorders and independent mood and anxiety disorders were overwhelmingly positive and significant, suggesting that treatment for a comorbid mood or anxiety disorder should not be withheld from individuals with substance use disorders.
Simulation of electron densities and breakdown voltages in argon-filled cylindrical electrodes

Breakdown voltage (VBD) is the most fundamental parameter to detect different gases in ionization gas sensor. In this work we present the simulated VBD in DC discharges and combined DC and RF discharges in argon using Particle-in-Cell Monte Carlo Collision (PIC-MCC) method. Electron density which plays a crucial role in the breakdown mechanism is also calculated at different positions between the cylindrical electrodes. The breakdown voltages agree well with experimentally measured and other simulated data for various ranges of gas pressures.
Symmetry and history quantum theory: An analog of Wigner’s theorem

The basic ingredients of the ‘‘consistent histories’’ approach to quantum theory are a space UP of ‘‘history propositions’’ and a space D of ‘‘decoherence functionals. ’’ In this article we consider such history quantum theories in the case where UP is given by the set of projectors P(V) on some Hilbert space V. We define the notion of a ‘‘physical symmetry of a history quantum theory’’ (PSHQT) and specify such objects exhaustively with the aid of an analog of Wigner’s theorem. In order to prove this theorem we investigate the structure of D, define the notion of an ‘‘elementary decoherence functional,’’ and show that each decoherence functional can be expanded as a certain combination of these functionals. We call two history quantum theories that are related by a PSHQT ‘‘physically equivalent’’ and show explicitly, in the case of history quantum mechanics, how this notion is compatible with one that has appeared previously.
Guided Alignment Training for Topic-Aware Neural Machine Translation

In this paper, we propose an effective way for biasing the attention mechanism of a sequence-to-sequence neural machine translation (NMT) model towards the well-studied statistical word alignment models. We show that our novel guided alignment training approach improves translation quality on real-life e-commerce texts consisting of product titles and descriptions, overcoming the problems posed by many unknown words and a large type/token ratio. We also show that meta-data associated with input texts such as topic or category information can significantly improve translation quality when used as an additional signal to the decoder part of the network. With both novel features, the BLEU score of the NMT system on a product title set improves from 18.6 to 21.3%. Even larger MT quality gains are obtained through domain adaptation of a general domain NMT system to e-commerce data. The developed NMT system also performs well on the IWSLT speech translation task, where an ensemble of four variant systems outperforms the phrase-based baseline by 2.1% BLEU absolute.