Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Lean-Seafood and Non-Seafood Diets on Fasting and Postprandial Serum Metabolites and Lipid Species: Results from a Randomized Crossover Intervention Study in Healthy Adults

The metabolic effects associated with intake of different dietary protein sources are not well characterized. We aimed to elucidate how two diets that varied in main protein sources affected the fasting and postprandial serum metabolites and lipid species. In a randomized controlled trial with crossover design, healthy adults (n = 20) underwent a 4-week intervention with two balanced diets that varied mainly in protein source (lean-seafood versus non-seafood proteins). Nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry analyses were applied to examine the effects of the two diets on serum metabolites. In the fasting state, the lean-seafood diet period, as opposed to the non-seafood diet period, significantly decreased the serum levels of isoleucine and valine, and during the postprandial state, a decreased level of lactate and increased levels of citrate and trimethylamine N-oxide were observed. The non-seafood diet significantly increased the fasting level of 26 lipid species including ceramides 18:1/14:0 and 18:1/23:0 and lysophosphatidylcholines 20:4 and 22:5, as compared to the lean-seafood diet. Thus, the lean-seafood diet decreased circulating isoleucine and valine levels, whereas the non-seafood diet elevated the levels of certain ceramides, metabolites that are associated with insulin-resistance.
Public Administration Reform and Its Implications for Foreign Petroleum Companies in Kazakhstan

ABSTRACT Since 2000, Kazakhstan has followed the New Public Management reform trajectory in modernizing its public sector and public service delivery. This article employs an actor-centered perspective to examine the effects of the public administration reform and its implications for foreign petroleum companies in Kazakhstan. The study builds on primary sources in the form of 81 semi-structured interviews with public servants, representatives of foreign petroleum companies and experts. The main conclusion is that the reform effects are ambiguous. Despite some success in greater efficiency of public services, many weaknesses remain, with highly varying implications for foreign petroleum companies.
Mining of Customer Reviews Using Deep Learning

Natural language processing (NLP), as a branch of artificial intelligence (AI), has found many important applications in human daily life. In particular, it has improved the ways that computers and humans interact. In this report, we investigate some connections between NLP and business by analyzing a dataset of 1525 negative reviews given by customers of low-rated McDonald’s restaurants in the United States. The reviews are labeled by one or several labels from eight categories. We apply word embedding and two deep learning architectures to build a model to assign the best set of labels to each review. At the end, we evaluate our model performance by considering its accuracy and Hamming loss.
A provisional strategy for treating true bifurcation lesions employing a scoring balloon for the side branch

The provisional approach for bifurcation stenting with side‐branch balloon angioplasty is associated with dissections and suboptimal results requiring kissing balloon techniques or bailout stenting. We hypothesized that using a scoring balloon for the side branch and a drug‐eluting stent for the main vessel might improve outcomes of true bifurcation lesions.
Stock Movement Prediction from Tweets and Historical Prices

Stock movement prediction is a challenging problem: the market is highly stochastic, and we make temporally-dependent predictions from chaotic data. We treat these three complexities and present a novel deep generative model jointly exploiting text and price signals for this task. Unlike the case with discriminative or topic modeling, our model introduces recurrent, continuous latent variables for a better treatment of stochasticity, and uses neural variational inference to address the intractable posterior inference. We also provide a hybrid objective with temporal auxiliary to flexibly capture predictive dependencies. We demonstrate the state-of-the-art performance of our proposed model on a new stock movement prediction dataset which we collected.
New insights into the function and global distribution of 1 polyethylene terephthalate ( PET ) degrading bacteria and enzymes 2 in marine and terrestrial metagenomes 3 4

*Correspondence 21 E-Mail: wolfgang.streit@uni-hamburg.de 22 Department of Microbiology and Biotechnology, 23 Biocenter Klein Flottbek, University of Hamburg 24 Ohnhorststr.18, D-22609 Hamburg, Germany 25 Tel. (+49) 40-42816-463, Fax. (+49) 40-42816-459 26 AEM Accepted Manuscript Posted Online 2 February 2018 Appl. Environ. Microbiol. doi:10.1128/AEM.02773-17 Copyright © 2018 Danso et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.
Assessment on various node voltage stability indices — A review

With the surge in demand for electrical energy and the consequent need to operate the power system close to its limits, the need to compute the voltage stability limit and the system's proximity to this limit has become mandatory. Among the methods to compute these parameters, the Voltage Stability Indices stand out owing to their attributes of simplicity and minimal computational effort and have also served varied applications. This paper presents a review on Node Voltage Stability Indices with respect to approach, values at critical point, deviation from critical point value, accuracy and response at different power factors via graphical means. The results and conclusions presented in this paper have been arrived at by performing the computations on IEEE 30 Bus system on MATLAB 8.0R 2012b environment.
GaRSIVis: improving the predicting of self-interruption during reading using gaze data

Gaze pattern data provides a promising opportunity to create a predictive model of self-interruption during reading that could support active interventions to keep a reader's attention at times when self-interruptions are predicted to occur. We present two systems designed to help analysts create and improve such a model. We present GaRSIVis, (Gaze Reading Self-Interruption Visualizer), that integrates a visualization front-end suitable for data cleansing and a prediction back-end that can be run repeatedly as the input data is iteratively improved. It allows analysts refining the predictive model to filter out unwanted parts of the gaze data that should not be used in the prediction. It relies on data gathered by GaRSILogger, which logs gaze data and activity associated with interruptions during on-screen reading. By integrating data cleansing and our prediction results in our visualization, we enable analysts using GaRSIVis to come up with a comprehensible way of understanding self-interruption from gaze related features.
Steroid Receptors and Aromatase Gene Expression in Different Brain Areas of Copulating and Sexually Sluggish Male Rats.

INTRODUCTION Sexually sluggish (SS) males have been identified in several species of mammals including rats. These animals take more than 30 minutes to ejaculate; they do not ejaculate or do so inconsistently despite being tested repeatedly with sexually receptive females. Different brain areas and hormones play an important role in the control of male sexual behavior. AIMS Determine gene expression for the androgen receptor (AR), the estrogen receptor alpha (ERα), the progesterone receptor (PR), and the aromatase enzyme (ARO), in brain regions important in the control of male sexual behavior including the medial preoptic area (MPOA), the amygdala (AMG), the olfactory bulb (OB), and, as a control, the cortex (CTX) of copulating (C) and SS male rats. METHODS Males that ejaculated within 30 minutes in three tests with receptive females were included in the C group, while those males that ejaculated in one or none of the four tests were included in the SS group. RNA was isolated 1 week after the last test of sexual behavior, and cDNA was synthesized from the brain areas listed above. MAIN OUTCOMES MEASURES Expression of the AR, ERα, PR, and ARO genes was determined by quantitative polymerase chain reaction (qPCR). Cyclophilin A (CycA) and tyrosine 3-monooxygenase-tryptophan activation protein zeta (Ywhaz) were housekeeping genes used to determine relative gene expression with the 2(-ΔΔCt) method. RESULTS The expression of mRNA for AR and ARO increased in the MPOA of SS males. ARO mRNA was increased in the AMG of SS males. In the OB, ERα mRNA was increased and AR mRNA reduced in SS males. CONCLUSION These results indicate SS and C males show differences in gene expression within brain regions controlling sexual behavior.
Single determinant N‐representability and the kernel energy method applied to water clusters

The Kernel energy method (KEM) is a quantum chemical calculation method that has been shown to provide accurate energies for large molecules. KEM performs calculations on subsets of a molecule (called kernels) and so the computational difficulty of KEM calculations scales more softly than full molecule methods. Although KEM provides accurate energies those energies are not required to satisfy the variational theorem. In this article, KEM is extended to provide a full molecule single‐determinant N‐representable one‐body density matrix. A kernel expansion for the one‐body density matrix analogous to the kernel expansion for energy is defined. This matrix is converted to a normalized projector by an algorithm due to Clinton. The resulting single‐determinant N‐representable density matrix maps to a quantum mechanically valid wavefunction which satisfies the variational theorem. The process is demonstrated on clusters of three to twenty water molecules. The resulting energies are more accurate than the straightforward KEM energy results and all violations of the variational theorem are resolved. The N‐representability studied in this article is applicable to the study of quantum crystallography. © 2017 Wiley Periodicals, Inc.
Animal Models to Study Hepatitis C Virus Infection

With more than 71 million chronically infected people, the hepatitis C virus (HCV) is a major global health concern. Although new direct acting antivirals have significantly improved the rate of HCV cure, high therapy cost, potential emergence of drug-resistant viral variants, and unavailability of a protective vaccine represent challenges for complete HCV eradication. Relevant animal models are required, and additional development remains necessary, to effectively study HCV biology, virus–host interactions and for the evaluation of new antiviral approaches and prophylactic vaccines. The chimpanzee, the only non-human primate susceptible to experimental HCV infection, has been used extensively to study HCV infection, particularly to analyze the innate and adaptive immune response upon infection. However, financial, practical, and especially ethical constraints have urged the exploration of alternative small animal models. These include different types of transgenic mice, immunodeficient mice of which the liver is engrafted with human hepatocytes (humanized mice) and, more recently, immunocompetent rodents that are susceptible to infection with viruses that are closely related to HCV. In this review, we provide an overview of the currently available animal models that have proven valuable for the study of HCV, and discuss their main benefits and weaknesses.
Estimating Default and Recovery Rate Correlations

The paper analyzes a two-factor credit risk model allowing to capture default and recovery rate variation, their mutual correlation, and dependence on various explanatory variables. At the same time, it allows computing analytically the unexpected credit loss. We propose and empirically implement estimation of the model based on aggregate and exposure level Moody’s default and recovery data. The results confirm existence of significantly positive default and recovery rate correlation. We empirically compare the unexpected loss estimates based on the reduced two-factor model with Monte Carlo simulation results, and with the current regulatory formula outputs. The results show a very good performance of the proposed analytical formula which could feasibly replace the current regulatory formula.
Solar Photovoltaic and Thermal Energy Systems: Current Technology and Future Trends

Solar systems have become very competitive solutions for residential, commercial, and industrial applications for both standalone and grid connected operations. This paper presents an overview of the current status and future perspectives of solar energy (mainly photovoltaic) technology and the required conversion systems. The focus in the paper is put on the current technology, installations challenges, and future expectations. Various aspects related to the global solar market, the photovoltaic (PV) modules cost and technology, and the power electronics converter systems are addressed. Research trends and recommendations for each of the PV system sectors are also discussed.
Protein Engineering on Human Recombinant Follistatin: Enhancing Pharmacokinetic Characteristics for Therapeutic Application

Follistatin (FS) is an important regulatory protein, a natural antagonist for transforming growth factor-β family members activin and myostatin. The diverse biologic roles of the activin and myostatin signaling pathways make FS a promising therapeutic target for treating human diseases exhibiting inflammation, fibrosis, and muscle disorders, such as Duchenne muscular dystrophy. However, rapid heparin-mediated hepatic clearance of FS limits its therapeutic potential. We targeted the heparin-binding loop of FS for site-directed mutagenesis to improve clearance parameters. By generating a series of FS variants with one, two, or three negative amino acid substitutions, we demonstrated a direct and proportional relationship between the degree of heparin-binding affinity in vitro and the exposure in vivo. The triple mutation K(76,81,82)E abolished heparin-binding affinity, resulting in ∼20-fold improved in vivo exposure. This triple mutant retains full functional activity and an antibody-like pharmacokinetic profile, and shows a superior developability profile in physical stability and cell productivity compared with FS variants, which substitute the entire heparin-binding loop with alternative sequences. Our surgical approach to mutagenesis should also reduce the immunogenicity risk. To further lower this risk, we introduced a novel glycosylation site into the heparin-binding loop. This hyperglycosylated variant showed a 10-fold improved exposure and decreased clearance in mice compared with an IgG1 Fc fusion protein containing the native FS sequence. Collectively, our data highlight the importance of improving pharmacokinetic properties by manipulating heparin-binding affinity and glycosylation content and provide a valuable guideline to design desirable therapeutic FS molecules.
Enterobacterial Repetitive Intergenic Consensus Polymerase Chain Reaction (ERIC-PCR) Genotyping of Escherichia coli Strains Isolated from Different Animal Stool Specimens

Background: Escherichia coli is a commensal-pathogenic organism, which includes a wide range of strains. Despite several advanced molecular-genomic technologies for detecting and identifying different strains of E. coli, Enterobacterial Repetitive Intergenic Consensus Polymerase Chain Reaction (ERIC-PCR) technique is a quick, sharp and cost effective fingerprint method. The major purpose of the present study was to determine the distribution of ERICs within E. coli strains isolated from different healthy animal stool specimens including hens, sheep, and cows, as an appropriate and quick molecular-genomic tool. Methods: The animal stool samples were obtained during 1 year (October 2012 to October 2013), from animal husbandries around Tehran and Alborz provinces, Iran. After screening processes, the E. coli bacteria were isolated and cultured via standard microbiological methods. The DNA molecules of E. coli bacteria were harvested and Enterobacterial Repetitive Intergenic Consensus Polymerase Chain Reaction (ERIC-PCR) was applied for bacterial molecular genotyping. The ERIC-PCR products were run on 1% gel electrophoresis. The final images regarding gel electrophoresis banding patterns were used for dendrogram generation via the GelClust software. Results: Of 120 isolated samples, 115 different strains were recognized as E. coli. The fingerprint patterns involved 380 to 3280 bp bands. The predominant bands included 2900 bp, 1200 bp, and 1200 bp in stool samples of hens, sheep, and cows, respectively. The highest frequencies and diversities were seen among E. coli strains isolated from hens and sheep stool samples. Conclusion: The DNA profiles were clearly detectable via specific fingerprint patterns. The ERIC-PCR seemed to be a good approach for molecular typing of E. coli strains isolated from different animal sources.
A study of the distance teacher education programme (DTEP) offered by the Lesotho College of Education in Maseru Lesotho.

2 Declaration 3 Acknowledgements 4 Dedication 5 List of Tables 6 Acronyms 7 Table of Content 8 CHAPTER 1: INTRODUCTION 11 1.1. Background Information 11 1.2. Statement of the Problem 13 1.3. Aims and Research Questions 14 1.4. Rationale 15 CHAPTER 2: LITERATURE REVIEW 17 2.
Land Access and Livelihood Strategies in Mvomero District Tanzania

Land is a key asset for rural livelihoods. The general objective of this paper is to determine the relationship between land access and livelihood strategies (LS) in the context of land scarcity. A good understanding of the above relationship is of great importance to policy makers and all those interested in improving the well-being of those living in such areas. Moreover, the above could offer guidance for focused poverty interventions aiming at promoting diversity of LS. The paper is based on a study that was carried out in Mvomero District, Tanzania. The study adopted a cross-sectional research design and both qualitative and quantitative data were collected through a pre-structured questionnaire, focus group discussions and key informant interviews. A total of 267 respondents were involved in the household surveys that aimed to explore the portfolio of household's livelihood strategies, the availability of assets requisite for smooth diversification, challenges associated with LS and the effects of land access on LS. The quantitative data collected was analyzed using the SPSS software: descriptive and multinomial logistic regression were performed to identify dominant LS, determine assets portfolios and the influence of land access and selected household socio-economic characteristics on choices of LS. Qualitative data were analysed using the content analysis method and used to supplement the quantitative information. The results show that, farming is the dominant household LS. However, a significant proportion of households cope with land shortage by engaging in survival off-farm LS due to lack of labour skills, savings and capital necessary for undertaking high paying LS. A households location and its distance to the farm was positively related to its engagement in survival off-farm LS. Moreover, ownership of land without formal land titles negatively influenced a household's diversification of its LS (p < 0.05). It is therefore recommended that strategies for improvement of the well-being of households in the study areas and those with similar context should centre on promotion of diversification of LS. Nonetheless, investment in education and labour skills training is crucial for a meaningful diversification of LS. In addition, households should be encouraged to save, access to credit should be improved and formalization of land titles should be done.
Development and Validation of an Age-Specific Lower Extremity Finite Element Model for Simulating Pedestrian Accidents

The objective of the present study is to develop an age-specific lower extremity finite element model for pedestrian accident simulation. Finite element (FE) models have been used as a versatile tool to simulate and understand the pedestrian injury mechanisms and assess injury risk during crashes. However, current computational models only represent certain ages in the population, the age spectrum of the pedestrian victims is very large, and the geometry of anatomical structures and material property of the lower extremities changes with age for adults, which could affect the injury tolerance, especially in at-risk populations such as the elderly. The effects of age on the material mechanical property of bone and soft tissues of the lower extremities as well as the geometry of the long bone were studied. Then an existing 50th percentile male pedestrian lower extremity model was rebuilt to depict lower extremity morphology for 30- to 70-year-old (YO) individuals. A series of PMHS tests were simulated to validate the biofidelity and stability of the created age-specific models and evaluate the lower extremity response. The development of age-specific lower extremity models will lead to an improved understanding of the pedestrian lower extremity injury mechanisms and injury risk prediction for the whole population in vehicle-pedestrian collision accidents.
Institutional change for strong sustainable consumption: sustainable consumption and the degrowth economy

Abstract The environmental space concept illustrates that socially unsustainable underconsumption must be overcome and environmentally unsustainable overconsumption must be phased out. The planetary boundaries help to quantify the “ceiling,” while the social protection floor concept operationalizes the linea de dignidad, the minimal conditions for a dignified life. In order for Western societies to respect these limits, significant institutional change is needed with respect to both orientations and mechanisms. For the ceiling, this article suggests a shift to an orientation of “better but less” for affluent groups, and toward “enough and better” for those still living in poverty. The corresponding mechanisms include a redistribution of income and wealth, a cap on income, an unconditional minimum income, and a strengthening of democracy. The choice of instruments has to take into account that consumption is to a large degree not an individual but a social act and to employ informational, financial, and legal measures that overcome the preference of decision makers for market instruments. Implementing these changes would alter the fabric of our societies. Important first steps can be taken here and now.
Learning to Rank Documents by Learning to Rank Passages

According to TREC’s relevance judgment regime, a document can be deemed relevant to a query even if it contains a very short passage of text with pertinent information. This fact has motivated work on passage-based document retrieval: document ranking methods that induce information from the document’s passages. However, the main source of passage-based information utilized was passage-query similarities. We address the challenge of utilizing richer sources of passage-based information to improve document retrieval effectiveness. Specifically, we devise a suite of learning-to-rank-based document retrieval methods that utilize a highly effective ranking of passages produced in response to the query; passage ranking is also induced using a learning-to-rank approach. Empirical evaluation attests to the clear merits of our methods with respect to strong baselines.