Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence of a new ordered vacancy crystal structure in the compound Cu 3 In 7 Te 12

The crystal structure of the ordered vacancy compound (OVC) Cu3In7Te12 is analyzed using powder X-ray diffraction data. It is found that this OVC crystallizes with a chalcopyrite-related structure, in the tetragonal space group P 4 2c (No 112), with unit cell parameters and volume a = 6.1720(2) Å, c = 12.3597(8) Å, and V = 470.83(4) Å 3 . The Rietveld refinement of 28 instrumental and structural parameters led to Rp = 9.27 %, Rwp = 10.30 %, Rexp = 6.95% and S = 1.48, for 4501 step intensities and 130 independent reflections, respectively. This compound is isostructural with Cu3In7Se12, and has a defect adamantane structure.
Learning Strategy of Think Talk Write Based Inquiry Approach Toward the Scientific Communication Ability of Students

This study has purpose to determine the comparison of the scientific communication ability of students between groups using the think talk write learning based inquiry approach to groups using the experimental learning, and determine the relationship between students' initial ability and students' scientific communication ability. The study was conducted with an experimental approach carried out in grade XI Persiapan Grafika SMK Islam Al Bisyri Semarang, by comparing the Think Talk Write learning groups based inquiry approach to the experimental learning. The variables studied were scientific communication ability obtained through observation during the learning process. The data were analyzed using Mann Whitney U and Spearman Rank. The results showed that the scientific communication ability of the think talk write based inquiry approach learning group based on the inquiry approach reviewd from four components, the Think Talk Write based inquiry approach learning group had the ability to access and utilize the latest library resources, the ability to contribute ideas in group work, the ability to prepare reports in accordance with the guidelines for scientific paper reports, it is better than the experimental learning, however, in the component of communicating products or reports verbally (presentations) did not show a significant difference between the think talk write based inquiry approach learning group and the experimental learning group. The initial ability of students does not affect the scientific communication ability of students in the think talk write learning group based inquiry approach and experimental learning groups.
SOCIODEMOGRAPHIC DETERMINANTS OF LOW BIRTH WEIGHT: A HOSPITAL BASED PROSPECTIVE CASE CONTROL STUDY IN RURAL SOUTH INDIA -

find the of LBW for size estimation and pilot study pretested Study include 100 LBW babies (cases) and 100 normal body weight babies (controls) among all deliveries within the study period. Maternal age and parity were matched for selection of the controls. If two or more suitable matched controls were available for a case, ABSTRACT Background: The birth weight of an infant is one of the most important determinants of its chances of survival, healthy growth, and development. Objectives: To estimate the proportion of babies with low birth weight (LBW) and to identify the sociodemographic risk factors associated with these LBW deliveries. Materials and Methods: This study is a hospital based case-control study undertaken in the postnatal care wards of KVG Medical College Hospital, Sullia. The study subject includes all mothers who underwent normal delivery within the study period and their neonates. The study covered a period of 1 year from January 2010 to December 2010. Data were collected by questionnaire method and analyzed. Results: Proportion of LBW found was 25.64%. The difference in distribution of cases and controls in relation to maternal education, maternal occupation, socioeconomic status was found to be statistically significant ( P < 0.05). On conditional logistic regression analysis important risk factors associated with LBW babies were maternal education status illiteracy (odds ratio [OR] - 1.425, 95% confidence of interest [CI] - 1.014-2.754), primary and secondary level education (OR - 1.174, 95% CI - 1.085-2.839), maternal occupation status coolies (OR - 2.743, 95% CI - 1.604-3.730) and agricultural workers (OR - 2.667, 95% CI - 1.516-4.649)], socioeconomic status (Class IV) (OR - 3.168, 95% CI - 2.876-4.593) and Class V (OR - 2.24, 95% CI - 1.573-4.771). Interpretation and Conclusion: Since most of these factors can be tackled easily by providing adequate antenatal care the LBW problem can be tackled effectively. Thus findings of the present study emphasizes the need for improving the quality and utilization of antenatal care, nutritional education to improve the pre-delivery body weight, spacing, avoidance of strenuous work during pregnancy, prevention and proper management of risk factor like anemia along with improving socioeconomic and educational status of mothers. LBW in housewifes and engaged in work compared to in nonprofessional with heavy physical
Sediments Transport Across the Fringing Reef in the Gulf of Aqaba , Red Sea and the Implications on Live Corals

This study was conducted on the shallow fringing reef of Aqaba, Red Sea. Unconsolidated sediment samples were collected along two transects perpendicular to the coast to determine the pattern of grain size distribution across the reef complex. The iron, aluminum and strontium concentrations were used to delineate the reef topography and zonation. The results indicate that the grain size distribution depends upon the local rate of skeletal production, the prevailing hydrodynamic conditions and the rate of coarse terrigenous materials delivered to the reef. The main zones of sediment production are those exposed to the wave action, the reef flat and the reef edge. Deposition dominates in most sheltered fore reef zone. Fine materials produced on the reef flat find its way mainly to the fore reef, while the effect of terrigenous input is limited to the backreef zone. In the depositional zone, the sediments are mostly medium to coarse, poorly sorted and symmetrically skewed, while the reef flat is occupied by the coarsest sediments, poorly to moderately sorted and symmetrical in skewness. Iron and aluminum are mainly originated from terrigenous source and marked the backreef zone, while high concentration of strontium associated with carbonate indicate the fore reef and reef flat zones. Dumping of terrigenous materials associated with mud delivered by floods to the reef may negatively affect the live corals in the fore reef.
How Capital Structure Affects Business Valuation: A Case Study of Slovakia

A company’s capital structure is a significant factor in valuing its business. The relative levels of equity and debt affect risk and cash flow and, therefore, the amount an investor would be willing to pay for the company or an interest in it. Capital structure matters because it influences the cost of capital. Therefore, this paper aims to quantify the effect of the capital structure on the cost of capital of Slovak enterprises and to suggest an effective way of financial decision-making. The data used in the study was gained from the Bratislava Stock Exchange because publicly available information on enterprises issuing their shares on the stock exchange was needed to calculate the cost of capital. Due to the underdeveloped capital market of Slovakia, we chose 17 stock companies (except for commercial banks) operating on the Slovak market having all the data required. The financial data of companies were obtained from their financial statements spanning 2013 to 2017. The impact of the capital structure on the cost of capital was investigated by the Pearson correlation coefficient, regression analysis and Mann-Whitney U-test. The study found that there is an indirect relationship between the capital structure, the cost of capital and the size of the company. We also conclude that the growing volume of debt may result in a decline in the corporate costs of capital. These findings concerning Slovak enterprises incline to the respected compromise theory.
Self-Supervised Deep Multi-View Subspace Clustering

As a new occurring unsupervised method, multi-view clustering offers a good way to investigate the hidden structure from multi-view data and attracts extensive attention in the community of machine learning and data mining. One popular approach is to identify a common latent subspace for capturing the multi-view information. However, these methods are still limited due to the unsupervised learning process and suffer from considerable noisy information from different views. To address this issue, we present a novel multi-view subspace clustering method, named self-supervised deep multi-view subspace clustering (S2DMVSC). It seamlessly integrates spectral clustering and affinity learning into a deep learning framework. S2DMVSC has two main merits. One is that the clustering results can be sufficiently exploited to supervise the latent representation learning for each view (via a classification loss) and the common latent subspace learning (via a spectral clustering loss) for multiple views. The other is that the affinity matrix among data objects is automatically computed according to the high-level and cluster-driven representation. Experiments on two scenarios, including original features and multiple hand-crafted features, demonstrate the superiority of the proposed approach over the state-of-the-art baselines.
Multivariate Time Series Prediction Based on Optimized Temporal Convolutional Networks with Stacked Auto-encoders

Multivariate time series prediction has recently attracted extensive research attention due to its wide applications in the area of financial investment, energy consumption, environmental pollution and so on. Because of the temporal complexity and nonlinearity existing in multivariate time series, few existing models could provide satisfactory prediction results. In this paper, we proposed a novel prediction approach based on optimized temporal convolutional networks with stacked auto-encoders, which can achieve better prediction performance as demonstrated in the experiments. Stacked auto-encoders are employed to extract effective features from complex multivariate time series. A temporal convolutional network is then constructed serving as the prediction model, which has a flexible receptive field and enjoys faster training speed with parallel computing ability than recurrent neural networks. The optimal hyperparameters in these models are discovered by Bayesian optimization. We performed extensive experiments by comparing the proposed algorithms and other popular algorithms on three different datasets, where the proposed approach obtain the best prediction results in various prediction horizons. In addition, we carefully analyze the search process of Bayesian optimization and provide further insights into hyperparametric tuning processes combining the exploration strategy with the exploitation strategy.
Association of -174 G>C interleukin-6 gene polymorphism with interleukin-6 and c-reactive protein levels and obesity: A case-control study among people/residents of Western Indonesia.

BACKGROUND Interleukin-6 (IL-6) and C-Reactive Protein (CRP) are mediators of inflammatory responses and increase in people who are obese . The increase of IL-6 and CRP levels is modified by polymorphism of -174 G>C IL-6 gene. AIM The purpose of this study was to investigate the relationship between -174 G>C IL-6 polymorphism gene on the level of IL-6 and CRP in the population of western Indonesia obese who are obese. METHODS In this study, we examined 178 subjects consisting of 89 who are obese with BMI> 25, and controls with BMI between 18.5 and 23. Fasting blood was taken from each subject for the examination of IL-6 and CRP levels by the ELISA method. Determination of genotype -174 G>C IL-6 gene was examined by Polymerase Chain reaction- Restriction Fragment Length Polymorphism (PCR-RFLP) methods. RESULTS The results of this study showed increased levels of IL-6 and CRP in the obese group compared to the controls. In the obese group, CC genotype had higher CRP and lower IL-6 levels than the GC and GG genotypes. The frequency of CC genotype in the obese group was 47.2% compared with 28.1% in controls and this genotype was considered a risk factor for obesity. Carriers of the C genotype as a dominant or a recessive model had greater risk of obesity. CONCLUSION It was concluded that the polymorphism - 174G>C IL-6 gene is a risk factor for obesity and is associated with increased levels of IL-6 and CRP in an obese group of the Western Indonesian ethnic population.
CHARACTERIZATIONS ON FRACTURE PROCESS ZONE OF PLAIN CONCRETE

The fracture property of concrete is essential for the safety and durability analysis of concrete structures. Investigating the characteristics of the fracture process zone (FPZ) is of great significance to clarify the nonlinear fracture behaviour of concrete. Experimental and numerical investigations on the FPZ of plain concrete in pre-notched beams subjected to three-point bending were carried out. Electronic speckle pattern interferometry (ESPI) technique was used to observe crack evolution and measure the full-field deformation of the beams. The development of the FPZ were evaluated qualitatively and quantitatively based on the in-plane strain contours and displacement field measured by ESPI, respectively. By integrating the cohesive crack model and finite element (FE) model, various tension softening curves (TSCs) were employed to simulate the fracture response of concrete beams. By comparing the deformation obtained by FE simulation and experiments, the TSCs of plain concrete were evaluated and most suitable TSCs of concrete were recommended.
Placenta microbiome : Proteobacteria Firmicutes Fusobacteria Tenericutes Age 0-3 : Proteobacteria Actinobacteria > 3 years : Proteobacteria Actinobacteria Firmicutes Bacteroidetes

The latest research cumulates staggering information about the correlation between the microbiota-gut-brain axis and neurodevelopmental disorders. This review aims to shed light on the potential influence of the microbiome on the development of the most prevalent neurodevelopmental disease, attention-deficit-hyperactive disorder (ADHD). As the etiology and pathophysiology of ADHD are still unclear, finding viable biomarkers and effective treatment still represent a challenge. Therefore, we focused on factors that have been associated with a higher risk of developing ADHD while simultaneously influencing the microbial composition. We reviewed the effect of a differing microbial composition on neurotransmitter concentrations important in the pathophysiology of ADHD. Additionally, we deduced factors that correlate with a high prevalence of ADHD while simultaneously affecting the gut microbiome such as emergency c-sections, and premature birth as the former leads to a decrease of the gut microbial diversity and the latter causes neuroprotective Lactobacillus levels to be reduced. Also, we assessed nutritional influences such as breastfeeding, ingestion of short-chain fatty acids (SCFAs) and polyunsaturated fatty acids (PUFAs) on the host’s microbiome and development of ADHD. Finally, we discussed the potential significance of Bifidobacterium as a biomarker for ADHD, the importance of preventing premature birth as prophylaxis and nutrition as a prospective therapeutic measurement against ADHD.
Near infrared spectrometry ( NIRS ) prediction of minor components in sunflower seeds

Minor components such as tocopherol and phytosterol present in sunflower seed are becoming interesting to consumers for their health properties, and to the food industry and sunflower breeders to obtain an added value to their products. The near infrared spectrometry (NIRS) technique could be a rapid and accurate method to determine the content of these useful molecules. The total tocopherol content reference values used to make calibration by NIRS varied from 62.8 to 451.9 mg/kg of dry matter (DM) and total phytosterol content values ranged from 53.9 to 189.0 mg/100g DM. The calibration equations obtained by NIRS showed a relatively good correlation coefficient between reference values and predicted values R = 0.58 for the tocopherol content and of 0.61 for the phytosterol content. These encouraging results showed that NIRS could be employed to estimate minor components such as tocopherols and phytosterol rapidly in sunflower seeds. Nevertheless, further investigations are required to improve calibration equations to permit an accurate selection with this method.
Best Practice Statement: Use of Ankle-Foot Orthoses Following Stroke

The development of this Best Practice Statement (BPS) was a collaboration between NHS Quality Improvement Scotland (NHS QIS), National Centre for Prosthetics and Orthotics, University of Strathclyde and a multidisciplinary group of relevant specialists. NHS QIS is a strategic health board which has a lead role in supporting the NHS in Scotland to improve the quality of healthcare. It does this by producing advice and evidence in a number of different formats, including BPS. These statements reflect the commitment of NHS QIS to sharing local excellence at a national level, and the current emphasis on delivering care that is patient-centred, cost-effective and fair. As part of a scoping exercise commissioned by NHS QIS in 2007, allied health professionals (AHPs) across Scotland identified the use of AFOs following stroke in adults as a clinical improvement priority. Orthotic intervention following stroke has been recognised as a treatment option for many years, but there is wide variation in current practice, and a lack of evidence-based research to determine the optimal rehabilitation programme for individuals following stroke. Stroke is the most frequent cause of severe adult disability in Scotland, with approximately 8,500 diagnoses of first-ever stroke each year, and more than 70,000 individuals affected by the condition. A recent Scottish Government strategy document confirms stroke as a national clinical priority for the Scottish NHS. In addition to developing a BPS and sharing this with healthcare professionals across Scotland, the initiative also sought to develop resource material to support the implementation of the BPS and to share the work internationally. In order to inform the development of the BPS a systematic literature review on AFO use following stroke was undertaken, including work of both a qualitative and quantitative nature. The full literature review, together with recommendations for future research, was included in the BPS. As it was felt that many medical professionals and AHPs may be unfamiliar with the principles underpinning orthotic practice, additional educational resources that would improve understanding of the reasons why the recommendations were being made were developed and included in the BPS. In addition to the full BPS, the key recommendations were summarised as a two-page 'quick reference guide' for ease of use in a clinical setting.
Interest Rate Rules in DSGE Models : Tracking the Efficient Real Interest Rate I

The empirical Dynamic Stochastic General Equilibrium (DSGE) literature pays surprisingly little attention to the behavior of the monetary authority. Alternative policy rule specifications abound, but their relative merit is rarely discussed. We contribute to filling this gap by undertaking a systematic comparison of the fit of several families of interest rate rules within two popular New Keynesian models. We find that the best fitting rules are those in which the nominal interest rate tracks the evolution of the model-consistent efficient real interest rate—an empirical hypothesis not previously explored in the literature.
ROLES OF PREPARATION CONDITIONS IN THE MORPHOLOGICAL EVOLUTION OF ELECTRODEPOSITED COPPER

We scrutinized the roles of fabrication conditions in the morphological construction of electrodeposited Cu using generated H2 bubbles as dynamic negative templates. Adjusting the concentration of acetic acid changed the shapes of the deposited Cu particles, adding cetyltrimethylammonium bromide made the generated Cu easily deposit and grow on the stabilized bubbles for more formation of interconnected dendrites, and decreasing Cu 2+
Automatic Hot Patch Generation for Android Kernels

The rapid growth of the Android ecosystem has led to the fragmentation problem where a wide range of (customized) versions of Android OS exist in the market. This poses a severe security issue as it is very costly for Android vendors to ﬁx vulnerabilities in their customized Android kernels in time. The recent development of the hot patching technique provides an ideal solution to solve this problem since it can be applied to a wide range of Android kernels without in-terrupting their normal functionalities. However, the current hot patches are written by human experts, which can be time-consuming and error-prone. To this end, we ﬁrst study the feasibility of automatic patch generation from 373 Android kernel CVEs ranging from 2012 to 2016. Then, we develop an automatic hot patch generation tool, named V ulmet , which produces semantic preserving hot patches by learning from the o ﬃ cial patches. The key idea of V ulmet is to use the weakest precondition reasoning to transform the changes made by the o ﬃ cial patches into the hot patch constraints. The experiments have shown that V ulmet can generate correct hot patches for 55 real-world Android kernel CVEs. The hot patches do not a ﬀ ect the robustness of the kernels and have low performance overhead.
CHAPTER 14 Design Considerations for Postcombustion CO 2 Capture With Membranes

The design of low-energy intensive, low-cost, and efficient CO2 capture unit is of extreme importance for the development of carbon capture and storage (CCS) technologies at industrial scale (Davidson and Metz, 2005). This mainly holds for the postcombustion, where the carbon dioxide is diluted in nitrogen with a volume fraction typically between 4% (i.e., gas turbine) and 15% (coal-fired power plant) and the flue gases to be treated are at atmospheric pressure conditions (Table 14.1). These two specificities address a great engineering challenge, especially in terms of the energy requirement of the separation process (Steeneveldt et al., 2006; Herzog, 2001; Wilcox, 2012).
Layer-wise Performance Bottleneck Analysis of Deep Neural Networks

Deep neural networks (DNNs) are becoming the inevitable part of a wide range of applications domains, such as visual and speech recognition. Recently, Graphics Processing Units (GPUs) are showing great success in helping meet the performance and energy efficiency demands of DNNs. In this paper, we identify GPU performance bottlenecks via characterizing the data access behaviors of AlexNet and VGG16 models in a layer-wise manner. The goal of this work is to find the performance bottlenecks of DNNs. We obtain following findings: (i) Backward propagation is more performance critical than forward propagation. (ii) The working set of convolutional interlayers does not fit in L1 cache, while convolutional input layer can exploit L1 cache sufficiently. (iii) Interconnect network can also be a performance bottleneck that substantially increase GPU memory bandwidth demand.
APERTURE AND OPTICS – MEASUREMENTS AND CONCLUSIONS

In 2011, the LHC has delivered collisions with different optics configurations in the four interaction points, at an operating energy of 3.5 TeV. The performance has been pushed during the year until a final configuration with 3 IPs squeezed to 1 m was achieved. Correspondingly, the machine aperture has been measured in the different configurations at injection and at top energy, to ensure a safe operation in all conditions of β∗ and crossing angle configuration. In this paper, the 2011 commissioning experience of LHC optics is reviewed and the results of aperture measurements are presented. Measurement requirements for 2012 and possible improvements are also discussed.