Miracle-dz/UniFAR-FTUs huggingface dataset:
Nanoscale Aluminum-Metal Oxide (Thermite) Reactions for Application in Energetic Materials

Energetic materials find use in both military and civilian applications, however many commonly used materials suffer from serious deficiencies including toxicity and high sensitivity. Nanothermites exhibit vastly differing characteristics compared to their well known micron scale relatives and through the use of various preparatory chemical techniques can be tailored to have a wide spectra of chemical and energetic properties. This may allow use as superior replacements of conventional energetic materials in various applications.
Opportunities and Challenges of Small-Scale Irrigation And Its Implications For Livelihood Improvement: (The Case Of Tigray Regional State, Northern Ethiopia)

The paper examines the challenges and opportunities of small-scale irrigation schemes in northern Ethiopia, with the view of strengthening their significance in improving rural livelihoods in Tigray region. It adopts quantitative and qualitative research approach. A total of 100 respondents from three weredas were involved in the survey. When the Pearson relationship of the different independent variables is seen in relation to agricultural production, factors such as investment and construction of ponds, investment in purchase of inputs, investment in purchase of pumps, total irrigated land in ha and revenue from agricultural products are playing an important role in promoting agricultural production and there is positive and significant relationship to agricultural production. The research result also identified that the problems of small-scale irrigations as shortage of agricultural inputs specially improved seed and pesticides, financial constraints especially for the purchase of motor pumps, high cost of irrigation, shortage of water pump technologies, spare parts and gabions, technical problems such as maintenance of motor pumps, insufficient market information and market networks, shortage of ponds and diversion, infrastructure specially road and storage, theft of fruits, diseases and pests. The result of the research also indicates that there is potential for the development of small-scale irrigation specially water, land and labour. In conclusion, if small-scale irrigation schemes are to play their role, an integrated effort of all development partners such as government (specifically Bureau of Agriculture and Rural Development, Woreda Office of Agriculture and Rural Development), cooperative promoters, microfinance institutions, private banks, donor agencies, private sector and the society at large is crucial to address the aforementioned problems faced by farmers. Moreover, farmers should establish viable and strong linkages with development /extension agents and other cooperative societies in the areas of irrigation, agricultural production, finance, marketing and technology adoption.
A comparison of resampling and recursive partitioning methods in random forest for estimating the asymptotic variance using the infinitesimal jackknife

The infinitesimal jackknife (IJ) has recently been applied to the random forest to estimate its prediction variance. These theorems were verified under a traditional random forest framework that uses classification and regression trees and bootstrap resampling. However, random forests using conditional inference trees and subsampling have been found to be not prone to variable selection bias. Here, we conduct simulation experiments using a novel approach to explore the applicability of the IJ to random forests using variations on the resampling method and base learner. Test data points were simulated and each trained using random forest on one hundred simulated training data sets using different combinations of resampling and base learners. Using conditional inference trees instead of traditional classification and regression trees as well as using subsampling instead of bootstrap sampling resulted in a much more accurate estimation of prediction variance when using the IJ. The random forest variations here have been incorporated into an open‐source software package for the R programming language. Copyright © 2017 John Wiley & Sons, Ltd.
Analyzing Protein Dynamics Using Dimensionality Reduction

This thesis investigates dimensionality reduction for analyzing the dynamics ofprotein simulations, particularly disordered proteins which do not fold into a xedshape but are thought to perform their functions through their movements. Ratherthan analyze the movement of the proteins in 3D space, we use dimensionalityreduction to project the molecular structure of the proteins into a target space inwhich each structure is represented as a point. All that is needed to do this arethe pairwise distances between the protein structures. We can then visualize theprojected structures in three dimensions to get a general idea of the dynamics ofthe protein. We can also measure how well the projection preserves the pairwisedistances between structures for a particular target dimension to get an idea ofthe dimension of the dynamics of the protein in the original space.
Okra Polysaccharides Improves Spleen Weight and B-Lymphocytes Proliferation in Mice Infected by Staphylococcus aureus

Okra ( Abelmoschus esculentus ) is reported to have various biological functions such as antioxidant, anticancer and anti-inflammation. However, only few studies have been reported immunomodulatory activities of okra to prevent disease caused by bacteria infection. In this study, the immunomodulatory activities of polysaccharides from okra pods were investigated further through the spleen weight and B-lymphocytes proliferation in mice infected by Staphylococcus aureus . Okra polysaccharides were obtained by water extraction and ethanol precipitation. Okra polysaccharides with doses of 25, 50, 75, and 100 mg/kg BW were orally administrated to mice with or without Staphylococcus aureus infection. Spleen weight was evaluated in both treatment group and control group. B-lymphocytes proliferation was evaluated by MTT assay using LPS induction. Results showed that okra polysaccharide at the doses of 50, 75, and 100 mg/kg increased spleen weight (p < 0.05) significantly. While at the dose of 75 and 100 mg/kg, it increased the B-lymphocytes proliferation (p < 0.05) significantly. There is positive correlation between the spleen weight and B-lymphocytes proliferation by 73.3%. These result reveal that okra polysaccharide could improve the immune response and be utilized as a novel candidate of neutraceutical.
Should Network Structure Matter in Agent-Based Finance?

We derive microscopic foundations for a well-known probabilistic herding model in the agent-based finance literature. Lo and behold, the model is quite robust with respect to behavioral heterogeneity, yet structural heterogeneity, in the sense of an underlying network structure that describes the very feasibility of agent interaction, has a crucial and non-trivial impact on the macroscopic properties of the model.
Seasonal and interplanetary magnetic field dependence of the field-aligned currents for both Northern and Southern Hemispheres

Abstract. The configuration of the Earth's magnetosphere under various Interplanetary Magnetic Field (IMF) and solar wind conditions alters the global distribution of Field-Aligned Currents (FACs) at the high latitude ionospheres. We use magnetic field data obtained from the Iridium constellation to extend recent studies that infer the dependence of the global FAC configuration on IMF direction and magnitude, hemisphere and season. New results are a reduced IMF By influence on the FAC configuration for the winter hemisphere and a redistribution of FAC to the nightside for winter relative to the summer hemisphere. These effects are linked to the winter ionosphere conductance distribution being dominated by localised nightside enhancement associated with ionisation from energetic particle precipitation. A comparison of an estimated open-closed field line boundary (OCFLB) with the Region 1 FAC locations shows reasonable agreement for summer FAC configurations. However, the OCFLB location is decoupled from the Region 1 FACs in winter, especially for IMF Bz>0.
Pragmatic Analysis on Malware Classification

: Malware are tiny software which are created to harm our computers or to steal valuable information. Recently with the advancement in machine learning algorithms, researches also started looking to a solution which can detect the malware and classify them automatically so that necessary step can be decided. In this paper we discussed and reviewed the methods adopted and suggested by various researchers to detect and classify malwares using machine learning and clustering algorithms. Since this is not a very old field so research papers used to review are not very old.
Meditation-Based Intervention as a Complementary Treatment for Adenomyosis: A Case Report

Objective:Adenomyosis is a common benign gynecological condition in pre- menopausal women, with symptoms such as menorrhagia and dysmenorrhea, greatly affecting women’s health and quality of life. The treatment options of adenomyosis are hysterectomy, anti-inflammatory, hormone medications and conservative surgeries. However, they might be either temporary symptom control, or side effects, or compromised fertility, or no fertility. Meditation- based intervention has been shown beneficial to various diseases. The patient was a 45-year-old Taiwanese woman who was diagnosed with adenomyosis, after experiencing severe symptoms, including menorrhagia and dysmenorrheal. The intervention was to identify her greatest stressor firstly and then let go of it to reduce the greatest portion of the stress; next, to do mantra meditation, Six Character Great Bright Mantra, and mindfulness meditation intensively to keep reducing stress, while taking medicine of anti-inflammatory, hemostatic drugs, iron and vitamin B as necessary. She was an experienced meditation practitioner of mantra and mindfulness. The result was that serum cancer antigen 125 (CA 125), menstrual pain and bleeding reduced considerably within 1.5 months. The symptoms were alleviated successfully. Her symptoms of adenomyosis intensified at her age of 50. She did meditation-based intervention and alleviated symptoms successfully again. The intervention enabled her to pass into menopause well without hysterectomy or any conservative operation or hormone medications.
ACCURACY OF ESTIMATES OF VOLUME FRACTION

When estimating a volume fraction VV from point count fractions PP using Delesse's principle VV = PP, very little information on the accuracy of the estimator can be obtained from the basic theory of stereology. Existing methods for quantifying the variability of PP are mainly large-sample approximations such as Cochran's formula for the variance of a ratio. Cruz -Orive proposed an alternative method, but this requires statistical assumptions to be made on the point counts P, that do not hold in general. We introduc e two alternative methods for quantifying the variability of PP, namely the bootstrap method and explicit statistical modelling of the bivariate distribution. The bootstrap method requires few statistical assumptions about the point counts but requires lar ge sample size. The explicit statistical modelling method does make assumptions, but they can be checked directly from the data. To explore this approach, we propose a statistical model, the Type I Bivariate Binomial (BVB) distribution to model the pairs o f count data (P, P). We show how to fit the BVB model to the data and how to assess the goodness-of-fit of this model. A formula for the variance of PP under the BVB model is also derived. The three approaches are compared in their application to nine exam ple data sets taken from macroscopic sections of cerebral hemispheres of selected domesticated animals. The BVB model appears to be a good fit to these data sets. Implications for stereological estimation are discussed.
Registration of Point Cloud Data Based on PSO

At present,3-D model can be build through point clouds data which is quickly get by laser scanning technology. Most of the researches on registration problems are focused on feature matching method. This paper discusses a method with global optimization algorithm. In order to solve the problem efficiently, we present a method using PSO algorithm with Cross Products of Normal Vector. This method does not require artificial targets and feature points frequently. The fitness function is used the sum of normal vectors’ cross products to define, and it applies an efficient “Universal Search” and implements cloud data registration based on the best registration criterion. The application and analysis on example indicates the proposed method is effective and feasible. Keywords-point cloud; registration; PSO; cross products of normal vector.
PERFORMANCE ANALYSIS OF ENTREPRENEURSHIP POLICY: WHICH BUSINESS INCUBATORS GENERATE THE HIGHEST LEVELS OF ECONOMIC PERFORMANCE?

Business incubators, organizations created to help small and young firms become stable and profitable, are a mainstay of economic development programs. This study looks at how the incubation process and the attributes of incubators affect the performance of their clients during and after incubation. Results reveal that some types of incubators achieve greater success and that success often varies on whether the entrepreneur is a woman or minority.
Reforming Secondary Music Teaching in the New Century

This article argues for a redefinition of how secondary music teachers might think about teaching content. Rather than considering only performance-based education that reaches only a small portion of the secondary school population, music teachers should consider composition, improvisation, and active listening as important additional concerns for a wider population of students. Such an approach is important for serving gifted and talented students as part of mainstream instruction and is in tune with latest developments in curriculum design and research. Constructivism as an educational philosophy is suggested as a conceptual base and advances in music technology and the encouragement of creative thinking are cited as important contributions to this reform.
Isolation of a Peniophora Strain Capable of Producing Ethanol from Starch and Kitchen Waste

A white rot basidomycete identified as Peniophora sp. produced ethanol from glucose, mannose, cellobiose, and maltose with yields ranging from 0.37 to 0.41 g-1 ethanol consumed sugar. Peniophora sp. was also capable of directly fermenting various types of starches, including soluble, corn, potato, and wheat starches, at a yield of 0.39 to 0.41 g-1 ethanol added starch. The fungus also directly converted untreated kitchen waste to ethanol at 73% of the theoretical yield in the absence of externally added enzymes or nitrogen. Our findings indicate that Peniophora sp. efficiently hydrolyzes biomass to fermentable sugars, which are then directly converted to ethanol. The metabolic properties of this fungus may permit cost-effective and environmental friendly bioethanol production from various starting materials, including kitchen waste.
HARDNESS DATA SYNTHESIS FOR HEIGHT-FIELD BASED LANDSCAPE MODELS

Landscape modelling is a key element of synthetic environments in virtual reality systems such as: military training systems, virtual reconstruction of cultural heritage, digital entertainment and game development. Most popular and simplest to implement data structures for terrain models are based on the height-field representation. Unfortunately, such models do not contain information about hardness of terrain or it susceptibility for erosion forces in different landscape areas. It is possible to derive hardness data from actual geological records, but for virtual environments we propose the fully automated synthesis of hardness information for terrain models. Our method stems from classical Poisson Faulting algorithm, that was originally used by Mandelbrot and Voss to model ragged landscapes and whole planets. The proposed technique can help to generate hardness data under the height-field base terrain, with regard to different geological materials. The algorithm ensures that those materials are not randomly displaced but form clusters throughout the entire virtual terrain. In addition, the technique can be simply parallelized and implemented in CUDA programming environment. Obtained data structure can be used for further synthesis of eroded landscapes or can work as a test bed for comparison of different geological erosion simulating some models.
Orientation of Hydroxyapatite C-Axis under High Magnetic Field with Mold Rotation and Subsequent Sintering Process

Orientation of hydroxyapatite (HAp) crystals is one of the promising ways to utilize their anisotropic nature of chemical and biological properties. On the other hand, the development of super conducting magnet technology enables to introduce a high magnetic field which can control crystal orientation of non-magnetic materials with magnetic anisotropy. In this study, a horizontal 10 T static magnetic field was imposed on slurry containing HAp crystals under the horizontal mold rotation during slip casting process so as to introduce c-axis orientation for some amount of crystals in the sample, and then it was sintered in atmosphere without the magnetic field. From SEM observation and X-ray diffraction, it has been found that the c-axis of pillar shape HAp crystals in the sample treated with the magnetic field and the mold rotation were oriented to a particular direction and it was enhanced by the subsequent sintering process, while the c-axis crystal orientation of the sample treated without the magnetic field and with the mold rotation was not observed before and after the sintering.
Probabilistic Community Detection With Unknown Number of Communities

ABSTRACT A fundamental problem in network analysis is clustering the nodes into groups which share a similar connectivity pattern. Existing algorithms for community detection assume the knowledge of the number of clusters or estimate it a priori using various selection criteria and subsequently estimate the community structure. Ignoring the uncertainty in the first stage may lead to erroneous clustering, particularly when the community structure is vague. We instead propose a coherent probabilistic framework for simultaneous estimation of the number of communities and the community structure, adapting recently developed Bayesian nonparametric techniques to network models. An efficient Markov chain Monte Carlo (MCMC) algorithm is proposed which obviates the need to perform reversible jump MCMC on the number of clusters. The methodology is shown to outperform recently developed community detection algorithms in a variety of synthetic data examples and in benchmark real-datasets. Using an appropriate metric on the space of all configurations, we develop nonasymptotic Bayes risk bounds even when the number of clusters is unknown. Enroute, we develop concentration properties of nonlinear functions of Bernoulli random variables, which may be of independent interest in analysis of related models. Supplementary materials for this article are available online.
Effects of Ramadan Fasting on Some Physiological and Biochemical Parameters in Healthy and Hypertensive Subjects in Aurangabad District of Maharashtra, India

Throughout the world, millions of Muslims fast daily during the month of Ramadan from sunrise (Sahar) until sunset (Iftar). Considering the impacts of environment on physiological functions, we performed this study in order to examine the effects of Ramadan fasting on some blood parameters of healthy volunteers and hypertensive patients. According to the results, there were no significant changes in the weight, heart rate (HR), blood pressure (BP), serum total cholesterol and packed cell volume (PCV) of volunteers before and after fasting (P 0.05). Therefore, it can be concluded that hypertensive patients, while continuing their previous medications, can safely fast during the month of Ramadan.
An updated simulation of particle fluxes and cosmogenic nuclide production in the Earth's atmosphere

[1] Since the publication of our first paper devoted to this subject, we have extended our model, using new cosmic ray and nuclear data. Therefore, we revised particle fluxes in the atmosphere and used them in concert with experimental or evaluated cross sections to calculate the production rates of 3H, 7Be, 10Be, 14C, and 36Cl. The dependencies of these production rates on solar activity and geomagnetic field intensity were investigated in detail. Our simulations cover a whole range of these two parameters observed in the past. Comparison of the production rates calculated from two of the most frequently used primary galactic cosmic ray spectra showed weak dependence on the shape of the spectra. Alpha particles were included in the simulations for the first time, and we showed that the previously used scheme for estimation of alpha particle contribution to the total production rates is more complicated and latitude dependent. The production rates obtained agree well with most published experimental values.
Productivity of white lupin (Lupinus albus L.) as an effect of diversified farming systems

A one–factor field experiment with white lupin cv. Butan was conducted in the years 2011–2015 in Gorzyn (52°33’53 N, 15°53’42 E; Poland). The factor consisted of farming systems: low-input (LI), medium-input (MI) and high-input (conventional-CONV). The lowest weed density and biomass were found in CONV and the highest in LI. The weather conditions significantly influenced yielding. Each year the highest yield was found in CONV and significantly lowest in LI. On an average, the highest increase in the seed yield was obtained following increasing intensity of cultivation from LI to MI (20.3%). Farming systems did not influence the chemical composition of seeds. The highest protein yield was found in CONV (804 kg ha-1) and significantly lower – by about 6% in MI and about 19% in LI. The highest income and the lowest cost of production for 1 t of seeds and protein were recorded for LI.
The Gut Microbiota: Ecology and Function

The Gut Microbiota: Ecology and Function Benjamin P. Willing 1 and Janet K. Jansson 2 Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada V6T 1Z4. Department of Ecology, Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720. J.K. Jansson’s work is partially supported by the U.S. Department of Energy and LBNL under Contract No. DE- AC02-05CH11231.
Statistical properties of ionospheric stimulated electromagnetic emissions

We have analysed the statistical properties of the stimulated electromagnetic emissions (SEE) spectral features in the steady state, reached after a long period of continuous HF pumping of the ionosphere in experiments performed at the Sura ionospheric radio research facility in Russia. Us- ing a digital filter bank method, we have been able to anal- yse complex valued signals within narrow frequency bands. Each of the SEE spectral features are thereby separated into a number of narrow spectral components. Statistical tests were performed for all these spectral components and the distribu- tions of the spectral amplitudes and phases were evaluated. Also, a test for sinusoidal components was performed. These tests showed that all observed SEE features were indistin- guishable from coloured Gaussian noise. The test results ex- clude that the SEE features can be the result of a single iso- lated coherent process, but does not rule out that there could be many statistically independent parametric wave-wave pro- cesses taking place simultaneously at various parts of the HF-pumped ionosphere, as long as the superposition from all these is incoherent. Furthermore, from the test results, we cannot exclude the possibility that the waveforms of some, or all, of the SEE features may be chaotic.