Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting specific impulse distributions for spherical explosives in the extreme near-field using a Gaussian function

Accurate quantification of the blast load arising from detonation of a high explosive has applications in transport security, infrastructure assessment and defence. In order to design efficient and safe protective systems in such aggressive environments, it is of critical importance to understand the magnitude and distribution of loading on a structural component located close to an explosive charge. In particular, peak specific impulse is the primary parameter that governs structural deformation under short-duration loading. Within this so-called extreme near-field region, existing semi-empirical methods are known to be inaccurate, and high-fidelity numerical schemes are generally hampered by a lack of available experimental validation data. As such, the blast protection community is not currently equipped with a satisfactory fast-running tool for load prediction in the near-field. In this article, a validated computational model is used to develop a suite of numerical near-field blast load distributions, which are shown to follow a similar normalised shape. This forms the basis of the data-driven predictive model developed herein: a Gaussian function is fit to the normalised loading distributions, and a power law is used to calculate the magnitude of the curve according to established scaling laws. The predictive method is rigorously assessed against the existing numerical dataset, and is validated against new test models and available experimental data. High levels of agreement are demonstrated throughout, with typical variations of <5% between experiment/model and prediction. The new approach presented in this article allows the analyst to rapidly compute the distribution of specific impulse across the loaded face of a wide range of target sizes and near-field scaled distances and provides a benchmark for data-driven modelling approaches to capture blast loading phenomena in more complex scenarios.
An Analytical Approach to Predict Employability Status of Students

One of the major concerns of the students after graduation is the job opportunities offered to them. Not only students, but also the universities are inclined towards maximizing the job offers for their students through campus recruitment drives. Against this background, the scope of this study is to gauge the performance of top four known classification techniques of data mining, which are, Decision tree, Random forest, Naive Bayes & KNN. These machine learning algorithms are applied on students’ data, collected from the university database of Manipal University Jaipur and student models are created which will predict the employability status of students in future and discover factors which will significantly contribute to their employability. After applying and studying the ac- curacies of these algorithms, we have found that Random forest behaves better than the rest of the algorithms with 89% accuracy.
Gender-affirmation surgery and bariatric surgery in transgender individuals in The Netherlands: Considerations, surgical techniques and outcomes

Abstract Introduction The number of transgender individuals seeking medical and surgical care has increased over the last years. Within the transgender population overweight and obesity is more frequently observed when compared to the general population. Little is known on the prevalence of bariatric surgery in the transgender population and the effects on the surgical gender transition path of the individual transgender with overweight or obesity. Material and methods All transgender individuals who underwent gender-affirming surgery (GAS) between 1980 and 2020 were retrospectively identified from our hospital registry. Those with a history of bariatric surgery were selected. A retrospective chart study was conducted, recording gender identity, bariatric surgery specifications, gender surgery specifications, complications, reoperations and clinical follow-up time. Results A total of 15 transgender individuals (11 transgender men, 4 transgender women) who underwent bariatric surgery were identified. All individuals underwent bariatric surgery before any GAS procedure, except for one transgender man. At the first GAS procedure, all individuals experienced significant weight loss when compared to their weight at bariatric surgery (mean 13.1 ± 3.8 BMI points lost for transgender men, mean BMI points lost 14.3 ± 2.8 for transgender women, p < 0.01). Obesity was still frequently prevalent in transgender men after bariatric surgery. All included transgender men underwent mastectomy via the double incision with free nipple grafting technique. Only one transgender man underwent genital GAS. All transgender women underwent penile-inversion vaginoplasty, one in combination with prosthesis-based augmentation mammoplasty. Conclusion Surgical gender transition is possible after massive weight loss after bariatric surgery. Specific surgical subtechniques will be more prevalent in this population.
Prediction of Chemical Oxygen Demand from The Chemical Composition of Wastewater by Artificial Neural Networks

In our era, many technical applications are being used. Artificial Neural Networks (ANNs) as one of the artificial intelligence tools have emerged to learn and discover a model of dynamic nonlinear. In this study, six input parameters were taken to predict the value of the Chemical Oxygen Demand (COD) in the wastewater before and after the treatment at the North Gas Company/Kirkuk, by using the standard back propagation algorithm. The network was trained with the 150 data collected from the quality indices of the untreated and treated wastewater, such as total chloride ions Cl-, nitrate ions NO3 −, phosphate ions PO4 −3, sulfate ions SO4 −2, ammonia NH3, Biochemical Oxygen Demand (BOD5) to predict one element, that is the COD. After properly training of the neural network, it was tested by using the test data, and the best results were selected by the consideration of the mean square error and the regression coefficient, where the best result appeared before wastewater treatment is 0.98235 and the best result after wastewater treatment is 0.99999. The findings of this study suggest that artificial neural networks are accurate and effective tools for predicting the COD values of treated wastewater.
Bimorph vs stacked actuator deformable mirror for laser beam focusing through a moderately scattering medium

Bimorph and stacked actuator deformable mirrors were used to increase the efficiency of focusing of partially coherent laser radiation propagated through the scattering suspension that was equivalent to the middle-density fog layer with the length ranging from 300–500 meters up to 5 kilometers. We used Shack-Hartmann sensor to measure the averaged wavefront distortions and CCD camera to estimate the intensity distribution of the focal spot in the far-field. Numerical and experimental investigations of focusing improvement demonstrated that it is possible to increase the peak intensity of the focal spot by more than 60 %.
Control mechanisms and role performance: The moderating effects of social interaction

ABSTRACTS In contrast to previous studies, which view output and process control as having only positive or only negative effects, this study investigates nonlinear relationships between output and process control and role performance as well as the moderating effects of social interaction on the above relationships. Results from a sample of 206 Chinese buyer-supplier relationships demonstrate that output and process controls have different curvilinear effects on role performance. Specifically, output control has an inverted U-shaped effect, whereas process control has a U-shaped effect. Social interaction weakens the effect of output control on role performance, but strengthens the effect of process control on role performance. These findings demonstrate previous conflicting arguments on the role of output and process control in coordinating channel relationships and enlarge the understanding on control mechanisms by examining their role in improving role performance, and also provide some practical implications for channel members.
A Review on the Processing Technologies for Corrosion Resistant Thermoelectric Oxide Coatings

Oxide coatings are corrosion resistant at elevated temperatures. They also show intensive phonon scattering and strong quantum confinement behavior. Such features allow them to be used as new materials for thermoelectric energy conversion and temperature measurement in harsh environments. This paper provides an overview on processing thermoelectric oxide coatings via various technologies. The first part deals with the thermoelectricity of materials. A comparison on the thermoelectric behavior between oxides and other materials will be made to show the advantages of oxide materials. In the second part of the paper, various processing technologies for thermoelectric metal oxide coatings in forms of thin film, superlattice, and nanograin powder will be presented. Vapor deposition, liquid phase deposition, nanocasting, solid state approach, and energy beam techniques will be described. The structure and thermoelectric property of the processed metal oxide coatings will be discussed. In addition, the device concept and applications of oxide coatings for thermoelectric energy conversion and temperature sensing will be mentioned. Perspectives for future research will be provided as well.
Critical Appraisal of Studies Conducted in the Department of Periodontics, Mashhad School of Dentistry, in the Last Twenty Years (1994-2014)

Critical appraisal of research studies is an essential process in quality assessments and development, in which various aspects of a subject are carefully analyzed. In recent decades, many articles have been published in medical journals especially in dental field, without being officially criticized. Citing results of these epidemiological studies requires proper validation. The validation is performed through ‘critical appraisal’ according to standard criteria and checklists. In this paper, 81 studies conducted between 1994 and 2014 in periodontics field in dentistry were divided into five categories: observational studies, diagnostic, clinical, animal, and meta-analysis, and reviewed by STROBE, STARD, CONSORT, ARRIVE, PRISMA Checklists. In most studies, participants' characteristics and inclusion and exclusion criteria were mentioned. In most studies, random sampling was not performed without bias. It is hoped that in future studies, researchers will use standard checklists from the initial stages of the study to obtain valid and scientific results.
Essential Oil Compositions and Bioactivities of the Various Parts of Cinnamomum camphora Sieb. var. linaloolifera Fujuta

In this study, we used hydrodistillation and headspace GC methods to separate essential oils from the leaves, flowers and twigs of a ”linalool tree” (Cinnamomum camphora Sieb. var. linaloolifera Fujuta) and establish their yields and compositions. Furthermore, the antioxidative and antifungal activities of the oils were evaluated. A total of 68, 77 and 83 compounds were identified respectively from the leaf, flower and twig oils of the tree by the hydrodistillation method, and their yields were 3.94±0.06, 2.77±0.12 and 0.59±0.04ml/100g of the oven-dried (o. d.) materials, respectively. The headspace-gas chromatography (HS-GC) method, on the other hand, generated 49, 59 and 65 identified compounds respectively from the leaves, flowers, and twigs of the tree. Yields of essential oil were determined using the multiple headspace extraction (MHE) method and found to be 3.93±0.11, 2.72±0.10 and 0.61±0.03ml/100g of o. d. materials for the leaves, flowers and twigs, respectively. The main compounds based on the 2 methods were similar and those in the leaves and flowers were linalool, and in twigs were linalool, camphor etc. Twig oils showed the highest antioxidant activity, with an IC50 of merely 104μg/ml. As for the antifungal activities, the leaf oil showed the best activity. All 3 oils had excellent capability in suppression wood decaying fungi. Therefore, in addition to being raw materials for producing high-grade fragrance agents, these oils are also applicable to the antioxidant and antifungal purposes and exhibit the multipurpose potential of expanded essential oil applications.
Rethinking Diabetes: Entanglements with Trauma, Poverty, and HIV. Emily Mendenhall. Ithaca and London: Cornell University Press, 2019, 240 pp. $28.95, paper. ISBN 9781501738432.

Using ethnographic fieldwork from four distinct settings across the globe, Mendenhall finds that diabetes is produced by dynamics that are more complicated than can be understood by merely locating individuals in a context A common trope for understanding the global diabetes "epidemic" is that diabetes is produced by processed food diets and sedentary lifestyles that have accompanied "modernization " [Extracted from the article] Copyright of Journal of Anthropological Research is the property of The University of New Mexico and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all Abstracts )
The issue of entrepreneurship as a political gimmick or sustainability? (A study on 2019 presidential election campaign)

Entrepreneurship for sustainable development is a multilevel phenomenon connecting social, environmental, and economic dimensions between entrepreneurial processes, market transformations. Sandiaga viewed entrepreneurship as an opportunity to draw voters’ sympathy through his social media narration during the 2019 Presidential Election. The present study aimed to explore the form of Uno’s entrepreneurship narration in Instagram related to SDGs and identify the narration that influenced young people during the campaign period. The thematic content analysis, was applied. This study’s data was the documentation of the narrative posts presented in the @sandiuno Instagram account during the campaign period starting from 23 September - 14 April 2019. Of all the posts on that date will be selected from the highest number of comments, after being listed, the unit of analysis in this study is March 18 - April 13, 2019. The study’s findings revealed that Uno’s narration focused on building hopes and motivation to draw millennial’s interest in entrepreneurship. Unfortunately, the narrated entrepreneurship does not depict a holistic description of the entrepreneurship process. It ignored the supporting elements of entrepreneurship, such as capital, market strategy, and strategy to survive the competition. Besides, it neglects the potential risk and does not highlight the sustainability of entrepreneurship.
Interactions between Water Vapor, Potential Vorticity, and Vertical Wind Shear in Quasi-Geostrophic Motions: Implications for Rotational Tropical Motion Systems

A linear two-layer model is used to elucidate the role of prognostic moisture on quasigeostrophic (QG) motions in the presence of a mean thermal wind (). Solutions to the basic equations reveal two instabilities that can explain the growth of moist QG systems. The well-documented baroclinic instability is characterized by growth at the synoptic scale (horizontal scale of ~1000 km) and systems that grow from this instability tilt against the shear. Moisture–vortex instability—an instability that occurs when moisture and lower-tropospheric vorticity exhibit an in-phase component—exists only when moisture is prognostic. The instability is also strongest at the synoptic scale, but systems that grow from it exhibit a vertically stacked structure. When moisture is prognostic and is easterly, baroclinic instability exhibits a pronounced weakening while moisture vortex instability is amplified. The strengthening of moisture–vortex instability at the expense of baroclinic instability is due to the baroclinic () component of the lower-tropospheric flow. In westward-propagating systems, lower-tropospheric westerlies associated with an easterly advect anomalous moisture and the associated convection toward the low-level vortex. The advected convection causes the vertical structure of the wave to shift away from one that favors baroclinic instability to one that favors moisture–vortex instability. On the other hand, a westerly reinforces the phasing between moisture and vorticity necessary for baroclinic instability to occur. Based on these results, it is hypothesized that moisture–vortex instability is an important instability in humid regions of easterly such as the South Asian and West African monsoons.
Hydrological Properties of a Clay Loam Soil as Affected by Biochar Application in a Pot Experiment

Improving soil-water relations by amending soil with biochar might play a significant role in increasing water availability for agricultural crops as well as decreasing water loss through drainage or runoff. While the effects of biochar on the hydrological properties on coarse-textured soils are generally positive and well-documented in the literature, studies on biochar effects on fine-textured soils are rather scarce and even contradictory. Therefore, the aim of this paper was to investigate the impact of biochar on the bulk density, water retention curve (together with several water capacitive indicators) and water infiltration rate in a clay loam soil. A pot experiment was carried out under lab conditions in which biochar was mixed with soil at rates of 0 (B0 or control), 2, 4, 6, 8 and 10% dw (B2, B4, B6, B8 and B10, respectively). Water retention of soil–biochar mixtures at different matrix potentials was determined using a pressure plate apparatus. From these measurements, a series of capacitive indicators was derived and the fitting of the van Genuchten model was also performed. Water infiltration into soil–biochar mixtures was measured by means of a mini-disk infiltrometer and the obtained data were analyzed both directly and by fitting the Philip’s model. Biochar significantly affected the considered soil properties. As the biochar rate increased, the bulk density decreased and water retention increased (B6, B8 and B10 > B2, B4 and B0), while the infiltration rate decreased (B0 > B2, B4, B6, B8 and B10). Although the experiment was performed on sieved and repacked soil samples under lab conditions, the results confirmed that biochar has the potential to increase plant-available water, while possibly reducing drainage water in a clay loam soil by lowering the infiltration rate.
Islands of runs of homozygosity indicate selection signatures in Ovis aries 6 (OAR6) of French dairy sheep

Graphical Abstract Summary: The occurrence of runs of homozygosity (ROH) is not randomly distributed across the genome, and ROH islands across many animals may be the result of selective pressure. The objective of this study was to demonstrate that the presence of ROH islands may be indicative of selection signatures in French dairy sheep breeds and subpopulations. One island of ROH was detected on OAR6 in the same genomic position across animals (between 30 and 40 Mb). Global Wright's differentiation coefficients (FST) for 2 SNP (OAR6_41583796.1 and OAR6_41709987.1) within this ROH island were high (0.67–0.68). ROH and single SNP FST analyses agreed that selection signatures exist around both SNP that were located near the NCAPG and LCORL genes.
Calibration for Instrument Argumentation Skills on the Subject of Fluid Statics Using Item Response Theory

This study aims to calibrate the instrument of argumentation skills on the subject of Fluid Statics using item response theory (IRT). The blueprint instrument developed based on the aspects and sub-aspects of argumentation skills, totaling 20 items. The scoring uses the Partial Credit Model (PCM) principle in 4 categories. Subjects involved in the study were 206 undergraduate students at two different universities. The validation of the instrument using expert judgment techniques, which consisted of linguists, physicists, and educational measurement experts. Instrument calibration for argumentation skills is carried out by (1) analysis of item fit with PCM by testing goodness of fit items, (2) testing prerequisite analysis, (3) reliability, (4) difficulty level, and (5) Standard Error of Measurement (SEM). The test developed is valid with Aiken V index values in the range 0.93 to 1. The analysis of IRT assumptions uses two parameters, the adequacy test of the sample and the factor analysis. The Chi-Square value in the Bartlett test is 2202.67 with df 190, and a p-value value (Sig.) <0.05 indicates that the sample size used has met the unidimensional requirements. The instrument developed has met the criteria for scoring the Polytomus items, based on a) the MNSQ INFIT value is in the range of 0.70 to 1.30, and b) the difficulty index test is in the range -2.00 <b <2.00. The results of the reliability estimate on the test equipment obtained a reliability value of 0.86, which means that the reliability of the test is in the high category. The graph of the information function and SEM converge on the ability scales of -2.8 and +1.5, meaning that the skills test kit argues it is suitable for testees in the low to moderate ability range.
Multi Node Based Smart Monitoring System with Motor Dry Run Avoidance for Sustainable Agriculture

Food is the major source for the existence of the mankind. In order to meet the food requirements for the ever increasing population, the quantity of the food production has to be increased maintaining the quality standards. Agriculture is one such major sector which provides the food for mankind. It not only provides food but also supplies raw materials for industries. Implementation of advanced technologies such as Internet of Things in agriculture helps in improving the production with limited resources. The key parameter for the sustainable agriculture is moisture content available for the crop from the soil. This can be supplied efficiently by controlling the irrigation process. In this system an intelligent agriculture monitoring system with multiple wireless monitoring sensor nodes are used at different locations to monitor the parameters such as temperature, moisture content in the soil, humidity and rainfall. The data from the various sensors is aggregated at each node and transmitted to the coordinator station using long range transceiver. The data received at the coordinator station is subjected to a rule based decision making process to efficiently control the irrigation process. Also motor protection against the dry run was implemented, which not only protects the motor from break down but also avoids the unwanted power consumption. All the live data is in turn uploaded to the cloud so that the user can have a track of the current status of his farm at any time.
A smart near-infrared fluorescent probe for H2O2 in alkaline environment and H2O2 imaging in vitro and in vivo

Development of fluorescent probes for selectively detecting two or more events simultaneously is imperative for further application in bio-detecting area. Recently, an intelligent fluorescent probe based on Changsha ( CS NIR ) dye and arylboronic acid ( CSBOH ) that can selectively detect H 2 O 2 in alkaline environment was reported. The probe can detect both H 2 O 2 and pH change simultaneously with different fluorescent signal changes, which will be more useful in the H 2 O 2 detection in living organisms. CSBOH exhibited remarkably different fluorescence changes at 650 nm and 720 nm in the presence of H 2 O 2 in different pH buffers when excited at 560 and 670 nm, respectively. The cell experiments demonstrated that CSBOH can image endogenously generated H 2 O 2 in Macrophages and A431 cells. CSBOH was also used to image H 2 O 2 in living animals successfully.