Miracle-dz/UniFAR-FTUs huggingface dataset:
Proximate Composition and Glycaemic Index of Cookies from Corn Flour Mixed Black Soybean

The metabolic characteristics of type 2 diabetes subject are abnormally high concentration of glucose in blood. They need low glycaemic index food to control their bloods glucose. Meals from cereal and bean have important protein, vegetable oils, dietary fibre, and low starch to controlling it. The purpose of this research was to analyzed the proximate composition and glycaemic index of cookies from corn flour and black soybean flour. Proximate composition determined by AOAC methods. The glycaemic index data was measured from nine normal subject (± 23 years) that selected from agricultural student in Garut University. About 50 g glucose was consumed by subjects. Capillary blood samples were taken by glucometer in the fasting state and then at 15, 30, 45, 60, 90, and 120 minutes from the start consumption of glucose. After a week, subjects were consumed of cookies sample equivalent with 50 g glucose. Samples were analyzed for blood glucose concentration and incremental areas under blood glucose curves were calculated. The glycaemic index of cookies was calculated as the incremental area under curve (iAUC) of the cookies expressed as a percentage of the individual’s average incremental area under curve (iAUC) of the glucose. The results showed that the cooky contained moisture (3.79±0.07%), ash (1.07±0.03%), lipid (29.97±0.28%), protein (6.03±0.06%), crude fiber (3.13±0.38%), and carbohydrate (59.15±0.31%). The cookies have 40.00±17.95 glycaemic index and it was classified as low glycaemic food (less than 55). Furthermore, consuming the cookies could be control the blood glucose of subjects.
Introduction: Legal regimes under pandemic conditions: A comparative anthropology

As it has spread globally, the pathogen SARS-CoV-2 (known colloquially as the coronavirus) has already caused untold suffering, with more most certainly to come Yet as the virus afflicts, it has also encountered a range of human responses – from initial indifference and outright denial in parts of the Anglo-American West to society-wide mobilizations in much of the rest of the world In doing so, the virus has become a sort of diagnostic tool that can reveal a lot about any body politic that it happens to enter, something we attempt to leverage in this issue's forum through reflections from ethnographers working in both India (Dey) and the United States (Brinkworth et al , McGranahan)
Rapid Late Pleistocene climate change reconstructed from a lacustrine ostracod record in central Italy (Lake Trasimeno, Umbria)

This study presents, for the first time, a detailed quantitative reconstruction of winter (January) and summer (July) palaeotemperatures from the Late Pleistocene to Holocene transition in central Italy based on ostracod assemblages in an 8.59‐m‐long sediment core retrieved in Lake Trasimeno. Of 19 ostracod species recovered, 13 were calibrated according to their living temperature ranges, enabling us to reconstruct mean January and July temperature ranges using the mutual ostracod temperature range (MOTR) method. The occurrences of Cytheromorpha fuscata and Limnocythere suessenbornensis from 44 000 to 25 500 cal. a BP showed mean January temperatures at least 7 °C colder and mean July temperature at least 1 °C cooler in some intervals compared to present‐day temperatures. Comparison of the MOTR‐derived January minima curve with a Greenland oxygen isotope record (NGRIP) shows a remarkable correlation of warmer Greenland Interstadial and the colder Greenland Stadial events with clear peaks and troughs in the MOTR signal. These correlations were tested successfully by tuning the MOTR curve to the NGRIP record, resulting in an improved age‐depth model combining radiocarbon ages with MOTR tie points. The results demonstrate that a record of rapid climate change in the North Atlantic region is archived in lacustrine ostracod assemblages in central Italy.
The Effectiveness of School- Based in Reducing and Preventing Childhood Obesity in China

Research Aim: To describe thecomponents and effectiveness of school-focused interventions to reduce obesity among children in China. Background: The rise in global childhood obesity is a significant healthcare issue. Obesity and overweight are responsible for more than 3.4 million deaths around the world every year. The health risks associated with childhood obesity include cardiovascular diseases, type 2 diabetes, and many other breathing-related complications. Notably, childhood obesity is a major predictor of adult obesity and if obesity is not addressed during childhood, obese children become obese adults. Thus, there is a need to examine interventions that aim to prevent and reduce childhood obesity. Methods: The structured literature review (SLR) synthesized and analysed four randomised controlled trials(RCTs) of school-based interventions which took place in China. Besides, the review employed an array of criteria to select suitable studies for research. For instance, only sources, which were focused on school-based intervention and publishedfrom 2015 until2019, were eligible for inclusion. Furthermore, the review conducted its search from renowned journal-databases such as CENTRAL, CINAHL, and MEDLINE. Results: The SLR included four studies with a sample size of 23,029. All four studies concluded that the school-based interventions were effective in reducing the participants’ body mass index (BMI), reducing participants’body weight and increasing the participants’ knowledge of healthy lifestyle bahaviours and increasing levels of physical activities. The research further recorded a positive impact of the interventions on the children’s dietary bahaviours. However, only a few studies looked at sedentary lifestyle as an outcome, but the studies stated that there wasno significant effect of the interventions on children’s sedentary bahaviour. Conclusion: The SLR revealed that school-based interventions to reduce obesity in China were often successful in increasing physical activity, reducing BMI and weight, and increasing awareness of healthy lifestyle factors. However, the review was not conclusive in relation to waist circumference and the prevalence of sedentary behaviour as many studies did not report on these variables. In general, because there were few studies focusing on the area of school-based obesity intervention in China, further studies are needed to better understand how to address the problem and prevent it in the future.
The Development of Silicon for AI: Different Design Approaches

This paper provides a review of design approaches towards artificial intelligence (AI) System-on-Chip. AI algorithms have progressed over the past decades from perceptron-based neural network (NN) and neuro-fuzzy (NF) system to today’s deep neural network (DNN) and neuromorphic computing. Recent DNN hardware accelerators focus on energy-efficient integration of digital circuits to realize real-time DNN operation while neuromorphic processors deploy new memory technologies with analog computation for low power consumption. However, different design approaches can be applied to such processor implementation with their pros and cons. This paper reviews from the early processor designs for NN and NF in both mixed-mode and digital implementations to the recent DNN SoC designs that we have proposed for a decade. The former content deals with NN and NF processors used as a functional building block of a machine vision SoC, while the latter concentrates on integration of the whole DNN function. We also provide a discussion on the approaches, and provide perspective on future research directions.
Giant Clams (Bivalvia: Cardiidae: Tridacninae): A Comprehensive Update of Species and their Distribution, Current Threats and Conservation Status

1St. John’s Island National Marine Laboratory, c/o Tropical Marine Science Institute, National University of Singapore, 18 Kent Ridge Road, Singapore 119227, Singapore 2The Pacific Community (SPC), BPD5, 98800 Noumea, New Caledonia 3Changing Ocean Research Unit, Institute for the Oceans and Fisheries, The University of British Columbia, AERL, 2202 Main Mall, Vancouver, BC, Canada 4Aquasearch, 6–10 Elena Street, Nelly Bay, Magnetic Island, Queensland 4819, Australia 5Indo-Pacific Sea Farms, P.O. Box 1206, Kailua-Kona, HI 96745, Hawaii, USA 6UMR ENTROPIE Institut de Recherche pour le développement, Université de La Réunion, CNRS; Centre IRD de Noumea, BPA5, 98848 Noumea Cedex, New Caledonia 7UMR ENTROPIE Institut de Recherche pour le développement, Université de La Réunion, CNRS; Centre IRD de Tahiti, BP529, 98713 Papeete, Tahiti, French Polynesia 8Institute of Marine Science, University of Auckland, P. Bag 92019, Auckland 1142, New Zealand 9School of Biological Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia 10Marine Science Institute, University of the Philippines, Diliman, Velasquez Street, Quezon City 1101, Philippines 11Experimental Marine Ecology Laboratory, Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117557, Singapore *Corresponding authors: Mei Lin Neo e-mail: tmsnml@nus.edu. sg Peter A. Todd e-mail: dbspat@nus.edu. sg
Fluctuations and Entropy in The Energetics and Function of Protein Complexes

Conformational entropy is a potentially important thermodynamic parameter contributing to protein function. Quantitative measures of conformational entropy are necessary for an understanding of its role but have been difficult to obtain experimentally. We have recently introduced an empirical calibration method that utilizes the changes in conformational dynamics as a proxy for changes in conformational entropy. This approach raises several questions with regards to the microscopic origins of the measured conformational entropy as well as its general applicability. One of the goals in this work was to probe the microscopic origins of the link between conformational dynamics and conformational entropy. Using MD simulations, we find that the motions of methyl-bearing side chains are sufficiently coupled to that of other side chains and serve as excellently reporters of the overall side chain conformational entropy. We also propose a modified weighting scheme to project the change in NMR-measured methyl dynamics to conformational entropy. This approach has been extended to 36 different protein-ligand complexes each with different ligand types (small molecules, DNA/RNA, peptides and proteins) and binding affinities (10-4 to 10-14 M). There is excellent agreement between the NMR-measured conformational dynamics derived measure of conformational entropy and the total binding entropy, essentially postulating a 'Universal Entropy Meter'. This universal entropy meter can be utilized to measure the conformational entropy change for any protein-ligand interaction. The second major goal of this work is to understand the role played by conformational entropy in very high affinity interaction. A dominant view of very high affinity interactions involving proteins is that they are largely driven by both large favorable interactions at the interaction interface and by an increase in solvent entropy due to the creation of dry or solvent depleted interface. The role of conformational entropy, though admitted as a potentially favorable contribution, remains largely obscured by this view. Utilizing NMR measured conformational dynamics, protein conformational entropy was indeed found to play a pivotal role in achieving very high affinity interactions. In the barnase-barstar protein-protein complex (Kd = 10-14 M) and the histamine-binding protein bound to small molecule histamine (Kd = 2.5x10-9 M), large favorable changes in conformational entropy offset unfavorable entropic contributions from both solvent and rotationaltranslational contributions. Collectively, these results reveal that this mechanism involving modulation of protein conformational entropy changes to offset other entropic penalties could be a more prevalent paradigm for achieving high affinity interactions than previously anticipated. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Biochemistry & Molecular Biophysics This dissertation is available at ScholarlyCommons: http://repository.upenn. edu/edissertations/1327 First Advisor Joshua A. Wand
On the Analysis of New COVID-19 Cases in Pakistan Using an Exponentiated Version of the M Family of Distributions

This paper develops the exponentiated Mfamily of continuous distributions, aiming to provide new statistical models for data fitting purposes. It stands out from the other families, as it depends on two baseline distributions, with the use of ratio and power transforms in the definition of the main cumulative distribution function. Thanks to the joint action of the possibly different baseline distributions, flexible statistical models can be created, motivating a complete study in this regard. Thus, we discuss the theoretical properties of the new family, with emphasis on those of potential interest to the overall probability and statistics. Then, a new three-parameter lifetime distribution is derived, with the choices of the inverse exponential and exponential distributions as baselines. After pointing out the great flexibility of the related model, we apply it to analyze an actual dataset of current interest: the daily COVID-19 cases observed in Pakistan from 21 March to 29 May 2020 (inclusive). As notable results, we demonstrate that the proposed model is the best among the 15 top ranked models in the literature, including the inverse exponential and exponential models, several modern extensions of them depending on more parameters, and the “unexponentiated” version of the proposed model as well. As future perspectives, the proposed model can be of interest to analyze data on COVID-19 cases in other countries, for possible comparison studies.
3D Ultrastructure of the Cochlear Outer Hair Cell Lateral Wall Revealed By Electron Tomography

Outer hair cells in the mammalian cochlea display a unique type of voltage-induced mechanical movement, termed electromotility, which amplifies auditory signals and contributes to the sensitivity and frequency selectivity of mammalian hearing. Electromotility occurs in the outer hair cell (OHC) lateral wall, and it is not fully understood how the supramolecular architecture of the lateral wall enables this unique form of cellular motility. Employing electron tomography of high-pressure frozen and freeze-substituted OHCs, we visualized the 3D structure and organization of the membrane and cytoskeletal components of the OHC lateral wall. The subsurface cisterna (SSC) is a highly prominent feature, and we report that the SSC membranes and lumen possess hexagonally ordered arrays of particles that endow the SSC with a previously unrealized anisotropic structural rigidity. We also find the SSC is tightly connected to adjacent actin filaments by short filamentous protein connections spaced at regular intervals. Pillar proteins that join the plasma membrane to the cytoskeleton appear as variable structures considerably thinner than actin filaments and significantly more flexible than actin-SSC links. The structurally rich organization and rigidity of the SSC coupled with apparently weaker mechanical connections between the plasma membrane and cytoskeleton reveal that the membrane-cytoskeletal architecture of the OHC lateral wall is more complex than previously appreciated. These observations are important for our understanding of OHC mechanics and need to be considered in computational models of OHC electromotility that incorporate subcellular features.
Buffer Overflow Vulnerability Detection Based on Unsafe Function Invocation

Buffer overflow vulnerabilities are widespread in software programs and pose a serious security threat. In order to effectively mitigate buffer vulnerabilities, we proposed a buffer overflow vulnerability detection technique based on unsafe function invocation. By extracting the typical characteristics of the insecure function call operation, a vulnerability code characteristic model is constructed, and the model is used as a guide to use the data flow analysis method for vulnerability detection. Experimental results show that our method can effectively detect buffer overflow problems caused by unsafe function invocation in programs.
A New Text Sentiment Analysis Method Based on Chinese Morphological Features and HowNet

Traditional deep learning methods have two problems when using vectorized words as input. One is that they only consider the overall semantic information of the vocabulary, but ignore the morphological features of the Chinese vocabulary and the prior knowledge of the Chinese external knowledge base. Second, the word vector corresponding to each word will be limited to a single word vector training model. Aiming at these problems, we propose a double-channel convolutional neural network model based on Chinese morphological features and HowNet. First, the cw2vec model and the SAT model (Sememe Attention over Target Model) are used to train the word vectors. Second, the two different word vectors are used as the input of the two channels of the model. Finally, the convolutional neural network are used to extract the characteristics of the two channels to complete the sentiment analysis task. The comparative experimental results on the two data sets show that the proposed model achieves significantly better classification performance than traditional sentiment analysis methods.
Biology of restriction-modification systems at the single-cell and population level

Restriction-modification (RM) represents the simplest and possibly the most widespread mechanism of self/non-self discrimination in nature. In order to provide bacteria with immunity against bacteriophages and other parasitic genetic elements, RM systems rely on a balance between two enzymes: the restriction enzyme, which cleaves non-self DNA at specific restriction sites, and the modification enzyme, which tags the host’s DNA as self and thus protects it from cleavage. In this thesis, I use population and single-cell level experiments in combination with mathematical modeling to study different aspects of the interplay between RM systems, bacteria and bacteriophages. First, I analyze how mutations in phage restriction sites affect the probability of phage escape – an inherently stochastic process, during which phages accidently get modified instead of restricted. Next, I use single-cell experiments to show that RM systems can, with a low probability, attack the genome of their bacterial host and that this primitive form of autoimmunity leads to a tradeoff between the evolutionary cost and benefit of RM systems. Finally, I investigate the nature of interactions between bacteria, RM systems and temperate bacteriophages to find that, as a consequence of phage escape and its impact on population dynamics, RM systems can promote acquisition of symbiotic bacteriophages, rather than limit it. The results presented here uncover new fundamental biological properties of RM systems and highlight their importance in the ecology and evolution of bacteria, bacteriophages and their interactions.
Data mining of DNA sequences submitted by Peruvian institutions to public genetic databases

Genetic diversity is an important component of biodiversity, and it is crucial for current efforts to protect and sustainably manage several organisms and habitats. As far as we know, there is only one work describing Peruvian genetic information stored in public databases. We aimed to update this previous work searching in four public databases that stored digital sequence information: Nucleotide, BioProject, PATRIC, BOLD. With this information, we comment on the contribution of Peruvian institutions during recent years. In Nucleotide, the largest database, Bacteria are the most sequenced organisms by Peruvian institutions (70.60%), pathogenic bacteria such as Pasteurella multocida, Neisseria meningitidis, and Vibrio parahaemolyticus were the most abundant. We found no sequence records from the Archaea domain. In BioProject, the most common sequence belongs to Salmonella enterica subsp. enterica serovar Infantis. In PATRIC, a database of pathogenic agents, Mycobacterium tuberculosis and Yersinia pestis had the highest number of entries. Finally, in BOLD, an exclusively Eukaryotic database, Chordata (Aves and Actinopterygii), Angiospermae, and Arthropoda (Insecta, and Arachnida) were the most frequent records. Our results would indicate research preferences of Peruvian institutions, focusing on infectious diseases and some Eukaryotic phyla. Although there has been a significant increase of DNA information submitted by Peruvian institutions since the last report, the genetic diversity reflected in these databases remains inconsistent with the diversity in the country. More efforts must be made to obtain genetic information from more underestimated taxonomic groups and to promote more genetic research in regional Peruvian institutions.
Traffic issues categorization of Indian Cities using Word2Vec by Social Media Data

In traditional ways, traffic related and road and transport related issued are highlighted and detected by mostly physical place visit in most of the world. New research area aims to use Social Media data and Classification techniques to detect Road and Transport Related issues. As current work has been done using Twitter data using Word2Vec classification algorithm to detect various issues at major cities of India. During our research work we plan to use Social Media Data and News Data with Word2Vec classification algorithm. We also intend to include tweets from local languages . We also planned to apply Word2Vec classification for Multi-Class Classification Problem and NLP for feature extraction. We have used cosine similarity function to find similarity among tweets and after find similarity we have obtained result from tweets into positive, negative, neutral with the help of semantic analysis.
The Candida albicans Hsp90 co-chaperone complex regulates aspects of virulence

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Mappings with finite length distortion and Riemann surfaces

ISSN 1025-6415. Допов. Нац. акад. наук Укр. 2020. No 6: 7—14 Ц и т у в а н н я: Ryazanov V.I. , Volkov S.V. Mappings with finite length distortion and Riemann surfaces. Допов. Нац. акад. наук Укр. 2020. No 6. С. 7—14. https://doi.org/10.15407/dopovidi2020.06. 007
Modified Analog-to-Information Conversion and Reconstruction for Approximately Sparse Signal

: The framework for analog-to-information conversion (AIC) as an alternative to conventional ADC is inspired by the recent theory of Compressed Sensing (CS). Both of them require that the input signal has a sparse representation in some domain. But mostly, the signals in our daily lives are approximately sparse ones. The modiﬁed analog-to-information conversion (MAIC) and a new approximately sparse signal reconstruction algorithm are proposed. The contour of the input real-time streaming signal is pre-extracted and the details are compressed, and then adaptive piece-wise basis pursuit (APBP) algorithm is used to reconstruct the input precisely. The validity of the MAIC framework and APBP algorithm is demonstrated. As is shown in the simulation, the mean square error of APBP reconstruction in the MAIC framework is of the order of about 10 − 14