Miracle-dz/UniFAR-FTUs huggingface dataset:
New Motion Estimation Algorithms and its VLSI Architectures for Real Time High Definition Video Coding

Nowadays, a vast number of applications use digital videos. Usually, these applications need to focus on performance for real time at 30 frames per second, which is necessary to show sense of continuity. With this increase in the number of applications, the video quality is also been increasing, which makes high definition videos more common. High definition videos need a lot of storage space and also a high bandwidth to be transmitted. These facts contribute to increase the effort in video coding research, and the development of new video coding standards. Current video coders, as H.264/AVC [1], for example, divide the coding process in many steps. The main steps of a current video coder are: intra frame prediction, inter frame prediction, transforms and entropy encoding. The inter frame prediction is explored by the Motion Estimation (ME) and is the focus of this work. ME represents 80% of the total computational complexity of current video coders [2]. The ME must find the best matching in the reference frames for each block of the current frame, defining a motion vector indicating where the best matching was found. A search algorithm defines how the search is done and a similarity criterion is used to compare the candidate blocks. The search for best vectors is known to be very expensive in terms of calculations and, consequentially, in terms of processing time. The Full Search (FS) [3] algorithm must explore all possibilities in a given search area, which implies in a very high computational cost, especially for high resolution videos, which requires the use of larger search areas. Based on this fact, it is important to explore new solutions, which bring a good tradeoff between objective quality, measured in Peak-to-Signal Noise Ratio (PSNR), and computational cost. There are many fast search algorithms in scientific literature. These algorithms deal with this complexity at different levels of impact in objective quality (PSNR). Exploring characteristic of locality among temporal correlated blocks allows these algorithms to achieve good results in terms of numbers of calculations and also allows achieving high video quality when low resolution videos are considered. However, these algorithms assume that the error function decreases monotonically on the surface of the frame, in order to speed up the algorithm. This assumption does not hold true sometimes, and the search might be trapped into a local minima, especially in high definition videos. ABSTRACT
Potential Health Benefits of Conjugated Linoleic Acid: An Important Functional Dairy Ingredient

Conjugated linoleic acid (CLA) refers to a class of positional and geometrical isomers of linoleic acid (cis-9, cis-12 octadecadienoic acid) having conjugate double bond system. CLA are synthesized in rumen of the ruminants by biohydrogenation of dietary fatty acids; and thus, can be obtained from dairy products as well as from the meat of sheep, lamb and other ruminants. Among the several isomers, c9, t11-CLA isomer is the most biologically active form and accounts approximately 80% of total isomers. A number of clinical and epidemiological studies have demonstrated the role of CLA as anti-atherogenic, anti-inflammatory, anti-oxidative, anticarcinogenic, etc. Several researchers have suggested the positive association of CLA in weight management, hypercholesterolemia, immunomodulatory functions, and improved bone metabolism.
Two-dimensional first-order phase transition as signature change event in contact statistical manifolds with Finsler metric

In this work we propose a phase transition model associated with the metric–signature–change events in its pseudo-Finsler–Langmuir configuration space. We prove that the change of signature of the contact statistical manifold endowed with a Langmuir–Finsler metric occurs, and that this event corresponds to the first-order phase transition in the Langmuir monolayer under compression. We determine the Cartan tensor and the nonlinear Barthel connection, which provide a tool to estimate how far is the Finsler model from the pseudo-Euclidean one, and to construct the Finsler adapted frames for the module of sections of the tangent bundle. As well, the Berwald curvature of the Finsler space is explicitly determined and it is shown that it vanishes everywhere except the regions of anomaly which correspond to the phase transition. M.S.C. 2010: 53B40, 53C60.
Effects of Industrial and Agricultural Wastes on Mud Blocks Using Geopolymer

For this research, the red soil sample was drawn, and a steady percentage of the geopolymer was used along with distinct proportions of stabilizers such as fly ash, groundnut shell ash, bagasse ash, and GGBFS. Geopolymer was used in the manufacture of stabilized mud blocks as a binding agent. The geopolymer solution’s effects on mud block strength have been researched. The effects of industrial by-products and waste such as fly ash, groundnut shell ash, bagasse ash, and GGBFS were also explored with the geopolymer to stabilize the mud blocks.
Potential roles of extracellular vesicles in the pathophysiology, diagnosis, and treatment of autoimmune diseases

Since extracellular vesicles (EVs) were discovered in 1983 in sheep reticulocytes samples, they have gradually attracted scientific attention and become a topic of great interest in the life sciences field. EVs are small membrane particles, released by virtually every cell that carries a variety of functional molecules. Their main function is to deliver messages to the surrounding area in both physiological and pathological conditions. Initially, they were thought to be either cell debris, signs of cell death, or unspecific structures. However, accumulating evidence support a theory that EVs are a universal mechanism of communication. Thanks to their biological characteristics and functions, EVs are likely to represent a promising strategy for obtaining pathogen information, identifying therapeutic targets and selecting specific biomarkers for a variety of diseases, such as autoimmune diseases. In this review, we provide a brief overview of recent progress in the study of the biology and functions of EVs. We also discuss their roles in diagnosis and therapy, with particular emphasis on autoimmune diseases.
Cancer Classification using Gene Expression Data with Deep Learning

Technological advances in DNA sequencing technologies allow sequencing the human genome for a low cost and with in a reasonable time span. This advance conduces to a huge increase in available genomic data, enabling the establishment of large-scale sequencing data projects. Producing genomic datasets, which describe genomic information in particular, we concentrate on our attention on gene expression datasets which describe healthy and tumoral cells for various cancer types. The purpose of this thesis is to apply deep learning to classification of tumors based on gene expression. Two different Deep Learning approaches for analyzing the genomic data. First one is to create a feed-forward network (FFN) with supervised learning, second one is using ladder network with semi-supervised learning [42] . Main purpose of both approaches is to perform binary classification, cancerous or healthy as the outcome, over the Cancer Genome Atlas (TCGA) database.Two cancer types selected from TCGA. Breast cancer is selected because it has the highest available amount of sample in all cancer types in TCGA. The reason for kidney cancer to be selected is because, it has the one of the highest mortality rate among rest. Moreover, three feature extraction method, PCA, ANOVA and random forests, employed to preprocess the selected datasets. Experiments show that, FFN reaches the acceptable accuracy rate but fails to reach a stabilization. On the other hand, ladder network, outperforms the FFN in both accuracy and stabilization meaning. Effects of feature extraction method shows us that, main goal as accuracy is reached by PCA & ladder network combination, main goal as performance is reached by ANOVA & ladder network combination.
Strategic Exits in Secondary Venture Capital Markets

Abstract The market for secondary venture capital transactions provides a way for investors to obtain liquidity if the investee start-up corporation has not yet reached sufficient maturity for an IPO. It also creates divestment opportunities for badly performing ventures that investors would rather abandon. We analyze the way in which the opportunistic behavior and liquidity constraints of venture capital funds channel deal flow into the secondary venture capital market. Such opportunistic behavior leads to the strategic exit of seed financing venture capitalists. These exits enlarge investors' opportunity set of strategies and therefore affect the deal terms with entrepreneurs. In this paper, we show that two contracts are possible in a world with financially constrained venture capital investors, staged investments, and premature divestment opportunities. Both contracts have their disadvantages. With the first, the venture capitalist will never liquidate a project, even if it is a lemon, but will instead engage in a secondary transaction. With the second contract, although lemons will be systematically abandoned, high-quality ventures may also be liquidated. Entrepreneurs need to consider these effects when aiming to maximize their benefits and must trade off the contract parameters accordingly. Our model provides guidance to entrepreneurs in this respect, helps to explain deal flow into the secondary venture capital market, and offers several empirical predictions.
An Enhanced Ant Bee Colony Based Feature Selection method with Support Vector Machine for Heart Disease Prediction

Machine Learning presents tools, techniques, and methods that can assistresolvinganalytic and predictive problems in a variety of medical areas. Machine Learning is also being used for data analysis, such as detection of regularities in the data by correctly dealing with damaged data, considerate of incessant data used in the Intensive Care Unit, and elegantdisturbing resulting in capable and efficient monitoring. It is argue that the successful implementation of Machine learningmethods can support the addition of computer-based schemes in the healthcare environment providing opening to ease and develop the work of medical experts and eventually to expand the efficiency and value of medical care.Unnecessary features contribute to the incorrect classification of the Heart disease. So, eliminating the redundant features reduces the size of the data and computation complexity. Identifying a best feature subset for winning classification is a non-trivial job. This needsacomplete search over the example space of the Heart disease dataset. The important objective of this work is to apply a Swarm intelligence based Artificial Bee Colony (ABC) algorithm is used to discover the best features in the Heart diseaseclassification. This studycontains the data mining classification of heart disease dataset using data mining Support Vector Machinealgorithm (SVM). The Heart disease data results show that SVMcan be successfully used for medical data set namely heart disease diagnosing. The algorithm of efficient diagnosis and the advantages of data preparation on machine learning basedroutine medical diagnosis scheme are recommended by the outcomes.
In silico Screening of Protein Rv3228 to have a Vision towards Survival and Pathogenesis of Mycobacterium tuberculosis H37Rv

Tuberculosis has appeared as a main world health problem with almost 1/3rd of the world society today infected with causative pathogen Mycobacterium tuberculosis (M. tuberculosis). M. tuberculosis is a grampositive bacterium makes so many difficulties in its abolition totally. Rv3228 is a conserved hypothetical gene of M. tuberculosis. Rv3228 is an expected GTP/ATP binding protein. It also shows metal ion binding or GTPase activity. GTP/ATPs are energy-rich molecules that facilitate binding of respective protein factor either to ribosomes or to the tRNA. This manuscript considered some of the valuable aspects of Rv3228 protein being the function as unknown. The main visions of this study include retrieval of protein sequence database, multiple sequence alignment, string interaction study, sub-cellular localization, ligand binding prediction, B-cell and T-cell epitopes prediction, structure-based function prediction by COFACTOR and VICMpred. VICMpred predicts that this gene is a virulence factor. Ab-Inito modelling by RAPTOR X and validates by RAMPAGE, ERRAT, and VERIFY3D, mutation analysis by MAESTRO WEB SERVER. This study will be helpful in the development of new drugs and the treatment of tuberculosis disease.
Geographical trajectories of refugees in Sweden

Many countries actively seek to disperse refugees to counteract residential segregation or/and take measures to attract and retain international migrants in smaller communities to mitigate or reverse population decline. This study explores the regional distribution and interregional mobility among refugees in Sweden. It uses individual-level register data to follow two cohorts for eight years after their arrival in Sweden, distinguishing between refugees subject to a placement policy in the 1990s and recent cohorts that had either arranged their own housing or had been assigned housing. It uses sequence analysis and multinomial logit regression to analyse regional trajectories, and event history analysis to examine mobility determinants. The results indicate that most refugees remained in the same type of region throughout the period. A significant proportion of refugees with assigned housing in large city or small city/rural regions stayed there over a long period, suggesting that refugee settlement policies have long-lasting consequences.
The Study of Stage-like Development of Morpho-syntactic Structures in EFL Learners’ Writing Performance: A Processability Theory Account for Cases of “Plural -s” and “Adverb Fronting”

Processability Theory (PT) is a theory of second language acquisition (SLA) developed to explain developmental sequences in SLA as well as some other phenomena (Pienemann, 1998; 2015). Processability has been a significant concern in second language acquisition research since the 1990s. Within the framework of processability theory and through analyzing the writing performances of Iranian EFL Received: November 2017; Accepted: February 2018 ∗Corresponding author 1 Journal of Studies in Learning and Teaching English Volume. 7, Issue. 2, Ser. 14, (2018), 1-30 The Study of Stage-like Development of Morpho-Syntactic Structures in EFL Learners’ Writing Performance: A Processability Theory Account for Cases of “Plural-s” and “Adverb Fronting” Mahin Sadat Tabatabaee Ph.D. Candidate of TEFL English Language Department Islamic Azad University, Malayer Branch Hamedan, Iran marjantabatabaee@gmail.com Keivan Mahmoodi∗ Assistant Professor English Language Department Islamic Azad University, Malayer Branch Hamedan, Iran Keivan mahmoodi@aol.com Abbas Bayat Assistant Professor English Language Department Islamic Azad University, Malayer Branch Hamedan, Iran Abbasbayat305@yahoo.com Abstract. Processability Theory (PT) is a theory of second language acquisition (SLA) developed to explain developmental sequences in SLA as well as some other phenomena (Pienemann, 1998; 2015). Processability has been a significant concern in second language acquisition research since the 1990s. Within the framework of processability theory and through analyzing the writing performances of Iranian EFL Processability Theory (PT) is a theory of second language acquisition (SLA) developed to explain developmental sequences in SLA as well as some other phenomena (Pienemann, 1998; 2015). Processability has been a significant concern in second language acquisition research since the 1990s. Within the framework of processability theory and through analyzing the writing performances of Iranian EFL Received: November 2017; Accepted: February 2018 ∗Corresponding author
Molecular crosstalk between plant beneficial rhizobacteria: identification of Pseudomonas compounds influencing the growth and antimicrobial potential of Bacillus velezensis

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Detecting Contract Cheating Using Learning Analytics

Keystroke logging and clickstream data, both emergent areas of study in the field of learning analytics, present promising alternative methods of detecting and preventing contract cheating. The current study examines whether analysis of keystroke and clickstream data can detect when a student is creating their own authentic writing or transcribing from another source. Participants were 62 university students (47 women, 15 men) who completed three writing tasks under experimental conditions: free writing, general transcription, and self-transcription. Analyses revealed that while completing the free-writing task, participants typed in shorter bursts with longer pauses and typed more slowly with more revisions compared to the two transcription tasks. Model-based clustering was able to accurately distinguish the free-writing task from the two transcription tasks based on patterns of bursts and writing speed. Overall, these results suggest that keystroke and clickstream analysis may be able to distinguish between a student writing an authentic piece of work and one transcribing a completed work. These findings signal significant implications for the detection of contract cheating.
Staіkov P

The results of barіatrіc іnterventіons іn the clіnіc of the Department of Surgery No. 2 of the KhNMU wіth the use of mіnі-іnvasіve іnterventіons that were performed from September 2015: 7 patіents (3 women, 4 men) wіth morbіd obesіty (7) on the background of dіabetes mellіtus (1) at the age of 37-55 g. The weіght before operatіon was 125.75 [107-143] kg; BMІ 46.3 [45.2-52.1] kg\m2. The followіng types of surgіcal іnterventіons were performed: іn 4 patіents laparoscopіc sleeve resectіon of the stomach; іn 3 laparoscopіc gastrіc bypass. All patіents began to eat and walk іn 4-6 hours after surgery. There were not complіcatіons and postoperatіve mortalіty. Patіents were dіscharged in a 7 days from the hospіtal. Tіme of observatіon is from 6 months to 3.5 years. Evaluatіon of the percentage of excess weіght loss (EWL %) was performed.The results are: on the averaged іn patіents undergoіng after gastrіc bypass: 1 months 21%, sleeve gastrectomy (gastrіc sleeve resectіon): up to 1 months on the average of 26,4%. The qualіty of patіents lіfe has іmproved sіgnіfіcantly.
Technological Challenges for Management of Genetic Complexities of Myelodysplastic Syndromes

Ab s t r Ac t Background: Chromosomal abnormalities (CA), including del(3q, 5q, 7q, 11q, 12p, 17p, 20q); loss of 5, 7, and Y; trisomy(8,19); i(17q); and balanced and unbalanced translocations have been demonstrated as prognostic markers in 5-tier risk-grouping and WHO-2016 classification of myelodysplastic syndromes (MDS). However, monosomal karyotype (MK) in the presence or absence of a complex karyotype (CK) has not been considered in the WHO classification. Additionally, a plethora of somatic mutations of MDS-specific and elderly populations collected through a-CGH, SNP-array, next-generation, and targeted sequencing has led to understanding of their impact on MDS-phenotype, initiation and progression of the disease, and treatment outcome in single or cooperating effects of comutations of several pathway-mechanisms. Methods: The present review on technological challenges has been raised on the information available through Google-search using MDSgenetics, mutations of MDS, diagnosis and prognosis of MDS, etc. with a view to understanding the possibilities in low-resource settings. Results: Mutual exclusivity and cross-talk of such mutations help in self-renewal of leukemic stem cells. However, molecular screening is not only time-consuming but also expensive in poor-economic settings. Nevertheless, the significance of unspecific and uncalled mutations is yet to be understood. In contrast, conventional cytogenetic assays have specific aberrations of prognostic and therapeutic values, which cover the whole genome in a cost-effective manner. However, since somatic mutations of clonal hematopoiesis of indeterminate potential (CHIP) in asymptomatic and/or patients with idiopathic cytopenia of undetermined significance (ICUS) have the potential for favoring the leukemic onset to progression, molecular screening has inherent importance within the disease-mechanism. Conclusion: The WHO-2016 risk-classification has considered mutations of SF3B1, TP53, and MLL for management of MDS, and also powered conventional cytogenetics for diagnosis and risk-stratification of MDS.
The eating culture of the Sundanese: Does the traditional salad (Lalapan) improve vegetable intake and blood β-carotene concentration?

This study explores how consumption of the traditional salad Lalapan, central to the eating culture of the Sundanese, is associated with skin quality perception, daily β-carotene intake and blood β-carotene concentrations. This cross-sectional study was conducted in Gunung Malang Village and Leuweung Kolot Village, Bogor District, West Java. 60 healthy Sundanese women, aged 30-49 years, were selected using simple random sampling. Their body weight and height were measured, and they were interviewed about the eating culture of Lalapan, skin quality perceptions after consumption of Lalapan, and consumption habits of Lalapan using a semi-quantitative month-long food frequency questionnaire (SQ-FFQ). The blood β-carotene concentrations of about 25% of the subjects were analysed and Chi-square used to evaluate the association between variables. The results show that about 60% and 51.7% subjects had a good eating culture of Lalapan and good skin quality perceptions respectively. The eating culture of Lalapan had a positive association with skin quality perception (p=0.000), β-carotene intake from Lalapan (p=0.008), daily β-carotene intake (p=0.035), and blood β-carotene concentrations (p=0.031). The consumption of Lalapan is a wisdom culture in Sundanese society that serves to improve vegetable consumption at the community level. In particular, it increases nutrient intake, especially β-carotene that is beneficial to health. Given that vegetable consumption is low in the community, maintenance of the good eating culture of Lalapan should be an urgent policy priority to ensure the nutrition and health of the community.