Miracle-dz/UniFAR-FTUs huggingface dataset:
Title : IDH 1 Mutations Induce Organelle Defects Via Dysregulated Phospholipids 1

Adrian Lita1, Artem Pliss2, Andrey Kuzmin2,3, Tomohiro Yamasaki1, Lumin Zhang1, Tyrone 2 Dowdy1, Christina Burks4, Natalia de Val4,5,6, Orieta Celiku1, Victor Ruiz-Rodado1 , Elena-Raluca 3 Nicoli7, Michael Kruhlak8, Thorkell Andresson9, Sudipto Das9, Chunzhang Yang1, Rebecca 4 Schmitt2, Christel Herold-Mende10, Mark R. Gilbert1, Paras N. Prasad2,3, and Mioara Larion1* 5 6 Affiliations: 1Neuro-Oncology Branch, National Cancer Institute, Center for Cancer Research, 7 National Institute of Health, Bethesda, Maryland; 2Institute for Lasers, Photonics and 8 Biophotonics, University at Buffalo, Buffalo, New York; 3Advanced Cytometry Instrumentation 9 Systems, LLC, Buffalo, NY 4Electron Microscopy Laboratory, Frederick National Laboratory for 10 Cancer Research, Center for Cancer Research, National Cancer Institute, Frederick, MD 21702, 11 USA; 5Center for Molecular Microscopy, Center for Cancer Research, National Cancer Institute, 12 Frederick, MD, 21702, USA; 6Cancer Research Technology Program, Frederick National 13 Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, MD, 21701, USA; 14 7Undiagnosed Diseases Program, National Human Genome Research Institute (NHGRI), 15 National Institutes of Health (NIH), Bethesda, MD 20892, USA; Common Fund, Office of the 16 Director, NIH, Bethesda, MD 20892, USA; 8Confocal Microscopy Core, National Cancer Institute, 17 National Institutes of Health (NIH), Bethesda, MD 20892, USA; 9Protein Characterization 18 Laboratory of the Cancer Research Technology Program (CRTP) 10Division of Neurosurgical 19 Research, Department of Neurosurgery, University Hospital Heidelberg, Germany; 20
Determination of Cashew Juice specie’s Shelf-Life at Natural Storage Using Multivariate Regression Model

There is an inevitable decline in quality value especially the ascorbic acid in preserving cashew apple juice. The maximum shelf life of red sample of cashew apple juice was estimated and the quality value multivariate regression model was developed. Data were drawn from 3 full factorial experiments conducted in three replicates with the order of the replicates randomized. The model developed for the sample of cashew fruit juice revealed that pH and duration of storage with other interactions were the major parameters that govern the shelf-life and characterization qualities of cashew fruit juice. The coefficient of correlation (R) of the dependent variable (ascorbic acid) and independent variables (temperature, total soluble solid, pH and duration of storage) in the model was 0.954. The regression model revealed that temperature of 34.4 C, 11.13 Brix value, pH of 3.99, 16 days storage duration of the sample maintained ascorbic acid levels of 239.59 mg/100 ml at maximum shelf life. The sample of the juice had 31 insignificant regression coefficients at 5 percent probability level after checking the adequacy of the predicted model. Equation 34 expresses the fitted model for predicting the shelf life of red sample of cashew fruit juice which recorded 17 experiments that did not meet minimum quality requirement of ascorbic acid level.
Effect of hydro- alcoholic extract of Heracleum persicum during pregnancy on liver enzymes (AST-ALT-ALP) and biochemical factors (Albumin and protein) of infant male rats

Introduction : Liver is one of the vital organs in the body with a key role in regulating many physiological mechanisms. The present study was conducted to examine the effect of the hydroalcoholic extract of Heraclum persicum administered to the mother rats during pregnancy on liver enzymes and blood biochemical factors in their infant male rats. Materials and Methods: The present experimental study was conducted on 40 infant male Wistar rats divided into 5 groups of 8, whose mothers were then divided into 5 groups of 8 during their pregnancy, including a negative control group, a sham control group and three experimental groups. The negative control group did not receive any treatments while the sham control group received only distilled water. Experimental groups 1, 2 and 3 received, respectively, 100, 200 or 400 mg/kg oral doses of Heracleum persicum on a daily basis for a period of 21 days (the pregnancy term). At the end of the pregnancy and when the male infant rats were 25 days old, the infant rats' blood samples were taken and their liver enzymes (alanine transaminase [ALT], aspartate aminotransferase [AST] and alkaline phosphatase [ALP]) and biochemical factors (Albumin and total serum protein) were measured. The data obtained were analyzed using the ANOVA and Tukey's post-hoc test. P<0.05 was taken as the level of statistical significance. Results: The AST and ALT levels had increased significantly in experimental groups 2 and 3 compared to in the negative and sham control groups (P<0.05). The Albumin level had also increased significantly in experimental group 3 compared to in the negative and sham control groups (P<0.05). There was also a significant difference between ALP and serum protein levels in the experimental groups and the negative and sham control groups. Conclusion: The hydroalcoholic extract of Heracleum persicum may have changed the liver function and increased ALT and AST as a result of its furanocoumarin and trans-anethole content. The extract's alkaloid and flavonoid content also increase serum Albumin levels.
A Web Based Application for Investment Evaluation of Medical Devices Development

The present research investigates investment evaluations in the context of medical device development, with an emphasis on a web-based application as the likely solution. In recent years, the medical industry has seen an evolution with new innovations revolutionizing how healthcare, treatments and patient wellbeing are handled and managed. This has allowed companies not only to look towards innovation to help with new products but also as a means to procure better profits and competencies. The solution lies in a web-based application which is both user-friendly and efficient. This research examines the need for a model that looks at the process of development in stages and so that the entirely process is not only based on data and information but is also geared towards cost efficacy and control. The fine line between the success and failure of any product or innovation lies in how needed it is and how well the market responds to it.
The Long Tail Effect of Personalized Rankings

We study the extent to which consumers benefit from personalized product suggestions offered by online retailers. Using data from a large-scale randomized experiment conducted by a major online retailer, we show that personalized product rankings induce users to purchase a greater variety of items relative to non-personalized bestseller-based rankings. To study whether users benefit from this shift in demand, we estimate an empirical choice model and use it to measure the effect of personalization on consumer surplus. Our model captures flexible taste heterogeneity by combining a standard consideration model with a latent factorization approach from computer science. This combination enables us to estimate users' tastes from data on both search histories and personalized rankings, while also recognizing that user histories are confounded by the prominence of displayed items. We estimate users' tastes and show that personalized rankings increase consumer surplus by 30% for the average user. This effect arises primarily because personalization makes users with niche tastes more likely to discover relevant niche items. Without personalization, the retailer would only offer 25% of its current assortment because most of these niche items would never find their audience.
Concept Detection in Images Using SVD Features and Multi-Granularity Partitioning and Classification

New visual and static features, namely, right singular feature vector, left singular feature vector and singular value feature vector are proposed for the semantic concept detection in images. These features are derived by applying singular value decomposition (SVD) " directly " to the " raw" images. In SVD features edge, color and texture information is integrated simultaneously and is sorted based on their importance for the concept detection. Feature extraction is performed in a multi-granularity partitioning manner. In contrast to the existing systems, classification is carried out for each grid partition of each granularity separately. This separates the effect of classifications on partitions with and without the target concept on each other. Since SVD features have high dimensionality, classification is carried out with K-nearest neighbor (K-NN) algorithm that utilizes a new and " stable " distance function, namely, multiplicative distance. Experimental results on PASCAL VOC and TRECVID datasets show the effectiveness of the proposed SVD features and multi-granularity partitioning and classification method.
Performance Report on Adaptive Resolution Isosurface Algorithm

Isosurfaces obtained from densely sampled datasets often contain a large number of simplices that do not provide any useful topological or geometric information. It might be bene(cid:2)cial if one could replace them without losing too much information with fewer, larger simplices. An algorithm to identify regions in the dataset where there was no signi(cid:2)cant topological event happening was proposed by us in an earlier paper [R. Kazhiyur-Mannar et al. 2003]. The paper also described an algorithm to construct crack-free isosurface from an adaptive resolution dataset. We report the performance statistics of our implementation of the algorithms.
An event calculus-based approach to reasoning about mobile apps

Software running on mobile platforms has become increasingly important. Given the essential tasks that many of these \apps" are intended to carry out, the importance of specifying their behavior precisely and adequately testing them against the speci(cid:12)cations is clear. In this report, we describe our e(cid:11)orts to develop an approach to specifying and testing of apps for the Android platform. We explore the use of event-calculus for this, and discuss its pros and cons.
Short Note about the Robin’s Inequality

In mathematics, the Riemann hypothesis is a conjecture that the Riemann zeta function has its zeros only at the negative even integers and complex numbers with real part 1 2 . Many consider it to be the most important unsolved problem in pure mathematics. The Robin’s inequality consists in σ(n) < eγ × n × ln lnn where σ(n) is the divisor function and γ ≈ 0.57721 is the Euler-Mascheroni constant. The Robin’s inequality is true for every natural number n > 5040 if and only if the Riemann hypothesis is true. Given a natural number n = q1 1 ×q a2 2 ×· · ·×q am m such that n > 5040, q1, q2, · · · , qm are prime numbers and a1, a2, · · · , am are positive integers, then the Robin’s inequality is true for n when qα 1 × qα 2 × · · · × qα m ≤ n, where α = (lnn′)β , β = ( 2 6 − 1) and n′ is the squarefree kernel of n.
Doppler Boosting and cosmological redshift on relat ivistic jets

In this study our goal was to identify the possible effects that influence with the Spectral Energy Distribution of a blazar, which we deducted that ar e Doppler Boosting effect and cosmological redshift . Then we investigated how the spectral energy distribution v aries by changing intrinsic parameters of the jet l ike its Lorentz factor, the angle of the line of sight respect to t he jet orientation or the blazar redshift. The obta ined results showed a strong enhancing of the Spectral Energy Distributio n for nearly 0o angles and high Lorentz factors, wh ile t e increase in redshift produced the inverse effect, reducing t he normalization of the distribution and moving the peak to lower energies. These two effects compete in the observat ions of all known blazars and our simple model conf irmed the experimental results, that only those blazars with optimal characteristics, if at very high redshift, are suitable to be measured by the actual instruments, making the stud y of blazars with a high redshift an issue that nee ds very deep observations at different wavelengths to collect en ough data to properly characterize the source popul ation.
The Predictability of Tree-based Machine Learning Algorithms in the Big Data Context

This research work is concerned with the predictability of ensemble and singular tree-based machine learning algorithms during the recession and prosperity of the two companies listed in the Tehran Stock Exchange in the context of big data. In this regard, the main issue is that economic managers and the academic community require predicting models with more accuracy and reduced execution time; moreover, the prediction of the companies recession in the stock market is highly significant. Machine learning algorithms must be able to appropriately predict the stock return sign during the market downturn and boom days. Addressing the stated challenge will upgrade the quality of stock purchases and, subsequently, will increase profitability. In this article, the proposed solution relies on the utilization of tree-based machine learning algorithms in the context of big data. The proposed solution exploits the decision tree algorithm, which is a traditional and singular tree-based learning algorithm. Furthermore, two modern and ensemble tree-based learning algorithms, random forest and gradient boosted tree, has been utilized for predicting the stock return sign during recession and prosperity. The mentioned cases were implemented by applying the machine learning tools in python programming language and PYSPARK library that is used explicitly for the big data context. The utilized research data of the current study are the shares information of two companies of the Tehran Stock Exchange. The obtained results reveal that the applied ensemble learning algorithms have performed better than the singular learning algorithms. Additionally, adding 23 technical features to the initial data and subsequent applying of the PCA feature reduction method have demonstrated the best performance among other modes. In the meantime, it has been concluded that the initial data do not possess the proper resolution or generalizability, either during prosperity or recession.
Levels of Detail in Visual Augmentations for the Novice and Expert Audiences

Digital Musical Instruments offer countless opportunities for musical expression as they allow artists to produce sound without the physical constraints of analogical instruments. However, by breaking the intuitive link between gestures and sound, they may hinder the audience experience, making the musician’s contribution and expressiveness difficult to perceive. In order to cope with this issue without altering the instruments, researchers and artists have designed techniques to augment their performances with additional information, through audio, haptic or visual modalities. These techniques have, however, only been designed to offer a fixed level of information, without taking into account the variety of spectators’ expertise and preferences. In this paper, we introduce the concept of controllable Level of Details (LOD) for visual augmentations. We investigate their design, implementation and effect on objective and subjective aspects of audience experience. We conduct a controlled experiment with 18 participants, including novices and experts in electronic music. Our results expose the subjective nature of expertise and its biases. We analyse quantitative and qualitative data to reveal contrasts in the impact of LOD on experience and comprehension for experts and novices. Finally, we highlight the diversity of usage of LODs in visual augmentations by spectators and propose a new role on stage, the augmenter.
A Review of Content-Based and Context-Based Recommendation Systems

In our work, we have presented two widely used recommendation systems. We have presented a context-aware recommender system to filter the items associated with user’s interests coupled with a context-based recommender system to prescribe those items. In this study, context-aware recommender systems perceive the user’s location, time, and company. The context-based recommender system retrieves patterns from World Wide Web-based on the user’s past interactions and provides future news recommendations. We have presented different techniques to support media recommendations for smartphones, to create a framework for context-aware, to filter E-learning content, and to deliver convenient news to the user. To achieve this goal, we have used content-based, collaborative filtering, a hybrid recommender system, and implemented a Web ontology language (OWL). We have also used the Resource Description Framework (RDF), JAVA, machine learning, semantic mapping rules, and natural ontology languages that suggest user items related to the search. In our work, we have used E-paper to provide users with the required news. After applying the semantic reasoning approach, we have concluded that by some means, this approach works similarly as a content-based recommender system since by taking the gain of a semantic approach, we can also recommend items according to the user’s interests. In a content-based recommender system, the system provides additional options or results that rely on the user’s ratings, appraisals, and interests.
Constructing Isosurfaces with Sharp Features from Scalar Data - Tech Report

Previous algorithms for constructing isosurfaces with sharp features required gradients or surface normals to be provided as input to the algorithm. We present an algorithm for constructing isosurfaces with sharp features from scalar data on a regular grid. Our algorithm has two parts: (1) an algorithm to construct reliable gradients from scalar data; (2) an algorithm to construct isosurfaces with sharp features from scalar data combined with gradient data. We give experimental re-sults on industrial CT scans. Our algorithm produces isosurface meshes with sharp edges and corners reliably represented by mesh edges and vertices. Our algorithm also produces reliable representations and good visualizations of sharp features in the isosurface.
Pulmonary Function Test of Coal Miners in Damini Colliery, M. P., India

Coal mining is an ancient occupation, long-standing identification as being difficult and responsible due to injuries and disease. Spirometry predicts early damage of pulmonary system and respiratory chronic airway disorders. Exposure of coal dust affects various body systems. The present study focused on coal workers who are constantly exposed to air pollutants such as coal dust. Study was conducted among 400 male coal mine workers. Out of total mine workers, 205 workers were smokers and remaining 195 were nonsmokers. Spirometry test revealed 9.75 % of workers were mild (26-30 years of age group), 20% moderate (31-35 and 36-40 years of age group), 6.25 % were moderately severe (41-45 years of age) and 12 % (from 46 years and above) of them was found severe obstruction stage among smoking workers. Non smoking workers were not affected by any types of obstruction, so there was significantly correlation between forced vital capacity and smoking workers. The results suggest that there is a need to improve their health and change their habits because it is more harmful to their health. Coal workers, forced vital capacity, lung function, spirometry test, dust exposure
Entrepreneurial orientation and CSR: a dynamic capability in the corporate performance of Mexican SMEs

In the current business context, SMEs play a determining role for most regions. For this reason, more and more companies are adopting business strategies that lead them to maintain and increase their competitiveness. Two of these strategies are Entrepreneurial Orientation (EO) and Corporate Social Responsibility (CSR). The purpose of the study is to observe the effects that the EO has on the CSR and on the Corporate Performance (CPERF). In addition, it seeks to determine if the CSR has significant effects on the Corporate Performance, and it has also been proposed to examine the mediating effect that the CSR has between the variable EO and Corporate Performance. The study analyzes a sample of 488 trade and service SMEs from the Northwest region in Mexico. The information was collected through a self-directed survey of the manager of each SME from May to September 2018. For the analysis of the data, the statistical technique PLS-SEM was used (partial least squares structural equation modeling). The results report that EO has a strong significant effect on CSR and also on the Corporate Performance of SMEs. Furthermore, the results have corroborated that CSR is a mediating variable between EO and Corporate Performance. The study contributes to the development of the theory of Dynamic Capabilities and of Stakeholders, corroborating that SMEs that adopt EO and CSR can lead them to the permanent adoption of sustainable entrepreneurship and the improvement of their corporate performance results. * This research has been funded with support from the Government of Mexico through the program of the Ministry of Public Education for the Strengthening of Educational Quality (PFCE 2019, 2020) https://www.dgespe. sep.gob. mx/pfce/reglas_operacion and with resources from the Technological Institute of Sonora (ITSON), during the year 2020. European Regional Development Fund and Junta of Extremadura (Business Research [INVE] Research Group [SEJ022 code]) and by the VI Action Plan 2018–2020 under grant number GR18058. ENTREPRENEURSHIP AND SUSTAINABILITY ISSUES ISSN 2345-0282 (online) http://jssidoi.org/jesi/ 2021 Volume 8 Number 3 (March) http://doi.org/10.9770/jesi.2021. 8.3(41) Make your research more visible, join the Twitter account of ENTREPRENEURSHIP AND SUSTAINABILITY ISSUES: @Entrepr69728810 655
Acetabular fractures: epidemiological, lesional, therapeutic and evolutionary aspects

Background: Fractures of the acetabulum are serious because they affect a deep, load-bearing joint that is difficult to repair surgically at first. They occur in a context of polytrauma. The aim of our work is to study the epidemiological, lesional, therapeutic and evolutionary aspects of acetabulum fractures.Methods: This is a 5-year retrospective study from January 2012 to December 2016 including 45 patients treated for acetabulum fracture.Results: 45 patients including 38 men and 7 women with a mean age of 36 years (extremes 18 and 74). The circumstances of occurrence were dominated by road traffic accidents with 42 cases (93.3%). According to the Judet-Letournel classification, we observed 28 elementary fractures (16 posterior wall fractures, 11 posterior column fractures, 1 anterior column fracture) and 17 complex fractures (7 posterior column and posterior wall fractures, 6 transverse and posterior wall fractures, 3 posterior and anterior column fractures, 1 anterior column and posterior hemi-transverse fracture). The association of a dislocation with an acetabulum fracture was found in 32 cases. Associated lesions (fractures) were observed in 23 patients. One case of associated TCE was noted. Treatment was orthopedic in 18 patients, surgical in 18 patients and functional in 9 patients. According to the Matta criteria we obtained after treatment 46.7% good reduction, 51.1% satisfactory and 2.2% unsatisfactory reduction. According to the Postel-Merle D'Aubigné rating, 16 patients obtained excellent results with overall 93.3% satisfactory results. The complications found were coxarthrosis (15 cases), para-articular ossification (2 cases) and vicious callus (1 case). Conclusions: The treatment of acetabulum fractures depends on the type of fracture, the age and activities of the patients. Orthopedic, surgical as well as functional treatment can give good acetabular reconstructions and functional results.