Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of dynamic and static characteristics of igneous bedrock by means of suspension P-S logging and uniaxial compressive strength tests

This paper provides correlations between the values of P-wave velocity and dynamic elastic modulus through in-situ dynamic testing (suspension P-S logging) and the values of uniaxial compressive strength (UCS) and static elastic modulus through laboratory static testing (uniaxial compressive) of sound rock from two sites located in South Carolina and Virginia. For both sites, the bedrock, which classified as good to excellent, is hard fresh to slightly discolored metamorphic rock, or igneous rock with numerous metamorphic inclusions. Suspension P-S logging tests were performed in 12 uncased fluid-filled boreholes, to rock depths of over 120 m. The investigation further included the results of unconfined compression tests on rock cores and assessment of the variation of static elastic modulus with UCS from these compression tests. The comparisons show that the low strain elastic moduli values of sound rock agree well with the higher strain values obtained from the unconfined compression tests. RÉSUMÉ Ce document fournit des corrélations entre les valeurs de vélocité d' ondes-P et module dynamique d'élasticité par le biais de terrain des essais dynamiques (suspension P-S logging), et les valeurs de résistance uniaxiale à la compression et module statique d'élasticité des essais laboratoires statiques (uniaxial compression) de rocher solide de deux sites aux Étas-Unis, situés dans la Caroline du Sud et en Virginie. Pour les deux sites, le substrat rocheux) , classé comme bon jusqu'à excellent, est entre dur fraîche du roc igné légèrement décoloré avec de nombreuses inclusions métamorphiques. Des essais “suspension P-S logging” ont été effectués en 12 trous de fourage sans revêtement remplis de liquide, dans des profondeurs de roc dépassant les 120 m. L'enquête a inclus les résultats des essais de compression non-restreinte des carottes rocheux, et l'évaluation de la variation de statique du module élastique statique avec résistance uniaxiale de ces tests de compression. Les comparaisons montrent que les valeurs des modules elastiques d’une faible souche de roc solide conviennent bien aux valeurs obtenues des tests de compression non-restreinte.
Reducing Spatial Stochastic Models of Membrane Receptors to Approximately Equivalent Chemical Reaction Networks through Coarse Graining

Reducing Spatial Stochastic Models of Membrane Receptors to Approximately Equivalent Chemical Reaction Networks through Coarse Graining Christopher Todd Short Computational models are necessary for understanding how biological functionality emerges from a complex network of molecular interactions such as in cell signaling. Due to the complexity of biological systems, the normal scientific method of hypothesizing then testing predictions is becoming increasingly difficult. The large number of processes limits the level of modeling detail; signaling models typically adopt a non-spatial representation where each molecular process is characterized by a few parameters. However, modern microscopic imaging of receptors on cell membranes reveals an intricate structure of microdomains. Receptors, such as epidermal growth factor receptor (EGFR), vascular endothelial growth factor receptor (VEGFR), and others, tend to be grouped in the microdomains as clusters that range from a few to hundreds of biomolecules. While the origin of these clusters is not well understood, a likely explanation is the existence of microdomains with an affinity for the receptors. Using this hypothesis, we can ignore the underlying cause of the microdomains. The size and geometry of these domains can be inferred directly from microscopy; however, the relevant physical properties can only be verified through simulations. In this thesis, I propose a flexible approach to performing such simulations in a coarse grained model that is validated through solving the differential equations when possible and through equilibrium calculations when not. Due to the non-trivial nature of these cell membrane features, fully spatial models need to be used to address these issues. However, fully spatial models are computationally intense and little insight can be gained from them, because of this I propose a method to construct the well-mixed model from the spatial one. The primary issue is the difficulty of extracting the correct kinetic coefficients and that limits the predictive power of spatial models due to the inherent challenges of estimating dynamical parameters. I will use the Metropolis-Hastings Algorithm to extract these parameters from the fully spatial simulations. I use the spatial model as an intermediary step because the spatial simulations can be matched to experimental techniques that provide molecular level resolution, such as single particle tracking (SPT) data. I will then discuss issues that emerge from a baseline comparison between spatial and non-spatial simulations of a simple reversible dimerization process; the spatial simulation employed an algorithm similar to Smoldyn.
The Influence of Memory Enhancement Techniques on Source Monitoring

The Influence of Memory Enhancement Techniques on Source Monitoring Ria M. Travers An important aspect of accurate eyewitness testimony is not only being able to recall the details of an event, but being able to trace that memory back to its source or origin (Johnson, Hashtroudi, & Lindsay, 1993). The current study examined the use of two memory enhancement interventions to improve the accuracy of source memory, or the correct attribution of a memory to its origin, and free recall. The first intervention, motivational instructions, informed participants that they are capable of recalling an event if they try their best. The second intervention, focused meditation, used a breathing exercise to focus individuals’ attention while they recalled the to-be-remembered stimuli. The study compared the efficacy of these two interventions to one another and a control condition in which participants completed the source monitoring test and free recall task without receiving a memory enhancement intervention. Fifty-nine undergraduate college student participants viewed a video of an event and then answered written questions. Two days later, participants either received a memory enhancement technique or no technique. Following this, they received a source monitoring test during which participants listened to statements and were asked to identify the source of the statement. Next, they free recalled all details they remembered about the event. The number of correct ideas recalled and the number of incorrect ideas were calculated and statistically compared across conditions. The number of correct responses to the source monitoring questions was also compared across conditions. The two memory enhancement techniques were not found to increase source monitoring accuracy or accurate free recall compared to the no-intervention control condition. These results suggest that focused meditation and motivational instructions may not be effective in increasing accurate source memory on the source monitoring task that was used. The result that these techniques did not increase free recall is unexpected, and may be due to procedural ideas of the study design.
New Insights for Cellular and Molecular Mechanisms of Aging and Aging-Related Diseases: Herbal Medicine as Potential Therapeutic Approach

Aging is a progressive disease affecting around 900 million people worldwide, and in recent years, the mechanism of aging and aging-related diseases has been well studied. Treatments for aging-related diseases have also made progress. For the long-term treatment of aging-related diseases, herbal medicine is particularly suitable for drug discovery. In this review, we discuss cellular and molecular mechanisms of aging and aging-related diseases, including oxidative stress, inflammatory response, autophagy and exosome interactions, mitochondrial injury, and telomerase damage, and summarize commonly used herbals and compounds concerned with the development of aging-related diseases, including Ginkgo biloba, ginseng, Panax notoginseng, Radix astragali, Lycium barbarum, Rhodiola rosea, Angelica sinensis, Ligusticum chuanxiong, resveratrol, curcumin, and flavonoids. We also summarize key randomized controlled trials of herbal medicine for aging-related diseases during the past ten years. Adverse reactions of herbs were also described. It is expected to provide new insights for slowing aging and treating aging-related diseases with herbal medicine.
Abelian Hopf Galois structures from almost trivial commutative nilpotent algebras

Let L/K be a Galois extension of fields with Galois group G an elementary abelian p-group of rank n for p an odd prime. It is known that nilpotent Fp-algebra structures A on G yield regular subgroups of the holomorph Hol(G), hence Hopf Galois structures on L/K. In this paper we illustrate the richness of Hopf Galois structures on L/K by examining the case where A is abelian of Fp-dimension n where dim(A) = 1. We determine the number of Hopf Galois structures that arise in these cases, describe those structures explicitly, and estimate the extent of failure of surjectivity of the Galois correspondence for those structures.
A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks

Evaluation of Bayesian deep learning (BDL) methods is challenging. We often seek to evaluate the methods' robustness and scalability, assessing whether new tools give `better' uncertainty estimates than old ones. These evaluations are paramount for practitioners when choosing BDL tools on-top of which they build their applications. Current popular evaluations of BDL methods, such as the UCI experiments, are lacking: Methods that excel with these experiments often fail when used in application such as medical or automotive, suggesting a pertinent need for new benchmarks in the field. We propose a new BDL benchmark with a diverse set of tasks, inspired by a real-world medical imaging application on \emph{diabetic retinopathy diagnosis}. Visual inputs (512x512 RGB images of retinas) are considered, where model uncertainty is used for medical pre-screening---i.e. to refer patients to an expert when model diagnosis is uncertain. Methods are then ranked according to metrics derived from expert-domain to reflect real-world use of model uncertainty in automated diagnosis. We develop multiple tasks that fall under this application, including out-of-distribution detection and robustness to distribution shift. We then perform a systematic comparison of well-tuned BDL techniques on the various tasks. From our comparison we conclude that some current techniques which solve benchmarks such as UCI `overfit' their uncertainty to the dataset---when evaluated on our benchmark these underperform in comparison to simpler baselines. The code for the benchmark, its baselines, and a simple API for evaluating new BDL tools are made available at this https URL.
Study of Osteopontin as a Noveltumor Marker for Detection of Hepatocellular Carcinoma = دراسة الأوستیوبونتن كدلالة أورام في تشخیص سرطان الكبد

Background: Hepatocellular carcinoma (HCC) is one of the most common malignancies and the third most common cause of death from cancer worldwide. Approximately, 80 to 90% of HCC occur in a cirrhotic liver. HCC is now a rather common malignancy in Egypt which usually develops on top of liver cirrhosis secondary to viral infection. Hepatitis C virus increases the risk of HCC in the Egyptian patients. Osteopontin (OPN) is a glycoprotein secreted by cells as osteoblasts, osteoclasts, activated macrophages and T cells. It is over expressed in a variety of human tumors, including carcinomas of stomach, breast, prostate, lung, colon, and liver. Plasma level of osteopontin may be a biomarker for HCC. Objective: This study aimed to evaluate plasma osteopontin (OPN) level and determine its sensitivity and specificity as a screening tool for detection of HCC patients. Subjects and Methods: Plasma OPN level was measured in 64 patients(Twenty two patients with non-cirrhotic HCV, twenty two with cirrhotic HCV and twenty HCC patients on top of chronic cirrhotic HCV)in addition to twenty healthy controls. Plasma OPN level using ELISA technique was done to all participants. Also, liver enzymes (AST) and (ALT), serum bilirubin, albumin, alpha-fetoprotein and blood hemoglobin (Hb) were done to all participants. Results: The mean plasma osteopontin (OPN) level significantly elevated in patients with HCC group than all groups. The sensitivity and specificity in detection of HCC were 100% and 97% respectively at cut off level of 270 ng/ml with accuracy 95%. Conclusion: Plasma OPN level can be used as a routine biomarker for clinical prediction of the recurrence, metastasis, and prognosis in patients with HCC.
ANALYZING THE BASIC METEOROLOGICAL ASPECTS OF A PARTICULATE AIR POLLUTION EPISODE OVER THE INDUSTRIAL AREA OF NORTHWESTERN GREECE DURING THE NOVEMBER 2009

The complex terrain basin of Amyntaio – Ptolemais – Kozani in Western Macedonia of Greece is an area characterized by increased industrial activity and therefore it demands continuous and assiduous environmental monitoring. A prolonged particulate matter air pollution episode was recorded in the area during November 2009. Basic meteorological aspects are analyzed, during the episode period. Daily and hourly PM10 and PM2.5 concentration measurements were used along with surface and lower atmosphere hourly meteorological parameters from 13 measuring stations. The observational data were supported by data produced by the meteorological component of an air pollution model. The overall analysis showed that the episode was primarily the result of the synoptic setting of the middle and lower troposphere. An Omega blocking pattern which gradually transformed to a highover-low pattern prevailed over central and southern Europe during the episode’s period. The examination of the vertical wind field in the lower troposphere and appropriate stability indices, revealed a continuous absence of significant convection. The weak horizontal wind field near the surface and the reduced mixing height combined with the lack of synoptic forcing resulted in the trapping of the pollutants in the lower troposphere and the recording of increased airborne particulate matter concentrations. The radical change of the synoptic setting in the first days of December marked the end of the episode.
Standard enteral feeding improves nutritional status compared with hospital-prepared blended formula among Intensive Care Unit (ICU) patients

Introduction: There have been great advances in enteral nutrition among critically ill patients in recent decades. However, manufactured standard enteral formula is a new material in Iran and most hospitals are still opting to use traditional hospital-prepared blended formulas. Objective: To evaluate effects of standard enteral feeding for improving nutritional status compared with hospital-prepared blended formula among Intensive Care Unit (ICU) patients. Methods: Forty patients participated in enteral feeding by the standard system and forty patients participated in enteral feeding by hospital-prepared blended formulas. Results: Albumin was much increased in the standard enteral feeding group compared to hospital-prepared blended formulas (P<0.005). There were significant differences in results of albumin, hemoglobin (Hg) and calcium before and after feeding. Conclusion: The macronutrients intake was elevated after standard enteral nutrition and helped patients to recover. The standard enteral formula has more benefits than hospital-prepared blended formulas for ICU patients and medical care givers should be advised and taught to use it rather than hospital-prepared blended formula.
Characteristic of Somatotype, Obesity and Nutrition Intake in Adult Woman (Study in 5 Different Civil Servant Offices in Semarang City)

Somatotype is parameter used to describe body composition. Nutrition intake affects somatotype. The aim of this study is to analyze the correlation of somatotype with obesity parameter and to analyze the correlation of nutrition intake with somatotype. This study was an observational with cross sectional design. The study subject was 64 women aged 25-40 years in Semarang, chosen by using random sampling method. The studied variable were somatotype, waist circumference, BMI (Body Mass Index) and nutrition intake. Nutritional intake was measured using Semi Quantitative Food Frequency Questionnaire (SQ-FFQ). The data was analyzed by using Pearson Product Moment and Rank Spearman. Most subjects had a body type of endomorphic (75%) with highest sub category was mesomorphic-endomorph (59.4%). Subjects who had nutritional status of overweight were 50% and 51,6% had central obesity. The value of endomorph, mesomorph and ectomorph was related to BMI and waist circumference. There was positive correlation between energy intake and endomorph value. In contrast, there was negative correlation between energy intake and ectomorph value. The higher endomorph and mesomorph value and the lower ectomorph value, the higher waist circumference and BMI. The higher energy intake, the higher endomorph and the lower ectomorph value. Keywords—somatotype, obesity, nutrition intake
How to iNNvestigate neural network’s predictions!

In recent years, deep neural networks have revolutionized many application domains of machine learning and are key components of many critical decision or predictive processes such as autonomous driving or medical image analysis. In these and many other domains it is crucial that specialists can understand and analyze actions and predictions, even of the most complex neural network architectures. Despite these arguments neural networks are often treated as black boxes and their complex internal workings as well as the basis for their predictions are not fully understood. In the attempt to alleviate this shortcoming many analysis methods were proposed, yet the lack of reference implementations often makes a systematic comparison between the methods a major effort. In this tutorial we present the library iNNvestigate which addresses the mentioned issue by providing a common interface and out-of-the-box implementation for many analysis methods. In the first part we will show how iNNvestigate enables users to easily compare such methods for neural networks. The second part will demonstrate how the underlying API abstracts a common operations in neural network analysis and show how users can use them for the development of (future) methods. iNNvestigate and the tutorial resources are available at: https://github.com/albermax/innvestigate
“Employment creation in Kenya: exploring the Jua

ARTICLE INFO Eric E. Mang’unyi, Christine W. Mwanzia and Krishna K. Govender (2018). Employment creation in Kenya: exploring the Jua Kali enterprises. Problems and Perspectives in Management, 16(4), 453-467. doi:10.21511/ppm.16(4). 2018.38 DOI http://dx.doi. org/10.21511/ppm.16(4). 2018.38 RELEASED ON Wednesday, 26 December 2018 RECEIVED ON Wednesday, 26 September 2018 ACCEPTED ON Thursday, 06 December 2018
University of Birmingham Mechanisms of tissue injury in autoimmune liver diseases

Autoimmune diseases affecting the liver are mainly represented by autoimmune hepatitis (AIH), primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). The characteristic morphologic patterns of injury are a chronic hepatitis pattern of damage in AIH, destruction of small intrahepatic bile ducts in PBC and periductal fibrosis and inflammation involving larger bile ducts in PSC. The factors responsible for initiation and perpetuation of the injury in all the three autoimmune liver diseases are not understood completely, but are likely to be environmental triggers on the background of genetic variation in immune regulation. In this review, we summarize the current understanding of the mechanisms underlying the breakdown of self-tolerance in autoimmune liver diseases.
A Simple Model for Reasoning about Limits on Coupling in Object-Oriented Software

Given that all of a program's code must be reachable from its main method, and that type-safety causes this reachability to substantially manifest as compilation dependencies among the program's classes, a simple model for reasoning about limits on coupling among a program's classes—a long-standing question in the software design literature—is proposed. The model takes the form of a directed graph with classes as nodes and four distinct forms of compilation dependencies as labeled edges. As manifested in compilation dependencies, the model suggests that there is a trade-off between direct and transitive coupling, and that certain forms of coupling in a class are prerequisites for the existence of other forms in that same class.
Detecting Domain-specific Information needs in Conversational Search Dialogues

As conversational search becomes more pervasive, it becomes increasingly important to understand the user's underlying needs when they converse with such systems in diverse contexts. We report on an insitu experiment to collect conversationally described information needs in a home cooking scenario. A human experimenter acted as the perfect conversational search system. Based on the transcription of the utterances, we present a preliminary coding scheme comprising 27 categories to annotate the information needs of users. Moreover, we use these annotations to perform prediction experiments based on random forest classification to establish the feasibility of predicting the information need from the raw utterances. We find that a reasonable accuracy in predicting information need categories is possible and evidence the importance of stopwords in the classfication task.
A Study on Motivation of High School Students towards Science Learning

Science is a masculine subject and it is best understood by men’. Social scientists have studied it, lawyers have tried to fix it and post-feminist society is over it. But women are still playing an under representative role by men in math, science and engineering fields.Keeping this in view, the current study is done to explore the motivation of grade IX and X students towards science learning. An essential element of science learning is motivation to learn.The objective of present study is to examine the extent of motivation towards learning science, and study the differenceof motivation towards learning science on the basis of gender, location, class, parental qualification and caste.This research study was conducted as a descriptive survey based quantitative study. A 5-point rating scale is used which is a modified version of students’ motivation towards science learning (SMTSL) questionnaire made by Tuan H. L. et al. It consists of 30 items arranged under five constructs a. Self-efficacy, b. Active learning strategies, c. Science learning value, d. Performance goal, e. Achievement goal. SMTSL was administered to 152 students, from 4 randomly selected schools in Purulia district. CR and F tests were used for analyzing the data and verifying the hypotheses.The study revealed that the high school students are averagely motivated towards science learning. The result exhibited that there is significant difference between the motivation of male and female, class IX and X, parents’ educational qualification below and above 10th pass high school students towards science learning. It was also found that female students are more motivated than male high school students in science learning. There is no significant difference between the motivation of Rural and Urban students towards science learning. The study also exposed that caste has not played an important role in the motivation of students towards science learning.