Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of aqueous extract of Solanum macrocarpum Linn. fruit on serum creatinine, urea and some electrolytes in rats pre-fed 1% cholesterol and groundnut oil

Studies were conducted on the effect of the aqueous fruit extract of Solanum macrocarpum Linn. in hypercholesterolaemic rats. The plant material was Soxhlet-extracted with distilled water and the extract was concentrated in vacuo with a yield of 15.34 % /w. The extract was stored in a specimen bottle at room temperature until when required. The kidney function parameters- w serum creatinine, urea and electrolytes (sodium, potassium, calcium and phosphates) were determined. The results showed that with increase in extract dose, the creatinine level increased significantly (p 0.05). The effect of the aqueous extract on the electrolytes showed that both sodium and phosphate dose-dependently increased and the increase was significant (p (p>0.05). The change in calcium with increase in extract dose was not statistically significant (p>0.05). The increase in sodium ion could be due to the high level of Sodium in the plant or as a result of loss of body fluid. Elevated levels of creatinine observed in this study may be due to impaired kidney function.
Footwear and insole design features for offloading the diabetic at risk foot—A systematic review and meta‐analyses

The aim of this systematic review was to identify the best footwear and insole design features for offloading the plantar surface of the foot to prevent foot ulceration in people with diabetic peripheral neuropathy. We searched multiple databases for published and unpublished studies reporting offloading footwear and insoles for people with diabetic neuropathy and nonulcerated feet. Primary outcome was foot ulcer incidence; other outcome measures considered were any standardized kinetic or kinematic measure indicating loading or offloading the plantar foot. Fifty‐four studies, including randomized controlled studies, cohort studies, case‐series, and a case‐controlled and cross‐sectional study were included. Three meta‐analyses were conducted and random‐effects modelling found peak plantar pressure reduction of arch profile (37 kPa (MD, −37.5; 95% CI, −72.29 to −3.61; P < .03), metatarsal addition (35.96 kPa (MD, −35.96; 95% CI, −57.33 to −14.60; P < .001) and pressure informed design 75.4 kPa (MD, −75.4 kPa; 95% CI, −127.4 to −23.44 kPa; P < .004). The remaining data were presented in a narrative form due to heterogeneity. This review highlights the difficulty in differentiating the effect of different insole and footwear features in offloading the neuropathic diabetic foot. However, arch profiles, metatarsal additions and apertures are effective in reducing plantar pressure. The use of pressure analysis to enhance the effectiveness of the design of footwear and insoles, particularly through modification, is recommended.
Periodontal disease: the portrait of an epidemic

Periodontal disease is conventionally defined as an inflammatory disorder involving both soft and hard periodontal structures (1). The early phase, conventionally defined as gingivitis, is characterized by a modest and selflimiting inflammation of periodontal structures. When the local inflammation progresses, the disease evolves towards periodontitis, which has been defined by the 1999 International Workshop on Classification of Periodontal Diseases as a microbially-associated and host-mediated inflammation, resulting in loss of periodontal attachment (2). In the following 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions, it was then specified that the diagnosis of periodontitis shall be based on clinical attachment loss (CAL) by circumferential assessment of erupted dentition using standardized periodontal probes with reference to cementoenamel junction (3). According to the pathophysiological basis, periodontitis can be classified in three different forms, i.e., periodontitis, periodontitis associated with systemic diseases and necrotizing periodontitis. Periodontal disease progressively evolves when left untreated, thus causing several local complications such as the development of deep periodontal lesions, periodontal bone and tooth loss, up to masticatory failure (3). It has been recently hypothesized that some bacteria responsible for periodontitis may actively enter the Original Article
Distinct Functions of POT1 in Telomere Protection and Length Regulation

Distinct Functions of POT1 in Telomere Protection and Length Regulation by Katharine Specchio Barrientos Department of Pharmacology and Cancer Biology Duke University Date: November 20th, 2008 Approved: ___________________________ Christopher M. Counter, Ph.D., Supervisor ___________________________ Shawn Ahmed, Ph.D. ___________________________ Ann Marie Pendergast, Ph.D. ___________________________ Dennis Thiele, Ph.D. ___________________________ Xiao-Fan Wang, Ph.D. An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor in Philosophy in the Department of Pharmacology and Cancer Biology in the Graduate School of Duke University 2008 Copyright by Katharine Specchio Barrientos 2008
Development of microsatellite loci from a reference genome for the Neotropical butterfly Heliconius numata and its close relatives

The Neotropical butterfly Heliconius numata (Lepidoptera: Nymphalidae: Heliconiinae) is known for its striking diversity of wing color patterns driven by the Müllerian mimicry of multiple local models and controlled by a single supergene locus. Such fine‐scale variation of traits under strong selection offers a unique opportunity for the study of the ecology and genetics of adaptation. However, little is still known of the population processes driving geographical variation in wing‐pattern phenotypes. We report the characterization of 26 microsatellite markers for the butterfly H. numata, including six located inside the wing color‐pattern supergene region. All markers are polymorphic, with allele numbers ranging from 2 to 21 per locus, an observed heterozygosity of 0.111 to 0.848 and an expected heterozygosity of 0.126 to 0.942. A subset of 18 of these markers was tested on five closely related sympatric Heliconius species with an amplification success ranging from 88% to 94%. The obtained set of microsatellite markers provides a new and useful set of tools to investigate patterns of differentiation and selection in populations of mimetic Heliconius butterflies. Moreover, markers developed within the color‐pattern supergene will facilitate characterization of the association between the genetic architecture and the functional diversity of wing patterns. Finally, the cross‐species amplification success of the described markers extends their utility to also encompass comparative population genetic studies of closely related species within a clade of rapidly diversifying species.
Modeling the Environment in Deep Reinforcement Learning: The Case of Energy Harvesting Base Stations

In this paper, we focus on the design of energy self-sustainable mobile networks by enabling intelligent energy management that allows the base stations to mostly operate off-grid by using renewable energy. We propose a centralized control algorithm based on Deep Reinforcement Learning. The single agent is able to learn how to efficiently balance the energy inflow and spending among base stations observing the environment and interacting with it. In particular, we provide a study on the performance achieved by this approach when considering different representations of the environment. Numerical results demonstrate that using a good level of abstraction in the choice of the representation variables may enable a proper mapping of the environment into actions to take, so as to maximize the numerical reward.
Nonparametric bivariate distribution estimation using Bernstein polynomials under right censoring

Abstract The paper deals with non parametric estimation of the joint distribution function of two random variables X and Y. Especially, we consider the case when one of the two variables, says Y, is subject to right censoring. The newly proposed estimator is built using Bernstein polynomials. The asymptotic properties of this estimator such as, bias, variance and normality are provided. Also, we prove the strong uniform convergence. The proposed estimator is applied to analyze the Loss-ALAE dataset from insurance.
Developing English modules with integrated Islamic values and the Jambi local wisdom

Since studies about integrating Islamic values and local wisdom, especially in the Jambi context, have been scarcely found in the literature, this research is aimed to investigate the integration of such values in the English module that is suitable and practical for high school students. This developmental research used ADDIE approach which consists of five stages: analyze, design, develop, implement and evaluate. The sample for this study was an English teacher and 38 students of class IX of at one of the Islamic junior high school in Jambi by using instrument interviews, observation, and questionnaires. Based on the result of the validity questionnaire by two expert validators, a mean percentage of 82.07% is obtained and categorized as very valid. The result of students’ practicality questionnaire shows a percentage of 83.86% and categorized as very practical. Meanwhile, the result of teachers’ practicality is 87.50%, and also categorized as very practical. It could be concluded that the integrated Islamic values and Jambi local wisdom on the English module is suitable, practical and beneficial for both students and teacher. The researcher further recommends using this module for teaching English, especially for the procedure text type as discussed in the paper.
Exact Sparse Nonnegative Least Squares

We propose a novel approach to solve exactly the sparse nonnegative least squares problem, under hard ℓ0 sparsity constraints. This approach is based on a dedicated branch-and-bound algorithm. This simple strategy is able to compute the optimal solution even in complicated cases such as noisy or ill-conditioned data, where traditional approaches fail. We also show that our algorithm scales well, despite the combinatorial nature of the problem. We illustrate the advantages of the proposed technique on synthetic data sets, as well as a real-world hyperspectral image.
Hisse Senedi Piyasasında Likidite ve Getiri Oynaklığı İlişkisi: Borsa İstanbul Örneği (The Relationship between Liquidity and Return Volatility in the Stock Market: The Case of Borsa İstanbul)

Purpose – The aim of this study is to empirically analyze the existence and direction of the relationship between liquidity and return volatility in Borsa Istanbul for the period of January 2008 - August 2019 using different liquidity measures. Design/methodology/approach – The relationship between liquidity level and return volatility is investigated under VAR model by using Granger (1969) causality test and generalized impulse response analysis. In this context, three liquidity measures are formed in order to represent liquidity: high-low range, Amihud illiquidity measure and volatility over volume ratio. Return volatility is estimated by GARCH (1,1) model. Findings – The findings reveal a bi-directional Granger causality relationship between all liquidity measures and the return volatility for Borsa Istanbul. Impulse response analyses show that a shock to the liquidity level increases the return volatility rapidly and this effect is long lasting. On the other hand, the findings suggest that a shock to return volatility reduces the liquidity level, but the response is less than the return volatility gives to the liquidity level. Discussion – The study supports firms and policy makers to take measures to increase liquidity. In this context, it would be useful to focus on the determinants of liquidity in the future studies.
Antibacterial Activity of Ulva fasciata against Multidrug Resistant Bacterial Strains

The present study was conducted to evaluate the antibacterial activity of different organic solvent increasing polarity viz., hexane, chloroform, ethyl acetate, acetone and methanol extracts of Ulva fasciata (Chlorophyceae) were collected from Kanniyakummari, Gulf of Mannar biosphere Reserve, Tamilnadu, India. Marine green algae extracts of U. fasciata against multi-drug resistant standard and clinical bacterial strains viz., Bacillus subtilis, Streptococcus pyogenes, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Salmonella typhimurium, Vibrio cholerae, Shigella flexneri, Proteus mirabilis and P. vulgaris. The ethyl acetate extracts of U. fasciata showed highest antibacterial activity against all the bacterial strains tested. The mean zone of inhibition produced by the extracts in disc diffusion assays were ranged from 7.1 mm to 15.0 mm. The Minimum Inhibitory Concentrations (MIC) were between 125 μg/ml and 500 μg/ml, while the Minimum Bactericidal Concentrations (MBC) were between 250 μg/ml and 1000 μg/ml. The highest mean of zone inhibition (15.0 mm) and lowest MIC (125 μg/ml) and MBC (250 μg/ml) values were observed in ethyl acetate extract of U. fasciata against B. subtilis. The ethyl acetate extract of the U. fasciata showed the presence of phytochemicals, terpenoids, tannins and phenolic compounds in U. fasciata than the other solvents extracts. The present results of the ethyl acetate extract of U. fasciata can be used as an antibacterial substance for the treatment of multi drug resistant bacterial infections
Enabling Efficient Coexistence of DSRC and C-V2X in Vehicular Networks

Radio access technologies, such as C-V2X and DSRC, have been used to support robust communication in connected vehicles scenarios. However, existing studies mostly dealt with homogenous vehicular networks, where coexistence of different radio access technologies in vehicles are not considered. More precisely, such multi-radio interface environments burden communications among vehicles. In this article, we first review DSRC and C-V2X radio access technologies and existing packet relaying mechanisms that are specifically designed for homogenous or heterogeneous vehicular environments. We then present a quality of service aware relaying algorithm (QR) that incorporates multi-metric to prioritize dual interface vehicles (DVs) and provides robust communications among vehicles that are equipped with different radio access technologies. The simulation results confirm the superiority of the proposed QR in terms of message reception and relaying count as compared to the standard protocols.
Evaluation And A Reconcile Analysis Of Lda And Svm Category

: Fixed sequence classification is an important task in data mining. The problem of sequence classification is the use of rules consisting of interesting items that are contained in the data sets labeled sequences and the included class labels. Interesting levels are calculated from a set of items that are in a class ordered by linking and maintaining each item. There are a number of security patterns that may be hidden in the database. A mining algorithm looks for a complete set of patterns and meets the minimum support threshold (frequency), highly efficient and scalable, with a number of database scans incorporating various types of user-specific constraints. In the existing system, sequence classification techniques use several machine learning algorithms such as NaiveBayes, neighboring K-neighbors, decision trees, hidden markov models, SVM. This exit methodology can handle cases of minor deviations in certain events and acknowledges the occurrence of the pattern several times. In this work, LDA classifiers are used to classify and train datasets to improve dataset accuracy and efficiency to facilitate user analysis. Machine learning process is implemented to maintain the effectiveness of the prediction methodology. LDA prediction compared to SVM to prove performance improvement and linear classification id is used to improve classifier accuracy. Finally, the quality of the miner pattern is evaluated by the proposed approach pattern as features in several classification features based on different features.
Mediating Role of Customer Experience in Social Media Marketing and
Purchase Intention: A Case Study

In today’s dynamic business environment, the idea of customer experience gained significant importance among practitioners as well as academics. Many managers and service researchers are interested in customer experience. However, research on customer experience about social media marketing role on building purchase intention appears to be scarce. This work investigates the mediating role of customer experience in social media marketing and customer purchase intention in lifestyle products. Data for the study were collected from 279 Indian consumers using a survey by personal visiting and contacting prospective respondents located at different places in Lucknow city, India. The study found that customer experience mediate social media marketing activities and purchase intention relationship. Customer experience and social media marketing are correlated, and both of them together affect purchase intention of customer. The current study model confirms that social media build up customer experience, which in turn affects purchase intention. It is surprising that the effect of social media on purchase intention was insignificant. This study recommends that marketers should use social media marketing to enhance customer engagement and relationships, provide valuable information, reinforce their brand choice, and subsequently strengthen customer experience.
Projected Weight Regularization to Improve Neural Network Generalization

Generalization of a deep neural network (DNN) is one major concern when employing the deep learning approach for solving practical problems. In this paper we propose a new technique, named projected weight regularization (PWR), to improve the generalization capacity of a DNN model. Consider a weight matrix W from a particular neural layer in the model. Our objective is to make the eigenvalues of the matrix product WWT have comparable or roughly the same magnitudes while allowing the DNN model to fit the training data sufficiently accurate. Intuitively speaking, by doing so, it would prevent the W matrix from matching the training data too well. Specifically, at each iteration, we first project the W matrix to a number of vectors along randomly generated directions. After that, we build an objective function of the projected vectors to regularize their behaviours towards comparable eigenvalue magnitudes of WWT. Experimental results on training VGG16 for CIFAR10 show that PWR combined with centered weight normalization (CWN) yields promising validation performance compared to orthonormal regularisation combined with CWN.
Heat, Salinity, and Acidity, Commonly Upregulate A1aB1b Proglycinin in Soybean Embryonic Axes

Patricia Arce-Paredes1, Rosalva Mora-Escobedo1, Juan Pedro Luna-Arias2, Guillermo Mendoza-Hernandez3 and Oscar Rojas-Espinosa1 1Departamentos de Ingenieria Bioquimica e Inmunologia, Escuela Nacional de Ciencias Biologicas, Instituto Politecnico Nacional, Mexico D.F. , 2Departamento de Biologia Celular, Centro de Investigacion y Estudios Avanzados, Instituto Politecnico Nacional, Mexico D.F. , 3Departamento de Bioquimica, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico D.F. Mexico
A Study of Effect of BMI on Pulmonary Function Tests in Young Individuals at Rajkot City

Background: Obesity is a complex, multi-factorial, chronic condition that is associated with mortality and significant morbidity and is prevalent worldwide. The aim of the study is to determine the effect of obesity on pulmonary function abnormality in young adults in our population. Method: A cross sectional study on 140 individuals, selected randomly from general population of Rajkot city was performed. A thorough history analysis (Height, Weight, BMI), Physical examinations Spirometry were done on all individuals after explaining the procedure and taking their consent. Parameters measured by the spirometer were FEV1, FVC, FEV1/FVC, PEFR, ERV, IC, EC, VC. Result & conclusion: It was observed that lung volumes decreased with statistically significant decreased ERV (0.66±0.09 L) & FVC (3.10±0.91) as the BMI increases (30-35Kg/m 2 ). Negative correlation was found between BMI and ERV (-0.307) at higher BMI Values.
Benthic foraminifera as tracers of brine production in the Storfjorden “sea ice factory”

Abstract. The rapid response of benthic foraminifera to environmental factors (e.g. organic matter quality and quantity, salinity, pH) and their high fossilisation potential make them promising bio-indicators for the intensity and recurrence of brine formation in Arctic seas. Such an approach, however, requires a thorough knowledge of their modern ecology in such extreme settings. To this aim, seven stations along a north–south transect across the Storfjorden (Svalbard archipelago) have been sampled using an interface multicorer. This fjord is an area of intense sea ice formation characterised by the production of brine-enriched shelf waters (BSW) as a result of a recurrent latent-heat polynya. Living (rose bengal-stained) foraminiferal assemblages were analysed together with geochemical and sedimentological parameters in the top 5 cm of the sediment. Three major biozones were distinguished. (i) The “inner fjord” zone, dominated by typical glacier proximal calcareous species, which opportunistically respond to fresh organic matter inputs. (ii) The “deep basins and sill” zone, characterised by glacier distal agglutinated fauna; these are either dominant because of the mostly refractory nature of organic matter and/or the brine persistence that hampers the growth of calcareous species and/or causes their dissolution. (iii) The “outer fjord” zone, characterised by typical North Atlantic species due to the intrusion of the North Atlantic water in the Storfjordrenna. The stressful conditions present in the deep basins and sill (i.e. acidic waters and low food quality) result in a high agglutinated ∕ calcareous ratio ( A∕C ). This supports the potential use of the A∕C ratio as a proxy for brine persistence and overflow in Storfjorden.
Compartmentalization of Peyer’s Patch Anlagen Before Lymphocyte Entry1

We have shown that Peyer’s patch (PP) first develops as a simple and even cell aggregation during embryogenesis. To investigate when and how such a simple cell aggregation forms the complex PP architecture, we analyzed the distribution of cells expressing IL-7Rα (PP inducer cells), VCAM-1 (mesenchymal cells), CD11c (dendritic cells), and mature lymphocytes by whole-mount immunostaining of 17.5 days postcoitus to 2 days postpartum mouse gut. Our results show that compartmentalization of PP anlagen commences at day 18.5 of gestation by clustering and subsequent follicle formation of IL-7Rα+, VCAM-1+, and CD11c+ cells. This process adds the primitive architecture of PP anlage with several follicles in which IL-7Rα+ cells localize in the center, while VCAM-1+ and CD11c+ cells localize at the fringe. This follicle formation is accompanied by the establishment of PP-specific vascular network expressing mucosal addressin cellular adhesion molecule-1. Mature B and T lymphocytes entering in the PP anlage are distributed promptly to their own target zones; B cells to the follicle and T cells to nonfollicular zones. Our analysis of scid/scid mouse indicate that the initial processes including formation of PP-specific vascular network occur in the absence of lymphocytes. These observations indicate that the basic architecture of PP is formed by a set of cell lineages assembled during the initial phase of induction of PP anlagen before entry of mature lymphocytes.