Miracle-dz/UniFAR-FTUs huggingface dataset:
Querying capability comparison of Hadoop technologies to find the more sustainable platform for big data

Big Data analytics is an upcoming field in the world of computing. It has much more complex requirements for processing and maintenance and thus it should be dealt using high-end servers. So, in turn, it has a lot more energy requirements. High energy requirements can lead to more energy wastage which is not a sustainable practice. In this paper, the comparison is done between 3 platforms that provide the framework for big data management. The platforms are Hive, Impala, and Spark. Many other platforms are also available but these three have been chosen because they can be easily implemented on even a single node Hadoop cluster. The results have shown that Cloudera Impala outperforms both the other platforms as it takes approximately 90% lesser time to do the same task.
Concise semantic analysis based text categorization using modified hybrid union feature selection approach

Text categorization mainly comprises of deriving a representation of the corpus in a standard bag-of-words format. The merit of bag-of-word representations is that they considering every term as a feature, while the downside of this is that the computation cost increases with the number of features and the representation of relations between documents and features. Semantic analysis can help in gaining an edge through document and term correlation in a concept space. However, most semantic analysis techniques have their own limitations when used for text categorization. In this work, a Concise Semantic Analysis (CSA) technique that extracts concepts from corpus and then interpret the document & word relationship in a given concept space is proposed. To improve the performance of CSA, a novel feature selection technique called the Modified hybrid union (MHU) was designed, which considerably reduced computation time and cost. To experimentally validate the proposed approach, MHU based CSA was applied to the problem of text categorization. Experiments performed on standard data sets like Reuters-21578 and WSDL-TC, show that the proposed CSA with MHU approach significantly improved performance in terms of execution time and categorization accuracy.
Multiclass genetic programming based approach for classification of intrusions

Classification plays a major role in distinguishing the normal traffic from the intrusive ones in any intrusion detection system. Different approaches have been used by various researchers to improve the accuracy of the classifiers for binary and multiclass classification problems. Genetic programming (GP) algorithms have been applied in the previous studies and have confirmed that it performs well for classification problems. In our work, we have used a variation of the mutation operation which will be applied when the fitness of the individual does not change significantly for a specified number of generations. Several experiments were conducted using the standard GP method and using the modified mutation operation and the results obtained show that our approach gives good results for multiclass problem in comparison to the standard GP method.
Mesenchymal stem cells home to but do not modulate acute renal injury in a canine model

Background: Acute kidney injury (ARI) is a common clinical event that occurs in 5-35% of all hospitalized patients and is associated with a two- to five fold increased mortality risk. , with no significant improvement on pharmacologic therapy. The need for better treatment strategies for ARI called for cellular based strategies aiming to regenerate damaged tissues. Mesenchymal stem cells (MSCs) hold special promise in attenuating kidney injury, since nephrons are largely of mesenchymal origin. Objectives: The objective of this study is to evaluate the role of bone marrow derived (MSCs) in regeneration of post-ischemic acute renal injury in mongrel dogs. Material and Methods: Fifteen adult male mongrel dogs were used in this study. Animals were divided into: Group I, normal group (3 dogs); Group II, nine dogs subjected to ischemic/reperfusion injury (IRI) by clamping both renal pedicles for 60 minutes and not subjected to stem cell therapy which were further divided into: 6 dogs without sham injection, 3 sacrificed 3 days and 3 after 7 days after IRI and 3 dogs with sham injection sacrificed 7 days after IRI. and Group III (3 dogs) which underwent IRI and received systemic autologous MSC injection. This group underwent aspiration of 15-20 ml bone marrow from posterior iliac spine, mononuclear cell separation and MSC separation. MSCs were tagged by iron oxide and injected in a dose of 2million /kg systemically through the femoral vein. Evaluation of Therapeutic Effect: 1. Functional evaluation of renal functions using serum creatinine preoperative and 30 minutes, 1 day, 2days, 4days, 7days postoperative.2. Renal histology and injury scores: using H&E, PAS using morphometry. 3. Tracing of injected MSCs (homing) in renal tissues using Prussian blue staining . 4. Immunohistochemical evaluation of the apoptosis and proliferative capacity of MSCs using caspase3 and KI 67. Results: Bone marrow derived MSCs were found in the renal cortex and medulla, epithelial lining of the cortical tubules, glomeruli, the Bowman's space, in some peritubular capillaries and among the epithelial lining of the renal tubules of treated animals. However,MSCs did not undergo trans- differentiation to renal cells, There was no difference in the regeneration, apoptosis or proliferation between treated and non-treated animals. Conclusions: Injected MSCs homed to but did not affect regeneration of renal tissue after acute injury. Although MSCs did not prove to differentiate into renal tissue, they can be used as vehicles for cytokines or growth factors as they home to injured sites.
SRB-2: a promiscuous rainbow aptamer for live-cell RNA imaging

Abstract The SRB-2 aptamer originally selected against sulforhodamine B is shown here to promiscuously bind to various dyes with different colors. Binding of SRB-2 to these dyes results in either fluorescence increase or decrease, making them attractive for fluorescence microscopy and biological assays. By systematically varying fluorophore structural elements and measuring dissociation constants, the principles of fluorophore recognition by SRB-2 were analyzed. The obtained structure-activity relationships allowed us to rationally design a novel, bright, orange fluorescent turn-on probe (TMR-DN) with low background fluorescence, enabling no-wash live-cell RNA imaging. This new probe improved the signal-to-background ratio of fluorescence images by one order of magnitude over best previously known probe for this aptamer. The utility of TMR-DN is demonstrated by imaging ribosomal and messenger RNAs, allowing the observation of distinct localization patterns in bacteria and mammalian cells. The SRB-2 / TMR-DN system is found to be orthogonal to the Spinach/DFHBI and MG/Malachite green aptamer/dye systems.
Achieving Dynamic Capabilities Through the Benefits Management Approach

The IS/IT has played a key role in the improvement of business strategies and in changing skills and organizational capabilities. However, the promised benefits of these investments have been difficult to monitor, implement and account for. Benefits Management (BM) is becoming an increasingly important approach for projects which implement IS/IT investments. The authors' motivation was answer to the following research question: How BM can help organizations obtain the Dynamic Capabilities (DC) required to meet the growing market challenges? This paper proposes a framework for assisting organizations identify and monitor the benefits of IS/IT investments, and for leveraging through IS/IT the internal changes necessary to quickly respond to the demands presented by the dynamic business environment. The authors' research approach explored an enriched single case study. They conducted an in-depth and multi-faceted exploration, collecting and using data from documentation, archival records, interviews, direct and participant observations.
Applicability of No-Reference Visual Quality Indices for Visual Security Assessment

From literature it is known that full-reference visual quality indices are a poor fit for the estimation of visual security for selective encryption. The question remains whether no-reference visual quality indices can perform where full reference indices falter. Furthermore, no-reference visual quality indices frequently use machine learning to train a model of natural scene statistics. It would be of interest to be able to gauge the impact of learning statistics from selectively encrypted images on performance as quality estimators for encryption. In the following we will answer these two questions.
Phytochemical screening and antibacterial activity of Vigna radiata L. against bacterial pathogens involved in food spoilage and food borne diseases

Chemical preservatives have been used in the food industry for many years. However, with increased health concerns, consumers prefer additive-free products or food preservatives based on natural products. In this context, this study evaluated antibacterial activities of extracts from Vigna radiata L. belonging to the Fabaceae family, to explore their potential for use against pathogens causing food borne diseases so that new food preservatives may be developed. Sprouted seeds of V. radiata were extracted with three different solvents such as methanol, ethyl acetate and hexane The antibacterial potentiality using solvent extracts were studied by agar well diffusion and broth dilution method against antibiotic resistant food borne or food spoilage pathogenic bacteria. The methanol extracts showed significant concentration dependent antibacterial activity against almost all the test pathogens. Qualitative phytochemical tests and thin layer chromatography of active methanolic extract demonstrated the presence of various phytochemicals in V. radiata including glycosides, steroids, phenols, saponins, alkaloids and flavonoids as major active constituents. This study assumes much significance in finding antibacterial phytochemicals from the sprouts of V. radiata and the study has to be proceeded further to isolate, purify and characterize the active principle.
1 Strategies to Engage Adolescents in Digital Health 2 Interventions for Obesity Prevention and 3 Management 4

Obesity is one of the greatest health challenges facing today’s adolescents. Dietary 15 interventions are the foundation of obesity prevention and management. As adolescents are digital 16 frontrunners and early adopters of technology, digital health interventions appear the most practical 17 modality for dietary behaviour change interventions. Despite the rapid growth in digital health 18 interventions, effective engagement with adolescents remains a pertinent issue. Key strategies for 19 effective engagement include co-designing interventions with adolescents, personalisation of 20 interventions, and just-in-time adaptation using data from wearable devices. The aim of this paper 21 is to appraise these strategies, which may be used to improve effective engagement and thereby 22 improve the dietary behaviours of adolescents now and in the future. 23
Role of Oxygen for Boron Diffusion From Borosilicate Glass Layers Deposited by Atmospheric Pressure Chemical Vapor Deposition

We investigate the impact of different oxygen concentrations during boron diffusion at 950°C using borosilicate glass (BSG) layers deposited by atmospheric pressure chemical vapor deposition. Therefore, we vary the boron concentration in the BSG layer and the oxygen concentration in the gaseous ambient of the high-temperature step. Characterization includes sheet resistance as well as electrochemical capacitance voltage measurements for the determination of the resulting boron doping profile. In addition, we perform quasi steady-state photoconductance measurements to investigate the influence of the oxygen concentration on the recombination parameters of the boron-diffused surface. Low recombination current densities J0 of J0 = 38 fA/cm² at a sheet resistance of 54 Ω/sq are observed. Finally, we show that the oxygen concentration is a crucial parameter to prevent the formation of a boron-rich layer at the silicon surface.
The Sharing Economy as a Local Economic Engine: The Heterogeneous Impact of Airbnb on Restaurant Employment Growth

This paper examines the heterogeneous economic spillover effects of a home sharing platform—Airbnb—on the growth of a complimentary local service—restaurants. By providing access to underutilized inventory Airbnb is attracting the visitors of a city to vicinities without a significant hotel presence. These visitors generally have two options. On the one hand, they may simply use the local area for lodging and commute to more traditional tourist and business localities regularly. On the other hand, they may utilize the market structure of the local community and, as a result, bring with them significant spending power. To evaluate the economic spillover effect of this spending, we focus on the impact of Airbnb on the employment growth of New York City (NYC) restaurants. Our results indicate that if the intensity of Airbnb activity (Airbnb reviews per household) increases by 2.5% in a neighborhood with the median number of households (79,000), then the restaurant employment in that neighborhood grows by approximately 3.8%. We validate the underlying mechanism behind this result—Airbnb visitors frequent local restaurants—by evaluating the impact of Airbnb on Yelp visitor reviews. In particular, neighborhoods with increasing Airbnb activity also experience a surge in their share of NYC visitor reviews. To delineate the intricacies of Airbnbs effect across localities, we investigate the role of demographics and market concentration in driving the variation. Notably, restaurants in areas with a relatively high number of Black residents or a relatively high number of Hispanic residents do not seem to benefit from the economic spillover of Airbnb activity.
The Use of Clinical Registries in the United States: A Landscape Survey

Introduction: The use of information from clinical registries for improvement and value-based payment is increasing, yet information about registry use is not widely available. We conducted a landscape survey to understand registry uses, focus areas and challenges. The survey addressed the structure and organization of registry programs, as well as their purpose and scope. Setting: The survey was conducted by the National Quality Registry Network (NQRN), a community of organizations interested in registries. NQRN is a program of the PCPI, a national convener of medical specialty and professional societies and associations, which constitute a majority of registry stewards in the United States. Methods: We surveyed 152 societies and associations, asking about registry programs, governance, number of registries, purpose and data uses, data collection, expenses, funding and interoperability. Results: The response rate was 52 percent. Many registries were self-funded, with 39 percent spending less than $1 million per year, and 32 percent spending $1-9.9 million. The typical registry had three full-time equivalent staff. Registries were frequently used for quality improvement, benchmarking and clinical decision support. 85 percent captured outpatient data. Most registries collected demographics, treatments, practitioner information and comorbidities; 53 percent captured patient-reported outcomes. 88 percent used manual data entry and 18 percent linked to external secondary data sources. Cost, interoperability and vendor management were barriers to continued registry development. Conclusions: Registries captured data across a broad scope, audited data quality using multiple techniques, and used a mix of automated and manual data capture methods. Registry interoperability was still a challenge, even among registries using nationally accepted data standards.
The association between “Brain‐Age Score” (BAS) and traditional neuropsychological screening tools in Alzheimer's disease

We present the Brain‐Age Score (BAS) as a magnetic resonance imaging (MRI)‐based index for Alzheimer's disease (AD). We developed a fully automated framework for estimating the BAS in healthy controls (HCs) and individuals with mild cognitive impairment (MCI) or AD, using MRI scans.
Data mining techniques for IoT and big data — A survey

Data Mining is the discovery of “models” of data. Data dredging is a process of derogatory referring to attempts for extracting information that was not supported by the data. Today, data mining is more similar to machine learning and most techniques uses algorithms from machine learning in order to discover unusual events hidden within the large amounts of data. The recent advancements in communication technology, people and the things are becoming increasingly interconnected. The availability of the Internet makes it possible to connect various devices that can communicate with each other and share data. The Internet of Things (IoT) is a new concept that allows users to connect various sensors and smart devices to collect real-time data from the environment. Big Data is a vast amount of data collected from IoT environment and it applies to information that can't be processed or analyzed using traditional tools. Every organization is facing more and more challenges to access a wealth of information and how to get values out of large variety of data. As creation of data is much easier than analyzing it, there is a need for Novel approaches in data mining techniques to deal with huge data. From the perspective of software, the traditional mining algorithms are applicable only for small scale IoT data. This paper first focuses on a review of existing techniques and data mining algorithms that are used to process massive data of IoT and also the limitations are discussed. Second, the work and advancements related to data mining algorithms that are implemented with Hadoop and Spark technology are presented. Third, Hybrid data mining algorithms using MapReduce framework are reviewed. Finally, open research challenges and issues are presented as a conclusion.
Hormonal Contraceptive Use Does Not Affect Strength, Endurance, or Body Composition Adaptations to Combined Strength and Endurance Training in Women.

Myllyaho, MM, Ihalainen, JK, Hackney, AC, Valtonen, M, Nummela, A, Vaara, E, Häkkinen, K, Kyröläinen, H, and Taipale, RS. Hormonal contraceptive use does not affect strength, endurance, or body composition adaptations to combined strength and endurance training in women. J Strength Cond Res XX(X): 000-000, 2018-This study examined the effects of a 10-week period of high-intensity combined strength and endurance training on strength, endurance, body composition, and serum hormone concentrations in physically active women using hormonal contraceptives (HCs, n = 9) compared with those who had never used hormonal contraceptives (NHCs, n = 9). Training consisted of 2 strength training sessions and 2 high-intensity running interval sessions per week. Maximal bilateral isometric leg press (Isom), maximal bilateral dynamic leg press (one repetition maximum [1RM]), countermovement jump (CMJ), a 3,000-m running test (3,000 m), body composition, and serum hormone levels were measured before and after training between days 1-5 of each subject's menstrual cycle. Both groups increased 1RM and CMJ: HC = 13.2% (p < 0.001) and 9.6% (p < 0.05), and NHC = 8.3% (p < 0.01) and 8.5% (p < 0.001). Hormonal contraceptive improved 3,000 m by 3.5% (p < 0.05) and NHC by 1% (n.s.). Never used hormonal contraceptive increased lean mass by 2.1% (p < 0.001), whereas body fat percentage decreased from 23.9 ± 6.7 to 22.4 ± 6.0 (-6.0%, p < 0.05). No significant changes were observed in body composition in HC. No significant between-group differences were observed in any of the performance variables. Luteinizing hormone concentrations decreased significantly (p < 0.05) over 10 weeks in NHC, whereas other hormone levels remained statistically unaltered in both groups. It seems that the present training is equally appropriate for improving strength, endurance, and body composition in women using HC as those not using HC without disrupting hypothalamic-pituitary-gonadal axis function.
Colorimetric in situ assay of membrane-bound enzyme based on lipid bilayer inhibition of ion transport

Membrane-bound enzymes (MBEs), which make up a very high proportion of intracellular enzymes, catalyze a variety of activities that are currently analyzed by various techniques after purification. However, due to their amphipathic character, the purification of MBEs is difficult. Therefore, the most productive approach represents in situ analysis of MBEs in the cellular membrane. Methods: In this study, using membrane-bound α-glucosidase (α-Glu) as an example, we have developed a colorimetric in situ assay for MBEs based on the inhibitory effect of lipid bilayer on ion transport. The enzyme substrate could mediate the self-assembly of phospholipid PEG derivative around magnetic nanospheres that were modified with boronic acid. The formation of lipid bilayer could inhibit the leaking of iron ions under acidic conditions. However, the product of the catalytic reaction had no capability for self-assembly of the lipid bilayer, leading to the release of iron ions from the magnetic nanospheres under acidic pH. Results: The colorimetric in situ assay for MBEs could not only analyze the activity of membrane-bound α-Glu located on Caco-2 cells but could also evaluate the α-Glu inhibitors in cell medium. Conclusions: The simple, economic, and efficient method proposed here offers a potential application for high-throughput testing of α-Glu and its inhibitors. Our study also outlines a strategy for exploring the colorimetric method to detect the activities of MBEs in situ.
Construction and characterization of a new TRAIL soluble form, active at picomolar concentrations

Apoptosis induction has emerged as a treatment option for anticancer therapy. Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), a type II transmembrane protein, is a potent and specific pro-apoptotic protein ligand, which activates the extrinsic apoptosis pathway of the cell death receptors. Here we describe the construction and characterization of a new soluble TRAIL, sfTRAIL, stabilized with the trimerization Foldon domain from the Fibritin protein of the bacteriophage T4. Supernatants of 0.22 μM-filtered supernatants were produced in Vero-transduced cells with HSV1-derived viral amplicon vectors. Experiments were undertaken in two known TRAIL-sensitive (U373 and MDA.MB.231) and two TRAIL-resistant (MCF7 and A549) cell lines, to determine (i) whether the sfTRAIL protein is synthetized and, (ii) whether sfTRAIL could induce receptor-mediated apoptosis. Our results showed that sfTRAIL was able to induce apoptosis at concentrations as low as 1899.29 pg/mL (27.71 pM), independently of caspase-9 activation, and reduction in cell viability at 998.73 fM.