nils-herrmann/clean_scirepeval huggingface dataset:
Effect of sleep deprivation on the attitude and performance of medical students, Riyadh, Saudi Arabia

Sleep is crucial for learning, performance, and physical and mental health. College students often have erratic sleep schedules, poor sleep hygiene, and correspondingly poor sleep quality, which might affect their performance.  To study the effect of sleep deprivation on medical students at different academic levels and investigate causes of sleep deprivation affecting them and problems related to it.  This cross sectional study was conducted in September 2012. The participants were medical students of the first, second, third, fourth, and fifth academic years in the College of Medicine, King Saud University, Riyadh, Saudi Arabia.  There were 341 responses, with a response rate of 88.8% The number of medical students who had normal sleeping hours was 104 (53.1% male students and 71 (49% female students. The prevalence of sleep deprivation was more among male students (62 [31.6% as compared with female students (42 [29% P value was 0.278. Fifth level students were more deprived on weekdays and weekends than other level students with P value 0.216 and 0.001, respectively. There was a significant difference in the grade point average (GPA) in relation to sleep deprivation. The number of students who got GPA 4 or more and who were sleep deprived was 68 (65.4% whereas the number of those who were not sleep deprived was 180 (83% (P 0.0004)  The most common cause of sleep deprivation among medical students was studying. Certain sleep disorders were found in this group of students, the most common one was not getting enough sleep time. Sleep deprivation was negatively associated with academic performance in the medical students. It is the role of the educators and college authorities to empower and educate college students about good sleep habits to improve their performance.
Prevalence of poor sleep quality in college students of Iran: Systematic review and Meta analysis

Prevalence of poor sleep quality in college students of Iran: Systematic review and Meta analysis Mehdi Ranjbaran Department of Epidemiology and Reproductive Health, Reproductive Epidemiology Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran *Corresponding author) Mahboobeh Khorsandi, PhD, Associate Professor of Health Education, Department of Health Education and Health Promotion, School of Health, Arak University of Medical Sciences, Arak, Iran. dr.khorsandi@arakmu.ac.i r  Students sleep pattern, due to the stress of studying and teaching workload are different with other non student peers. The aim of this study was to determine the prevalence of poor sleep quality in college students of Iran by a meta analysis study, to be as a final measure for policy makers in this field.  In this meta analysis study, the databases of PubMed, Science Direct, Scopus, Google Scholar and interior databases were searched up to November, 2014. Between the studies with regard to the inclusion and exclusion criteria, 15 studies were selected. Data analyzed by using Stata11 software. Publication bias was assessed by Begg and Egger tests. Also heterogeneity assessed by Cochran's Q statistic and I2 index. Couse of heterogeneity was evaluated by using meta regression.  Total samples in the 15 studies were 3260. Begg and Egger tests with the P value of 0.88 and 0.15 respectively, indicated the absence of publication bias. Cochran's Q statistic and I2 index revealed heterogeneity of the samples (Q=975.26, P value <0.001 and I2= 98.6) Overall prevalence of poor sleep quality in student based on the random effect was obtained 56.0% (95% CI: 43.2 68.7)  Considering the high prevalence of sleep quality and its increase in previous years, detection of affecting factors, intervention and preventive actions, and education about the importance of sleep and time management skills in students seem essential.  sleep quality, students, meta analysis, Iran
Should we treat obesity in COPD? The effects of diet and resistance exercise training
Venue: Respirology

Obesity is an established risk factor for poor health outcomes, but paradoxically in chronic obstructive pulmonary disease (COPD) it is associated with improved survival and lung function. A major evidence gap exisits to inform treatment recommendations for patients with COPD who are obese. We aimed to determine the effect of weight reduction involving a low energy diet utilizing a partial meal replacement plan, coupled with resistance exercise training in obese COPD patients.
The activated sludge ecosystem contains a core community of abundant organisms
Venue: The ISME Journal

Understanding the microbial ecology of a system requires that the observed population dynamics can be linked to their metabolic functions. However, functional characterization is laborious and the choice of organisms should be prioritized to those that are frequently abundant (core) or transiently abundant, which are therefore putatively make the greatest contribution to carbon turnover in the system. We analyzed the microbial communities in 13 Danish wastewater treatment plants with nutrient removal in consecutive years and a single plant periodically over 6 years, using Illumina sequencing of 16S ribosomal RNA amplicons of the V4 region. The plants contained a core community of 63 abundant genus level operational taxonomic units (OTUs) that made up 68% of the total reads. A core community consisting of abundant OTUs was also observed within the incoming wastewater to three plants. The net growth rate for individual OTUs was quantified using mass balance, and it was found that 10% of the total reads in the activated sludge were from slow or non growing OTUs, and that their measured abundance was primarily because of immigration with the wastewater. Transiently abundant organisms were also identified. Among them the genus Nitrotoga (class Betaproteobacteria) was the most abundant putative nitrite oxidizer in a number of activated sludge plants, which challenges previous assumptions that Nitrospira (phylum Nitrospirae) are the primary nitrite oxidizers in activated sludge systems with nutrient removal.
A Study About Life Style of Jenu Kuruba Tribes Working as Unorganised Labourers

Tribals usually are primitive people, living socially as homogeneous unit with their own culture different subsistence pattern, custom, superstitious beliefs, distinct life style living in isolation from outside influence. Forests are closely associated with the tribal economy and culture. Foreign invasion affected tribal life by assimilating through invading their culture. The independent India saw the legal takeover of prime tribal lands in the name of development dispelling millions of tribes. The Government of India adopted a policy to integrate tribes with modernization by encouraging partnership between the tribes and non tribes. The policy of integration or progressive acculturation has laid the foundation for the march of the tribes towards Equality, Upward Mobility, Economic viability and National mainstreaming. The tribes who are very backward are grouped into 'Primitive Tribes' having a low level of literacy, declining in population, poor technological access and extreme economic backwardness. Jenu Kuruba Tribes are one of the vulnerable Tribal Groups living in the state of Karnataka. This paper examines the socio economic life of Jenu Kuruba Tribes covering personal profile, economic condition, literacy, housing pattern and the use of welfare schemes. This research will suggest ways for new interventions to solve the problems through the collective intervention of government officials, local administration, social workers, and the general public.
A review on the applications of neuro fuzzy systems in business
Venue: Artificial Intelligence Review

This paper presents a review of the application of neuro fuzzy systems (NFS) in business on the basis of the research articles issued in various reputed international journals and conferences during 2005 2015. The use of NFS for tackling various real world problems in different business domains has diversified significantly during this period. In effect NFS has emerged as a dominant technique for addressing various difficult research problems in business. Based on a detailed review of these research papers we have identified finance, marketing, distribution, business planning, information systems, production and operations as the main business application domains of NFS during this period. This paper also discusses the impact of NFS in various business domains and the trend of this application based research during this period. This paper also surveys the various innovations in NFS methodologies employed by the researchers to deal with different business problems in each of these years. Moreover the paper includes some articles published during 2016 in several international journals to present the latest progress in the application of NFS in various business domains.
The Effect of Fluoropolymer on Wettability Alteration of Sandstone at Elevated Temperatures

Gas condensate reservoirs are generally recovered using a pressure depletion drive. Gas can condensate into the liquid phase near the wellbore region when the reservoir pressure falls below the dew point pressure, which can kill gas deliverability. Wettability alteration is an effective means of overcoming this problem; core wettability can be altered from liquid wet to gas wet to alleviate the effect of condensate accumulation near the wellbore region. To establish the effect of fluoropolymer on wettability alteration in a gas condensate reservoir, a gas wetting alteration agent was synthesized by emulsion polymerization using different molar ratios of fluorine containing monomers and acrylic monomers. FTIR and SEM were performed to analyze the structure of the gas wetting agent. Contact angle measurements were used to assess surface alteration by the Owens two liquid method. The effects of alteration agent concentration, salt concentration, pH and temperature on gas wetting alteration were also evaluated. Results showed that the best molar ratio of fluoropolymer monomer to acrylic monomers was 1:2. The egg like structure of the fluoropolymer latex on the core surface mainly contributes to gas wetting alteration. The contact angles of brine and oil can be altered from 23deg and 0deg to 137deg and 67deg by 1 wt% FP 2 treatment, respectively. The surface free energy of the core was reduced from 67.52 to 1.66 mN/m. Moreover, the treated cores remain gas wetting up to 100 g L 1 of salt solution, 120 degC and within the pH range of 5 7. This novel gas wetting alteration agent can be used to solve the problem of liquid blocking effects in gas condensate reservoirs and improve gas recovery significantly.
PENGARUH CUSTOMER EXPERIENCE TERHADAP REVISIT INTENTION DI THE TRANS LUXURY HOTEL BANDUNG :Survei pada wisatawan sebagai Individual First Timer Guest The Trans Luxury Hotel Bandung

Tourist's needs of hotel are going higher contributes to the development of the hotel industry in Bandung. In 2013, the number of 5 star hotel has 9 hotels. Among the nine hotels is The Trans Luxury Hotel which opened in 2012 with a 6 star hotel concept. Despite its young age, The Trans Luxury has been able to attract people to stay so the occupancy rate has been able to achieve an average occupancy rate in the city of Bandung. In a period of 20 months, the number of guests who stayed at The Trans Luxury Hotel Bandung was dominated by individual guests, as many as 64% while the number of business guests only reached 36% Overall, the number of individual guests who stayed at The Trans Luxury Bandung during the period May 2012 to December 2013 was as much as 43.212 persons. The number of individual guests who stayed at The Trans Luxury Hotel Bandung is still dominated by first timer guests in the amount of 63.38% so it can be identified that the guest's intent to return still very low. As a new hotel, The Trans Luxury Hotel Bandung also has a goal to get the loyal customers. In the process of achieving customer loyalty, The Trans Luxury trying to focus on the characteristics of loyalty, one of them with efforts to increase guest's intent in return to stay. In order to increase the guest's intent in return to stay, The Trans Luxury Hotel Bandung implementing marketing strategies that focus on the individual guests, one of which is to implement customer experience. In this study, the independent variable (X) which is used is the customer experience includes the physical environment and social interaction. The dependent variable (Y) is revisit intention. This type of research is descriptive verification, and the method used was a survey with simple random sampling technique, and then obtained a total sample of 100 respondents. Techniques of data analysis and hypothesis testing used is a multiple linear regression analysis. The results showed that there is a strong relationship between customer experience with revisit intention which is equal to 0.658 and simultaneously the customer experience effect on revisit intention of 43.3%
Metagenomic Based Screening and Molecular Characterization of Cowpea Infecting Viruses in Burkina Faso
Venue: PloS one

Cowpea, (Vigna unguiculata L. (Walp) is an annual tropical grain legume. Often referred to as "poor man's meat" cowpea is one of the most important subsistence legumes cultivated in West Africa due to the high protein content of its seeds. However, African cowpea production can be seriously constrained by viral diseases that reduce yields. While twelve cowpea infecting viruses have been reported from Africa, only three of these have so far been reported from Burkina Faso. Here we use a virion associated nucleic acids (VANA) based metagenomics method to screen for the presence of cowpea viruses from plants collected from the three agro climatic zones of Burkina Faso. Besides the three cowpea infecting virus species which have previously been reported from Burkina Faso (Cowpea aphid borne mosaic virus [Family Potyviridae] the Blackeye cowpea mosaic virus a strain of Bean common mosaic virus [Family Potyviridae] and Cowpea mottle virus [Family Tombusviridae] five additional viruses were identified: Southern cowpea mosaic virus (Sobemovirus genus) two previously uncharacterised polerovirus like species (Family Luteoviridae) a previously uncharacterised tombusvirus like species (Family Tombusviridae) and a previously uncharacterised mycotymovirus like species (Family Tymoviridae) Overall, potyviruses were the most prevalent cowpea viruses (detected in 65.5% of samples) and the Southern Sudan zone of Burkina Faso was found to harbour the greatest degrees of viral diversity and viral prevalence. Partial genome sequences of the two novel polerovirus like and tombusvirus like species were determined and RT PCR primers were designed for use in Burkina Faso to routinely detect all of these cowpea associated viruses.
Bradyrhizobium Inoculants Enhance Grain Yields of Soybean and Cowpea in Northern Ghana
Venue: Front. Plant Sci.

This study evaluated the symbiotic effectiveness and economic evaluation of Rhizobium inoculants with the objective of recommending the most effective inoculant strain for soybean and cowpea production in Northern Ghana. Field experiments were established in three locations using randomized complete block design with five blocks. A total of four treatments (Legumefix, Biofix, 100 kg N ha 1 and uninoculated control for soybean and BR 3267, BR 3262, 100 kg N ha 1 and uninoculated control for cowpea) were applied. At Nyankpala, inoculation of soybean with Legumefix and Biofix led to significant (P 0.05) increases in nodule number (90 118% nodule dry weight >two folds) and grain yield (12 19% relative to the control. The Biofix effect on soybean grain yield was 1.5 fold of Legumefix. Similarly, inoculation of cowpea with BR 3262 and BR 3267 significantly (P 0.05) increased nodule number (41 68% nodule dry weight (45 65% and grain yield (11 38% relative to the control. Strain BR 3267 performed consistently >two folds) better than BR 3262 on grain yield. At Nyagli, there was no significant effect of inoculation on cowpea. Wilks lambda values (0.067, 0.039; P 0.00) indicated that 93.3 and 96.1% of the variations observed in soybean and cowpea, respectively, were due to the applied inoculants. Biofix and BR 3267 were economically profitable with VCR ratio of 8.7 and 4.6, respectively. Based on grain yield and economic returns observed, Biofix and BR 3267 can be recommended in Nyankpala for inoculation of soybean and cowpea, respectively.
Genetic Diversity and Population Structure of Cowpea (Vigna unguiculata L. Walp)
Venue: PloS one

The genetic diversity of cowpea was analyzed, and the population structure was estimated in a diverse set of 768 cultivated cowpea genotypes from the USDA GRIN cowpea collection, originally collected from 56 countries. Genotyping by sequencing was used to discover single nucleotide polymorphism (SNP) in cowpea and the identified SNP alleles were used to estimate the level of genetic diversity, population structure, and phylogenetic relationships. The aim of this study was to detect the gene pool structure of cowpea and to determine its relationship between different regions and countries. Based on the model based ancestry analysis, the phylogenetic tree, and the principal component analysis, three well differentiated genetic populations were postulated from 768 worldwide cowpea genotypes. According to the phylogenetic analyses between each individual, region, and country, we may trace the accession from off original, back to the two candidate original areas (West and East of Africa) to predict the migration and domestication history during the cowpea dispersal and development. To our knowledge, this is the first report of the analysis of the genetic variation and relationship between globally cultivated cowpea genotypes. The results will help curators, researchers, and breeders to understand, utilize, conserve, and manage the collection for more efficient contribution to international cowpea research.
Fog computing: Driving force behind the emergence of edge computing
Venue: 2016 International Conference System Modeling Advancement in Research Trends (SMART)

This Fog computing is basically a concept which extends cloud computing theory to the edge of the network. Fog provides data, compute storage and application services to the end user. This facilitates new variety of application and services. The Internet of Things represents a new age of information and communication technologies from anytime, anyplace connectivity for anybody. Application of fog computing platform is well thought out as suitable platform for IOTs services and applications are not restricted to the connected vehicles, smart grid and smart cities. Response time and scalability plays an important role in machine to machine communication. The edge computing platform solves this problem by locating small type server namely edge server and devices over the surrounding area of the users and passing to the some of the load of central server and/or user devices.
Optimal mobile device selection for mobile cloud service providing
Venue: The Journal of Supercomputing

With the rapid growth of the mobile devices and the emergence of cloud computing, mobile cloud computing has gained widespread interest. In mobile cloud computing, a large scale collection of mobile devices cooperate with each other to provide a cloud service at the edge. However, the improper mobile device selection has a negative effect on the quality of service. Existing methods are difficult to solve the problem, because they do not take the status and the historical characteristics of the mobile devices into consideration. This paper introduces a device status aware and stability aware mobile device selection method. Firstly, a model is designed to store the status and the historical characteristics of each mobile device. Secondly, an optimized cloud model is employed to evaluate the stability of each mobile device. Lastly, an optimal mobile device searching algorithm is presented to select the optimal mobile device. We provide an extensive evaluation of our method. The results show that our method can increase the quality of mobile cloud service compared with the traditional method.
Entropy Based Application Layer DDoS Attack Detection Using Artificial Neural Networks
Venue: Entropy

Distributed denial of service (DDoS) attack is one of the major threats to the web server. The rapid increase of DDoS attacks on the Internet has clearly pointed out the limitations in current intrusion detection systems or intrusion prevention systems (IDS/IPS) mostly caused by application layer DDoS attacks. Within this context, the objective of the paper is to detect a DDoS attack using a multilayer perceptron (MLP) classification algorithm with genetic algorithm (GA) as learning algorithm. In this work, we analyzed the standard EPA HTTP (environmental protection agency hypertext transfer protocol) dataset and selected the parameters that will be used as input to the classifier model for differentiating the attack from normal profile. The parameters selected are the HTTP GET request count, entropy, and variance for every connection. The proposed model can provide a better accuracy of 98.31% sensitivity of 0.9962, and specificity of 0.0561 when compared to other traditional classification models.
Detection of Application Layer DDoS attack by feature learning using Stacked AutoEncoder
Venue: 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT)

An Application Layer Distributed Denial of Service Attack (DDoS) is one of the biggest concerns for web security. Many detection methods are designed to mitigate DDoS attack based on IP and TCP layer instead of the Application layer. These methods are not suitable for detection of Application layer DDoS attack since most of the IP and TCP layer DDoS attacks are based on request flooding attack. But Application layer DDoS attacks consist of request flooding, session flooding, and asymmetric attack. The solutions available to detect Application layer DDoS attack, detect only limited number of Application layer DDoS attacks. The solutions that detect all types of Application layer DDoS attacks have huge algorithm complexity. One of the major challenges in the detection of an Application layer DDoS attack is the non availability of features to detect such attacks. Hence it is difficult to model normal user behavior from attack behavior. In this paper, Deep learning architecture is introduced to learn deep features of Application layer DDoS attack. Deep learning architecture consist of very deep neural network, typically more than three layers. In the proposed work the concept of AutoEncoder is applied, which is one of the deep learning based models that learns deep useful features in the Application layer DDoS attack dataset. The Stacked AutoEncoder deep learning architecture, is aimed to receive high level features. The performance of the proposed method was evaluated in terms of the metrics such as false positive rate and detection rate. Comparison of the proposed method with the existing methods reveals that the proposed method performs better than the existing methods.