nils-herrmann/clean_scirepeval huggingface dataset:
Resource scheduling algorithm with load balancing for cloud service provisioning
Venue: Appl. Soft Comput.
Year: 2019

Cloud computing uses scheduling and load balancing for virtualized file sharing in cloud infrastructure. These two have to be performed in an optimized manner in cloud computing environment to achieve optimal file sharing. Recently, Scalable traffic management has been developed in cloud data centers for traffic load balancing and quality of service provisioning. However, latency reducing during multidimensional resource allocation still remains a challenge. Hence, there necessitates efficient resource scheduling for ensuring load optimization in cloud. The objective of this work is to introduce an integrated resource scheduling and load balancing algorithm for efficient cloud service provisioning. The method constructs a Fuzzy based Multidimensional Resource Scheduling model to obtain resource scheduling efficiency in cloud infrastructure. Increasing utilization of Virtual Machines through effective and fair load balancing is then achieved by dynamically selecting a request from a class using Multidimensional Queuing Load Optimization algorithm. A load balancing algorithm is then implemented to avoid underutilization and overutilization of resources, improving latency time for each class of request. Simulations were conducted to evaluate the effectiveness using Cloudsim simulator in cloud data centers and results shows that the proposed method achieves better performance in terms of average success rate, resource scheduling efficiency and response time. Simulation analysis shows that the method improves the resource scheduling efficiency by 7% and also reduces the response time by 35.5 when compared to the state of the art works.
Application of endurance time method to seismic fragility evaluation of highway bridges considering scour effect
Year: 2020

Earthquake and flood scour are two main causes of failures to highway bridges. This study developed an alternative fragility analysis framework of bridges based on endurance time method (ETM) A two span reinforced concrete highway bridge supported by three types of substructures, e.g. shaft foundation, two column bent foundation and pile group foundation, was taken as the example bridge. The developed framework was used to obtain the fragility curves of the example bridges. The influences of scour depth, substructure design, ground motion direction and scour countermeasure on the seismic fragility of bridges were investigated. The developed seismic fragility analysis framework based on endurance time method yields accurate and efficient calculation compared with IDA method. Scour reduces the bearing capacity of the foundation and affects the seismic fragility of bridges. However, the effect of scour on the seismic fragility varies with the bridge substructure design, the ground motion direction and the application of the scour countermeasure.
Relation between Conflict Level and Leadership Style in a Military Medical Sciences Research Center
Year: 2016

Effective leadership is a requirement in every research institute in order to create and sustain an optimized level of conflict. The aim of the present research was to study the relationship between conflict level and leadership style in the employees of a military medical research center.  This study was a cross sectional study. Data was gathered by three questionnaires (demographic, fielder's least preference co worker (LPC) and Rahim conflict inventory I questionnaire) from 42 managers and faculties of a military medical research center in 2015. Data was analyzed with Independent T Test, Spearman Coefficient and linear regression using SPSS version 18.  No significant difference was seen between conflict level and also leadership style with demographic variables including sex, age, and the duration of working years (P Value> 0.05) Linear regression showed that leadership score had a negative and significant difference with intrapersonal conflict level (r= 0.377 and P Value 0.05)  Empowering managers for improvement in relation oriented leadership styles has an effect on decreasing organizational conflict levels. In order to optimize conflict levels, planning to decrease Intrapersonal conflict levels and increase intergroup conflict levels is recommended.
Journey of brain derived neurotrophic factor: from intracellular trafficking to secretion.
Venue: Cell and tissue research
Year: 2020

Brain derived neurotrophic factor (BDNF) is known to control a wide variety of brain functions, ranging from memory formation to food intake. However, since the BDNF levels are extremely low in the nervous system, the dynamics in neurons from intracellular trafficking to secretion is absolutely complicated; the understanding is not fully promoted. We here review the findings of those critical mechanisms from intracellular trafficking to the secretion of BDNF. Furthermore, to solve this issue, technological advances for the detection, measurement, and imaging of this growth factor are essential. We believe that this review helps the study of these complex but critical mechanisms of BDNF.
Post stroke dysphagia rehabilitation in the old and oldest old: outcome and relevance for discharge home
Venue: International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation
Year: 2019

We assessed the outcome of dysphagia rehabilitation in all the 139 patients with post stroke dysphagia admitted to our Neurorehabilitation Unit during 2 years (2017 and 2018) divided into two groups: old (aged 65 84 years) and oldest old (aged 85 or above) We studied which factors predicted dysphagia improvement in the two groups. The potential association of improvement with type of discharge was also evaluated. On admission, 'old' patients had more frequently aphasia (P 0.02) and less frequently dysarthria (P 0.03) 'oldest old' had more severe pressure ulcers (P 0.008) higher levels of c reacting protein (P 0.01) and more heart problems (P 0.004) None of these factors was associated with the outcome of dysphagia. We found no difference between the two groups in the severity of dysphagia, as measured with Dysphagia Outcome and Severity Scale on admission and discharge, but due to minor differences, the degree of improvement was higher in the 'old' group (P 0.02) The number of patients discharged with improved swallowing was also comparable. Cognitive impairment had a negative predicting role in the 'old' group (odds ratio 0.270, 95% confidence interval 0.101 0.725, P 0.007) Norton Scale score predicted dysphagia improvement in the 'oldest old' group (odds ratio 1.611, 95% confidence interval 1.102 2.355, P 0.007) Dysphagia improvement was associated with discharge home in general (P 0.011) and in the 'old' group (P 0.04) Our data, though preliminary, could give a contribution to implement patient specific rehabilitation strategies; these could increase swallowing improvement in post stroke dysphagia.
The Comparative Moderating Effect of Risk Management Committee and Audit Committee on the Association Between Voluntary Risk Management Disclosure and Firm Performance
Year: 2017

The purpose of this study is to examine the comparative moderating effects of two separate risk governance mechanisms on the relationship between voluntary risk management disclosure (VRMD) and firm performance (FP) This study utilizes content analysis method to collect VRMD data, while FP is measured based on investors' perspective, represented by Tobin's Q. Multivariate statistical tests show that the existence of Risk Management Committee (RMC) augmented the association between VRMD and FP. However, the appointment of audit committee (AC) and the quality of AC which are represented by size, independence, education and number of AC meetings, do not have any moderating effect on the relationship between VRMD and FP. The findings suggest that risk governance mechanisms do matter to investors in evaluating risk management information. The findings also provide empirical evidence that should be of interest to the management of company and regulatory bodies in terms of deciding upon whether or not to establish RMC as a separate committee from AC.  Risk management committee; audit committee; risk governance; voluntary risk management disclosure; non financial Industry ABSTRAK Tujuan kajian ini adalah untuk mengkaji kesan penyederhana secara komparatif dua mekanisme tadbir urus risiko terhadap hubungan antara pendedahan maklumat sukarela pengurusan risiko (PMSPR) dan prestasi syarikat (PS) Kajian ini menggunakan kaedah analisis kandungan untuk mengumpul data PMSPR, manakala PS diukur berdasarkan perspektif pelabur, yang diwakili oleh Tobin's Q. Ujian statistik multivariat menunjukkan bahawa kewujudan Jawatankuasa Pengurusan Risiko (JPR) meningkatkan hubungan antara PMSPR dan PS. Walau bagaimanapun, perlantikan Jawatankuasa Audit (JA) dan kualiti JA yang diwakili oleh saiz, kebebasan, pendidikan dan bilangan mesyuarat JA tidak mempunyai kesan penyederhana terhadap hubungan PMSPR dan PS. Dapatan kajian ini menunjukkan bahawa mekanisme tadbir urus risiko adalah penting kepada pelabur dalam menilai maklumat pengurusan risiko. Dapatan ini juga memberikan bukti empirikal kepada pihak pengurusan syarikat dan badan pengawalseliaan dari segi penentuan sama ada untuk menubuhkan JPR atau tidak secara berasingan daripada JA.  Jawatankuasa pengurusan risiko; jawatankuasa audit; tadbir urus risiko; pendedahan maklumat sukarela pengurusan risiko; industri bukan kewangan
A Bi Model Based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling
Venue: NAACL
Year: 2018

Intent detection and slot filling are two main tasks for building a spoken language understanding(SLU) system. Multiple deep learning based models have demonstrated good results on these tasks The most effective algorithms are based on the structures of sequence to sequence models (or "encoder decoder" models) and generate the intents and semantic tags either using separate models. Most of the previous studies, however, either treat the intent detection and slot filling as two separate parallel tasks, or use a sequence to sequence model to generate both semantic tags and intent. None of the approaches consider the cross impact between the intent detection task and the slot filling task. In this paper, new Bi model based RNN semantic frame parsing network structures are designed to perform the intent detection and slot filling tasks jointly, by considering their cross impact to each other using two correlated bidirectional LSTMs (BLSTM) Our Bi model structure with a decoder achieves state of art result on the benchmark ATIS data, with about 0.5% intent accuracy improvement and 0.9 slot filling improvement.
Leadership in the era of the Trump presidency: implications for the education of American Indian children and youth
Year: 2018

In this manuscript, I outline what I perceive to be the potential implications of the Trump presidency for the education of American Indian children and youth. In doing so, I argue that failure to provide adequate educational programs and services for American Indian children and youth represents an abrogation of the federal government's trust responsibilities for American Indian people and places the futures of American Indian tribes and their members at risk.
The Structure of Economic Attitudes of the Youth Representatives of the Indigenous Small Numbered Peoples of the Arctic Zone of the Russian Federation: Results of a Pilot Study
Venue: Journal of Siberian Federal University. Humanities Social Sciences
Year: 2019

The article presents the results of a pilot study of economic attitudes of young people representatives of indigenous peoples of the Arctic zone (hereinafter youth) The authors of the article used a multivariate questionnaire developed by O. S. Deineka and E. V. Zabelina as the main methodological tool to carry out the express diagnostics of economic attitudes. As a result, the article presents the structure of economic attitudes of youth. In addition, using a factor analysis, the authors found four fundamental factors that should be considered as types of economic consciousness, but only one of them is financially confident and literate. The other three types are experiencing difficulties with knowledge in the field of economics, which can lead to dissatisfaction and disappointment of young people in this field in the future. In conclusion, there are general conclusions and trends characterizing the tendency of young people from the indigenous peoples of the Arctic zone to passive, safe, and non risky financial strategies
Dysgraphia detection through machine learning
Venue: Scientific reports
Year: 2020

Dysgraphia, a disorder affecting the written expression of symbols and words, negatively impacts the academic results of pupils as well as their overall well being. The use of automated procedures can make dysgraphia testing available to larger populations, thereby facilitating early intervention for those who need it. In this paper, we employed a machine learning approach to identify handwriting deteriorated by dysgraphia. To achieve this goal, we collected a new handwriting dataset consisting of several handwriting tasks and extracted a broad range of features to capture different aspects of handwriting. These were fed to a machine learning algorithm to predict whether handwriting is affected by dysgraphia. We compared several machine learning algorithms and discovered that the best results were achieved by the adaptive boosting (AdaBoost) algorithm. The results show that machine learning can be used to detect dysgraphia with almost 80% accuracy, even when dealing with a heterogeneous set of subjects differing in age, sex and handedness.
Sexually dimorphic patterns of episomal rAAV genome persistence in the adult mouse liver and correlation with hepatocellular proliferation.
Venue: Molecular therapy the journal of the American Society of Gene Therapy
Year: 2009

Recombinant adeno associated virus vectors (rAAVs) show exceptional promise for liver targeted gene therapy, with phenotype correction in small and large animal disease models being reported with increasing frequency. Success in humans, however, remains a considerable challenge that demands greater understanding of host vector interactions, notably those governing the efficiency of initial gene transfer and subsequent long term persistence of gene expression. In this study, we examined long term enhanced green fluorescent protein (eGFP) expression and vector genome persistence in the mouse liver after rAAV2/8 mediated gene transfer in early adulthood. Two intriguing findings emerged of considerable scientific and clinical interest. First, adult female and male mice showed distinctly different patterns of persistence of eGFP expression across the hepatic lobule after exhibiting similar patterns initially. Female mice retained a predominantly perivenous pattern of expression, whereas male mice underwent inversion of this pattern with preferential loss of perivenous expression and relative retention of periportal expression. Second, these changing patterns of expression correlated with sexually dimorphic patterns of genome persistence that appear linked both spatially and temporally to underlying hepatocellular proliferation. Observation of the equivalent phenomenon in man could have significant implications for the long term therapeutic efficacy of rAAV mediated gene transfer, particularly in the context of correction of liver functions showing metabolic zonation.
EFFECTS OF MUSCLE FATIGUE ON SHOULDER JOINT POSITION SENSE
Year: 2014

The shoulder complex relies heavily on sensory motor control for maintaining functional joint stability, due to its poor osseous and capsuloligamentous stability. Proprioceptive deficits have been related to shoulder injuries and some studies have shown that muscle fatigue can also decrease propriocetive acuity [1 3] However, these studies have focused on shoulder internal and external rotation movements, which may not be functional for the general population. Therefore, this study aimed to investigate the effects of muscle fatigue on shoulder joint position sense during an active repositioning task at different angles of shoulder elevation in the scapular plane.
Reef Life Survey: establishing the ecological basis for conservation of shallow marine life
Year: 2020

Reef Life Survey (RLS) provides a new model for ecological monitoring through training experienced recreational divers in underwater visual census methods to the level of skilled scientists. Detail produced is similar to that of programs with professional scientific teams, at low cost to allow global coverage. RLS differs from most other citizen science initiatives in its emphasis on rigorous training and data quality rather than open participation, selectively involving the most skilled and committed members. Volunteers participate primarily because they appreciate the close relationship with scientists, other divers, and managers, and see their efforts directly contributing to improved environmental outcomes. RLS works closely with Australian management agencies, scheduling annual events at core monitoring sites associated with 10 inshore marine protected areas Australia wide. Surveys of 12 offshore Australian Marine Parks (AMPs) are realized through 2 4 week voyages in a sailing catamaran crewed by volunteers. Across the AMP network, RLS surveys have quantified densities of fishes, mobile invertebrates, macroalgae and corals at 350 shallow coral reef sites (180 sites surveyed on two or more occasions) providing an understanding of (i) population changes amongst threatened species including sea snakes, (ii) responses of fish and invertebrate populations following fisheries closures, (iii) ecosystem wide impacts of marine heat waves, and (iv) the extent that AMPs spanning the network comprehensively encompass national coral reef biodiversity. This scientist/volunteer/manager collaboration could be greatly expanded globally (presently 3537 sites in 53 countries)
Facial Expression Recognition in Video with Multiple Feature Fusion
Venue: IEEE Transactions on Affective Computing
Year: 2018

Video based facial expression recognition has been a long standing problem and attracted growing attention recently. The key to a successful facial expression recognition system is to exploit the potentials of audiovisual modalities and design robust features to effectively characterize the facial appearance and configuration changes caused by facial motions. We propose an effective framework to address this issue in this paper. In our study, both visual modalities (face images) and audio modalities (speech) are utilized. A new feature descriptor called Histogram of Oriented Gradients from Three Orthogonal Planes (HOG TOP) is proposed to extract dynamic textures from video sequences to characterize facial appearance changes. And a new effective geometric feature derived from the warp transformation of facial landmarks is proposed to capture facial configuration changes. Moreover, the role of audio modalities on recognition is also explored in our study. We applied the multiple feature fusion to tackle the video based facial expression recognition problems under lab controlled environment and in the wild, respectively. Experiments conducted on the extended Cohn Kanade (CK+ database and the Acted Facial Expression in Wild (AFEW) 4.0 database show that our approach is robust in dealing with video based facial expression recognition problems under lab controlled environment and in the wild compared with the other state of the art methods.
Developmental trajectories of positive and negative affect in children at high and low familial risk for depressive disorder.
Venue: Journal of child psychology and psychiatry, and allied disciplines
Year: 2011

Although low positive affect (PA) and high negative affect (NA) have been posited to predispose to depressive disorders, little is known about the developmental trajectories of these affects in children at familial risk for mood disorders.  We examined 202 offspring of mothers who had a history of juvenile onset unipolar depressive disorder (n 60) or no history of major psychopathology (n 80) Offspring participated in up to seven annual, structured laboratory tasks that were designed to elicit PA and NA.  Growth curve analyses revealed that PA increased linearly and similarly for all children from late infancy through age 9. However, there also were individual differences in early PA. Relative to control peers, offspring of mothers with lifetime unipolar depression had consistently lower levels of PA, and this association remained significant even when controlling for current maternal depression and maternal affect displays. Growth curve analyses also revealed a significant linear decrease in NA in children across time; however, there was no significant inter individual variation either in early NA or rate of change in NA.  Attenuated PA (rather than excessive NA) may be an early vulnerability factor for eventual unipolar depressive disorder in at risk children and may represent one pathway through which depression is transmitted.
Hypergraph Clustering Based on Intra class Scatter Matrix for Mining Higher order Microbial Module
Venue: 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Year: 2019

Microbial ecosystems are complex, by analyzing co occurrence modules of microbial communities, we can better understand the conditions of microbial interactions in each environment, and help understand the interaction patterns that maintain the stability of microbial communities. Imbalances in human microbiome are closely related to human disease. Previous modular clustering analysis was based only on the relationship between paired microorganisms. In this paper, we propose calculating the logical relationship between microbial triplet in human body by information entropy and construct a hypergraph based on the triplet network. Based on the hypergraph clustering, we proposed a novel hypergraph clustering algorithm based on intra class scatter matrix (HCIS) to reconstruct hyperedge similarity, and selected the optimal cluster number by maximizing modularity to analyze higher order module of microorganisms. The clustering results verify the effectiveness and feasibility of HCIS algorithm for higher order microbial module analysis.
Self adaptive resource allocation for energy aware virtual machine placement in dynamic computing cloud
Venue: J. Netw. Comput. Appl.
Year: 2018

Cloud computing is a type of Internet based computing that provides shared computing resources and data on demand. To support the massive cloud services, a data center is built with thousands of servers and switches connected by a communication network called a data center network (DCN) Along with the development of virtualization, the data center manager conducts virtual machine (VM) resizing and live migrations to adjust the allocation of VMs and improve the server utilization. However, compared to VM resizing, live migrations can negatively impact the performance of the system depending on the amount of transferred data and the path length. In this paper, we propose an online resource allocation algorithm using VM consolidation to achieve energy efficiency and reduce service level agreement (SLA) violations of data centers while considering the power usage of servers, the number of migrations, and the path length of migrations in DCNs. Compared to the state of the art mechanism, the proposed algorithm successfully reduces the power consumption, the number of migrations, and the path length of migrations for a dynamic cloud service.