nils-herrmann/clean_scirepeval huggingface dataset:
Exercise is medicine in oncology: Engaging clinicians to help patients move through cancer
Venue: CA: a cancer journal for clinicians
Year: 2019

Multiple organizations around the world have issued evidence based exercise guidance for patients with cancer and cancer survivors. Recently, the American College of Sports Medicine has updated its exercise guidance for cancer prevention as well as for the prevention and treatment of a variety of cancer health related outcomes (eg, fatigue, anxiety, depression, function, and quality of life) Despite these guidelines, the majority of people living with and beyond cancer are not regularly physically active. Among the reasons for this is a lack of clarity on the part of those who work in oncology clinical settings of their role in assessing, advising, and referring patients to exercise. The authors propose using the American College of Sports Medicine's Exercise Is Medicine initiative to address this practice gap. The simple proposal is for clinicians to assess, advise, and refer patients to either home based or community based exercise or for further evaluation and intervention in outpatient rehabilitation. To do this will require care coordination with appropriate professionals as well as change in the behaviors of clinicians, patients, and those who deliver the rehabilitation and exercise programming. Behavior change is one of many challenges to enacting the proposed practice changes. Other implementation challenges include capacity for triage and referral, the need for a program registry, costs and compensation, and workforce development. In conclusion, there is a call to action for key stakeholders to create the infrastructure and cultural adaptations needed so that all people living with and beyond cancer can be as active as is possible for them.
A novel causally consistent replication protocol with partial geo replication
Year: 2018

Distributed storage systems are a fundamental component of large scale Internet services. To keep up with the increasing expectations of users regarding availability and latency, the design of data storage systems has evolved to achieve these properties, by exploiting techniques such as partial replication, geo replication and weaker consistency models. While systems with these characteristics exist, they usually do not provide all these properties or do so in an inefficient manner, not taking full advantage of them. Additionally, weak consistency models, such as eventual consistency, put an excessively high burden on application programmers for writing correct applications, and hence, multiple systems have moved towards providing additional consistency guarantees such as implementing the causal (and causal+ consistency models. In this thesis we approach the existing challenges in designing a causally consistent replication protocol, with a focus on the use of geo and partial data replication. To this end, we present a novel replication protocol, capable of enriching an existing geo and partially replicated datastore with the causal+ consistency model. In addition, this thesis also presents a concrete implementation of the proposed protocol over the popular Cassandra datastore system. This implementation is complemented with experimental results obtained in a realistic scenario, in which we compare our proposal with multiple configurations of the Cassandra datastore (without causal consistency guarantees) and with other existing alternatives. The results show that our proposed solution is able to achieve a balanced performance, with low data visibility delays and without significant performance penalties.
How Can Self regulated Learning Be Supported in E learning 2.0 Environment: a Comparative Study
Year: 2016

As a critical factor that affects the learning performance in distance education, selfregulated learning (SRL) has elicited considerable interest. Self regulated learners can manage their learning activities efficiently but researchers indicate that learners have difficulties in SRL behavior. Thus, providing support to facilitate self regulatory processes is important. E learning has the potential to be a learning tool to examine students' self regulatory skills. New advances in technology, especially the development of Web 2.0 technology, have provided effective support for self regulated learning. This study addresses the following research question: How can SRL be supported properly in E learning environment? Because learning processes cannot be conceptualized without the sociocultural context this study investigate environmental variations between two samples of Mainland China and Hong Kong distance learners (N=289) The purpose is to chart the underlying relationships between learner self regulation and distance education environments using regression analysis and to find differences of environmental factors and self regulation in different cultural orientations. The study has found significant differences between Mainland China and Hong Kong distance students on demography variables except age characteristics. In the relation model however, no difference has been found. Self regulation is to be equivalent in the two cultures and can be influenced by the same environmental factors.
Netherlands country report for European Commission study on Human Rights Due Diligence in the Supply Chain
Year: 2020

markdownabstractThe Dutch parliamentary dossier on the topic of socially responsible business conduct (maatschappelijk verantwoord ondernemen or MVO) which literally translates as 'corporate social responsibility' or 'CSR' dates back to 1999. Over time, the dossier has become increasingly focused on the international dimension of the topic, i.e. on human rights violations and environmental harm related to business activities in the global supply chains of Netherlands based internationally operating business enterprises. The term that has in recent years become associated with this international dimension is that of international responsible business conduct (IRBC) (internationaal maatschappelijk verantwoord ondernemen or IMVO) In November 2014, the Dutch government presented the results of a Sector Risk Analysis in which thirteen sectors of Dutch industry were identified as involving relatively high risks of adverse impacts on human rights and the environment. The government indicated that it expected companies in these sectors to both take steps aimed at preventing and mitigating the CSR related risks in their value chains, and engage with other companies and stakeholders to come to concrete agreements on the ways in which these risks could be dealt with in a structural manner. Those agreements were to be laid down, preferably, in so called covenants: agreements between the Dutch government and one or more societal parties aimed at realizing certain policy aims, which typically take the form of a written document setting out the actions that each of the parties is expected to take in furtherance of those aims. These covenants on International Responsible Business Conduct (IRBC covenants) were to be drafted along the lines set out in a 2014 report by the Dutch Social and Economic Council (SER) on the same topic.
A novel hybrid algorithm for electricity price and load forecasting in smart grids with demand side management
Year: 2016

Smart grid is a platform that enables the participants of electricity market to adjust their bidding strategies based on Demand Side Management (DSM) models. Responsiveness of the market participants can improve reliability of system operation as well as capital cost investments. In this regard, the accurate forecast of electricity price and demand in smart grids is an important challenge as their strong correlation makes a separate forecasting to be ineffective. Therefore, this paper proposes a novel hybrid algorithm for simultaneous forecast of price and demand that uses a set of effective tools in preprocessing part, forecast engine and tuned algorithm. To highlight our contributions, the proposed forecast algorithm classified into three main parts. The first part employs a new Flexible Wavelet Packet Transform (FWPT) to decompose a signal into multiple terms at different frequencies, and a new feature selection method that employs Conditional Mutual Information (CMI) and adjacent features in order to select valuable input data. The second part consists of a novel Multi Input Multi Output (MIMO) model based on Nonlinear Least Square Support Vector Machine (NLSSVM) and Autoregressive Integrated Moving Average (ARIMA) in order to model the linear and nonlinear correlation between price and load in two stages. The final part employs a modified version of Artificial Bee Colony (ABC) algorithm based on time varying coefficients and stumble generation operator, called TV SABC, in order to optimize NLSSVM parameters in a learning process. The proposed hybrid forecasting algorithm is evaluated on several real and well known markets illustrating its high accuracy in simultaneous forecast of electricity price and demand. Moreover, the interactive effects of demand side management programs on load factor (load curve) and price signal are investigated by numerical indices.
Robust Bayesian Transfer Learning between Autoregressive Inference Tasks
Venue: 2021 32nd Irish Signals and Systems Conference (ISSC)
Year: 2021

Bayesian transfer learning typically relies on a complete stochastic dependence specification between source and target learners. We advocate a solution to the Bayesian transfer learning paradigm which adopts Fully Probabilistic Design (FPD) to search for an optimal choice of distribution constrained by probabilistic source knowledge. Using this optimal decisionmaking strategy, an algorithm for accepting source knowledge is identified but is found to be effectively insensitive to source uncertainty. Therefore, we propose an adaptation of the FPD framework which results in a robust transfer learning algorithm.Experimental evidence gathered via synthetic data shows enhanced performance when employing both optimal algorithms in a low source data predictor variance regime. In a high source data predictor variance setting, only our adapted FPD optimal algorithm achieves robustness.
Two Dimensional Quantum Walk with Non Hermitian Skin Effects
Year: 2020

We construct a two dimensional, discrete time quantum walk exhibiting non Hermitian skin effects under open boundary conditions. As a confirmation of the non Hermitian bulk boundary correspondence, we show that the emergence of topological edge states are consistent with Floquet winding numbers calculated using a non Bloch band theory invoking time dependent generalized Billouin zones. Further, the non Bloch topological invariants associated with the Floquet bands are captured by a non Hermitian local Chern marker in real space, defined through local biorthogonal eigen wave functions of the non unitary Floquet operator. Our work suggests the possibility of directly measuring non Bloch topological invariants in quantum walk dynamics, and would stimulate further studies of non Hermitian Floquet topological phases where skin effects play a key role.
Structural analysis of aquaculture net cages in current
Year: 2010

A method for structural analysis of aquaculture net cages has been developed and verified for a netting solidity of 0.23, water current velocities from 0.1 to 0.5 m/s and relatively large deformations (volume reduction up to 70% by comparing the numerical results to tests in a flume tank. Strength analysis was performed using commercial explicit finite element software to calculate distribution of loads in the net cage due to current, weights and gravity. The net cage was modelled using truss elements that represented several parallel twines. Sub elements allowed the trusses to buckle in compression, and only negligible compressive forces were seen in the numerical results. Resulting drag loads and cage volume were shown to be dependent on the net cage size and weight system. Drag loads increased almost proportional to the current velocity for velocities in the range of 0.2 0.5 m/s, while the cage volume was reduced proportional to the current velocity. The calculated forces in ropes and netting of full size net cages were well below the design capacity for current velocities up to 0.5 m/s. However, netting seams in the bottom panel of the net cage were identified as a potential problem area as the forces could reach the design capacity.
Sitotoksisitas fraksi protein daun mimba (Azadirachta indica A. Juss) hasil pengendapan dengan Amonium Sulfat 30% 60% dan 100% jenuh terhadap kultur sel raji
Year: 2006

ABSTRAK Kanker merupakan salah satu penyakit penyebab kematian terbesar. Suatu penelitian untuk menemukan obat antikanker dari tanaman mimba (Azadirachta indica A. Juss) menyimpulkan bahwa fraksi protein total daun mimba memiliki efek sitotoksik terhadap sel HeLa dan sel Raji namun tidak berpotensi untuk dikembangkan sebagai antikanker. Mengacu pada penelitian tersebut, pada penelitian ini dilakukan fraksinasi protein secara bertingkat untuk mendapatkan efek sitotoksik yang lebih besar. Tujuan penelitian ini adalah untuk mengetahui fraksi protein daun mimba manakah dari hasil pengendapan dengan amonium sulfat 30% 60% dan 100% jenuh yang memiliki potensi terbesar untuk dikembangkan sebagai antikanker. Penelitian ini adalah penelitian eksperimental murni yang dilakukan mengikuti rancangan acak lengkap pola satu arah. Uji sitotoksisitas dilakukan secara in vitro terhadap sel HeLa dan sel Raji menggunakan metode MTT (3 4(4,5 dimetil diazol 2 il) 2,5 diphenil tetrazolium bromid) Fraksi protein diperoleh lewat pengendapan dengan penambahan amonium sulfat dengan konsentrasi 30% 60% dan 100% jenuh. Hasil uji dinyatakan dalam prosentase kematian yang selanjutnya diolah dengan analisis statistika one way anova dan probit. Hasil uji sitotoksisitas menunjukkan harga LC50 untuk fraksi protein yang diendapkan dengan ammonium sulfat 30% 60% dan 100% jenuh terhadap sel HeLa berturut turut sebesar 1,0 mg/ml 4,1 mg/ml, dan 407,7 mg/ml sedangkan harga LC50 untuk fraksi protein 30% dan 60% jenuh terhadap sel Raji sebesar 15,3 mg/ml dan 24,0 mg/ml. Fraksi protein hasil pengendapan dengan amonium sulfat 30% jenuh memiliki efek sitotoksik yang terbesar terhadap sel HeLa dan sel Raji serta memiliki potensi untuk dikembangkan sebagai antikanker.
Changes in spatial and temporal distribution and vocal behavior of Blainville's beaked whales (Mesoplodon densirostris) during multiship exercises with mid frequency sonar
Year: 2011

The number and distribution of vocalizing groups of Blainville's beaked whales (Mesoplodon densirostris) were analyzed before, during, and after multiship mid frequency active sonar operations at the US Navy's Atlantic Undersea Test and Evaluation Center (AUTEC) in the Bahamas. Groups of foraging animals were isolated by detecting their echolocation clicks using an array of bottom mounted hydrophones. Two data sets were evaluated consisting of 115 and 240 h of acoustic data in May 2007 and 2008, respectively. Vocal activity was observed to decline during active sonar exercises and increase upon cessation of sonar transmissions in both data sets. Vocal activity did not recover to preexposure levels in the postexposure time period in 2007 nor in the initial postexposure period in the 2008 data set. Clicks detected during sonar operations were generally found to be on the periphery of the hydrophone field and vocal durations declined for those groups that remained on the range in that time period. Receive levels were calculated for several vocal groups of whales and indicated that animals continued to forage when exposed to sonar at levels as high as 157 dB re: mPa.
Multi view Video Based Object Segmentation A Tutorial
Year: 2009

Video based object segmentation (VBOS) is an important step in many computer vision and multimedia tasks such as video editing and compositing. In recent years, multi view VBOS systems have become more and more popular because the stereo clues from multiview data can be e ciently incorporated to improve the segmentation results and eliminate the required initial user input. In this paper, we give a review on recent development of multi view VBOS systems and the related techniques including data acquisition, camera calibration, depth reconstruction, object segmentation and tracking. Furthermore, we introduce our multiple objects segmentation system from multiview video sequence to illustrate the practical implementation of multi view VBOS system for 3D video rendering applications.
Contentious Freedom: Sex Work and Social Construction
Venue: Hypatia
Year: 2006

In this article, Brison extends the analysis of freedom developed in Nancy J Hirschmann's book, The Subject of Liberty: Toward a Feminist Theory of Freedom, to an area of controversy among feminist theorists: that of sex work, including prostitution and participation in the production of pornography. This topic raises some of the same issues concerning choice and consent as the three topics Hirschmann discusses in her book domestic violence, the current welfare system in the United States, and Islamic veiling but it also raises some distinct ones concerning the social construction of sexuality and possible conflicts between the freedom of some women (who may choose to engage in sex work) and the freedom of others (who may be harmed by the contribution of such work to the social construction of categories such as "women" and "sex"
Joint Contextual Modeling for ASR Correction and Language Understanding
Venue: ICASSP 2020 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2020

The quality of automatic speech recognition (ASR) is critical to Dialogue Systems as ASR errors propagate to and directly impact downstream tasks such as language understanding (LU) In this paper, we propose multi task neural approaches to perform contextual language correction on ASR outputs jointly with LU to improve the performance of both tasks simultaneously. To measure the effectiveness of this approach we used a public benchmark, the 2nd Dialogue State Tracking (DSTC2) corpus. As a baseline approach, we trained task specific Statistical Language Models (SLM) and fine tuned state of the art Generative Pre training (GPT) Language Model to re rank the n best ASR hypotheses, followed by a model to identify the dialog act and slots. i) We further trained ranker models using GPT and Hierarchical CNN RNN models with discriminatory losses to detect the best output given n best hypotheses. We extended these ranker models to first select the best ASR output and then identify the dialogue act and slots in an end to end fashion. ii) We also proposed a novel joint ASR error correction and LU model, a word confusion pointer network (WCN Ptr) with multihead self attention on top, which consumes the word confusions populated from the n best. We show that the error rates of off the shelf ASR and following LU systems can be reduced significantly by 14% relative with joint models trained using small amounts of in domain data.
Dynamic Gene Regulatory Networks Drive Hematopoietic Specification and Differentiation
Venue: Developmental cell
Year: 2016

Metazoan development involves the successive activation and silencing of specific gene expression programs and is driven by tissue specific transcription factors programming the chromatin landscape. To understand how this process executes an entire developmental pathway, we generated global gene expression, chromatin accessibility, histone modification, and transcription factor binding data from purified embryonic stem cell derived cells representing six sequential stages of hematopoietic specification and differentiation. Our data reveal the nature of regulatory elements driving differential gene expression and inform how transcription factor binding impacts on promoter activity. We present a dynamic core regulatory network model for hematopoietic specification and demonstrate its utility for the design of reprogramming experiments. Functional studies motivated by our genome wide data uncovered a stage specific role for TEAD/YAP factors in mammalian hematopoietic specification. Our study presents a powerful resource for studying hematopoiesis and demonstrates how such data advance our understanding of mammalian development.
Cytokine storm and immunomodulatory therapy in COVID 19: Role of chloroquine and anti IL 6 monoclonal antibodies
Venue: International Journal of Antimicrobial Agents
Year: 2020

Highlights Discussion of the role of immunomodulatory agents to reduce the cytokine storm in severe cases of COVID 19. Potential immunomodulatory agents currently used in the treatment of COVID 19 (chloroquine, hydroxychloroquine and tocilizumab) are discussed. Other immunomodulatory agents with good safety profiles may be considered for use in combination with antiviral drugs for the treatment of severe or critical cases of COVID 19.
Successful Treatment of Hepatitis C Virus associated Oral Lichen Planus by Interferon free Therapy with Direct acting Antivirals
Venue: Clinical and Translational Gastroenterology
Year: 2016

Oral lichen planus (OLP) is one of the extrahepatic manifestations of hepatitis C virus (HCV) infection. Presently developed interferon (IFN) free direct acting antivirals (DAAs) used to treat HCV infection have low side effect profiles and high efficacy. However, there are no studies examining the relationship between OLP and IFN free DAAs. The aim of this study was to evaluate the disease course in patients with HCV associated OLP, who received treatment with IFN free DAAs.Seven patients with HCV related OLP (including one with cutaneous LP) who received IFN free treatment with daclatasvir (DCV)/asunaprevir (ASV) at our hospital in Japan from October, 2014 to February, 2015 were enrolled in the study. The subjects included four males and three females (average age, 73.9 years) We compared the symptoms of OLP in the patients before and at 24 weeks after the end of DAA therapy.No worsening of symptoms was observed during treatment with the DAAs. The symptoms of OLP had subsided in all seven patients. Lesions of OLP and cutaneous LP disappeared in four, and improved in three of the seven patients after sustained virological response 24. No systemic clinical adverse events were observed in all patients.Herein, we have reported the outcomes of HCV associated OLP in patients who received successful treatment with IFN free DAAs, using the DCV/ASV combination therapy.
Design of a Functional Size Measurement Procedure for Real Time Embedded Software Requirements Expressed using the Simulink Model
Venue: 2011 Joint Conference of the 21st International Workshop on Software Measurement and the 6th International Conference on Software Process and Product Measurement
Year: 2011

To obtain the functional size of software and reduce measurement variance caused by the interpretations of individual measurers, a number of measurement procedureshave been designed based on measurement methods approved as international standards. To date, most of these procedures have targeted Management Information Systems software, while only a few were designed for real time and reactiveembedded software. In this paper, we propose a functional size measurement (FSM) procedure for real time embedded software, based on the COSMIC method, version 3.0.1 (ISO 19761) and with requirements documented using the Simulinkmodel. The design of this FSM procedure is based on the mapping of key concepts in both Simulink and COSMIC, and the identification of the mapping rules for extracting the information stored in the Simulink files that is required formeasurement. This procedure therefore provides the foundation for automating the measurement of software requirements documented using Simulink. The backgroundstudy for this procedure was conducted at Renault SAS using ECU (Electronic Control Unit) functional requirements expressed with the Simulink tool.