nils-herrmann/clean_scirepeval huggingface dataset:
A Federated Discovery Service for the Internet of Things
Venue: M4IoT@Middleware
Year: 2015

The Internet of Things (IoT) is an emergent paradigm characterized by a plethora of smart objects connected to the Internet and collaborating with other physical and virtual resources available in the Web. The development of IoT systems faces important challenges such as the high dynamicity of IoT environments as well as the wide distribution and heterogeneity of the available resources. In this context, discovery services play a significant role as they can allow clients (e.g. middleware platforms, end users, applications) to retrieve available resources based on search criteria such as resource type, capabilities, location, etc. Moreover, the high heterogeneity of these resources requires means of describing them in an unambiguous, machine interpretable way. To cope with these functionalities, we propose ForwarDS IoT, a federated discovery service aiming at providing resource discovery based on multiple attributes, range queries, and synchronous/asynchronous operations. ForwarDS IoT also encompasses an ontology based information model for semantically describing resources and IoT services. In this paper, we present the ForwarDS IoT architecture and its information model as well as a prototype implementation.
Barriers to Access: Report on the Barriers Faced by Young Disabled and D/deaf People in Accessing Youth Arts Provision in Scotland
Year: 2016

This report outlines research that investigated the barriers faced by young disabled and D/deaf people in accessing youth arts provision in Scotland. Funded by the Time to Shine National Youth Arts Strategy for Scotland, the research was conducted by Dr. Matson Lawrence in conjunction with Birds of Paradise Theatre Company. The research relates to young people aged 0 25, with specific empirical focus on young people aged 16 25. Through in depth interviews and online surveys, the research engaged with 20 disabled and D/deaf young people across Scotland, alongside a number of individuals working within the Scottish youth arts sector and in disability and D/deaf arts. The research found that young disabled and D/deaf people face multiple and intersecting barriers to accessing arts provision. Five main barriers were identified: 1. Finding suitable arts provision; 2. Availability of access information; 3. Lack of provision for access and support; 4. Travel, transport and location; and 5. Attitudes and awareness of arts providers. The research identified five key strategies to address these barriers: 1. Provision specifically for young disabled and D/deaf people; 2. Centralised information about arts opportunities; 3. Front Door to Stage Door Access provision; 4. Connections built with disabled and D/deaf communities across Scotland; and 5. Education and awareness for arts providers. These strategies offer arts providers concrete recommendations for improving disabled and D/deaf access. It is anticipated that, in light of this report, organisations and agencies providing arts opportunities to young people will be better informed of the barriers faced by young disabled and D/deaf people, and better equipped to address these barriers and improve access to their provision.
Path planning for active SLAM based on deep reinforcement learning under unknown environments
Venue: Intell. Serv. Robotics
Year: 2020

Autonomous navigation in complex environment is an important requirement for the design of a robot. Active SLAM (simultaneous localization and mapping) combining, which combine path planning with SLAM, is proposed to improve the ability of autonomous navigation in complex environment. In this paper, fully convolutional residual networks are used to recognize the obstacles to get depth image. The avoidance obstacle path is planned by Dueling DQN algorithm in the robot's navigation; at the same time, the 2D map of the environment is built based on FastSLAM. The experiments show that the proposed algorithm can successfully identify and avoid moving and static obstacles with different quantities in the environment, and realize the autonomous navigation of the robot in a complex environment.
Multifidelity Sampling for Fast Bayesian Shape Estimation With Tactile Exploration
Venue: IEEE Transactions on Industrial Informatics
Year: 2020

This article presents a novel multifidelity based optimal sampling method to rapidly estimate the shape of an object from the touch down points on its surface given a highly limited number of sampling trials. The proposed approach attempts to improve the existing shape estimation via tactile exploration, which uses Gaussian process regression for implicit surface modeling with sequential sampling. The main objective is to make the process of sample point selection more efficient and systematic such that the unknown shape can be estimated fast and accurately with highly limited sample points (e.g. less than 1% of the original dataset) Specifically, we propose to select the next best sample point based on two optimization criteria: 1) the mutual information (MI) for uncertainty reduction, and 2) the local curvature for fidelity enhancement. The combination of these two objectives leads to an optimal sampling process that balances between the exploration of the whole shape and the exploitation of the local area where the higher fidelity (or more sampling) is required. Simulation and experimental results successfully demonstrate the advantage of the proposed method in terms of estimation speed and accuracy over the conventional methods. Our approach allows us to reconstruct recognizable three dimensional shapes using only around optimally selected 0.4% of the original dataset.
A conceptual framework of the relationship between total quality management, corporate social responsibility, innovation capability, and financial performance
Year: 2017

Total quality management, corporate social responsibility, and innovation are considered as strategic orientations allowing the achievement of a sustainable competitive advantage. However, there is a gap in the literature regarding the study of the links between these three concepts in a single analysis, the majority of researchers do not gather the study of these three concepts at once, as they do not as well link them to the financial performance. The main purpose of this conceptual paper is to examine the relationship between quality, innovation, corporate social responsibility and financial performance. We are aiming to build a conceptual framework with a particular emphasis on the role that may be played by TQM practices in the development of the bidirectional link between corporate social responsibility innovation capability, and its impact on the improvement of the firm's financial performance.
Life Cycle Assessment (LCA) of Apple Orchard Management: an insight into sustainable agriculture and new opportunities
Year: 2020

Food systems rely heavily on resource and energy inputs, and are associated with environmental impacts such as emissions to air, land, and water that can affect ecosystem health and productivity. In 2018, agriculture was responsible for an estimated 661 million metric tons of CO2 equivalent, representing 9.9% of total United States (US) greenhouse gas emissions (US Environmental Protection Agency, 2018) In the face of growing populations and need for food, agricultural systems have looked towards sustainable solutions for food production so they are able to meet the needs of the consumer while decreasing environmental consequences where possible. Agricultural sustainability is a fundamental requirement for environmental conservation, food production, and food security. In order to achieve agricultural sustainability, it is essential that policies are put in place that support sustainable practices and that agricultural institutions are provided access to the necessary knowledge and technology in order to avoid eroding biodiversity and environmental quality while preparing for the inevitable challenges of climate change. In an increasingly globalized food system, sustainable agricultural systems face even more challenges in being financially competitive in even its local market. Policies that support the development of localized food systems can support consumer valuation on the relationship between themselves, the producer, and the product (Selfa Qazi, 2005; Heron Roche, 2018; Papaoikonomou Ginieis, 2017) For most agricultural producers, it would be more realistic from an economic standpoint to not be fully localized, but rather distribute in local networks and distribute through larger supply chains beyond regional networks (Heron Roche, 2018) Even when distributing outside of the local network, agricultural sustainability can be achieved when internal and external policies align to support the needs of the industry as well as the demands of the consumer.
Serology characteristics of SARS CoV 2 infection since the exposure and post symptoms onset
Venue: medRxiv
Year: 2020

Timely diagnosis of SARS CoV 2 infection is the prerequisite for treatment and preventive quarantine. The serology characteristics and complement diagnosis value of antibody test to RNA test needs to be demonstrated.  A patient cohort study was conducted at the first affiliated hospital of Zhejiang University, China. Serial sera of COVID 19 patients were collected and total antibody (Ab) IgM and IgG antibody against SARS CoV 2 were detected. The antibody dynamics during the infection were described.  The seroconversion rate for Ab, IgM and IgG in COVID 19 patients was 98.8% (79/80) 93.8% (75/80) and 93.8% (75/80) respectively. The first detectible serology marker is total antibody and followed by IgM and IgG, with a median seroconversion time of 15, 18 and 20 day post exposure (d.p.e) or 9, 10 and 12 days post onset, separately. The antibody levels increased rapidly since 6 d.p.o and accompanied with the decline of viral load. For patients in the early stage of illness (0 7d.p.o),Ab showed the highest sensitivity (64.1% compared to the IgM and IgG (33.3% for both, p<0.001) The sensitivities of Ab, IgM and IgG detection increased to 100% 96.7% and 93.3% two weeks later, respectively.  Typical acute antibody response is induced during the SARS CoV 2 infection. The serology testing provides important complementation to RNA test for pathogenic specific diagnosis and helpful information to evaluate the adapted immunity status of patient. It should be strongly recommended to apply well validated antibody tests in the clinical management and public health practice to improve the control of COVID 19 infection.
PERANCANGAN ALAT PENUKAR KALOR UNTUK PEMBANGKIT SISTEM ORC
Year: 2020

Konsumsi energi listrik nasional yang terus meningkat merupakan tantangan bagi warga negara Indonesia untuk dapat menemukan atau memberikan ide gagasan yang dapat dilakukannya penghematan sumber energi listrik. Dengan adanya energi biomassa, banyak variabel variabel yang dapat dimanfaatkan munculnya sistem penghasil energi listrik salah satunya ialah sistem Organic Rankine Cycles (ORC) Tujuan dari penelitian ini untuk rancangan alat penukar kalor yang terdapat dalam sistem ORC menggunakan refrigerant, memanfaatkan gas buang dari proses pirolisis yang merupakan salah satu proses biomassa dan merencanakan kontruksi alat penukar kalor yang berada dalam siklus ORC dengan jenis Shell and Tube. Alat penukar kalor yang direncanakan berjenis evaporator. Perencanaan ini menghitung perpindahan kalor dan kontruksi alat penukar kalor tipe Shell and Tube. Sistem ORC ini merupakan sebuah kesamaan pada sistem siklus rankine yang membedakannya ialah jika siklus rankine menggunakan fluida kerjanya adalah air, ORC menggunakan fluida kerja refrigerant. Refrigerant dipanaskan sehingga menjadi uap yang akan memutar turbin. Ukuran utama yang didapatkan dari hasil perhitungan alat penukar kalor yaitu diameter dalam Shell 488,95 mm (19,25 in) dan panjang 143657,6 mm" Fluida yang mengalir pada Shell adalah gas buang, dan fluida yang mengalir pada Tube adalah refrigerant jenis R 134a, material 304 Stainless Steel dengan jumlah 73 Tube tebal Tube 18 BWG, diameter luar Tube 1431,75 mm" Dari hasil penelitian ini dapat disimpulkan bahwa system OCR dapat ditukar dengan jenis sheel dan tube dengan spesifikasi diameter dalam Shell 19,25 in menggunakan jumlah 73 tube, dengan tebal 18 BWG, berbahan 304 Stainless Steel, fluida yang mengalir adalah R 134a.
Lifetime Portfolio Selection under Uncertainty: the Continuous time Case
Year: 2006

M OST models of portfolio selection have been one period models. I examine the combined problem of optimal portfolio selection and consumption rules for an individual in a continuous time model where his income is generated by returns on assets and these returns or instantaneous "growth rates" are stochastic. P A. Samuelson has developed a similar model in discrete time for more general probability distributions in a companion paper C81. I derive the optimality equations for a multiasset problem when the rate of returns are generated by a Wiener Brownian motion process. A particular case examined in detail is the two asset model with constant relative riskaversion or iso elastic marginal utility. An explicit solution is also found for the case of constant absolute risk aversion. The general technique employed can be used to examine a wide class of intertemporal economic problems under uncertainty. In addition to the Samuelson paper [S] there is the multi period analysis of Tobin  Phelps [6] has a model used to determine the optimal consumption rule for a multi period example where income is partly generated by an asset with an uncertain return. Mirrless S has developed a continuous time optimal consumption model of the neoclassical type with technical progress a random variable.
La evaluacion educativa del alumnado en la Universidad Tecnica de Manabi 2015
Year: 2017

La Ley Organica de Educacion Superior (LOES) de Ecuador, en la resolucion del ano 2014, establece que El Consejo de Evaluacion, Acreditacion y Aseguramiento de la Calidad de la Educacion Superior (CEAACES) sera el organismo evaluador de las instituciones de educacion superior (IES) con la finalidad de determinar si su desempeno cumple con las caracteristicas y estandares de calidad, de acuerdo a su mision, los propositos y los objetivos de la institucion. En Ecuador como tambien ocurre en paises como Mexico, Chile y Brasil, la evaluacion educativa se ha implantado como pilar fundamental de las politicas de la Educacion Superior, y esta siendo fundamental en el diseno educativo para producir una educacion de calidad. La presente investigacion, trata de diagnosticar la calidad de los procesos aplicados en la evaluacion educativa desde la valoracion de diferentes agentes que intervienen como autoridades, profesorado y alumnado. Para ello, se han considerado los indicadores "Modelo Educativo" "Motivacion" y "Evaluacion" La metodologia seleccionada aplica una encuesta contrastada por expertos y prueba piloto, que dio como resultado la encuesta final, la cual fue utilizada para medir los diferentes niveles de valoracion del proceso de evaluacion educativa desde el punto de vista de los diferentes agentes objeto de estudio en la Universidad Tecnica de Manabi.
Fast switching magnet serving a spallation driven ultracold neutron source
Venue: Physical Review Accelerators and Beams
Year: 2019

A fast switching, high repetition rate magnet and power supply have been developed for and operated at TRIUMF, to deliver a proton beam to the new ultracold neutron (UCN) facility. The facility possesses unique operational requirements: a time averaged beam current of 40~\mu$A with the ability to switch the beam on or off for several minutes. These requirements are in conflict with the typical operation mode of the TRIUMF cyclotron which delivers nearly continuous beam to multiple users. To enable the creation of the UCN facility, a beam sharing arrangement with another facility was made. The beam sharing is accomplished by the fast switching (kicker) magnet which is ramped in 50~\mu$s to a current of 193~A, held there for approximately 1~ms, then ramped down in the same short period of time. This achieves a 12~mrad deflection which is sufficient to switch the proton beam between the two facilities. The kicker magnet relies on a high current, low inductance coil connected to a fast switching power supply that is based on insulated gate bipolar transistors (IGBTs) The design and performance of the kicker magnet system and initial beam delivery results are reported.
Adiabatic compressed air energy storage for the grid integration of wind power
Year: 2006

An increasing share of electricity from renewable sources is the stated aim of national and European energy policies. However, a grid compatible integration of this fluctuating energy production to the European electricity systems is expected to be an issue in the mid term in particular in coast regions close to offshore wind farms. Large scale storage technologies can substantially mitigate the expected shortages of balancing and transport capacities. The concept of Adiabatic Compressed Air Energy Storage is a promising candidate, representing a locally emission free, pure storage technology with a high storage efficiency and a high application potential in Europe. This paper outlines the technology and reports on several areas of its development in the European "AA CAES" Project. Intermediate results indicate the technical feasibility of the concept and good prospects for its economical viability.
Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks
Venue: PSB
Year: 2017

Deep neural network (DNN) models have recently obtained state of the art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signals and give insights as to why TFs bind to certain locations. In this paper, we propose a toolkit called the Deep Motif Dashboard (DeMo Dashboard) which provides a suite of visualization strategies to extract motifs, or sequence patterns from deep neural network models for TFBS classification. We demonstrate how to visualize and understand three important DNN models: convolutional, recurrent, and convolutional recurrent networks. Our first visualization method is finding a test sequence's saliency map which uses first order derivatives to describe the importance of each nucleotide in making the final prediction. Second, considering recurrent models make predictions in a temporal manner (from one end of a TFBS sequence to the other) we introduce temporal output scores, indicating the prediction score of a model over time for a sequential input. Lastly, a class specific visualization strategy finds the optimal input sequence for a given TFBS positive class via stochastic gradient optimization. Our experimental results indicate that a convolutional recurrent architecture performs the best among the three architectures. The visualization techniques indicate that CNN RNN makes predictions by modeling both motifs as well as dependencies among them.
Genetic parameters for fatty acid composition and feed efficiency traits in Japanese Black cattle.
Venue: Animal an international journal of animal bioscience
Year: 2011

We estimated the genetic parameters related to feed intake (FI) feed efficiency traits (including feed conversion ratio (FCR) and residual feed intake (RFI) of digestible crude protein (DCP) and total digestible nutrients (TDN) beef marbling score (BMS) melting point of fat (MP) and fatty acid composition. Fat and meat (Musculus trapezius) samples were taken from the carcasses of 863 Japanese Black steers derived from 65 sires, for determination of the MP and fatty acid composition of the total lipid in intramuscular adipose tissue. Genetic parameters were estimated using uni and bivariate animal models. In addition, pedigree information for 4841 animals was used. Heritability estimates for BMS, MP, individual fatty acids, monounsaturated fatty acids (MUFA) the ratio of saturated fatty acids to MUFA (MUS) and the ratio of elongation (ELONG) were generally high. The FI values of TDN and DCP were also high, but FCRs and RFIs of those were low (0.09 to 0.22) Genetic correlation of BMS with MP was 0.34 (favorable) and with C18:1, MUFA, MUS and ELONG values were 0.40, 0.28, 0.29 and 0.37, respectively (favorable) Genetic correlations of MP with C18:1, MUFA, MUS and ELONG were negative (also favorable) and high 0.85, 0.98, 1.00 0.996) and 0.66, respectively) The correlation estimates for feed efficiency traits of DCP were quite similar to those of TDN. Genetic correlations of BMS with FCRs and RFIs of TDN and DCP were all positive (unfavorable; 0.21 to 0.51) and in particular, the correlations with RFIs of those were high. The correlations of C18:1, MUFA, MUS and ELONG with RFIs of TDN and DCP were positive (unfavorable) but low (0.06 to 0.17) whereas the corresponding correlations with FCRs of those were all negative (favorable; 0.38 to 0.10) These results suggest that the quantity and quality of beef fat can be simultaneously improved and that the quality of beef fat (fatty acid composition) can be improved directly or indirectly with MP. Furthermore, selecting MP or fatty acid traits does not significantly affect feed efficiency.
An image overall complexity evaluation method based on LSD line detection
Year: 2017

In the artificial world, whether it is the city's traffic roads or engineering buildings contain a lot of linear features. Therefore, the research on the image complexity of linear information has become an important research direction in digital image processing field. This paper, by detecting the straight line information in the image and using the straight line as the parameter index, establishing the quantitative and accurate mathematics relationship. In this paper, we use LSD line detection algorithm which has good straight line detection effect to detect the straight line, and divide the detected line by the expert consultation strategy. Then we use the neural network to carry on the weight training and get the weight coefficient of the index. The image complexity is calculated by the complexity calculation model. The experimental results show that the proposed method is effective. The number of straight lines in the image, the degree of dispersion, uniformity and so on will affect the complexity of the image.
Formaldehyde in multicomponent reactions
Year: 2021

Acting as a C1 building block, formaldehyde is of great significance in organic synthesis. It is also a key feedstock in several industries, such as resins, polymers, adhesives, and paints. Multicomponent reactions (MCRs) have emerged as applicable tools in organic reactions because efficient MCRs allow the creation of several chemical bonds in one sequence without labor consuming reaction condition optimization and work up procedures, thus minimizing waste production, cost, and labor consumption. In this review, we mainly focus on the recent advances in the contribution of formaldehyde, which was herein used as a versatile C1 building block to produce either acyclic or heterocyclic molecules via MCRs with the potential to be more sustainable than lengthier alternatives and used as a divergent chemical thanks to its excellent reactivity, flexibility, and hydrophilicity.