nils-herrmann/clean_scirepeval huggingface dataset:
Dietary Supplementation of Inorganic, Organic, and Fatty Acids in Pig: A Review
Venue: Animals an open access journal from MDPI
Year: 2020

The role of acids in pig feed strategies has changed from feed acidifier and preservative to growth promoter and antibiotics substitute. Since the 2006 European banning of growth promoters in the livestock sector, several feed additives have been tested with the goal of identifying molecules with the greatest beneficial antimicrobial, growth enhancing, or disease preventing abilities. These properties have been identified among various acids, ranging from inexpensive inorganic acids to organic and fatty acids, and these have been widely used in pig production. Acids are mainly used during the weaning period, which is considered one of the most critical phases in pig farming, as well as during gestation, lactation, and fattening. Such supplementation generally yields improved growth performance and increased feed efficiency; these effects are the consequences of different modes of action acting on the microbiome composition, gut mucosa morphology, enzyme activity, and animal energy metabolism.  Reduction of antibiotic use has been a hot topic of research over the past decades. The European ban on growth promoter use has increased the use of feed additivities that can enhance animal growth performance and health status, particularly during critical and stressful phases of life. Pig farming is characterized by several stressful periods, such as the weaning phase, and studies have suggested that the proper use of feed additives during stress could prevent disease and enhance performance through modulation of the gastrointestinal tract mucosa and microbiome. The types of feed additive include acids, minerals, prebiotics, probiotics, yeast, nucleotides, and phytoproducts. This review focuses on commonly used acids, classified as inorganic, organic, and fatty acids, and their beneficial and potential effects, which are widely reported in the bibliography. Acids have long been used as feed acidifiers and preservatives, and were more recently introduced into feed formulated for young pigs with the goal of stabilizing the stomach pH to offset their reduced digestive capacity. In addition, some organic acids represent intermediary products of the tricarboxylic acid cycle (TCA) and thus could be considered an energy source. Moreover, antimicrobial properties have been exploited to modulate microbiota populations and reduce pathogenic bacteria. Given these potential benefits, organic acids are no longer seen as simple acidifiers, but rather as growth promoters and potential antibiotic substitutes owing to their beneficial action on the gastrointestinal tract (GIT)
General overview on the merits of multimodal neuroimaging data fusion
Venue: NeuroImage
Year: 2014

Multimodal neuroimaging has become a mainstay of basic and cognitive neuroscience in humans and animals, despite challenges to consider when acquiring and combining non redundant imaging data. Multimodal data integration can yield important insights into brain processes and structures in addition to spatiotemporal resolution complementarity, including: a comprehensive physiological view on brain processes and structures, quantification, generalization and normalization, and availability of biomarkers. In this review, we discuss data acquisition and fusion in multimodal neuroimaging in the context of each of these potential merits. However, limitations due to differences in the neuronal and structural underpinnings of each method have to be taken into account when modeling and interpreting multimodal data using generative models. We conclude that when these challenges are adequately met, multimodal data fusion can create substantial added value for neuroscience applications making it an indispensable approach for studying the brain.
Trustworthy Cloud Service Level Agreement Enforcement with Blockchain Based Smart Contract
Venue: 2018 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)
Year: 2018

Cloud Service Level Agreement (SLA) is challengeable due to lacking a trustworthy platform. This paper presents a witness model to credibly enforce the cloud service level agreement. Through introducing the witness role and using the blockchain based smart contract, we solve the trust issues about who can detect the service violation, how the violation is confirmed and the compensation is guaranteed. In this model, a verifiable consensus sortition algorithm proposed by us is firstly leveraged to select independent witnesses to form a witness committee. They are responsible for a specific service level agreement and get paid by monitoring and detecting service violation. Through carefully designing the witness' payoff function in the agreement, we further leverage game theory to analyze and prove that it is not the witness itself is trustworthy. Instead, the witness has to tell the truth because of its greedy nature, which is the desire to maximize its own revenue. As long as the service violation is confirmed by the witness committee, the compensation is automatically transferred to the customer by the smart contract. Finally, we implement a proof of concept prototype with the smart contract of Ethereum blockchain. It demonstrates the feasibility of our model.
EVM Closed Form Expression for OFDM Signals With Tone Reservation Based PAPR Reduction
Venue: IEEE Transactions on Wireless Communications
Year: 2020

Peak to average power ratio (PAPR) reduction of OFDM signals has extensively been studied in the literature. Tone Reservation (TR) is one of the most famous algorithms and has already been included in some digital television standards such as DVB T2 and ASTC3.0. However, the literature is still lacking theoretical analysis and performance bounds for the PAPR reduction of OFDM signals, especially using TR algorithms. For the first time, this paper provides fundamental results establishing the links between TR PAPR reduction and the remaining signal distortions at the output of a non linear high power amplifier (HPA) with and without memory effects. We first derive a generic EVM expression relying on the statistical characteristics of the samples composing the time domain signal and for any PAPR reduction technique. Computing these moments in the case of the quadratically constrained quadratic problem (QCQP) algorithm known as the optimal solution to the TR PAPR reduction problem allows us to get the lower bound of the EVM of OFDM signals after TR PAPR reduction and non linear HPA. As a reference, we also provide the EVM expression using a clipping based PAPR reduction method. The obtained EVM expressions have direct practical meaning since they are in function of the input power back off (IBO) applied to the signal before the HPA. They also consist in a general analytical framework for OFDM PAPR reduction since they can be further exploited to analyze the performance of sub optimal TR based PAPR reduction algorithms.
Deconstructing perfectionism in college students: Patterns of behavior, emotion, and cognition
Venue: Personality and Individual Differences
Year: 2019

Perfectionism is a complex, multidimensional personality construct that has been linked to both adaptive and maladaptive behavioral and mental health outcomes, particularly for college students. Based on the premise that personality reflects patterns of affect, cognition, and behavior, we deconstructed perfectionism into these constituent parts, with the goal of examining how they contribute to disparate expressions of the trait. We hypothesized that distinct profiles of perfectionism would be identified, and that these profiles would be differently associated with indices of mental health and well being. Participants (N 410; M 18.9 years of age) were recruited from a voluntary online pool of undergraduate students. Data was collected through administration of several self report measures. Six underlying factors of perfectionism were identified by submitting measures of behavioral, emotional, and cognitive correlates to a principal components analysis. These factor scores were submitted to cluster analysis, which identified four distinct profiles: constructive, motivated, obsessive, and non perfectionist. The data indicated that these profiles were associated with differences in well being. Among college students, constructive and motivated expressions of perfectionism may allow individuals to pursue high standards without suffering the mental health consequences that can result from inevitable challenges and setbacks experienced in a demanding environment.
The Global Transformation: History, Modernity and the Making of International Relations
Venue: Perspectives on Politics
Year: 2016

The 'long nineteenth century' (1776 1914) was a period of political, economic, military and cultural revolutions that re forged both domestic and international societies. Neither existing international histories nor international relations texts sufficiently register the scale and impact of this 'global transformation' yet it is the consequences of these multiple revolutions that provide the material and ideational foundations of modern international relations. Global modernity reconstituted the mode of power that underpinned international order and opened a power gap between those who harnessed the revolutions of modernity and those who were denied access to them. This gap dominated international relations for two centuries and is only now being closed. By taking the global transformation as the starting point for international relations, this book repositions the roots of the discipline and establishes a new way of both understanding and teaching the relationship between world history and international relations.
Learning at the Museum
Year: 2013

Muzeji su neformalna okruzenja za ucenje, u kojima je ucenje istinski motivirano i procesirano preko znatizelje, promatranja i raznih aktivnosti. Proces takva ucenja moze biti drugaciji od procesa ucenja koje vezemo uz formalna okruzenja. Posebna prilika koju muzeji nude jest eksperimentalna priroda ucenja koja se temelji na susretima sa stvarnim objektima. U neformalnim okruzenjima kognitivno i afektivno ucenje su povezani i mogu se nadograditi. Cilj ovog rada bio je istraziti stavove studenata o ucenju u muzeju, njegovoj ucinkovitosti i pozitivnim konotacijama na odgoj i obrazovanje djece. Istrazivan je utjecaj varijable spola na oblikovanje stavova. U istrazivanju je sudjelovalo 380 studenata, od toga 140 muskaraca i 240 zena. Studenti su visoko ocijenili znacaj takva nacina ucenja, smatraju ga ucinkovitim i potrebnim u odgoju i obrazovanju ucenika. Dobiveni rezultati trebali bi aktualizirati temu poticanja sveobuhvatnije suradnje muzeja i odgojno obrazovnih ustanova.
A Two Stage Deep Learning Method for Robust Shape Reconstruction With Electrical Impedance Tomography
Venue: IEEE Transactions on Instrumentation and Measurement
Year: 2020

As a noninvasive and radiation free imaging modality, electrical impedance tomography (EIT) has attracted much attention in the last two decades and owns many industry and biomedical applications. However, due to the nonlinearity and ill posedness of its inverse problem, the EIT images always suffer from low spatial resolution and are sensitive to the modeling errors. To achieve high resolution and modeling error robust EIT image, a two stage deep learning (TSDL) method is proposed. The proposed method consists of a prereconstruction block and a convolutional neural network (CNN) The prereconstruction block learns the regularization pattern from the training data set and provides a rough reconstruction of the target. The CNN postprocesses the prereconstruction result in a multilevel feature analysis strategy and eliminates the modeling errors with prior information of the observation domain shape. The prereconstruction and CNN blocks are trained together by using a minimum square approach. To evaluate the performance of the TSDL method, the lung EIT problem was studied. The training data set is calculated from more than 100 000 EIT simulation models generated from computed tomography (CT) scans across 792 patients. Lung injury, measurement noise, and model errors are randomly simulated during the model generation process. The trained TSDL model is evaluated with simulation testes, as well as the experimental tests from a laboratory setting. According to the results, the TSDL method could achieve high accuracy shape reconstructions and is robust against measurement noise and modeling errors.
Forecasting of Groundwater Level using Artificial Neural Network by incorporating river recharge and river bank infiltration
Year: 2017

Groundwater tables forecasting during implemented river bank infiltration (RBI) method is important to identify adequate storage of groundwater aquifer for water supply purposes. This study illustrates the development and application of artificial neural networks (ANNs) to predict groundwater tables in two vertical wells located in confined aquifer adjacent to the Langat River. ANN model was used in this study is based on the long period forecasting of daily groundwater tables. ANN models were carried out to predict groundwater tables for 1 day ahead at two different geological materials. The input to the ANN models consider of daily rainfall, river stage, water level, stream flow rate, temperature and groundwater level. Two different type of ANNs structure were used to predict the fluctuation of groundwater tables and compared the best forecasting values. The performance of different models structure of the ANN is used to identify the fluctuation of the groundwater table and provide acceptable predictions. Dynamics prediction and time series of the system can be implemented in two possible ways of modelling. The coefficient correlation (R) Mean Square Error (MSE) Root Mean Square Error (RMSE) and coefficient determination (R2) were chosen as the selection criteria of the best model. The statistical values for DW1 are 0.8649, 0.0356, 0.01, and 0.748 respectively. While for DW2 the statistical values are 0.7392, 0.0781, 0.0139, and 0.546 respectively. Based on these results, it clearly shows that accurate predictions can be achieved with time series 1 day ahead of forecasting groundwater table and the interaction between river and aquifer can be examine. The findings of the study can be used to assist policy marker to manage groundwater resources by using RBI method.
Global prevalence and distribution of vancomycin resistant, vancomycin intermediate and heterogeneously vancomycin intermediate Staphylococcus aureus clinical isolates: a systematic review and meta analysis
Venue: Scientific Reports
Year: 2020

Vancomycin resistant Staphylococcus aureus (VRSA) Vancomycin intermediate S. aureus (VISA) and heterogeneous VISA (hVISA) are subject to vancomycin treatment failure. The aim of the present study was to determine their precise prevalence and investigate prevalence variability depending on different years and locations. Several international databases including Medline (PubMed) Embase and Web of Sciences were searched (data from 1997 to 2019) to identify studies that addressed the prevalence of VRSA, VISA and hVISA among human clinical isolates around the world. Subgroup analyses and meta regression were conducted to indicate potential source of variation. Publication bias was assessed using Egger's test. Statistical analyses were conducted using STATA software (version 14.0) Data analysis showed that VRSA, VISA and hVISA isolates were reported in 23, 50 and 82 studies, with an overall prevalence of 1.5% among 5855 S. aureus isolates, 1.7% among 22,277 strains and 4.6% among 47,721 strains, respectively. The overall prevalence of VRSA, VISA, and hVISA before 2010 was 1.2% 1.2% and 4% respectively, while their prevalence after this year has reached 2.4% 4.3% and 5.3% The results of this study showed that the frequency of VRSA, VISA and hVISA after 2010 represent a 2.0, 3.6 and 1.3 fold increase over prior years. In a subgroup analysis of different strain origins, the highest frequency of VRSA (3.6% and hVISA (5.2% was encountered in the USA while VISA (2.1% was more prevalent in Asia. Meta regression analysis showed significant increasing of VISA prevalence in recent years p value 0.05) Based on the results of case reports (which were not included in the calculations mentioned above) the numbers of VRSA, VISA and hVISA isolates were 12, 24 and 14, respectively, among different continents. Since the prevalence of VRSA, VISA and hVISA has been increasing in recent years (especially in the Asian and American continents) rigorous monitoring of vancomycin treatment, it's the therapeutic response and the definition of appropriate control guidelines depending on geographical regions is highly recommended and essential to prevent the further spread of vancomycin resistant S. aureus
WO3 Based Gas Sensors: Identifying Inherent Qualities and Understanding the Sensing Mechanism.
Venue: ACS sensors
Year: 2020

Semiconducting metal oxide based gas sensors are an attractive option for a wide array of applications. In particular sensors based on WO3 are promising for applications varying from indoor air quality to breath analysis. There is a great breadth of literature which examines how the sensing characteristics of WO3 can be tuned via changes in e.g. morphology or surface additives. Due to variations in measurement conditions, however, it is difficult to identify inherent qualities of WO3 from these reports. Here, the sensing behavior of five different WO3 samples is examined. The samples show good complementarity to SnO2 (the most commonly used material) based sensors. A surprising homogeneity, despite variation in morphology and preparation method is found. Using operando diffuse reflectance infrared Fourier transform spectroscopy, it is found that the oxygen vacancies are the dominant reaction partner of WO3 with the analyte gas. This surface chemistry is offered as an explanation for the homogeneity of the WO3 based sensors.
Use of programme theory to understand the differential effects of interventions across socio economic groups in systematic reviews a systematic methodology review
Venue: Systematic Reviews
Year: 2017

BackgroundSystematic review guidance recommends the use of programme theory to inform considerations of if and how healthcare interventions may work differently across socio economic status (SES) groups. This study aimed to address the lack of detail on how reviewers operationalise this in practice. methodological systematic review was undertaken to assess if, how and the extent to which systematic reviewers operationalise the guidance on the use of programme theory in considerations of socio economic inequalities in health. Multiple databases were searched from January 2013 to May 2016. Studies were included if they were systematic reviews assessing the effectiveness of an intervention and included data on SES. Two reviewers independently screened all studies, undertook quality assessment and extracted data. A narrative approach to synthesis was adopted. total of 37 systematic reviews were included, 10 of which were explicit in the use of terminology for 'programme theory' Twenty nine studies used programme theory to inform both their a priori assumptions and explain their review findings. Of these, 22 incorporated considerations of both what and how interventions do/do not work in SES groups to both predict and explain their review findings. Thirteen studies acknowledged 24 unique theoretical references to support their assumptions of what or how interventions may have different effects in SES groups. Most reviewers used supplementary evidence to support their considerations of differential effectiveness. The majority of authors outlined a programme theory in the "Introduction" and "" sections of the review to inform their assumptions or provide explanations of what or how interventions may result in differential effects within or across SES groups. About a third of reviews used programme theory to inform the review analysis and/or synthesis. Few authors used programme theory to inform their inclusion criteria, data extraction or quality assessment. Twenty one studies tested their a priori programme theory.ConclusionsThe use of programme theory to inform considerations of if, what and how interventions lead to differential effects on health in different SES groups in the systematic review process is not yet widely adopted, is used implicitly, is often fragmented and is not implemented in a systematic way.
Competitive Multi agent Deep Reinforcement Learning with Counterfactual Thinking
Venue: 2019 IEEE International Conference on Data Mining (ICDM)
Year: 2019

Counterfactual thinking describes a psychological phenomenon that people re infer the possible results with different solutions about things that have already happened. It helps people to gain more experience from mistakes and thus to perform better in similar future tasks. This paper investigates the counterfactual thinking for agents to find optimal decision making strategies in multi agent reinforcement learning environments. In particular, we propose a multi agent deep reinforcement learning model with a structure which mimics the human psychological counterfactual thinking process to improve the competitive abilities for agents. To this end, our model generates several possible actions (intent actions) with a parallel policy structure and estimates the rewards and regrets for these intent actions based on its current understanding of the environment. Our model incorporates a scenario based framework to link the estimated regrets with its inner policies. During the iterations, our model updates the parallel policies and the corresponding scenario based regrets for agents simultaneously. To verify the effectiveness of our proposed model, we conduct extensive experiments. Experimental results show that counterfactual thinking can actually benefit the agents to obtain more accumulative rewards from the environments with fair information by comparing to their opponents.
Survey on Plastic Usage among the Teenagers of Alappuzha Town, Kerala
Year: 2016

The survey was done to analyze the usage of plastic among the teenagers of Alappuzha town. College and school students as well as some of their neighbours were selected as the sample population. The sample population belonged to three age groups i.e. 15 17, 19 21 and 40 50, majority being teenagers i.e. the first two groups, comprising 91% of the total population. It is evident from the survey that without stringent control measures/ban from the side of government, the unhealthy usage of plastic as well as the pollution of environment by plastic waste would increase alarmingly. Though 73.5% of the surveyed subjects are of the opinion that plastic should be completely banned and 77% say they are ready to be involved in an initiative against plastic pollution, 92% disagree to carry a plastic bag in hand to shop so that it could be reused to maximum, 37% still prefer to use plastic carry bags instead of cloth/paper bags, 42% has adopted burning as a method of disposing plastic carry bags, 14% use more than six plastic carry bags each day, and 75% carry drinking water in plastic bottles. 51% of the people had never heard about Bisphenol A, a chemical that leaks from plastic. Survey shows that awareness given though education is not enough to equip students to take deterrent actions that favour the conservation of the environment instead of favouring ones comfort and convenience.