nils-herrmann/clean_scirepeval huggingface dataset:
Supply chain models with greenhouse gases emissions, energy usage, imperfect process under different coordination decisions
Venue: International Journal of Production Economics
Year: 2019

Environmental issues, mainly greenhouse gas (GHG) emissions, are in large part the result of the excessive use of energy in production systems. The scarcity of resources, governmental regulations, and public awareness about sustainability make them expensive for companies. The speed of producing items (production rate) impacts GHG emissions generation in manufacturing, i.e. usually faster production results in more emissions, which is controllable in many cases. The production rate also affects the process quality and reliability; i.e. fast production speeds deteriorate the system fast, resulting in reworking defective items and machine failure. Such quality and reliability issues increase energy consumption and subsequently costs. This paper develops two level (vendor buyer) supply chain models that tackle these issues. It considers two coordinated policies: classical and vendor managed inventory with consignment stock (VMI CS) where the objective is to find the values of the decision variables that yield the minimum total supply chain cost. It includes the costs of holding inventory, GHG emissions and tax, energy usage, product and process quality, and transportation operations. The decision variables are the order quantity, the number of shipments, and the production rate. The paper compares the numerical results of the two coordination policies. It also provides managerial insights on the economic and environmental performance of the supply chains.
Physical activity shapes the intestinal microbiome and immunity of healthy mice but has no protective effects against colitis in MUC2 mice
Year: 2020

The interactions among humans, their environment, and the trillions of microbes residing within the human intestinal tract form a tripartite relationship that is fundamental to the overall health of the host. Disruptions in the delicate balance between the intestinal microbiota and their host immunity are implicated in various chronic diseases including inflammatory bowel disease (IBD) There is no known cure for IBD, therefore, novel therapeutics targeting prevention and symptoms management are of great interest. Recently, physical activity in healthy mice was shown to be protective against chemically induced colitis, however the benefits of physical activity during or following disease onset is not known. In this study, we examine whether voluntary wheel running is protective against primary disease symptoms in a mucin 2 deficient (Muc2 life long model of murine colitis. We show that 6 weeks of wheel running in healthy C57BL/6 mice leads to distinct changes in fecal bacteriome, increased butyrate production, and modulation in colonic gene expression of various cytokines, suggesting an overall primed anti inflammatory state. However, these physical activity derived benefits are not present in Muc2 mice harboring a dysfunctional mucosal layer from birth, ultimately showing no improvements in clinical signs. We extrapolate from our findings that while physical activity in healthy individuals may be an important preventative measure against IBD, for those with a compromised intestinal mucosa, a commonality in IBD patients, these benefits are lost.
IE ACCME: Intelligenza Emotiva: Abilita, Credenze e Concetto di se Meta Emotivo in preadolescenti e adolescenti
Year: 2014

Antonella D'Amico Dottore di Ricerca in Psicologia generale, e ricercatore presso laFacolta di Scienze della Formazione dell'Universita degli Studi di Palermo. Ha insegnato in diversi corsi di laurea, Master universitari e Scuole di Specializzazione. Da diversi anni si occupa di Intelligenza Emotiva, ed e coautore, insieme ad Antonietta Curci, della validazione italiana del Mayer Salovey Caruso Emotional Intelligence Test (MSCEIT) Altri suoi temi di ricerca sono la psicologia dell'apprendimento e della memoria e le difficolta di apprendimento.
Animal Rights and Captivity in a Non Ideal World
Year: 2020

This chapter explores what animal ethics has to say about the issue of captivity. The best known version of animal rights morally prohibits all use of animals, including confinement. One obvious response is to reject animal rights in favor of a traditional animal welfare ethic. It is argued in this chapter, however, that there are two ways it is possible to justify animal captivity from an animal rights perspective. The first involves the adoption of a more nuanced, interest based, rights theory. This allows us to claim that animals do not have a strong enough interest in liberty to be accorded a right not to be kept in captivity. The second involves the adoption of a non ideal theory of animal rights. This allows us to bracket liberty, and therefore the issue of captivity, as a component of an ideal theory and therefore not of immediate ethical concern.
Joint Beamforming and Power Allocation Cognitive Radio Networks under Imperfect CSI
Year: 2015

Traditional beamforming and power control algo rithms in cognitive radio (CR) are based on the assumption of perfect channel state information (CSI) however; this may lead to performance degradation in realistic systems. In this paper, the problem of joint beamforming and power control is investigated in underlay CR networks with imperfect CSI. Our objective is to maximize the sum utility of secondary users (SUs) under the primary users (PUs) interference power constraints and the transmission power constraint of SUs. First, the joint beamforming and power control problem is formulated under game theory framework, where the SUs compete with each other over the beamforming vectors and transmission power level made available by the PUs. Moreover, the channel uncertainty is described using ellipsoid sets and the interference power constraints can be converted into robust interference power constraints. Besides, Nash equilibrium (NE) is considered as the solution of this game. Finally, simulation results show that the proposed scheme can converge to a locally optimal pair of beamforming vector and transmission power level in the presence of channel uncertainty.
Research on China's Cross Border E Commerce Shared Logistics Overseas Warehouse Construction
Year: 2019

In recent years, China's cross border ecommerce has entered a period of rapid development, and the overall transaction volume has maintained a growth rate of more than 20% for several consecutive years. However, at the same time as the rapid development of cross border ecommerce in China, cross border logistics has incurred problems such as high cost, long transportation and distribution time, and difficulties in returning and exchanges, which seriously restricts the development of cross border ecommerce, traditional cross border logistics. It is difficult to solve these problems. A new cross border shared logistics model overseas warehouses came into being. Although overseas warehouses can solve most problems of cross border e commerce enterprises and cross border logistics, the development of China's overseas warehouses has also encountered many difficulties. This paper first introduces the development status of cross border e commerce industry and cross border e commerce logistics, especially shared logistics overseas warehouses, and then deeply analyzes the reasons for the development of overseas warehouses. Finally, comments and suggestions on these issues are made from both macro and
Regulation of Angiotensin II receptor signaling by cysteine modification of NF kB.
Venue: Nitric oxide biology and chemistry
Year: 2011

Angiotensin II (Ang II) is a major vasoactive peptide of the renin angiotensin system. Ang II is originally found as one of potent vasoconstrictors, but is now attracted attention as an essential mediator of many cardiovascular problems, including endothelial dysfunction, arrhythmia and structural remodeling of cardiovascular systems. Most of the known pathophysiological effects of Ang II are mediated through Ang type1 receptors (AT(1)Rs) and the up regulation of AT(1)Rs is one of important causes by which Ang II can contribute to cardiovascular diseases. A growing body of evidence has suggested that reactive oxygen species (ROS) and reactive nitrogen species (RNS) play important roles in the regulation of AT(1)R signaling. In cardiac fibroblasts, stimulation with cytokines or bacterial toxins induces AT(1)R up regulation through NADPH oxidase dependent ROS production. In contrast, nitric oxide (NO) decreases AT(1)R density through cysteine modification (S nitrosylation) of a transcriptional factor, nuclear factor kB (NF kB) The difference between the effects of ROS and NO on AT(1)R expression may be caused by the difference between intracellular location of ROS signaling and that of NO signaling, as the agonist induced S nitrosylation of NF kB requires a local interaction between NO synthase (NOS) and NF kB in the perinuclear region. Thus, the spatial and temporal regulation of cysteine modification by ROS or RNS may underlie the resultant changes of AT(1)R signaling induced by agonist stimulation.
IMPLEMENTASI METODE KRIPTOGRAFI IDEA PADA PRIORITY DEALER UNTUK LAYANAN PENJUALAN DAN PEMESANAN HANDPHONE
Year: 2011

With the rapid development of technology today, dealers priority mode used when giving a statement on the distributor is relatively old because of priority dealers still have to come to this langsung.hal distributor of course take time and cost. Yet today many Web based sales system with the aim of facilitating exchange of information data remotely so that more efficient and no cost, but the weakness of using the WEB system security is not guaranteed confidentiality of data transmission. Therefore in this final project created a system Imlementasi IDEA Cryptography Methods in Priority dealer for Sales and Booking Service Mobile based WEB. So the priority dealer does not need to come directly to distributors only to make the purchase and ordering goods. Simply by logging on WEB server distributor sales reports and ordering can be performed by the priority of security dealers and confidentiality of data or messages may be secured from other parties. The results of this final project is service Generate sales and reservations system, Mobile based WEB using IDEA cryptographic algorithm so that when sending data or messages from the server to a priority dealer distributor gated.  Cryptography, IDEA, WEB server, Priority dealer.
Effective Deep Reinforcement Learning Setups for Multiple Goals on Visual Navigation
Venue: 2020 International Joint Conference on Neural Networks (IJCNN)
Year: 2020

Deep Reinforcement Learning (DRL) represents an interesting class of algorithms, since its objective is to learn a behavioral policy through interaction with the environment, leveraging the function approximation properties of neural net works. Nonetheless, for episodic problems, it is usually modeled to deal with a unique goal. In this sense, some works showed that it is possible to learn multiple goals when using a Universal Value Function Approximator (UVFA) i.e. a method to learn a universal policy by taking information about the current state of the agent and the goal. Their results are promising but show that there is still space for new contributions regarding the integration of the goal information into the model. For this reason, we propose using the Hadamard product or the Gated Attention module in the UVFA architecture for visual based problems. Also, we propose a hybrid exploration strategy based on the greedy and the categorical probability distribution, namely categorical. By systematically comparing different architectures of UVFA for different exploration strategies, and applying or not the Trust Region Policy Optimization (TRPO) we demonstrate through experiments that, for visual topologic navigation, combining visual information of the current and goal states through Hadamard product or Gated Attention module allows the network learning near optimal navigation policies. Also, we empirically show that the categorical policy helps to avoid local minimums during the training, which facilitates the convergence to better results.
Advancing Theory with Review Articles
Year: 2020

Reviewing a body of work presents unique opportunities for making a theoretical contribution. Review articles can make readers think theoretically differently about a given field or phenomenon. Yet, review articles that advance theory have been historically under represented in Journal of Management Studies. Accordingly, the purpose of this editorial is to propose a multi faceted approach for fashioning theoretical contributions in review articles, which we hope will inspire more authors to develop and submit innovative, original, and high quality theory building review articles. We argue that advancing theory with review articles requires an integrative and generative approach. We propose a non exhaustive set of avenues for developing theory with a review article: exposing emerging perspectives, analysing assumptions, clarifying constructs, establishing boundary conditions, testing new theory, theorizing with systems theory, and theorizing with mechanisms. As a journal, Journal of Management Studies is a journal of ideas new ideas; ideas drawn from reflections on extant theory and ideas with potential to change the way we understand and interpret theory. With this in mind, we think that advancing theory with review articles is an untapped source of new ideas.
"Gay capital" in gay student friendship networks
Year: 2018

This article draws on qualitative interviews with 40 gay male undergraduates at four universities across England to explore the dynamics of participants' friendship networks in the context of decreased homophobia. Describing their schools and universities as gay friendly spaces, most participants developed close friendships with both straight and sexual minority peers in spontaneous ways, away from institutional venues such as lesbian, gay, bisexual, and transgender student societies. Building on Bourdieu's conceptualization of the symbolic economy of class, I introduce a new concept to understand how having a visible gay identity can act as a form of privilege in inclusive, post gay social fields: gay capital. Through shared knowledge of gay cultures, belonging to gay social networks, and having one's gay identity recognized as a form of prestige, gay capital supplements cultural, social, and symbolic forms of capital. These findings trouble traditional generalizations of gay youth as victimized due to their sexual minority status. However, finding that participants' experiences differed across the four research settings, this article also develops an intersectional analysis by highlighting that access to gay capital is limited by other forms of class, gender, and sexual hierarchy.
GIS Based Estimation of Seasonal Solar Energy Potential for Parking Lots and Roads
Venue: 2020 IEEE Green Technologies Conference(GreenTech)
Year: 2020

The amount of sun cast on roads and parking lots determines the charging opportunities for solar vehicles and impacts the efficiency of conventional vehicles. Estimates of solar energy potential on urban surfaces to assess parking and driving conditions need to account for the shadows cast by surrounding trees and buildings. However, though existing GIS tools can calculate solar potential on surfaces that have buildings and trees, these tools do not estimate the conditions beneath trees and do not consider the seasonal changes in deciduous trees. We introduce a new approach to address these factors using pixel substitution and a light penetration factor. In this paper, we describe how to integrate these techniques into a workflow for computing solar potential estimates for parking and driving conditions. We demonstrate the methodology in an urban setting in North Carolina that includes a mixture of urban structures and trees. We provide code samples so that this workflow is easily repeatable. The solar maps produced with our method are a useful resource for planning solar vehicle parking and routing, and identifying shaded conditions for conventional vehicles.
The deterrent effects of Australian street level drug law enforcement on illicit drug offending at outdoor music festivals.
Venue: The International journal on drug policy
Year: 2017

Australian and international street level drug law enforcement deploy many strategies in efforts to prevent or deter illicit drug offending. Limited evidence of deterrence exists. This study assessed the likely impacts of four Australian policing strategies on the incidence and nature of drug use and supply at a common policing target: outdoor music festivals.  A purpose built national online survey (the Drug Policing Survey) was constructed using five hypothetical experimental vignettes that took into account four policing strategies (High Visibility Policing, Riot Policing, Collaborative Policing, and policing with Drug Detection Dogs) and a counter factual (no police presence) The survey was administered in late 2015 to 2115 people who regularly attend festivals. Participants were block randomised to receive two vignettes and asked under each whether they would use, possess, purchase, give or sell illicit drugs.  Compared to 'no police presence' any police presence led to a 4.6% point reduction in engagement in overall illicit drug offending: reducing in particular willingness to possess or carry drugs into a festival. However, it had minimal or counterproductive impacts on purchasing and supply. For example, given police presence, purchasing of drugs increased significantly within festival grounds. Offending impacts varied between the four policing strategies: Drug Detection Dogs most reduced drug possession but High Visibility Policing most reduced overall drug offending including supply. Multivariate logistic regression showed police presence was not the most significant predictor of offending decisions at festivals.  The findings suggest that street level policing may deter some forms of drug offending at music festivals, but that most impacts will be small. Moreover, it may encourage some perverse impacts such as drug consumers opting to buy drugs within festival grounds rather than carry in their own. We use our findings to highlight trade offs between the goals of public health promotion and crime control in street level enforcement.
An expert system for detecting automobile insurance fraud using social network analysis
Venue: Expert Syst. Appl.
Year: 2011

The article proposes an expert system for detection, and subsequent investigation, of groups of collaborating automobile insurance fraudsters. The system is described and examined in great detail, several technical difficulties in detecting fraud are also considered, for it to be applicable in practice. Opposed to many other approaches, the system uses networks for representation of data. Networks are the most natural representation of such a relational domain, allowing formulation and analysis of complex relations between entities. Fraudulent entities are found by employing a novel assessment algorithm, Iterative Assessment Algorithm (IAA) also presented in the article. Besides intrinsic attributes of entities, the algorithm explores also the relations between entities. The prototype was evaluated and rigorously analyzed on real world data. Results show that automobile insurance fraud can be efficiently detected with the proposed system and that appropriate data representation is vital.
Bayesian Nonnegative Matrix Factorization With Dirichlet Process Mixtures
Venue: IEEE Transactions on Signal Processing
Year: 2020

Nonnegative Matrix Factorization (NMF) is valuable in many applications of blind source separation, signal processing and machine learning. A number of algorithms that can infer nonnegative latent factors have been developed, but most of these assume a specific noise kernel. This is insufficient to deal with complex noise in real scenarios. In this paper, we present a hierarchical Dirichlet process nonnegative matrix factorization (DPNMF) model in which the Gaussian mixture model is used to approximate the complex noise distribution. Moreover, the model is cast in the nonparametric Bayesian framework by using Dirichlet process mixture to infer the necessary number of Gaussian components. We derive a mean field variational inference algorithm for the proposed nonparametric Bayesian model. We first test the model on synthetic data sets contaminated by Gaussian, sparse and mixed noise. We then apply it to extract muscle synergies from the electromyographic (EMG) signal and to select discriminative features for motor imagery single trial electroencephalogram (EEG) classification. Experimental results demonstrate that DPNMF performs better in extracting the latent nonnegative factors in comparison with state of the art methods.
UAV video coverage quality maps and prioritized indexing for wilderness search and rescue
Venue: HRI 2010
Year: 2010

Video equipped mini unmanned aerial vehicles (mini UAVs) are becoming increasingly popular for surveillance, remote sensing, law enforcement, and search and rescue operations, all of which rely on thorough coverage of a target observation area. However, coverage is not simply a matter of seeing the area (visibility) but of seeing it well enough to allow detection of targets of interest, a quality we here call "see ability" Video flashlights, mosaics, or other geospatial compositions of the video may help place the video in context and convey that an area was observed, but not necessarily how well or how often. This paper presents a method for using UAV acquired video georegistered to terrain and aerial reference imagery to create geospatial video coverage quality maps and indices that indicate relative video quality based on detection factors such as image resolution, number of observations, and variety of viewing angles. When used for offline post analysis of the video, or for online review, these maps also enable geospatial quality filtered or prioritized non sequential access to the video. We present examples of static and dynamic see ability coverage maps in wilderness search and rescue scenarios, along with examples of prioritized non sequential video access. We also present the results of a user study demonstrating the correlation between see ability computation and human detection performance.
Measuring and Modeling Execution Cost and Risk
Year: 2012

Financial markets are considered to be liquid if a large quantity can be traded quickly and with minimal price impact. Although the idea of a liquid market involves both a cost as well as a time component, most measures of execution costs tend to focus on only a single number that reflects average costs and do not explicitly account for the temporal dimension of liquidity. In practice, trading takes time because larger orders are often broken up into smaller transactions or because of price limits. Recent work shows that the time taken to transact introduces a risk component in execution costs. In this setting, the decision can be viewed as a risk reward trade off faced by the investor who can solve for a mean variance utility maximizing trading strategy. Engle, Ferstenberg, and Russell introduce an econometric method to jointly model the expected cost and risk of the trade, thereby characterizing the mean variance tradeoffs associated with different trading approaches, given market and order characteristics. They apply their methodology to a novel dataset and show that the risk component is a nontrivial part of the transaction decision.