nils-herrmann/clean_scirepeval huggingface dataset:
IHRM and expatriation in Japanese MNCs: HRM practices and their impact on adjustment and job performance

Studies of international human resource management (IHRM) have pointed out that Japanese multinational companies (MNCs) tend to use more parent country nationals (PCNs) than do western MNCs. The ethnocentric staffing policies imply that the management of expatriation has a greater influence on the success of Japanese MNCs. We use survey data from 149 Japanese repatriates to examine the relationship between IHRM practices selection, preparation and corporate support and expatriate adjustment and job performance, as well as identify differences by the location of assignment. We find that selection criteria, language ability and familiarity with local cultures are positively related to work adjustment, and that leadership and relational abilities are slightly associated with job performance though there were no significant relationships between considerations for family situations and adjustment or job performance. The results also reveal that HRM practices while abroad, in particular the interactive exchange of information between expatriates and the headquarters, have a significant influence. Pre departure preparation programs are not related to the dependent variables. The data also suggests that living and working in China is a particular problem for Japanese expatriates.
Type I Interferons in Bacterial Infections: A Balancing Act
Venue: Front. Immunol.

Defense against bacterial infections requires activation of the immune response as well as timely reestablishment of tissue and immune homeostasis. Instauration of homeostasis is critical for tissue regeneration, wound healing, and host recovery. Recent studies revealed that severe infectious diseases frequently result from failures in homeostatic processes rather than from inefficient pathogen eradication. Type I interferons (IFN) appear to play a key role in such processes. Remarkably, the involvement of type I IFNs in the regulation of immune and tissue homeostasis upon bacterial insult may have beneficial or detrimental consequences for the host. The reasons for such ambivalent function of type I IFNs are not understood. The disparate effects of type I IFNs on bacterial infections are in marked contrast to their well established protective roles in most viral infections. In this review, we will focus on type I IFN effector mechanisms which balance processes involved in immune and tissue homeostasis during specific bacterial infections and highlight the most important missing links in our understanding of type I IFN functions.
"APEC Blue" Secondary Aerosol Reductions from Emission Controls in Beijing
Venue: Scientific reports

China implemented strict emission control measures in Beijing and surrounding regions to ensure good air quality during the 2014 Asia Pacific Economic Cooperation (APEC) summit. We conducted synchronous aerosol particle measurements with two aerosol mass spectrometers at different heights on a meteorological tower in urban Beijing to investigate the variations in particulate composition, sources and size distributions in response to emission controls. Our results show consistently large reductions in secondary inorganic aerosol (SIA) of 61 67% and 51 57% and in secondary organic aerosol (SOA) of 55% and 37% at 260 m and ground level, respectively, during the APEC summit. These changes were mainly caused by large reductions in accumulation mode particles and by suppression of the growth of SIA and SOA by a factor of 2 3, which led to blue sky days during APEC commonly referred to as "APEC Blue" We propose a conceptual framework for the evolution of primary and secondary species and highlight the importance of regional atmospheric transport in the formation of severe pollution episodes in Beijing. Our results indicate that reducing the precursors of secondary aerosol over regional scales is crucial and effective in suppressing the formation of secondary particulates and mitigating PM pollution.
A paradox for air pollution controlling in China revealed by "APEC Blue" and "Parade Blue"
Venue: Scientific reports

A series of strict emission control measures were implemented in Beijing and surrounding regions to ensure good air quality during the 2014 Asia Pacific Economic Cooperation (APEC) summit and 2015 Grand Military Parade (Parade) which led to blue sky days during these two events commonly referred to as "APEC Blue" and "Parade Blue" Here we calculated Multi Axis Differential Optical Absorption Spectroscopy (MAX DOAS) and Ozone Monitoring Instrument (OMI) NO2 and HCHO results based on well known DOAS trace gas fitting algorithm and WRF Chem model (with measured climatology parameter and newest emission inventor) simulated trace gases profiles. We found the NO2 columns abruptly decreased both Parade (43% and APEC (21% compared with the periods before these two events. The back trajectory cluster analysis and the potential source contribution function (PSCF) proved regional transport from southern peripheral cities plays a key role in pollutants observed at Beijing. The diminishing transport contribution from southern air mass during Parade manifests the real effect of emission control measures on NO2 pollution. Based on the ratios of HCHO over NO2 we found there were not only limited the NO2 pollutant but also suppress the O3 contaminant during Parade, while O3 increased during the APEC.
What is the state of play?

My initial response to the question posed to me is that the state of play, as a scientific field, is actually pretty healthy. By this I mean that psychologists, biologists, ethologists, neuroscientists, educators, sociologists, and others are realizing that play is an important, if not critical, aspect of life and an exciting and diverse research field. The increased interest in play over the last decade has been remarkable, and it is on this issue I will comment. On the other hand, the state of play in our children and others in our society is clearly not so promising, as other commentators in this forum have noted. Even the mass media are replete with stories on problems with the lack of recess in schools, reduction in free play, and over emphasis on organized sports and training camps for preteens. Natureoriented summer camps and exploration of the outdoors are on the decline. Targeted athletic, computer, and academically focused summer activities are emphasized by parents who are worried about the future of their children in an uncertain economic world, along with health, accident, and widely publicized fears of violence when children are left on their own to have fun. Too many adults also, it seems, focus more on watching shows and sports rather than participating actively in their leisure time. Here, I will discuss areas of play research with which I am most familiar: the origins, meaning, and diversity of play in organisms throughout the animal kingdom. Since the publication of my book on animal play (Burghardt, 2005) the study of play and related phenomena in a wide range of species has expanded greatly, and progress is being made in understanding the origins, mechanisms, evolution, development, and experience of play on many fronts (Burghardt, 2015b) These findings should be of interest to those working on basic and applied aspects of play in people. Although the situation is changing, too often scientists working on basic aspects of animal play are unfamiliar with exciting research on play in humans and human play researchers are too anthropocentrically focused on humans. This is especially true of work on pretend, sociodramatic, artistic, creative, and educationally directed play. Too often the active, locomotor, rough and tumble, and highly physical play is ignored, if not suppressed (Pellegrini Smith, 1998) But these types of play are what nonhuman animal researchers often focus on, and which are helping to understand the biological workings of play and the adaptive function of play (Pellis Pellis, 2009; Pellis, Pellis, Louise, Henzi, 2014) Indeed, studying social play may be critical to understanding the dynamics and evolution of communication (Palagi et al. 2016) But the role of play in creative and innovative behavior in animals is also receiving attention (Bateson Martin, 2013; Burghardt, 2015a)
High dietary advanced glycation end products are associated with poorer spatial learning and accelerated Ab deposition in an Alzheimer mouse model
Venue: Aging cell

There is growing evidence of the involvement of advanced glycation end products (AGEs) in the pathogenesis of neurodegenerative processes including Alzheimer's disease (AD) and their function as a seed for the aggregation of Ab, a hallmark feature of AD. AGEs are formed endogenously and exogenously during heating and irradiation of foods. We here examined the effect of a diet high in AGEs in the context of an irradiated diet on memory, insoluble Ab42, AGEs levels in hippocampus, on expression of the receptor for AGEs (RAGE) and on oxidative stress in the vasculature. We found that AD like model mice on high AGE diet due to irradiation had significantly poorer memory, higher hippocampal levels of insoluble Ab42 and AGEs as well as higher levels of oxidative stress on vascular walls, compared to littermates fed an isocaloric diet. These differences were not due to weight gain. The data were further supported by the overexpression of RAGE, which binds to Ab42 and regulates its transport across the blood brain barrier, suggesting a mediating pathway. Because exposure to AGEs can be diminished, these insights provide an important simple noninvasive potential therapeutic strategy for alleviating a major lifestyle linked disease epidemic.
A study on gait entropy image analysis for clothing invariant human identification
Venue: Multimedia Tools and Applications

A simple and common human gait may be viewed as a strong biometric cue to solve human identification problem through understanding the intrinsic patterns of gait biometrics. An individual's gait pattern appears to be different in gallery and probe gait sequences due to wearing dissimilar clothing types. The gait dataset captures the possible changes found in silhouette shape image which provides the difficulty in distinguishing among individuals. In this paper, a robust feature selection technique has been addressed through Gait Entropy Image (GEnI) analysis. The GEnI has the capacity to accumulate most significant motion information. The width of GEnI, along the horizontal axis is taken as discriminative feature which produces a small intra class variance. This information is studied as an evidence of feature invariance. The standard statistical tests such as pair wise clothing correlation and intra clothing variance are performed on gait dataset to evaluate the reliability of feature. Experimental results demonstrate the efficiency of proposed feature selection method using k nearest neighbor (k NN) minimum distance classifier (MDC) and support vector machine (SVM) algorithms. The performance analysis of recognition system has been evaluated on OU ISIR Treadmill B gait database with different error metrics after performing N fold cross validation method.
The optimization of the weblog central cluster using the genetic K means algorithm
Venue: 2016 International Seminar on Application for Technology of Information and Communication (ISemantic)

Clustering is part of data mining. Clustering is used to group objects so that one group has the same characteristics. K means widely used because it is relatively easy to use. However K means has shortcomings. K means depends on the initial centroid. Selection of initial centroid done randomly so that the cluster formed is often not optimal. The clustering results are sometimes good and sometimes bad. In this research, the Genetic K means Algorithm is used to improve K means method. Genetic algorithm method is used to find the initial centroid. The initial centroid will be used by K means. So K means can get the optimal cluster. Cluster results is validated by SSW (Sum of Square within Cluster) and SI (Silhouette Index) SSW values by Genetic K means Algorithm amounted 1,648,150,772.8 and K means amounted 2.390.800.216,39. In this research, it was found that Genetic K means Algorithm creates a homogenous cluster of 45% better than the K means. So Genetic K means Algorithm more accurate than K means in determining patterns of data.
Robust adaptive genetic K Means algorithm using greedy selection for clustering
Venue: 2016 11th International Conference on Knowledge, Information and Creativity Support Systems (KICSS)

Clustering is a task to divide objects into group depends on their similarity. The optimal of solving clustering problem occurs when the data joins in one group which has a similar category. This study combines Adaptive Genetic Algorithm, K Means and Greedy Selection to solve clustering problem, named RAGKA. In first step, the centroid is determined by K Means. Crossover and mutation are performed based on the fitness value of each centroid. At last, the greedy search is operated to get the better solution. To show the performance of RAGKA, five data sets of clustering problem are used. Moreover, RAGKA is compared with other methods as well. The result shows that RAGKA is successfully to solve cluster problem and outperforms than the others.
Smart Feature Extraction from Acoustic Camera Multi sensor Measurements

The paper applies recently developed smart approach for feature extraction from multi dimensional data sets using Echo state networks (ESN) to the focalized spectra obtained from the acoustic camera multi sensor measurements. The aim of the study is development of distance diagnostic system for prediction of wearing out of bearings. The procedure for initial features selection and features extraction from the focalized spectra was developed. Then the k means clustering algorithm and Support vector machine (SVM) classifiers were applied to differentiate the tested bearings into two classes with respect to their condition "Good" or "Bad" The results using different dimensions of the extracted features space were compared.
Preventive obesity agent montmorillonite adsorbs dietary lipids and enhances lipid excretion from the digestive tract
Venue: Scientific reports

Western diets are typically high in fat and are associated with long term complications such as obesity and hepatic steatosis. Because of the enjoyable taste of high fat diets (HFDs) we are interested in determining how to decrease lipid absorption and enhance lipid excretion from the digestive tract after the consumption of eating fatty foods. Montmorillonite was initially characterized as a gastrointestinal mucosal barrier protective agent for the treatment of diarrhoea. Dietary lipid adsorbent montmorillonite (DLA M) was isolated and purified from Xinjiang montmorillonite clay via the water extraction method. Here, we show that DLA M has an unexpected role in preventing obesity, hyperlipidaemia and hepatic steatosis in HFD fed rats. Interestingly, combined application of polarized light microscopy and lipid staining analyses, showed that DLA M crystals have dietary lipid adsorbing ability in vitro and in vivo, which enhances lipid excretion via bowel movements. In summary, our results indicate that DLA M prevent HFD induced obesity. This novel dietary lipid adsorbing agent can help prevent obesity and its comorbidities.
Retinex theory based active contour model for segmentation of inhomogeneous images
Venue: Digit. Signal Process.

Intensity inhomogeneity in images makes automated segmentation of these images difficult. As intensity inhomogeneity is often caused by inhomogeneous light reflection, the Retinex theory can be used to reduce inhomogeneity. We introduce the Retinex theory into the active contour model, which is commonly used for image segmentation. The segmentation procedure is then guided by the image intensity and light reflection. In order to solve the proposed model efficiently, we develop a new fast Split Bregman algorithm. Experimental results on a variety of real images with inhomogeneity validate the performance of the proposed methods.
Active contour driven by multi scale local binary fitting and Kullback Leibler divergence for image segmentation
Venue: Multimedia Tools and Applications

Image segmentation is an important processing in many applications such as image retrieval and computer vision. One of the most successful models for image segmentation is the level set methods which are based on local context. The methods, though comparatively effective in segmenting images with inhomogeneous intensity, are considerably computation intensive and at the risk of falling into local minima in the convergence of the active contour energy function. To address the issues, we propose a region based level set method, called KL MLBF, which is based on the multi scale local binary fitting (MLBF) and the Kullback Leibler (KL) divergence. We first apply the multi scale theory to the local binary fitting model to build MLBF. Then the energy term measured by KL divergence between regions to be segmented is incorporated into the energy function of MLBF. KL MLBF utilizes the between cluster distance and the adaptive kernel function selection strategy to formulate the energy function. Being more robust to the initial location of the contour than the classical segmentation models, KL MLBF can deal with blurry boundaries and noise problems. The results of experiments on synthetic and real images have shown that KL MLBF can improve the effectiveness of segmentation while ensuring the accuracy by accelerating the minimization of the energy function.
Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles
Venue: IEEE Transactions on Smart Grid

Electric vehicles (EVs) can be considered as flexible mobile battery storages in microgrids. For multiple microgrids in an area, coordinated scheduling on charging and discharging are required to avoid power exchange spikes between the multimicrogrid system and the main grid. In this paper, a two stage integrated energy exchange scheduling strategy for multimicrogrid system is presented, which considers EVs as storage devices. Then, several dual variables, which are representative of the marginal cost of proper constraints, are utilized to form an updated price, thereby being a modification on the original electricity price. With this updated price signal, a price based decentralized scheduling strategy is presented for the microgrid central controller. Simulation results show that the two stage scheduling strategy reduces the electricity cost and avoids frequent transitions between battery charging/discharging states. With the proposed decentralized scheduling strategy, each microgrid only needs to solve its local problem and limits the total power exchange within the safe range.
Integrated energy management system for isolated microgrids
Venue: 2016 Power Systems Computation Conference (PSCC)

This paper proposes an integrated energy management system (IEMS) for isolated microgrids considering demand response, fossil fuel based and renewable based distributed generators (DGs) and energy storage systems (ESS) In the proposed approach, the unit commitment (UC) and optimal power flow (OPF) constraints are jointly included in the IEMS model, and to account for forecasting errors in renewable generation and electricity demand, a model predictive control (MPC) technique is adopted. The proposed IEMS model is compared with a "standard" decoupled energy management system (DEMS) in which the dispatch problem is decomposed into UC and OPF sub problems, and the impact of MPC implementation and forecast errors are also analyzed. Both IEMS and DEMS approaches are tested and compared using a modified CIGRE medium voltage benchmark system. The results demonstrate the effectiveness of the proposed IEMS and MPC techniques.
Modeling Multi Product Multi Stage Supply Chain Network Design

Supply chain network makes it possible to create an effective and helpful context for managing supply chain. This network is a series of equipments that play roles in the supply chain development. In this network exist producers of raw materials and product making factories, centers of distributing products and customers. The aim of the network is minimizing the total cost so that customer's demands might be answered. In this paper, three phase multi product supply chain network model is presented. The super innovative method of genetic algorithm is used to solve these problems since they are classified into NP Hard problems. Encoding of this presented. The super innovative method of genetic algorithm is used to solve these problems since they are classified into NP Hard problems. Encoding of this genetic algorithm is based on priority centered encoding. In this method, the network nodes are developed according to their priority. Some types of problems are posed that are solved by means of genetic algorithm and mathematic programming problem solving software (LINGO) and then the results are compared. Moreover, this algorithm is shown to give acceptable answers and is therefore suitable for solving the problems in three phase multi product supply chain network.
Identifying a robust design space for glycosylation during monoclonal antibody production
Venue: Biotechnology progress

Glycan distribution has been identified as a "critical quality attribute" for many biopharmaceutical products, including monoclonal antibodies. Consequently, determining quantitatively how process variables affect glycan distribution is important during process development to control antibody glycosylation. In this work, we assess the effect of six bioreactor process variables on the glycan distribution of an IgG1 produced in CHO cells. Our analysis established that glucose and glutamine media concentration, temperature, pH, agitation rate, and dissolved oxygen (DO) had small but significant effects on the relative percentage of various glycans. In addition, we assessed glycosylation enzyme transcript levels and intracellular sugar nucleotide concentrations within the CHO cells to provide a biological explanation for the observed effects on glycan distributions. From these results we identified a robust operating region, or design space, in which the IgG1 could be produced with a consistent glycan distribution. Since our results indicate that perturbations to bioreactor process variables will cause only small (even if significant) changes to the relative percentage of various glycans 1.5% changes that are too small to affect the bioactivity and efficacy of this IgG1 significantly it follows that the glycan distribution obtained will be consistent even with relatively large variations in bioreactor process variables. However, for therapeutic proteins where bioactivity and efficacy are affected by small changes to the relative percentage of glycans, the same analysis would identify the manipulated variables capable of changing glycan distribution, and hence can be used to implement a glycosylation control strategy.