nils-herrmann/clean_scirepeval huggingface dataset:
Land abandonment under rural restructuring in China explained from a cost benefit perspective

China has experienced socio economic transitions in recent decades, featuring a large amount of rural labor migrating into urban areas. As a response, rural land use has been restructured across large areas. In this process, vast amounts of land have been abandoned due to labor loss, especially in mountainous areas. Understanding how land attributes determine which land parcels are abandoned is essential to sustainable development of rural areas. Here we examine how two main farmland parcel attributes, farmland to housing distance and land quality, by affecting farming costs and benefits, and thereby profits, determine farmland abandonment. We constructed a semi empirical crop profit model based on output benefits and input costs derived from household survey data from mountainous Wulong County, Chongqing Province, China. With this model, crop profits can be estimated and in turn the farmland to housing distances at which farming profits diminish to zero "zero profit distance" abbreviated as "ZPD" can be identified. Based on the hypothesis that land will be abandoned when cultivation cannot make profits, ZPD values can be used to predict patterns of abandonment. At current price levels, the ZPD values are 5.94 km, 3.84 km, 2.52 km and 1.48 km for first class, second class, third class and fourth class land, respectively. Overall, the observed occurrence of land abandonment in relation to farmland to housing distance and land quality is concordant with the model's predictions, supporting the underlying hypothesis that land will be abandoned when the farmland to housing distance exceeds the ZPD. These findings may serve as an important tool for predicting land abandonment and identifying countermeasures for mountainous areas.
Understanding rural restructuring in China: The impact of changes in labor and capital productivity on domestic agricultural production and trade

In China, the provinces of Shandong and Henan are the leading provinces for grain production and also have the highest populations. In this study, we quantitatively analyze the impact of the two primary factors that indicate rural restructuring (namely, an increase in labor and capital augmenting technical change, represented by labor and capital productivity) on wheat production in Shandong and Henan provinces, and the consequent effects on exported and imported wheat volumes in other provinces through to 2020. For the analysis, we use The Enormous Regional Model (TERM) an established multi region computable general equilibrium model. The results show that the magnitude of change generated by the increase in labor productivity is larger than that generated by the increase in capital productivity. Therefore, great importance should be attached not only to increasing capital technical change but also improving labor technical change. This study also reveals that regional competitive industry can easily shape absolute competition superiority, which consequently exerts a large impact on the homogeneity of products. Rural China is moving into a critical stage of restructuring, and therefore the government should provide rational top down guidance. The central government should avoid adopting a "one size fits all" policy and simply supporting a single industry or particular development patterns. Rural China should form stable, sustainable, and specialized agricultural production arranged by geographic areas, which would not only guarantee China's food security, but also improve the nation's competitive capacity in the international market.
Content Based Image Retrieval Using Dominant Color and Texture Features

The purpose of this Paper is to describe our research on different feature extraction and matching techniques in designing a Content Based Image Retrieval (CBIR) system. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Content Based Image Retrieval (CBIR) is the retrieval of images based on features such as color and texture. Image retrieval using color feature cannot provide good solution for accuracy and efficiency. The most important features are Color and texture. In this paper technique used for retrieving the images based on their content namely dominant color, texture and combination of both color and texture. The technique verifies the superiority of image retrieval using multi feature than the single feature.
Automatic Playing Field Detection and Dominant Color Extraction in Sports Video Shots of Different View Types
Venue: MISSI

Sports videos are the most popular videos searched in the Web. To retrieve efficiently and effectively sports videos we need to use very sophisticated techniques of content based analysis. Many strategies of content based indexing have been already proposed, tested, and applied to categorize video shots in sports news videos. One of the techniques is based on player scene analyses leading to the detection of playing fields. The characteristic of a playing field strongly depends on the sports category. Some sports videos are characterized by a very dynamic background, others by a static background, close up view of players, in field medium view, wide view, or out of field view of the audience, small or great objects of foreground, homogeneous type of playing field with one dominant color or very diversified field. The recognition of such sports video features as dominant color of playing field and type of shot view can significantly help to categorize sports news videos. The paper discusses some aspects of the processes of automatic dominant color extraction and playing field detection basing on the experiences achieved during the experiments performed in the Automatic Video Indexer AVI.
Geological Segmentation on UAV Aerial Image Using Shape Based LSM with Dominant Color
Venue: 2016 30th International Conference on Advanced Information Networking and Applications Workshops (WAINA)

This paper proposed a geological segmentation algorithm to segment different geology, such as rivers, woodlands, and soil, etc. according on differences image feature of geology for aerial photography. In this paper, aerial image capture from low flying quadcopter unmanned aircraft vehicle (UAV) Using Fuzzy C Mean method for aerial image color classification, and estimate some dominant colors of aerial image. And then estimates each dominant color similar distribution map. Finally, shape based level set method (LSM) is employed to segment the distribution of geological that the dominant color represents. The experimental results show that the proposed algorithm is efficacious and reliable in geological segmentation.
New Approach to Image Edge Detection Based on Quantum Entropy

We propose a novel edge detection algorithm based on quantum entropy using a flexible representation of the quantum image. We use information entropy to measure the amount of information contained in digital images in view of quantum information processing. Quantum entropy can take correlations among quantum bases into the calculation of entropy, while Shannon entropy is powerless on this, namely, quantum entropy is more accurate than Shannon entropy in quantum information measurements. Therefore, the quasithreshold that leads to maximum quantum entropy should be adopted as the optimal threshold, because the maximum amount of information is obtained under this circumstance. The quantum version of the image segmentation works with computational basis states, exclusively. We prove the efficiency of the approach proposed on examples from the real world, microscopy, microarray, medical, and satellite images. We present the performance evaluation of the proposed technique based on the peak signal to noise ratio.
Long Term Forensic Mental Health Services: An Exploratory Comparison of 18 European Countries

The objective of this study was to explore current provisions within forensic mental health inpatient services for people who require longer term care within Europe. We used a structured questionnaire and follow up semi structured interviews with experts in forensic psychiatry in 18 European countries. All experts interviewed acknowledged the issue of 'long stay' in forensic psychiatry with patient characteristics including chronic mental disorder, treatment resistance and violent behavior. Formal and informal definitions of 'long stay' varied widely between countries. Eight experts stated that long stay services are currently available in their country. Of the countries without long stay services, five experts expressed a need develop them. Improved quality of life and promotion of wellbeing were emphasized as the fundamental treatment philosophy. Even without an agreed definition of 'long stay' it is clear that a proportion of mentally disordered offenders (MDOs) are 'stuck' in 'the system' Experts shared common concerns in terms of political pressures to contain dangerous MDOs for ensuring public safety as well as ethical debates regarding long term forensic mental health care. Further research is required to promote dialogue between and within countries to address the balance of patient' rights and public safety, and to produce longitudinal and economic analyses of existing long stay forensic service provisions.
Quantitative easing and related capital flows into Brazil: Measuring its effects and transmission channels through a rigorous counterfactual evaluation

We show that unconventional monetary policy in the United States appears to influence capital inflows to Brazil and, through this channel, its overall economic outlook and financial stability. In particular, quantitative easing leads to capital inflows, exchange rate appreciation, stock market price increases, credit growth and expansion of domestic activity related to consumption. Such effects are significant when considering both parameter uncertainty and a new significance test for abnormal behavior. According to a new channel identification method proposed in the paper, capital inflow is the only domestic propagation channel that systematically accounts for the estimated effects across variables and samples. Results are robust across a wide range of policy counterfactuals, regime break assumptions, testing procedures and model specifications.
Effects of Quantitative Easing Monetary Policy Exit Strategy on East Asian Currencies

type="main" With the end of the Federal Reserve Board's quantitative easing monetary policy, it is expected that the federal funds rate will be raised from almost 0% in the near future. We investigate the effects of changes in monetary policy, especially the effects of raising interest rates in the United States on East Asian currencies. Specifically, we use data on interest rates as a monetary policy instrument to investigate how changes in the US interest rates affect interest rates, exchange rates, and capital flows in East Asian emerging market economies. The analytical results suggest that East Asian countries would face capital outflows that depreciate their home currencies, with upward pressure against their own interest rates when the Federal Reserve Board raises the interest rate.
AMAC scheduling: To optimize QOS for DSRC
Venue: 2016 IEEE International Conference on Recent Trends in Electronics, Information Communication Technology (RTEICT)

Vehicle to Vehicle communication is comes under ehicular ad hoc network (VANET) VANET uses the concept of mobile ad hoc network. VANET gives flexibility to communicate between high speeds vehicles and create a network. VANET classification is done in three different category such as Vehicle to Infrastructure (V2I) Vehicle to Vehicle (V2V) and Hybrid network which is a combination of V2V and V2I network. VANET can be very effective in road safety communication, at the time of network congestion or entertainment purpose. But as services is increases QoS providing to the end user is a challenging task for service provider because of wireless medium and nature of node (vehicle is mobile with very high speed. The existing protocol proposed till today's date does not consider network initialization advertisement, periodic beaconing factor which are necessary to provide effective V2V. Due to which the broadcasted packets are neither acknowledged nor it is retransmitted which in turn increases the frame loss due to channel error. To cater this in work the author propose an Adaptive Medium Access Control (AMAC) Scheduler for prioritized multi channel Dedicated Short Range Communication (DSRC) based V2V communication in IEEE 802.11pMAC protocol. The simulation is conducted for collision, packet transmission and throughput efficiency for varied vehicle. The experimental result shows the proposed AMAC scheduler, performs better than existing Non Cooperative Cognitive Multiple Access (NCCMA) in term of collision, successful packet transmission and throughput efficiency for varied no. of vehicle and thus helps improving QoS for DSRC based V2V communication for different application like safety and non safety related application.
Morphometric Variation of Fishery Exploited Muricidae Hexaplex trunculus in the Mediterranean Sea and the Northeastern Atlantic Ocean: Implications for Stock Identification

Morphological studies of species with wide distribution range and high commercial value, such as the banded murex Hexaplex trunculus (Linnaeus, 1758) provide information on stock structure, which is the basis for understanding fish population dynamics and enable resource assessment for fisheries management. In the present study, we examined morphological variation among Atlantic and Mediterranean populations of H. trunculus using multivariate analysis. Our results supported the existence of four distinguishable stocks (Atlantic, Alboran, Western Mediterranean and Eastern Mediterranean) correctly classified 71.7% of specimens, and indicated significant degrees of variation in morphometric characteristics between regions. Examination of the contribution of each morphometric variable to the principal components and canonical functions indicated that differences among samples seemed to be associated with the shell and aperture length and width. Samples from the Atlantic Ocean and the Alboran Sea had the largest shell size and the greatest morphometric divergence. This strong morphometric differentiation appears to be associated with local environmental factors (exposure on the rocky shores, food availability and predation) and oceanographic current barriers.
1001 Inventions The Enduring Legacy Of Muslim Civilization

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Current Issues And Enduring Questions A Guide To Critical Thinking And Argument With Readings

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New puzzles for the use of non invasive ventilation for immunosuppressed patients.
Venue: Journal of thoracic disease

On October 27, 2015, Lemile and colleagues published an article in JAMA entitled "Effect of Noninvasive Ventilation vs. Oxygen Therapy on Mortality among Immunocompromised Patients with Acute Respiratory Failure: A Randomized Clinical Trial" which investigated the effects of non invasive ventilation (NIV) in 28 day mortality of 374 critically ill immunosuppressed patients. The authors found that among immunosuppressed patients admitted to the intensive care unit (ICU) with hypoxemic acute respiratory failure, early NIV compared with oxygen therapy alone did not reduce 28 day mortality. Furthermore, different from the previous publications, there were no significant differences in ICU acquired infections, duration of mechanical ventilation, or lengths of ICU or hospital stays. The study power was limited, median oxygen flow used was higher than used before or 9 L/min, NIV settings provided tidal volumes higher than what is considered protective nowadays or from 7 to 10 mL/kg of ideal body weight and the hypoxemic respiratory failure was moderate to severe (median PaO2/FIO2 was around 140) a group prone to failure in noninvasive ventilatory support. Doubts arose regarding the early use of NIV in immunosuppressed critically ill patients with non hypercapnic hypoxemic respiratory failure that need to be solved in the near future.
Implementation intention and planning interventions in Health Psychology: Recommendations from the Synergy Expert Group for research and practice
Venue: Psychology health

The current article details a position statement and recommendations for future research and practice on planning and implementation intentions in health contexts endorsed by the Synergy Expert Group. The group comprised world leading researchers in health and social psychology and behavioural medicine who convened to discuss priority issues in planning interventions in health contexts and develop a set of recommendations for future research and practice. The expert group adopted a nominal groups approach and voting system to elicit and structure priority issues in planning interventions and implementation intentions research. Forty two priority issues identified in initial discussions were further condensed to 18 key issues, including definitions of planning and implementation intentions and 17 priority research areas. Each issue was subjected to voting for consensus among group members and formed the basis of the position statement and recommendations. Specifically, the expert group endorsed statements and recommendations in the following areas: generic definition of planning and specific definition of implementation intentions, recommendations for better testing of mechanisms, guidance on testing the effects of moderators of planning interventions, recommendations on the social aspects of planning interventions, identification of the preconditions that moderate effectiveness of planning interventions and recommendations for research on how people use plans.
Longitudinal Analysis in Occupational Health Psychology: A Review and Tutorial of Three Longitudinal Modeling Techniques

There is an increasing call for the collection of longitudinal data and the use of longitudinal analysis in occupational health psychology research. Some useful and popular longitudinal analysis techniques include the cross lagged model, the latent growth model, and the latent change score model. However, previous reviews and discussions on these modeling techniques are quite generic and often overlook the connections among these techniques. Therefore, in the current article, we first reviewed the three modeling techniques as well as their existing applications in occupational health psychology research. We then present a detailed tutorial regarding how to utilise these techniques to analyze a simulated dataset. Finally, we compare the three techniques and discuss their utility for addressing different research questions in occupational health psychology.
Clinical Health Psychology And Primary Care Practical Advice And Clinical Guidance For Successful Collaboration

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Implicit processes in health psychology: Diversity and promise.
Venue: Health psychology official journal of the Division of Health Psychology, American Psychological Association

Implicit processes refer to cognitive, affective, and motivational processes that influence health decisions and behavior without the person intending that influence. This special issue aims to increase appreciation of the diverse and promising research on implicit processes in health psychology, and to promote discussion about how this research improves understanding of health behavior change and can be harnessed to meet public health mandates. The articles included in the special issue showcase this diversity and promise, and present not only new findings, but also new theories, new measures, and state of the art summaries of progress. The research demonstrates the added value of considering implicit processes for understanding health behaviors, their interactions with explicit processes and neural mechanisms, as well as the benefits of targeting implicit processes in health behavior interventions. At the same time, however, the papers in this special issue also point to potential boundary conditions, the importance of good measures and appropriate tests of implicit processes, and the challenges involved in assessing implicit processes' causal role in determining health behaviors.
Money Matters: Recommendations for Financial Stress Research in Occupational Health Psychology.
Venue: Stress and health journal of the International Society for the Investigation of Stress

Money is arguably the most important resource derived from work and the most important source of stress for contemporary employees. A substantial body of research supports the relationship between access to financial resources and health and well being, both at individual and aggregated (e.g. national) levels of analysis. Yet, surprisingly little occupational health psychology research has paid attention to financial issues experienced specifically by those in the labour force. With these issues in mind, the overarching goal of the present paper was to address conceptual and measurement issues in the study of objective and subjective aspects of financial stress and review several assessment options available to occupational health psychology researchers for both aspects of financial stress. Where appropriate, we offer guidance to researchers about choices among various financial stress measures and identify issues that require further research attention.
Modelling the Emergence of Shared Attitudes from Group Dynamics Using an Agent Based Model of Social Comparison Theory

We propose a novel agent based implementation of Festinger's social comparison theory (SCT) The social comparison model (SCM) consists of connectionist networks that simulate agent level social comparison processes. Agent networks are combined into an adaptive network structure that is shaped by social comparisons between individual agents. Simulations show how the SCM produces behavior consistent with the empirical literature on group dynamics. In addition, experimental results are reported that show how the SCM can simulate how critical and conformist norms affect interpersonal processes and emergent attitudes. We conclude that the coupling of simulations and experiments, and the use of psychologically plausible agent models within adaptive network structures, can provide new impetus to the development of models of individual and social cognition. An integrated framework such as the SCM allows investigating key theoretical predictions around the origin and maintenance of socially shared information through social comparisons in fundamentally novel ways.