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We present measurements of the differential cross sections of inclusive J/ψ meson production as a function of transverse momentum (pTJ/ψ) using the μ+μ- and e+e- decay channels in proton+proton collisions at center-of-mass energies of 510 and 500 GeV, respectively, recorded by the STAR detector at the Relativistic Heavy Ion Collider. The measurement from the μ+μ- channel is for 0<pTJ/ψ<9 GeV/c and rapidity range |yJ/ψ|<0.4, and that from the e+e- channel is for 4<pTJ/ψ<20 GeV/c and |yJ/ψ|<1.0. The ψ(2S) to J/ψ ratio is also measured for 4<pTmeson<12 GeV/c through the e+e- decay channel. Model calculations, which incorporate different approaches toward the J/ψ production mechanism, are compared with experimental results and show reasonable agreement within uncertainties. © 2019 authors. Published by the American Physical Society.

Invasive crustacean species have been present in the Long Island Sound, northwestern Atlantic Ocean, for over two centuries. Three new records of introduction are recorded here from collections by local fishermen. Two records are for male Dungeness crabs, Metacarcinus magister (Dana, 1852), collected in the Western Long Island Sound (2017) and Cape Cod Bay (2018). The other record is that of a range extension documented by a single male Chinese mitten crab, Eriocheir sinensis (Milne-Edwards, 1853), found in New Haven Harbor, Connecticut. Both species could potentially harbor nonnative epibionts and endoparasites. Additionally, E. sinensis may be more likely to establish, as it has in numerous locations in the region and worldwide. © Hudson et al.

As the targets of numerous campaigns, intellectuals have sustained mental torment and physical suffering on a large scale. Like the deprivation of human rights for biological and genetic reasons in other lands or other ages, Chinese intellectuals were destined to suffer abridgement of their human rights in the People’s Republic of China for political and ideological reasons. The term “intellectuals” refers to all those who have had a middle school/higher education and those with similar educational levels. Included in the ranks of intellectuals were members of the so-called democratic parties. These people, never large in number, were mostly well educated and well known in intellectual circles. The Cultural Revolution will be long remembered by intellectuals not only as a period of continued mental torment from the earlier days, but more particularly as a period of the most cruel physical abuses in human history. Intellectuals, deprived of their most precious human rights, continue to exist in mainland China as an underclass. © 1988 by Taylor & Francis. All rights reserved.

In 1966, Mao Zedong launched the Great Proletarian Cultural Revolution in a last attempt to remake China in his image. He believed that the country was led by a party infested from the top on down with “capitalist-roaders” who had betrayed the proletarian goals of true socialism by following the bourgeois line. Denied support in the power structure, Mao sought help from the outside, mobilizing millions of high school and college students as the “Red Guards” to strike down his enemy in an unprecedented campaign that left the nation nearly paralyzed. Red Guard organizations of confusing ideological persuasions soon proliferated throughout the country, and the whole movement quickly got out of control and degenerated into total chaos. That the Red Guards were used by Mao as a tool in the ideologically based power struggle within the party is not only the consensus of most observers but also has been freely admitted by many former Red Guards. © 1988 by Taylor & Francis. All rights reserved.

Many former Red Guards who through the Cultural Revolution were encouraged to participate in unrestrained violence, saw the seamy side of the regime as a result and were themselves eventually suppressed and reached the conclusion that the system was corrupt and had to be changed. Former Red Guards who turned political activists varied greatly in their often vaguely defined outlooks and their intensity of commitment and activity. Wei Jingsheng, China’s most celebrated Red Guard-turned dissident, related a similar experience in an unfinished autobiographical account written before his arrest and smuggled out of the country in 1980. Many former Red Guards understandably see a silver lining in the destructive rampage they committed during the height of the Cultural Revolution. The Red Guard movement has come full circle. The human rights tragedy of the movement is threefold. In the first stage, the Red Guards were Mao’s “little generals” trampling on the human rights of their victims. © 1988 by Taylor & Francis. All rights reserved.

Since the fall of the Soviet Union, Belarus has been the slowest of the countries in Eastern Europe to shake off its authoritarian past and ties with Russia. However, the Maidan revolution in Ukraine and Russia's subsequent annexation of Crimea and occupation of parts of Eastern Ukraine in 2014 might have forced Belarus's president, Aleksander Lukashenka, to start questioning the terms of this relationship. Russia's violation of Ukraine's sovereignty created a much more real possibility-and fear-that, if push came to shove, Russia would not hesitate to act similarly toward Belarus. Belarus's political choices are hard to predict: will it remain a dictatorship in Russia's shadow or will it embrace democracy and the rule of law and seek closer integration with the West? This study examines Belarus's global policy alignment from 2007 to 2017 by analyzing its voting patterns on contested issues-those on which Russia's and the U.S.'s votes diverged-at the United Nations General Assembly. While Belarus seems to have been disassociating itself from Russia on some global issues, as evidenced by its voting record at the UN General Assembly, and its democracy level increased from 2014-2016, there is insufficient evidence to believe that Belarus might in fact be aligning more with the West and moving away from Russia. While Belarus's diplomatic pendulum has increasingly swung toward the US, it has inevitably bounced back to its "home base"-Russia. © 2019 Heldref Publications. All rights reserved.

In this paper, we present a Neighborhood Search Genetic Algorithms (NSGAs) for mobile robot path planning. GAs have been used successfully in a variety of path planning problem because they can search the space of all possible paths and provide the optimal one. The convergence process of GAs might be lengthy compared to traditional search techniques that depend on local search methods. We propose a hybrid approach that allows GAs to combine both the advantages of GAs and local search algorithms. GAs will create a multiple waypoint path allowing a mobile robot to navigate through static obstacles and finding the optimal path in order to approach the target location without collision. The proposed NSGAs has been examined over four different path planning case studies with varying complexity. The performance of the enhanced GA has been compared with A-star algorithm (A∗) standard GA, particle swarm optimization (PSO) algorithm. The obtained results show that the proposed approach is able to get good results compared to other algorithms. © 2019 ACM.

For decades, participant carelessness has been considered a problem in collecting data using surveys. Although participant carelessness cannot be disputed to exist, the impact it has on data quality or the level of influence or bias it produces in results is questionable. The main purpose of this paper is to determine whether participant carelessness is a substantial problem that significantly influences or biases the results of statistical analyses. This is accomplished by analyzing established management relationships through a comparison of the full, careful, and careless samples to determine the impact participant carelessness has on data results regarding correlations, t-tests, and simple linear regressions. Four detection approaches were used to identify careless participants individually, in pairs, and in three method combinations. The second purpose of this paper is to use the resampled individual reliability (RIR) approach to detect careless participants and compare it to the individual reliability approach to determine whether the two approaches are fundamentally similar. Data were collected using Mechanical Turk (N = 678). Based on the findings, participant carelessness does not appear to be a substantial problem or demonstrate levels of bias in the results in this study. There are two significant differences between the full and careful samples with the t-tests and the regression comparisons of fit statistics demonstrate the careful samples to have a weak improvement over the full sample however, none indicate bias. The findings also suggest that the individual reliability and the RIR approaches are not entirely fundamentally similar. © ACPIL.

An interpretive qualitative approach insists on the plural and negotiated nature of the meanings that humans attach to their social realities. Thus, the qualitative researcher must navigate multiple and sometimes conflicting commitments to method, data, oneself, participants, and one’s reader. This can lead us to obscure the messiness of data analysis in final research reports and to downplay how methodological choices can make our participants ‘say things.’ In this article, we compare two interpretive methods, thematic and narrative analysis, including their shared epistemological and ontological premises, and offer a pedagogical demonstration of their application to the same data excerpt. However, our broader goal is to use the divergent results to critically examine how our choice of analytic method in interpretive research influences how we (researcher + method) ‘author’ data stories. Ultimately, researcher reflexivity must go beyond acknowledging how one’s position may influence the data analysis or the participant. © 2019, © 2019 Australian and New Zealand Communication Association.

With the growing access to technology in the medical domain, an increased volume of medical data is recorded. The size and complexity of these data make the process of analysis of meaningful discoveries of beneficial patterns more challenging. This problem has attracted numerous researchers around the world. Statistical methods have been employed to handle medical data for diagnosis purposes. Unfortunately, these methods were less capable of dealing with these massive and complex datasets. To solve this problem, we suggest a process to classify medical data which includes feature selection and classification using a number of supervised learning techniques. Binary Brain Storm Optimization (BBSO) is used for feature selection, which is a population search approach that simulates the process of electing the best idea (solution), among others. We simulated six different classifiers: Naive-Bayes, K-Nearest Neighbor, Support Vector Machine, Linear Discriminant Analysis, Decision Tree and Random Forest. Five datasets adopted from the UCI Machine Learning Repository, (Breast Cancer, Diabetes, Heart Disease, Chronic Kidney, and SPECT), are employed as a benchmark test data. The performance of BBSO is evaluated using accuracy on the datasets using the various classifiers. Experimental results show that the proposed approach improves the classification performance for better medical diagnosis. © 2019 ACM.

Keystroke dynamics has been used as a form of one-time user authentication and continuous verification especially when it comes to securing the cyberspace. In this paper, we present the idea of using keystroke dynamics as a form of second layer authentication in web applications. We showed that this method can authenticate a user with high accuracy and can be used as an alternate to CAPTCHA tests, security questions and image selections that are being used today. We have developed a working web-based platform in a browser environment that enforces the proposed second-layer security. We performed penetration test experiments by launching a total of 598,500 impostor and genuine authentication attempts and found the Equal Error Rate (EER) as 10.5%. © 2019 IEEE.

Agriculture ranks one of the top contributors to global warming and nutrient pollution. Quantifying life cycle environmental impacts from agricultural production serves as scientific foundation for forming effective remediation strategies. However, the methods capable of accurately and efficiently calculating spatially explicit life cycle global warming and eutrophication impacts at a fine spatial scale over a geographic region are lacking. The objective of this study was to compare two regression models for estimating spatially explicit life cycle global warming and eutrophication, with corn production in the Midwest region as a demonstrating example. The results indicated that the gradient boosting regression tree model built with monthly weather features yielded higher predictive accuracy for life cycle global warming impact and life cycle EU. Moreover, predictive accuracy was improved at the cost of simulation time. The gradient boosting regression tree model required longer training time. Additionally, all machine learning models were million times faster than the traditional process-based model and were suitable for use in computationally-intensive applications like optimization and predication. © 2019 IEEE.

Post-discharge call programs are a simple and effective way to identify and intervene for patient care issues that may occur after discharge. Nurses play a key role in these programs and can lead quality improvement projects on their units to improve patient care during the transition from hospital to home. © 2019, Anthony J. Jannetti Publications, Inc.. All rights reserved.

As the social work field increasingly recognizes economic abuse within intimate partner relationships, the field has developed financial empowerment programs to empower survivors for their financial future. Although research has demonstrated the effectiveness of financial literacy programs, there are barriers to their implementation in the field. Studies have explored, from the perspective of advocates, best practices in incorporating financial literacy into services; however, no studies have explored implementation approaches from the perspective of survivors. This study explores, from the perspective of 34 survivors, approaches for implementing financial literacy programming. Participants described their understanding of financial empowerment as being in charge of finances, having financial power, and not having to endure the struggle. To counter financial disempowerment, participants identified the need for financial confidence, knowledge, and tools. Participants shared their strategies for saving money, though many participants reported barriers to using banks as savings tools. Almost all participants stressed the importance of financial literacy services for survivors, especially around banking, credit, and debt. Finally, participants shared recommendations for job readiness and training programming. Findings have implications for domestic violence and broader social work organizations implementing financial empowerment services. Social workers can support financial empowerment efforts through program development and research efforts. © 2019 National Association of Social Workers.

The growth in using various smart wireless devices in the last few decades has given rise to indoor localization service (ILS). Indoor localization is defined as the process of locating a user location in an indoor environment. Indoor device localization has been widely studied due to its popular applications in public settlement planning, health care zones, disaster management, the implementation of location-based services (LBS) and the Internet of Things (IoT). The ILS problem can be formulated as a learning problem utilizing Wi-Fi technology. The measured Wi-Fi signal strength can be used as an indication of the distribution of users in a various indoor location. Developing a classification model with high accuracy can be achieved using a machine learning approach. Artificial Neural Network is one of the most successful trends in machine learning. In this article, we provide our initial idea of using Cascaded Layered Recurrent Neural Network (L-RNN) for the classification of user localization in an indoor environment. Several neural network models were trained, with the best performance attainment is reported. The experimental results marked that the presented L-RNN model is highly accurate for indoor localization and can be utilized for many applications. © 2019 IEEE.