Meta Federated Reinforcement Learning for Distributed Resource Allocation

In cellular networks, resource allocation is usually performed in a centralized way, which brings huge computation complexity to the base station (BS) and high transmission overhead. This paper explores a distributed resource allocation method that aims to maximize energy efficiency (EE) while ensuring the quality of service (QoS) for users. Specifically, in order to address wireless channel conditions, we propose a robust meta federated reinforcement learning (\textit{MFRL}) framework that allows local users to optimize transmit power and assign channels using locally trained neural network models, so as to offload computational burden from the cloud server to the local users, reducing transmission overhead associated with local channel state information. The BS performs the meta learning procedure to initialize a general global model, enabling rapid adaptation to different environments with improved EE performance. The federated learning technique, based on decentralized reinforcement learning, promotes collaboration and mutual benefits among users. Analysis and numerical results demonstrate that the proposed \textit{MFRL} framework accelerates the reinforcement learning process, decreases transmission overhead, and offloads computation, while outperforming the conventional decentralized reinforcement learning algorithm in terms of convergence speed and EE performance across various scenarios.Comment: Submitted to TW

Leveraging Trust Relations to Improve Academic Patent Recommendation

Academic patent trading is one of the important ways for university technology transfer. Compared to industry patent trading, academic patent trading suffers from a more serious information asymmetric problem. It needs a recommendation service to help companies identify academic patents that they want to pay. However, existing recommendation approaches have limitations in facilitating academic patent trading in online patent platforms because most of them only consider patent-level characteristics. A high trust degree of a company towards academic patents can alleviate the information asymmetry and encourage trading. This study proposes a novel academic patent recommendation approach with a hybrid strategy, combining citation-based relevance, connectivity, and trustworthiness. An offline experiment is conducted to evaluate the performance of the proposed recommendation approach. The results show that the proposed method performs better than the baseline methods in both accuracy and ranking

To Branch Out or Stay Focused?: Affective Shifts Differentially Predict Organizational Citizenship Behavior and Task Performance

We draw from personality systems interaction theory (PSI; Kuhl, 2000) and regulatory focus theory (Higgins, 1997) to examine how dynamic positive and negative affective processes interact to predict both task and contextual performance. Using a twice-daily diary design over the course of a three-week period, results from multi-level regression analysis revealed that distinct patterns of change in positive and negative affect optimally predicted contextual and task performance among a sample of 71 individuals employed at a medium-sized technology company. Specifically, within persons, increases (upshifts) in positive affect over the course of a work day better predicted the subsequent day’s organizational citizenship behavior (OCB) when such increases were coupled with decreases (downshifts) in negative affect. The optimal pattern of change in positive and negative affect differed, however, in predicting task performance. That is, upshifts in positive affect over the course of the work day better predicted the subsequent day’s task performance when such upshifts were accompanied by upshifts in negative affect. The contribution of our findings to PSI theory and the broader affective and motivation regulation literatures, along with practical implications, are discussed

Discrimination, Perceived Social Inequity, and Mental Health Among Rural-to-Urban Migrants in China

Status-based discrimination and inequity have been associated with the process of migration, especially with economics-driven internal migration. However, their association with mental health among economy-driven internal migrants in developing countries is rarely assessed. This study examines discriminatory experiences and perceived social inequity in relation to mental health status among rural-to-urban migrants in China. Cross-sectional data were collected from 1,006 rural-to-urban migrants in 2004-2005 in Beijing, China. Participants reported their perceptions and experiences of being discriminated in daily life in urban destination and perceived social inequity. Mental health was measured using the symptom checklist-90 (SCL-90). Multivariate analyses using general linear model were performed to test the effect of discriminatory experience and perceived social inequity on mental health. Experience of discrimination was positively associated with male gender, being married at least once, poorer health status, shorter duration of migration, and middle range of personal income. Likewise, perceived social inequity was associated with poorer health status, higher education attainment, and lower personal income. Multivariate analyses indicate that both experience of discrimination and perceived social inequity were strongly associated with mental health problems of rural-to-urban migrants. Experience of discrimination in daily life and perceived social inequity have a significant influence on mental health among rural-to-urban migrants. The findings underscore the needs to reduce public or societal discrimination against rural-to-urban migrants, to eliminate structural barriers (i.e., dual household registrations) for migrants to fully benefit from the urban economic development, and to create a positive atmosphere to improve migrant\u27s psychological well-being

Acupuncture treatment for ischaemic stroke in young adults: protocol for a randomised, sham-controlled clinical trial

INTRODUCTION: Stroke in young adults is not uncommon. Although the overall incidence of stroke has been recently declining, the incidence of stroke in young adults is increasing. Traditional vascular risk factors are the main cause of young ischaemic stroke. Acupuncture has been shown to benefit stroke rehabilitation and ameliorate the risk factors for stroke. The aims of this study were to determine whether acupuncture treatment will be effective in improving the activities of daily living (ADL), motor function and quality of life (QOL) in patients of young ischaemic stroke, and in preventing stroke recurrence by controlling blood pressure, lipids and body weight. METHODS AND ANALYSIS: In this randomised, sham-controlled, participant-blinded and assessor-blinded clinical trial, 120 patients between 18 and 45 years of age with a recent (within 1 month) ischaemic stroke will be randomised for an 8-week acupuncture or sham acupuncture treatment. The primary outcome will be the Barthel Index for ADL. The secondary outcomes will include the Fugl-Meyer Assessment for motor function; the World Health Organization Quality of Life BREF (WHOQOL-BREF) for QOL; and risk factors that are measured by ambulatory blood pressure, the fasting serum lipid, body mass index and waist circumference. Incidence of adverse events and long-term mortality and recurrence rate during a 10-year and 30-year follow-up will also be investigated. ETHICS AND DISSEMINATION: Ethics approval was obtained from the Ethics Committee of The Third Affiliated Hospital of Zhejiang Chinese Medical University. Protocol V.3 was approved in June 2013. The results will be disseminated in a peer-reviewed journal and presented at international congresses. The results will also be disseminated to patients by telephone during follow-up calls enquiring on the patient's post-study health status. TRIAL REGISTRATION NUMBER: ChiCTR-TRC- 13003317; Pre-results