Miracle-dz/UniFAR-FTUs huggingface dataset:
Ginkgolide C Suppresses Adipogenesis in 3T3-L1 Adipocytes via the AMPK Signaling Pathway

Ginkgolide C, isolated from Ginkgo biloba leaves, is a flavone reported to have multiple biological functions, from decreased platelet aggregation to ameliorating Alzheimer disease. The study aim was to evaluate the antiadipogenic effect of ginkgolide C in 3T3-L1 adipocytes. Ginkgolide C was used to treat differentiated 3T3-L1 cells. Cell supernatant was collected to assay glycerol release, and cells were lysed to measure protein and gene expression related to adipogenesis and lipolysis by western blot and real-time PCR, respectively. Ginkgolide C significantly suppressed lipid accumulation in differentiated adipocytes. It also decreased adipogenesis-related transcription factor expression, including peroxisome proliferator-activated receptor and CCAAT/enhancer-binding protein. Furthermore, ginkgolide C enhanced adipose triglyceride lipase and hormone-sensitive lipase production for lipolysis and increased phosphorylation of AMP-activated protein kinase (AMPK), resulting in decreased activity of acetyl-CoA carboxylase for fatty acid synthesis. In coculture with an AMPK inhibitor (compound C), ginkgolide C also improved activation of sirtuin 1 and phosphorylation of AMPK in differentiated 3T3-L1 cells. The results suggest that ginkgolide C is an effective flavone for increasing lipolysis and inhibiting adipogenesis in adipocytes through the activated AMPK pathway.
Fluid analysis of delay and packet discard performance for QoS support in wireless networks

Providing quality-of-service (QoS) guarantees over wireless links requires thorough understanding and quantification of the interactions among the traffic source, the wireless channel, and the underlying link-layer error control mechanisms. We account for such interactions in an analytical model that we use to investigate the delay distribution and the packet discard rate (PDR) over a wireless link. Our analysis accommodates the inherent autocorrelations in both the traffic source as well as the channel error characteristics. An on-off fluid process is used to model the arrival of packets at the transmitter. These packets are temporarily stored in a first-in-first-out (FIFO) buffer before being transmitted over a channel with a time-varying and autocorrelated service rate. Using fluid analysis, we first derive the distribution for the queueing delay at the transmitter. As part of this analysis, we solve a fundamental fluid problem, namely, the probability distribution for the workload generated by a two-state fluid source over a fixed time interval. We then use the delay analysis to derive the PDR at the receiver. A closed-form expression for the effective bandwidth subject to a delay constraint is provided as a function of the source, channel, and error scheme parameters. This expression enables fast assessment of the bandwidth requirement of real-time traffic over QoS-based wireless networks. Numerical results and simulations are used to verify the adequacy of the analysis and to study the interactions among various system parameters.
Speech separation based on improved deep neural networks with dual outputs of speech features for both target and interfering speakers

In this paper, a novel deep neural network (DNN) architecture is proposed to generate the speech features of both the target speaker and interferer for speech separation. DNN is adopted here to directly model the highly nonlinear relationship between speech features of the mixed signals and the two competing speakers. With the modified output speech features for learning the parameters of the DNN, the generalization capacity to unseen interferers is improved for separating the target speech. Meanwhile, without any prior information from the interferer, the interfering speech can also be separated. Experimental results show that the proposed new DNN enhances the separation performance in terms of different objective measures under the semi-supervised mode where the training data of the target speaker is provided while the unseen interferer in the separation stage is predicted by using multiple interfering speakers mixed with the target speaker in the training stage.
In Vivo Imaging of NF-κB Activity1

A wide range of human disorders involves inappropriate regulation of NF-κB, including cancers and numerous inflammatory conditions. Toward our goal to define mechanisms through which NF-κB leads to the development of disease, we have developed transgenic mice that express luciferase under the control of NF-κB, enabling real-time in vivo imaging of NF-κB activity in intact animals. We show that in the absence of extrinsic stimulation, strong luminescence is evident in lymph nodes in the neck region, thymus, and Peyer’s patches. Treating mice with TNF-α, IL-1α, or LPS increased the luminescence in a tissue-specific manner, with the strongest activity observed in skin, lungs, spleen, Peyer’s patches, and the wall of the small intestine. Liver, kidney, heart, muscle, and adipose tissue displayed less intense activities. Also, exposure of skin to a low dose of UV radiation increased luminescence in the exposed areas. Furthermore, induction of chronic inflammation resembling rheumatoid arthritis produced strong NF-κB activity in the affected joints, as revealed by in vivo imaging. Thus, we have developed a versatile model for monitoring NF-κB activation in vivo.
Economic Growth and Government Spending in Saudi Arabia: An Empirical Investigation

This paper empirically examines the effects of different types of government expenditures, on economic growth in Saudi Arabia. We use different econometric techniques to estimate the short- and long-run effects of these expenditures on growth and employ annual data over the period 1969-2010. Our findings indicate that while private domestic and public investments, as well as healthcare expenditure, stimulate growth in the long-run, openness to trade and spending in the housing sector can also boost short-run production. These findings draw some policy implications for Saudi policymakers on maximizing the returns of the government spending on economic growth.
Ego-net Community Mining Applied to Friend Suggestion

In this paper, we present a study of the community structure of ego-networks---the graphs representing the connections among the neighbors of a node---for several online social networks. Toward this goal, we design a new technique to efficiently build and cluster all the ego-nets of a graph in parallel (note that even just building the ego-nets efficiently is challenging on large networks). Our experimental findings are quite compelling: at a microscopic level it is easy to detect high quality communities. Leveraging on this fact we, then, develop new features for friend suggestion based on co-occurrences of two nodes in different ego-nets' communities. Our new features can be computed efficiently on very large scale graphs by just analyzing the neighborhood of each node. Furthermore, we prove formally on a stylized model, and by experimental analysis that this new similarity measure outperforms the classic local features employed for friend suggestions.
The role of plant species in biomass production and response to elevated CO 2 and N

In an experiment that factorially manipulated plant diversity, CO2, and N, we quantified the effects of the presence of species on assemblage biomass over 10 time points distributed over 5 years. Thirteen of the 16 species planted had statistically significant effects on aboveground and/or belowground biomass. Species differed dramatically in their effects on biomass without any relationship between aboveground and belowground effects. Temporal complementarity among species in their effects seasonally, successionally, and in response to a dry summer maintained the diversity‐biomass relationships over time and may be the cause behind higher diversity plots having less variation in biomass over time. The response of plant biomass to elevated N, but not CO2, was at times entirely dependent on the presence of a single species.
ZOE: A Cloud-less Dialog-enabled Continuous Sensing Wearable Exploiting Heterogeneous Computation

The wearable revolution, as a mass-market phenomenon, has finally arrived. As a result, the question of how wearables should evolve over the next 5 to 10 years is assuming an increasing level of societal and commercial importance. A range of open design and system questions are emerging, for instance: How can wearables shift from being largely health and fitness focused to tracking a wider range of life events? What will become the dominant methods through which users interact with wearables and consume the data collected? Are wearables destined to be cloud and/or smartphone dependent for their operation? Towards building the critical mass of understanding and experience necessary to tackle such questions, we have designed and implemented ZOE - a match-box sized (49g) collar- or lapel-worn sensor that pushes the boundary of wearables in an important set of new directions. First, ZOE aims to perform multiple deep sensor inferences that span key aspects of everyday life (viz. personal, social and place information) on continuously sensed data; while also offering this data not only within conventional analytics but also through a speech dialog system that is able to answer impromptu casual questions from users. (Am I more stressed this week than normal? ) Crucially, and unlike other rich-sensing or dialog supporting wearables, ZOE achieves this without cloud or smartphone support - this has important side-effects for privacy since all user information can remain on the device. Second, ZOE incorporates the latest innovations in system-on-a-chip technology together with a custom daughter-board to realize a three-tier low-power processor hierarchy. We pair this hardware design with software techniques that manage system latency while still allowing ZOE to remain energy efficient (with a typical lifespan of 30 hours), despite its high sensing workload, small form-factor, and need to remain responsive to user dialog requests.
The influence of dementia on falls, gait and rehabilitation

Background Cognitive impairment is a risk factor for falls in older adults. There is some evidence that the ability to dual-task contributes to maintaining postural stability and that cognitive impairment may impair this ability, thereby increasing falls risk. This research aims to explore physical risk factors associated with cognitive impairment and falls in older adults with mild dementia. Potential interventions for these participants will be searched for, described and theoretically modelled to develop an intervention programme to reduce their falls risk. Methods A cross-sectional survey described gait, dual-task cost, balance and falls risk characteristics of participants with mild dementia. Potential interventions were identified using two systematic literature reviews. A realist review explored theoretical mechanisms underpinning exercise-based interventions in older adults with dementia. An intervention programme was developed and preliminarily tested during a 6-week, small sample, non-randomised feasibility study. Results Older adult participants (n 69; mean age 81 years) with mild dementia (mean MoCA 21) had an increased risk of falls (1.5 median falls in previous six months; 2.48 mean physiological profile assessment [PPA] falls risk score), poor gait pattern and reduced balance. Cognition was negatively associated with gait pattern in both in simple walking and dual-task conditions. Exercise was a frequently reported intervention, with combined physical and cognitive exercise-components showing efficacy at improving gait speed (weighted mean difference [WMD] 0.08 [0.03-0.12] Z=3.65 [p≤0.001]) and balance (WMD 1.23 [0.69-1.77] Z=4.48 [p<0.001]) at a mild stage of cognitive impairment. Physiological-responses and encouragement were identifiable important mechanisms in these interventions. Findings were synthesised into a study protocol. Ten older adults (median age 84, range 69 to 89; 50% women) with mild dementia (median MoCA 21, range 16 to 26) were recruited and completed the developed intervention of combined physical and cognitive exercises. Mean differences between pre- and post-intervention assessment demonstrated improvement in falls risk, balance, and gait. Conclusion Mixed methods contributed to each component of development for this complex intervention. A combined physical and cognitive exercise-based programme was deliverable, feasible, and acceptable to older adults with mild dementia. A list of clinically-relevant recommendations for the content, delivery, and supervision of this intervention for an adequately powered, and randomised study, was produced.
Social Accounting and Unethical Behavior: Does Looking Fair Undermine Actually Being Fair?

In organizations, it is inevitable that some business activities might seem unfair to subordinates. Social accounts—the explanations managers give their subordinates for those decisions—are known to be a useful tool for managing subordinates’ fairness concerns. Over three decades of research, we learn that social accounts are effectiveness in improving subordinates’ fairness perceptions and reducing their negative reactions. Yet, we have only limited understanding about how social accounts affect the perceptions and behaviors of managers—those who construct and give them. The purpose of this dissertation is to examine the extent to which constructing accounts affects account-givers’ perceptions and behaviors. Drawing on research in social account and behavioral ethics, a model was developed to test the positive effect of constructing accounts on unethical behavior (direct effect) through moral disengagement and guilt (indirect effect). In respect to account types, it was hypothesized that constructing justifications would lead to higher moral disengagement, less guilt, and more unethical behavior, compared with constructing excuses. Account feedback was hypothesized to moderate the indirect effects of justifications and excuses on unethical behaviors such that account acceptance would strengthen moral disengagement and weaken guilt, and in turn, increase unethical behavior. Two experimental designed studies were conducted to test these hypotheses. In Study 1, utilizing a sample of 128 management students, constructing accounts was found to have a
‘I Know What Freedom and Responsibility Mean Now’

This article analyses narratives of autonomous adulthood among Korean international students at an American state university. I categorize student narratives in terms of the number of activities associated with achieving adulthood markers and the efficacy of individual agency. A broad perspective considers a wide variety of activities to contribute to autonomous adulthood and valourizes individual agency. A narrow perspective focuses on activities tailored to one’s career, and downplays individual agency compared to larger institutional-structural factors. I examine these narratives among three groups of international students, depending on their time of arrival: pre-college migrants who moved to the USA during middle or high school, college-migrants who arrived during the first or second year of undergraduate college and post-college migrants who came for advanced degrees (e.g., MA, PhD). The finding suggests that students negotiate agency and structure differently depending on their past and current experiences in the sending and receiving countries.
Human values, subjective well-being and the metropolitan region

ABSTRACT Human values, subjective well-being and the metropolitan region. Regional Studies. Living in a country’s largest metropolitan centre has a negative effect on subjective well-being. Although documented in many developed economies, the reasons for this particular geography of well-being are still poorly understood. Meanwhile a separate body of research has shown that the holding of extrinsic or personally focused values is also associated with lower levels of subjective well-being. This paper demonstrates the link between the two. It draws on the European Social Survey (ESS) 2012 to show how metropolitan residents in Finland are more likely to hold extrinsic values such as power and achievement.
Real-Time Anomalous Behavior Detection and Localization in Crowded Scenes

In this paper, we propose an accurate and real-time anomaly detection and localization in crowded scenes, and two descriptors for representing anomalous behavior in video are proposed. We consider a video as being a set of cubic patches. Based on the low likelihood of an anomaly occurrence, and the redundancy of structures in normal patches in videos, two (global and local) views are considered for modeling the video. Our algorithm has two components, for (1) representing the patches using local and global descriptors, and for (2) modeling the training patches using a new representation. We have two Gaussian models for all training patches respect to global and local descriptors. The local and global features are based on structure similarity between adjacent patches and the features that are learned in an unsupervised way. We propose a fusion strategy to combine the two descriptors as the output of our system. Experimental results show that our algorithm performs like a state-of-the-art method on several standard datasets, but even is more time-efficient.
The strength of random search on automated program repair

Automated program repair recently received considerable attentions, and many techniques on this research area have been proposed. Among them, two genetic-programming-based techniques, GenProg and Par, have shown the promising results. In particular, GenProg has been used as the baseline technique to check the repair effectiveness of new techniques in much literature. Although GenProg and Par have shown their strong ability of fixing real-life bugs in nontrivial programs, to what extent GenProg and Par can benefit from genetic programming, used by them to guide the patch search process, is still unknown. To address the question, we present a new automated repair technique using random search, which is commonly considered much simpler than genetic programming, and implement a prototype tool called RSRepair. Experiment on 7 programs with 24 versions shipping with real-life bugs suggests that RSRepair, in most cases (23/24), outperforms GenProg in terms of both repair effectiveness (requiring fewer patch trials) and efficiency (requiring fewer test case executions), justifying the stronger strength of random search over genetic programming. According to experimental results, we suggest that every proposed technique using optimization algorithm should check its effectiveness by comparing it with random search.
Implementing the New Structural Model of the Czech National Bank

The purpose of the paper is to introduce the new â€œg3â€ structural model of the Czech National Bank and illustrate how it is used for forecasting and policy analysis. As from January 2007 the model was regularly used for shadowing official forecasts, and in July 2008 it became the core model of the CNB. In the paper we highlight the most important and unusual features of the model and discuss tools and procedures that help us in forecasting and assessing the economy with the model. The paper is not meant to provide a full derivation of the model or the complete characteristics of its behavior and should not be regarded as model documentation. Rather, the paper demonstrates how the model is used and how it contributes to policy analysis.
Re-Greening Ethiopia: History, Challenges and Lessons

In Ethiopia, deforestation rates remain high and the gap between demand and domestic supply of forest products is expanding, even though government-initiated re-greening efforts began over a century ago. Today, over 3 million hectares (ha) of degraded forest land are under area exclosure; smallholder plantations cover 0.8 million ha; and state-owned industrial plantations stagnate at under 0.25 million ha. This review captures experiences related to re-greening practices in Ethiopia, specifically with regards to area exclosure and afforestation and reforestation, and distills lessons regarding processes, achievements and challenges. The findings show that farmers and non-governmental organizations (NGOs) are the main players, and that the private sector has so far played only a small role. The role of the government was mixed: supportive in some cases and hindering in others. The challenges of state- and NGO-led re-greening practices are: inadequate involvement of communities; poorly defined rehabilitation objectives; lack of management plans; unclear responsibilities and benefit-sharing arrangements; and poor silvicultural practices. The lessons include: a more active role for non-state actors in re-greening initiatives; more attention to market signals; devolution of management responsibility; clear definition of responsibilities and benefit-sharing arrangements; and better tenure security, which are all major factors
Alienation and Persistent School Absenteeism

Several studies have drawn attention to the importance of the psychological concept of alienation for education (Seeman, 1959; Dean, 1961, Burbach, 1972; Anderson,1973). Cohen (1976: p. 75) has suggested that when a pupil fails to gain recognition and a favourable self-image he will tend to withdraw from the particular activity and strive to devalue its worth. By implication, therefore, if a pupil consistently meets unrewarding stimuli at school, he can become alienated from his school. The possibility exists that over a longer period of time this pupil will first decide to withdraw from school and later graduate to the point where he becomes a persistent school absentee. Despite this posstbtltty.fhere have been no previous investigations which have directly studied the relationship between alienation at school and persistent school absenteeism.
Adolescent Romantic Relationship–Oriented Facebook Behaviors: Implications for Self-Esteem

Despite the consistent, high use of Facebook among adolescents, few studies have examined how adolescents use Facebook when forming and maintaining romantic relationships. Based on the Internet-enhanced self-disclosure hypothesis, romantic relationship–oriented Facebook behaviors are likely to relate to adolescent self-esteem. The goal of this study is to examine romantic relationship–oriented Facebook behaviors (private exchanges, monitoring, public displays, and oversharing information) between adolescents and their romantic partners or crushes, and then test how these behaviors relate to self-esteem. Data come from an online survey of adolescents from the Midwestern United States who are current Facebook users. Results demonstrated that the most common romantic relationship–oriented Facebook behavior was monitoring. Regression analyses revealed that monitoring predicted lower adolescent self-esteem. Relationship satisfaction moderated the association between self-esteem and both private exchanges and oversharing information. Implications for adolescent romantic relationship development are discussed.