Miracle-dz/UniFAR-FTUs huggingface dataset:
Social capital and risk and protective behaviors: a global health perspective

Social capital and health research has emerged as a focus of contemporary behavioral epidemiology, while intervention research is seeking more effective measures to increase health protective behaviors and decrease health-risk behaviors. In this review we explored current literature on social capital and health outcomes at the micro-, mesa-, and macro-levels with a particular emphasis on research that incorporates a social capital framework, and adolescent and young adult engagement in risk behaviors. These data indicate that across a broad range of socio-cultural and economic contexts, social capital can affect individuals’ risk for negative health outcomes and their engagement in risk behaviors. Further research is needed which should focus on differentiating and measuring positive and negative social capital within both mainstream and alternative social networks, assessing how social constructions of gender, ethnicity, and race – within specific cultural contexts – mediate the relationship between social capital and risk and/or protective behaviors. This new research should integrate the existing research within historical socioeconomic and political conditions. In addition, social capital scales need to be developed to be both culturally and developmentally appropriate for use with adolescents living in a diversity of settings. Despite the proliferation of social capital research, the concept remains underutilized in both assessment and intervention development for adolescents’ and young adults’ engagement in risk behaviors and their associated short- and long-term poor health outcomes.
Innate Immunity and Inflammation Post-Stroke: An α7-Nicotinic Agonist Perspective

Stroke is one of the leading causes of death and long-term disability, with limited treatment options available. Inflammation contributes to damage tissue in the central nervous system across a broad range of neuropathologies, including Alzheimer’s disease, pain, Schizophrenia, and stroke. While the immune system plays an important role in contributing to brain damage produced by ischemia, the damaged brain, in turn, can exert a powerful immune-suppressive effect that promotes infections and threatens the survival of stroke patients. Recently the cholinergic anti-inflammatory pathway, in particular its modulation using α7-nicotinic acetylcholine receptor (α7-nAChR) ligands, has shown potential as a strategy to dampen the inflammatory response and facilitate functional recovery in stroke patients. Here we discuss the current literature on stroke-induced inflammation and the effects of α7-nAChR modulators on innate immune cells.
Understanding acculturation of consumer culture in an emerging market

Purpose – The purpose of this paper is to study the extent of behavioral acculturation of consumer culture (B‐ACC) and attitudinal acculturation of consumer culture (A‐ACC) among the urban, educated, middle class Indian consumers. It also aims to test if B‐ACC and A‐ACC among various demographic segments of Indian consumers differ on the basis of their ownership/usage of foreign brands vis‐a‐vis Indian brands.Design/methodology/approach – An empirical study has been conducted to address the above mentioned objectives. Data have been collected from urban, educated, middle class Indian consumers using structured questionnaire and following snowball and judgment sampling methods. Data analysis has been done using ANOVA and T‐test.Findings – The results show that highly educated Indian consumers who fall under the age group of 16‐25 years and belong to upper‐middle class show greater levels of B‐ACC as well as A‐ACC vis‐a‐vis other demographic segments of Indian consumers. In the total sample as well as among.
FRoDO: Friendly routing over dunbar-based overlays

Centralized Online Social Networks (OSNs) have become the main communication channel in both the personal and the business domain. A current trend for developing OSN services is towards the distribution of the social network infrastructure by using P2P architectures as basis for Distributed Online Social Networks (DOSNs). One of the main challenges of DOSNs comes from guaranteeing privacy and protection of private data. In previous work [18], we proposed a Dunbar-based approach to preserve data availability in DOSNs. Using Dunbar's circles of intimacy a certain level of trust is ensured which bases on the users confidence in their friends. Now, to achieve privacy and anonymity, we focus on the incorporation of social contacts into existing Peer-to-Peer Overlays and show that a naive integration of social links into existing Overlays like Chord and Pastry is not satisfactory. In order to address drawbacks of the naive approach we introduce goLLuM, a general solution which can be used on top of existing structured and unstructured P2P networks. Our protocol enables to route messages via friendly nodes only, even if only few friends per node exist. By using synthetic models and real-data traces for the representation of friendship relationships we highlight the drawbacks of the naive solution and show the functionality of goLLuM.
The development of labour market from regional point of view

Particular counties of Czech Republic differ as a result of diverse historical, natural, demographic and economic features. These divergencies are reflected on labour market not only in different employment, unemployment rate and average wages etc., but subsequently also in differentiated share of economicaly poor households, in relation to differentiated duration of unemployment, respectively working inability. The new regional and public administration breakdown should enable even more detailed view of regional differences on labour market. It should serve as a basis for application of appropriate instruments and measures in particular county.
Quadrotor tuning for attitude control based on PID controller using fictitious reference iterative tuning (FRIT)

This paper proposes a method for quadrotor tuning focusing on attitude control (roll, pitch and yaw channel). The control structure is based upon PID control which is widely used in many flight controller boards. However, it is not easy to tune control parameters of a PID controller that satisfies the desired transient response, especially using manual tuning. Thus, this paper proposes the method for quadrotor tuning by using the fictitious reference iterative tuning (FRIT) to tune the PID gains for attitude control. The proposed method is to tune the PID gains by using FRIT so that the attitude response of a quadrotor of each channel matches with a reference model response by using only one-shot first experimental input-output data from each channel. Simulation results are provided to show the effectiveness of the proposed method.
Bioconjugated Pluronic Triblock-Copolymer Micelle-Encapsulated Quantum Dots for Targeted Imaging of Cancer: In Vitro and In Vivo Studies

Early in this study, CdTe/ZnS core/shell quantum dots (QDs) were encapsulated in carboxylated Pluronic F127 triblock polymeric micelle, to preserve the optical and colloidal stability of QDs in biological fluids. Folic acid (FA) was then conjugated to the surface of QDs for the targeted delivery of the QD formulation to the tumor site, by exploiting the overexpressed FA receptors (FARs) on the tumor cells. Cytotoxicity study demonstrated that the QD formulation has negligible in vitro toxicity. The in vitro study showed that the bioconjugated micelle-encapsulated QDs, but not the unconjugated QDs, were able to efficiently label Panc-1 cancer cells. In vivo imaging study showed that bioconjugated QDs were able to target tumor site after intravenous injection of the formulation in tumor-bearing mice.
Mapping concurrent applications on network-on-chip platforms

Networks-on-chip have been proposed as the interconnect solution for building large systems-on-chip. Such platforms will be made of hardware cores, running concurrently to achieve high compute power and keep power consumption low. These platforms have many things in common with distributed systems. In this article we analyze the issues related to mapping concurrent applications on a networks-on-chip based platform. We show that the quality of the decisions made at different stages of mapping has a high impact on the overall system performance. The critical stages of application mapping for networks-on-chip platforms include partitioning the application into processing cores, mapping the communication between the cores, and resolving platform-dependent problems such as race conditions and multipoint-to-point communications. We investigate these problems using an MPEG4 video decoder application and we evaluate the performance of the mapped system in a simulation environment, using a SystemC networks-on-chip simulator.
A scalable GPU-enabled framework for training deep neural networks

In the last fifteen years, Big Data created a new generation of data analysis problems, which does not only involve the problems themselves but also the way these data are handled. Since managing terabytes of data without a proper infrastructure is unfeasible, a smart way to process these data is also necessary. A solution to this aspect deals with the creation of general algorithms that learn from observations. In this context, Deep Learning promises general, powerful, and fast machine learning algorithms, moving them one step closer to artificial intelligence. Nevertheless, fitting a deep learning model may require an huge amount of time, thus, the need of scalable infrastructures for processing large scale data sets has become ever more meaningful. In this paper, we present a framework for training these deep neural networks using heterogeneous computing resources of either grid or cloud infrastructures. The framework lets the end-users define the deep architecture they need for processing their own Big Data, while dealing with the execution of the learning algorithms on a distributed set of nodes (through Apache Flink) as well as with offloading the computation on multiple Graphics Processing Units.
A lattice worldsheet sum for 4-d Euclidean general relativity

A lattice model for four dimensional Euclidean quantum general relativity is proposed for a simplicial spacetime. It is shown how this model can be expressed in terms of a sum over worldsheets of spin networks, and an interpretation of these worldsheets as spacetime geometries is given, based on the geometry defined by spin networks in canonical loop quantized GR. The spacetime geometry has a Planck scale discreteness which arises "naturally" from the discrete spectrum of spins of SU(2) representations (and not from the use of a spacetime lattice). The lattice model of the dynamics is a formal quantization of the classical lattice model of \cite{Rei97a}, which reproduces, in a continuum limit, Euclidean general relativity.
Social innovation and the division of labour

This book is part of the series "The Library of Political Economy" which examines the interaction between economics and the technical, social, and political environment. In Social Innovation and the Division of Labour , Jonathan Gershuny proposes a new model of economic development for countries of the `First World`. Explaining all technical terms, he examines the way in which the increased use of `informal modes of production, for example, in domestic services, transport facilities, and entertainment, promoted economic growth in the 1950s and 1960s. Gershuny asks important questions about the future impact of technological changes on work patterns and the division of labour between the sexes, and the welfare state. He addresses the challenges of the future, such as the use of Information Technology to increase productivity in the public sector, and he raises the issue of securing full employment and the problems which this entails. Readership: sixth form and undergraduate students of economics, politics, sociology, and administration.
Medical Yoga for Patients with Stress-Related Symptoms and Diagnoses in Primary Health Care: A Randomized Controlled Trial

An increasing number of patients are suffering from stress-related symptoms and diagnoses. The purpose of this study was to evaluate the medical yoga treatment in patients with stress-related symptoms and diagnoses in primary health care. A randomized controlled study was performed at a primary health care centre in Sweden from March to June, 2011. Patients were randomly allocated to a control group receiving standard care or a yoga group treated with medical yoga for 1 hour, once a week, over a 12-week period in addition to the standard care. A total of 37 men and women, mean age of 53 ± 12 years were included. General stress level (measured using Perceived Stress Scale (PSS)), burnout (Shirom-Melamed Burnout Questionnaire (SMBQ)), anxiety and depression (Hospital Anxiety and Depression Scale (HADS)), insomnia severity (Insomnia Severity Index (ISI)), pain (visual analogue scale (VAS)), and overall health status (Euro Quality of Life VAS (EQ-VAS)) were measured before and after 12 weeks. Patients assigned to the Yoga group showed significantly greater improvements on measures of general stress level (P < 0.000), anxiety (P < 0.019), and overall health status (P < 0.018) compared to controls. Treatment with medical yoga is effective in reducing levels of stress and anxiety in patients with stress-related symptoms in primary health care.
Distributed PCA-based anomaly detection in wireless sensor networks

Detecting anomalies is an important challenge for intrusion detection and fault diagnosis in wireless sensor networks (WSNs). In this paper, we propose a distributed energy-efficient approach for detecting anomalies in sensed data in a WSN. The anomalies in sensed data can be caused due to compromised or malfunctioning nodes. In the proposed approach, we use distributed principal component analysis (DPCA) and fixed-width clustering (FWC) in order to establish a global normal profile and to detect anomalies. The process of establishing the global normal profile is distributed among all sensor nodes. We also use weighted coefficients and a forgetting curve to periodically update the established normal profile. We demonstrate that the proposed distributed approach achieves comparable accuracy compared to a centralized approach, while the communication overhead in the network and energy consumption is significantly reduced.
Recovery of neurofilament following early monocular deprivation

Postnatal development of the mammalian geniculostriate visual pathway is partly guided by visually driven activity. Disruption of normal visual input during certain critical periods can alter the structure of neurons, as well as their connections and functional properties. Within the layers of the dorsal lateral geniculate nucleus (dLGN), a brief early period of monocular deprivation can alter the structure and soma size of neurons within deprived-eye-receiving layers. This modification of structure is accompanied by a marked reduction in labeling for neurofilament protein, a principle component of the stable cytoskeleton. This study examined the extent of neurofilament recovery in monocularly deprived cats that either had their deprived eye opened (binocular recovery), or had the deprivation reversed to the fellow eye (reverse occlusion). The loss of neurofilament and the reduction of soma size caused by monocular deprivation were ameliorated equally and substantially in both recovery conditions after 8 days. The degree to which this recovery was dependent on visually driven activity was examined by placing monocularly deprived animals in complete darkness. Though monocularly deprived animals placed in darkness showed recovery of soma size in deprived layers, the manipulation catalyzed a loss of neurofilament labeling that extended to non-deprived layers as well. Overall, these results indicate that both recovery of soma size and neurofilament labeling is achieved by removal of the competitive disadvantage of the deprived eye. However, while the former occurred even in the absence of visually driven activity, recovery of neurofilament did not. The finding that a period of darkness produced an overall loss of neurofilament throughout the dLGN suggests that this experiential manipulation may cause the visual pathways to revert to an earlier more plastic developmental stage. It is possible that short periods of darkness could be incorporated as a component of therapeutic measures for treatment of deprivation-induced disorders such as amblyopia.
Evaluation of a Genetic Programming Approach to Generate Wireless Sensor Network Applications

This article presents a systematic evaluation of a framework based on Genetic Programming (GP) which aims the automatic generation of Wireless Sensor Network (WSN) applications. Developing WSN applications poses a challenge due to massive distribution of the network nodes. The automatic generation of applications reduces drastically costs, since the manual development is a laborious process. In our approach, the user describes the desired global behavior as a fitness function which guides the evolution of the application by the GP. A scripting language based on events and actions is used to represent the WSN behavior and the GP generates programs in this language. In order to evaluate the framework, a problem of multiple events detection is introduced. Several problem instances were used to appraise the performance of our method under different parameters. Results evidence the feasibility of our approach for the proposed problem, highlighting the challenges posed by the large search space and the dead end routing problem.
Intracellular control of axial shape in non-uniform neurites: a serial electron microscopic analysis of organelles and microtubules in AI and AII retinal amacrine neurites

AI and AII cat retinal amacrine cells have highly varicose non-uniform, neuritic processes. Processes of both types were reconstructed via a computer system using serial electron micrographs. These reconstructions were analyzed for (a) varicosity volume, surface area, and length, (b) "neck" volume, surface area, and length, (c) number of microtubules within the varicosity, (d) number of microtubules within the "neck," and (e) volume and surface area of mitochondria and smooth endoplasmic reticulum and large smooth vesicular bodies within the processes. Correlation of these parameters revealed a linear relationship between the number of microtubules in the necks and mean neck cross-sectional area (rs = 0.780, P less than 0.001), while microtubule number within the varicosities showed no correlation with varicosity volume (rs = 0.239, P greater than 0.2). Varicosity volume did, however, correlate strongly with the summed volume of mitochondria and smooth vesicular bodies contained within the varicosity for both cell types examined. The ratio between membranous organelle volume and varicosity volume for AI amacrine processes of 1:6.97 (rs = 0.927), differed from the ratio of 1:1.80 for the AII amacrine processes (rs = 0.987). Similar relationships were observed in other nonvaricose neurites such as optic tract axons. Membranous organelles appear to contribute an additional obligatory volume to the cytosol that can be as much as seven times the organelles' direct volume. These observations suggest that both the cytoskeletal components, and the membrane organelles play a direct role in determining neurite shape.
Symptomatic Neonatal Arterial Ischemic Stroke: The International Pediatric Stroke Study

BACKGROUND: Neonatal arterial ischemic stroke (AIS) has emerged as a leading cause of perinatal brain injury, cerebral palsy, and lifelong disability. The pathogenesis is poorly understood, which limits the development of treatment and prevention strategies. Multicenter studies must define epidemiology, risk factors, treatment practices, and outcomes to advance clinical trials and improve the adverse outcomes suffered by most survivors. METHODS: The International Pediatric Stroke Study is a global research initiative of 149 coinvestigators (30 centers in 10 countries). Patients with clinical and neuroimaging confirmation of symptomatic neonatal AIS were enrolled (2003–2007). Standardized, Web-based data entry collected clinical presentations, risk factors, investigations, treatments, and early outcomes. We examined predictors of infarct characteristics and discharge outcome by using multivariate logistic regression. RESULTS: Two hundred forty-eight neonates were studied (57% male, 10% premature). Most of them presented with seizure (72%) and nonfocal neurologic signs (63%). MRI was completed for 92% of the infants, although <50% had vascular imaging. Infarcts preferentially involved the anterior circulation and left hemisphere and were multifocal in 30%. Maternal health and pregnancies were usually normal. Neonates often required resuscitation (30%) and had systemic illnesses (23%). Cardiac and prothrombotic abnormalities were identified in <20% of the infants. Antithrombotic treatment was uncommon (21%) and varied internationally. Half (49%) of the infants had deficits at discharge, and data on their long-term outcomes are pending. CONCLUSIONS: Newborns with AIS are often systemically sick, whereas their mothers are usually healthy. Definitive causes for most neonatal AISs have not been established, and large-scale case-control studies are required to understand pathogenesis if outcomes are to be improved.
Modeling of slip for wheeled mobile robots

Wheeled mobile robots (WMRs) are known to be non-holonomic systems, and most dynamic models of WMRs assume that the wheels undergo rolling without slipping. This paper deals with the problem of modeling and simulation of motion of a WMR when the conditions for rolling are not satisfied at the wheels. The authors use a traction model where the adhesion coefficient between the wheels of a WMR and a hard flat surface is a function of the wheel slip. This traction model is used in conjunction with the dynamic equations of motion to simulate the motion of the WMR. The simulations show that controllers which do not take into account wheel slip give poor tracking performance for the WMR and path deviation is small only for large adhesion coefficients. This work shows the importance of wheel slip and suggests use of accurate traction models for improving tracking performance of a WMR. >