Miracle-dz/UniFAR-FTUs huggingface dataset:
Progressive Resistance Exercise and Parkinson's Disease: A Review of Potential Mechanisms

This paper reviews the therapeutically beneficial effects of progressive resistance exercise (PRE) on Parkinson's disease (PD). First, this paper discusses the rationale for PRE in PD. Within the first section, the review discusses the central mechanisms that underlie bradykinesia and muscle weakness, highlights findings related to the central changes that accompany PRE in healthy individuals, and extends these findings to individuals with PD. It then illustrates the hypothesized positive effects of PRE on nigro-striatal-thalamo-cortical activation and connectivity. Second, it reviews recent findings of the use of PRE in individuals with PD. Finally, knowledge gaps of using PRE on individuals with PD are discussed along with suggestions for future research.
Heritability of Verbal and Performance Intelligence in a Pediatric Longitudinal Sample

The longitudinal stability of IQ is well-documented as is its increasing heritability with age. In a longitudinal twin study, we addressed the question to what extent heritability and stability differ for full scale (FSIQ), verbal (VIQ), and performance IQ (PIQ) in childhood (age 9–11 years), and early adolescence (age 12–14 years). Genetic and environmental influences and correlations over time were evaluated in an extended twin design, including Dutch twins and their siblings. Intelligence was measured by the Wechsler Intelligence Scale for children — Third version (WISC III). Heritability in childhood was 34% for FSIQ, 37% for VIQ, and 64% for PIQ, and increased up to 65%, 51%, and 72% in early adolescence. The influence of common environment decreased between childhood and early adolescence from explaining 43% of the phenotypic variance for FSIQ to 18% and from 42% for VIQ to 26%. For PIQ common environmental influences did not play a role, either in childhood or in early adolescence. The stability in FSIQ and VIQ across the 3-year interval (rp) was . 72 for both measures and was explained by genetic and common environmental correlations across time (FSIQ, rg = .96, rc = 1.0; VIQ, rg =.78, rc = 1.0). Stability of PIQ (rp =.56) was lower and was explained by genetic influences (rg = .90). These results confirm the robust findings of increased heritability of general cognitive abilities during the transition from childhood to adolescence. Interestingly, results for PIQ differ from those for FSIQ and VIQ, in that no significant contribution of environment shared by siblings from the same family was detected.
A practical approach to scatternet formation and routing on Bluetooth

Bluetooth is a mobile ad-hoc network aiming to serve voice, video, and data applications. Piconet is the smallest Bluetooth network unit that can be formed by a group of nodes. Scatternets are formed by joining piconets. In this paper, a practical scatternet formation protocol and an application utilizing this protocol are introduced. Scatternet formation protocols proposed until now are slow to establish the network for many application types. The suggested protocol is built on the experience gained from other scatternet formation protocols, ad-hoc routing protocols and sensor network routing protocols. It is practical, quick to establish, and easy to operate when data is flowing across the network
The Difficulty of Path Traversal in Information Networks

This paper introduces a set of classification techniques for determining the difficulty — for a human — of path traversal in an information network. In order to ensure the generalizability of our approach, we do not use ontologies or concepts of expected semantic relatedness, but rather focus on local and global structural graph properties and measures to determine the difficulty of finding a certain path. Using a large corpus of over two million traversed paths on Wikipedia, we demonstrate how our techniques are able to accurately assess the human difficulty of finding a path between two articles within an information network.
Association rule mining for project performance measurement of Technology Transfer Centers in Thailand

In Thailand, there are many Technology Transfer Centers (TTC) located in every district of the country. However, the evaluation of their performance is difficult and complex since TTCs are different in size, location, type of training and expertise. Accordingly, the study of TTC project performance in Thailand is scanty due to the limitations of confidentiality. This study uses data mining techniques to analyze historical data of project profiles from Technology Transfer Centers (TTC) in Thailand. TTC data are segmented into groups according to their performance. This method is used to separate value centers from the inactive ones. Then a priori algorithm is applied to find the relationships within TTC features and project profiles of clusters having different performances. The results of this study will benefit the organization in exploiting it to bring about a competitive advantage and being able to improve the efficiency of TTC as well as its application to strategic planning.
Trade Unions and EU Politics: Explaining Variation in European Strategies

[From the introduction]. Already in the years preceding the SEA, broad transformations in the nature of work and economy had undermined the position of many trade unions across Western Europe.1 Even in cases where trade unions retained influence with government, over the 1980s central political authority was undermined as, "Decisions on macroeconomic conditions were increasingly made, not in national policy arenas where neo-corporatist deals could be struck, but in intergovernmental negotiations and global markets beyond most unions’ control.2" But especially since the 1986 Single European Act (SEA), European integration has changed the environment in which trade unions act in important ways. In the past twenty years, European integration has moved beyond its relatively narrow economic basis, to impact areas of key significance for trade unions, including macroeconomic policies, social policies and even industrial relations. This expansion of the EU’s competence has changed the opportunity structure facing the trade unions by creating both challenges as well as new opportunities. That is to say that European integration has undermined existing national trade union arrangements while simultaneously creating a new arena of policy-making open to trade union influence. While integration has acted as a force for economic liberalization and deregulation, it also provides for a significant amount of actual and potential re-regulation at the European level. And although deregulatory processes have advanced much farther than has European level social re-regulation, the institutionalization of the European arena nevertheless creates new opportunities for trade union influence.
A scalable, on‐board localisation and communication system for indoor multi‐robot experiments

We describe the first prototypes of an inter‐robot infrared localisation and communication system. The system detects the relative positions (both range and bearing) of autonomous mobile robots with an update rate of up to 20 Hz, a range of up to 3 m and an accuracy of 40 cm for range and 45° for bearing. In addition, each robot can send at least 1 byte of data to all the other robots within the range per update cycle. Flocking on a group of eight robots is used as a non‐trivial real‐world test of this system. We conclude the paper by discussing advantages, limitations, and future improvements of the system.
Medication and creativity in Attention Deficit Hyperactivity Disorder (ADHD).

BACKGROUND The aim of this study was to determine the effect of methylphenidate (MPH) on creative potential in a group of children with attention deficit disorder with hyperactivity (ADHD). METHOD A randomized single blind crossover study was performed with 24 children with ADHD, aged between 18 and 96 (M = 10.0, SD = 1.3), evaluating each child’s creativity with and without MPH, using the Torrance Tests of Creative Thinking-Figural (TTCT). RESULTS Children under treatment with MPH showed a lower global Creative Index and lower scores on Fluency, Originality and Creative Strengths, compared to when not under treatment. The capacities for Elaboration, Abstractness of Titles, and Resistance to Closure did not differ whether on or off pharmacological treatment. CONCLUSION Our finding suggests that is important to take into account the impact that MPH might have on the creative potential of a child with ADHD to develop a more accurate evaluation and to develop better treatment plans.
The Australian Pharmaceutical Industry and its Global Context

The knowledge content in OECD economies has intensified over the last two decades (OECD 2001). As a sector of strategic importance for social welfare, the pharmaceutical industry has attracted considerable research energy. However, there has been insufficient attention given to the industry in macroeconomics; only fragments of the big picture are recorded. Several studies also point to a trend towards concentration of business activity in the USA away from Europe. We seek to gain more comprehensive view of the industry. The evidence presented here highlights the diversity of OECD countries and the rise of a few centres of excellence in the 1990s. The paper also reviews the performance of the Australian industry and compares it with other OECD countries.
Semantic Concepts Classification on Outdoor Scene Images Based on Region-Based Approach

Outdoor scene analysis is a complex problem for both image processing and pattern recognition domains. There are two methods of segmenting images to look for objects in an image, block-based and region-based. Region-based method can provide some useful information about objects even though segmentation may not be perfect. There are three phases in this system: segmentation, features extraction and classification. The basic idea of this system is to classify local image regions into semantic concept classes such as tree, sky and road etc. In this paper, modified Marker-Controlled Watershed (MCWS) algorithm is proposed. Firstly, the modified (MCWS) algorithm is used to segment input image. And then, texture feature vectors are extracted from segmented regions by Gray-Level Co-occurrence Matrix (GLCM). Finally, classification is performed by 3-layer Artificial Neural Network (ANN). This system is applied on real scene images dataset.
Innovation in the Energy Sector

This study analyses the diffusion of renewable energy (RE) technologies. It analyses the transition dynamics as the sector broadens its energy mix and changes its capital stock. This shift is found to be desirable from an environmental, geopolitical and economic perspective. Yet, it greatly increases the technical and industrial complexity, and is not Pareto-efficient. We focus on wind and solar power, and discuss their promoted deployment against the energy policy principles of the EU. Put drastically, the promotion of ‘sustainability’ undermined ‘competitive’ mechanisms. This has potentially adverse effects on the ‘security of supply’ due to the market design that seeks to keep prices low. RE outperforms conventional facilities. Emergency capacities, however, are also exiting, especially in Germany. If markets are seen as one, there seems to be a threshold of wind and solar power that the current back-up system can incorporate without risking the security of supply. The policy relevant crux lies in conflicting mechanisms: the top-down promotion and planning policies undermine the bottom-up market selection. Then again, without interventions the market does not provide the socially desired outcomes. If tensions aggravate further, the implementation of the new technology base is likely to stall. In addition, the generous promotion resulted in the fast deployment of RE, which may have shortened the ‘formative phase’ of the diffusion process. A longer formative phase would have created more learning effects and fostered more incremental innovations. In addition, costs of subsidies are allocated differently across countries. Mechanisms that allocate costs to the public budget have greater acceptance rates than budget neutral ones that assign costs to consumers. The latter affect households asymmetrically across income classes. Also ownership structures changed; a large number of actors now constitute the energy sector. Citizens increasingly appeared as producers and investors, which stimulated the social acceptance of RE, and in some cases unlocked initially unfavourable vested interests.
Robust High Dimensional Sparse Regression and Matching Pursuit

We consider high dimensional sparse regression, and develop strategies able to deal with arbitrary -- possibly, severe or coordinated -- errors in the covariance matrix $X$. These may come from corrupted data, persistent experimental errors, or malicious respondents in surveys/recommender systems, etc. Such non-stochastic error-in-variables problems are notoriously difficult to treat, and as we demonstrate, the problem is particularly pronounced in high-dimensional settings where the primary goal is {\em support recovery} of the sparse regressor. We develop algorithms for support recovery in sparse regression, when some number $n_1$ out of $n+n_1$ total covariate/response pairs are {\it arbitrarily (possibly maliciously) corrupted}. We are interested in understanding how many outliers, $n_1$, we can tolerate, while identifying the correct support. To the best of our knowledge, neither standard outlier rejection techniques, nor recently developed robust regression algorithms (that focus only on corrupted response variables), nor recent algorithms for dealing with stochastic noise or erasures, can provide guarantees on support recovery. Perhaps surprisingly, we also show that the natural brute force algorithm that searches over all subsets of $n$ covariate/response pairs, and all subsets of possible support coordinates in order to minimize regression error, is remarkably poor, unable to correctly identify the support with even $n_1 = O(n/k)$ corrupted points, where $k$ is the sparsity. This is true even in the basic setting we consider, where all authentic measurements and noise are independent and sub-Gaussian. In this setting, we provide a simple algorithm -- no more computationally taxing than OMP -- that gives stronger performance guarantees, recovering the support with up to $n_1 = O(n/(\sqrt{k} \log p))$ corrupted points, where $p$ is the dimension of the signal to be recovered.
Detecting Undiagnosed Type 2 Diabetes: Family History as a Risk Factor and Screening Tool

A family history of diabetes is a major risk factor for the disease. As such, it is often included in a variety of tools designed to detect either people at risk of diabetes or people with undiagnosed diabetes. One of the reasons to screen for diabetes is that it has a prolonged asymptomatic phase, which includes impaired fasting glucose, impaired glucose tolerance, and the early stages of diabetes. In terms of prevalence, diabetes is a major public health problem. Evidence shows that the detection of impaired glucose metabolism in its early stages (prediabetes) could lead to the delay or prevention of the disease and its complications. However, the issue of using family history to screen for diabetes must be discussed within the context of screening for diabetes in general. Screening for a disease among asymptomatic people must meet a series of stringent requirements to ensure the best possible outcomes. Screening for diabetes meets most of these requirements but the ones it does not meet are still important. Therefore, based on systematically collected evidence or simply by consensus among scientists, influential organizations recommend screening only among high-risk individuals. As a result, researchers have developed a variety of simple tools to identify high-risk individuals for diabetes in populations. Family history is included as a key variable in the vast majority of them. This article is a brief overview of the reasons to screen for diabetes in general, the tools available for conducting this screening, and the role of family history in these tools.
Resting Human Memory B Cells Are Intrinsically Programmed for Enhanced Survival and Responsiveness to Diverse Stimuli Compared to Naive B Cells1

Enhanced secondary Ab responses are a vital component of adaptive immunity, yet little is understood about the intrinsic and extrinsic regulators of naive and memory B cells that result in differences in their responses to Ag. Microarray analysis, together with surface and intracellular phenotyping, revealed that memory B cells have increased expression of members of the TNF receptor, SLAM (signaling lymphocytic activation molecule), B7, and Bcl2 families, as well as the TLR-related molecule CD180 (RP105). Accordingly, memory B cells exhibited enhanced survival, proliferation, and Ig secretion, and they entered division more rapidly than did naive B cells in response to both T cell-dependent and T cell-independent stimuli. Furthermore, both IgM and isotype-switched memory B cells, but not naive B cells, costimulated CD4+ T cells in vitro through a mechanism dependent on their constitutive expression of CD80 and CD86. This study demonstrates that up-regulation of genes involved in activation, costimulation, and survival provides memory B cells with a unique ability to produce enhanced immune responses and contributes to the maintenance of the memory B cell pool.
Extreme Events and the Market for Terrorist Insurance

Institute of University of I ' ~ Business and S California at . I Economic Research Berkeley FISHER CENTER FOR REAL ESTATE AND URBAN ECONOMICS WORKING PAPER SERIES WORKING PAPER NO. 02-282 EXTREME EVENTS AND THE MARKET FOR TERRORIST INSURANCE BY . Tq°S°PaP¢*s.a“*P‘““'“¥qa‘Y S DWIGHT JAFFEE ’sqﬁ,'I§,“fa’fc' §§§§f,§§§f,‘,’,°§§d’s t° , THOMAS RUSSELL comment. Therefore, they are not to be cited or quoted in any publication without the ex- press permission of the author. WALTER A. HAAS SCHOOL OF BUSINESS
Human Mobility Trace Acquisition and Social Interactions Monitoring for Business Intelligence Using Smartphones

Human mobility monitoring and respective traces are important for understanding human behavior, respective patterns and associated context. Such data can be potentially used in business intelligence-oriented systems, for providing added value commercial services or insight to internal enterprise procedures. At the same time, smart phones are rapidly becoming an indispensable tool for our everyday life, while their advanced networking and computing capabilities are increasingly being used as enablers for new applications. We discuss here a system using a stable computing and networking infrastructure along with smart phone applications, based on commodity technologies, meant to be deployed rapidly and provide analytics almost in real-time for such aspects. We also discuss a related scenario in order to provide insight as to where our system could be used. We briefly present the deployment of our system in two settings, an office building and a research exhibition event, along with our experiences. Our findings show that it is feasible and efficient to deploy and operate our system relatively easy, producing meaningful data.
Cannabinoids Elicit Antidepressant-Like Behavior and Activate Serotonergic Neurons through the Medial Prefrontal Cortex

Preclinical and clinical studies show that cannabis modulates mood and possesses antidepressant-like properties, mediated by the agonistic activity of cannabinoids on central CB1 receptors (CB1Rs). The action of CB1R agonists on the serotonin (5-HT) system, the major transmitter system involved in mood control and implicated in the mechanism of action of antidepressants, remains however poorly understood. In this study, we demonstrated that, at low doses, the CB1R agonist WIN55,212-2 [R(+)-[2,3-dihydro-5-methyl-3-[(morpholinyl)]pyrrolo[1,2,3-de]-1,4-benzoxazinyl]-(1-naphthalenyl) methanone mesylate] exerts potent antidepressant-like properties in the rat forced-swim test (FST). This effect is CB1R dependent because it was blocked by the CB1R antagonist rimonabant and is 5-HT mediated because it was abolished by pretreatment with the 5-HT-depleting agent parachlorophenylalanine. Then, using in vivo electrophysiology, we showed that low doses of WIN55,212-2 dose dependently enhanced dorsal raphe nucleus 5-HT neuronal activity through a CB1R-dependent mechanism. Conversely, high doses of WIN55,212-2 were ineffective in the FST and decreased 5-HT neuronal activity through a CB1R-independent mechanism. The CB1R agonist-induced enhancement of 5-HT neuronal activity was abolished by total or medial prefrontocortical, but not by lateral prefrontocortical, transection. Furthermore, 5-HT neuronal activity was enhanced by the local microinjection of WIN55,212-2 into the ventromedial prefrontal cortex (mPFCv) but not by the local microinjection of WIN55,212-2 into the lateral prefrontal cortex. Similarly, the microinjection of WIN55,212-2 into the mPFCv produced a CB1R-dependent antidepressant-like effect in the FST. These results demonstrate that CB1R agonists possess antidepressant-like properties and modulate 5-HT neuronal activity via the mPFCv.
Infrared Face Recognition Based on Personalized Features Selection of LBP

The compact and discriminative feature extraction is vital for infrared face recognition. This paper proposes a personalized feature selection algorithm for infrared face recognition. Firstly, LBP operator is applied to infrared face for texture information. Secondly, for each subject, a two-class training problem is constructed by one to other means. Then, based on two-class discriminative ability, we adaptively select a personalized subset of features from LBP for each subject. Finally, the nearest neighbor classifier based on chi-square distance is utilized to get final recognition result. The experimental results show the personalized feature selection is effective in useful information extraction for infrared face recognition, which outperform the state of the art methods based on LBP.
Room volume estimation based on statistical properties of binaural signals using humanoid robot

Humans can recognize approximate room size only by binaural audition. However, sound reverberation is not negligible in most environments. The reverberation causes temporal fluctuation in the short-term Interaural Phase Differences (IPDs) of sound pressure. In this study, a novel method for estimating room volume is proposed based on the short-term IPDs of sound pressure by using a binaural humanoid robot. The humanoid robot turns its head toward a sound source, recognizes the sound source, then estimates the ego-centric distance by its stereovision. By interpolating the relations between room volume, average standard deviation and egocentric distance experimentally obtained for various rooms in a prepared database, the room volume was estimated by binaural audition from the average standard deviation of short-term IPDs at the estimated distance.
Improved SIFT matching algorithm for 3D reconstruction from endoscopic images

SIFT (Scale Invariant Feature Transform) is wildly used in image matching but suffered from low matching pairs when employed in endoscope image. This paper presented an improved algorithm based on SIFT, the core contribution of which is Zone Matching approach. By collecting all feature points in a neighbor patch around the coordinate of an objective feature in the key image and finding the closest one to the feature in current image, the Zone Matching can obtain more matching pairs in shorter time. The experiment result shows a good improvement on the matching results both in matching number and computing time.