Miracle-dz/UniFAR-FTUs huggingface dataset:
The Meditative Mind: A Comprehensive Meta-Analysis of MRI Studies

Over the past decade mind and body practices, such as yoga and meditation, have raised interest in different scientific fields; in particular, the physiological mechanisms underlying the beneficial effects observed in meditators have been investigated. Neuroimaging studies have studied the effects of meditation on brain structure and function and findings have helped clarify the biological underpinnings of the positive effects of meditation practice and the possible integration of this technique in standard therapy. The large amount of data collected thus far allows drawing some conclusions about the neural effects of meditation practice. In the present study we used activation likelihood estimation (ALE) analysis to make a coordinate-based meta-analysis of neuroimaging data on the effects of meditation on brain structure and function. Results indicate that meditation leads to activation in brain areas involved in processing self-relevant information, self-regulation, focused problem-solving, adaptive behavior, and interoception. Results also show that meditation practice induces functional and structural brain modifications in expert meditators, especially in areas involved in self-referential processes such as self-awareness and self-regulation. These results demonstrate that a biological substrate underlies the positive pervasive effect of meditation practice and suggest that meditation techniques could be adopted in clinical populations and to prevent disease.
Nonlinear Discrete Observer for Flexibility Compensation of Industrial Robots

Abstract This paper demonstrates the solutions of digital observer implementation for industrial applications. A nonlinear high-gain discrete observer is proposed to compensate the tracking error due to the flexibility of robot manipulators. The proposed discrete observer is obtained by using Euler approximate discretization of the continuous observer. A series of experimental validations have been carried out on a 6 DOF industrial manipulator during a Friction Stir Welding process. The results showed good performance of discrete observer and the observer based compensation has succeed to correct the positioning error in real-time implementation.
The Impact of Culture on Accounting Choices: Can Cultural Conservatism Explain Accounting Conservatism?

We explore the extent to which cultural conservatism explains accounting conservatism. Our primary measure for accounting conservatism is the magnitude of non-operating accruals, which are highly discretionary in nature. Culture permeates values and attitudes, and thus governs many aspects of human behavior. Hence it is likely to affect managers’ accounting choice behaviors. However, there is surprisingly little evidence on the association between the two types of conservatism in the literature. Using a sample of 800 firms originating from 21 countries during the nine-year period from 1993 to 2001, we find strong evidence that the managers in more conservative cultural environments tend to make more conservative accounting choices (e.g., report lower estimates for future cash flows). We also find some empirical support for the idea that culture and legal regime interact as substitutes in explaining accounting conservatism.
Exposing Digital Image Forgeries by Detecting Discrepancies in Motion Blur

The widespread availability of photo manipulation software has made it unprecedentedly easy to manipulate images for malicious purposes. Image splicing is one such form of tampering. In recent years, researchers have proposed various methods for detecting such splicing. In this paper, we present a novel method of detecting splicing in images, using discrepancies in motion blur. We use motion blur estimation through image gradients in order to detect inconsistencies between the spliced region and the rest of the image. We also develop a new measure to assist in inconsistent region segmentation in images that contain small amounts of motion blur. Experimental results show that our technique provides good segmentation of regions with inconsistent motion blur. We also provide quantitative comparisons with other existing blur-based techniques over a database of images. It is seen that our technique gives significantly better detection results.
Enhanced multi-radio AODV in hybrid wireless mesh networks

Wireless mesh networks (WMNs) have became the focus of many researchers as a promising technology for a broad range of applications due to their self-organizing, self-configuring and self-healing capability, in addition to their low equipments and deployment cost. WMNs are not mobile ad hoc networks (MANETs); instead they can be considered as a superset of traditional mobile ad hoc networks (MANETS). WMNs may exist in the absence of a central infrastructure taking the form of a MANET. However on the other hand, they may exist as networks comprised of an infrastructure connecting extended ad hoc networks. One significant area of research within ad hoc networks is routing and in particular, the efficient thereof. Owing to the characteristics of WMNs, routing algorithms designed for ad hoc networks however may not always be applicable to WMNs. Moreover, traditional ad hoc routing protocols which disseminate routing information by flooding, a technique which requires a significant consumption of energy and bandwidth, cannot achieve optimal performance especially in hybrid WMNs. In this paper, we use a technique to reduce the cost of disseminating information in a power-constrained environment by limiting the cardinality of the subset of nodes which retransmit a packet. This technique can improve the performance of AODV in hybrid mesh networks. Key words: Wireless mesh networks, multi-radio, routing, hybrid mesh networks, limited forwarding, AODV
A generic analytical model of fractance response in time domain

In this research, a generic analytical model of voltage response of fractance in time domain which is often cited in various disciplines such as control engineering and electronic engineering etc., has been proposed. This model can be applied to fractance of any order under any type of current excitation. So, it has been found to be beneficial to various fractance involved disciplines stated above which are the crucial basis in the development of technology for internet of things due to its generality.
Vertebral fractures and mortality in older women: a prospective study. Study of Osteoporotic Fractures Research Group.

BACKGROUND Osteoporotic fractures, including clinically detected vertebral fractures, are associated with increased mortality. However, only one third of vertebral fractures are diagnosed. It is unknown whether vertebral fractures, whether clinically apparent or not, are associated with greater mortality. OBJECTIVES To test the hypothesis that women with prevalent vertebral fractures have greater mortality than those without fractures and to describe causes of death associated with vertebral fractures. DESIGN Prospective cohort study with mean follow-up of 8.3 years. SETTING Four clinical centers in the United States. PARTICIPANTS A total of 9575 women aged 65 years or older and enrolled in the Study of Osteoporotic Fractures. MEASUREMENTS Vertebral fractures by radiographic morphometry; calcaneal bone mineral density; demographic, medical history, and lifestyle variables; blood pressure; and anthropometric measures. In a subset of 606 participants, thoracic curvature was measured during a second clinic visit. MAIN OUTCOME MEASURES Hazard ratios for mortality and cause-specific mortality. RESULTS At baseline, 1915 women (20.0%) were diagnosed as having vertebral fractures. Compared with women who did not have a vertebral fracture, women with 1 or more fractures had a 1.23-fold greater age-adjusted mortality rate (95% confidence interval, 1.10-1.37). Mortality rose with greater numbers of vertebral fractures, from 19 per 1000 woman-years in women with no fractures to 44 per 1000 woman-years in those with 5 or more fractures (P for trend, <.001). In particular, vertebral fractures were related to the risk of subsequent cancer (hazard ratio, 1.4;95% confidence interval, 1.1-1.7) and pulmonary death (hazard ratio, 2.1;95% confidence interval, 1.4-3.0). In the subset of women who underwent thoracic curvature measurements, severe kyphosis was also related to pulmonary deaths (hazard ratio, 2.6;95% confidence interval, 1.3-5.1). CONCLUSION Women with radiographic evidence of vertebral fractures have an increased mortality rate, particularly from pulmonary disease and cancer.
Compact Groups of Galaxies

▪ Abstract Compact groups of galaxies have posed a number of challenging questions. Intensive observational and theoretical studies are now providing answers to many of these and, at the same time, are revealing unexpected new clues about the nature and role of these systems. Most compact groups contain a high fraction of galaxies having morphological or kinematical peculiarities, nuclear radio and infrared emission, and starburst or active galactic nuclei (AGN) activity. They contain large quantities of diffuse gas and are dynamically dominated by dark matter. They most likely form as subsystems within looser associations and evolve by gravitational processes. Strong galaxy interactions result and merging is expected to lead to the ultimate demise of the group. Compact groups are surprisingly numerous and may play a significant role in galaxy evolution.
High-resolution line scan diffusion tensor MR imaging of white matter fiber tract anatomy.

BACKGROUND AND PURPOSE MR diffusion tensor imaging permits detailed visualization of white matter fiber tracts. This technique, unlike T2-weighted imaging, also provides information about fiber direction. We present findings of normal white matter fiber tract anatomy at high resolution obtained by using line scan diffusion tensor imaging. METHODS Diffusion tensor images in axial, coronal, and sagittal sections covering the entire brain volume were obtained with line scan diffusion imaging in six healthy volunteers. Images were acquired for b factors 5 and 1000 s/mm(2) at an imaging resolution of 1.7 x 1.7 x 4 mm. For selected regions, images were obtained at a reduced field of view with a spatial resolution of 0.9 x 0.9 x 3 mm. For each pixel, the direction of maximum diffusivity was computed and used to display the course of white matter fibers. RESULTS Fiber directions derived from diffusion tensor imaging were consistent with known white matter fiber anatomy. The principal fiber tracts were well observed in all cases. The tracts that were visualized included the following: the arcuate fasciculus; superior and inferior longitudinal fasciculus; uncinate fasciculus; cingulum; external and extreme capsule; internal capsule; corona radiata; auditory and optic radiation; anterior commissure; corpus callosum; pyramidal tract; gracile and cuneatus fasciculus; medial longitudinal fasciculus; rubrospinal, tectospinal, central tegmental, and dorsal trigeminothalamic tract; superior, inferior, and middle cerebellar peduncle; pallidonigral and strionigral fibers; and root fibers of the oculomotor and trigeminal nerve. CONCLUSION We obtained a complete set of detailed white matter fiber anatomy maps of the normal brain by means of line scan diffusion tensor imaging at high resolution. Near large bone structures, line scan produces images with minimal susceptibility artifacts.
Heartbeat Mechanism for Proxy Mobile IPv6

Proxy Mobile IPv6 is a network-based mobility management protocol. The mobility entities involved in the Proxy Mobile IPv6 protocol, the Mobile Access Gateway (MAG) and the Local Mobility Anchor (LMA), setup tunnels dynamically to manage mobility for a mobile node within the Proxy Mobile IPv6 domain. This document describes a heartbeat mechanism between the MAG and the LMA to detect failures quickly and take appropriate action.
Multi-agent system architecture for heart failure management in a home care environment

Health status management of heart failure patients is a rather complex and difficult procedure. Currently, a well-promising approach facilitating this aim is home care systems, which provide monitoring, educational and surveillance services over several communication platforms, guaranteeing continuity and quality of care. In this paper, a multi-agent system architecture is proposed to support heart failure management in a generic home care setting. The system incorporates various processing modules based on statistics, rules and models that are applied to the medical data of patients, as well as learning capabilities based on the medical interventions that take place, and negotiation schemes among agents. The ultimate goal of this system is the characterization of the patients' health status and accordingly the notification of the corresponding medical personnel to take medical actions.
Hornbills can distinguish between primate alarm calls

Some mammals distinguish between and respond appropriately to the alarm calls of other mammal and bird species. However, the ability of birds to distinguish between mammal alarm calls has not been investigated. Diana monkeys (Cercopithecus diana) produce different alarm calls to two predators: crowned eagles (Stephanoaetus coronatus) and leopards (Panthera pardus). Yellow–casqued hornbills (Ceratogymna elata) are vulnerable to predation by crowned eagles but are not preyed on by leopards and might therefore be expected to respond to the Diana monkey eagle alarm call but not to the leopard alarm call. We compared responses of hornbills to playback of eagle shrieks, leopard growls, Diana monkey eagle alarm calls and Diana monkey leopard alarm calls and found that they distinguished appropriately between the two predator vocalizations as well as between the two Diana monkey alarm calls. We discuss possible mechanisms leading to these responses.
El Nio and World Primary Commodity Prices: Warm Water or Hot Air?

This paper examines the historical effects of the El Nio-Southern Oscillation (ENSO) cycle on world prices and economic activity. The primary focus is on world real non-oil primary commodity prices, although the effects on G-7 consumer price inflation and GDP growth are also considered. This paper has several distinct advantages over previous studies. First, several econometric models are estimated using fairly broad measures of prices and economic activity. Second, the models include continuous measures of ENSO intensity (sea surface temperature and sea-level air pressure anomalies in the Pacific Ocean) rather than dummy variable measures. Finally, confidence intervals are constructed for all estimated effects of ENSO on world prices and economic activity. The analysis indicates that ENSO has economically important and statistically significant effects on world real commodity prices. A one-standard-deviation positive surprise in ENSO, for example, raises real commodity price inflation about 3.5 to 4 percentage points. Moreover, ENSO appears to account for almost 20 of commodity price inflation movements over the past several years. ENSO also has some explanatory power for world consumer price inflation and world economic activity, accounting for approximately 10 to 20 of movements in those variables.
A Dual-Consequent-Pole Vernier Memory Machine

This paper proposes a novel dual-consequent-pole Vernier memory machine (DCP-VMM) featuring alternatively arranged NdFeB and low coercive-force (LCF) magnet poles on the rotating and stationary sides, respectively. Due to the presence of LCF magnets that can be repetitively magnetized or demagnetized via a simple current pulse, the extra-high torque density at low-speed, and excellent high-efficient high-speed flux-weakening performance can be simultaneously realized. The configuration and operating principle, as well as the design considerations of the proposed machine are introduced, respectively. The finite element method (FEM) coupled with a nonlinear analytical hysteresis model for LCF magnets is employed to investigate the electromagnetic performance of the machine, which verifies the effectiveness of machine design and the feasibility as a competent candidate for automotive applications.
The Cyclin-dependent Kinase Inhibitor CYC 202 ( R-Roscovitine ) Inhibits Retinoblastoma Protein Phosphorylation , Causes Loss of Cyclin D 1 , and Activates the Mitogen-activated Protein Kinase Pathway

Deregulation of the cell cycle commonly occurs during tumorigenesis, resulting in unrestricted cell proliferation and independence from mitogens. Cyclin-dependent kinase inhibitors have the potential to induce cell cycle arrest and apoptosis in cancer cells. CYC202 (R-roscovitine) is a potent inhibitor of CDK2/cyclin E that is undergoing clinical trials. Drugs selected to act on a particular molecular target may exert additional or alternative effects in intact cells. We therefore studied the molecular pharmacology of CYC202 in human colon cancer cells. Treatment of HT29 and KM12 colon carcinoma cell lines with CYC202 decreased both retinoblastoma protein phosphorylation and total retinoblastoma protein. In addition, an increase in the phosphorylation of extracellular signalregulated kinases 1/2 was observed. As a result, downstream activation of the mitogen-activated protein kinase pathway occurred, as demonstrated by an increase in ELK-1 phosphorylation and in c-FOS expression. Use of mitogen-activated protein kinase kinases 1/2 inhibitors showed that the CYC202-induced extracellular signal-regulated kinases 1/2 phosphorylation was mitogen-activated protein kinase kinases 1/2 dependent but did not contribute to the cell cycle effects of the drug, which included a reduction of cells in G1, inhibition of bromodeoxyuridine incorporation during S-phase, and a moderate increase in G2-M phase. Despite activation of the mitogen-activated protein kinase pathway, cyclin D1 protein levels were decreased by CYC202, an effect that occurred simultaneously with loss of retinoblastoma protein phosphorylation and inhibition of cell cycle progression. The reduced expression of cyclin D1 protein was independent of the p38 and phosphatidylinositol 3-kinase pathways, which are known regulators of cyclin D1 protein. Interestingly, CYC202 caused a clear reduction in cyclins D1, A, and B1 mRNA, whereas c-FOS mRNA increased by 2-fold. This was accompanied by a loss of RNA polymerase II phosphorylation and total RNA polymerase II protein, suggesting that CYC202 was inhibiting transcription, possibly via inhibition of CDK7 and CDK9 complexes. It can be concluded that although CYC202 can act as a CDK2 inhibitor, it also has the potential to inhibit CDK4 and CDK1 activities in cancer cells through the down-regulation of the corresponding cyclin partners. This provides a possible mechanism by which CYC202 can cause a reduction in retinoblastoma protein phosphorylation at multiple sites and cell cycle arrest in G1, S, and G2-M phases. In addition to providing useful insights into the molecular pharmacology of CYC202 in human cancer cells, the results also suggest potential pharmacodynamic end points for use in clinical trials with the drug.
Coseeded Schwann cells myelinate neurites from differentiated neural stem cells in neurotrophin-3-loaded PLGA carriers

Biomaterials and neurotrophic factors represent promising guidance for neural repair. In this study, we combined poly-(lactic acid-co-glycolic acid) (PLGA) conduits and neurotrophin-3 (NT-3) to generate NT-3-loaded PLGA carriers in vitro. Bioactive NT-3 was released stably and constantly from PLGA conduits for up to 4 weeks. Neural stem cells (NSCs) and Schwann cells (SCs) were coseeded into an NT-releasing scaffold system and cultured for 14 days. Immunoreactivity against Map2 showed that most of the grafted cells (>80%) were differentiated toward neurons. Double-immunostaining for synaptogenesis and myelination revealed the formation of synaptic structures and myelin sheaths in the coculture, which was also observed under electron microscope. Furthermore, under depolarizing conditions, these synapses were excitable and capable of releasing synaptic vesicles labeled with FM1-43 or FM4-64. Taken together, coseeding NSCs and SCs into NT-3-loaded PLGA carriers increased the differentiation of NSCs into neurons, developed synaptic connections, exhibited synaptic activities, and myelination of neurites by the accompanying SCs. These results provide an experimental basis that supports transplantation of functional neural construction in spinal cord injury.
The cost of early school-leaving and school failure

This report examines how low educational attainment is associated with significant economic costs for private individuals, for taxpayers, and for society. Specifically, higher education levels are associated with higher earnings, increased labor market participation, better health status (including lower prevalence of epidemic disease), and improvements in family decision-making; education is also associated with lower rates of poverty and intra-household benefits such as improved family nutrition. It describes the method for calculating these costs of school failure. It then highlights methodological challenges as well as key assumptions that underlie estimates of the overall costs of school failure. The method is illustrated with case studies from seven countries: Indonesia; Ghana; Kenya; Pakistan; Mexico; Chile; Ukraine; and Egypt. Using the best available research evidence, the gross costs of school failure are calculated for each of these countries. In each case these costs are significant. However, the magnitude of these costs depends on several key assumptions, including: the appropriate discount rate; the valuation of informal activity; and the economic value of improved health.
VLSI design of on-line add/multiply algorithms

We present some VLSI structures suitable for online arithmetic embedded algorithms using a radix-two fixed point signed digit system. As an application, we present online add/multiply architectures allowing the obtention of a zero-delay operator. An example of a circuit for online computation of several real functions using polynomials is also discussed. <<ETX>>
A soft computing approach for collision risk assessments

In this paper, we propose a collision risk assessment system using soft computing method. By using Monte Carlo Method, we make some samples for collision risk, and we recover collision risk of whole area using neural network. Multi-layer perceptron neural network will be applied to proposed algorithm. And fuzzy system will decide the final collision risk by considering not only collision risk but also time for collision. Simulation results will show the validity of our proposed method.