Miracle-dz/UniFAR-FTUs huggingface dataset:
Mental Exercise and Mental Aging

It is widely believed that keeping mentally active will prevent age-related mental decline. The primary prediction of this mental-exercise hypothesis is that the rate of age-related decline in measures of cognitive functioning will be less pronounced for people who are more mentally active, or, equivalently, that the cognitive differences among people who vary in level of mental activity will be greater with increased age. Although many training studies, and comparisons involving experts, people in specific occupations, and people whose mental activity levels are determined by their self-reports, have found a positive relation between level of activity and level of cognitive functioning, very few studies have found an interactive effect of age and mental activity on measures of cognitive functioning. Despite the current lack of empirical evidence for the idea that the rate of mental aging is moderated by amount of mental activity, there may be personal benefits to assuming that the mental-exercise hypothesis is true.
An agent-based resource allocator for close air support

A multi-agent approach for system development has been used for solving more and more complex systems. Recent work has shown the benefits of this approach for building decision support applications in a complex real-time environment. In this paper, the development of an agent-based, time-critical decision support tool in the field of Command, Control, Communications, and Intelligence (C3I), is described. For the design of this tool, techniques from agent-based computing, object-orientation, and design patterns have been combined, and reuse has been a key design consideration from the start. The work has been carried out as a part of the EUCLID RTP 6.1 project, which is a European collaborative military research programme, aimed at developing an advanced workstation for C3I.
Increased Activity Imbalance in Fronto-Subcortical Circuits in Adolescents with Major Depression

Background A functional discrepancy exists in adolescents between frontal and subcortical regions due to differential regional maturational trajectories. It remains unknown how this functional discrepancy alters and whether the influence from the subcortical to the frontal system plays a primacy role in medication naïve adolescent with major depressive disorder (MDD). Methodology/Principal Findings Eighteen MDD and 18 healthy adolescents were enrolled. Depression and anxiety severity was assessed by the Short Mood and Feeling Questionnaire (SMFQ) and Screen for Child Anxiety Related Emotional Disorders (SCARED) respectively. The functional discrepancy was measured by the amplitude of low-frequency fluctuations (ALFF) of resting-state functional MRI signal. Correlation analysis was carried out between ALFF values and SMFQ and SCARED scores. Resting brain activity levels measured by ALFF was higher in the frontal cortex than that in the subcortical system involving mainly (para) limbic-striatal regions in both HC and MDD adolescents. The difference of ALFF values between frontal and subcortical systems was increased in MDD adolescents as compared with the controls. Conclusions/Significance The present study identified an increased imbalance of resting-state brain activity between the frontal cognitive control system and the (para) limbic-striatal emotional processing system in MDD adolescents. The findings may provide insights into the neural correlates of adolescent MDD.
Markers for Characterization of Bone Marrow Multipotential Stromal Cells

Given the observed efficacy of culture-expanded multipotential stromal cells, also termed mesenchymal stem cells (MSCs), in the treatment of graft-versus host and cardiac disease, it remains surprising that purity and potency characterization of manufactured cell batches remains rather basic. In this paper, we will initially discuss surface and molecular markers that were proposed to serve as the indicators of the MSC potency, in terms of their proliferative potential or the ability to differentiate into desired lineages. The second part of this paper will be dedicated to a critical discussion of surface markers of uncultured (i.e., native) bone marrow (BM) MSCs. Although no formal consensus has yet been reached on which markers may be best suited for prospective BM MSC isolation, markers that cross-react with MSCs of animal models (such as CD271 and W8-B2/MSCA-1) may have the strongest translational value. Whereas small animal models are needed to discover the in vivo function on these markers, large animal models are required for safety and efficacy testing of isolated MSCs, particularly in the field of bone and cartilage tissue engineering.
Scene classification based on rough set method features selection for outdoor images

Scene classification is valuable in image retrieval from databases because an understanding of the scene content can be used for efficient and effective database organization and browsing. a scene classification based on rough set method features selection for outdoor images is developed in this paper, support vector machines and k-nearest neighbors classification model are used, experiments on University of Massachusetts image segmentation database shows that based on rough set method features selection can improve the scene classification performance for outdoor images.
Christian Trade Unionism in Europe Since 1968: Tensions Between Identity and Practice

Christian trade unionism - country summaries: secularization and the preservation of christian trade unionism in France the partial depillarization in the Netherlands a powerful movement in Belgium Luxembourg - between unity and individuality Switzerland - internal tension in a federal country West Germany - on the edge of the DGB Austria - a christian faction in the unified trade union christian trade unionism in Italy - nothing is what it seems Christian trade unionism in Eastern Europe? The international "christian" trade union movement: from IFCTU to WCL - a revolution towards trade union unification at European level crisisin the WCL christian trade unionism in Europe after the foundation of the ETUC. Christian identity and international trade action: the international christian metal-workers - the struggle for an efficient representation of interests the opportunities of the international trade federation for office workers.
Using Engel Curves to Estimate CPI Bias for the Elderly

We use shifts in food Engel curves among the U.S. elderly to estimate the extent of Consumer Price Index (CPI) bias specific to this population. Over the last thirty years the share of total expenditure devoted to food has declined more rapidly for elderly-headed households than for other households. This decline is not explained by a more rapid increase in measured total expenditure for the elderly, or by relative change in other covariates such as household composition. We present this as evidence that the true cost of living increased more slowly for the elderly than for the nonelderly over this period, in contrast to conventional wisdom that the elderly face a higher inflation rate.
Culture and Conflict : A study of a course focusing on the relationship between culture and conflict

Conflict is a term that has very negative connotations for many people. In Japan, a culture in which harmony and groups are highly valued, conflict represents an idea that is almost taboo it seems. Nonetheless, despite a dislike for bringing up topics that might cause conflict, it exists in most aspects of everyday life, even in Japan. With this concept in mind, a course was created at the request of a Japanese university to be taught in English, but as an elective lecture class. Even after leaving the original university the course was created for, the contents continued to be incorporated in similar courses taught at two other universities in Japan. This paper will examine the concepts of conflict as perceived by Japanese university students who took the course, the actual course goals of creating more awareness by Japanese students about culture and conflict, and the success or lack of success of the course.
Semantic Graph Construction for Weakly-Supervised Image Parsing

We investigate weakly-supervised image parsing, i.e., assigning class labels to image regions by using image-level labels only. Existing studies pay main attention to the formulation of the weakly-supervised learning problem, i.e., how to propagate class labels from images to regions given an affinity graph of regions. Notably, however, the affinity graph of regions, which is generally constructed in relatively simpler settings in existing methods, is of crucial importance to the parsing performance due to the fact that the weakly-supervised parsing problem cannot be solved within a single image, and that the affinity graph enables label propagation among multiple images. In order to embed more semantics into the affinity graph, we propose novel criteria by exploiting the weak supervision information carefully, and develop two graphs: L1 semantic graph and k-NN semantic graph. Experimental results demonstrate that the proposed semantic graphs not only capture more semantic relevance, but also perform significantly better than conventional graphs in image parsing.
Linguistic Categories as Basins of Curvature

Linguistic grammars do a good job of elucidating the lexical categories and phrasal units of the languages they model. Certain recurrent Connectionist networks can model similar data but it is not easy to discern the abstract structures of the resulting representations. Hierarchical clustering is helpful in this regard, but it often produces implausible clusters and there seems to be no principled way of deciding which clusters are relevant. A more promising approach is to examine the curvature of the hidden space image in the output space. Because the relative frequency distributions of lexical items tend to be highly categorical in nature, with probabilistic variation in only a few dimensions, they generally lie on the linear surfaces of the output space. Consequently, categories are associated with regions of low curvature. I show that categoryextraction based on this principle can produce a more revealing analysis than hierarchical clustering in certain cases.
Use of Artificial Neural Network for the Prediction of Ammonia Emission Concentration of Granulated Blast Furnace Slag Mortar

In this study, an artificial neural networks study was carried out to predict the quantity of ammonia gas ( NH 3 ) of Granulated Blast Furnace Slag (GBFS) cement mortar. A data set of a laboratory work, in which a total of 4 mortars were produced, was utilized in the Artificial Neural Networks (ANNs) study. The mortar mixture parameters were four different GBFS ratios (0%, 20%, 40% and 60%). Measurement ammonia of moist cured specimens were measured at 1, 3, 10, 30, 100, 365 days. ANN model is constructed, trained and tested using these data. The data used in the ANN model are arranged in a format of two input parameters that cover the cement, GBFS and age of samples and, an output parameter which is concentrations of ammonia emission of mortar. The results showed that ANN can be an alternative approach for the predicting the ammonia concentration of GBFS mortar using mortar ingredients as input parameters.
The multipolling mechanism based on the prioritization for WLAN network with multiple access points

In this paper, we propose a new polling-based mechanism for the point coordination function (PCF) in IEEE 802.11 wireless local area network (WLAN). The proposed mechanism uses prioritization on two stages to enhance the ability to support quality of service (QoS) in networks with a high density of access points (APs). First step: in the competition between APs, only one AP can get the right to access the environment. This step helps reduce the collision and influence of hidden node problems. Second step: that AP uses a multipolling mechanism to poll all stations (STAs) in a prioritized group m. This step helps reduce delay and polling overhead. The major innovation is the use of multipolling mechanism for WLAN network with multiple APs instead of WLAN network with single AP. We propose Polling List Update (PLU) and Multi Polling Prioritized period (MPP) frames. The PLU frame is used to collect information from STAs and update polling list. The MPP frame coordinates data transmissions without collision. Comparing with the single polling scheme used in the conventional IEEE802.11 MAC protocol, the proposed scheme can reduce the overhead caused by the polling frames. We evaluate the efficacy of the proposed mechanism in terms of polling overhead, delay, data dropped and retransmission attempts.
Reproducibility and Reliability of Quantitative and Weighted T1 and T2∗ Mapping for Myelin-Based Cortical Parcellation at 7 Tesla

Different magnetic resonance (MR) parameters, such as R1 (=1/T1) or T2∗, have been used to visualize non-invasively the myelin distribution across the cortical sheet. Myelin contrast is consistently enhanced in the primary sensory and some higher order cortical areas (such as MT or the cingulate cortex), which renders it suitable for subject-specific anatomical cortical parcellation. However, no systematic comparison has been performed between the previously proposed MR parameters, i.e., the longitudinal and transversal relaxation values (or their ratios), for myelin mapping at 7 Tesla. In addition, usually these MR parameters are acquired in a non-quantitative manner (“weighted” parameters). Here, we evaluated the differences in ‘parcellability,’ contrast-to-noise ratio (CNR) and inter- and intra-subject variability and reproducibility, respectively, between high-resolution cortical surface maps based on these weighted MR parameters and their quantitative counterparts in ten healthy subjects. All parameters were obtained in a similar acquisition time and possible transmit- or receive-biases were removed during post-processing. It was found that CNR per unit time and parcellability were lower for the transversal compared to the longitudinal relaxation parameters. Further, quantitative R1 was characterized by the lowest inter- and intra-subject coefficient of variation (5.53 and 1.63%, respectively), making R1 a better parameter to map the myelin distribution compared to the other parameters. Moreover, quantitative MRI approaches offer the advantage of absolute rather than relative characterization of the underlying biochemical composition of the tissue, allowing more reliable comparison within subjects and between healthy subjects and patients. Finally, we explored two parcellation methods (thresholding the MR parameter values vs. surface gradients of these values) to determine areal borders based on the cortical surface pattern. It is shown that both methods are partially observer-dependent, needing manual interaction (i.e., choice of threshold or connecting high gradient values) to provide unambiguous borders.
THE DEMAND FOR FOOD QUALITY IN RUSSIA AND ITS LINKAGE TO OBESITY

This study analyses whether Russian households differ in their choice of food quality when they differ in their number of overweight and obese members. Using survey data from the Russia Longitudinal Monitoring Survey (RLMS) for the years 1995-2005, households are classified into three weight groups. Quality elasticities of expenditures are estimated by a fixed-effects panel model regressing unit values of several food groups on expenditures and a set of household characteristics. Coefficients for each weight group are received by including interaction terms of expenditures and weight group dummies. A set of Wald tests is applied to test for slope heterogeneity across weight groups. Descriptive statistics reveal that obese households actually purchase larger quantities and pay less per unit for many food products. However, estimates of the quality elasticity show low absolute values and range from -0.2 to 1.1 for single food groups and the null hypothesis of equal parameters for all weight groups cannot be rejected.
On the diversity and complexity of Zero Forcing receivers for MIMO Zero Padded systems

Zero padded systems with linear receivers are shown to be robust and amenable to fast implementations in single antenna scenarios. In this paper, properties of such systems are investigated when multiple antennas are present at both ends of the communication link. In particular, their diversity and complexity are evaluated for precoded transmissions. The linear receivers are shown to exploit multipath and receive diversities, even in the absence of any coding at the transmitter. Use of additional redundancy to improve performance is considered and the effect of transmission rate on diversity order is analyzed. Low complexity implementations of Zero Forcing receivers are devised to further enhance their applicability.
Land-surface modelling in hydrological perspective

Land-surface modelling in hydrological perspective J. Overgaard, D. Rosbjerg, and M. B. Butts Institute of Environment & Resources, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark DHI Water & Environment, DK-2970 Horsholm, Denmark Received: 18 October 2005 – Accepted: 13 November 2005 – Published: 13 December 2005 Correspondence to: J. Overgaard (jov@dhi.dk) © 2005 Author(s). This work is licensed under a Creative Commons License.
The Role of the Exchange Rate for Adjustment in Boom and Bust Episodes

Numerous countries have experienced boom-bust episodes in asset prices in the past 20 years. This study looks at stylised facts and conducts statistical and econometric analysis for such episodes, distinguishing between industrialised countries that experienced external adjustment (via real effective exchange rate depreciation during busts) and those that relied on an internal adjustment process (and experienced no depreciation). The study finds that different adjustment experiences are correlated with the degree of macroeconomic imbalances and balance sheet problems. Internal adjustment seems more prevalent when financial vulnerabilities, excess demand and competitiveness loss remain relatively contained in the boom. In the bust, internal adjusters experience more protracted but less deep downturns than external adjusters as imbalances unwind more slowly. Some Central and East European EU Member States are currently experiencing strong credit and asset price growth in conjunction with rapid economic expansion. Against this background the experience of other countries may raise awareness of related policy challenges. JEL Classification: E32, E63, E65
Similarity of Documents and Document Collections using Attributes with Low Noise

In this paper, a unified framework for clustering documents based on vocabulary overlap and in-link similarity is presented. A small number of non-zero attributes per document, taken from a very large set of possible attributes, ensure efficient comparisons procedures. We show that A) low frequent words are excellent attributes for textual documents as well as B) sources of in-links as attributes for web documents. In the cases of web documents, co-occurrence analysis is used to identify similarity. The documents are represented as nodes in a graph with edges weighted by similarity. A graph clustering algorithm is applied to group similar documents together. Evaluation for textual documents against a gold standard is provided.
Listeners' ERP responses to false starts and repetitions in spontaneous speech

Hindle [1] suggested that false starts and repetitions should be handled differently in a computational account of the processing of the two kinds of disfluency, and there is behavioural evidence that the human sentence processing mechanism likewise honours this distinction [2]. The same dichotomy was also evident in the electrophysiological data reported here. False starts and repetitions were identified in a corpus of spontaneous speech. Control items for the false starts were prepared by excising the reparanda to yield apparently fluent items. Continuous EEG was recorded while subjects listened to items containing the false starts, fluent false start controls, and first and second tokens of repetitions. Compared with identical words in their fluent controls, the false starts elicited a positive response similar to the P600 which is reported for syntactically anomalous words [3, 4, 5]. By contrast, second tokens of repetitions in general resulted in increased amplitude of the N400 [6]; yet, when the same repetitions were excised from context and presented listfashion, they elicited the positive-going response which has been reported by other researchers [7].
2007 State Policies on Assessment Participation and Accommodations for Students with Disabilities. Synthesis Report 69.

A 2008 report updating the National Center on Educational Outcomes' (NCEO) report from 2006 that tracked and analyzed state policies on assessment participation and accommodations since 1992. The purpose of the current analysis is to update information on these policies that was last reported by NCEO in 2006 (based on 2005 data). In this analysis, policies from all 50 states, plus 8 of the unique states, were reviewed. The current analysis of states' 2007 participation and accommodation policies found that state policies on participation and accommodation continue to evolve, and that they have become more detailed and specific than in previous years.
Performance evaluation of ego-motion methods in static environment

Estimating the observer position in 3D environment using a visual image data is called the egomotion. This method consists of three steps: in the first step, feature points of image are detected; in the second step, optical flow information is obtained; in the third and final step appropriate transformation parameters are calculated using the optimization method. Especially in enclosed areas where GPS can not be used or high estimation errors occured, in underground systems, visual egomotion is critically important. As well as the precise location estimation, providing a low cost solution is one of the superior properties of egomotion method. In this study, different egomotion methods has been observed, the numerical results in noisy and noiseless environment obtained by comparing the accuracy of algorithms presented in the table.
Model Based Sampling - Fitting an Ensemble of Models into a Single Model

Large ensembles of classifiers usually outperform single classifiers. Unfortunately ensembles have two major drawbacks compared to single classifier, interpretability and classifications times. Using the Combined Multiple Models (CMM) framework for compressing an ensemble of classifiers into a single classifier the problems associated with ensembles can be avoided while retaining almost similar classification power as that of the original ensemble. One open question when using CMM concerns how to generate values that constitute the synthetic example. In this paper we present a novel method for generating synthetic examples by utilizing the structure of the ensemble. This novel method is compared with other methods for generating synthetic examples using the CMM framework. From the comparison it is concluded that the novel method outperform the other methods.