Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Eight Weeks of Exercise in Water on the Levels of Stress, Anxiety and Depression of Elderly Men

Introduction: Nowadays, the trend of dramatic growth in the aging population and its relation with mental disorders is on the rise. In this vein, the present study aimed to investigate the effect of eight weeks of exercise in water on the levels of stress, anxiety and depression of elderly men in Gachsaran city. Methods: In this semi-experimental study, 30 male volunteers with a mean age of 66 ± 0.5 years, who met the inclusion criteria of the study, were randomly selected and assigned into two control and experimental groups of 15 subjects. The experimental group performed the selected exercises in water in accordance with the planned protocol, and the control group just performed their daily routine activities during this period. Running pretest and post-test, stress (GHQ questionnaire), anxiety (Cattle’s questionnaire) and depression (Beck’s questionnaire) were measured in both groups. To analyze the findings, analysis of covariance was employed using SPSS software (version 21) (p≤0.05). Results: Exercise in water had a significant effect on stress components such as reduction of physical symptoms, anxiety symptoms and symptoms of depression and an increase in symptoms of social action compared to control group (p≤0.05), exercise in water had a significant effect on anxiety reduction compared to control group (p≤0.05) Also, exercise in water had a significant effect on depression reduction compared to control group (p≤0.05). Conclusion: Regarding the results of this study, it seems that exercise in water reduces anxiety and depression and some stress factors in elderly people.
A Soft Detector with Good Performance/Complexity Trade-Off for a MIMO System

We present a hybrid soft detector that has a good performance/complexity trade-off for a multiple-input multiple-output (MIMO) wireless communication system with known channel information. The new soft detector combines the merits of a simple unstructured least-squares (LS)-based soft detector and a list sphere decoder (LSD)-based soft detector for data bit detection. The former is computationally much more efficient than the latter at the cost of poorer performance. The poor performance of the former occurs mainly when the channel matrix is ill-conditioned. Whenever this happens, we use the LSD-based soft detector in the hybrid soft detector; otherwise, we use the LS-based one. Moreover, we provide a tight radius for a sphere decoder, a hard detector, via using the output of an LS-based hard detector. These two hard detectors are needed to determine if LS or LSD should be used in the hybrid soft detector. As an application example, we consider doubling the maximum data rate of the IEEE 802.11a conformable wireless local area networks by a MIMO system with two transmit and two receive antennas. For this application, the new soft detector is about 10 times faster than the LSD-based one and is about 10 times slower than the LS-based one. Yet the packet error rate due to using the new soft detector is quite close to that of using the LSD-based one.
Improving geo-spatial linked data with the wisdom of the crowds

Currently, there is more and more interest in geo-spatial data sources providing rich information about a huge number of interconnected geo-entities and points of interest located in the real world. Moreover, this kind of sources is one of the first to be published as linked open data. Noteworthy examples are the Geonames and GeoLinkedData initiatives. On the one hand, making available more data sources as linked open data allows querying the sources in an integrated way. On the other hand, it is known that content of geo-spatial data sources suffers from various drawbacks, mainly concerning data quality and conflicts. In this context, relevant feedbacks from users with specific experience and knowledge about POIs in a certain spatial region are considered valuable contributions to improve data quality and solve description conflicts. In this context, we propose a conceptual framework called M-PREGeD (Multi-Providers cRowd-Enhanced Geo linked Data) devoted to collect, organize and rank user-generated corrections and completions to improve accuracy and completeness of Geo-spatial Linked Data from different data sources. Metrics have been defined for both contributors and contents. In the framework, validated and ranked corrections and completions are stored as linked open data in a separate repository but linked to the original data sources. The repository can be queried in a combined way with the original data sources.
Combining Multiple Types of Eye-gaze Information to Predict User ’ s Conversational Engagement

In face-to-face conversations, speakers are continuously checking whether the listener is engaged in the conversation by monitoring the partner’s eye-gaze behaviors. The goal of this study is to build an intelligent conversational agent that can recognize user’s engagement from multiple types of eye-gaze information. In our previous work, we developed a method of estimating the user’s conversational engagement using user’s gaze transition patterns. However, it was not accurate enough. In this study, we added new variables in our gaze analysis: occurrence of mutual gaze, gaze duration, and distance of eye movement. Then, based on the results of the analysis, we used the variables as estimation parameters, and set up prediction models which consist of different combinations of parameters. To test which parameters are effective, the performance of these models were compared. As the result, it was revealed that a model using the gaze transition patterns, occurrence of mutual gaze, gaze duration, distance of eye movement, and pupil size as prediction parameters performed the best and was able to predict the user’s conversational engagement quite well. Author
A Comparative Study of Transient Flow through Cerebral Aneurysms using CFD

The recent advances in computational fluid dynamics (CFD) can be useful in observing the detailed hemodynamics in cerebral aneurysms for understanding not only their formation and rupture but also for clinical evaluation and treatment. However, important hemodynamic quantities are difficult to measure in vivo. In the present study, an approximate model of normal middle cerebral artery (MCA) along with two cases consisting broad and narrow saccular aneurysms are analyzed. The models are generated in ANSYS WORKBENCH and transient analysis is performed in ANSYS-CFX. The results obtained are compared for three cases and agree well with the available literature.
Evaluation of the CENTURY Model Using Long-Term Fertilization Trials under Corn-Wheat Cropping Systems in the Typical Croplands of China

Soil organic matter models are widely used to study soil organic carbon (SOC) dynamics. Here, we used the CENTURY model to simulate SOC in wheat-corn cropping systems at three long-term fertilization trials. Our study indicates that CENTURY can simulate fertilization effects on SOC dynamics under different climate and soil conditions. The normalized root mean square error is less than 15% for all the treatments. Soil carbon presents various changes under different fertilization management. Treatment with straw return would enhance SOC to a relatively stable level whereas chemical fertilization affects SOC differently across the three sites. After running CENTURY over the period of 1990–2050, the SOC levels are predicted to increase from 31.8 to 52.1 Mg ha−1 across the three sites. We estimate that the carbon sequestration potential between 1990 and 2050 would be 9.4–35.7 Mg ha−1 under the current high manure application at the three sites. Analysis of SOC in each carbon pool indicates that long-term fertilization enhances the slow pool proportion but decreases the passive pool proportion. Model results suggest that change in the slow carbon pool is the major driver of the overall trends in SOC stocks under long-term fertilization.
The sensitivity of cultured mammalian cells in different stages of the division cycle to nitrogen and sulfur mustards.

Summary Strain L mouse fibroblasts growing in vitro were exposed to varying concentrations of nitrogen and sulfur mustards, and the surviving fraction of cells was measured by their ability to form macroscopically visible colonies. Nitrogen mustard required 3 hours but sulfur mustard less than 1 hour to exert maximum killing effect. The mean lethal dose (D 37 ) for nitrogen mustard acting for 1 hour on an exponentially growing culture was 0.16 µg/ml. The D 37 for the uniterrupted action of sulfur mustard on exponentially growing cells was 0.12 µg/ml. Partially synchronously growing cultures were prepared by the addition of 5-fluoro-2′-deoxyuridine, followed 16 hours later by the addition of thymidine. Cell samples were taken from the synchronized culture at various times, and their sensitivity to the mustards was ascertained. With nitrogen mustard the D 37 obtained for cells in the period of DNA synthesis was 0.08 µg/ml. The D 37 for G 2 cells was 0.18 µg/ml. Cells in the G 1 stage were also less sensitive than those in the period of DNA synthesis, but it was not possible to obtain a quantitative value. Sulfur mustard gave similar results.
Comparison of semiclassical transport formulations including quantum corrections for advanced devices with High-K gate stacks

Long-channel effective mobilities as well as transfer characteristics of a 32 nm single-gate SOI and a 16 nm double-gate (DG) MOSFET have been simulated with live different Monte Carlo (MC) device simulators. The differences are mostly rather small for the SOI-FET with quantum effects having a minor effect on threshold voltage due to the lowly doped channel, while the two multi-subband MC simulators show some prominent deviations in the case of the DG-FET. High-K mobility degradation by remote phonon scattering (RPS) in free carrier MC approximation leads to smaller performance degradation compared to multi-subband MC with remote Coulomb scattering (RCS) and RPS, but requires further investigations.
Summer temperature can predict the distribution of wild yeast populations

The wine yeast, Saccharomyces cerevisiae, is the best understood microbial eukaryote at the molecular and cellular level, yet its natural geographic distribution is unknown. Here we report the results of a field survey for S. cerevisiae, S. paradoxus and other budding yeast on oak trees in Europe. We show that yeast species differ in their geographic distributions, and investigated which ecological variables can predict the isolation rate of S. paradoxus, the most abundant species. We find a positive association between trunk girth and S. paradoxus abundance suggesting that older trees harbour more yeast. S. paradoxus isolation frequency is also associated with summer temperature, showing highest isolation rates at intermediate temperatures. Using our statistical model, we estimated a range of summer temperatures at which we expect high S. paradoxus isolation rates, and show that the geographic distribution predicted by this optimum temperature range is consistent with the worldwide distribution of sites where S. paradoxus has been isolated. Using laboratory estimates of optimal growth temperatures for S. cerevisiae relative to S. paradoxus, we also estimated an optimum range of summer temperatures for S. cerevisiae. The geographical distribution of these optimum temperatures are consistent with the locations where wild S. cerevisiae have been reported, and can explain why only human-associated S. cerevisiae strains are isolated at northernmost latitudes. Our results provide a starting point for targeted isolation of S. cerevisiae from natural habitats, which could lead to a better understanding of climate associations and natural history in this important model microbe.
Reassessing and refining theory in qualitative accounting research

Purpose This paper focuses on the role of theory in the process of doing qualitative accounting research. It discusses the role of theory in qualitative accounting studies, and provides and example of how theory can be reflected upon, reassessed and refined during a research process. Design/methodology/approach This paper provides an illustrative account of theorizing during the process of qualitative accounting research. The paper places specific emphasis on an abductive approach to theorizing. An abductive theoretical framework is used to reflect on the theorizing process. Findings The “findings” reflect on the use of theory and the process of theorizing during a research process. The paper finds that abduction may be a useful way of theorizing in qualitative accounting research because it encourages the researcher to remain open to alternative explanations of data, which may promote theoretical development. This paper does not report the accounting practices of an organization in the traditional sense, but illustrates how the empirical findings led to an initial theoretical framework being developed. Practical implications The paper is intended to be informative in showing how theory can be used and developed during research. It may be of value and interest to new and emerging researchers. It may also interest established researchers seeking to reflect on their use of theory in research. Originality/value There are few contributions that focus exclusively and explicitly on how theory is used and developed during the process of qualitative accounting research. Moreover, the abductive approach has received limited attention in accounting. This paper aims to address these gaps.
NATURE’S MEANINGS FOR PSYCHOLOGICAL WELL-BEING

The present article makes an introduction for an interdisciplinary theme: the connection between well-being and nature. This theme will be explored starting from highlighting the importance of the concept of well-being in the health and illness models, and the transition it allows from an atomist point of view to a holistic approach. Results of previous academic studies will help understand that, by examining the effects of natural environment on several aspects of psychological and psychosomatic functioning, a holistic approach would become possible. Results of public data will be discussed as a way of expanding the explanation framework. Also a theoretical framework will be presented so that all these would have a meaning for practitioners. Finally, acknowledging the fact that the environments’ benefits have been known and consciously used for human growth in several aspects, as in yoga or martial arts, some recent application will be discussed such as those in psychotherapy (nature psychotherapy or unification experiential psychotherapy).
Extremum-seeking control for periodic steady-state response optimization

Extremum-seeking control is a powerful adaptive technique to optimize steady-state system performance. To this date, extremum-seeking control has mainly been used to optimize plants with constant steady-state outputs, whereas the case in which the steady-state outputs are time varying, has received less attention. We propose an extremum-seeking scheme for the optimization of nonlinear plants with periodic steady-state outputs. Extremum-seeking control in this setting is relevant in e.g. the scope of tracking and disturbance rejection problems. We show that under certain assumptions the proposed extremum-seeking controller design guarantees that for an arbitrarily large set of initial conditions the steady-state performance of the plant converges arbitrarily close to its optimal value.
Working Paper Number 70 Capital Account Liberalisation and Poverty

While poverty reduction has become the central focus of the multilateral institutions, research into macroeconomic policy has lagged behind and continues to be almost solely growth-focused. This paper aims to contribute to one policy area, that of capital account regulation, and sets out a framework of linkages to poverty. The key conclusion is that while the growth benefits of liberalisation are far from clear for poorer countries, there may be significant costs in poverty terms. While further research is required in a number of areas identified, the main policy implication is that capital controls must be retained as part of the toolbox of pro-poor macroeconomic policymaking.
Adaptive Hierarchical Key Structure Generation for Key Management in Wireless Sensor Networks using A

— Wireless Sensor networks have a wide spectrum of civil and military applications that call for secure communication such as the terrorist tracking, target surveillance in hostile environments. For the secure communication in these application areas, we propose a method for generating a hierarchical key structure for the efficient group key management. In this paper, we apply A* algorithm in generating a hierarchical key structure by considering the history data of the ratio of addition and eviction of sensor nodes in a location where sensor nodes are deployed. Thus generated key tree structure provides an efficient way of managing the group key in terms of energy consumption when addition and eviction event occurs. A* algorithm tries to minimize the number of messages needed for group key management by the history data. The experimentation with the tree shows efficiency of the proposed method.
Effects of Temperature on Gene Expression and Sex Determination in the Mangrove Rivulus, Kryptolebias marmoratus

Title of Document: EFFECTS OF TEMPERATURE ON GENE EXPRESSION AND SEX DETERMINATION IN THE MANGROVE RIVULUS, KRYPTOLEBIAS MARMORATUS Jennifer Strykowski, Master of Science 2011 Directed by: Assistant Professor Dr. Edward F. Orla ndo, Department of Animal and Avian Sciences Rivulus is a hermaphroditic, self-fertilizing fish pecies that possesses an ovotestis and, in the wild, exist as androdioecious populations compr ised of hermaphrodites and males. Following embryonic incubation at an ambient temper ature of 25 °C, rivulus develop normally as hermaphrodites. Embryos exposed to a l ower temperature of 20 °C during a critical phase of embryogenesis develop as males. In this study, rivulus embryos were maintained at ambient (25 °C), low (20 °C), or high (31 °C) temperatures during various stages of embryogenesis. The expression of seven e volutionary conserved genes with known relevance to gonadal differentiation includin g figα, foxl2, cyp19a1b, cyp19a1a, dmrt1, sox9a, and sox9b was measured using real-time PCR. The expression of cyp19a1a was downregulated at 20 °C and the expression of ovarian-specific genes increased throughout embryogenesis. These results provide the first data documenting how temperature affects the expression of genes rel vant to sex determination during embryogenesis in rivulus. EFFECTS OF TEMPERATURE ON GENE EXPRESSION AND SEX DETERMINATION IN THE MANGROVE RIVULUS, KRYPTOLEBIAS MARMORATUS
A recursive least M-estimate algorithm for robust adaptive filtering in impulsive noise: fast algorithm and convergence performance analysis

This paper studies the problem of robust adaptive filtering in impulsive noise environment using a recursive least M-estimate algorithm (RLM). The RLM algorithm minimizes a robust M-estimator-based cost function instead of the conventional mean square error function (MSE). Previous work has showed that the RLM algorithm offers improved robustness to impulses over conventional recursive least squares (RLS) algorithm. In this paper, the mean and mean square convergence behaviors of the RLM algorithm under the contaminated Gaussian impulsive noise model is analyzed. A lattice structure-based fast RLM algorithm, called the Huber Prior Error Feedback-Least Squares Lattice (H-PEF-LSL) algorithm is derived. Part of the H-PEF-LSL algorithm was presented in ICASSP 2001. It has an order O(N) arithmetic complexity, where N is the length of the adaptive filter, and can be viewed as a fast implementation of the RLM algorithm based on the modified Huber M-estimate function and the conventional PEF-LSL adaptive filtering algorithm. Simulation results show that the transversal RLM and the H-PEF-LSL algorithms have better performance than the conventional RLS and other RLS-like robust adaptive algorithms tested when the desired and input signals are corrupted by impulsive noise. Furthermore, the theoretical and simulation results on the convergence behaviors agree very well with each other.
Resveratrol Sensitizes Selectively Thyroid Cancer Cell to 131-Iodine Toxicity

Background. In this study, the radiosensitizing effect of resveratrol as a natural product was investigated on cell toxicity induced by 131I in thyroid cancer cell. Methods. Human thyroid cancer cell and human nonmalignant fibroblast cell (HFFF2) were treated with 131I and/or resveratrol at different concentrations for 48 h. The cell proliferation was measured by determination of the percent of the survival cells using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Results. Findings of this study show that resveratrol enhanced the cell death induced by 131I on thyroid cancer cell. Also, resveratrol exhibited a protective effect on normal cells against 131I toxicity. Conclusion. This result indicates a promising effect of resveratrol on improvement of cellular toxicity during iodine therapy.
Usage-oriented multimedia information retrieval technological evaluation

Shared evaluation tasks have become popular over the last decades as ways of making communities of researchers advance together. This paper presents the organization of five new shared task evaluation campaigns for image indexing and retrieval. We have designed these campaigns based on our previous experience of participating in or organizing various text retrieval campaigns such as TREC, AMARYLLIS and CLEF. Our purpose behind these campaigns is to minimize the gap between technology evaluation and user-oriented evaluation in the field of information retrieval.
Photo‐ and Proton‐Dual‐Responsive Fluorescence Switch Based on a Bisthienylethene‐Bridged Naphthalimide Dimer and Its Application in Security Data Storage

have thus been investigated. However,most of these systems show on/off switching of fluorescencein only single-mode stimulus–response. For further practi-cal applications, and also to enhance the multifunctionalityof these systems, it is better to combine highly integratedmodes into a single molecular unit that can exhibit multire-sponsive modulation of luminescence.
Mindfulness is associated with intrinsic functional connectivity between default mode and salience networks

Mindfulness is attention to present moment experience without judgment. Mindfulness practice is associated with brain activity in areas overlapping with the default mode, salience, and central executive networks (DMN, SN, CEN). We hypothesized that intrinsic functional connectivity (iFC; i.e., synchronized ongoing activity) across these networks is associated with mindfulness scores. After 2 weeks of daily 20 min attention to breath training, healthy participants were assessed by mindfulness questionnaires and resting-state functional MRI. Independent component analysis (ICA) of imaging data revealed networks of interest, whose activity time series defined inter-network intrinsic functional connectivity (inter-iFC) by temporal correlation. Inter-iFC between subnetworks of the DMN and SN—and inter-iFC between subnetworks of the SN and left CEN at trend—was correlated with mindfulness scores. Additional control analyses about visual networks’ inter-iFC support the specificity of our findings. Results provide evidence that mindfulness is associated with iFC between DMN and SN. Data suggest that ongoing interactions among central intrinsic brain networks link with the ability to attend to current experience without judgment.