Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent Developments on Related Studies of the "Mozart Effect" Phenomenon on Social Learning Behavior.

After a five (5) day observation period and successfully documenting the current dynamics of high students in the academic and social settings before the exposure to Mozart‘s music, the researcher continues with a twenty (20) day observation period of the same participants in their respective environments while exposed to Mozart‘s music. Before the exposure to Mozart‘s music, the dynamics of High School students in the Academic setting, during the five (5) day observation period, has shown to have a minimal number of students displaying behavior leading to learning. Presented are the averages of the observed behavior of High School students before the exposure to Mozart‘s music. On the other hand, the dynamics of High School students in the Social setting, during the five (5) day observation period, many students have not shown behavior leading to social interaction. Presented are the averages of the observed behavior of High School students before the exposure to Mozart‘s music. However, after the exposure to Mozart‘s music, in the academic setting, during the exposure to Mozart‘s music for a period of twenty (20) days, there was an increase in percentages from Day 16 to Day 20. Every student was eliciting two (2) or more behaviors leading to learning. In comparison to Day 1 to Day 15, the last five (5) days, Day 16 to Day 20, showed very high percentages of students that showed behavior leading to learning. To further illustrate the high percentages of students that showed behavior leading to learning during the Day 16 to Day 20, the following data is presented representing the averages of the percentage of students that showed behavior leading to learning during this time frame.
Global geometric properties of AdS space and the AdS/CFT correspondence

The Poisson kernels and relations between them for a massive scalar field in a unit ball B n with Hua's metric and conformal flat metric are obtained by describing the B n as a submanifold of an ( n +1)-dimensional embedding space. Global geometric properties of the AdS space are discussed. We show that the ( n +1)-dimensional AdS space AdS n+1 is isomorphic to RP 1 × B n and boundary of the AdS is isomorphic to RP 1 ×S n -1 . Bulk-boundary propagator and the AdS/CFT like correspondence are demonstrated based on these global geometric properties of the RP 1 × B n .
Comparative Analysis of Data Mining Tools and Techniques for Evaluating Performance of Database System

Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Nowadays, large amount of data and information are available, Data can now be stored in many different kinds of databases and information repositories, being available on the Internet. There is a need for powerful techniques for better interpretation of these data that exceeds the human's ability for comprehension and making decision in a better way. There are data mining, web mining and knowledge discovery tools and software packages such as WEKA Tool and RapidMiner tool. The work deals with analysis of WEKA, RapidMiner and NetTools spider tools KNIME and Orange. There are various tools available for data mining and web mining. Therefore awareness is required about the quantitative investigation of these tools. This paper focuses on various functional, practical, cognitive as well as analysis aspects that users may be looking for in the tools. Complete study addresses the usefulness and importance of these tools including various aspects. Analysis presents various benefits of these data mining tools along with desired aspects and the features of current tools.
Robot therapy for severely impaired stroke survivors: Toward a concurrent regulation of task difficulty and degree of assistance

Many exercise protocols for robot therapy are designed to adjust their degree of difficulty in order to maintain a constant challenge level. A simple way to do this is to design exercises that consist of a variable number of sub-movements in different directions - task difficulty is determined by the number of sub-movements. But, how does recovery proceed in these tasks, and how to regulate the magnitude of the assistance provided by the robot in this case? Here we focus on a simple task in which subjects had to complete a square figure. At every trial, an adaptive regulator selects the appropriate degree of robot assistance needed to complete the entire figure. We tested this protocol with four severely impaired stroke survivors during a multisession study. Robotic training succeeded - the controller gradually reduced the degree of assistance while performance remained constant, suggesting that in fact recovery took place. We used a dynamic model of the recovery process to further analyze the effects of the assistive force and the temporal evolution of the subjects' voluntary control. The model provided an excellent fitting of the subjects' performance and revealed that magnitude and modalities of recovery are very different in the different sub-movements. These results suggest that in order to maximize the recovery the modulation of assistance should occur at the level of each sub-movement.
A comparative evolutionary study of transcription networks

We present a comparative analysis of large-scale topological and evolutionary properties of transcription networks in three species, the two distant bacteria E. coli and B. subtilis, and the yeast S. cerevisiae. The study focuses on the global aspects of feedback and hierarchy in transcriptional regulatory pathways. While confirming that gene duplication has a significant impact on the shaping of all the analyzed transcription networks, our results point to distinct trends between the bacteria, where time constraints in the transcription of downstream genes might be important in shaping the hierarchical structure of the network, and yeast, which seems able to sustain a higher wiring complexity, that includes the more feedback, intricate hierarchy, and the combinatorial use of heterodimers made of duplicate transcription factors.
Dystrophin Dp71 Is Critical for the Clustered Localization of Potassium Channels in Retinal Glial Cells

The Müller cell is the principal glial cell of the vertebrate retina. The primary conductance in Müller cells is the inwardly rectifying potassium channel Kir4.1 (BIR10 and KAB-2), which is highly concentrated at the endfeet at the vitreal border and to processes enveloping blood vessels. Such asymmetric and clustered distribution of Kir4.1 channels in Müller cells is thought to be critical for the buffering of extracellular potassium concentration in retina. Herein we investigated whether the distribution and functional properties of Kir4.1 channels are dependent on expression of the Dp71, a dystrophin isoform expressed in Müller cells. Kir4.1 distribution was determined in mouse retinal sections and whole mounts using anti-Kir4.1 antibodies and confocal microscopy. In Müller cells from wild-type mice, Kir4.1 is highly clustered in their endfeet and perivascular processes. In contrast, in Müller cells from the mdx3Cv mouse, which lacks the expression of Dp71, the Kir4.1 immunoreactivity is evenly distributed throughout the cell membrane. Surface expression of Kir4.1 is not affected in mdx3Cv Müller cells as current density of barium-sensitive inward currents in mdx3Cv Müller cells are not different from wild type. Focal extracellular potassium increases in isolated Müller cells shows that Kir channels in the mdx3Cv cells, as opposed to wild type, are less prominently concentrated in their endfeet. In summary, our data indicate that Dp71 is critical for the clustering but not membrane expression of Kir4.1 in mouse Müller cells. These results point to a new role for dystrophin in glial cells.
Exploring intergenerational, intra-generational and transnational patterns of family caring in minority ethnic communities: the example of England and Wales

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Efficient Illumination Insensitive Object Tracking by Normalized Gradient Matching

We propose a novel tracking algorithm by minimizing the sum-of-squared differences (SSD) between the normalized image gradients of the template image and the input image from the test image sequence. The proposed tracking algorithm is efficient to implement since it is based on the framework of the inverse compositional algorithm, a computationally efficient tracking technique. The experiments show that the proposed tracking algorithm is superior to the intensity-based inverse compositional algorithm in tracking objects under varying illumination conditions.
Evaluating and optimizing computational protein design force fields using fixed composition-based negative design

An accurate force field is essential to computational protein design and protein fold prediction studies. Proper force field tuning is problematic, however, due in part to the incomplete modeling of the unfolded state. Here, we evaluate and optimize a protein design force field by constraining the amino acid composition of the designed sequences to that of a well behaved model protein. According to the random energy model, unfolded state energies are dependent only on amino acid composition and not the specific arrangement of amino acids. Therefore, energy discrepancies between computational predictions and experimental results, for sequences of identical composition, can be directly attributed to flaws in the force field's ability to properly account for folded state sequence energies. This aspect of fixed composition design allows for force field optimization by focusing solely on the interactions in the folded state. Several rounds of fixed composition optimization of the 56-residue β1 domain of protein G yielded force field parameters with significantly greater predictive power: Optimized sequences exhibited higher wild-type sequence identity in critical regions of the structure, and the wild-type sequence showed an improved Z-score. Experimental studies revealed a designed 24-fold mutant to be stably folded with a melting temperature similar to that of the wild-type protein. Sequence designs using engrailed homeodomain as a scaffold produced similar results, suggesting the tuned force field parameters were not specific to protein G.
Information Dissemination of Location Dependent Data in Consideration of Connectivity and Network Partition in Mobile Ad Hoc Sensor Networks

In mobile ad hoc networks, due to the movement of hosts, obstacles, etc, it is difficult for mobile hosts to access the data on other hosts. To solve this problem, replica distribution methods which distribute the replicas of data items to other hosts and maintain them have been proposed. We have proposed LDR (Link-aware and Density-based Rearrangement) method for dynamic rearrangement of replicas of location dependent data. In the LDR method, replicas of the location dependent data items are placed on mobile hosts which are the neighbors of branch points of the ad hoc networks and the density of replicas are controlled according to the degree of the network topology. We evaluated the performance of the LDR method by simulation. The simulation results show that the LDR method achieves higher performance than other methods when the distance between the requesting host and the location where the data item is associated is long and the host moving velocity is high.
A pedometric approach to valuing the soil resource

This paper presents an approach to valuation of the soil resource, using pedometric techniques. This value is broken down by soil functions which provide services, classified as (1) supporting; (2) production, (3) regulating; (4) cultural. For each the value can in principle be assessed quantifying the functions, enumerating and quantifying soil properties relevant to the function, and applying a quantitative model of the functions as affected by the properties. In practice this is approximated by a subset of functions and simple models. This procedure faces some complications, notably finding a common measure of value; disentangling the concepts of ‘soil’ and ‘land’; discounting the future; and combining valuations of individual services into a common value.
Population structure, virulence potential and antibiotic susceptibility of uropathogenic Escherichia coli from Northwest England.

OBJECTIVES Multilocus sequence typing (MLST) has been used to characterize diverse pathogens, including uropathogenic Escherichia coli (UPEC). There has been significant interest in the contribution of the O25b:H4-ST131 lineage to UPEC disease, as these isolates are often highly virulent and exhibit multidrug resistance. To reveal the wider impact of sequence type (ST) 131, we have examined its contribution to the overall population structure of UPEC isolates that were not selected on the basis of virulence or antibiotic resistance. METHODS Three hundred UPEC isolates were recovered from community and hospital urine samples examined by clinical microbiology laboratories in the Northwest region of England in June 2007 and June 2009. They were characterized by susceptibility profiling, MLST and virulence gene PCR. PFGE was used to examine isolates from key clones. RESULTS The most common lineage was ST73 (16.6%) followed by ST131 (13.3%), ST69 (9%), ST95 (6.3%), ST10 (4.3%) and ST127 (3.6%). ST131 isolates were significantly more likely to exhibit high levels of antibiotic resistance (35% being CTX-M-15 PCR positive) and those of ST127 were the most widely susceptible but carried the highest number of virulence genes. Only when the CTX-M-15-O25b-positive strains were examined was a high level of virulence observed for ST131 isolates. PFGE indicated ongoing local evolution in ST131. CONCLUSIONS ST131 isolates are well established in the wider UPEC population. This clone is still evolving and we further support suggestions that it represents a real threat to health. We suggest that ST127 is a recently emerged, community-associated, virulent clone that warrants further study.
An area-efficient 5GHz/10GHz dual-mode VCO with coupled helical inductors in 0.13-UM CMOS technology

The helical inductor is a three-dimensional multi-layer inductor with relatively higher quality factor and self-resonance frequency compare with other multi-layer inductors. A new dual-mode coupled-inductor VCO based on helical inductors is proposed, which is able to work on 5GHz and 10GHz band. Because of the helical inductors used, the proposed VCO is much more area-efficient than previous coupled-inductor structure. The simulation results show that the phase noise at 1 MHz offset is −101.6dBc/Hz and −101.3dBc/Hz at the frequency of 4.8GHz and 10.4GHz, respectively. The VCO draws 4mA from 1.2 V supply.
REDUCTION OF NUMBER OF ASSOCIATION RULES WITH INTER ITEMSET DISTANCE IN TRANSACTION DATABASES

Association Rule discovery has been an important problem of investigation in knowledge discovery and data mining. An association rule describes associations among the sets of items which occur together in transactions of databases.The Association Rule mining task consists of finding the frequent itemsets and the rules in the form of conditional implications with respect to some prespecified threshold values of support and confidence.The interestingness of Association Rules are determined by these two measures. However, other measures of interestingness like lift and conviction are also used. But, there occurs an explosive growth of discovered association rules and many of such rules are insignificant. In this paper we introduce a new measure of interestingness called Inter Itemset Distance or Spread and implemented this notion based on the approaches of the apriori algorithm with a view to reduce the number of discovered Association Rules in a meaningful manner. An analysis of the working of the new algorithm is done and the results are presented and compared with the results of conventional apriori algorithm.
Reduced Expression of Organic Cation Transporters rOCT1 and rOCT2 in Experimental Diabetes

Recent reports have documented a functional deficit of organic cation transport in diabetic rats by an unknown mechanism. This study was designed to test the hypothesis that experimental diabetes decreases expression of organic cation transporters at the basolateral membrane. Streptozotocin-induced diabetic rats were maintained for varying durations after induction of diabetes. A second group of age-matched control rats was maintained in a parallel manner. Kinetic analysis of tetraethylammonium accumulation in freshly isolated proximal tubular cells indicated a significantly lower Vmax value for the diabetics versus controls with no statistical difference in Km values between the two groups. Cortex sections were processed by standard procedures for Northern and immunoblot analysis. Protein expression of the organic cation transporters rOCT1 and rOCT2 progressively decreased with increasing duration of diabetes. After 21 days of diabetes, rOCT1 and rOCT2 were maximally reduced by 50 and 70%, respectively. Quantification of mRNA expression revealed that the roct1 transcript remained unchanged, whereas the roct2 transcript was decreased by 50% after 14 days of diabetes. Treatment with insulin prevented the reductions in transporter levels. These results support the hypothesis by demonstrating that experimental diabetes decreased expression of both rOCT1 and rOCT2 protein and also of roct2 mRNA accumulation. On the other hand, roct1 mRNA levels were unaffected by the diabetic state. This suggests that differences in rOCT2 protein may result from transcriptional and/or translational changes, whereas rOCT1 deficits may be due to posttranscriptional alterations.
A Literature Review on the Use of Soft Computing in Support of Human Resource Management

Organizational Human Resource Management (HRM) presents com- plex problems, some of them difficult to aboard by traditional problem solving strategies, because of the necessity to face subjective or imprecise issues, such as the evaluation of knowledge or abilities of a candidate for a specific job. Be- cause of the above, researchers and practitioners have used Soft Computing, or Computational Intelligence, approaches to aboard some of the problems faced in HRM. This paper present the results of a systematic literature review con- ducted to know how Soft Computing has contributed to solve the problems that exist in HRM. The research identified is classified according to the problems faced in the field of HRM, and the Soft Computing techniques used to aboard such problems.
School choice and school competition: Evidence from the United States

Summary The most frequently asked questions about school choice are: Do public schools respond constructively to competition induced by school choice, by raising their own productivity? Does students’ achievement rise when they attend voucher or charter schools? Do voucher and charter schools end up with a selection of the better students (“cream-skim”)? I review the evidence on these questions from the United States, relying primarily on recent policy experiments. Public schools do respond constructively to competition, by raising their achievement and productivity. The best studies on this question examine the introduction of choice programs that have been sufficiently large and long-lived to produce competition. Students’ achievement generally does rise when they attend voucher or charter schools. The best studies on this question use, as a control group, students who are randomized out of choice programs. Not only do currently enacted voucher and charter school programs not cream-skim; they disproportionately attract students who were performing badly in their regular public schools. This confirms what theory predicts: there are no general results on the sorting consequences of school choice. The sorting consequences of a school choice plan depend strongly on its design.
The Enigma of Domestic and Sexual Violence: Introduction to Special Edition

focuses on issues of domestic and sexual violence. The journal articles are all original research projects first presented at the one-day RESOLVE Alberta conference held in Calgary, Alberta in November of 2007. On that occasion, the RESOLVE Alberta conference was offered in partnership with Calgary’s Domestic Violence Committee, which hosted a
Generalization Error of Linear Neural Networks in an Empirical Bayes Approach

It is well known that in unidentifiable models, the Bayes estimation has the advantage of generalization performance to the maximum likelihood estimation. However, accurate approximation of the posterior distribution requires huge computational costs. In this paper, we consider an empirical Bayes approach where a part of the parameters are regarded as hyperparameters, which we call a subspace Bayes approach, and theoretically analyze the generalization error of three-layer linear neural networks. We show that a subspace Bayes approach is asymptotically equivalent to a positivepart James-Stein type shrinkage estimation, and behaves similarly to the Bayes estimation in typical cases.
Pathogenesis of Lassa Fever

Lassa virus, an Old World arenavirus (family Arenaviridae), is the etiological agent of Lassa fever, a severe human disease that is reported in more than 100,000 patients annually in the endemic regions of West Africa with mortality rates for hospitalized patients varying between 5-10%. Currently, there are no approved vaccines against Lassa fever for use in humans. Here, we review the published literature on the life cycle of Lassa virus with the specific focus put on Lassa fever pathogenesis in humans and relevant animal models. Advancing knowledge significantly improves our understanding of Lassa virus biology, as well as of the mechanisms that allow the virus to evade the host’s immune system. However, further investigations are required in order to design improved diagnostic tools, an effective vaccine, and therapeutic agents.
Are Students Representatives of Professionals in Software Engineering Experiments?

Background: Most of the experiments in software engineering (SE) employ students as subjects. This raises concerns about the realism of the results acquired through students and adaptability of the results to software industry. Aim: We compare students and professionals to understand how well students represent professionals as experimental subjects in SE research. Method: The comparison was made in the context of two test-driven development experiments conducted with students in an academic setting and with professionals in a software organization. We measured the code quality of several tasks implemented by both subject groups and checked whether students and professionals perform similarly in terms of code quality metrics. Results: Except for minor differences, neither of the subject groups is better than the other. Professionals produce larger, yet less complex, methods when they use their traditional development approach, whereas both subject groups perform similarly when they apply a new approach for the first time. Conclusion: Given a carefully scoped experiment on a development approach that is new to both students and professionals, similar performances are observed. Further investigation is necessary to analyze the effects of subject demographics and level of experience on the results of SE experiments.