Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving well-being and behavior in adolescents utilizing a school-based positive psychology intervention

ABSTRACT This study is a multi-component Positive Psychology Intervention (PPI) with the goal of improving daily happiness and classroom behavior in a sample at-risk high-school students. PPIs have increasingly been used in school settings to enhance student well-being, student success, and to increase positive affect. The current study utilized a multiple baseline design, across five adolescents, to examine whether a manualized PPI implemented in individual school-based counseling sessions with at-risk high-school students, would lead to increased happiness, improved classroom behavior, and life satisfaction, measured through a Daily Happiness survey, the Direct Behavior Rating (DBR), General Happiness Scale, Brief Multidimensional Students’ Life Satisfaction Scale, and the Student Life Satisfaction Scale. Results demonstrated high variability in the data and an overall null effect of the intervention on the two dependent variables of daily happiness and classroom behavior. Limitations included individual impacts of outside factors on student reports and behavior. Due to the small scale of the study and lack of observed intervention effects, more research is needed to draw conclusions about the application of the intervention. However, social validity data revealed that school-based mental health professionals may still consider this intervention to teach students strategies to improve life satisfaction.
Quantum-inspired evolutionary clustering algorithm based on manifold distance

Based on the concepts and principles of quantum computing, a quantum-inspired evolutionary algorithm for data clustering (QECA) is proposed in this paper. And a novel distance measurement index called manifold distance is introduced. These attribute data are the main source of clustering problem, due to its complex distribution, most clustering algorithms available are only suitable for these types of characteristic data. In this study, a new algorithm which can deal with these data with manifold distribution is more effective. The main motives of using QECA consist in searching for appropriate cluster center so that a similarity metric of clusters are optimized more quickly and effectively. The superiority of QECA over fuzzy c-means (FCM) algorithm and immune evolutionary clustering algorithm (IECA) is extensively demonstrated in our experiments.
Downregulation of OPA 1 alters mouse mitochondrial morphology , PTP function , and cardiac adaptation to pressure overload Running title : OPA 1 deficit and cardiac mitochondria

Aims: The optic atrophy 1 (OPA1) protein is an essential protein involved in the fusion of the mitochondrial inner membrane. Despite its high level of expression, the role of OPA1 in the heart is largely unknown. We investigated the role of this protein in Opa1 mice, having a 50% reduction in OPA1 protein expression in cardiac tissue. Methods and Results: In mutant mice, cardiac function assessed by echocardiography was not significantly different from that of the Opa1. Electron and fluorescence microscopy revealed altered morphology of the Opa1 mitochondrial network; unexpectedly, mitochondria were larger with the presence of clusters of fused mitochondria and altered cristae. In permeabilized mutant ventricular fibers, mitochondrial functional properties were maintained, but direct energy channeling between mitochondria and myofilaments was weakened. Importantly, the mitochondrial permeability transition pore (PTP) opening in isolated permeabilized cardiomyocytes and in isolated mitochondria was significantly less sensitive to mitochondrial calcium accumulation. Finally, 6 weeks after transversal aortic constriction (TAC), Opa1 hearts demonstrated hypertrophy almost two-fold higher (p<0.01) than in wild type mice with altered ejection fraction (decrease of 43% versus 22% in Opa1 mice, p<0.05). Conclusions: These results suggest that, in adult cardiomyocytes, OPA1 plays an important role in mitochondrial morphology and PTP functioning. These properties may be critical for cardiac function under conditions of chronic pressure overload. in se rm -0 08 71 86 5, v er si on 1 10 O ct 2 01 3 Author manuscript, published in "Cardiovasc Res 2012;94(3):408-17" DOI : 10.1093/cvr/cvs117
Learning to Love: Milestones and Mechanisms

are "What develops? ", "What is the course of development? ", and "What are the mechanisms of change? " Highlighting seemingly purposeful and context sensitive secure base behavior that organizes attachment relationships, Bowlby (1958) defin ed attachment as an emotional bond that ties the child to one or a few figures across time and space. He described its development in terms of emerging preference for one or a few figures, the onset of secure base behavior, and a change in the representation of attachment figures during the childhood transition from sensorimotor to representational thought.
Phloem-specific expression of a melon Aux/IAA in tomato plants alters auxin sensitivity and plant development

Phloem sap contains a large repertoire of macromolecules in addition to sugars, amino acids, growth substances and ions. The transcription profile of melon phloem sap contains over 1000 mRNA molecules, most of them associated with signal transduction, transcriptional control, and stress and defense responses. Heterografting experiments have established the long-distance trafficking of numerous mRNA molecules. Interestingly, several trafficking transcripts are involved in the auxin response, including two molecules coding for auxin/indole acetic acid (Aux/IAA). To further explore the biological role of the melon Aux/IAA transcript CmF-308 in the vascular tissue, a cassette containing the coding sequence of this gene under a phloem-specific promoter was introduced into tomato plants. The number of lateral roots was significantly higher in transgenic plants expressing CmF-308 under the AtSUC2 promoter than in controls. A similar effect on root development was obtained after transient expression of CmF-308 in source leaves of N. benthamiana plants. An auxin-response assay showed that CmF-308-transgenic roots are more sensitive to auxin than control roots. In addition to the altered root development, phloem-specific expression of CmF-308 resulted in shorter plants, a higher number of lateral shoots and delayed flowering, a phenotype resembling reduced apical dominance. In contrast to the root response, cotyledons of the transgenic plants were less sensitive to auxin than control cotyledons. The reduced auxin sensitivity in the shoot tissue was confirmed by lower relative expression of several Aux/IAA genes in leaves and an increase in the relative expression of a cytokinin-response regulator, TRR8/9b. The accumulated data suggest that expression of Aux/IAA in the phloem modifies auxin sensitivity in a tissue-specific manner, thereby altering plant development.
A GENETIC ALGORITHM FOR REGRESSION TEST CASE PRIORITIZATION USING CODE COVERAGE

Regression testing is a testing technique which is used to validate the modified software. The regression test suite is typically large and needs an intelligent method to choose those test cases which will detect maximum or all faults at the earliest. Many existing prioritization techniques arrange the test cases on the basis of code coverage with respect to older version of the modified software. In this approach, a new Genetic Algorithm to prioritize the regression test suite is introduced that will prioritize test cases on the basis of complete code coverage. The genetic algorithm would also automate the process of test case prioritization. The results representing the effectiveness of algorithms are presented with the help of an Average Percentage of Code Covered (APCC) metric.
Ambient Air Pollution and Atherosclerosis in Los Angeles

Associations have been found between long-term exposure to ambient air pollution and cardiovascular morbidity and mortality. The contribution of air pollution to atherosclerosis that underlies many cardiovascular diseases has not been investigated. Animal data suggest that ambient particulate matter (PM) may contribute to atherogenesis. We used data on 798 participants from two clinical trials to investigate the association between atherosclerosis and long-term exposure to ambient PM up to 2.5 μm in aerodynamic diameter (PM2.5). Baseline data included assessment of the carotid intima-media thickness (CIMT), a measure of subclinical atherosclerosis. We geocoded subjects’ residential areas to assign annual mean concentrations of ambient PM2.5. Exposure values were assigned from a PM2.5 surface derived from a geostatistical model. Individually assigned annual mean PM2.5 concentrations ranged from 5.2 to 26.9 μg/m3 (mean, 20.3). For a cross-sectional exposure contrast of 10 μg/m3 PM2.5, CIMT increased by 5.9% (95% confidence interval, 1–11%). Adjustment for age reduced the coefficients, but further adjustment for covariates indicated robust estimates in the range of 3.9–4.3% (p-values, 0.05–0.1). Among older subjects (≥60 years of age), women, never smokers, and those reporting lipid-lowering treatment at baseline, the associations of PM2.5 and CIMT were larger with the strongest associations in women ≥60 years of age (15.7%, 5.7–26.6%). These results represent the first epidemiologic evidence of an association between atherosclerosis and ambient air pollution. Given the leading role of cardiovascular disease as a cause of death and the large populations exposed to ambient PM2.5, these findings may be important and need further confirmation.
Improved Morphological TOP-HAT Filter Optimized with Genetic Algorithm

The Top-Hat morphological filters are a class of nonlinear signal processing algorithms, which have been applied extensively to computer vision, image processing, and more recently target detection. In this paper a novel method for optimal learning of morphological filtering parameters for spot target detection is presented. We show how the Genetic Algorithms can be used for an automatic optimization of structuring elements. Experimental results show that the identified probability to the image of SNR 2 can reach more than 98% by this method.
Roofline-aware DVFS for GPUs

Graphics processing units (GPUs) are becoming increasingly popular for compute workloads, mainly because of their large number of processing elements and high-bandwidth to off-chip memory. The roofline model captures the ratio between the two (the compute-memory ratio), an important architectural parameter. This work proposes to change the compute-memory ratio dynamically, scaling the voltage and frequency (DVFS) of 1) memory for compute-intensive workloads and 2) processing elements for memory-intensive workloads. The result is an adaptive roofline-aware GPU that increases energy efficiency (up to 58%) while maintaining performance.
ANALYSIS OF BIDIRECTIONAL DC-DC CONVERTER FOR LOW POWER APPLICATIONS

In this paper, a bidirectional converter capable of operating in both buck and boost modes is proposed. The proposed converter consists of power switches and coupled inductor with equal number of turns in both primary and secondary windings. Power switches can be turned on with zero-voltage switching thereby reducing the switching loss and improving the conversion efficiency significantly. In boost mode, the coupled inductor is operated in parallel charge and series discharge configuration. The power is transferred from battery to motor. In buck mode, the power flow is reversed. Here, the coupled inductor operated in series charge parallel discharge. This converter shows improved values of gain during the forward and reverse power flow, compared with conventional converter. The dynamic performance of the proposed converter is validated through time domain simulations performed in PSIM environment.
Transaction Routing with Freshness Control in a Cluster of Replicated Databases

We consider the use of a cluster system with a shared nothing architecture for update-intensive autonomous databases. To optimize load balancing, we use optimistic database replication with freshness control. We propose a solution to transaction routing that preserves database and application autonomy and a cost model to estimate replica freshness. Then we propose an algorithm for transaction routing that takes into account freshness requirements of transactions and replica freshness. We implemented our solution on a Linux cluster running Oracle 8i and performed extensive performance experiments using the TPCC OLTP benchmark. Our results show that our solution outperforms existing solutions for typical transaction workloads.
Propionate: a candidate metabolite to link colonic metabolism to human adipose tissue inflammation

Wie voedingsvezels en niet-verteerbare koolhydraten eet, bijvoorbeeld volkoren producten, vermindert zijn risico op diabetes. Twee promovendi, Wang Hongwei en Sa’ad Al Lahham, hebben hiervoor nieuwe aanwijzingen gevonden. Ook brachten zij het onderliggende mechanisme in kaart. Steeds meer mensen lijden aan obesitas en ziektes die daarmee gepaard gaan, zoals type 2 diabetes en hart- en vaatziekten. Chronische ontsteking wordt gezien als een belangrijke factor in het ontstaan van deze ziekten. Ons vetweefsel speelt daarbij een sleutelrol. Tevens zorgt het eten van veel vet voor een sterkere ontstekingsreactie. Maar het lichaam kan deze ontstekingsreactie ook tegengaan. Na consumptie van niet-verteerbare koolhydraten ontstaan in de dikke darm fermentatieproducten, de zogeheten korte keten vetzuren. Deze hebben anti-ontstekingseffecten. De promovendi Wang Hongwei en Sa’ad Al-Lahham brachten in kaart wat voor effect propionzuur heeft, een van de korte keten vetzuren die in de dikke darm wordt geproduceerd. Ze ontdekten dat propionzuur de productie van diverse ontstekingsstoffen (cytokines, chemokines) en van merkers van macrofagen (betrokken bij ontstekingen) kan remmen. Bovendien stimuleert propionzuur processen die een positief effect kunnen hebben op insulinegevoeligheid en andere aandoeningen die met obesitas gepaard gaan. Hiermee bieden de promovendi een verklaring voor de beschermende effecten van voedingsvezels op de ontwikkeling van diabetes type 2. Ook tonen de onderzoekers aan dat gezonde mannen die ’s avonds niet-verteerbare koolhydraten eten, de volgende ochtend na het ontbijt een verlaagde glucoserespons en lagere ontstekingsfactoren in het bloed hebben. Ze vonden duidelijke aanwijzingen dat fermentatie in de dikke darm verantwoordelijk is voor deze gunstige eigenschappen. Consumptie van niet-verteerbare koolhydraten lijkt dan ook een veelbelovende aanpak bij de bescherming tegen diabetes.
Causal KL: Evaluating Causal Discovery

The two most commonly used criteria for assessing causal model discovery with artificial data are edit-distance and Kullback-Leibler divergence, measured from the true model to the learned model. Both of these metrics maximally reward the true model. However, we argue that they are both insufficiently discriminating in judging the relative merits of false models. Edit distance, for example, fails to distinguish between strong and weak probabilistic dependencies. KL divergence, on the other hand, rewards equally all statistically equivalent models, regardless of their different causal claims. We propose an augmented KL divergence, which we call Causal KL (CKL), which takes into account causal relationships which distinguish between observationally equivalent models. Results are presented for three variants of CKL, showing that Causal KL works well in practice.
An approximate message passing approach for tensor-based seismic data interpolation with randomly missing traces

In this paper, we consider the reconstruction of a high-dimensional seismic volume with randomly missing traces. Seismic data in the frequency-space domain are represented via a high-order tensor. Applying the parallel matrix factorization model to the underlying seismic tensor, we propose an iterative approximate message passing (AMP) approach to seismic data interpolation based on loopy belief propagation. In particular, we extend the bilinear generalized AMP (BiG-AMP) approach to incorporate parallel low-rank matrix factorizations by using a "turbo" framework, enabling iterative message passing between the subgraphs of the allmode unfoldings of the seismic tensor. The computational complexity of our algorithmic framework is low and scales linearly with the data size. Simulation results with synthetic seismic data suggest that the proposed algorithm yields better reconstruction performances relative to existing methods.
An information theoretic approach based Kullback-Leibler discrimination for multiple target tracking

To task space-based sensors to efficiently estimate the states of targets, an information theoretic approach is developed based on Kullback-Leibler (KL) discrimination for myopic sensor resource allocation. The technique employs the principle that sensors should take actions that maximize the expected KL discrimination as information gain. Calculate KL discrimination between the priori state probability distribution of targets in cells and the state probability distribution after dummy observations, and use expected KL discrimination to determine the best sensing action to take before actually executing it. Because targets' possible locations and possible dummy observations become a great many with target number and cell number increasing, algorithm modification is designed to combine the states with the same likelihood functions to speedup calculation. Finally the effectiveness of the proposed approach is evaluated by simulations and is verified that it is more effective and accurate to estimate target state and reduce uncertainty than other candidate methods especially in conditions of low SNR or poor sensors.
An environment for the specification and analysis of cryptoprotocols

We present the environment CPV (Cryptographic Protocol Verifier), a tool-set for the specification and analysis of cryptographic protocols. The CPV environment is based on the LSFM method that has been advanced as a formal, automatic and implicit verification method for security protocols. We recall briefly the essence of this method and present the architecture of the CPV environment. We discuss its main software components and detail the key issues in its implementation. Finally, we illustrate the LSFM method and the CPV environment on two case studies.
Staphylococcus aureus Virulence Factors Identified by Using a High-Throughput Caenorhabditis elegans-Killing Model

ABSTRACT Staphylococcus aureus is an important human pathogen that is also able to kill the model nematode Caenorhabditis elegans. We constructed a 2,950-member Tn917 transposon insertion library in S. aureus strain NCTC 8325. Twenty-one of these insertions exhibited attenuated C. elegans killing, and of these, 12 contained insertions in different genes or chromosomal locations. Ten of these 12 insertions showed attenuated killing phenotypes when transduced into two different S. aureus strains, and 5 of the 10 mutants correspond to genes that have not been previously identified in signature-tagged mutagenesis studies. These latter five mutants were tested in a murine renal abscess model, and one mutant harboring an insertion in nagD exhibited attenuated virulence. Interestingly, Tn917 was shown to have a very strong bias for insertions near the terminus of DNA replication.
Forest type classification using data fusion of multispectral and panchromatic high-resolution satellite imageries

This paper proposes fusion analysis of high-resolution multispectral and panchromatic satellite imageries for forest type classification. We have shown the performance of forest type classification using panchromatic and multispectral high-resolution QuickBird satellite imageries separately. With texture features obtained from a panchromatic imagery, forest was classified into two types, such as coniferous and broad-leaved forests. On the other hand, with spectral features obtained from a multispectral imagery, forest was classified into six types, such as three coniferous, one broad-leaved and two mixed forests. These results showed that both texture and spectral features are effective for classification of forest types. In this paper, we apply the object-based classification using the common segments obtained from a pansharpen imagery to fusion and single imagery analysis in order to compare the difference only between texture and spectral features. The mean value of each texture and spectral feature from a segment is adopted in the supervised classification, the standard nearest neighbor method, using radiometrically corrected satellite imageries. We selected the contrast as texture feature, and normalized band values and differences between normalized band values as spectral features. From the comparison of the result with ones obtained from a single imagery analysis, we demonstrated that data fusion analysis exceeds a single imagery analysis in accuracy.
How to Use Engineering in High School Science: Two Case Studies

Jessica Chin is an Artist/Designer/Researcher focusing on blending creativity with mechanical design. She has been collaborating with leading research and development laboratories including the Modeling, Analysis, and Predcition (MAP) Laboratory at Northeastern University in Boston, Mass. and the Center for STEM Education at Northeastern. For the past four years, Chin was a researcher working on the development of a predictive model for chronic wound tracking. In addition, she also supports a National Science Foundation initative to increase STEM (Science, Technology, Engineering, and Mathematics) in K-12 Education.
Variation under domestication in plants: 1859 and today

Charles Darwin began The Origin of Species with a chapter entitled variation under domestication, which encapsulated decades of his research on a diverse array of animal and plant domesticated species. Variation in these species compared with that in their wild relatives, their origins and their selection by humans, formed a paradigm for his theory of the evolutionary origin of species by means of natural selection. This chapter, its subsequent expansion into a two-volume monograph, together with the rediscovery of Mendel's laws, later became the foundation of scientific plant breeding. In the period up to the present, several advances in genetics (such as artificial mutation, polyploidy, adaptation and genetic markers) have amplified the discipline with concepts and questions, the seeds of which are in Darwin's original words. Today, we are witnessing a flowering of genomic research into the process of domestication itself, particularly the specific major and minor genes involved. In one striking way, our view of domestic diversity contrasts with that in Darwin's writing. He stressed the abundance of diversity and the diversifying power of artificial selection, whereas we are concerned about dwindling genetic diversity that attends modern agriculture and development. In this context, it is paramount to strive for a deeper understanding of how farmer selection including both deliberate selection and unconscious selection, might generate and retain diversity. This knowledge is essential for devising in situ conservation measures.