PROMOTING WELL-BEING AMONG COLLEGE STUDENTS: THE EFFECTS OF A POSITIVE PSYCHOLOGY COURSE

College students report high rates of mental distress, including depression, high stress, anxiety, lack of social support, and physical ailments. College campuses use a variety of approaches to address the well-being of students. However, existing interventions have mixed results and do not always reach all students who may need mental health support. Positive psychology courses and positive psychology interventions have shown promise in promoting well-being. In this quantitative, quasi-experimental, pretest-posttest archival study, I examined the effects of a semester-long happiness and positive psychology course (COUN 195) on students’ well-being and mental health. This innovative happiness course included didactic lectures, small group and lab work, and one-on-one happiness consultations with counselors in training. Students who took COUN 195 reported higher levels of positive affect, hope, social support, and physical health as compared to the control group. The results indicate that semester long happiness courses may be useful in promoting positive mental health among college students. Conclusions and recommendations for future research are provided

Diazotrophs Show Signs of Restoration in Amazon Rain Forest Soils with Ecosystem Rehabilitation.

Biological nitrogen fixation can be an important source of nitrogen in tropical forests that serve as a major CO2 sink. Extensive deforestation of the Amazon is known to influence microbial communities and the biogeochemical cycles they mediate. However, it is unknown how diazotrophs (nitrogen-fixing microorganisms) respond to deforestation and subsequent ecosystem conversion to agriculture, as well as whether they can recover in secondary forests that are established after agriculture is abandoned. To address these knowledge gaps, we combined a spatially explicit sampling approach with high-throughput sequencing of nifH genes. The main objectives were to assess the functional distance decay relationship of the diazotrophic bacterial community in a tropical forest ecosystem and to quantify the roles of various factors that drive the observed changes in the diazotrophic community structure. We observed an increase in local diazotrophic diversity (α-diversity) with a decrease in community turnover (β-diversity), associated with a shift in diazotrophic community structure as a result of the forest-to-pasture conversion. Both diazotrophic community turnover and structure showed signs of recovery in secondary forests. Changes in the diazotrophic community were primarily driven by the change in land use rather than differences in geochemical characteristics or geographic distances. The diazotroph communities in secondary forests resembled those in primary forests, suggesting that at least partial recovery of diazotrophs is possible following agricultural abandonment.IMPORTANCE The Amazon region is a major tropical forest region that is being deforested at an alarming rate to create space for cattle ranching and agriculture. Diazotrophs (nitrogen-fixing microorganisms) play an important role in supplying soil N for plant growth in tropical forests. It is unknown how diazotrophs respond to deforestation and whether they can recover in secondary forests that establish after agriculture is abandoned. Using high-throughput sequencing of nifH genes, we characterized the response of diazotrophs' β-diversity and identified major drivers of changes in diazotrophs from forest-to-pasture and pasture-to-secondary-forest conversions. Studying the impact of land use change on diazotrophs is important for a better understanding of the impact of deforestation on tropical forest ecosystem functioning, and our results on the potential recovery of diazotrophs in secondary forests imply the possible restoration of ecosystem functions in secondary forests

Parton Distributions for Event Generators

In this paper, conventional Global QCD analysis is generalized to produce parton distributions optimized for use with event generators at the LHC. This optimization is accomplished by combining the constraints due to existing hard-scattering experimental data with those from anticipated cross sections for key representative SM processes at LHC (by the best available theory) as joint input to the global analyses. The PDFs obtained in these new type of global analyses using matrix elements calculated in any given order will be best suited to work with event generators of that order, for predictions at the LHC. This is most useful for LO event generators at present. Results obtained from a few candidate PDF sets (labeled as CT09MCS, CT09MC1 and CT09MC2) for LO event generators produced in this way are compared with those from other approaches.Comment: 35 pages, 19 figures, and 4 table

A novel image segmentation algorithm with applications on confocal microscopy analysis

Motivation: Developing cells change their gene expression profiles dynamically upon induction by proper triggers, typically diffusible morphogens that are spatially distributed (1). These changes impact cell cycle and apoptosis regulators differentially, eventually determining the final structure and size of the mature organs (2). A quantitative model that links gene regulation and tissue growth must be provided with precise experimental data at cell resolution level in order to proceed to its validation, which in some cases is essential for model screening (i.e. reverse ingineering methods). Image analysis from laser confocal microscopy (LCM) has already been used to address modelling problems in developmental tissues such as these (3). However current methods for LCM segmentation rely upon watershed algorithms that show variable efficiency, relatively high parametrization and oversegmentation problems that are critical on very aggregated objects (4). Here we present a different segmentation method based on the maximum complementary n-ball set (MCnB set) concept. The segmentation algorithm takes a full MCnB set as a starting graph representation of the whole stack, which is later contracted using a parallel implementation approach.Results: We assayed the performance by segmenting a randomly generated set of spheres with different resolutions, signal aggregation levels and densities, and compared to the results delivered by a common segmentation free software, (i.e. Vaa3D), which is based on watersheds (5). We also applied this comparison on DAPI stained samples from Drosophila eye-antenna imaginal discs. The results indicate that the mean square displacement of detected spheres centroids is higher in the 3D watershed implementation results than when our method is applied. The same results are obtained when the number of sets or their size are checked instead.Conclusions: The results indicate that our method is adequate enough for image segmentation in three dimensions. It makes no assumptions on what the shape or signal features of the objects are, and does not require any calibration since it can proceed with no specific user parameters. Moreover it beats at least one segmentation method that has already been set up for counting and segmentation. Since the shape of the voxel aggregates is not critical, we sugget that further implementations could be potentially applied in higher dimension samples with interesting applications in developmental biology (i.e. 4D 'movies' segmentation). However one major drawback is that at least one operation runs with a O(n^2) time complexity, which is time (and memory) consuming for very big images

Production Performance of Indigenous Chicken under Semi Intensive Management Conditions in Central Tanzania

A study to evaluate four indigenous chicken – namely: Horasi, Kuchi, Naked neck and Frizzled in order to obtain grand-parent and parent stocks was carried out at Tanzania Livestock Research Institute, Mpwapwa district of Dodoma, Tanzania. The perfomance of the ecotypes were compared so as to come out with the best indigenous chicken among the four. A total of 548 indigenous chicken including Horasi (162), Kuchi (253), Naked neck (81) and Frizzled (52) were used in the study. All chicken were treated equally in terms of management under semi intensive system. Data were collected on body weight, external egg characteristics, day old chick weight, body weight gain, weight at 4, 8, 12, 16, 20, 24 weeks of age for each ecotype. Age at first egg and egg number were also determined. The collected data was analysed using General Linear Model of SAS (2006). The results showed that there were significant differences in mature body and egg weight between the ecotypes. The mature body weight and egg weight respectively were 2075g, 2070g, 1792g , 1622g and 44.73g, 45.94g, 38.28g, 38.08g for Horasi, Kuchi, Naked neck and Frizzled respectively. Day old chick weight were 34.26g, 36.26g, 31.99g and 29.02g for Horasi, Kuchi, Naked neck and Frizzled respectively. Average growth rate per day in grams for Horasi and Kuchi was 3.67g and 3.96g per day from day old chick to week 4 and 6.83g and 8.25g per day from week 5 to week 8, respectively. Average egg numbers per clutch for Horasi and Naked neck were 16 and 18 eggs respectively. Average body weight at week 24 for naked neck and Horasi (F1) were 1427g and 1572.8g respectively. Average ages at first egg for Horasi and Naked neck (F1) were found to be 15 weeks and 16 weeks, respectively. The study reveals that, Horasi and Naked neck ecotypes under semi intensive system perform better than Frizzed. It was conclude that, Horasi and Naked neck can be used at farm level for egg production and Kuchi could be used to improve meat production on other indigenous chicken hence increase income of smallholder farmers

Solution to the Ward Identities for Superamplitudes

Supersymmetry and R-symmetry Ward identities relate on-shell amplitudes in a supersymmetric field theory. We solve these Ward identities for (Next-to)^K MHV amplitudes of the maximally supersymmetric N=4 and N=8 theories. The resulting superamplitude is written in a new, manifestly supersymmetric and R-invariant form: it is expressed as a sum of very simple SUSY and SU(N)_R-invariant Grassmann polynomials, each multiplied by a "basis amplitude". For (Next-to)^K MHV n-point superamplitudes the number of basis amplitudes is equal to the dimension of the irreducible representation of SU(n-4) corresponding to the rectangular Young diagram with N columns and K rows. The linearly independent amplitudes in this algebraic basis may still be functionally related by permutation of momenta. We show how cyclic and reflection symmetries can be used to obtain a smaller functional basis of color-ordered single-trace amplitudes in N=4 gauge theory. We also analyze the more significant reduction that occurs in N=8 supergravity because gravity amplitudes are not ordered. All results are valid at both tree and loop level.Comment: 29 pages, published versio

Molecular characterisation of the caprine (Capra hircus) lymphocyte function-associated antigen-1 alpha subunit-encoding cDNA

BACKGROUND: Lymphocyte function-associated antigen-1 (LFA-1, CD11a/CD18, alpha L beta 2) is required for many cellular adhesive interactions during the immune response. RESULTS: The Capra hircus CD11a-encoding cDNA was sequenced and compared with its human, murine, rat, bovine and ovine counterparts. Despite some focal differences, it shares all the main characteristics of its known mammalian homologues. CONCLUSION: Therefore, along with the caprine CD18-encoding cDNA, which has been available for a few months, the sequence data revealed here will allow the Capra hircus LFA-1 expression in vitro as a tool to explore the specificities of inflammation in the caprine species

Holographic duals of SQCD models in low dimensions

We obtain gravity duals to supersymmetric gauge theories in two and three spacetime dimensions with unquenched flavor. The supergravity solutions are generated by a set of color branes wrapping a compact cycle in a Calabi-Yau threefold, together with another set of flavor branes extended along the directions orthogonal to the cycle wrapped by the color branes. We construct supergravity backgrounds which include the backreaction induced by a smeared set of flavor branes, which act as delocalized dynamical sources of the different supergravity fields.Comment: 42 pages, 5 figures;v2: typos correcte

The wild boar (Sus scrofa) Lymphocyte function-associated antigen-1 (CD11a/CD18) receptor: cDNA sequencing, structure analysis and comparison with homologues

BACKGROUND: The most predominant beta2-integrin lymphocyte function-associated antigen-1 (LFA-1, CD11a/CD18, alphaLbeta2), expressed on all leukocytes, is essential for many adhesive functions of the immune system. Interestingly, RTX toxin-producing bacteria specifically target this leukocyte beta2-integrin which exacerbates lesions and disease development. RESULTS: This study reports the sequencing of the wild boar beta2-integrin CD11a and CD18 cDNAs. Predicted CD11a and CD18 subunits share all the main structural characteristics of their mammalian homologues, with a larger interspecies conservation for the CD18 than the CD11a. Besides these strong overall similarities, wild boar and domestic pig LFA-1 differ by 2 (CD18) and 1 or 3 (CD11a) substitutions, of which one is located in the crucial I-domain (CD11a, E168D). CONCLUSION: As most wild boars are seropositive to the RTX toxin-producing bacterium Actinobacillus pleuropneumoniae and because they have sustained continuous natural selection, future studies addressing the functional impact of these polymorphisms could bring interesting new information on the physiopathology of Actinobacillus pleuropneumoniae-associated pneumonia in domestic pigs

Comparison of classification methods for detecting associations between SNPs and chick mortality

Multi-category classification methods were used to detect SNP-mortality associations in broilers. The objective was to select a subset of whole genome SNPs associated with chick mortality. This was done by categorizing mortality rates and using a filter-wrapper feature selection procedure in each of the classification methods evaluated. Different numbers of categories (2, 3, 4, 5 and 10) and three classification algorithms (naïve Bayes classifiers, Bayesian networks and neural networks) were compared, using early and late chick mortality rates in low and high hygiene environments. Evaluation of SNPs selected by each classification method was done by predicted residual sum of squares and a significance test-related metric. A naïve Bayes classifier, coupled with discretization into two or three categories generated the SNP subset with greatest predictive ability. Further, an alternative categorization scheme, which used only two extreme portions of the empirical distribution of mortality rates, was considered. This scheme selected SNPs with greater predictive ability than those chosen by the methods described previously. Use of extreme samples seems to enhance the ability of feature selection procedures to select influential SNPs in genetic association studies