Search for low-scale gravity signatures in multi-jet final states with the ATLAS detector at s√ = 8 TeV

We search for evidence of physics beyond the Standard Model in the production of final states with multiple high transverse momentum jets, using 20.3 fb−1 of proton-proton collision data recorded by the ATLAS detector at s√ = 8 TeV. No excess of events beyond Standard Model expectations is observed, and upper limits on the visible cross-section for non-Standard Model production of multi-jet final states are set. Using a wide variety of models for black hole and string ball production and decay, the limit on the cross-section times acceptance is as low as 0.16 fb at the 95% CL for a minimum scalar sum of jet transverse momentum in the event of about 4.3 TeV. Using models for black hole and string ball production and decay, exclusion contours are determined as a function of the production mass threshold and the gravity scale. These limits can be interpreted in terms of lower-mass limits on black hole and string ball production that range from 4.6 to 6.2 TeV.

Measuring university-to-work success: development of a new scale

Purpose – The purpose of this paper is to develop a subjective multidimensional measure of early career success during university-to-work transition. Design/methodology/approach – The construct of university-to-work success (UWS) was defined in terms of intrinsic and extrinsic career outcomes, and a three-stage study was conducted to create a new scale. Findings – A preliminary set of items was developed and tested by judges. Results showed the items had good content validity. Factor analyses indicated a four-factor structure and a second-order model with subscales to assess: career insertion and satisfaction, confidence in career future, income and financial independence, and adaptation to work. Third, the authors sought to confirm the hypothesized model examining the comparative fit of the scale and two alternative models. Results showed that fits for both the first- and second-order models were acceptable. Research limitations/implications – The proposed model has sound psychometric qualities, although the validated version of the scale was not able to incorporate all constructs envisaged by the initial theoretical model. Results indicated some direction for further refinement. Practical implications – The scale could be used as a tool for self-assessment or as an outcome measure to assess the efficacy of university-to-work programs in applied settings. Originality/value – This study provides a useful single measure to assess early career success during the university-to-work transition, and might facilitate testing of causal models which could help identify factors relevant for successful transition.

Three-dimensional technology facilitates surgical performance of novice laparoscopy surgeons: a quantitative assessment on a porcine kidney model

Objective To determine whether the use of 3-dimensional (3D) imaging translates into a better surgical performance of naïve urologic laparoscopic surgeons during pyeloplasty (PY) and partial nephrectomy (PN) procedures. Materials and Methods Eighteen surgeons without any previous laparoscopic experience were randomly assigned to perform PY and PN in a porcine model using initially 2-dimensional (2D) and 3D laparoscopy. A surgical performance score was rated by an "expert" tutor through a modified 5-item global rating scale contemplating operative field view, bimanual dexterity, efficiency, tissue handling, and autonomy. Overall surgical time, complications, subjective perception of participating surgeons, and inconveniences related to the 3D vision were recorded. Results No difference in terms if operative time was found between 2D or 3D laparoscopy for both the PY (P =.51) and the PN (P =.28) procedures. A better rate in terms of surgical performance score was noted by the tutors when the study participants were using 3D vs 2D, for both PY (3.6 [0.8] vs 3.0 [0.4]; P =.034) and PN (3.6 [0.51] vs 3.15 [0.63]; P =.001). No complications occurred in any of the procedures. Most (77.2%) of the participating na??ve laparoscopic surgeons had the perception that 3D laparoscopy was overall easier than 2D. Headache (18.1%), nausea (18.1%), and visual disturbance (18.1%) were the most common issues reported by the surgeons during 3D procedures. Conclusion Despite the absence of translation in a shorter operative time, the use of 3D technology seems to facilitate the surgical performance of naive surgeons during laparoscopic kidney procedures on a porcine model.

Development of computational and experimental methods for biomass composition and evaluation of its impact in genome-scale models prediction

The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.

Harmonization guidelines for HLA-peptide multimer assays derived from results of a large scale international proficiency panel of the Cancer Vaccine Consortium.

PURPOSE: The Cancer Vaccine Consortium of the Cancer Research Institute (CVC-CRI) conducted a multicenter HLA-peptide multimer proficiency panel (MPP) with a group of 27 laboratories to assess the performance of the assay. EXPERIMENTAL DESIGN: Participants used commercially available HLA-peptide multimers and a well characterized common source of peripheral blood mononuclear cells (PBMC). The frequency of CD8+ T cells specific for two HLA-A2-restricted model antigens was measured by flow cytometry. The panel design allowed for participants to use their preferred staining reagents and locally established protocols for both cell labeling, data acquisition and analysis. RESULTS: We observed significant differences in both the performance characteristics of the assay and the reported frequencies of specific T cells across laboratories. These results emphasize the need to identify the critical variables important for the observed variability to allow for harmonization of the technique across institutions. CONCLUSIONS: Three key recommendations emerged that would likely reduce assay variability and thus move toward harmonizing of this assay. (1) Use of more than two colors for the staining (2) collect at least 100,000 CD8 T cells, and (3) use of a background control sample to appropriately set the analytical gates. We also provide more insight into the limitations of the assay and identified additional protocol steps that potentially impact the quality of data generated and therefore should serve as primary targets for systematic analysis in future panels. Finally, we propose initial guidelines for harmonizing assay performance which include the introduction of standard operating protocols to allow for adequate training of technical staff and auditing of test analysis procedures.

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Can a Lucas model with habit generate realistic conditional volatility in exchange rate returns?

In this paper, we attempt to give a theoretical underpinning to the well established empirical stylized fact that asset returns in general and the spot FOREX returns in particular display predictable volatility characteristics. Adopting Moore and Roche s habit persistence version of Lucas model we nd that both the innovation in the spot FOREX return and the FOREX return itself follow "ARCH" style processes. Using the impulse response functions (IRFs) we show that the baseline simulated FOREX series has "ARCH" properties in the quarterly frequency that match well the "ARCH" properties of the empirical monthly estimations in that when we scale the x-axis to synchronize the monthly and quarterly responses we find similar impulse responses to one unit shock in variance. The IRFs for the ARCH processes we estimate "look the same" with an approximately monotonic decreasing fashion. The Lucas two-country monetary model with habit can generate realistic conditional volatility in spot FOREX return.

Institutions and the Scale Effect

Growth models which imply a scale effect are commonly refuted on the basis of empirical evidence. A focus on the extent of the market as opposed to the scale of the country has led recent studies to reconsider the role that country scale plays when conditioning on other factors. We consider a variant of a simple learning by doing model to account for the potential role for institutions in determining the strength – and direction – of the scale effect. Using cross-country data, we find a significant interaction between property rights institutions and the effect of scale on long-run growth: In countries with poor property rights institutions, scale is positively related with income per capita; where property rights institutions are good, higher scale is associated with lower per capita ncomes. We find no evidence of such role for contracting institutions.

A general model to predict individual exposure to solar UV by using ambient irradiance data

Excessive exposure to solar ultraviolet (UV) is the main cause of skin cancer. Specific prevention should be further developed to target overexposed or highly vulnerable populations. A better characterisation of anatomical UV exposure patterns is however needed for specific prevention. To develop a regression model for predicting the UV exposure ratio (ER, ratio between the anatomical dose and the corresponding ground level dose) for each body site without requiring individual measurements. A 3D numeric model (SimUVEx) was used to compute ER for various body sites and postures. A multiple fractional polynomial regression analysis was performed to identify predictors of ER. The regression model used simulation data and its performance was tested on an independent data set. Two input variables were sufficient to explain ER: the cosine of the maximal daily solar zenith angle and the fraction of the sky visible from the body site. The regression model was in good agreement with the simulated data ER (R(2)=0.988). Relative errors up to +20% and -10% were found in daily doses predictions, whereas an average relative error of only 2.4% (-0.03% to 5.4%) was found in yearly dose predictions. The regression model predicts accurately ER and UV doses on the basis of readily available data such as global UV erythemal irradiance measured at ground surface stations or inferred from satellite information. It renders the development of exposure data on a wide temporal and geographical scale possible and opens broad perspectives for epidemiological studies and skin cancer prevention.

Debris flow susceptibility mapping at a regional scale

Debris flow susceptibility mapping at a regional scale has been the subject of various studies. The complexity of the phenomenon and the variability of local controlling factors limit the use of process-based models for a first assessment. GISbased approaches associating an automatic detection of the source areas and a simple assessment of the debris flow spreading may provide a substantial basis for a preliminary susceptibility assessment at the regional scale. The use of a digital elevation model, with a 10 m resolution, for the Canton de Vaud territory (Switzerland), a lithological map and a land use map, has allowed automatic identification of the potential source areas. The spreading estimates are based on basic probabilistic and energy calculations that allow to define the maximal runout distance of a debris flow.

Validation of the German version of the Career Adapt-Abilities Scale and its relation to orientations to happiness and work stress

Career adapt-ability has recently gained momentum as a psychosocial construct that not only has much to offer the field of career development, but also contributes to positive coping, adjustment and self-regulation through the four dimensions of concern, control, curiosity and confidence. The positive psychology movement, with concepts such as the orientations to happiness, explores the factors that contribute to human flourishing and optimum functioning. This research has two main contributions; 1) to validate a German version of the Career Adapt-Abilities Scale (CAAS), and 2) to extend the contribution of adapt-abilities to the field of work stress and explore its mediating capacity in the relation between orientations to happiness and work stress. We used a representative sample of the German-speaking Swiss working population including 1204 participants (49.8% women), aged between 26 and 56 (Mage = 42.04). Results indicated that the German version of the CAAS is valid, with overall high levels of model fit suggesting that the conceptual structure of career adapt-ability replicates well in this cultural context. Adapt-abilities showed a negative relationship to work stress, and a positive one with orientations to happiness. The engagement and pleasure scales of orientations to happiness also correlated negatively with work stress. Moreover, career adapt-ability mediates the relationship between orientations to happiness and work stress. In depth analysis of the mediating effect revealed that control is the only significant mediator. Thus control may be acting as a mechanism through which individuals attain their desired life at work subsequently contributing to reduced stress levels.

Revisiting the size-R&D productivity relation: introducing the mediating role of decision-making style on the scale and quality of innovative output

We develop a mediation model in which firm size is proposed to affect the scale and quality of innovative output through the adoption of different decision styles during the R&D process. The aim of this study is to understand how the internal changes that firms undergo as they evolve from small to larger organizations affect R&D productivity. In so doing, we illuminate the underlying theoretical mechanism affecting two different dimensions of R&D productivity, namely the scale and quality of innovative output which have not received much attention in previous literature. Using longitudinal data of Spanish manufacturing firms we explore the validity of this mediation model. Our results show that as firms evolve in size, they increasingly emphasize analytical decision making, and consequently, large-sized firms aim for higher-quality innovations while small firms aim for a larger scale of innovative output.

Ascertaining late-life depressive symptoms in Europe: an evaluation of the survey version of the EURO-D scale in 10 nations. The SHARE project.

The reported prevalence of late-life depressive symptoms varies widely between studies, a finding that might be attributed to cultural as well as methodological factors. The EURO-D scale was developed to allow valid comparison of prevalence and risk associations between European countries. This study used Confirmatory Factor Analysis (CFA) and Rasch models to assess whether the goal of measurement invariance had been achieved; using EURO-D scale data collected in 10 European countries as part of the Survey of Health, Ageing and Retirement in Europe (SHARE) (n = 22,777). The results suggested a two-factor solution (Affective Suffering and Motivation) after Principal Component Analysis (PCA) in 9 of the 10 countries. With CFA, in all countries, the two-factor solution had better overall goodness-of-fit than the one-factor solution. However, only the Affective Suffering subscale was equivalent across countries, while the Motivation subscale was not. The Rasch model indicated that the EURO-D was a hierarchical scale. While the calibration pattern was similar across countries, between countries agreement in item calibrations was stronger for the items loading on the affective suffering than the motivation factor. In conclusion, there is evidence to support the EURO-D as either a uni-dimensional or bi-dimensional scale measure of depressive symptoms in late-life across European countries. The Affective Suffering sub-component had more robust cross-cultural validity than the Motivation sub-component.

Orthogonal higher order structure and confirmatory factor analysis of the French Wechsler Adult Intelligence Scale (WAIS-III).

According to the most widely accepted Cattell-Horn-Carroll (CHC) model of intelligence measurement, each subtest score of the Wechsler Intelligence Scale for Adults (3rd ed.; WAIS-III) should reflect both 1st- and 2nd-order factors (i.e., 4 or 5 broad abilities and 1 general factor). To disentangle the contribution of each factor, we applied a Schmid-Leiman orthogonalization transformation (SLT) to the standardization data published in the French technical manual for the WAIS-III. Results showed that the general factor accounted for 63% of the common variance and that the specific contributions of the 1st-order factors were weak (4.7%-15.9%). We also addressed this issue by using confirmatory factor analysis. Results indicated that the bifactor model (with 1st-order group and general factors) better fit the data than did the traditional higher order structure. Models based on the CHC framework were also tested. Results indicated that a higher order CHC model showed a better fit than did the classical 4-factor model; however, the WAIS bifactor structure was the most adequate. We recommend that users do not discount the Full Scale IQ when interpreting the index scores of the WAIS-III because the general factor accounts for the bulk of the common variance in the French WAIS-III. The 4 index scores cannot be considered to reflect only broad ability because they include a strong contribution of the general factor.