Risk scoring models for trade credit in small and medium enterprises

Trade credit refers to providing goods and services on a deferred payment basis. Commercial credit management is a matter of great importance for most small and medium enterprises (SMEs), since it represents a significant portion of their assets. Commercial lending involves assuming some credit risk due to exposure to default. Thus, the management of trade credit and payment delays is strongly related to the liquidation and bankruptcy of enterprises. In this paper we study the relationship between trade credit management and the level of risk in SMEs. Despite its relevance for most SMEs, this problem has not been sufficiently analyzed in the existing literature. After a brief review of existing literature, we use a large database of enterprises to analyze data and propose a multivariate decision-tree model which aims at explaining the level of risk as a function of several variables, both of financial and non-financial nature. Decision trees replace the equation in parametric regression models with a set of rules. This feature is an important aid for the decision process of risk experts, as it allows them to reduce time and then the economic cost of their decisions

SEAS: A System for SEED-Based Pathway Enrichment Analysis

Pathway enrichment analysis represents a key technique for analyzing high-throughput omic data, and it can help to link individual genes or proteins found to be differentially expressed under specific conditions to well-understood biological pathways. We present here a computational tool, SEAS, for pathway enrichment analysis over a given set of genes in a specified organism against the pathways (or subsystems) in the SEED database, a popular pathway database for bacteria. SEAS maps a given set of genes of a bacterium to pathway genes covered by SEED through gene ID and/or orthology mapping, and then calculates the statistical significance of the enrichment of each relevant SEED pathway by the mapped genes. Our evaluation of SEAS indicates that the program provides highly reliable pathway mapping results and identifies more organism-specific pathways than similar existing programs. SEAS is publicly released under the GPL license agreement and freely available at http://csbl.bmb.uga.edu/~xizeng/research/seas/

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children <18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p<0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p<0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p<0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

Genome Sequence of a Lancefield Group C Streptococcus zooepidemicus Strain Causing Epidemic Nephritis: New Information about an Old Disease

Outbreaks of disease attributable to human error or natural causes can provide unique opportunities to gain new information about host-pathogen interactions and new leads for pathogenesis research. Poststreptococcal glomerulonephritis (PSGN), a sequela of infection with pathogenic streptococci, is a common cause of preventable kidney disease worldwide. Although PSGN usually occurs after infection with group A streptococci, organisms of Lancefield group C and G also can be responsible. Despite decades of study, the molecular pathogenesis of PSGN is poorly understood. As a first step toward gaining new information about PSGN pathogenesis, we sequenced the genome of Streptococcus equi subsp. zooepidemicus strain MGCS10565, a group C organism that caused a very large and unusually severe epidemic of nephritis in Brazil. The genome is a circular chromosome of 2,024,171 bp. The genome shares extensive gene content, including many virulence factors, with genetically related group A streptococci, but unexpectedly lacks prophages. The genome contains many apparently foreign genes interspersed around the chromosome, consistent with the presence of a full array of genes required for natural competence. An inordinately large family of genes encodes secreted extracellular collagen-like proteins with multiple integrin-binding motifs. The absence of a gene related to speB rules out the long-held belief that streptococcal pyrogenic exotoxin B or antibodies reacting with it singularly cause PSGN. Many proteins previously implicated in GAS PSGN, such as streptokinase, are either highly divergent in strain MGCS10565 or are not more closely related between these species than to orthologs present in other streptococci that do not commonly cause PSGN. Our analysis provides a comparative genomics framework for renewed appraisal of molecular events underlying APSGN pathogenesis

Search for neutral MSSM Higgs bosons decaying to a pair of tau leptons in pp collisions

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Constraints on parton distribution functions and extraction of the strong coupling constant from the inclusive jet cross section in pp collisions at √s=7 TeV

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Study of hadronic event-shape variables in multijet final states in pp collisions at √s=7 TeV

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Measurement of prompt J/ψ pair production in pp collisions at √s = 7 Tev

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Searches for electroweak production of charginos, neutralinos, and sleptons decaying to leptons and W, Z, and Higgs bosons in pp collisions at 8 TeV

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Measurement of top quark–antiquark pair production in association with a W or Z boson in pp collisions at √s=8 TeV

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