Diversity of anura amphibians in an anthropic lake in the state of Paraíba, Brazil: distribution and temporal variation

The Caatinga is highly heterogeneous, many species being found in their regions. Much of anurofauna this area is commonly found in many open environments. In the present study both the diversity and the temporal occurrence of frogs were determined to Bela Vista Lagoon, located in the municipality of Cuité, Paraíba. 4 areas for sampling were marked, these being covered slowly by hiking. The naturalistic observations were conducted from May 2012 until April 2013 Methods of visual and auditory search were used to simultaneously capture and frequency of species. 6 frog species belonging to 4 genera were found distributed in three families: Bufonidae (2 species), Hylidae (2 species) and Leptodactylidae (2 species). Site 1 showed a wealth of three species, the other areas had a wealth equivalent of 5 species each. The anurofauna recorded high occupancy presented to water bodies and low associations zones altered by man. Nonparametric estimators, calculated for the 36 surveys for the pond Bela Vista, not reached its asymptote, but the Bootstrap model showed a tendency toward stabilization. Among the four sampled areas, Area 2 was the one with the highest diversity, areas 3 and 4 presented the lowest diversity, this fact being related to high dominance of species Rinnella jimi. Regarding the temporal distribution, amphibians showed up influenced by temperature and rainfall record for the region.

An Empirical Study on the Impact of Team Entrepreneurship Passion on the Tobacco Products Entrepreneurial Performance of New Ventures: Mediating Effect Test Based on Bootstrap Model

In this paper, following the research logic of Emotion/Feature-Behavior-Result, the focus is put on how the entrepreneurial passion of interactive-oriented teams in the tobacco products entrepreneurial can improve corporate performance by affecting entrepreneurial learning. The multiple regression method is used to test 238 valid questionnaires of new ventures, and the Bootstrap model is used to verify the mediating effect of entrepreneurial learning according to the multiple mediating effect analysis method proposed by scholars. The results show that: (1) The entrepreneurial passion of the team will affect the tobacco products entrepreneurial process of the new venture team, and the team with high passion atmosphere is more likely to improve the performance of the new enterprise. As a strong positive emotion experienced by the entrepreneurial team in their entrepreneurial activities, can not only influence the entrepreneurial team to identify with their entrepreneurial identity sharing, but also promote the growth of enterprises. (2) There is a significant mediating effect of exploratory learning and exploitative learning in the process of the impact of team entrepreneurial passion on the performance of the innovator but no significant difference in the mediating effects of the two. Entrepreneurial passion drives the tobacco products entrepreneurs to make a strong emotional commitment to the new innovator and invest much effort, and entrepreneurial learning is an effective way to help solve the problem of the new innovator. The research results can help to further interpret the mechanism of the role of the tobacco products entrepreneurial enthusiasm on the performance of innovators, expand the mediating factors between the two from psychological to behavioral factors, enrich the research on the performance promotion mechanism of new innovators, promote the organization learning behavior combined with entrepreneurship research, and also provide references and suggestions for the tobacco products entrepreneurs to improve their entrepreneurial performance through learning behaviors.

Critical exponents and transport properties near the QCD critical endpoint from the statistical bootstrap model

We present an estimate of the behavior of the shear and bulk viscosity coefficients when the QCD critical point is approached from the hadronic side, describing hadronic matter within the statistical bootstrap model of strong interactions. The bootstrap model shows critical behavior near the quark-hadron transition temperature if the parameter characterizing the degeneracy of Hagedorn states is properly chosen. We calculate the critical exponents and amplitudes of relevant thermodynamic quantities near the QCD critical point and combine them with an Ansatz for the shear and bulk viscosity coefficients to derive the behavior of these coefficients near the critical point. The shear viscosity to entropy density ratio is found to decrease when the temperature is increased, and to approach the Kovtun–Son–Starinets bound $$1/(4\pi )$$ 1 / ( 4 π ) faster near the critical point, while the bulk viscosity coefficient is found to rise very rapidly.

Multistage allocation problem for Mexican pension funds

The problem of multistage allocation is solved using the Target Date Fund (TDF) strategy subject to a set of restrictions which model the latest regulatory framework of the Mexican pension system. The investment trajectory or glide-path for a representative set of 14 assets of heterogeneous characteristics is studied during a 161 quarters long horizon. The expected returns are estimated by the GARCH(1,1), EGARCH(1,1), GJR-GARCH(1,1) models, and a stationary block bootstrap model is used as a benchmark for comparison. A fixed historical covariance matrix and a multi-period estimation of DCC-GARCH(1,1) are also considered as inputs of the objective function. Forecasts are evaluated through their asymmetric dependencies as quantified by the transfer entropy measure. In general, we find very similar glide-paths so that the overall structure of the investment is maintained and does not rely on the particular forecasting model. However, the GARCH(1,1) under a fixed historical covariance matrix exhibits the highest Sharpe ratio and in this sense represents the best trade-off between wealth and risk. As expected, the initial stages of the obtained glide-paths are initially dominated by risky assets and gradually transition into bonds towards the end oof the trajectory. Overall, the methodology proposed here is computationally efficient and displays the desired properties of a TDF strategy in realistic settings.

Projecting hospital resource utilization during a surge using parametric bootstrapping

During the initial wave of the COVID-19 pandemic in the United States, hospitals took drastic action to ensure sufficient capacity, including canceling or postponing elective procedures, expanding the number of available intensive care beds and ventilators, and creating regional overflow hospital capacity. However, in most locations the actual number of patients did not reach the projected surge leaving available, unused hospital capacity. As a result, patients may have delayed needed care and hospitals lost substantial revenue. These initial recommendations were made based on observations and worst-case epidemiological projections, which generally assume a fixed proportion of COVID-19 patients will require hospitalization and advanced resources. This assumption has led to an overestimate of resource demand as clinical protocols improve and testing becomes more widely available throughout the course of the pandemic. Here, we present a parametric bootstrap model for forecasting the resource demands of incoming patients in the near term, and apply it to the current pandemic. We validate our approach using observed cases at UCLA Health and simulate the effect of elective procedure cancellation against worst-case pandemic scenarios. Using our approach, we show that it is unnecessary to cancel elective procedures unless the actual capacity of COVID-19 patients approaches the hospital maximum capacity. Instead, we propose a strategy of balancing the resource demands of elective procedures against projected patients by revisiting the projections regularly to maintain operating efficiency. This strategy has been in place at UCLA Health since mid-April.

Opioid antagonists are associated with a reduction in the symptoms of schizophrenia: a meta-analysis of controlled trials

Current treatments for the symptoms of schizophrenia are only effective for positive symptoms in some individuals, and have considerable side effects that impact compliance. Thus, there is a need to investigate the efficacy of other compounds in treating both positive and negative symptoms. We conducted a meta-analysis of English language placebo-controlled clinical trials of naloxone, naltrexone, nalmefene, and buprenorphine in patients with schizophrenia to determine whether opioid antagonists have therapeutic efficacy on positive, negative, total, or general symptoms. We searched online databases Ovid Medline and PsychINFO, PubMed, EMBASE, Scopus, Cochrane library/CENTRAL, Web of Science, and Google Scholar from 1970 through February 2019. Following PRISMA guidelines, Hedges g was calculated for each study. Primary study outcomes were the within-subject change on any symptom assessment scale for positive, negative, total, or general symptoms of schizophrenia between active drug and placebo conditions. Thirty studies were included with 434 total patients. We found a significant effect of all drugs on all scales combined with both a standard random effects model: (g = 0.26; P = 0.02; k = 22; CI = 0.03–0.49) and a more inclusive bootstrap model: (g = 0.26; P = 0.0002; k = 30; CI = 0.11–0.51) and a significant effect on total scales with the bootstrap model (g = 0.25288; P = 0.015; k = 19; CI = 0.04–0.35). We also observed a significant effect of all drugs on all positive scales combined with both the random effects (g = 0.33; P = 0.015; k = 17; CI = 0.07–0.60) and bootstrap models (g = 0.32; P < 0.0001; k = 21; CI = 0.13–1.38). This evidence provides support for further testing in randomized clinical trials of a new class of non-D2-receptor drugs, based on opioid mechanisms, for the treatment of positive and negative symptoms of schizophrenia.