Structural Equation Model on Work Engagement among Employees of Large Retail Enterprises in Region Xii

 The ultimate goal of this research undertaking was to identify the best fit model involving the following exogenous variables: transformational leadership, motivation, and human resource management practices to endogenous variable – work engagement. A survey questionnaire was issued to the various large retail employees in Region XII, Philippines with 425 respondents for the purpose of data collection. The research method used in the analysis was descriptive — correlation design was used to find the best fit model through structural equation modeling. The results revealed that the model presented positive relationship between transformational leadership, motivation and human resource management practices and work engagement. Nevertheless, the three established exogenous variables of transformational leadership, motivation, and human resource management practices emerged as the primary predictors of work engagement, taking into account their observed variables as depicted in the study's final and best fit model

Chimera states in hybrid coupled neuron populations

Here we study the emergence of chimera states, a recently reported phenomenon referring to the coexistence of synchronized and unsynchronized dynamical units, in a population of Morris-Lecar neurons which are coupled by both electrical and chemical synapses, constituting a hybrid synaptic architecture, as in actual brain connectivity. This scheme consists of a nonlocal network where the nearest neighbor neurons are coupled by electrical synapses, while the synapses from more distant neurons are of the chemical type. We demonstrate that peculiar dynamical behaviors, including chimera state and traveling wave, exist in such a hybrid coupled neural system, and analyze how the relative abundance of chemical and electrical synapses affects the features of chimera and different synchrony states (i.e. incoherent, traveling wave and coherent) and the regions in the space of relevant parameters for their emergence. Additionally, we show that, when the relative population of chemical synapses increases further, a new intriguing chaotic dynamical behavior appears above the region for chimera states. This is characterized by the coexistence of two distinct synchronized states with different amplitude, and an unsynchronized state, that we denote as a chaotic amplitude chimera. We also discuss about the computational implications of such state. (c) 2020 Elsevier Ltd. All rights reserved.MU acknowledges Bulent Ecevit University Research Foundation, Turkey under Project No. BAP2018-39971044-01. JJT acknowledges the Spanish Ministry for Science and Technology and the "Agencia Espanola de Investigacion, Spain'' (AEI) for financial support under grant FIS2017-84256-P (FEDER funds). AC acknowledges financial support from the Scientific and Technological Research Council of Turkey (TUBITAK) BIDEB-2214/A International Research Fellowship Program, and the hospitality of the Institute Carlos I for Theoretical and Computational Physics at University of Granada

Vibrational resonance in a scale-free network with different coupling schemes

We investigate the phenomenon of vibrational resonance (VR) in neural populations, whereby weak low-frequency signals below the excitability threshold can be detected with the help of additional high-frequency driving. The considered dynamical elements consist of excitable FitzHugh–Nagumo neurons connected by electrical gap junctions and chemical synapses. The VR performance of these populations is studied in unweighted and weighted scale-free networks. We find that although the characteristic network features – coupling strength and average degree – do not dramatically affect the signal detection quality in unweighted electrically coupled neural populations, they have a strong influence on the required energy level of the high-frequency driving force. On the other hand, we observe that unweighted chemically coupled populations exhibit the opposite behavior, and the VR performance is significantly affected by these network features whereas the required energy remains on a comparable level. Furthermore, we show that the observed VR performance for unweighted networks can be either enhanced or worsened by degree-dependent coupling weights depending on the amount of heterogeneity

Vibrational resonance in a scale-free network with different coupling schemes

We investigate the phenomenon of vibrational resonance (VR) in neural populations, whereby weak low-frequency signals below the excitability threshold can be detected with the help of additional high-frequency driving. The considered dynamical elements consist of excitable FitzHugh–Nagumo neurons connected by electrical gap junctions and chemical synapses. The VR performance of these populations is studied in unweighted and weighted scale-free networks. We find that although the characteristic network features – coupling strength and average degree – do not dramatically affect the signal detection quality in unweighted electrically coupled neural populations, they have a strong influence on the required energy level of the high-frequency driving force. On the other hand, we observe that unweighted chemically coupled populations exhibit the opposite behavior, and the VR performance is significantly affected by these network features whereas the required energy remains on a comparable level. Furthermore, we show that the observed VR performance for unweighted networks can be either enhanced or worsened by degree-dependent coupling weights depending on the amount of heterogeneity

Prospective observational cohort study on grading the severity of postoperative complications in global surgery research

Background The Clavien–Dindo classification is perhaps the most widely used approach for reporting postoperative complications in clinical trials. This system classifies complication severity by the treatment provided. However, it is unclear whether the Clavien–Dindo system can be used internationally in studies across differing healthcare systems in high- (HICs) and low- and middle-income countries (LMICs). Methods This was a secondary analysis of the International Surgical Outcomes Study (ISOS), a prospective observational cohort study of elective surgery in adults. Data collection occurred over a 7-day period. Severity of complications was graded using Clavien–Dindo and the simpler ISOS grading (mild, moderate or severe, based on guided investigator judgement). Severity grading was compared using the intraclass correlation coefficient (ICC). Data are presented as frequencies and ICC values (with 95 per cent c.i.). The analysis was stratified by income status of the country, comparing HICs with LMICs. Results A total of 44 814 patients were recruited from 474 hospitals in 27 countries (19 HICs and 8 LMICs). Some 7508 patients (16·8 per cent) experienced at least one postoperative complication, equivalent to 11 664 complications in total. Using the ISOS classification, 5504 of 11 664 complications (47·2 per cent) were graded as mild, 4244 (36·4 per cent) as moderate and 1916 (16·4 per cent) as severe. Using Clavien–Dindo, 6781 of 11 664 complications (58·1 per cent) were graded as I or II, 1740 (14·9 per cent) as III, 2408 (20·6 per cent) as IV and 735 (6·3 per cent) as V. Agreement between classification systems was poor overall (ICC 0·41, 95 per cent c.i. 0·20 to 0·55), and in LMICs (ICC 0·23, 0·05 to 0·38) and HICs (ICC 0·46, 0·25 to 0·59). Conclusion Caution is recommended when using a treatment approach to grade complications in global surgery studies, as this may introduce bias unintentionally