Testing whether reduced cognitive performance in burnout can be reversed by a motivational intervention

It has been suggested that the motivation to spend effort is decreased in burnout patients, resulting in reduced cognitive performance. A question that remains is whether this decreased motivation can be reversed by motivational interventions. We investigated this by examining the effect of a motivational intervention on cognitive performance. We presented 40 burnout patients in The Netherlands and 40 matched healthy controls with a complex attention task. As expected, in a first block of trials the performance of the burnout patients was poorer than that of healthy controls. Subsequently, we provided the participants with fake positive feedback about their performance and announced that we would financially reward those who performed best in a subsequent block of trials. Contrary to the healthy controls, the burnout patients did not improve their performance and experienced more aversion to spend effort. The study demonstrated that impaired cognitive performance in burnout patients could not be reversed by motivational interventions, which is in line with contemporary theories on burnout that state that physiological changes in burnout may underlie a relatively long-term decrease in motivation. The implication of these results is that in practice employers and therapists might need to accept that there could be a reduction in cognitive performance in employees with burnout.     

Single-machine batch delivery scheduling with an assignable common due window

This paper addresses a batch delivery single-machine scheduling problem in which jobs have an assignable common due window. Each job will incur an early (tardy) penalty if it is early (tardy) with respect to the common due window under a given schedule. There is no capacity limit on each delivery batch, and the cost per batch delivery is fixed and independent of the number of jobs in the batch. The objective is to find the optimal size and location of the window, the optimal dispatch date for each job, as well as an optimal job sequence to minimize a cost function based on earliness, tardiness, holding time, window location, window size, and batch delivery. We show that the problem can be optimally solved in O(n⁸)$O(n^8)$ time by a dynamic programming algorithm under a reasonable assumption on the relationships among the cost parameters. A computational experiment is also conducted to evaluate the performance of the proposed algorithm. We also show that some special cases of the problem can be optimally solved by lower order algorithms.     

Multiple criteria approach for solving feeder assignment and assembly sequence problem in PCB assembly

The feeder assignment and assembly sequence problem in printed circuit board (PCB) assembly with the twin objectives of minimizing magazine travel time and minimizing board travel time is presented in this study. The problem uses Dynamic Pick-and-Place (DPP) model where robot arm, board and magazine move together with different speeds based on relative coordinates between consecutive assembled points. The difficulty of the problem is that the feeder assignment depends on assembly sequence and vice versa. A new approach is proposed to improve the existing approaches. The trade-off between two strategies, assembly by area and assembly by component types, can give better results. The numerical experiments proved the efficiency of the new algorithm.     

Dynamic selection of dispatching rules for job shop scheduling

Although the academic contribution to job shop scheduling is abundant, its impact on practice has been minimal. The most preferred approach to job shop scheduling in the industry is dispatching rules. A major criticism against dispatching rules is that there is no single universal rule. The effective choice of dispatching rules depends on the scheduling criterion and existing job shop conditions. In this paper, the authors have proposed a scheduling method based on the analytic hierarchy process, that dynamically selects the most appropriate dispatching rule from several candidate rules. The selection is based on the existing job shop conditions. This method is applied to two formal job shop problems, and the results for single dispatching rules are inferior to the method proposed in this paper.     

Reverse logistics drivers: empirical evidence from a case study in an emerging economy

Academic and corporate interest in reverse logistics (RL) has risen considerably in recent years. In this context, the objective of this study was to identify the drivers that enable RL practice in an emerging economy. Firstly, international peer-reviewed publications on RL were used to develop a RL environment framework representing the main RL internal and external influences. Secondly, a case-based research was conducted in a large manufacturing company located in Southern Brazil. The results indicated that the most cited driver in the RL literature, the government and legislation, was not a main influence on the studied company. Environmental legislation is still limited in the country and struggles to provide incentives to increase materials recycling. An economic factor related to materials value recovery was also found to drive the backward flow. Finally, knowledge of the RL driving forces may support industries to better implement and manage reverse flows and to bridge the gap between existing and future solutions for reverse supply chains.     

The topology aware file distribution problem

We present theoretical results for large-file distribution on general networks of known topology (known link bandwidths and router locations). We show that the problem of distributing a file in minimum time is NP-hard in this model, and we give an O(logn) approximation algorithm, where n is the number of workstations that require the file. We also characterize our method as optimal amongst the class of “no-link-sharing” algorithms.     

Conceptualizing social-ecological drivers of change in urban forest patches

Urban Ecosystems - We introduce a conceptual model of the urban forest patch as a complex social-ecological system, incorporating cross-scale interactions. We developed this model through an...     

Population estimates of non-native rose-ringed parakeets Psittacula krameri (Scopoli, 1769) in the Durban Metropole,KwaZulu-Natal Province,South Africa

Urban Ecosystems - Rose-ringed parakeets Psittacula krameri are one of the most widely distributed urban avian invader species present in ~?35 countries with population sizes increasing....     

Infants’ abilities to respond to cues for joint attention vary by family socioeconomic status

The influence of socioeconomic variability on language and cognitive development is present from toddlerhood to adolescence and calls for investigating its earliest manifestation. Response to joint attention (RJA) abilities constitute a foundational developmental milestone that are associated with future language, cognitive, and social skills. How aspects of the family home environment shape RJA skills is relatively unknown. We investigated associations between family socioeconomic status (SES) —both parent education and family percentage of the federal poverty level (FPL)— parent depressive and anxiety symptoms and infant RJA performance in a cross-sectional sample of 173 infants aged 8–18 months and their parents from a variety of socioeconomic backgrounds. Results suggest that, correcting for age and receptive language, infants in families with greater economic resources respond to relatively less redundant, more sophisticated cues for joint attention. Although parent depressive and anxiety symptoms are negatively correlated with SES, parent depressive and anxiety symptoms were not associated with infant RJA. These findings provide evidence of SES-related differences in social cognitive development as early as infancy, calling on policymakers to address the inequities in the current socioeconomic landscape of the United States.     

OptBand: optimization-based confidence bands for functions to characterize time-to-event distributions

Classical simultaneous confidence bands for survival functions (i.e., Hall–Wellner, equal precision, and empirical likelihood bands) are derived from transformations of the asymptotic Brownian nature of the Nelson–Aalen or Kaplan–Meier estimators. Due to the properties of Brownian motion, a theoretical derivation of the highest confidence density region cannot be obtained in closed form. Instead, we provide confidence bands derived from a related optimization problem with local time processes. These bands can be applied to the one-sample problem regarding both cumulative hazard and survival functions. In addition, we present a solution to the two-sample problem for testing differences in cumulative hazard functions. The finite sample performance of the proposed method is assessed by Monte Carlo simulation studies. The proposed bands are applied to clinical trial data to assess survival times for primary biliary cirrhosis patients treated with D-penicillamine.