Guest Editorial Production Planning and Control in other Industries

This paper provides an excursion into various scheduling problems arising in the manufacturing environment and possible approaches that can be taken to solve them. It reviews the research in production scheduling from the perspective of designing and operating a production system and examines the research strategies adopted to find the solution of the practical problems. This review is in the form of the paradigms that evolved during the twentieth century and shows the transition in theory and practice of each paradigm. It covers the fundamental frameworks of scheduling theory, outlining various approaches that can be taken to solve (optimally or approximately) such problems, and the difficulties arising in their practical use. Subsequently, an iterative scheduling process is suggested as an extension of existing paradigms to solve practical production scheduling problems and to bridge the gap between theory and practice in production scheduling and control.     

Demographic differences in response rates for PHQ9 in a university student population

Objective: To examine differences in complete response rates for depression screening questions based on demographic characteristics. Methods: Cross-sectional study examining associations between demographic characteristics and completely responding depression-screening questions. Participants: “Healthy Minds Study” data, collected in a public University in February 2016, where 7,326 students participated. Results: women (AOR: 0.69; 95% CI =0.57–0.83) and gay/lesbian students (AOR: 0.24; 95% CI =0.10–0.60) had better complete response rates. Non-US (AOR: 1.46; 95% CI =1.03–2.07), black (AOR: 3.32; 95% CI =1.92–5.77), and Middle-Eastern students (AOR: 3.73; 95% CI =1.73–8.02) had lower complete response rates. Conclusions: Our study shows sex, gender, citizenship, and race categories have significant differences in complete response rates for the outcome. Our findings have several implications; including recognizing interventions for depression based on responders may not target those that tend to be “partial-responders”. Efforts in survey design, recruiting and completion of surveys should be maximized.     

There is an app for that? The impact of community knowledge workers in Uganda

Rapidly expanding mobile network coverage in developing countries offers new ways to reach poor farmers in isolated places. This article explores the potential for Information and Communication Technology to provide agricultural information and extension services to smallholder farmers, and links this to empirical insights of an intervention in Uganda, where community knowledge workers rely on mobile devices to deliver context- and time-sensitive data to farmers. Consistent with theoretical insights related to information inefficiencies, we find that the intervention leads farmers to move away from low-risk low-return crops toward more commercially oriented commodities. Our analysis also suggests that, for the case of maize, the intervention causes farmers to sell less on the market, but at significantly higher prices.     

#Funeral and Instagram: death,social media,and platform vernacular

This paper presents findings from a study of Instagram use and funerary practices that analysed photographs shared on public profiles tagged with ‘#funeral’. We found that the majority of images uploaded with the hashtag #funeral often communicated a person's emotional circumstances and affective context, and allowed them to reposition their funeral experience amongst wider networks of acquaintances, friends, and family. We argue that photo-sharing through Instagram echoes broader shifts in commemorative and memorialization practices, moving away from formal and institutionalized rituals to informal and personalized, vernacular practices. Finally, we consider how Instagram's ‘platform vernacular’ unfolds in relation to traditions and contexts of death, mourning, and memorialization. This research contributes to a broader understanding of how platform vernaculars are shaped through the logics of architecture and use. This research also directly contributes to the understanding of death and digital media by examining how social media is being mobilized in relation to death, the differences that different media platforms make, and the ways social media are increasingly entwined with the places, events, and rituals of mourning.     

From Experiments to Network Building: Trends in the Use of Research for Reconstructing Working Life

Many efforts to use the social sciences for the purpose of change and reconstruction have their roots in the idea of the field experiment. In various forms, the field experiment played a dominant role in the period 1930-1970. In more recent years, new patterns have emerged, such as complementary research roles in network building. In this contribution, focus is on the links between the early experiments and today's approaches, to see the latter in terms of responses to the challenges posed by the processes that were triggered off by the field experiments.     

How Cox models react to a study-specific confounder in a patient-level pooled dataset: random effects better cope with an imbalanced covariate across trials unless baseline hazards differ

Combining patient-level data from clinical trials can connect rare phenomena with clinical endpoints, but statistical techniques applied to a single trial may become problematical when trials are pooled. Estimating the hazard of a binary variable unevenly distributed across trials showcases a common pooled database issue. We studied how an unevenly distributed binary variable can compromise the integrity of fixed and random effects Cox proportional hazards (cph) models. We compared fixed effect and random effects cph models on a set of simulated datasets inspired by a 17-trial pooled database of patients presenting with ST segment elevation myocardial infarction (STEMI) and non-STEMI undergoing percutaneous coronary intervention. An unevenly distributed covariate can bias hazard ratio estimates, inflate standard errors, raise type I error, and reduce power. While uneveness causes problems for all cph models, random effects suffer least. Compared to fixed effect models, random effects suffer lower bias and trade inflated type I errors for improved power. Contrasting hazard rates between trials prevent accurate estimates from both fixed and random effects models.     

An integrated approach to evaluating urban forest functionality

Despite the fact that forests in urban areas play multiple and often conflicting roles, research and management efforts are typically geared towards a single role or purpose. Urban ecology addresses this multiplicity of function by viewing human and natural systems in urban areas not as separate entities, but as interacting components of an integrated whole. We present an interdisciplinary approach for evaluating the different ways that forests are often valued: economically, socially, and ecologically in residential areas of King County, WA. Economic function is measured as the change in housing prices attributed to location on the gradient, using a hedonic price model. For social function we use a survey to measure (1) residents’ use of parks and forests, and (2) satisfaction with their neighborhoods. We measure ecological function as songbird species richness, using bird survey data. Overlaying the curves of economic, social, and ecological function on the common axis of our urban gradient allows for relationships and tradeoffs to be qualitatively evaluated. Each function responds differently to the gradient. The housing price response is strongest at high and low levels of urbanization, with positive premiums in both areas. Satisfaction with neighborhood attributes decreases with increasing urbanization, while the likelihood of mentioning ‘parks’ as an important element of a resident’s neighborhood increases. Songbird richness peaks in less-developed areas. Evaluating the different functions together is an important step in recognizing and understanding the multiple roles forested areas play.     

Mode Jumping Proposals in MCMC

Markov chain Monte Carlo algorithms generate samples from a target distribution by simulating a Markov chain. Large flexibility exists in specification of transition matrix of the chain. In practice, however, most algorithms used only allow small changes in the state vector in each iteration. This choice typically causes problems for multi-modal distributions as moves between modes become rare and, in turn, results in slow convergence to the target distribution. In this paper we consider continuous distributions on R ⁿ and specify how optimization for local maxima of the target distribution can be incorporated in the specification of the Markov chain. Thereby, we obtain a chain with frequent jumps between modes. We demonstrate the effectiveness of the approach in three examples. The first considers a simple mixture of bivariate normal distributions, whereas the two last examples consider sampling from posterior distributions based on previously analysed data sets.