Across the Sonorous Desert: Sounding Migration in El Mar la Mar

Joshua Bonnetta and J. P. Sniadecki’s El Mar La Mar (2017), an experimental documentary on the migrant trail across the Mexico–US border, features a striking audiovisual assemblage that gives equal weight to sights and sounds, allowing the viewer to contemplate the history of not only the cinema of migration but also the various traditions that engage with field recordings. This chapter investigates the ways in which the film challenges our expectations of what a migrant geography feels like, with special attention to the film’s soundtrack, from its contact mic-enabled drone sounds to disembodied audio testimonials, and the broader acoustic ecology that the film construes (influenced by musique concrète and post-Pierre Schaeffer anecdotal sound, in the work of Luc Ferrari).

Designing a locating-routing three-echelon supply chain network under uncertainty

PurposeIn the present research, location and routing problems, as well as the supply chain, which includes manufacturers, distributor candidate sites and retailers, are explored. The goal of addressing the issue is to reduce delivery times and system costs for retailers so that routing and distributor location may be determined.Design/methodology/approachBy adding certain unique criteria and limits, the issue becomes more realistic. Customers expect simultaneous deliveries and pickups, and retail service start times have soft and hard time windows. Transportation expenses, noncompliance with the soft time window, distributor construction, vehicle purchase or leasing, and manufacturing costs are all part of the system costs. The problem's conceptual model is developed and modeled first, and then General Algebraic Modeling System software (GAMS) and Multiple Objective Particle Swarm Optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGAII) algorithms are used to solve it in small dimensions.FindingsAccording to the mathematical model's solution, the average error of the two suggested methods, in contrast to the exact answer, is less than 0.7%. In addition, the performance of algorithms in terms of deviation from the GAMS exact solution is pretty satisfactory, with a divergence of 0.4% for the biggest problem (N = 100). As a result, NSGAII is shown to be superior to MOSPSO.Research limitations/implicationsSince this paper deals with two bi-objective models, the priorities of decision-makers in selecting the best solution were not taken into account, and each of the objective functions was given an equal weight based on the weighting procedures. The model has not been compared or studied in both robust and deterministic modes. This is because, with the exception of the variable that indicates traffic mode uncertainty, all variables are deterministic, and the uncertainty character of demand in each level of the supply chain is ignored.Practical implicationsThe suggested model's conclusions are useful for any group of decision-makers concerned with optimizing production patterns at any level. The employment of a diverse fleet of delivery vehicles, as well as the use of stochastic optimization techniques to define the time windows, demonstrates how successful distribution networks are in lowering operational costs.Originality/valueAccording to a multi-objective model in a three-echelon supply chain, this research fills in the gaps in the link between routing and location choices in a realistic manner, taking into account the actual restrictions of a distribution network. The model may reduce the uncertainty in vehicle performance while choosing a refueling strategy or dealing with diverse traffic scenarios, bringing it closer to certainty. In addition, two modified MOPSO and NSGA-II algorithms are presented for solving the model, with the results compared to the exact GAMS approach for medium- and small-sized problems.

In Vitro Rearing Changes Social Task Performance and Physiology in Honeybees

In vitro rearing of honeybee larvae is an established method that enables exact control and monitoring of developmental factors and allows controlled application of pesticides or pathogens. However, only a few studies have investigated how the rearing method itself affects the behavior of the resulting adult honeybees. We raised honeybees in vitro according to a standardized protocol: marking the emerging honeybees individually and inserting them into established colonies. Subsequently, we investigated the behavioral performance of nurse bees and foragers and quantified the physiological factors underlying the social organization. Adult honeybees raised in vitro differed from naturally reared honeybees in their probability of performing social tasks. Further, in vitro-reared bees foraged for a shorter duration in their life and performed fewer foraging trips. Nursing behavior appeared to be unaffected by rearing condition. Weight was also unaffected by rearing condition. Interestingly, juvenile hormone titers, which normally increase strongly around the time when a honeybee becomes a forager, were significantly lower in three- and four-week-old in vitro bees. The effects of the rearing environment on individual sucrose responsiveness and lipid levels were rather minor. These data suggest that larval rearing conditions can affect the task performance and physiology of adult bees despite equal weight, pointing to an important role of the colony environment for these factors. Our observations of behavior and metabolic pathways offer important novel insight into how the rearing environment affects adult honeybees.

Allocation Optimization of Multi-Axis Suspension Dynamic Parameter for Tracked Vehicle

The dynamic parameter allocation of the suspension system has an important influence on the comprehensive driving performance of the tracked vehicle. Usually, the allocation of suspension parameters is based on a single performance index, which has the disadvantage of not being able to achieve multi-performance optimization. Therefore, a novel optimization method using multi-performance index-oriented is presented. Firstly, considering the vertical vibration excitation caused by road roughness, the input (excitation) model of road roughness is embedded to establish the parametric dynamic model of the tracked vehicle. Then, the evaluation index and its quantitative algorithm, which reflect the multi-aspect performance of the suspension system, are proposed. Moreover, the parameter allocation objective function based on multi-index information fusion is designed. Finally, two allocation optimization methods are presented to solve the parameter allocation, i.e., equal weight allocation and expert knowledge-based weight allocation. By comparing the results obtained by the two methods, it is found that the performance of the suspension system can be improved effectively by optimizing the parameters of suspension stiffness and damping. Furthermore, the optimization of weight allocation based on expert knowledge is more effective. These provide a better knowledge reference for suspension system design.

An Alternative Nutrient Rich Food Index (NRF-ai) Incorporating Prevalence of Inadequate and Excessive Nutrient Intake

Most nutrient profiling models give equal weight to nutrients irrespective of their ubiquity in the food system. There is also a degree of arbitrariness about which nutrients are included. In this study, an alternative Nutrient Rich Food index was developed (NRF-ai, where ai denotes adequate intake) incorporating prevalence of inadequate and excessive nutrient intake among Australian adults. Weighting factors for individual nutrients were based on a distance-to-target method using data from the Australian Health Survey describing the proportion of the population with usual intake less than the Estimated Average Requirement defined by the Nutrient Reference Values for Australia and New Zealand. All nutrients for which data were available were included, avoiding judgements about which nutrients to include, although some nutrients received little weight. Separate models were developed for females and males and for selected age groups, reflecting differences in nutrient requirements and usual intake. Application of the new nutrient profiling models is demonstrated for selected dairy products and alternatives, protein-rich foods, and discretionary foods. This approach emphasises the need to identify foods that are rich in those specific nutrients for which intake is below recommended levels and can be used to address specific nutrient gaps in subgroups such as older adults. In addition, the new nutrient profiling model is used to explore other sustainability aspects, including affordability (NRF-ai per AUD) and ecoefficiency (NRF-ai/environmental impact score).

Two-Stage Robust Optimization Model for Uncertainty Investment Portfolio Problems

Investment portfolio can provide investors with a more robust financial management plan, but the uncertainty of its parameters is a key factor affecting performance. This paper conducts research on investment portfolios and constructs a two-stage mixed integer programming (TS-MIP) model, which comprehensively considers the five dimensions of profit, diversity, skewness, information entropy, and conditional value at risk. But the deterministic TS-MIP model cannot cope with the uncertainty. Therefore, this paper constructs a two-stage robust optimization (TS-RO) model by introducing robust optimization theory. In case experiments, data crawler technology is used to obtain actual data from real websites, and a variety of methods are used to verify the effectiveness of the proposed model in dealing with uncertainty. The comparison of models found that, compared with the traditional equal weight model, the investment benefits of the TS-MIP model and the TS-RO model proposed have been improved. Among them, the Sharpe ratio, Sortino ratio, and Treynor ratio have the largest increase of 19.30%, 8.25%, and 7.34%, respectively.

Rationalist Resistance to Disagreement-Motivated Religious Skepticism

Many epistemologists argue that responses to disagreement should exhibit a certain kind of epistemic impartiality. “Strong conciliationists” claim that we ought to give equal weight to the views of those who, judged from a dispute-neutral perspective, appear to be our “epistemic peers” with respect to some disputed matter. Using a Bayesian framework, Chapter 8 considers whether there is a plausible epistemic impartiality principle that would require us to give up confident religious (or irreligious) belief in favor of religious skepticism. It is argued that the strong conciliationist’s epistemic impartiality is untenable, at least in contexts like the religious domain where the primary questions under dispute cannot be cleanly separated from questions about what qualifications are needed to reliably assess those primary questions. The chapter recommends instead a rationalist view on which rational insight can sustain justified confidence even when impartial grounds are lacking. It closes by defending the “religious acceptability” of this rationalist epistemology.

Understanding heuristics-based financial decision-making using behavioral portfolio strategies

PurposeThrough a portfolio choice model, the study empirically examines the influence of the heuristic simplification through peak-end rule (PER) and the associated neglect of the duration of the experience. The portfolio strategy adopted involves optimizing portfolios to capture the impact of heuristic-driven investors' experience of good and bad states. The study attempts to validate PER in an empirical context and is expected to generate trading rules, which would exploit pricing errors emerging out of the use of heuristics by investors.Design/methodology/approachThe empirical approach adopted in the study primarily examines returns to portfolios sorted according to various hedonic evaluation rules. Behavioral portfolios are constructed using hedonic experiences as conditioning variables.FindingsThe results imply that there is continued investor demand for such assets in the short run. An equal weight portfolio based on a three-month hedonic evaluation earns an average monthly return of 2.77% over the next 12 months.Originality/valueThe authors’ study may perhaps be the first attempt to use the peak-end heuristic in portfolio construction.

Valuing the Impacts of Landslides: A Choice Experiment Approach

This paper analyzes the preferences for reducing the negative impacts of landslides. Negative consequences of landslides include impacts on transport infrastructure, humans, the environment and important societal services. We apply a choice experiment. The analysis is based on 6048 observations from 504 participants in a web panel. The overall finding is that reducing the risk of landslides would have a positive impact on individuals’ utility, and that individuals prioritize preventing negative consequences on human health and safety over maintaining societal services, environmental status, and preventing damages to transport infrastructure, which seems to be least pressing. Results indicate that prioritizations of citizens differ from the prioritizations of public authorities, whose risk assessment model for evaluating the consequences of landslides gives equal weight to the different impacts.

Abstract 13607: Correlation in Hospital Survival Following Out-of-Hospital Cardiac Arrest With Variation in Post-Arrest Inpatient Intervention Rates in Michigan

Introduction: Wide variations in rates of survival to hospital discharge exist for survivors of out-of-hospital cardiac arrest (OHCA). The potential influence of variation in post-OHCA hospital care has not been adequately explored. We hypothesized that variation of in hospital survival rates may be influenced by variation of in-hospital care in Michigan. Methods: We performed a secondary analysis of a statewide cardiac arrest database constructed from two probabilistically-linked cardiac arrest registries [Cardiac Arrest Registry to Enhance Survival (CARES) and Michigan Inpatient Database (MIDB)] from 2014 - 2017. A novel composite rank score was created to characterize post-arrest in-hospital care, incorporating four specific interventions: left heart catheterization within 24 hours (LHC), emergent mechanical circulatory support (EMCS), targeted temperature management (TTM), and do-not-resuscitate order placed within 72 hours of arrival (DNR). The highest score (1 of 38) was given to the hospital with highest procedure rate (LHC, TTM, LHC) and the lowest rate of early DNR. Spearman’s correlation coefficients assessed the relationship between the equal weight composite rank score and rate of hospital survivors. Results: We included 3,644 patients admitted to 38 hospitals who treated >30 OHCA patients during the study period. Patient mean age was 62.4 years, and 59.3% were male. Survival, rank scores and correlation coefficients are listed below: We observed four-fold variation in survival for all patients and witnessed arrest, with a non-significant correlation with care provision. However, we identified a sixteen-fold variation in survival among unwitnessed arrests, which was significantly correlated with a higher rank of care provided. Conclusions: In Michigan, the greatest variation in survival was identified among unwitnessed arrests. This variation was robustly associated with a composite rank of in-hospital post-arrest interventions.