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Virtual Reality (VR) is a computer-generated environment with noteworthy didactic applications in different educational levels and areas of knowledge. The study of the perceptions of the agents involved about the use of VR in lectures is a fruitful line of research because it has implications in terms of the measures to be taken to improve the training and competence of professors in its use. In this paper, a quantitative, descriptive, and correlational research is carried out on the assessments of a sample of 1638 Latin American university professors on both (i) the didactic use of VR and (ii) the influence of the professors' area of knowledge on these assessments. For this purpose, a validated questionnaire was used, the responses to which were subjected to statistical analysis. As a result, it was found that the ratings of VR are very high, but professors believe that their digital skills for its use are insufficient. In addition, the professors' area of knowledge significantly influences their ratings, being higher in the areas of knowledge in which professors have a better self-concept of their digital skills. Furthermore, gender gaps have also been identified in the answers given, which behave differently according to the area of knowledge. Finally, some conclusions, implications, and recommendations are drawn from the results obtained.

The aim of this study is to examine the open access theses in the Social Sciences group with virtual reality in the title of the review results made in the Council of Higher Education Thesis Center, through systematic review and content analysis method. It is thought that this study will narrow the wide scope of the notion of virtual reality and can describe the change and development over the years in the context of the field of social sciences. In the research, 54 postgraduate theses were examined and the distribution of the theses with virtual reality in their title were analyzed according to the years they were published, by type, by languages, by universities, by departments, according to the purpose of theses, by type of virtual reality software used, by type of virtual reality hardware, by the names of software and hardware. Since theses on educational sciences were intense, analysis was also carried out according to research methods, data collection tools and samples. In addition, the distribution of keywords in theses was also determined. Based on the obtained data, the highest number of theses was reached in 2019, while most of the theses were completed as master's thesis. While theses on virtual reality are mostly completed at Bahçesehir University, they intensify on the Department of Computer Education and Instructional Technology in terms of department type. In the theses, especially virtual reality game experiences are aimed. 3600 Video and 3D Games are the most used software types, while the Virtual Reality Headsets are the most used hardware. Oculus Rift is the most used virtual reality hardware brand. Beside these, it is found that quantitative method is mostly preferred, the most used data collection tool is questionnaire, and the most used sample group is undergraduate students.

Technological advances have posed a challenge in university learning ecosystems in terms of the application of immersive technologies that offer an educational and innovative framework to the student. The evolution of global research on this topic during the period 1980 to 2019 was studied. For this purpose, a bibliometric analysis of 1296 articles was applied, obtaining results of the scientific productivity of the journals, authors, institutions, and countries that contribute to this research. The evidence shows a growing interest, especially in the last three years, in the study of the application of virtual reality in higher education. The main subject area is Social Science. The most productive research institution is the Complutense University of Madrid. The United States is the country with the most publications and citations. In addition, The United States, Spain and the United Kingdom are the countries with the most international collaborations in their publications. The study detected five new directions for future research. The growing worldwide trend of scientific production demonstrates the interest in developing aspects of the use of virtual reality in arts education in the context of higher education. This study contributes to the academic, scientific and institutional discussion around the improvement of decision making based on the available information.

Purpose: The aim of this research is to investigate the effect of Augmented Reality (AR) applications in the learning process. Problem: Research that determines the effectiveness of Augmented Reality (AR) applications in the learning process with different variables has not been encountered in national or international literature. Research Methods: To determine the effect of AR in the learning process, experimental studies conducted in 2007-2017 on the use of AR in education were analyzed by the Meta Analysis Method. Analyzed articles were selected among the publications in the journals scanned in the Social Sciences Citation Index (SSCI). In this context, 16 studies were examined to identify the effect of AR applications in the learning process. Findings: Findings indicated that AR applications increase students' academic achievement in the learning process compared to traditional methods. Implications for Research and Practice: It was concluded that AR applications do not show significant differences in academic success in the learning process. For example, the "grade level" variable of the study does not show a significant difference compared to traditional methods. When assessing AR display devices, the largest effect size was related to the use of mobile devices, while the smallest effect size was in the use of webcam-based devices. When comparing sample size in the study, it was identified that the effect size of large sample groups was affected by AR on a medium level, while small samples were affected minimally.

The cognitive-motivational process model of learning describes how personality traits in a specific situation influence current learner motivation and through certain mediators, the learning outcome. This study investigates the influence of personality traits and current motivation on these mediators. For 86 high school students playing a simulation game, the Big Five, the need for cognition, current motivations, immersion, and joy of learning were measured. A hierarchical regression analysis showed that need for cognition, interest, and challenge significantly and positively impacts the experienced immersion. Also, the joy of learning correlates positively with immersion. The adapted model was partly supported: Results of this study can explain to some extent the interaction of personality traits and current motivation as well as their combined impact on immersion in live-action social science simulation games.

Augmented reality (AR) technology is commonly used in education. AR offers a combination of the virtual and real world; thus, it can help students in learning abstract and complex subjects. The purpose of the current study was to determine the impact of mobile AR technology on achievement, cognitive load levels and views of 95 first-year university students (40 in the experimental group and 55 in the control group) enrolled in a geography course in the social sciences education department of the education faculty of a university in Turkey. A sequential explanatory design, a mixed method type of research, was used. The data were collected using an achievement test, a cognitive load scale, and a semi-structured interview form. The results of the study showed that AR increases students' achievement and decreases their cognitive load levels, and the students' views about AR technology were positive. Consequently, it can be stated that mobile AR technology is a useful tool for teaching geography, especially geomorphology topics.

Increasingly, international competence is considered an important skill to be acquired from an undergraduate education. Because international exchange presents a challenge to many students, there is a need to develop and implement alternative means for incorporating international and cross-cultural experiences into the undergraduate classroom. We report on the implementation of a semester-long, virtually shared course offering between a U.S. and a Bolivian university. As STEM (science, technology, engineering, and mathematics) majors tend to be under-represented in study-abroad programs, this class sought to provide a multidisciplinary experience that could be relevant to both hard and social science majors. Furthermore, the relevance and learning impact of this class was enhanced through the incorporation of a service-learning component in conjunction with a rural Bolivian partner organization. The results of this experience show that virtually shared classroom experiences can successfully facilitate international experiences for undergraduate students.

GlobalEd 2 (GE2) is a set of technology-mediated, problem-based learning (PBL) simulations for middle-grade students, that capitalises on the multidisciplinary nature of the social sciences as an expanded curricular space for students to learn and apply scientific literacies and concepts, while simultaneously also enriching their understanding of the social sciences. This paper reports the results of an implementation of the GE2 curriculum focused on water resources with 535 seventh and eighth grade students from both suburban and urban school systems. The results indicate positive changes in students' writing self-efficacy, interest in pursuing future science educational opportunities and the quality of their written scientific argumentation after participation in a GE2 simulation. Curricular implications and future research directions are discussed.

Purpose: This study investigates changes in the prevalence and practice of simulation in communication sciences and disorders (CSD) education. It is a follow-up to a 2015 survey on the same topic. Given the changes in program certification standards and the impact of the COVID-19 pandemic on clinical education programs across the United States, re-examination of simulation in CSD is warranted. Method: An online questionnaire was developed to survey university programs accredited by the Council on Academic Accreditation of the American Speech-Language-Hearing Association. University program directors and clinical directors received recruitment e-mails using QuestionPro, an online survey platform. The recruitment e-mail contained the purpose of the study and a link to the online questionnaire along with instructions to forward the survey to the appropriate designee. The consent form was then embedded in the questionnaire. Results: The results of this survey indicated changes in patterns and the use of simulation in clinical education for CSD. Results indicated an overall increase in the use of simulations, specifically in computer-based simulations. Distance simulation as a hybrid technology proved a major addition to clinical education programs during the COVID-19 pandemic. External and internal factors affecting the use of simulations in CSD were identified. Conclusions: The use of simulation to supplement clinical education in CSD has evolved in recent years. These changes are likely due in part to changes in certification standards in the profession, an increase in awareness and training, and reliance on distance simulation during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

This article uses a computer simulation method using the FlexSim program and the indicator method. To apply the indicated methods, real data obtained from the company, own observations and interviews with company employees were used. Three new warehouse space models developed for the reorganization show that there is a need to change the current warehouse layout. Working in the current arrangement is ineffective and dangerous due to the company's profile. The obtained results of indicator calculations clearly show that the new warehouse model will be a better solution for the examined company. Is recommended for the examined company to change the organization of the warehouse to a new model, the use of which will not only shorten the internal transport time but will also significantly increase the work safety of employees. The new warehouse model, described in detail, will bring many benefits to the company. Further research may concern a new model or a change in means of transport in the warehouse. An additional facilitation may be the use of 19 steps as a method supporting the organization of internal transport and designing the warehouse layout.

Emergency departments are the first point of contact for life-saving care worldwide. Despite this importance in patient care, emergency departments face a number of shortcomings. For example, emergency departments have been struggling for many years with a lack of resources, low levels of digitalization, or unregulated access to emergency departments. Thoughtful process analysis using discrete event simulation (DES) can support the implementation of better processes to improve quality of care sustainably. Based on empirical data obtained through observations, expert interviews, process analysis, and time studies, the authors modelled and simulated the flow of care in a general hospital’s emergency department using a stochastic DES model. The results of the DES study show that digital upgrades and additional staff resources, in particular, can reduce process times in terms of length of stay and waiting times. One can conclude that discrete event simulation is a suitable tool to realistic model and simulate complex systems such as emergency departments, and derive meaningful improvement potentials. In the future, the potential of digitalization concerning process flows should be considered more often in DES studies.

preCICE is a free/open-source coupling library. It enables creating partitioned multi-physics simulations by gluing together separate software packages. This paper summarizes the development efforts in preCICE of the past five years. During this time span, we have turned the software from a working prototype -- sophisticated numerical coupling methods and scalability on ten thousands of compute cores -- to a sustainable and user-friendly software project with a steadily-growing community. Today, we know through forum discussions, conferences, workshops, and publications of more than 100 research groups using preCICE. We cover the fundamentals of the software alongside a performance and accuracy analysis of different data mapping methods. Afterwards, we describe ready-to-use integration with widely-used external simulation software packages, tests, and continuous integration from unit to system level, and community building measures, drawing an overview of the current preCICE ecosystem.

A chronicled approach to the notion of computer simulations shows that there are two predominant interpretations in the specialized literature. According to the first interpretation, computer simulations are techniques for finding the set of solutions to a mathematical model. I call this first interpretation the problem-solving technique viewpoint (PST). In its second interpretation, computer simulations are considered to describe patterns of behavior of a target system. I call this second interpretation the description of patterns of behavior viewpoint of computer simulations (DPB). This article explores these two interpretations of computer simulations from three different angles. First, I collect a series of definitions of computer simulation from the historical record. I track back definitions to the early 1960s and show how each viewpoint shares similar interpretations of computer simulations-ultimately clustering into the two viewpoints aforementioned. This reconstruction also includes the most recent literature. Second, I unpack the philosophical assumptions behind each viewpoint, with a special emphasis on their differences. Third, I discuss the philosophical implications of each viewpoint in the context of the recent discussion on the logic of scientific explanation for computer simulations., Author(s): Juan M. Durán [sup.1] Author Affiliations: (1) grid.5292.c, 0000 0001 2097 4740, Faculty of Technology, Policy and Management, Delft University of Technology, , Building 31, Jaffalaan 5, 2628 BX, [...]

People automatically repeat behaviors that were frequently rewarded in the past in a given context. Such repetition is commonly attributed to habit, or associations in memory between a context and a response. Once habits form, contexts directly activate the response in mind. An opposing view is that habitual behaviors depend on goals. However, we show that this view is challenged by the goal independence of habits across the fields of social and health psychology, behavioral neuroscience, animal learning, and computational modeling. It also is challenged by direct tests revealing that habits do not depend on implicit goals. Furthermore, we show that two features of habit memory—rapid activation of specific responses and resistance to change—explain the different conditions under which people act on habit versus persuing goals. Finally, we tested these features with a novel secondary analysis of action-slip data. We found that habitual responses are activated regardless of goals, but they can be performed in concert with goal pursuit. [ABSTRACT FROM AUTHOR]

Eta squared is a popular effect size, but contains positive bias. Bootstrapping can be used to remove the bias from eta squared. Compared to epsilon squared and omega squared, bootstrap bias correction does not make distributional assumption, and it is easy to implement. A real example and computer simulations are included to illustrate its application. The bootstrap bias-corrected eta squared shows very little bias, and it serves as a good alternative to eta squared and epsilon squared, the latter of which can turn negative in some circumstances. [ABSTRACT FROM AUTHOR]

preCICE is a free/open-source coupling library. It enables creating partitioned multi-physics simulations by gluing together separate software packages. This paper summarizes the development efforts in preCICE of the past five years. During this time span, we have turned the software from a working prototype -- sophisticated numerical coupling methods and scalability on ten thousands of compute cores -- to a sustainable and user-friendly software project with a steadily-growing community. Today, we know through forum discussions, conferences, workshops, and publications of more than 100 research groups using preCICE. We cover the fundamentals of the software alongside a performance and accuracy analysis of different data mapping methods. Afterwards, we describe ready-to-use integration with widely-used external simulation software packages, tests, and continuous integration from unit to system level, and community building measures, drawing an overview of the current preCICE ecosystem.

The stability of a complex system generally decreases with increasing system size and interconnectivity, a counterintuitive result of widespread importance across the physical, life, and social sciences. Despite recent interest in the relationship between system properties and stability, the effect of variation in response rate across system components remains unconsidered. Here I vary the component response rates (γ) of randomly generated complex systems. I use numerical simulations to show that when component response rates vary, the potential for system stability increases. These results are robust to common network structures, including small-world and scale-free networks, and cascade food webs. Variation in γ is especially important for stability in highly complex systems, in which the probability of stability would otherwise be negligible. At such extremes of simulated system complexity, the largest stable complex systems would be unstable if not for variation in γ. My results therefore reveal a previously unconsidered aspect of system stability that is likely to be pervasive across all realistic complex systems. [ABSTRACT FROM AUTHOR]

The development of a new drug is an extremely high-risk enterprise. The attrition rates of development projects and the average costs for each launched product are daunting, and the completion of a development program requires a very long time horizon. These facts imply that there are huge potential gains, should one be able to improve efficiency and enhance decision-making capabilities. In this paper, we argue that substantial gains can be achieved by adapting a holistic view of drug development. Historically, too much planning, design and decision-making in the pharmaceutical development has been based on locally optimising separate parts of the development program, and too often important sources of uncertainty are ignored. We propose instead a model-based approach built on two essential pillars; (1) an integrated holistic view of the development program, including post-launch marketing and sales, with all parts evaluated simultaneously; (2) an explicit appreciation of all relevant sources of uncertainty. Computer simulations are utilised to evaluate the properties of the program options at hand, and to provide valuable quantitative decision support. Applications of this modelling approach have proven to add large value to development projects in terms of better program options being generated and more value-adding decisions taken. [ABSTRACT FROM AUTHOR]

Popular computational models of decision-making make specific assumptions about learning processes that may cause them to underfit observed behaviours. Here we suggest an alternative method using recurrent neural networks (RNNs) to generate a flexible family of models that have sufficient capacity to represent the complex learning and decision- making strategies used by humans. In this approach, an RNN is trained to predict the next action that a subject will take in a decision-making task and, in this way, learns to imitate the processes underlying subjects’ choices and their learning abilities. We demonstrate the benefits of this approach using a new dataset drawn from patients with either unipolar (n = 34) or bipolar (n = 33) depression and matched healthy controls (n = 34) making decisions on a two-armed bandit task. The results indicate that this new approach is better than baseline reinforcement-learning methods in terms of overall performance and its capacity to predict subjects’ choices. We show that the model can be interpreted using off-policy simulations and thereby provides a novel clustering of subjects’ learning processes—something that often eludes traditional approaches to modelling and behavioural analysis. [ABSTRACT FROM AUTHOR]

Orienteering problem (OP) is a routing problem, where the aim is to generate a path through set of nodes, which would maximize total score and would not exceed the budget. In this paper, we present an extension of classic OP—Orienteering Problem with Functional Profits (OPFP), where the score of a specific point depends on its characteristics, position in the route, and other points in the route. For solving OPFP, we developed an open-source framework for solving orienteering problems, which utilizes four core components of OP in its modular architecture. Fully-written in Go programming language our framework can be extended for solving different types of tasks with different algorithms; this was demonstrated by implementation of two popular algorithms for OP solving—Ant Colony Optimization and Recursive Greedy Algorithm. Computational efficiency of the framework was shown through solving four well-known OP types: classic Orienteering Problem (OP), Orienteering Problem with Compulsory Vertices (OPCV), Orienteering Problem with Time Windows (OPTW), and Time Dependent Orienteering Problem (TDOP) along with OPFP. Experiments were conducted on a large multi-source dataset for Saint Petersburg, Russia, containing data from Instagram, TripAdvisor, Foursquare and official touristic website. Our framework is able to construct touristic paths for different OP types within few seconds using dataset with thousands of points of interest. [ABSTRACT FROM AUTHOR]

We propose a funding scheme for theoretical research that does not rely on project proposals, but on recent past scientific productivity. Given a quantitative figure of merit on the latter and the total research budget, we introduce a number of policies to decide the allocation of funds in each grant call. Under some assumptions on scientific productivity, some of such policies are shown to converge, in the limit of many grant calls, to a funding configuration that is close to the maximum total productivity of the whole scientific community. We present numerical simulations showing evidence that these schemes would also perform well in the presence of statistical noise in the scientific productivity and/or its evaluation. Finally, we prove that one of our policies cannot be cheated by individual research units. Our work must be understood as a first step towards a mathematical theory of the research activity. [ABSTRACT FROM AUTHOR]

Evaluating the future consequences of actions is achievable by simulating a mental search tree into the future. Expanding deep trees, however, is computationally taxing. Therefore, machines and humans use a plan-until-habit scheme that simulates the environment up to a limited depth and then exploits habitual values as proxies for consequences that may arise in the future. Two outstanding questions in this scheme are “in which directions the search tree should be expanded?”, and “when should the expansion stop?”. Here we propose a principled solution to these questions based on a speed/accuracy tradeoff: deeper expansion in the appropriate directions leads to more accurate planning, but at the cost of slower decision-making. Our simulation results show how this algorithm expands the search tree effectively and efficiently in a grid-world environment. We further show that our algorithm can explain several behavioral patterns in animals and humans, namely the effect of time-pressure on the depth of planning, the effect of reward magnitudes on the direction of planning, and the gradual shift from goal-directed to habitual behavior over the course of training. The algorithm also provides several predictions testable in animal/human experiments. [ABSTRACT FROM AUTHOR]

Consideration of previous successes and failures is essential to mastering a motor skill. Much of what we know about how humans and animals learn from such reinforcement feedback comes from experiments that involve sampling from a small number of discrete actions. Yet, it is less understood how we learn through reinforcement feedback when sampling from a continuous set of possible actions. Navigating a continuous set of possible actions likely requires using gradient information to maximize success. Here we addressed how humans adapt the aim of their hand when experiencing reinforcement feedback that was associated with a continuous set of possible actions. Specifically, we manipulated the change in the probability of reward given a change in motor action—the reinforcement gradient—to study its influence on learning. We found that participants learned faster when exposed to a steep gradient compared to a shallow gradient. Further, when initially positioned between a steep and a shallow gradient that rose in opposite directions, participants were more likely to ascend the steep gradient. We introduce a model that captures our results and several features of motor learning. Taken together, our work suggests that the sensorimotor system relies on temporally recent and spatially local gradient information to drive learning. [ABSTRACT FROM AUTHOR]

Objectives: Traditionally, the acquisition of manual skills in most dental schools worldwide is based on exercises on plastic teeth placed in a "phantom head simulator". No manual trainings are done at home. Studies revealed that preliminary training of one motoric task leads to significant improvement in performance of the required motoric task that has similar components. Performing tasks indirectly via a dental mirror are complicated for the young dental students. We hypothesized that instructed training of basic skills required in dentistry at home on a tool simulating the phantom laboratory will improve the capabilities of the students and will be reflected by their clinical grades. Methods: We developed a portable tool PhantHome which is composed of jaws, gingival tissue, rubber cover and a compatible stand. Specific teeth produced by a 3D printer with drills in different directions were placed in both jaws. Students were requested to insert pins by using tweezers and dental mirror according to instructions initiating with easy tasks and continue to ones that are more complicated. 106 first clinical year dental students participated in the study; 65 trained only in the traditional phantom lab (control). 41 trained at home by the PhantHome tool two weeks before and 2 months during the initial stage of phantom lab. The students grades routinely provided in the phantom laboratory at different stages were compared. Results: Students who trained with the portable tool performed better than the control group in the first direct and second indirect preparations (p<0.05). These exams were taken when the PhantHome was available to the students. Then, the tool was returned and the phantom course continued regularly. We believe that this is why no differences between the grades of the groups were observed further on. Conclusions: Training by the PhantHome improves motor skills and consequently the clinical performances. [ABSTRACT FROM AUTHOR]

From his first attempts to explain attachment phenomena in the 1940s through his Attachment and Loss trilogy (Bowlby. 1969/1982, 1973, 1980), John Bowlby reformulated the theoretical underpinnings of attachment theory several times. He initially attempted to explain attachment phenomena in psychoanalytic terms. Then he invoked ethological theory' in the explanation of how and why people behave as they do in close personal relationships. The mature theoretical framework that he presented between 1969 and 1982 in the attachment and loss trilogy retained strengths and insights, ultimately situating them within an overarching control systems framework. This article describes key stages in Bowlby's theoretical development, with particular emphasis placed on the emergence of control systems theory as a cornerstone of the mature theory. It also compares Bowlby's control systems approach to contemporary cognitive science approaches. It concludes by suggesting how Bowlby's control systems formulation could evolve along the path opened up by contemporary work in computational modeling and how it could benefit by doing so. [ABSTRACT FROM AUTHOR]

Background: Given the increasing lifespan of the elderly and the higher proportion of older people in the global population, the incidence rate of neurodegenerative diseases is increasing. The aim of this study is to evaluate, by means of computer simulations, developments in the costs of treating and caring for people suffering from Alzheimer’s disease (AD) in the EU 28 by 2080, while assuming the introduction of drug administrations at various disease stages. Methods: Impact analysis leverages a mathematical model that compares five different population development scenarios when introducing different types of drugs to the scenarios but without changing the treatment. Changes in the economic burden are considered as of 2023, when new drugs are expected to enter the market. Findings: The results of the simulations show that by prolonging the length of a person’s ‘stay’ in the Mild, Moderate, or Severe stage, the total cost of care for all persons with AD will increase by 2080. For individual scenarios, the percentage of patients and costs increased as follows: Mild by one year, by 10.61%; Mild by two years, by 17.73%; Moderate by one year, by 16.79%; Moderate by two years, by 34.88%; and Severe by one year, by 23.79%. The change in cost development when prolonging the stay in the Mild cognitive impairment stage (by lowering the incidence by 10%, 30%, or 50%) reduced the cost (by 4.88%, 16.78% and 32.48%, respectively). Interpretation: The results unambiguously show that any intervention prolonging a patient’s stay in any stage will incur additional care costs and an increase in the number of persons with AD. Therefore, extending lifespan is important in terms of improving the quality of life of patients, and the introduction of new drugs must consider the additional costs imposed upon society. [ABSTRACT FROM AUTHOR]

A commonly cited reason for the failure of time-area closures to achieve fisheries management goals is the displacement of fishing effort from inside the closure into the surrounding area still open to fishing. Designing time-area closures that are predicted to achieve management goals under multiple spatial patterns of effort redistribution will increase chances of success. Using data from an estuarine gill net fishery, we tested if there are time-area closures predicted to reduce bycatch of two protected species groups while maintaining target catch under four simulated effort redistribution patterns. We found that the pattern of effort redistribution had a substantial impact on the amount of predicted bycatch in each closure scenario. Multiple closures were predicted to reduce bycatch of these species under all four simulations of effort redistribution. However, some combinations of closure and effort redistribution pattern resulted in estimated bycatch being higher than without a closure. We did not find any time-area closures that resulted in a predicted reduction in bycatch while maintaining target catch at original levels. We demonstrate a simple way for fisheries managers to account for the uncertainty in fishers' behavior by designing time-area closures that are predicted to reduce bycatch under multiple potential patterns of spatial redistribution of fishing effort. [ABSTRACT FROM AUTHOR]

In recent years, serious concerns have arisen about reproducibility in science. Estimates of the cost of irreproducible preclinical studies range from 28 billion USD per year in the USA alone (Freedman et al. in PLoS Biol 13(6):e1002165, 2015) to over 200 billion USD per year worldwide (Chalmers and Glasziou in Lancet 374:86-89, 2009). The situation in the social sciences is not very different: Reproducibility in psychological research, for example, has been estimated to be below 50% as well (Open Science Collaboration in Science 349:6251, 2015). Less well studied is the issue of reproducibility of simulation research. A few replication studies of agent-based models, however, suggest the problem for computational modeling may be more severe than for laboratory experiments (Willensky and Rand in JASSS 10(4):2, 2007; Donkin et al. in Environ Model Softw 92:142-151, 2017; Bajracharya and Duboz in: Proceedings of the symposium on theory of modeling and simulation—DEVS integrative M&S symposium, pp 6-11, 2013). In this perspective, we discuss problems of reproducibility in agent-based simulations of life and social science problems, drawing on best practices research in computer science and in wet-lab experiment design and execution to suggest some ways to improve simulation research practice. [ABSTRACT FROM AUTHOR]

In natural environments, odors are typically mixtures of several different chemical compounds. However, the implications of mixtures for odor processing have not been fully investigated. We have extended a standard olfactory receptor model to mixtures and found through its mathematical analysis that odorant-evoked activity patterns are more stable across concentrations and first-spike latencies of receptor neurons are shorter for mixtures than for pure odorants. Shorter first-spike latencies arise from the nonlinear dependence of binding rate on odorant concentration, commonly described by the Hill coefficient, while the more stable activity patterns result from the competition between different ligands for receptor sites. These results are consistent with observations from numerical simulations and physiological recordings in the olfactory system of insects. Our results suggest that mixtures allow faster and more reliable olfactory coding, which could be one of the reasons why animals often use mixtures in chemical signaling. [ABSTRACT FROM AUTHOR]

Brazil recently began granting timber concessions in public forests to promote sustainable forest use. The effectiveness of this strategy hinges on the design and implementation of the concessions themselves as well as their competitive position within the logging sector as a whole. There is, however, a lack of information on the competitive interaction between legal and illegal logging and its effects on concessions profits. We address this knowledge gap by using a spatially explicit simulation model of the Amazon timber industry to examine the potential impact of illegal logging on timber concessions allocation and profits in a 30-year harvest cycle. In a scenario in which illegal logging takes place outside concessions, including private and public “undesignated” lands, concession harvested area would decrease by 59% due to competition with illegal logging. Moreover, 29 out of 39 National Forests (≈74%) would experience a decrease in harvested area. This “leakage” effect could reduce concession net rents by up to USD 1.3 Billion after 30 years. Federal and State “undesignated” lands, if not adequately protected, could have 40% of their total volume illegally harvested in 30 years. Our results reinforce the need to invest in tackling illegal logging, if the government wants the forest concessions program to be successful. [ABSTRACT FROM AUTHOR]

When estimating psychometric functions with sampling procedures, psychophysical assessments should be precise and accurate while being as efficient as possible to reduce assessment duration. The estimation performance of sampling procedures is commonly evaluated in computer simulations for single psychometric functions and reported using metrics as a function of number of trials. However, the estimation performance of a sampling procedure may vary for different psychometric functions. Therefore, the results of these type of evaluations may not be generalizable to a heterogeneous population of interest. In addition, the maximum number of trials is often imposed by time restrictions, especially in clinical applications, making trial-based metrics suboptimal. Hence, the benefit of these simulations to select and tune an ideal sampling procedure for a specific application is limited. We suggest to evaluate the estimation performance of sampling procedures in simulations covering the entire range of psychometric functions found in a population of interest, and propose a comprehensive set of performance metrics for a detailed analysis. To illustrate the information gained from these metrics in an application example, six sampling procedures were evaluated in a computer simulation based on prior knowledge on the population distribution and requirements from proprioceptive assessments. The metrics revealed limitations of the sampling procedures, such as inhomogeneous or systematically decreasing performance depending on the psychometric functions, which can inform the tuning process of a sampling procedure. More advanced metrics allowed directly comparing overall performances of different sampling procedures and select the best-suited sampling procedure for the example application. The proposed analysis metrics can be used for any sampling procedure and the estimation of any parameter of a psychometric function, independent of the shape of the psychometric function and of how such a parameter was estimated. This framework should help to accelerate the development process of psychophysical assessments. [ABSTRACT FROM AUTHOR]

This work presents a nonparametric statistical test, S-maup, to measure the sensitivity of a spatially intensive variable to the effects of the Modifiable Areal Unit Problem (MAUP). To the best of our knowledge, S-maup is the first statistic of its type and focuses on determining how much the distribution of the variable, at its highest level of spatial disaggregation, will change when it is spatially aggregated. Through a computational experiment, we obtain the basis for the design of the statistical test under the null hypothesis of non-sensitivity to MAUP. We performed an exhaustive simulation study for approaching the empirical distribution of the statistical test, obtaining its critical values, and computing its power and size. The results indicate that, in general, both the statistical size and power improve with increasing sample size. Finally, for illustrative purposes, an empirical application is made using the Mincer equation in South Africa, where starting from 206 municipalities, the S-maup statistic is used to find the maximum level of spatial aggregation that avoids the negative consequences of the MAUP. [ABSTRACT FROM AUTHOR]

Coordination is essential for improving supply chain performance, and one of the most critical factors in achieving the coordination of a supply chain is the integrated research of production and distribution. In this paper, a novel two-stage hybrid solution methodology is proposed. In the first stage, products are processed on the serial machines of multiple manufacturers located in two industrial parks. A fuzzy multi-objective scheduling optimization is performed using a modified non-dominated sorting genetic algorithm II (NSGA-II). The result obtained in the first stage is used in the second stage to optimize the distribution scheduling problem using a modified genetic annealing algorithm (GAA). Finally, simulation results verify both the feasibility and efficiency of the proposed solution methodology. [ABSTRACT FROM AUTHOR]

It is usually assumed that each cooperator contributes equally to different public pools in spatial public goods game. However, it is more reasonable to invest differently according to individual investment preference. In this paper, an extended public goods game, in which cooperators contribute to the groups according to the investment preference, is developed. The investment preference of a cooperator is characterized by the fraction of the cooperator from his/her own memory about a group and the intensity of investment preference is represented by a tunable parameter α. The well-mixed population and the structured population are analyzed under this mechanism. It is shown that the investment preference can give rise to coordination. Moreover, the extensive numerical simulation results show that with the increasing of investment preference density or memory length, the proportion of cooperation can increase monotonously. This is because the investment preference could help cooperators resist the invasion from defectors. Compared with the basic version, the new mechanism is able to promote cooperation effectively. Our research may provide a valuable insight for further exploring the nature of cooperation in the real world. [ABSTRACT FROM AUTHOR]

Since all the known biological systems require water for their basic biochemical processes, one can find several osmoregulation mechanisms on living organisms for adaptation to related environmental challenges. Osmosis is a cellular mechanism of water movement across membranes which is known to be present throughout the tree of life and occurs by either diffusion across the membrane bilayer or by a faster movement mediated by transmembrane channel proteins, called aquaporins. The expression of aquaporins is regulated at, the cellular level, by environment conditions such as hydric stress, therefore allowing the adaptation of organisms to increase salinity in soils, water deprivation and increase beverage intake. Osmosis and diffusion concepts have been described to be difficult to learn, so, in order to promote meaningfull learning, we used a problem-based learning approach that integrates a laboratory activity and a computer simulation model of osmosis and a two phase conceptual mapping. We observed that high school students developed adequate laboratory skills and were able to communicate their results as text and using scientific drawings; and the learning environment was adequate. Therefore we presented a successful implementation case of integrated PBL, in a public portuguese school, that may constitute an example to facilitate the implementation of active inquiry strategies by other teachers, as well as the basis for future research.

A primary goal of the recent investment in sequencing is to detect novel genetic associations in health and disease improving the development of treatments and playing a critical role in precision medicine. While this investment has resulted in an enormous total number of sequenced genomes, individual studies of complex traits and diseases are often smaller and underpowered to detect rare variant genetic associations. Existing genetic resources such as the Exome Aggregation Consortium (>60,000 exomes) and the Genome Aggregation Database (~140,000 sequenced samples) have the potential to be used as controls in these studies. Fully utilizing these and other existing sequencing resources may increase power and could be especially useful in studies where resources to sequence additional samples are limited. However, to date, these large, publicly available genetic resources remain underutilized, or even misused, in large part due to the lack of statistical methods that can appropriately use this summary level data. Here, we present a new method to incorporate external controls in case-control analysis called ProxECAT (Proxy External Controls Association Test). ProxECAT estimates enrichment of rare variants within a gene region using internally sequenced cases and external controls. We evaluated ProxECAT in simulations and empirical analyses of obesity cases using both low-depth of coverage (7x) whole-genome sequenced controls and ExAC as controls. We find that ProxECAT maintains the expected type I error rate with increased power as the number of external controls increases. With an accompanying R package, ProxECAT enables the use of publicly available allele frequencies as external controls in case-control analysis. [ABSTRACT FROM AUTHOR]

We propose a method to accelerate a response of structured overlay networks by reducing the number of hops required to answer multi-queries. In the proposed method, by copying data items to the redundant storage spaces in other storages, a good data placement reflecting co-occurrence structures in the structured overlay network is achieved. We formulate the optimization problem of the data placement in the limited redundant space of the storages as an integer programming. A greedy approach to solve the optimization problem is also proposed. Through several simulations, it is confirmed that the proposed method can reduce the average number of hops required to answer multi-queries by about 30% at the maximum in our simulation settings. The reduction rate of the average number of hops depends on the level of co-occurrence. Further, the reduction of the computation time to solve the optimization problem with the greedy approach is evaluated. We also confirm that the proposed method does not affect load balancing of structured overlay networks. [ABSTRACT FROM AUTHOR]

Background: Mathematical models are increasingly being used to evaluate strategies aiming to achieve the control or elimination of parasitic diseases. Recently, owing to growing realization that process-oriented models are useful for ecological forecasts only if the biological processes are well defined, attention has focused on data assimilation as a means to improve the predictive performance of these models. Methodology and principal findings: We report on the development of an analytical framework to quantify the relative values of various longitudinal infection surveillance data collected in field sites undergoing mass drug administrations (MDAs) for calibrating three lymphatic filariasis (LF) models (EPIFIL, LYMFASIM, and TRANSFIL), and for improving their predictions of the required durations of drug interventions to achieve parasite elimination in endemic populations. The relative information contribution of site-specific data collected at the time points proposed by the WHO monitoring framework was evaluated using model-data updating procedures, and via calculations of the Shannon information index and weighted variances from the probability distributions of the estimated timelines to parasite extinction made by each model. Results show that data-informed models provided more precise forecasts of elimination timelines in each site compared to model-only simulations. Data streams that included year 5 post-MDA microfilariae (mf) survey data, however, reduced each model’s uncertainty most compared to data streams containing only baseline and/or post-MDA 3 or longer-term mf survey data irrespective of MDA coverage, suggesting that data up to this monitoring point may be optimal for informing the present LF models. We show that the improvements observed in the predictive performance of the best data-informed models may be a function of temporal changes in inter-parameter interactions. Such best data-informed models may also produce more accurate predictions of the durations of drug interventions required to achieve parasite elimination. Significance: Knowledge of relative information contributions of model only versus data-informed models is valuable for improving the usefulness of LF model predictions in management decision making, learning system dynamics, and for supporting the design of parasite monitoring programmes. The present results further pinpoint the crucial need for longitudinal infection surveillance data for enhancing the precision and accuracy of model predictions of the intervention durations required to achieve parasite elimination in an endemic location. [ABSTRACT FROM AUTHOR]

Background: The Supplemental Nutrition Assistance Program (SNAP) provides approximately US$70 billion annually to support food purchases by low-income households, supporting approximately 1 in 7 Americans. In the 2018 Farm Bill, potential SNAP revisions to improve diets and health could include financial incentives, disincentives, or restrictions for certain foods. However, the overall and comparative impacts on health outcomes and costs are not established. We aimed to estimate the health impact, program and healthcare costs, and cost-effectiveness of food incentives, disincentives, or restrictions in SNAP.Methods and Findings: We used a validated microsimulation model (CVD-PREDICT), populated with national data on adult SNAP participants from the National Health and Nutrition Examination Survey (NHANES) 2009-2014, policy effects from SNAP pilots and food pricing meta-analyses, diet-disease effects from meta-analyses, and policy, food, and healthcare costs from published literature to estimate the overall and comparative impacts of 3 dietary policy interventions: (1) a 30% incentive for fruits and vegetables (F&V), (2) a 30% F&V incentive with a restriction of sugar-sweetened beverages (SSBs), and (3) a broader incentive/disincentive program for multiple foods that also preserves choice (SNAP-plus), combining 30% incentives for F&V, nuts, whole grains, fish, and plant-based oils and 30% disincentives for SSBs, junk food, and processed meats. Among approximately 14.5 million adults on SNAP at baseline with mean age 52 years, our simulation estimates that the F&V incentive over 5 years would prevent 38,782 cardiovascular disease (CVD) events, gain 18,928 quality-adjusted life years (QALYs), and save $1.21 billion in healthcare costs. Adding SSB restriction increased gains to 93,933 CVD events prevented, 45,864 QALYs gained, and $4.33 billion saved. For SNAP-plus, corresponding gains were 116,875 CVD events prevented, 56,056 QALYs gained, and $5.28 billion saved. Over a lifetime, the F&V incentive would prevent approximately 303,900 CVD events, gain 649,000 QALYs, and save $6.77 billion in healthcare costs. Adding SSB restriction increased gains to approximately 797,900 CVD events prevented, 2.11 million QALYs gained, and $39.16 billion in healthcare costs saved. For SNAP-plus, corresponding gains were approximately 940,000 CVD events prevented, 2.47 million QALYs gained, and $41.93 billion saved. From a societal perspective (including programmatic costs but excluding food subsidy costs as an intra-societal transfer), all 3 scenarios were cost-saving. From a government affordability perspective (i.e., incorporating food subsidy costs, including for children and young adults for whom no health gains were modeled), the F&V incentive was of low cost-effectiveness at 5 years (incremental cost-effectiveness ratio: $548,053/QALY) but achieved cost-effectiveness ($66,525/QALY) over a lifetime. Adding SSB restriction, the intervention was cost-effective at 10 years ($68,857/QALY) and very cost-effective at 20 years ($26,435/QALY) and over a lifetime ($5,216/QALY). The combined incentive/disincentive program produced the largest health gains and reduced both healthcare and food costs, with net cost-savings of $10.16 billion at 5 years and $63.33 billion over a lifetime. Results were consistent in probabilistic sensitivity analyses: for example, from a societal perspective, 1,000 of 1,000 iterations (100%) were cost-saving for all 3 interventions. Due to the nature of simulation studies, the findings cannot prove the health and cost impacts of national SNAP interventions.Conclusions: Leveraging healthier eating through SNAP could generate substantial health benefits and be cost-effective or cost-saving. A combined food incentive/disincentive program appears most effective and may be most attractive to policy-makers. [ABSTRACT FROM AUTHOR]

Previous research shows that virtual reality perspective-taking experiences (VRPT) can increase prosocial behavior toward others. We extend this research by exploring whether this effect of VRPT is driven by increased empathy and whether the effect extends to ostensibly real-stakes behavioral games. In a pre-registered laboratory experiment (N = 180), participants interacted with an ostensible partner (a student from the same university as them) on a series of real-stakes economic games after (a) taking the perspective of the partner in a virtual reality, “day-in-the-life” simulation, (b) taking the perspective of a different person in a “day-in-the-life” simulation, or (c) doing a neutral activity in a virtual environment. The VRPT experience successfully increased participants’ subsequent propensity to take the perspective of their partner (a facet of empathy), but only if the partner was the same person whose perspective participants assumed in the virtual reality simulation. Further, this effect of VRPT on perspective-taking was moderated by participants’ reported feeling of immersion in the virtual environment. However, we found no effects of VRPT experience on behavior in the economic games. [ABSTRACT FROM AUTHOR]

Background and objective: Markov micro-simulation models are being increasingly used in health economic evaluations. An important feature of the Markov micro-simulation model is its ability to consider transition probabilities of heterogeneous subgroups with different risk profiles. A survival analysis is generally performed to accurately estimate the transition probabilities associated with the risk profiles. This study aimed to apply a flexible parametric survival model (FPSM) to estimate individual transition probabilities. Materials and methods: The data were obtained from a cohort study investigating ischemic stroke outcomes in Western China. In total, 585 subjects were included in the analysis. To explore the goodness of fit of the FPSM, we compared the estimated hazard ratios and baseline cumulative hazards, both of which are necessary to the calculate individual transition probabilities, and the Markov micro-simulation models constructed using the FPSM and Cox model to determine the validity of the two Markov micro-simulation models and cost-effectiveness results. Results: The flexible parametric proportional hazards model produced hazard ratio and baseline cumulative hazard estimates that were similar to those obtained using the Cox proportional hazards model. The simulated cumulative incidence of recurrent ischemic stroke and 5-years cost-effectiveness of Incremental cost-effectiveness Ratios (ICERs) were also similar using the two approaches. A discrepancy in the results was evident between the 5-years cost-effectiveness and the 10-years cost-effectiveness of ICERs, which were approximately 0.9 million (China Yuan) and 0.5 million (China Yuan), respectively. Conclusions: The flexible parametric survival model represents a good approach for estimating individual transition probabilities for a Markov micro-simulation model. [ABSTRACT FROM AUTHOR]

Purpose: Measuring accurate thresholds in children can be challenging. A typical psychophysical experiment is usually too long to keep children engaged. However, a reduction in the number of trials decreases the precision of the threshold estimate. We evaluated the efficiency of forced-choice paradigms with 2 or 4 alternatives (2-AFC, 4-AFC) in a disparity detection experiment. 4-AFC paradigms are statistically more efficient, but also more cognitively demanding, which might offset their theoretical advantage in young children. Methods: We ran simulations evaluating bias and precision of threshold estimates of 2-AFC and 4-AFC paradigms. In addition, we measured disparity thresholds in 43 children (aged 6 to 17 years) with a 4-AFC paradigm and in 49 children (aged 4 to 17 years) with a 2-AFC paradigm, both using an adaptive weighted one-up one-down staircase. Results: Simulations indicated a similar bias and precision for a 2-AFC paradigm with double the number of trials as a 4-AFC paradigm. On average, estimated threshold of the simulated data was equal to the model threshold, indicating no bias. The precision was improved with an increasing number of trials. Likewise, our data showed a similar bias and precision for a 2-AFC paradigm with 60 trials as for a 4-AFC paradigm with 30 trials. Trials in the 4-AFC paradigm took slightly longer as participants scanned more alternatives. However, the 4-AFC task still ended up faster for a given precision. Conclusion: Bias and precision were similar in a 4-AFC task compared to a 2-AFC task with double the number of trials. However, a 4-AFC paradigm was more time efficient and is therefore recommended. [ABSTRACT FROM AUTHOR]

Iterative prototyping is costly and time-consuming. Particularly when designing medical instruments, human factors related design choices significantly impact performance and safety. A tool is presented that allows for the evaluation of steerable instrument controls before the onset of the prototyping stage. The design tool couples gestural input to virtually simulated instrument motions using hand motion tracking. We performed a human-subject evaluation of two manual control strategies that differed in their degrees of freedom (DOF). 2DOF thumb control was compared to 4DOF thumb-index finger control. Results identified regions within the instrument workspace that are difficult to reach and showed participants to favor using the thumb for gross and fine-tuning motions at both control strategies. Index finger ab/adduction was found to be least functional. A strong learning effect was observed at 4DOF control. Based on the results, gesture-based instrument design is a viable design tool. [ABSTRACT FROM AUTHOR]

We examine two possible approaches to reducing residential mortgage default using a dynamic model of heterogeneous infinitely-lived agents acting optimally subject to uninsurable idiosyncratic earnings shocks and systemic house price shocks. We find higher down payments are very effective in minimizing residential mortgage foreclosures, even in periods of house price declines and recessions. In contrast, the length of the credit exclusionary period for people who experience bankruptcy or foreclosure has a much smaller impact on mortgage defaults. Thus, it is much more effective to prevent mortgage default before the mortgage closes than to pressure homeowners not to default once they are in financial trouble. This also suggests a major aspect of credit scores and credit policy is non-productive and punitive, harming people in return for little societal gain. [ABSTRACT FROM AUTHOR]

This paper focuses on the effects of vehicle gap changes on fuel and emission performance of the simulated traffic flow in the adaptive cruise control (ACC) strategy. Firstly, the close correlation of vehicle gap changes and the host car's behaviors was explored with the measured car-following data. Secondly, the correlation between the host car's velocity and vehicle gap changes with different memory steps was also explored to develop the nth car’s optimal velocity function. Thirdly, a microscopic traffic simulation program was created for analyzing the traffic flow evolution process and approximately estimating the fuel consumptions and exhaust emissions. As a result, it was seen that vehicle gap changes with memory significantly affect fuel economy and emission performance of the simulated traffic flow in the ACC strategy, which can result in low fuel consumptions and exhaust emissions. This study is an incremental step forward for designing the control strategy of the ACC system. [ABSTRACT FROM AUTHOR]