A Flexible Comparison Process as a Critical Mechanism for Context Effects

Context effects such as the attraction, compromise, and similarity effects demonstrate that a comparison process, i.e., a method of comparing dimension values, plays an important role in choice behavior. Recent research suggests that this same comparison process, made more flexible by allowing for a variety of comparisons, may provide an elegant account of observed correlations between context effects by differentially highlighting dimension-level and alternative-level stimulus characteristics. Thus, the present experiments test the comparison process as a critical mechanism underlying context-dependent choice behavior. Experiment 1 provides evidence that increasing a dimension-level property, spread, promotes the attraction and compromise effects and reduces the similarity effect, whereas increasing an alternative-level property, dispersion, introduces an alternative-level bias that influences choice in concert with the decoy. Experiment 2 utilizes eyetracking to test the influence of stimulus presentation format on information acquisition patterns and context-dependent choice behavior. Contrary to predictions, a By-Alternative presentation format appears to increase within-dimension transitions in eye fixations relative to a By-Dimension presentation format. Lastly, four computational models with theoretical accounts of the development of context effects over time were fit to joint choice and response time data. Though the MLBA provided the best fits to the subject-level mean choice proportions, it could not capture the crossover in preference between the target and competitor across RT quantiles; rather, MDFT and the AAM performed best in this regard. The present work therefore not only provides new insights into the relationship between choice and response times in preferential choice but sets important new constraints for theoretical models that seek to account for such behavior

The Influence of Discrete Emotional States on Preferential Choice

Past research has shown that emotion affects preferential choice outcomes. The goal of the present study was to further research on emotion and preferential choice by using mathematical modeling to investigate the effects of specific dimensions of emotion on the underlying mechanisms of preferential choice. Specifically, we aimed to determine whether the concurrent effects of positive-negative valence and situational certainty on attention and information accumulation threshold, respectively, would influence the magnitude of the similarity effect, a robust phenomenon in preferential choice. Participants first underwent either an Anger (negative and certain), Fear (negative and uncertain), or no (Control) emotion manipulation. All participants then completed an apartment choice task that was designed to elicit the similarity effect. A novel framing manipulation was used to test the effects of emotional valence on attention. Both feature framing and emotion condition significantly affected choice outcomes. These results suggest differences in deliberation style between Anger and Fear participants, as well as a surprising impact of alternatives outside the choice set on choice outcomes. Future directions are discussed

Estimating the proportion of guilty suspects and posterior probability of guilt in lineups using signal-detection models

Background The majority of eyewitness lineup studies are laboratory-based. How well the conclusions of these studies, including the relationship between confidence and accuracy, generalize to real-world police lineups is an open question. Signal detection theory (SDT) has emerged as a powerful framework for analyzing lineups that allows comparison of witnesses’ memory accuracy under different types of identification procedures. Because the guilt or innocence of a real-world suspect is generally not known, however, it is further unknown precisely how the identification of a suspect should change our belief in their guilt. The probability of guilt after the suspect has been identified, the posterior probability of guilt (PPG), can only be meaningfully estimated if we know the proportion of lineups that include a guilty suspect, P(guilty). Recent work used SDT to estimate P(guilty) on a single empirical data set that shared an important property with real-world data; that is, no information about the guilt or innocence of the suspects was provided. Here we test the ability of the SDT model to recover P(guilty) on a wide range of pre-existing empirical data from more than 10,000 identification decisions. We then use simulations of the SDT model to determine the conditions under which the model succeeds and, where applicable, why it fails. Results For both empirical and simulated studies, the model was able to accurately estimate P(guilty) when the lineups were fair (the guilty and innocent suspects did not stand out) and identifications of both suspects and fillers occurred with a range of confidence levels. Simulations showed that the model can accurately recover P(guilty) given data that matches the model assumptions. The model failed to accurately estimate P(guilty) under conditions that violated its assumptions; for example, when the effective size of the lineup was reduced, either because the fillers were selected to be poor matches to the suspect or because the innocent suspect was more familiar than the guilty suspect. The model also underestimated P(guilty) when a weapon was shown. Conclusions Depending on lineup quality, estimation of P(guilty) and, relatedly, PPG, from the SDT model can range from poor to excellent. These results highlight the need to carefully consider how the similarity relations between fillers and suspects influence identifications

model predictive control tools for evolutionary plants

The analysis and design of control system configurations for automated production systems is generally a challenging problem, in particular given the increasing number of automation devices and the amount of information to be managed. This problem becomes even more complex when the production system is characterized by a fast evolutionary behaviour in terms of tasks to be executed, production volumes, changing priorities, and available resources. Thus, the control solution needs to be optimized on the basis of key performance indicators like flow production, service level, job tardiness, peak of the absorbed electrical power and the total energy consumed by the plant. This paper proposes a prototype control platform based on Model Predictive Control (MPC) that is able to impress to the production system the desired functional behaviour. The platform is structured according to a two-level control architecture. At the lower layer, distributed MPC algorithms control the pieces of equipment in the production system. At the higher layer an MPC coordinator manages the lower level controllers, by taking full advantage of the most recent advances in hybrid control theory, dynamic programming, mixed‐integer optimization, and game theory. The MPC-based control platform will be presented and then applied to the case of a pilot production plant

Molecular analysis of endocrine disruption in hornyhead turbot at wastewater outfalls in southern california using a second generation multi-species microarray.

Sentinel fish hornyhead turbot (Pleuronichthysverticalis) captured near wastewater outfalls are used for monitoring exposure to industrial and agricultural chemicals of ~ 20 million people living in coastal Southern California. Although analyses of hormones in blood and organ morphology and histology are useful for assessing contaminant exposure, there is a need for quantitative and sensitive molecular measurements, since contaminants of emerging concern are known to produce subtle effects. We developed a second generation multi-species microarray with expanded content and sensitivity to investigate endocrine disruption in turbot captured near wastewater outfalls in San Diego, Orange County and Los Angeles California. Analysis of expression of genes involved in hormone [e.g., estrogen, androgen, thyroid] responses and xenobiotic metabolism in turbot livers was correlated with a series of phenotypic end points. Molecular analyses of turbot livers uncovered altered expression of vitellogenin and zona pellucida protein, indicating exposure to one or more estrogenic chemicals, as well as, alterations in cytochrome P450 (CYP) 1A, CYP3A and glutathione S-transferase-α indicating induction of the detoxification response. Molecular responses indicative of exposure to endocrine disruptors were observed in field-caught hornyhead turbot captured in Southern California demonstrating the utility of molecular methods for monitoring environmental chemicals in wastewater outfalls. Moreover, this approach can be adapted to monitor other sites for contaminants of emerging concern in other fish species for which there are few available gene sequences

Large-scale implementation of a new TDR-based system for the monitoring of pipe leaks

In this paper, the practical implementation of an innovative time domain reflectometry (TDR)-based system for leak detection in underground water pipes is presented. This system, which had been previously developed and experimented on pilot plants, has now been installed (for the first time) on a large scale, in 10 km of pipes. The present work describes all the practical aspects and technical details (from the design to the functional tests), related to the implementation of the system

Negative Life Events and Non-Suicidal Self-Injury in an Adolescent Inpatient Sample

Although life stressors have been implicated in the aetiology of various forms of psychopathology related to non-suicidal self-injury (NSSI), particularly depression and suicidal behavior, they have rarely been examined in relation with NSSI. The objective of the current study was to assess the association between life stressors and NSSI in adolescent inpatients

Sex-related differences in risk factors, type of treatment received and outcomes in patients with atrial fibrillation and acute stroke: Results from the RAF-study (Early Recurrence and Cerebral Bleeding in Patients with Acute Ischemic Stroke and Atrial Fibrillation)

Introduction: Atrial fibrillation is an independent risk factor of thromboembolism. Women with atrial fibrillation are at a higher overall risk for stroke compared to men with atrial fibrillation. The aim of this study was to evaluate for sex differences in patients with acute stroke and atrial fibrillation, regarding risk factors, treatments received and outcomes. Methods Data were analyzed from the “Recurrence and Cerebral Bleeding in Patients with Acute Ischemic Stroke and Atrial Fibrillation” (RAF-study), a prospective, multicenter, international study including only patients with acute stroke and atrial fibrillation. Patients were followed up for 90 days. Disability was measured by the modified Rankin Scale (0–2 favorable outcome, 3–6 unfavorable outcome). Results: Of the 1029 patients enrolled, 561 were women (54.5%) (p < 0.001) and younger (p < 0.001) compared to men. In patients with known atrial fibrillation, women were less likely to receive oral anticoagulants before index stroke (p = 0.026) and were less likely to receive anticoagulants after stroke (71.3% versus 78.4%, p = 0.01). There was no observed sex difference regarding the time of starting anticoagulant therapy between the two groups (6.4 ± 11.7 days for men versus 6.5 ± 12.4 days for women, p = 0.902). Men presented with more severe strokes at onset (mean NIHSS 9.2 ± 6.9 versus 8.1 ± 7.5, p < 0.001). Within 90 days, 46 (8.2%) recurrent ischemic events (stroke/TIA/systemic embolism) and 19 (3.4%) symptomatic cerebral bleedings were found in women compared to 30 (6.4%) and 18 (3.8%) in men (p = 0.28 and p = 0.74). At 90 days, 57.7% of women were disabled or deceased, compared to 41.1% of the men (p < 0.001). Multivariate analysis did not confirm this significance. Conclusions: Women with atrial fibrillation were less likely to receive oral anticoagulants prior to and after stroke compared to men with atrial fibrillation, and when stroke occurred, regardless of the fact that in our study women were younger and with less severe stroke, outcomes did not differ between the sexes

Stochastic models for the in silico simulation of synaptic processes

Background: Research in life sciences is benefiting from a large availability of formal description techniques and analysis methodologies. These allow both the phenomena investigated to be precisely modeled and virtual experiments to be performed in silico. Such experiments may result in easier, faster, and satisfying approximations of their in vitro/vivo counterparts. A promising approach is represented by the study of biological phenomena as a collection of interactive entities through process calculi equipped with stochastic semantics. These exploit formal grounds developed in the theory of concurrency in computer science, account for the not continuous, nor discrete, nature of many phenomena, enjoy nice compositional properties and allow for simulations that have been demonstrated to be coherent with data in literature. Results: Motivated by the need to address some aspects of the functioning of neural synapses, we have developed one such model for synaptic processes in the calyx of Held, which is a glutamatergic synapse in the auditory pathway of the mammalia. We have developed such a stochastic model starting from existing kinetic models based on ODEs of some sub-components of the synapse, integrating other data from literature and making some assumptions about non-fully understood processes. Experiments have confirmed the coherence of our model with known biological data, also validating the assumptions made. Our model overcomes some limitations of the kinetic ones and, to our knowledge, represents the first model of synaptic processes based on process calculi. The compositionality of the approach has permitted us to independently focus on tuning the models of the pre- and post- synaptic traits, and then to naturally connect them, by dealing with “interface” issues. Furthermore, we have improved the expressiveness of the model, e.g. by embedding easy control of element concentration time courses. Sensitivity analysis over several parameters of the model has provided results that may help clarify the dynamics of synaptic transmission, while experiments with the model of the complete synapse seem worth explaining short-term plasticity mechanisms. Conclusions: Specific presynaptic and postsynaptic mechanisms can be further analysed under various conditions, for instance by studying the presynaptic behaviour under repeated activations. The level of details of the description can be refined, for instance by further specifying the neurotransmitter generation and release steps. Taking advantage of the compositionality of the approach, an enhanced model could then be composed with other neural models, designed within the same framework, in order to obtain a more detailed and comprehensive model. In the long term, we are interested, in particular, in addressing models of synaptic plasticity, i.e. activity dependent mechanisms, which are the bases of memory and learning processes. More on the computer science side, we plan to follow some directions to improve the underlying computational model and the linguistic primitives it provides as suggested by the experiments carried out, e.g. by introducing a suitable notion of (spatial) locality

AtopyReg®, the Prospective Italian Patient Registry for Moderate-to-Severe Atopic Dermatitis in Adults: Baseline Demographics, Disease Characteristics, Comorbidities, and Treatment History

background and objective atopyReg((R)) is a multicenter, prospective, observational, non-profit cohort study on moderate-tosevere atopic dermatitis in adults promoted in 2018 by the Italian society of dermatology and Venereology (SIDeMaST). we aimed to describe baseline demographics, disease characteristics, comorbidities, and therapeutic data of adult patients affected by moderate-to-severe atopic dermatitis.methods patients were selected based on the following inclusion criteria: age >= 18 years; eczema area and severity Index score >= 7 or a numeric rating scale sleep loss score = 7, or a dermatology life quality Index score >= 10. score >= 16 or localization in visible or sensitive areas (face, neck, hands, or genitalia), or a numeric rating scale itchDemographic and clinical data at baseline were recorded and analyzed. results a total of 1170 patients (male 51.1%; mean age: 44.7 years; range 18-90 years) were enrolled by 12 Italian dermatology units between January 2019 and november 2022. skin lesions were eczematous in 83.2% of patients, the most involved site were the flexures (53.9%), face (50.9%), and neck (48.0%). mean eczema area and severity Index score was 22.3, mean dermatology life quality Index value was 17.6, mean patient oriented Eczema measure score was 13.1, and mean numeric rating scale itch and sleep loss scores were 7.6 and 5.9, respectively. previous systemic therapies were corticosteroids in 77.7% of patients, antihistamines in 50.3% of patients, and cyclosporine A in 42.6% of patients.conclusions this baseline data analysis deriving from atopyReg((R)) provides real-life evidence on patients with moderate-to-severe atopic dermatitis in Italy confirming the high burden of atopic dermatitis with a significant impact on patients' quality of life