Choice Mechanisms Research Articles

Does Proximity to MRT Stations Affect Online Shopping Use? An Analysis Using Data from Japan and New York

The rapid growth of the e-commerce market in the retail sector has led to a greater demand for home delivery services in recent years. In order to develop policies to address the issues related to delivery demand, it is critical to understand the demand mechanism of online shopping. Furthermore, the relationship between proximity to mass rapid transit and shopping mode choice mechanisms has not been studied, although, in the field of urban design, accessibility to mass rapid transit is known to affect travel behaviors. We focus on the relationship between proximity to mass rapid transit stations and the shopping mode choice mechanism and estimate structural equation models, considering in-person and online shopping propensities as the latent variables. We use the two datasets. One is from a web-based survey of online shoppers in Japan. The other is the 2019 NYC Citywide Mobility Survey data. The results based on Japanese survey data indicate a clear difference in shopping mode choice mechanisms between MRT-dependent neighborhoods and non-MRT-dependent neighborhoods, while such a difference is limited in NYC. Furthermore, the study reveals how individual and household characteristics and accessibility indicators affect online shopping propensity based on the type of neighborhood and city/country.

Contribution of amygdala to dynamic model arbitration under uncertainty.

Intrinsic uncertainty in the reward environment requires the brain to run multiple models simultaneously to predict outcomes based on preceding cues or actions, commonly referred to as stimulus- and action-based learning. Ultimately, the brain also must adopt appropriate choice behavior using reliability of these models. Here, we combined multiple experimental and computational approaches to quantify concurrent learning in monkeys performing tasks with different levels of uncertainty about the model of the environment. By comparing behavior in control monkeys and monkeys with bilateral lesions to the amygdala or ventral striatum, we found evidence for dynamic, competitive interaction between stimulus-based and action-based learning, and for a distinct role of the amygdala. Specifically, we demonstrate that the amygdala adjusts the initial balance between the two learning systems, thereby altering the interaction between arbitration and learning that shapes the time course of both learning and choice behaviors. This novel role of the amygdala can account for existing contradictory observations and provides testable predictions for future studies into circuit-level mechanisms of flexible learning and choice under uncertainty.

Cryptic female choice in response to male pheromones in Drosophila melanogaster

Females control the paternity of their offspring by selectively mating with males they perceive to be of high quality. In species where females mate with multiple males in succession, females may bias offspring paternity by favoring the sperm of one male over another, a process known as cryptic female choice.1 While evidence of cryptic female choice exists in multiple taxa, the mechanisms underlying this process have remained difficult to unravel.2 Understanding cryptic female choice requires demonstration of a female-driven post-mating bias in sperm use and paternity and a causal link between this bias and male cues.3 In this study, we present evidence of cryptic female choice in female Drosophila melanogaster. Through experiments utilizing transgenic males expressing fluorescent sperm, we observed that exposure to attractive males between matings prompts females to expel the ejaculate of their initial mate more rapidly than in the presence of less attractive males. While doing so, females exhibit a bias in sperm storage against their first mate, thereby favoring the paternity of their subsequent mate. Our findings reveal that females adjust the timing of ejaculate expulsion in response to male pheromones in their environment, specifically heptanal and 11-cis-vaccenyl acetate, which are sensed by females through specific odorant receptors. We provide a cryptic female choice mechanism allowing a female to modulate the share of paternity of her first mate depending on the sensing of the quality of potential mates in her environment. These findings showcase that paternity can be influenced by events beyond copulation.

Molecular, Cellular, and Developmental Organization of the Mouse Vomeronasal organ at Single Cell Resolution.

We have generated single cell transcriptomic atlases of vomeronasal organs (VNO) from juvenile and adult mice. Combined with spatial molecular imaging, we uncover a distinct, previously unidentified class of cells that express the vomeronasal receptors and a population of canonical olfactory sensory neurons in the VNO. High resolution trajectory and cluster analyses reveal the lineage relationship, spatial distribution of cell types, and a putative cascade of molecular events that specify the V1r, V2r, and OR lineages from a common stem cell population. The expression of vomeronasal and olfactory receptors follow power law distributions, but there is high variability in average expression levels between individual receptor and cell types. Substantial co-expression is found between receptors across clades, from different classes, and between olfactory and vomeronasal receptors, with nearly half from pairs located on the same chromosome. Interestingly, the expression of V2r, but not V1r, genes is associated with various transcription factors, suggesting distinct mechanisms of receptor choice associated with the two cell types. We identify association between transcription factors, surface axon guidance molecules, and individual VRs, thereby uncovering a molecular code that guides the specification of the vomeronasal circuitry. Our study provides a wealth of data on the development and organization of the accessory olfactory system at both cellular and molecular levels to enable a deeper understanding of vomeronasal system function.

Natural variation in sexual traits and gene expression between selfing and outcrossing Arabidopsis lyrata suggests sexual selection at work.

Flowering plants show significant diversity in sexual strategies, profoundly impacting the evolution of sexual traits and associated genes. Sexual selection is one of the primary evolutionary forces driving sexual trait variation, particularly evident during pollen-pistil interactions, where pollen grains compete for fertilization and females select mating partners. Multiple mating may intensify competition among pollen donors for siring, while in contrast, self-fertilization reduces sire-sire competition, relaxing the sexual selection pressure. Traits involved in male-male competition and female choice are well described, and molecular mechanisms underlying pollen development and pollen-pistil interactions have been extensively studied in the model species Arabidopsis thaliana. However, whether these molecular mechanisms are involved in sexual selection in nature remains unclear. To address this gap, we measured intrinsic pollen performance and its interaction with female choice, and investigated the associated gene expression patterns in a selfing and an outcrossing population of Arabidopsis lyrata. We found that pollen germination and pollen tube growth were significantly higher in outcrossers than selfers, and this difference was accompanied by changes in expression of genes involved in vesicle transport and cytoskeleton. Outcrosser mother plants showed a negative impact on pollen tube growth compared to selfer mother plants, together with a difference of expression for genes involved in auxin and stress response, suggesting a potential mechanism for female choice through molecular crosstalk at the post-pollination stage. Our study provides insight on the impact of sexual selection on the evolution of sexual gene expression in plants.

Improving Time to Antibiotics for Long-Bone Open Fractures: A Quality Improvement Initiative.

Open fractures, which are exposed to the external environment, are at a high risk of infection. Administering antibiotics within 60 minutes of emergency department (ED) arrival is crucial to prevent infection. However, this is difficult to achieve due to high ED patient volumes. The purpose of our project was to improve time to antibiotics for patients presenting with long-bone open fractures at a Level 1 trauma center ED. We used the Lean Six Sigma Define, Measure, Analyze, Improve, and Control project framework to guide our efforts. Our interventions composed of developing educational initiatives, creating an electronic medical record order set, and restructuring the ED workflow to prioritize long-bone open fractures for immediate evaluation and antibiotic administration in our critical care zone. After our intervention, the time to antibiotics for long-bone open fractures improved significantly, decreasing from 76 to 40 minutes (p < .001), with the percentage of patients receiving antibiotics within 60 minutes of ED arrival increasing from 64% to 92% (p < .001). Age, sex, mechanism of injury, antibiotic choice, and location of the open fracture remained consistent between the two groups. Our results highlight the successful application of process improvement methodologies in improving antibiotic administration time for long-bone open fractures.

A practical method to draw from multivariate extreme value distributions

Generating random draws from multivariate extreme value (MEV) distributions plays an important role in the microsimulation of travel behaviors, which can effectively avoid heavy computational burdens from simulation based on calculated probability values, particularly in simulations for a large population or choice behaviors from a large choice set. However, there are few practical and effective methods for drawing from MEV distributions. This paper proposes a simple and computationally efficient approach for drawing from MEV distributions in the nested logit (NL), cross-nested logit (CNL), and paired combinatorial logit (PCL) models. The proposed approach to draw from the MEV distribution for a CNL model provides a new perspective to understand the underlying choice mechanism of the CNL model. To our knowledge, this is the first study to draw from an MEV distribution in the PCL model. Random draws from the proposed approach approximately follow the standard Gumbel distribution, which is the marginal distribution of NL/CNL/PCL models, and approximate correlations among alternatives well. Simulation results of NL/CNL/PCL models show that the proposed approach provides high-level accuracy in recovering model parameters with the overall mean absolute percentage bias being less than 3%. The proposed approach is computationally more efficient than similar ones because it only needs to draw from Gumbel distributions. The proposed approach can be used to simulate NL/CNL/PCL models with a large choice set or a multiple discrete-continuous generalized extreme value model in various application settings such as joint destination-mode choices, time use allocations, etc.

The active time model of concurrent choice.

The following paper describes a steady-state model of concurrent choice, termed the active time model (ATM). ATM is derived from maximization principles and is characterized by a semi-Markov process. The model proposes that the controlling stimulus in concurrent variable-interval (VI) VI schedules of reinforcement is the time interval since the most recent response, termed here "the active interresponse time" or simply "active time." In the model after a response is generated, it is categorized by a function that relates active times to switch/stay probabilities. In the paper the output of ATM is compared with predictions made by three other models of operant conditioning: melioration, a version of scalar expectancy theory (SET), and momentary maximization. Data sets considered include preferences in multiple-concurrent VI VI schedules, molecular choice patterns, correlations between switching and perseveration, and molar choice proportions. It is shown that ATM can account for all of these data sets, while the other models produce more limited fits. However, rather than argue that ATM is the singular model for concurrent VI VI choice, a consideration of its concept space leads to the conclusion that operant choice is multiply-determined, and that an adaptive viewpoint-one that considers experimental procedures both as selecting mechanisms for animal choice as well as tests of the controlling variables of that choice-is warranted.

A Novel Real-Time Coordinated Ridesharing Route Choice Mechanism

A Novel Real-Time Coordinated Ridesharing Route Choice Mechanism

Exploring the Pedestrian Route Choice Behaviors by Machine Learning Models

To investigate pedestrian route choice mechanisms from a perspective distinct from that employed in discrete choice models (DCMs), this study utilizes machine learning models and employs SHapley Additive exPlanations (SHAP) for model interpretation. The data used in this paper come from several pedestrian flow experiments with two routes, which were recorded by UAV. Our findings indicate that logistic regression (similar to a binary logit model) exhibits good computational efficiency but falls short in predictive accuracy when compared to other machine learning models. Among the 12 machine learning models assessed, by calculating the new indicator named OP, we find that eXtreme Gradient Boosting (XGB) and Light Gradient Boosting (LGB) strike the best balance between accuracy and computational efficiency. Regarding feature contribution, our analysis reveals that bottlenecks exert the most significant influence on pedestrian route choice behavior, followed by the time it takes pedestrians to return from the end of the route to the origin (reflecting pedestrian characteristics and attitudes). While the pedestrian density of the shorter route contributes less compared to bottlenecks and return time, it exhibits a threshold effect, meaning that once the density of the shorter route surpasses a certain threshold, most pedestrians opt for the longer route.

Redistribution Methods for Income Equality in the United States

&#x0D; &#x0D; &#x0D; &#x0D; Redistribution for income equality is a contentious issue, with advocates citing increased economic stability and skeptics fearing potential negative impacts on economic growth. The United States (U.S.) faces notably high income inequality compared to the Organisation for Economic Co-operation and Development (OECD) average, with wealth concentrated in the top brackets. This paper critically examines the existing U.S. redistribution methods, including the taxation system and welfare programs, highlighting challenges such as the lack of tax progressiveness in top brackets and limited redistribution compared to European counterparts. Based on this overview, the study evaluates alternative redistribution strategies, including wealth and business taxes. The paper compares theory with insights from pilot programs in other countries. Finally, the paper argues for a universal basic income (UBI) set at per-capita welfare spending, positing that this approach can empower individuals to escape poverty traps, enhance productivity, and introduce a choice mechanism for welfare consumption. Ultimately, this research seeks to propose the most effective and feasible income redistribution policies for the U.S. to bridge the income inequality gap.&#x0D; &#x0D; &#x0D; &#x0D;

Modifications of Boston, Taiwanese and Chinese mechanisms are not comparable via counting manipulating students

We examine incentive compatibility of various school choice mechanisms as measured by the number of manipulating students. We find that Boston with Skips Mechanism, Secure Boston Mechanism, and Chinese Mechanism may have more manipulating students than Boston Mechanism. Similarly, Taiwan Mechanism with smaller deductions may induce more manipulating students than Taiwan Mechanism with larger deductions. Computational simulations show that on average Secure Boston Mechanism and especially Chinese Mechanism have fewer manipulating students than Boston Mechanism, while Boston with Skips Mechanism performs slightly worse than Boston Mechanism.

Molecular mechanisms of differentiation and class choice of olfactory sensory neurons.

The sense of smell is intricately linked to essential animal behaviors necessary for individual survival and species preservation. During vertebrate evolution, odorant receptors (ORs), responsible for detecting odor molecules, have evolved to adapt to changing environments, transitioning from aquatic to terrestrial habitats and accommodating increasing complex chemical environments. These evolutionary pressures have given rise to the largest gene family in vertebrate genomes. Vertebrate ORs are phylogenetically divided into two major classes; class I and class II. Class I OR genes, initially identified in fish and frog, have persisted across vertebrate species. On the other hand, class II OR genes are unique to terrestrial animals, accounting for ~90% of mammalian OR genes. In mice, each olfactory sensory neuron (OSN) expresses a single functional allele of a single OR gene from either the class I or class II OR repertoire. This one neuron-one receptor rule is established through two sequential steps: specification of OR class and subsequent exclusive OR expression from the corresponding OR class. Consequently, OSNs acquire diverse neuronal identities during the process of OSN differentiation, enabling animals to detect a wide array of odor molecules. This review provides an overview of the OSN differentiation process through which OSN diversity is achieved, primarily using the mouse as a model animal.

The Odorant Receptor Recognizing Camphor in a Camphor Tree Specialist Orthaga achatina (Lepidoptera: Pyralidae).

Camphor has been used as an effective repellent and pesticide to stored products for a long history, but Orthaga achatina (Lepidoptera: Pyralidae) has evolved to specifically feed on the camphor tree Cinnamomum camphora. However, the behavioral response of O. achatina to camphor and the molecular basis of camphor perception are totally unknown. Here, we demonstrated that both male and female adults were behaviorally attracted to camphor, suggesting the adaptation of O. achatina to and utilization of camphor as a signal of C. camphora. Second, in 40 O. achatina OR genes obtained by analyzing antenna transcriptomes, only OachOR16/Orco significantly responded to camphor in the Xenopus oocyte system. Finally, by molecular docking analysis and site-directed mutagenesis, the Ser209 residue is confirmed to be essential for binding of the oachOR16 with camphor. This study not only reveals the camphor-based host plant choice and olfactory mechanisms of O. achatina but also provides a molecular target for screening more potential insect repellents.

Significance of additives to enhance the acceptance of poison bait in poultry rodents of Haripur, Khyber Pakhtunkhwa, Pakistan.

Rodent infestation on poultry farms incurs heavy economic losses to this industry by causing feed loss and disease introduction. Development and continuous improvement of rodents control techniques are vital to minimize and control the damages caused by rodents. Here, we test the feed preference of rodents for locally available and palatable food grains viz. millet (whole), wheat (cracked) and rice (broken) and taste additives namely whole egg (5%), eggshell (5%), peanut cracked (5%) and yeast (2%) that were offered mixed in millet-wheat (50:50 by wt.) bait. We tested the preferences of different food additives through a process of feed choice mechanism. We applied two different techniques to compare the preference of mixed feed baits, these techniques included no-choice with multiple choice feeding tests and paired choice with multiple choices feeding tests. The results indicated that consumption of bait with added whole egg was significantly higher (p > 0.05). Further test for its effectiveness as a carrier for rodenticides revealed 56%, 82% and 92%, reduction in rodent activities with zinc phosphide (2%), coumatetralyl (0.0375%) and Brodifacoum (0.005%) respectively. Our results point to a need on continuous improvement of feed baits by using different combinations to effectively control the rodent infestation.

Neural mechanisms involved in female mate choice in invertebrates.

Mate choice is a critical decision with direct implications for fitness. Although it has been recognized for over 150 years, our understanding of its underlying mechanisms is still limited. Most studies on mate choice focus on the evolutionary causes of behavior, with less attention given to the physiological and molecular mechanisms involved. This is especially true for invertebrates, where research on mate choice has largely focused on male behavior. This review summarizes the current state of knowledge on the neural, molecular and neurohormonal mechanisms of female choice in invertebrates, including behaviors before, during, and after copulation. We identify areas of research that have not been extensively explored in invertebrates, suggesting potential directions for future investigation. We hope that this review will stimulate further research in this area.

Genetic mechanisms of multiciliated cell development: from fate choice to differentiation in zebrafish and other models.

Multiciliated cells (MCCS) form bundles of cilia and their activities are essential for the proper development and physiology of many organ systems. Not surprisingly, defects in MCCs have profound consequences and are associated with numerous disease states. Here, we discuss the current understanding of MCC formation, with a special focus on the genetic and molecular mechanisms of MCC fate choice and differentiation. Furthermore, we cast a spotlight on the use of zebrafish to study MCC ontogeny and several recent advances made in understanding MCCs using this vertebrate model to delineate mechanisms of MCC emergence in the developing kidney.

Application of Various Mechanisms on Students School Choice Problem

School choice mechanisms are used to determine how to assign students to the public schools. These mechanisms take into account the students preferences order and the schools priority order to calculate an assignment that meets the needs and preferences of both students and schools. This paper sketches the school choice problem and its real-life condition in some cities, discusses the theory background of school choice problem and its specialty as a one-side matching problem. Also, this paper introduces the Defer Acceptance (DA) mechanism, the Top Trading Cycle (TTC) mechanism, the Boston (BOS) mechanism and the Serial Dictatorship (SD) mechanism. The paper analyzes four different mechanisms desirable properties, including strategy-proofness, stability and Pareto efficiency. Meanwhile, the flaws of the mechanisms are introduced. At last, based on the analysis and the purpose of improving students welfare, the paper raises some suggestion for the government, schools and parents, ensuring the students a transparent, fair and equal environment of choosing their schools.

Designing school choice mechanisms: A structural model and demand estimation

AbstractDesigning the markets that allocate public school seats is a crucial policy consideration. This paper compares the design of school choice mechanisms in terms of economic efficiency, stability, and strategic behavior. We estimate demand for schools using data from a large US public school system with novel indicators of students' levels of strategic sophistication. We find important benefits of reserving a set of seats to be assigned by a pure lottery. In settings that share features in common with the school system we study, our findings suggest that non‐selective criteria such as lotteries induce a large increase in truth‐telling.

Impact of Intravenous Fat Emulsion Choice on Candida Biofilm, Hyphal Growth, and Catheter-Related Bloodstream Infections in Pediatric Patients.

Use of mixed-oil (MO) intravenous fat emulsion (IFE) was shown to inhibit Candida albicans biofilm formation and overall rate of catheter-related bloodstream infections (CR-BSIs) compared with soybean-oil (SO) IFE). We aimed to delineate this inhibitory mechanism and impact of IFE choice on distribution of fungal CR-BSIs. Transcriptional profiling was conducted on C. albicans grown in SO-IFE, MO-IFE, or SO-IFE with capric acid. Overexpression strains of shared down-regulated genes were constructed using a tetracycline-off system to assess hypha and biofilm formation in IFEs. A 5-year retrospective multicenter cohort study was performed to assess differences in CR-BSIs caused by Candida species based on the IFE formulation received in pediatric patients. Genes significantly down-regulated in MO-IFE and SO-IFE with capric acid included CDC11, HGC1, and UME6. Overexpression of HGC1 or UME6 enabled filamentation in capric acid and MO-IFE. Interestingly, only overexpression of UME6 was sufficient to rescue biofilm growth in MO-IFE. MO-IFE administration was associated with a higher proportion of non-albicans Candida versus C. albicans CR-BSIs (42% vs 33%; odds ratio, 1.22 [95% confidence interval, .46-3.26]). MO-IFE affects C. albicans biofilm formation and hyphal growth via a UME6-dependent mechanism. A numerical but not statistically significant difference in distribution of Candida spp. among CR-BSIs was observed.