Search Results (259)

We investigate whether a belief in trend continuation, often associated with the so-called “hot-hand effect,” can be endogenously triggered by personal performance feedback in a controlled financial experiment. Participants allocated funds across assets with randomly generated prices, under conditions of known probabilities and varying levels of risk. In a two-stage setup, participants were first exposed to random price sequences to learn the task and potentially develop perceptions of personal success. They then faced additional price paths under incentivized conditions. Our findings show that participants initially increased purchases following gains—consistent with a feedback-driven belief in momentum—but this pattern faded over time. When facing sustained losses, loss aversion dominated decision-making, overriding early optimism. These results highlight how cognitive heuristics and emotional biases interact dynamically, suggesting that belief in trend continuation is context-sensitive and constrained by the reluctance to realize losses. Full article

Children are not only concerned about fairness but also care for others. This study examined how experimentally induced empathic concern influences children’s responses to inequity, particularly when fairness considerations may conflict with empathy-driven motivations. A sample of 10- to 12-year-old children (N = 111, 62 boys, 49 girls) from China were randomly assigned to an empathic or non-empathic condition and completed multiple rounds of ultimatum and dictator games, acting as recipients and proposers. The results showed that children in the empathic concern condition were more likely to accept disadvantageous offers (F (1, 109) = 10.723, p = 0.001) and reject advantageous offers (F (1, 109) = 11.200, p = 0.001) than those in the non-empathic condition. Furthermore, in the dictator game, children in the empathic condition shared significantly more resources with the same protagonist (F (1, 109) = 110.740, p < 0.001). These findings suggest that empathic concern affects children’s inequity aversion and that empathic concern takes priority in guiding children’s inequity aversion when it conflicts with the fairness criterion. Moreover, our findings suggest that altruistic motivations potentially play a role in children’s responses to their inequity aversion. Full article

Neuroinflammation is a key feature of Alzheimer’s disease (AD), and stem cell therapies have emerged as promising candidates due to their immunomodulatory properties. Neuro-Cells (NC), a combination of unmodified mesenchymal stem cells (MSCs) and hematopoietic stem cells (HSCs), have demonstrated therapeutic potential in models of central nervous system (CNS) injury and neurodegeneration. Here, we studied the effects of NC in APPswe/PS1dE9 mice, an AD mouse model. Twelve-month-old APPswe/PS1dE9 mice or their wild-type littermates were injected with NC or vehicle into the cisterna magna. Five to six weeks post-injection, cognitive, locomotor, and emotional behaviors were assessed. The brain was stained for amyloid plaque density using Congo red, and for astrogliosis using DAPI and GFAP staining. Gene expression of immune activation markers (Il-1β, Il-6, Cd45, Tnf) and plasticity markers (Tubβ3, Bace1, Trem2, Stat3) was examined in the prefrontal cortex. IL-6 secretion was measured in cultured human monocytes following endotoxin challenge and NC treatment. Untreated APPswe/PS1dE9 mice displayed impaired learning in the conditioned taste aversion test, reduced object exploration, and anxiety-like behavior, which were improved in the NC-treated mutants. NC treatment normalized the expression of several immune and plasticity markers and reduced the density of GFAP-positive cells in the hippocampus and thalamus. NC treatment decreased amyloid plaque density in the hippocampus and thalamus, targeting plaques of <100 μm². Additionally, NC treatment suppressed IL-6 secretion by human monocytes. Thus, NC treatment alleviated behavioral deficits and reduced amyloid plaque formation in APPswe/PS1dE9 mice, likely via anti-inflammatory mechanisms. The reduction in IL-6 production in human monocytes further supports the potential of NC therapy for the treatment of AD. Full article

Route planning under uncertain traffic conditions requires accounting for not only expected travel times but also the risk of late arrivals. This study proposes a mean-upper partial moment (MUPM) framework for pathfinding that explicitly considers travel time unreliability. The framework incorporates a benchmark travel time to measure the upper partial moment (UPM), capturing both the probability and severity of delays. By adjusting a risk parameter ($\theta$), the model reflects different traveler risk preferences and unifies several existing reliability measures, including on-time arrival probability, late arrival penalty, and semi-variance. A bi-objective model is formulated to simultaneously minimize mean travel time and UPM. Theoretical analysis shows that the MUPM framework is consistent with the expected utility theory (EUT) and stochastic dominance theory (SDT), providing a behavioral foundation for the model. To efficiently solve the model, an SDT-based label-correcting algorithm is adapted, with a pre-screening step to reduce unnecessary pairwise path comparisons. Numerical experiments using GPS probe vehicle data from Louisville, Kentucky, USA, demonstrate that varying $\theta$ values lead to different non-dominated paths. Lower $\theta$ values emphasize frequent small delays but may overlook excessive delays, while higher $\theta$ values effectively capture the tail risk, aligning with the behavior of risk-averse travelers. The MUPM framework provides a flexible, behaviorally grounded, and computationally scalable approach to pathfinding under uncertainty. It holds strong potential for applications in traveler information systems, transportation planning, and network resilience analysis. Full article

5F-ADB, MDMB-4en-PINACA and ADB-4en-PINACA are three potent indazole-carboxamide synthetic cannabinoids (SCs) that have been widely abused in recent years. However, the pharmacological research on these compounds remains limited, especially in vivo research data. The purpose of the present study was to investigate the pharmacological effects of 5F-ADB, MDMB-4en-PINACA and ADB-4en-PINACA in mice, comparing their in vivo effects with those caused by Δ⁹-tetrahydrocannabinol (Δ⁹-THC), the main psychoactive substance in cannabis. We evaluated the cannabinoid-specific pharmacological effects of 5F-ADB, MDMB-4en-PINACA and ADB-4en-PINACA using the tetrad assay (locomotion inhibition, hypothermia, analgesia and catalepsy). Then we conducted conditioned place preference (CPP) and precipitated withdrawal assay to assess the rewarding effect and physical dependence, with Δ⁹-THC as a positive control. The results showed that all of the three SCs exhibited potential tetrad effects in a dose-dependent manner, with median effective dose (ED₅₀) values ranging from 0.03 to 0.77 mg/kg. In the CPP tests, they all exhibited a significant biphasic effect of conditioned place preference (CPP) and conditioned place aversion (CPA). A significant increase in paw tremors and head twitches was observed in the rimonabant-precipitated withdrawal assay, indicating that the repeated administration of these SCs can lead to potential physical dependence. All effective doses were lower than Δ⁹-THC. These findings strongly suggested that the three SCs exhibited similar but stronger cannabinoid-specific tetrad effects, rewarding effect and physical dependence compared with Δ⁹-THC, indicating their high abuse potential and possible threats to human health. The rank order of abuse potential for these drugs was 5F-ADB > MDMB-4en-PINACA > ADB-4en-PINACA > Δ⁹-THC. Full article

This study adopts an evolutionary game theory framework and focuses on the strategic interaction between brands and KOLs. It examines how the two parties interact under conditions of uncertainty and risk, especially when the KOLs’ contract fulfillment capability is low, and how they adjust strategies to achieve sustainable collaboration. Different from previous studies, this paper not only examines objective parameters such as commission rate, brand value, return cost, and reputation risk, but also introduces behavioral factors, including risk preference, loss aversion, and the psychological perception of gains and losses. By modeling the decision-making process of KOLs and brands under uncertainty and risk, the key factors affecting the evolution of cooperation strategies are identified. The simulation results show that although the cooperation strategy (such as information disclosure and truthful promotion) can achieve stability under certain conditions, the system is highly sensitive to external factors (such as environmental uncertainty) and internal psychological factors (such as risk preference and loss sensitivity). This study provides practical suggestions for brands and KOLs to promote long-term cooperation, emphasizing the importance of incentive coordination, reputation risk management, commission structure optimization, and psychological perception regulation. These findings provide practical guidance for enhancing the sustainability of brand–KOL collaborations. Full article

Breastfeeding is universally recognized for its extensive health benefits for both infants and mothers. However, for some women, the experience of breastfeeding can be complicated by intense negative emotional and physical reactions, including phenomena such as dysphoric milk ejection reflex and breastfeeding aversion/agitation. This review explores the neuroendocrine underpinnings of these conditions, emphasizing the interplay between oxytocin, prolactin, and dopamine. Oxytocin, traditionally viewed as a hormone promoting bonding and emotional regulation, can paradoxically provoke a stress response in vulnerable individuals. Prolactin, a key hormone for lactation and maternal behaviors, is implicated in stress resilience and mood regulation, but its dysregulation may contribute to depressive states. Dopamine, critical for reward processing and emotional stability, may underlie the acute emotional dysregulation seen in dysphoric milk ejection reflex. Together, disturbances in these neurohormonal systems may explain the aversive emotional experiences during breastfeeding. An improved understanding of these mechanisms offers critical insights into maternal mental health during lactation and underscores the importance of supportive clinical approaches for affected women. Full article

Following exposure to trauma, avoidance behavior can be protective but also contribute to severe symptoms and interfere with exposure-based therapy. Extinction of fear conditioning by exposure to the same environment or environmental cues that were present during the initial traumatic event but without including the aversive stimulus or stimuli is often used to study post-traumatic stress disorder (PTSD), a condition characterized by an inability to suppress conditioned fear responses. A limitation of this paradigm is that one cannot avoid the context or cues associated with the initial traumatic event. In contrast, in the passive avoidance test, one can escape the environment associated with the aversive stimulus. Genetic factors might modulate the ability to extinguish fear memory. In this study, we compared the effects of distinct human apoE isoforms on the extinction of contextual fear and passive avoidance memory, as well as on subsequent activity levels, depressive-like behavior, and hippocampal levels of tau, in targeted replacement mice. Full article

With the increasing integration of variable renewables, cascade hydro–photovoltaic (PV) systems face growing challenges in scheduling under PV output uncertainty. This paper proposes a risk-aware bi-level scheduling model based on the Information Gap Decision Theory (IGDT) to maximize renewable energy utilization while accommodating different risk preferences. The upper level optimizes the uncertainty horizon based on the decision-maker’s risk attitude (risk-neutral, opportunity-seeking, or risk-averse), while the lower level ensures operational feasibility under corresponding deviations in the PV and hydropower schedule. The bi-level model is reformulated into a single-level mixed-integer linear programming (MILP) problem. A case study based on four hydropower plants and two photovoltaic (PV) clusters in Southwest China demonstrates the effectiveness of the model. Numerical results show that the opportunity-seeking strategy (OS) achieves the highest total generation (68,530.9 MWh) and PV utilization (102.2%), while the risk-averse strategy (RA) improves scheduling robustness, reduces the number of transmission violations from 38 (risk-neutral strategy) to 33, and increases the system reserve margin to 20.1%. Compared to the conditional value-at-risk (CVaR) model, the RA has comparable robustness. The proposed model provides a flexible and practical tool for risk-informed scheduling in multi-energy complementary systems. Full article

Background/Objectives: This feasibility study explores the use of virtual reality (VR) as an adjunct therapy during capsaicin administration for individuals with chronic neuropathic pain. Chronic neuropathic pain poses significant management challenges due to its complex biopsychosocial nature. This study aimed to assess the acceptability, usability, and preliminary effectiveness of VR in reducing pain, anxiety, aversiveness, and rumination during painful procedures. Methods: A total of 24 patients participated in the study and received either capsaicin treatment with VR (n = 12) or treatment as usual (n = 12). The VR group engaged with “SnowWorld”, an immersive, interactive environment designed to promote distraction and relaxation. Outcomes including pain (average and worst), aversiveness, rumination, and anxiety, were assessed via 11-point scales. Results: Participants in the VR condition reported significantly lower scores for worst pain (2.83 vs. 6.33), average pain (2.08 vs. 5.42), aversiveness (1.50 vs. 6.08), rumination (1.17 vs. 5.75), and anxiety (0.83 vs. 5.17) compared to the controls (all p < 0.001). Participants reported high satisfaction regarding the VR experience, noting its immersive nature and ease of use. The qualitative feedback highlighted the VR’s ability to foster relaxation and distraction during capsaicin administration. Conclusions: These findings support the feasibility and preliminary efficacy of VR as an adjunctive tool for acute pain management during capsaicin treatment. Further studies with larger samples are warranted to confirm these effects and explore long-term outcomes. Full article

Due to accelerated urbanization, modern urban residents are facing increasing life pressures. Many citizens are experiencing situational aversion in daily commuting, and the deterioration in the traffic environment has led to psychological distress of varying degrees among urban dwellers. Cyclists, who account for about 7% of urban commuters, lack a sense of belonging in the urban space and experience significant deficiencies in the corresponding urban infrastructure, which causes more people to face significant barriers to choosing cycling as a mode of transportation. To address the aforementioned issues, this study proposes a bionic intelligent interaction helmet (BIIH) designed and validated based on the principles of bionics, which has undergone morphological design and structural validation. Constructed around the STM32-embedded development board, the BIIH is an integrated smart cycling helmet engineered to perceive environmental conditions and enable both human–machine interactions and environment–machine interactions. The system incorporates an array of sophisticated electronic components, including temperature and humidity sensors; ultrasonic sensors; ambient light sensors; voice recognition modules; cooling fans; LED indicators; and OLED displays. Additionally, the device is equipped with a mobile power supply, enhancing its portability and ensuring operational efficacy under dynamic conditions. Compared with conventional helmets designed for analogous purposes, the BIIH offers four distinct advantages. Firstly, it enhances the wearer’s environmental perception, thereby improving safety during operation. Secondly, it incorporates a real-time interaction function that optimizes the cycling experience while mitigating psychological stress. Thirdly, validated through bionic design principles, the BIIH exhibits increased specific stiffness, enhancing its structural integrity. Finally, the device’s integrated power and storage capabilities render it portable, autonomous, and adaptable, facilitating iterative improvements and fostering self-sustained development. Collectively, these features establish the BIIH as a methodological and technical foundation for exploring novel research scenarios and prospective applications. Full article

The low-carbon development (LCD) of energy markets not only serves as a critical enabler in combating global climate change and advancing the green economy but also enhances global industrial competitiveness. Grounded in prospect theory, this study develops a tripartite evolutionary game model involving three core energy market stakeholders, i.e., energy enterprises, the public, and the government, to investigate the determinant factors and decision-making mechanisms underlying the LCD of energy enterprises, with subsequent simulation analyses conducted through MATLAB R2024a. The research findings indicate that loss aversion serves as the primary driver for energy enterprises’ adoption of LCD strategies. Public supervision demonstrates optimal effectiveness only under conditions of low risk and low loss, while risk sensitivity remains the dominant factor influencing the government’s strategic choices. Notably, government incentives combined with public supervision demonstrate significant synergistic effects in accelerating the corporate transition toward LCD. Accordingly, the government should actively promote LCD strategies to mitigate transformation risks for energy enterprises while concurrently optimizing regulatory frameworks to reduce public supervision costs and amplify incentive benefits, thereby fostering active public participation in LCD. Full article

Blockchains are designed to produce a secure, append-only sequence of transactions. Establishing transaction sequentiality is typically achieved by underlying consensus protocols that either prevent forks entirely (no-forking-ever) or make forks short-lived. The main challenges facing blockchains are to achieve this no-forking condition while achieving high throughput, low response time, and low energy costs. This paper presents the Bounce blockchain protocol along with throughput and response time experiments. The core of the Bounce system is a set of satellites that partition time slots. The satellite for slot i signs a commit record that includes the hash of the commit record of slot $i-1$ as well as a sequence of zero or more Merkle tree roots whose corresponding Merkle trees each has thousands or millions of transactions. The ledger consists of the transactions in the sequence of the Merkle trees corresponding to the roots of the sequence of commit records. Thus, the satellites work as arbiters that decide the next block(s) for the blockchain. Satellites orbiting around the Earth are harder to tamper with and harder to isolate than terrestrial data centers, though our protocol could work with terrestrial data centers as well. Under reasonable assumptions—intermittently failing but non-Byzantine (i.e., non-traitorous) satellites, possibly Byzantine Ground Stations, and “exposure-averse” administrators—the Bounce System achieves high availability and a no-fork-ever blockchain. Our experiments show that the protocol achieves high transactional throughput (5.2 million transactions per two-second slot), low response time (less than three seconds for “premium” transactions and less than ten seconds for “economy” transactions), and minimal energy consumption (under 0.05 joules per transaction). Moreover, given five more cloud sites of the kinds currently available in CloudLab, Clemson, we show how the design could achieve throughputs of 15.2 million transactions per two second slot with the same response time profile. Full article

Large-scale penetration of renewable energy generation brings various challenges to the power system in terms of safety, reliability, economy and flexibility. The development of large-scale, high-security energy-storage technology can effectively address these challenges and improve the capabilities of power systems in power-supply guarantee and flexible adjustment. This paper proposes a novel distributed risk-averse optimization scheduling model of a hybrid wind–solar–storage system based on the adjustability of the storage system and the complementarity of renewable energy generation. The correlation of wind power and photovoltaic generation is quantified based on a Copula function. A risk-averse operation optimization model is proposed using conditional value at risk to quantify the uncertainty of renewable energy generation. A linear formulation of conditional value at risk under typical scenarios is developed by Gibbs sampling the joint distribution and Fuzzy C-Means clustering algorithm. A distributed solution algorithm based on an alternating-direction method of multipliers is developed to derive the optimal scheduling of hybrid wind–solar–storage system in a distributed manner. Numerical case studies based on IEEE 34-bus distribution network verify the effectiveness of the proposed model in reducing the uncertainty impact of renewable energy generation on an upstream grid (the overall amount of renewable energy generation sent back to the upstream grid has decreased about 80.6%) and ensuring the operational security of hybrid wind–solar–storage system (overall voltage deviation within 5.6%). Full article

This paper is dedicated to studying the optimal investment proportions of three types of assets with symmetry, namely, risky assets, risk-free assets, and wealth management products, when the stochastic expenditure process follows a jump-diffusion model. The stochastic expenditure process is treated as an exogenous cash flow and is assumed to follow a stochastic differential process with jumps. Under the Cox–Ingersoll–Ross interest rate term structure, it is presumed that the prices of multiple risky assets evolve according to a multi-dimensional geometric Brownian motion. By employing stochastic control theory, the Hamilton–Jacobi–Bellman (HJB) equation for the household portfolio problem is formulated. Considering various risk-preference functions, particularly the Hyperbolic Absolute Risk Aversion (HARA) function, and given the algebraic form of the objective function through the terminal-value maximization condition, an explicit solution for the optimal investment strategy is derived. The findings indicate that when household investment behavior is characterized by random expenditures and symmetry, as the risk-free interest rate rises, the optimal proportion of investment in wealth-management products also increases, whereas the proportion of investment in risky assets continually declines. As the expected future expenditure increases, households will decrease their acquisition of risky assets, and the proportion of risky-asset purchases is sensitive to changes in the expectation of unexpected expenditures. Full article