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Perishability can be defined as the characteristic of fresh items. The level of freshness is one of the most crucial indicators in the fresh food supply chain. The widespread information asymmetry has exacerbated the circulation losses to trigger the food safety incidents, such as the horse meat scandal in the UK, the widespread Romaine lettuce infection in the US, the contamination of Ecuadorian white shrimp, the counterfeiting of pork in China, and the þSalmon Incidentÿ. Food safety issues have resulted in adverse customer sentiment on the trust between consumers and the fresh produce business. Hence, risk- averse actions can be expected to implemented on the highly efficient and reliable traceability system for agricultural goods. The quality and safety traceability were enhanced to guarantee food safety throughout the whole supply chain of agricultural products. Fresh produce retailers can achieved in the transparency about freshness using traceability system. The fresh produce supply chain can be realized to decrease the food wastes for the high product quality and customer trust. Nascent Blockchain technology can offer to strengthening the stability of system, with the decentralization, openness, transparency, cryptographic protection and tamper-proof features. Information disclosure can also be utilized to ensure both openness and transparency of information. Additionally, the utilization and impact of information can be used to mitigate information asymmetry among supply chain participants in the product traceability. Furthermore, blockchain technology can be implemented in the entire supply chain of fresh food, particularly on data collection and storage. Real-time monitoring was realized to predict the product status during the production, processing, transportation and sales of products. As a result, the clear insight of consumers can be gained into the authentic information regarding all stages of production and distribution, thus ensuring transparency in product freshness. Supply chain efficiency was also optimized to foster the consumer trust and retailer reputation. Furthermore, customer confidence was enhanced the reputation of stores and precise supply matching. A robust and safe trust mechanism was effectively achieved for the fresh food supply chain. Blockchain technology can be implemented in the fresh produce retail industry, in order to balance and promote information sharing and transparency. Moreover, smart contract technology was utilized to reduce the circulating time of fresh produce and consumer risks, in order to enhance the efficiency and quality of consumer benefits. However, the technological application can also depend on the freshness of items and the degree to which consumers minimize risk. In this study, the information transparency and timeliness were enhanced to focus on the blockchain technology. A secondary fresh food supply chain was established to involve the suppliers, retailers, and consumers. The equilibrium solutions of the game between suppliers and retailers were compared both before and after the implementation of blockchain technology. The consumers risk avoidance behaviors were also examined on the application strategy and value. A systematic investigation was then made to determine the intention of retailers to adopt blockchain technology. Research indicated that high intention was achieved to use blockchain technology, when the product was a higher initial freshness. This selected was driven by the requirement to maximize revenues, consumer surplus and more social welfare. Conversely, blockchain technology was resulted in the decreased profits and motivation, if the product was a low initial freshness. In contrast, there was the increase in the retailer's willingness to apply the blockchain technology, as the level of consumer risk aversion increased, particularly when the initial freshness of the product was at an average level. [ABSTRACT FROM AUTHOR]

Green credit financing is closely related to corporate credit rating, so conducting in-depth research on the differentiation of green credit has practical significance. For the three-stage supply chain system composed of risk avoidance suppliers, retailers and banks, suppliers face a capital gap to produce green products to meet market demand. Based on Stackelberg game theory, this paper establishes a bank green credit and mixed financing model to study the best financing strategy of suppliers under differentiated green credit. Research shows that credit rating is not always positively correlated with product greenness, and it is important for enterprises to improve their own credit rating; the higher the degree of suppliers' risk avoidance, the lower their utility profit; only when the green sensitivity coefficient is low, the conclusion that retailers are more willing to choose to cooperate with suppliers with high credit rating is inevitable; banks providing loans to suppliers with middle credit rating can maximize their profits, and providing loans to suppliers with high credit rating can better stimulate green production. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence, reinforcement-learning-based intelligent control algorithms, which generally learn control strategies through trial and error, have received more attention in the automation equipment and manufacturing fields. Although they can intelligently adjust their control strategy without the need for human effort, the most relevant algorithms for servo motors only consider the overall performance, while ignoring the risks in special cases. Therefore, overcurrent problems are often triggered in the training process of the reinforcement learning agent. This can damage the motors' service life and even burn it out directly. To solve this problem, in this study we propose a risk-sensitive intelligent control algorithm based on value distribution, which uses the quantile function to model the probability distribution of cumulative discount returns and employs the condition value at risk to measure the loss caused by overcurrent. The agent can accordingly learn a control strategy that is more sensitive to environmental restrictions and avoid the overcurrent problem. The performance is verified on three different servo motors with six control tasks, and the experimental results show that the proposed method can achieve fewer overcurrent occurrences than others in most cases. [ABSTRACT FROM AUTHOR]

Most herbivores must balance demands to meet nutritional requirements, maintain stable thermoregulation and avoid predation. Species‐specific predator and prey characteristics determine the ability of prey to avoid predation and the ability of predators to maximize hunting success. Using GPS collar data from African wild dogs, lions, impala, tsessebes, wildebeest and zebra in the Okavango Delta, Botswana, we studied proactive predation risk avoidance by herbivores. We considered predator activity level in relation to prey movement, predator and prey habitat selection, and preferential use of areas by prey. We compared herbivore behaviour to lion and wild dog activity patterns and determined the effect of seasonal resource availability and prey body mass on anti‐predator behaviour. Herbivore movement patterns were more strongly correlated with lion than wild dog activity. Habitat selection by predators was not activity level dependent and, while prey and predators differed to some extent in their habitat selection, there were also overlaps, probably caused by predators seeking habitats with high prey abundance. Areas favoured by lions were used by herbivores more when lions were less active, whereas wild dog activity level was not correlated with prey use. Prey body mass was not a strong predictor of the strength of proactive predation avoidance behaviour. Herbivores showed stronger anti‐predator behaviours during the rainy season when resources were abundant. Reducing movement when top predators are most active and avoiding areas with a high likelihood of predator use during the same periods appear to be common strategies to minimize predation risk. Such valuable insights into predator–prey dynamics are only possible when using similar data from multiple sympatric species of predator and prey, an approach that should become more prevalent given the ongoing integration of technological methods into ecological studies. [ABSTRACT FROM AUTHOR]

Abstract The resolution of traffic congestion and personal safety issues holds paramount importance for human’s life. The ability of an autonomous driving system to navigate complex road conditions is crucial. Deep learning has greatly facilitated machine vision perception in autonomous driving. Aiming at the problem of small target detection in traditional YOLOv5s, this paper proposes an optimized target detection algorithm. The C3 module on the algorithm’s backbone is upgraded to the CBAMC3 module, introducing a novel GELU activation function and EfficiCIoU loss function, which accelerate convergence on position loss l box , confidence loss l obj , and classification loss l cls , enhance image learning capabilities and address the issue of inaccurate detection of small targets by improving the algorithm. Testing with a vehicle-mounted camera on a predefined route effectively identifies road vehicles and analyzes depth position information. The avoidance model, combined with Pure Pursuit and MPC control algorithms, exhibits more stable variations in vehicle speed, front-wheel steering angle, lateral acceleration, etc., compared to the non-optimized version. The robustness of the driving system's visual avoidance functionality is enhanced, further ameliorating congestion issues and ensuring personal safety.

The COVID-19 pandemic has affected the lives of all Americans, but the severity of the pandemic has been experienced unevenly across space and time. Some states saw sharp rises in COVID-19 cases in early March, whereas case counts rose much later in the rest of the country. In this article, we examine the relationship between exposure to COVID-19 and citizens' views on what type of measures are required to deal with the crises and how experience with and exposure to COVID-19 is associated with greater partisan polarization. We find consistent evidence of partisan divergence in pandemic-response policy preferences across the first six months of the COVID-19 pandemic: Republicans support national control measures whereas Democrats support welfare policies, and interparty differences grow over time. We find only limited evidence that exposure or experience moderates these partisan differences. Our findings are consistent with the view that Americans interpret the COVID-19 pandemic in fundamentally partisan manner, and that objective pandemic conditions play at most a minor role in shaping mass preferences.

The resolution of traffic congestion and personal safety issues holds paramount importance for human’s life. The ability of an autonomous driving system to navigate complex road conditions is crucial. Deep learning has greatly facilitated machine vision perception in autonomous driving. Aiming at the problem of small target detection in traditional YOLOv5s, this paper proposes an optimized target detection algorithm. The C3 module on the algorithm’s backbone is upgraded to the CBAMC3 module, introducing a novel GELU activation function and EfficiCIoU loss function, which accelerate convergence on position loss lbox, confidence loss lobj, and classification loss lcls, enhance image learning capabilities and address the issue of inaccurate detection of small targets by improving the algorithm. Testing with a vehicle-mounted camera on a predefined route effectively identifies road vehicles and analyzes depth position information. The avoidance model, combined with Pure Pursuit and MPC control algorithms, exhibits more stable variations in vehicle speed, front-wheel steering angle, lateral acceleration, etc., compared to the non-optimized version. The robustness of the driving system's visual avoidance functionality is enhanced, further ameliorating congestion issues and ensuring personal safety. [ABSTRACT FROM AUTHOR]

Entrepreneurial orientation significantly influences business financial performance, particularly in global markets, making it pivotal across economies. Developed nations provide a conducive environment for entrepreneurship, supported by educational systems and skill development programs. Conversely, in developing countries, cultural and social disparities create unique challenges, shaping entrepreneurial intentions. Psychological barriers such as risk aversion, fear of failure, and resistance to change hinder potential entrepreneurs, particularly in health science faculties. A study conducted in Turkey aimed to explore these barriers among health science students. Data collected from 788 students revealed that psychological factors explained 72% of entrepreneurial intentions. Regression analysis confirmed the significance of risk avoidance, fear of failure, attitude towards change, and stress avoidance in shaping intentions. Despite these barriers, heightened entrepreneurial intentions among health students were associated with greater success in overcoming obstacles. The findings emphasize the importance of addressing psychological barriers in fostering innovative and entrepreneurial healthcare professionals. By understanding these dynamics, educational institutions, policymakers, and healthcare practitioners can better support the development of an entrepreneurial healthcare workforce. The intersection of healthcare and entrepreneurship presents opportunities for transformative solutions, potentially enhancing patient outcomes and advancing the healthcare sector. Despite challenges, emerging trends suggest a growing interest in leveraging innovation for positive change in healthcare, highlighting the potential for impactful contributions to the industry's evolution. [ABSTRACT FROM AUTHOR]

Abstract Most herbivores must balance demands to meet nutritional requirements, maintain stable thermoregulation and avoid predation. Species‐specific predator and prey characteristics determine the ability of prey to avoid predation and the ability of predators to maximize hunting success. Using GPS collar data from African wild dogs, lions, impala, tsessebes, wildebeest and zebra in the Okavango Delta, Botswana, we studied proactive predation risk avoidance by herbivores. We considered predator activity level in relation to prey movement, predator and prey habitat selection, and preferential use of areas by prey. We compared herbivore behaviour to lion and wild dog activity patterns and determined the effect of seasonal resource availability and prey body mass on anti‐predator behaviour. Herbivore movement patterns were more strongly correlated with lion than wild dog activity. Habitat selection by predators was not activity level dependent and, while prey and predators differed to some extent in their habitat selection, there were also overlaps, probably caused by predators seeking habitats with high prey abundance. Areas favoured by lions were used by herbivores more when lions were less active, whereas wild dog activity level was not correlated with prey use. Prey body mass was not a strong predictor of the strength of proactive predation avoidance behaviour. Herbivores showed stronger anti‐predator behaviours during the rainy season when resources were abundant. Reducing movement when top predators are most active and avoiding areas with a high likelihood of predator use during the same periods appear to be common strategies to minimize predation risk. Such valuable insights into predator–prey dynamics are only possible when using similar data from multiple sympatric species of predator and prey, an approach that should become more prevalent given the ongoing integration of technological methods into ecological studies.

Abstract The application of risk management strategies is a common approach in emergency response scenarios. However, scant knowledge exists regarding its utilization in the specific context of an outbreak, both theoretically and practically. This study delves into the realm of risk management during the COVID-19 pandemic, focusing on four key measurements: risk avoidance (RA), risk reduction (RD), risk transfer (RT), and risk retention (RR). Using 800 valid responses collected from 31 provinces across China between August 1 and September 30, 2020, this study investigates spatial disparities in individuals’ intentions towards risk management. To achieve this, an extended version of the Theory of Planned Behavior (E-TPB) is applied. The Structural Equation Model’s path analyses revealed several findings: (1) discernible spatial disparities in RR, RA, and RD intentions between large and small cities; (2) RD and RR intentions were significantly associated with attitude, subjective norm, perceived behavioral control, and risk perception; (3) RA and RT intentions were significantly associated with attitude and risk perception; (4) risk perception exihibiting both direct and indirect effects on RA and RR intentions. This study contributs to the urban studies literature by extending the theoretical framework of risk management in the context of COVID-19. It enhances the measurement tools employed in the TPB model and scrutinizes spatial disparities in the adoption of preventative measures against COVID-19. The findings underscore the importance for local policymakers to consider geographical differences when formulating effective strategies for COVID-19 prevention.

This paper studies the computational problems of the optimal renewable energy power’s investment and production strategies for a class of noncooperative game models of power sales with risk avoidance considering renewable energy power production quotas and Green Power Certificate System. To accommodate the problems, the following steps are implemented: firstly, according to the objects of sales of the power produced by the energy suppliers and whether the players have characteristic of the risk avoidance, the models are subdivided into four kinds of models. Secondly, the employment of the gradient-like optimization method and the setting of auxiliary systems verify the existence and uniqueness of the Nash equilibrium for each of models (ie., the optimal renewable energy utilization rates) that is globally exponentially stable. Then, the definition of the complete information static game is employed to compute the Nash equilibriums and then the optimal power production quantities and the optimal revenue functions would be calculated by relevant equations. Finally, the convergent validations for renewable energy utilization rates, the numerical validations for the optimal calculations for the four proposed models are carried out through a specific numerical example. Moreover, the impacts of players’ characteristic of the risk avoidance are investigated and remarks on the impacts are provided.

The application of risk management strategies is a common approach in emergency response scenarios. However, scant knowledge exists regarding its utilization in the specific context of an outbreak, both theoretically and practically. This study delves into the realm of risk management during the COVID-19 pandemic, focusing on four key measurements: risk avoidance (RA), risk reduction (RD), risk transfer (RT), and risk retention (RR). Using 800 valid responses collected from 31 provinces across China between August 1 and September 30, 2020, this study investigates spatial disparities in individuals' intentions towards risk management. To achieve this, an extended version of the Theory of Planned Behavior (E-TPB) is applied. The Structural Equation Model's path analyses revealed several findings: (1) discernible spatial disparities in RR, RA, and RD intentions between large and small cities; (2) RD and RR intentions were significantly associated with attitude, subjective norm, perceived behavioral control, and risk perception; (3) RA and RT intentions were significantly associated with attitude and risk perception; (4) risk perception exihibiting both direct and indirect effects on RA and RR intentions. This study contributs to the urban studies literature by extending the theoretical framework of risk management in the context of COVID-19. It enhances the measurement tools employed in the TPB model and scrutinizes spatial disparities in the adoption of preventative measures against COVID-19. The findings underscore the importance for local policymakers to consider geographical differences when formulating effective strategies for COVID-19 prevention. [ABSTRACT FROM AUTHOR]

The current study employs a quasi-experimental design to test the efficacy of situational crime prevention (SCP) in understanding risk avoidance behavior in a darknet environment. Specifically, we deployed a web scraper to extract data from a popular darknet market. We then used these data to assess change in vendors and customers' behavior following the deliverance of a warning message from the market administrator regarding the former market administrator's intention to scam market participants. In the one-month following the message, vendors posted fewer advertisements and customers spent less and made fewer transactions on the marketplace. These findings expand the scope of SCP and provide evidence for Hutchings and Holt's notion that darknet markets can be disrupted by means of gossip. [ABSTRACT FROM AUTHOR]

Context. Predation risk, whether from large carnivores or humans, is a primary driver of movement and habitat selection for ungulates. Throughout much of the geographical range of white-tailed deer, predation risk during autumn and winter is driven by hunters; however, information about how deer respond to hunting pressure during a long hunting season is lacking. Aims. We aimed to determine how differences in daily temporal exposure to hunting risk affected habitat selection of adult male white-tailed deer. Methods. We deployed GPS collars on 42 adult male white-tailed deer during the 2017–2018 and 2018–2019 firearm hunting seasons in Mississippi, USA. GPS collars provided fine-scale spatial and temporal information regarding habitat use of our study area. Key results. We showed a mismatch between what hunters and deer selected; landscape characteristics selected most by hunters were least selected by deer during the day, which we believe has never been documented. Fine-scale temporal analysis showed that deer selected for some areas (food plots) as much as five times more often during the night, when no hunting risk was present, than during the day, when risk was present. Conclusions. Habitat selection by deer varies depending on the amount of risk that is present. Even in a high-risk heavily hunted area, adult male white-tailed deer can recognise external cues on the landscape, and shift habitat selection both spatially and temporally to favour areas that present less risk. Implications. This study, to our knowledge, provides the first evidence that white-tailed deer actively selected for habitat characteristics that hunters were not utilising. To minimise the effectiveness ofrisk-avoidance behaviours used by deer, we suggest hunters moderate temporal hunting effort across time to decrease the risk to which deer are exposed, thereby minimising the response by deer. [ABSTRACT FROM AUTHOR]

In order to avoid random risks in the power system and rationally allocate power to improve power consumption efficiency, this study designed a power system optimization model based on value-at-risk method, replaced the independent variables of particle swarm optimization algorithm with discrete quantities, and used discrete binary particle swarm optimization algorithm to solve the problem. The experimental results show that compared with other algorithms, DSO has the fastest downward trend, the smallest fluctuation and the best convergence. In the case of distribution power supply and optimization, the node voltage of power network operation is 0.97, the power loss is 0.54, and the system risk value is low. It is indicated that the addition of wind power generation and solar power generation, and the optimization of distribution network can effectively improve the operation of power system. It can be seen that the power system optimization model can effectively predict the risk value, and improve the accuracy of prediction and evaluation, which has certain practical significance and economic value in the field of power grid.

In the context of the development of neural networks and the legality of their use, the substantiated need to analyse the capabilities of artificial intelligence in the work of law enforcement agencies and to protect society from crime becomes increasingly relevant. The purpose of this study was to characterize the use of artificial intelligence in law enforcement, specifically, its impact on the level of crime, its detection and investigation, and the overall efficiency of law enforcement agencies. Using the comparative legal method, the author assesses various approaches to the use of artificial intelligence and analyses scientific representations of this issue based on the dialectical method. The terminological and normative-dogmatic methods helped to investigate the interpretation of the term “artificial intelligence” in modern scientific discussions and to give an axiological assessment of this phenomenon. The systemic-structural and formal-logical methods helped to consider the specific features of introducing artificial intelligence into law enforcement at the present stage. The study highlights the impact of artificial intelligence tools on the efficiency of law enforcement agencies, and substantiates the need to introduce regulations at the state level to avoid the risks of using artificial intelligence in law enforcement considering European integration. It is argued that the use of artificial intelligence to protect society from threats should follow the internationally established principles of its responsible use, which has not yet been prescribed in law. The risks of using artificial intelligence for human safety were highlighted. The study identified the main trends, problems, and prospects for the introduction of artificial intelligence in law enforcement. International practices in the use of artificial intelligence tools were updated. The results of this study can be used in the development of state policy in the field of artificial intelligence, development of legal regulation of its use, integration of artificial intelligence into the activities of state bodies, including law enforcement agencies

With the development of artificial intelligence, reinforcement-learning-based intelligent control algorithms, which generally learn control strategies through trial and error, have received more attention in the automation equipment and manufacturing fields. Although they can intelligently adjust their control strategy without the need for human effort, the most relevant algorithms for servo motors only consider the overall performance, while ignoring the risks in special cases. Therefore, overcurrent problems are often triggered in the training process of the reinforcement learning agent. This can damage the motors’ service life and even burn it out directly. To solve this problem, in this study we propose a risk-sensitive intelligent control algorithm based on value distribution, which uses the quantile function to model the probability distribution of cumulative discount returns and employs the condition value at risk to measure the loss caused by overcurrent. The agent can accordingly learn a control strategy that is more sensitive to environmental restrictions and avoid the overcurrent problem. The performance is verified on three different servo motors with six control tasks, and the experimental results show that the proposed method can achieve fewer overcurrent occurrences than others in most cases.

Demeanor evidence refers to the authoritative opinions of experts using analytical instruments to collect and interpret the formation of external physiological symptoms of the entire human body. With the development of modern technology, the observation of demeanor has entered a new stage of multimodal quantification. The quantifiable results of demeanor observation with the help of scientific and technological instruments play an important role in judicial work such as search, interrogation, and evidence review. The use of man-made reasoning in the field of legal settling has become increasingly broad. Specialists are giving increasingly more consideration to the securing of modular proof. This paper proposes the development of a component examination model for modular proof examination applications. The technique for this paper is to apply the guileless Bayes strategy, propose a superior information mining calculation, and lay out a model for proof observation and examination. The function of these methods is to systematically explore the basic theoretical issues of demeanor evidence based on the status quo of judicial application of demeanor evidence. Through the prediction of individual demeanor based on data mining algorithm, the evidence analysis model is designed, the neurobiological experiment is carried out, and the demeanor evidence animal stress model is constructed to verify the scientific basis of multidemeanor evidence observation. The experimental results showed that after repeated stimulation of SD rats, the maximum changes in the expression of HSP70 gene and SAA gene were 10.77 and 14.1 respectively, reflecting the high reliability of demeanor evidence biological experiments. The model can improve the accuracy of evidence use, and the correct use of demeanor evidence can realize the true litigation value of intelligent justice and the concept of human rights protection, and promote the construction of intelligent justice. [ABSTRACT FROM AUTHOR]

Whereas much research has looked at how recommendation systems influence online purchase intentions, this article illustrates the dual process model by which they occur. Using two studies, we fill the research void in interactive marketing by demonstrating how the dual processes of social proof and risk avoidance mediate the impact of recommendation labels on consumer decision-making contingent upon their level of involvement. Study 1 (n = 73), used a mixed-subjects design with a college student sample to demonstrate that both types of recommendation labels will lead to higher purchase intentions in an online setting. Most importantly, it provides evidence for the main effect of our theoretical model across different product categories. Study 2 (n = 160) provides support for our remaining four hypotheses by demonstrating the underlying process through which recommendation labels have a two-fold effect on purchase intentions. Specifically, the recommendation label increased the risk avoidance effect for high-involvement consumers and enhanced the social proof effect for low-involvement consumers. In both cases, the recommendation labels increased purchase intentions. Implications of our findings for theoretical and practical contributions and future directions are also explored. [ABSTRACT FROM AUTHOR]

Copyright of Soter: Journal of Religious Science / Religijos Mokslo Žurnalas is the property of Vytautas Magnus University, Faculty of Theology-Philosophy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Simple Summary: Animals differ in their foraging efficiency and it is not clear what drives this variation. We examined how the foraging efficiency of long-billed hermit hummingbirds changes with regard to three behavioral traits: (a) exploration, (b) risk avoidance and (c) arousal in conditions at two different levels of perceived risk (low and high). We found that foraging efficiency was lower in high-risk conditions, but behavioral traits explained the additional variation in foraging efficiency in a condition-dependent manner. More explorative individuals had higher foraging efficiency in low-risk conditions, but the opposite was the case in high-risk conditions. Regardless of the conditions, foraging efficiency increased with bird arousal and decreased if they were more cautious (higher risk avoidance). Our findings highlight the importance of taking into account additional behavioral dimensions to better understand the foraging strategies of individuals. Traditionally, foraging behavior has been explained as the response to a trade-off between energetic gain from feeding resources and potential costs from concomitant risks. However, an increasing number of studies has shown that this view fails to explain an important fraction of the variation in foraging across a variety of taxa. One potential mechanism that may account for this variation is that various behavioral traits associated with foraging may have different fitness consequences, which may depend on the environmental context. Here, we explored this mechanism by evaluating the foraging efficiency of long-billed hermit hummingbirds (Phaethornis longirostris) with regard to three behavioral traits: (a) exploration (number of feeders used during the foraging visit), (b) risk avoidance (latency to start feeding) and (c) arousal (amount of movements during the foraging visit) in conditions at two different levels of perceived risk (low—control and high—experimental, with a threatening bullet ant model). Foraging efficiency decreased in response to threatening conditions. However, behavioral traits explained additional variation in foraging efficiency in a condition-dependent manner. More exploration was associated with a higher foraging efficiency under control conditions, but this was reversed when exposed to a threat. Regardless of the conditions, arousal was positively associated with foraging efficiency, while risk avoidance was negatively related. Importantly, exploratory behavior and risk avoidance were quite repeatable behaviors, suggesting that they may be related to the intrinsic traits of individuals. Our findings highlight the importance of taking into account additional behavioral dimensions to better understand the foraging strategies of individuals. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of the article is to substantiate the features of risk management at the enterprise in conditions of uncertainty of the situation to increase its adaptive capabilities and maneuverability, as well as to outline the basic principles and methods allowing to quickly respond to existing and potential threats and to limit the negative impact of risks on the activities of the enterprise. The author identifies the transformation of the approach to the formation of a risk management system from financially-oriented to personnel-oriented. It is found that in the process of risk management, a register of risks along with a risk map should be formed and appropriate management measures should be worked out, which should not formally, but actually improve the quality of management. Based on the changing circumstances of business functioning, the basic principles of risk management in the enterprise are identified, including the following: systematicity, integratedness, comprehensiveness, efficiency, dynamism, prevention, consistency, multi-variateness. The stages of risk management in the enterprise are allocated, the quality of which affects the overall result that will be obtained in the end. Approaches to risk management in the enterprise are substantiated and attention is focused on the need for their regular review and adaptation to the conditions, which will ensure compliance with the requirements of dynamism and flexibility of business decision-making. The methods of risk management in the enterprise are systematized. It is proved that the methods can be applied both at the stage of preliminary elaboration of risks and managerial decision-making regarding them, and in the process of their transformation consequently to a certain level of uncertainty inherent in both the external and the internal environment

The agricultural marketing behavior of farmers is crucial for the realization of production value. Based on survey data from 406 citrus farmers in Hubei Province, this paper empirically examines the effects of risk aversion and Internet use on farmers' marketing behavior in terms of fresh produce. The results show that, first, farmers are generally reluctant to sell, with reluctant sellers accounting for about one-third of the total sample, and most report high levels of Internet use. Second, risk aversion and Internet use have a significant impact on farmers' reluctance to sell. The higher the level of farmer risk aversion, the lower the reluctance to sell, while Internet use significantly increases the probability of farmers being reluctant to sell. Third, Internet use weakens the inhibiting effect of risk aversion on reluctance to sell. These findings help to clarify the factors influencing farmers' reluctance to sell and provide reference suggestions for promoting high-quality agricultural development and rural industrial revitalization. [ABSTRACT FROM AUTHOR]

Copyright of Revista Gestão & Tecnologia is the property of Revista Gestao & Tecnologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Assessed neural dynamics of youth risk avoidance using Balloon Risk Avoidance Task. • All youth had smaller P3, larger FRN, larger theta to unsuccessful risk avoidance. • Socially anxious youth had larger P2, slow-wave, FRN to unsuccessful risk avoidance. • Socially anxious youth had smaller theta to successful/unsuccessful risk avoidance. Adolescents are at relatively high-risk for developing anxiety, particularly social anxiety. A primary hallmark of social anxiety is the impulse to avoid situations that introduce risk. Here, we examined the neural and behavioral correlates of risk avoidance in adolescents (N =59) 11 to 19 years of age. The Balloon Risk Avoidance Task was used with concurrent electroencephalography to measure event-related potentials (frontal P2; late slow-wave; N2, feedback-related negativity, FRN; posterior P3) and oscillatory dynamics (midfrontal theta, 4–7 Hz) in response to unsuccessful and successful risk avoidance conditions. Social anxiety was measured using the Social Phobia and Anxiety Inventory for Children. Results indicated that, across the whole sample, youth exhibited smaller P3, larger FRN, and larger theta responses to unsuccessful risk avoidance. Youth reporting high (compared to low) levels of social anxiety exhibited larger P2, slow-wave, and FRN responses to unsuccessful, compared to successful, risk avoidance. Further, greater social anxiety was associated with reduced theta responses to successful avoidance. Youth with higher levels of social anxiety showed smaller theta responses to both conditions compared to those with low levels of social anxiety. Taken together, the ERP-component differences and weakened theta power in socially anxious youth following unsuccessful avoidance are informative neural correlates for socially anxious youth during risk avoidance. [ABSTRACT FROM AUTHOR]

Ski touring is an emerging trend in the Alps, defined as ascending and descending a slope/backcountry with ski-touring equipment. The aim of this research is to understand risk-taking behavior, risk-avoidance behavior and assessed expertise (ascending/descending) of backcountry ski tourers. A cross-sectional survey design was chosen (N ​= ​300). Results show that e.g. genderwise, the difference is statistically significant in terms of ‘I consciously expose myself to danger’ t(158) ​= ​2.94, and e.g. skillwise, for ‘I check every piece of equipment before use’ t(152) ​= ​−2.98 – providing insights into the risk behavior of BCSTers in terms of gender and skills.

Competing Interests: Disclosures S.M.N. reports consulting from UpToDate and TDK, equity in LifeSignals and PhysCade Inc, and intellectual property owned by University of California Regents and Stanford University. E.S. has received institutional lecture fees from Abbott, AstraZeneca, Bristol Myers Squibb–Pfizer, and Johnson & Johnson.

Despite much progress in identifying risk genes for polygenic brain disorders, their core pathogenic mechanisms remain poorly understood. In particular, functions of many proteins encoded by schizophrenia risk genes appear diverse and unrelated, complicating the efforts to establish the causal relationship between genes and behavior. Using various mouse lines, recent studies indicate that alterations of parvalbumin-positive (PV+) GABAergic interneurons can lead to schizophrenia-like behavior. PV+ interneurons display fast spiking and contribute to excitation-inhibition balance and network oscillations via feedback and feedforward inhibition. Here, we first summarize different lines of genetically modified mice that display motor, cognitive, emotional, and social impairments used to model schizophrenia and related mental disorders. We highlight ten genes, encoding either a nuclear, cytosolic, or membrane protein. Next, we discuss their functional relationship in regulating fast spiking and other aspects of PV+ interneurons and in the context of other domains of schizophrenia. Future investigations combining behavioral genetics and cell biology should elucidate functional relationships among risk genes to identify the core pathogenic mechanisms underlying polygenic brain disorders., (Copyright © 2024. Published by Elsevier Ltd.)

Traditionally, foraging behavior has been explained as the response to a trade-off between energetic gain from feeding resources and potential costs from concomitant risks. However, an increasing number of studies has shown that this view fails to explain an important fraction of the variation in foraging across a variety of taxa. One potential mechanism that may account for this variation is that various behavioral traits associated with foraging may have different fitness consequences, which may depend on the environmental context. Here, we explored this mechanism by evaluating the foraging efficiency of long-billed hermit hummingbirds (Phaethornis longirostris) with regard to three behavioral traits: (a) exploration (number of feeders used during the foraging visit), (b) risk avoidance (latency to start feeding) and (c) arousal (amount of movements during the foraging visit) in conditions at two different levels of perceived risk (low—control and high—experimental, with a threatening bullet ant model). Foraging efficiency decreased in response to threatening conditions. However, behavioral traits explained additional variation in foraging efficiency in a condition-dependent manner. More exploration was associated with a higher foraging efficiency under control conditions, but this was reversed when exposed to a threat. Regardless of the conditions, arousal was positively associated with foraging efficiency, while risk avoidance was negatively related. Importantly, exploratory behavior and risk avoidance were quite repeatable behaviors, suggesting that they may be related to the intrinsic traits of individuals. Our findings highlight the importance of taking into account additional behavioral dimensions to better understand the foraging strategies of individuals.

Background: Cholecystectomies can sometimes be very complex operations, which place high demands on the surgeon. Objective: Are there preoperative and intraoperative procedures available for reducing the risk of intraoperative bile duct injuries during a complex cholecystectomy? Results: The complexity of the operation should be estimated preoperatively. Extended diagnostic examinations, preoperative biliary stenting and the performance of the operation by an experienced surgeon may help to reduce the operative risk. In high-risk patients, postponing the cholecystectomy may be indicated. The timely intraoperative recognition of the impossibility to perform a regular cholecystectomy is of decisive importance. In this situation, so-called bail-out procedures, such as fundus-down cholecystectomy or subtotal cholecystectomy are warranted. Conversion from laparoscopic to open surgery is not always necessary. Conclusion: Bail-out procedures are useful to reduce the risk of bile duct injuries during complex cholecystectomy and can enable a safe completion of the operation. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Administrative Sciences (John Wiley & Sons, Inc.) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The agricultural marketing behavior of farmers is crucial for the realization of production value. Based on survey data from 406 citrus farmers in Hubei Province, this paper empirically examines the effects of risk aversion and Internet use on farmers’ marketing behavior in terms of fresh produce. The results show that, first, farmers are generally reluctant to sell, with reluctant sellers accounting for about one-third of the total sample, and most report high levels of Internet use. Second, risk aversion and Internet use have a significant impact on farmers’ reluctance to sell. The higher the level of farmer risk aversion, the lower the reluctance to sell, while Internet use significantly increases the probability of farmers being reluctant to sell. Third, Internet use weakens the inhibiting effect of risk aversion on reluctance to sell. These findings help to clarify the factors influencing farmers’ reluctance to sell and provide reference suggestions for promoting high-quality agricultural development and rural industrial revitalization.

The last decade has seen an explosion of interest in drones—introducing new networking technologies, such as 5G wireless connectivity and cloud computing. The resulting advancements in communication capabilities are already expanding the ubiquitous role of drones as primary solution enablers, from search and rescue missions to information gathering and parcel delivery. Their numerous applications encompass all aspects of everyday life. Our focus is on networked and collaborative drones. The available research literature on this topic is vast. No single survey article could do justice to all critical issues. Our goal in this article is not to cover everything and include everybody but rather to offer a personal perspective on a few selected research topics that might lead to fruitful future investigations that could play an essential role in developing drone technologies. The topics we address include distributed computing with drones for the management of anonymity, countering threats posed by drones, target recognition, navigation under uncertainty, risk avoidance, and cellular technologies. Our approach is selective. Every topic includes an explanation of the problem, a discussion of a potential research methodology, and ideas for future research. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had detrimental impacts on hospitality businesses. Drawing on protection motivation theory (PMT), this study investigated what determined customer hesitation to patronize restaurants and hotels and whether such hesitation underwent changes in the duration of the pandemic. The research model was tested using three sets of survey data collected in December 2020 (n = 826), February 2021 (n = 832) and April 2021 (n = 808). The study found that expected COVID-19 safety precautions, COVID-19 risk avoidance, and demographic factors predicted customers' hesitation to visit restaurant/hotel. The analysis also showed significant shifts in how expectations about safety precautions, risk avoidance, and demographics affected customers' visit hesitation over time. These findings provide critical insights to restaurant and hotel managers and destination marketers. To ensure that customers feel safe and confident in visiting hotels and restaurants, managers should implement the recommended safety measures and clearly communicate the implementation of these measures to customers. [ABSTRACT FROM AUTHOR]

Special emphasis is put on the strategic management of insurance companies and the management of risks as a possibility to realize losses and to manage them by means of methods aimed at reducing, controlling and financing those risks. The process of risk management is an ongoing and evolving one with a clear separation of duties for the staff involved in its management in and out of the insurance company. The focus is on the risks for the insurance company and the search for adequate methods for risk management. The purpose of this article is to systematize the risks inherent in the insurance company and the possible methods of risk management with applicability in practice. The main thesis of the article is that risk management methods have an inherent and justified, full or partial application among insurance companies and must be complex. The complex nature also requires integrated application of management methods, by risks and levels – “insurance company level”, “insurance company level and insurance product” level. [ABSTRACT FROM AUTHOR]

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shenzhen University Science & Engineering is the property of Editorial Department of Journal of Shenzhen University Science & Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

There is a widespread phenomenon of trading goods ordered in advance in the commodity market, and consumers choose to imitate others for security reasons, to form a herd phenomenon of following the trend and following the crowd, this has become an important source of default by commodity booking party in transactions, causing a contingent loss to the producer of the goods. In this paper, the influence of the consumer herding effect is introduced into the characterization of default risk transmission, the herding conduction index is added to the intensity-based model of circular default, it makes the description of default risk more in line with the process of outbreak, aggregation and regression of actual risk. With the help of the credit default swap trading mechanism, the cost model of transaction default risk avoidance protocol is given. The simulation results of the model show that the herding effect has an important impact on the default probability of commodity booking party in transactions, it also makes the cost of default risk avoidance have a corresponding direction of change.

It is very important to maintain normal levels of risk avoidance in daily life. We found that DISC1-N TM mice, which are a model for mental disorders, had a phenotype marked by a risk-avoidance impairment as measured in an open-field test (OFT). We used optogenetic methods to modulate glutamatergic neurons in the basolateral amygdala (BLA) in an attempt to rescue this risk-avoidance impairment. We found that photostimulation of BLA neurons at 20 Hz modified DISC1-N TM mouse behavior from low risk avoidance to high risk avoidance. We observed following photostimulation that, compared to controls, the number of entries to the center of the open field was lower and less time was spent in the central area. We also found that the time spent immobile was higher during photostimulation compared with WT mice. We also used a lower photostimulation frequency of 5 Hz, which activated BLA glutamatergic neurons and rescued the risk-avoidance impairment in DISC1-N TM mice. Our findings confirm that the BLA participates in diverse risk-avoidance behavior. Our results are also a reminder that differences in neuronal firing patterns within the same pathway may lead to different physiological functions. • DISC1-N TM mice have an impairment in risk avoidance • 20-Hz photostimulation of BLA neurons induces high risk avoidance • 5-Hz photostimulation of BLA neurons rescues risk-avoidance impairment • The BLA participates in diverse risk-avoidance behavior [ABSTRACT FROM AUTHOR]

Intergroup conflicts are energetically more costly than intra-group disputes, and thus typically occur in contexts in which the energetic returns are relatively high. In anthropogenic environments, provisioned resources tend to be rich in energy and highly agglomerated. While females are expected to defend provisioned resources, the adult males, in turn, are expected to defend the females. Based on this premise, the present study focused on an urban forest in the city of Goiânia (Goiás, Brazil), which is inhabited by two groups of bearded capuchins. Behavioral data were collected using instantaneous scan sampling and all-events records to document intergroup conflicts and define their context. We used a backward logistic regression and stepwise linear regression to analyze the participation of the individuals in the conflicts. Conflicts were more frequent in the context of provisioning, although the number of neither females nor males involved in the conflict varied significantly between contexts. The females did avoid participating in conflicts involving adult males, however, to minimize the risk of being attacked by them. The adult males participated more in the presence of other adult males, which is partly consistent with the hypothesis of the defense of reproductive partners. The conflicts were not more intense in the context of provisioned resources, which contrasted with expectations. The hierarchical relationship between the two study groups, and the fact that the groups were derived from the same social unit, may have contributed to a reduction in the intensity of the conflicts. [ABSTRACT FROM AUTHOR]

We estimate the economic impact of South Korea's targeted responses to the large-scale COVID-19 clusters in a highly concentrated business area (Guro) and a highly concentrated entertainment area (Itaewon) in Seoul, respectively. We find that foot traffic and retail sales decreased only within a 300 m radius and recovered to their pre-outbreak level after four weeks in the case of the Guro cluster. The reductions appear to be driven by temporary business closures rather than by citizens' risk avoidance behavior. However, the adverse economic impacts measured by foot traffic and retail sales of another outbreak of the COVID-19 cluster in Itaewon were persistent. Our results imply that the effects of less intense but more targeted COVID-19 interventions, such as pinpointed, temporary closures of businesses, can differ by underlying geographical characteristics. [ABSTRACT FROM AUTHOR]

Light pollution, light in the wrong place at the wrong time, is an emerging environmental issue with wide-ranging consequences. It interferes with the fundamental 24 h light–dark cycle, and has biological effects at all levels, from molecules to ecosystems, including human health and welfare. Here, exemplified by flood-lit churches, artificial lights compromise the survival of resident bats, as darkness provides protection from predation. We predicted that brown long-eared bats Plecotus auritus emerging from churches should (1) avoid illuminated church walls, and (2) avoid extended flights in the open. To test these predictions, bats were observed emerging from 33 country churches in Sweden. A model for light intensity at increasing distances from light sources was made. This model, in combination with known distance between church walls and surrounding lamps, was used to predict lux levels (lx) at each church wall. Higher light intensities were strictly avoided and the majority of bats emerged when light intensities at church walls were below 1.25 lx. Further, most brown long-eared bats flew into the canopy of trees less than 15 m distant from the churches. Bats and their roosts are strictly protected in Europe, but this is poorly enforced with respect to churches and other historical buildings. Nevertheless, lighting of buildings is a key issue in bat conservation and of worldwide significance. We strongly advise that installation of lights near historical buildings is regulated and subject to environmental impact assessments. [ABSTRACT FROM AUTHOR]

There is a widespread phenomenon of trading goods ordered in advance in the commodity market, and consumers choose to imitate others for security reasons, to form a herd phenomenon of following the trend and following the crowd, this has become an important source of default by commodity booking party in transactions, causing a contingent loss to the producer of the goods. In this paper, the influence of the consumer herding effect is introduced into the characterization of default risk transmission, the herding conduction index is added to the intensity-based model of circular default, it makes the description of default risk more in line with the process of outbreak, aggregation and regression of actual risk. With the help of the credit default swap trading mechanism, the cost model of transaction default risk avoidance protocol is given. The simulation results of the model show that the herding effect has an important impact on the default probability of commodity booking party in transactions, it also makes the cost of default risk avoidance have a corresponding direction of change. [ABSTRACT FROM AUTHOR]