Wildlife conservation and management (WCM) practices have been historically drawn from a wide variety of academic fields, yet practitioners have been slow to engage with emerging conversations about animals as complex beings, whose individuality and sociality influence their relationships with humans. We propose an explicit acknowledgement of wild, nonhuman animals as active participants in WCM. We examined 190 studies of WCM interventions and outcomes to highlight 3 common assumptions that underpin many present approaches to WCM: animal behaviors are rigid and homogeneous; wildlife exhibit idealized wild behavior and prefer pristine habitats; and human–wildlife relationships are of marginal or secondary importance relative to nonhuman interactions. We found that these management interventions insufficiently considered animal learning, decision-making, individuality, sociality, and relationships with humans and led to unanticipated detrimental outcomes. To address these shortcomings, we synthesized theoretical advances in animal behavioral sciences, animal geographies, and animal legal theory that may help conservation professionals reconceptualize animals and their relationships with humans. Based on advances in these fields, we constructed the concept of animal agency, which we define as the ability of animals to actively influence conservation and management outcomes through their adaptive, context-specific, and complex behaviors that are predicated on their sentience, individuality, lived experiences, cognition, sociality, and cultures in ways that shape and reshape shared human–wildlife cultures, spaces, and histories. Conservation practices, such as compassionate conservation, convivial conservation, and ecological justice, incorporate facets of animal agency. Animal agency can be incorporated in conservation problem-solving by assessing the ways in which agency contributes to species’ survival and by encouraging more adaptive and collaborative decision-making among human and nonhuman stakeholders. 相似文献
Most petrochemical units run under extreme conditions, such as high temperatures, pressures, and speeds. Consequently, the equipment operators may commit errors because the startup and shutdown processes usually involve complicated operation steps; moreover, the operators may lack experience in handling abnormal situations. Misoperation can lead to accidents, including fires and explosions. Thus, risk analysis for process operations and the development of preventive measures have become an effective means of avoiding misoperation-related accidents. However, it is challenging to ensure the comprehensiveness of risk-analysis results. In this paper, we present a method for misoperation monitoring and early warning in the startup and shutdown processes of petrochemical units. The mechanisms of misoperation occurrence are summarized based on investigations of serious accidents in the recent past. Knowledge regarding the mechanisms of misoperation is crucial for the risk analysis of petrochemical units. The potential risk information, such as causes, adverse consequences, key monitoring parameters, and prevention control solutions, should be acquired and be employed to construct an early-warning knowledge database. Furthermore, misoperation judgment rules need to be formulated to identify misoperations. The data obtained from the monitoring module, misoperation judgment rules, and analysis results can aid in developing schemes to avoid possible abnormal situations. This paper reports a misoperation monitoring and early-warning system for a hydrogenation unit. As demonstrated, conducting risk analysis to determine the potential operational risks and formulating misoperation judgment rules to analyze the process data are essential for enabling early warning. The application of this method will contribute to operational guidance, economic loss reduction, and accident avoidance. 相似文献
Remediation and recovery efforts after a release of Bacillus anthracis (anthrax) spores may be difficult and costly. In addition, response and recovery technologies may be focused on critical resources, leaving the small business or homeowner without remediation options. This study evaluates the efficacy of relatively low levels of hydrogen peroxide vapor (HPV) delivered from off‐the‐shelf equipment for the inactivation of Bacillus spores within an indoor environment. Decontamination evaluations were conducted in a house using both Bacillus atrophaeus var. globigii (Bg; as surrogates for B. anthracis) inoculated on the carpet and galvanized metal as coupons and Geobacillus stearothermophilus (Gs) as biological indicators on steel. The total decontamination time ranged from 4 to 7 days. Using the longer exposure times, low concentrations of HPV (average levels below 20 parts per million) effectively inactivated Bg and Gs spores on the materials tested. The HPV was generated with commercial humidifiers and household‐strength hydrogen peroxide solutions. The presence of home furnishings did not have a significant impact on HPV efficacy. This simple, inexpensive, and effective decontamination method could have significant utility for remediation following a B. anthracis spore release, such as following a terrorist attack. 相似文献
Objective: The objective of this study is to develop a novel algorithm on a mobile system that can warn drivers about the possibility of a collision with a pedestrian. The constraints of the algorithm are near-real-time detection speed and a good detection rate.
Method: Histogram of gradients (HOG)-based detection is widely used in pedestrian safety applications; however, it has low detection speed for real-time systems. Hence, it has no direct usage for mobile systems. In order to achieve near-real-time detection speed, partial Haar transform predetections are applied to an image before HOG detection. The partial and HOG detections are merged and a score-based confidence level is defined for the final detection phase. In this way, the outcome is prioritized and different warning levels can be issued to warn the driver before a possible pedestrian collision.
Results: The proposed algorithm provides an increase in detection speed (from 46 to 76 fps) and detection rate (from 80 to 91%) with respect to HOG-based pedestrian detection. It also improves confidence of the results by multidetection merging and score assignment to detections.
Conclusions: Performance improvement of the algorithm is compared with respect to state-of-the-art detectors/algorithms. Based on the detection rate and detection speed performance, it can be concluded that the proposed algorithm is suitable to be used for mobile systems to warn drivers about the possibility of collision with a pedestrian. 相似文献
Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.
Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).
Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.
Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy. 相似文献