Level Of Threat Research Articles

The effects of fear appeals on reactance in climate change communication

Addressing the existential threat posed by climate change requires urgent actions, both on an individual level and on a policy level. In the present research, we applied an emotion-based persuasion appeal model to climate change mitigation to test the effect of climate mitigation appeals formulated with different levels of threat (high vs. low) and appealing to different types of climate change solutions (individual vs. policy) in eliciting psychological reactance, motivating support for climate change mitigation, and influencing willingness to discuss the issue with others. Through an online between-subjects experiment, we found that appealing to individuals (as opposed to policy) increased individuals' perceived threat to freedom, and psychological reactance. Our threat manipulation increased levels of fear, but the interaction between level of threat and type of appeal was not statistically significant on any of our dependent variables. Results are discussed in light of the active debate regarding the effectiveness of fear appeals in the climate change communication context.

The European Union as a Target: When Do Democratic Backsliders Rhetorically Challenge the EU?

AbstractPopulist actors who conduct democratic backsliding incrementally eat away at institutional checks on power. Whilst they largely focus on domestic institutions, European Union (EU) member states have an international democratic institution to consider as well. In this article, we present and test a theory explaining changes in backslider rhetoric towards the EU. Whilst they often claim a position of Euroscepticism, their interactions with the EU are complicated. We argue that anti‐democratic actors consider the public perception of the EU and the likelihood of enforcement and sanctions from the EU when deciding what type of rhetoric to use. Using speeches from Orbán in Hungary and Duda in Poland, we find that the effect of public opinion on speech sentiment varies between leaders. We also find evidence of position blurring in response to increases in EU threat levels.

Early warning of trends in commercial wildlife trade through novel machine-learning analysis of patent filing

Unsustainable wildlife trade imperils thousands of species, but efforts to identify and reduce these threats are hampered by rapidly evolving commercial markets. Businesses trading wildlife-derived products innovate to remain competitive, and the patents they file to protect their innovations also provide an early-warning of market shifts. Here, we develop a novel machine-learning approach to analyse patent-filing trends and apply it to patents filed from 1970-2020 related to six traded taxa that vary in trade legality, threat level, and use type: rhinoceroses, pangolins, bears, sturgeon, horseshoe crabs, and caterpillar fungus. We found 27,308 patents, showing 130% per-year increases, compared to a background rate of 104%. Innovation led to diversification, including new fertilizer products using illegal-to-trade rhinoceros horn, and novel farming methods for pangolins. Stricter regulation did not generally correlate with reduced patenting. Patents reveal how wildlife-related businesses predict, adapt to, and create market shifts, providing data to underpin proactive wildlife-trade management approaches.

Target Threat Level Classification Based on Improved Three-way Decisions

Target Threat Level Classification Based on Improved Three-way Decisions

Analyzing Threat Level of the Backdoor Attack Method for an Organization’s Operation

Backdoor attacks played a critical part in the catastrophe, as well as the overall impact of cyberattacks. Backdoor assaults are additionally influencing the landscape of malware and threats, forcing companies to concentrate more on detecting and establishing vulnerability tactics in order to avoid hostile backdoor threats. Despite advances in cybersecurity systems, backdoor assaults remain a source of concern because of their propensity to remain undetected long after the attack vector has been started. This research is aimed to examine the threats of backdoor attack methods in an organization's operational network, provide a full-scale review, and serve as direction for training and defensive measures. The fundamental inspiration was drawn from the alarming and involving threat in cybersecurity, which necessitates a better awareness of the level of risk and the concurrent requirement for increased security measures. Most traditional security solutions usually fail to detect harmful backdoors due to the stealthy nature of backdoor code within the system, necessitating a unique approach to full-scale threat analysis. A multi-phase approach that begins with considerable reading and examination of existing literature to get insight into typical backdoor attack methodologies and application methods. Following analysis, testing was carried out in a virtual lab in a controlled environment because thorough malware analysis testing must adhere to ethical and legal cyber testing laws to avoid any penalties or foolish breaches. This methodology also included testing on numerous attack channels combined with backdoor attacks, such as detecting software vulnerabilities, phishing emails, and direct payload injection, to determine the complexity of the different attack vectors. Each of the collected data is utilized to create a threat model that predicts the amount of risk associated with the backdoor attack approach. The finding contributes to the development of more resilient defence mechanisms, while also strengthening the overall organization's security architecture and protocols.

Species richness, composition, distribution and conservation status of herpetofauna in a global hotspot: The Mountains of Southwest China

Herpetofauna have attracted considerable global attention due to their high risk of extinction. The Mountains of Southwest China are among the 36 global biodiversity hotspots due to their high biodiversity and irreplaceability, and the Shaluli Mountains are the core area of this region. However, the diversity and conservation status of herpetofauna in the Shaluli Mountains remain unclear. In this study, we updated the species richness and composition information of herpetofauna in the Shaluli Mountains based on extensive field expeditions, published literature, and museum specimens. In addition, we identified the local hotspots and key environmental factors limiting species distribution using environmental niche models (ENMs). Furthermore, we evaluated the conservation status of the key species via the Red List Index and gap analysis. Our results revealed a total of 68 herpetofauna species, representing 30 amphibians (21 genera in nine families) and 38 reptiles (19 genera in six families). The amphibian richness showed a hump-shaped pattern along the elevational gradient, while the reptile richness showed a monotonically decreasing pattern. The dry-hot river valley was identified as a local hotspot, and the key environmental factors limiting the richness of herpetofauna species differed. Moreover, the regional Red List indices for amphibians and reptiles were 0.87 and 0.8, respectively, showing that the overall threat level of this region was low. However, there are large conservation gaps in the protection of key species. Our study indicated that new protected areas should be established and the existing protected areas should be upgraded to protect herpetofauna with a large conservation gap.

Adaptive Safety Coding in the Prefrontal Cortex.

Pivotal to self-preservation is the ability to identify when we are safe and when we are in danger. Previous studies have focused on safety estimations based on the features of external threats and do not consider how the brain integrates other key factors, including estimates about our ability to protect ourselves. Here we examine the neural systems underlying the online dynamic encoding of safety. The current preregistered study used two novel tasks to test four facets of safety estimation: Safety Prediction, Meta-representation, Recognition, and Value Updating. We experimentally manipulated safety estimation changing both levels of external threats and self-protection. Data were collected in two independent samples (behavioral N=100; fMRI N=30). We found consistent evidence of subjective changes in the sensitivity to safety conferred through protection. Neural responses in the ventromedial prefrontal cortex (vmPFC) tracked increases in safety during all safety estimation facets, with specific tuning to protection. Further, informational connectivity analyses revealed distinct hubs of safety coding in the posterior and anterior vmPFC for external threats and protection, respectively. These findings reveal a central role of the vmPFC for coding safety.

Does generative artificial intelligence pose a risk to performance validity test security?

Objective We examined the performance validity test (PVT) security risk presented by artificial intelligence (AI) chatbots asking questions about neuropsychological evaluation and PVTs on two popular generative AI sites. Method In 2023 and 2024, multiple questions were posed to ChatGPT-3 and Bard (now Gemini). One set started generally and refined follow-up questions based on AI responses. A second set asked how to feign, fake, or cheat. Responses were aggregated and independently rated for inaccuracy and threat. Responses not identified as inaccurate were assigned a four-level threat rating (no, mild, moderate, or high threat). Combined inaccuracy and threat ratings were examined cross-sectionally and longitudinally. Results Combined inaccuracy rating percentages were 35 to 42% in 2023 and 16 to 28% in 2024. Combined moderate/high threat ratings were observed in 24 to 41% of responses in 2023 and in 17 to 31% of responses in 2024. More ChatGPT-3 responses were rated moderate or high threat compared to Bard/Gemini responses. Over time, ChatGPT-3 responses became more accurate with a similar threat level, but Bard/Gemini responses did not change in accuracy or threat. Responses to how to feign queries demonstrated ethical opposition to feigning. Responses to similar queries in 2024 showed even stronger ethical opposition. Conclusions AI chatbots are a threat to PVT test security. A proportion of responses were rated as moderate or high threat. Although ethical opposition to feigning guidance increased over time, the natural language interface and the volume of AI chatbot responses represent a potentially greater threat than traditional search engines.

Experimental and Numerical Analysis of the Damage Mechanism of an Aramid Fabric Panel Engaged in a Medium-Velocity Impact.

The aim of this study is to analyze the ballistic impact behavior of a panel made of Twaron CT736 fabric with a 9 mm Full Metal Jacket (FMJ) projectile. Three shots are fired at different velocities at this panel. The ballistic impact test procedure was carried out in accordance with NIJ 010106. The NIJ-010106 standard is a document that specifies the minimum performance requirements that protection systems must meet to ensure performance. The 9 mm FMJ projectile is, according to NIJ 010106, in threat level II, but the impact velocity is in threat level IIIA. Analysis of macro-photographs of the impact of the Twaron CT736 laminated fabric panel with a 9 mm FMJ projectile involves a detailed examination of the images to gather information about the material performance and failure mechanisms at the macro- or even meso-level (fabric/layer, thread). In this paper, we analyze numerically and experimentally a panel consisting of 32 layers, made of a single material, on impact with a 9 mm FMJ projectile. The experimental results show that following impact of the panel with three projectiles, with velocities between 414 m/s and 428 m/s, partial penetration occurs, with a different number of layers destroyed, i.e., 15 layers in the case of the projectile velocity of 414 m/s, 20 layers of material in the case of the panel velocity of 422 m/s and 22 layers destroyed in the case of the projectile velocity of 428 m/s. Validation of the simulated model is achieved by two important criteria: the number of broken layers and the qualitative appearance. Four numerical models were simulated, of which three models validated the impact results of the three projectiles that impacted the panel. Partial penetration occurs in all four models, breaking the panel in the impact area, with only one exception, i.e., the number of layers destroyed, in which case the simulation did not validate the validation criterion. The performance of Twaron CT736 fabric is also given by the indentation depth values by two methods: according to NIJ 0101.06 and by 3D scanning. The NIJ 010106 standard specifies that a panel provides protection when the indentation depth values are less than 0.44 mm.

Fear, defense, and emotion: A neuroethological understanding of the negative valence research domain criteria.

We describe the close correspondence between predatory imminence continuum theory (PICT) and the National Institute of Mental Health's Research Domain Criteria (RDoC) for negative valence. RDoC's negative valence constructs relate aversively motivated behavioral reactions to various levels of threat. PICT divides defensive responses into distinct modes that vary along a continuum of the psychological closeness of predatory threat. While there is a close correspondence between PICT modes and negative valence threat constructs, based on PICT, we describe some potential elaborations of RDoC constructs. Both have consonant views of fear and anxiety and provide explicit distinctions between these emotional states, relating them to specific defensive behaviors and functions. We describe recent data that causally implicate human subjective emotional states with amygdala activity, which is also critical for defensive behavior. We conclude that attention to neuroethological views of defense can advance our understanding of the etiology and treatment of anxiety and stress disorders. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Landslide Damming Threats Along the Jinsha River, China

The 2280 km long Jinsha River has been blocked at least four times in the past 30 years. A landslide damming hazard chain can endanger communities and infrastructures hundreds of kilometers downstream from the damming site in alpine gorges. Past damming events have resulted in severe consequences, demanding a thorough assessment of damming threats along the entire Jinsha River. This study digitizes the Jinsha River and visualizes its topographic, tectonic, hydrologic, and climate characteristics in detail. A two-stage full-probability method is proposed for assessing the damming threats along this river, making it possible to identify potential damming hotspots and high-priority zones for hazard mitigation. It is found that the upper reach of the Jinsha River poses the greatest damming threat, and the threat level gradually decreases downstream. Approximately 33.4%, 36.7%, 20.5%, and 9.4% of the entire length of the Jinsha River are classified as low, moderate, high, and very high threat levels, respectively. Compared with existing hydropower projects, future projects in the upper reach are more likely to be exposed to landslide damming. We highlight the value of basin-scale spatial threat analysis and envisage that our findings will promote more targeted local-scale risk assessments for potential damming hotspots. These outcomes provide the basis for managing the risks of river damming and hydropower infrastructure along the Jinsha River.

Исследование дезинфицирующей способности феррата натрия

More and more attention has been recently paid to the disinfection of industrial wastewater. Food, petrochemical, pharmaceutical, and other industries cannot directly dump wastewater into the environment, therefore, the wastewater is fed to the deep biological treatment lines. A high level of biological threat and the expanding list of potential pathogens cause the need to search for new highly efficient disinfecting agents. The use of ferrates can be a new step in the improvement of the wastewater disinfection process due to the combination of processes of inactivation of pathogenic microflora and the reactant coagulation on ferric hydroxides generated during decontamination (oxidation). Within the framework of the study, the potential use of sodium ferrate as a disinfecting agent obtained by electrochemical dissolution of iron electrodes in alkali solutions has been confirmed. It has been established that sodium ferrate can effectively inactivate conditionally pathogenic cultures A. niger, B. subtillis which are part of activated sludge symbiosis. The efficient dosing of ferrate for complete inhibition of B. subtillis is 0.5 % mass, whereas for A. Niger it is 15 % mass. It has been proved that microflora inhibition occurs directly under the action of sodium ferrate and not due to the alkali reaction of the medium. Industrial tests of the disinfecting ability of ferrates in relation to wasted activated sludge of industrial wastewater deep biological treatment systems have confirmed the results obtained for individual objects (A. niger, B. subtillis). Based on the results, a conclusion about the potential use of ferrates in the deep biological treatment processes for highly bacteriologically contaminated industrial wastewater has been made. The main advantages of the suggested agent include the low toxicity of metabolites, minimum secondary contamination of treated water, and possible reactant advanced treatment (dephosphorization).

Oscillatory Neural Correlates of Police Firearms Decision-Making in Virtual Reality.

We investigated the neural signatures of expert decision-making in the context of police training in a virtual reality-based shoot/don't shoot scenario. Police officers can use stopping force against a perpetrator, which may require using a firearm and each decision made by an officer to discharge their firearm or not has substantial implications. Therefore, it is important to understand the cognitive and underlying neurophysiological processes that lead to such a decision. We used virtual reality-based simulations to elicit ecologically valid behavior from authorized firearms officers (AFOs) in the UK and matched novices in a shoot/don't shoot task and recorded electroencephalography concurrently. We found that AFOs had consistently faster response times than novices, suggesting our task was sensitive to their expertise. To investigate differences in decision-making processes under varying levels of threat and expertise, we analyzed electrophysiological signals originating from the anterior cingulate cortex. In line with similar response inhibition tasks, we found greater increases in preresponse theta power when participants inhibited the response to shoot when under no threat as compared with shooting. Most importantly, we showed that when preparing against threat, theta power increase was greater for experts than novices, suggesting that differences in performance between experts and novices are due to their greater orientation toward threat. Additionally, shorter beta rebounds suggest that experts were "ready for action" sooner. More generally, we demonstrate that the investigation of expert decision-making should incorporate naturalistic stimuli and an appropriate control group to enhance validity.

IMPACT OF THE BODY SCANNER APPLICATION ON PASSENGER SCREENING THROUGHPUT

The development of airport security screening systems requires the use of increasingly sophisticated and effective equipment to detect prohibited or hazardous items and substances. However, this can lead to a reduction in the throughput of the security checkpoint (SCP). This paper addresses the operationally important problem of the dilemma between screening effectiveness and screening checkpoint throughput, which is important to the real operational capabilities of an airport. In this paper, a comparison of traditional walk-through metal detectors (WTMD) gates and newer technology body scanners (BSs) was carried out in terms of SCP throughput as an element determining the operational capabilities of the airport. For this purpose, a simulation model was developed to study throughput based on a colored timed Petri net. The analysis showed that, depending on the characteristics of the available staff, the level of terrorist and epidemic threat, as well as the time of year, it is advantageous to use different strategies to vary the size of the stream of passengers directed for screening by the WTMD gate and BS.

Path Planning of Unmanned Aerial Vehicles Based on an Improved Bio-Inspired Tuna Swarm Optimization Algorithm.

The Sine-Levy tuna swarm optimization (SLTSO) algorithm is a novel method based on the sine strategy and Levy flight guidance. It is presented as a solution to the shortcomings of the tuna swarm optimization (TSO) algorithm, which include its tendency to reach local optima and limited capacity to search worldwide. This algorithm updates locations using the Levy flight technique and greedy approach and generates initial solutions using an elite reverse learning process. Additionally, it offers an individual location optimization method called golden sine, which enhances the algorithm's capacity to explore widely and steer clear of local optima. To plan UAV flight paths safely and effectively in complex obstacle environments, the SLTSO algorithm considers constraints such as geographic and airspace obstacles, along with performance metrics like flight environment, flight space, flight distance, angle, altitude, and threat levels. The effectiveness of the algorithm is verified by simulation and the creation of a path planning model. Experimental results show that the SLTSO algorithm displays faster convergence rates, better optimization precision, shorter and smoother paths, and concomitant reduction in energy usage. A drone can now map its route far more effectively thanks to these improvements. Consequently, the proposed SLTSO algorithm demonstrates both efficacy and superiority in UAV route planning applications.

Профессиональное выгорание педагогов средней школы в условиях террористической угрозы

<p style="text-align: justify;"><span lang="EN-US">This study aims to clarify the methodological status of the category “activity experience”. The characteristics of professional burnout and work passion among teachers from two regions are studied: a region with an indefinitely high (yellow) level of terrorist threat and a regular region. Subjects: 29 people. Group 1: 10 people – school teachers from a region with a terrorist threat, 20% men, 80% women, average age: 49.5 years. Group 2; 19 people from a region with no terrorist threat, 16% men, 84% women, average age: 41.2 years. Methods: Questionnaire “Utrecht Work Engagement Scale” adapted by D.A. Kutuzova, Maslach Burnout Questionnaire in Russian adaptation), Mann-Whitney U-criteria for unmatched groups. Results: the yellow level of terrorist threat in the region has an impact on the work of educational organizations (some classes are held remotely, the load associated with ensuring the safety of the educational institution increases). However, no differences were found in indicators of work passion (enthusiasm, energy, involvement) between teachers in different regions. There are also no differences in overall professional burnout and indicators of emotional exhaustion and depersonalization. The reduction in professional achievements among teachers from a region with a terrorist threat is significantly lower. Conclusions: the terrorist threat that lasts for six months does not have a direct impact on professional burnout and work commitment of teachers in the region. Perhaps it corresponds to the first stage of stress (anxiety) development, when internal resources are mobilized. Teachers need psychological support to prevent the development of deeper stages of stress.</span></p>

A threat assessment method based on correlation-similarity information and three-way decisions in interval intuitionistic fuzzy environment

Threat assessment of targets is a critical component of combat decision-making. Existing threat assessment methods only consider specific dimensions of information. When information is missing or abnormal, they may fail to provide accurate assessment results. Moreover, most methods can only obtain the threat level of targets without providing target threat levels based on the battlefield environment. Therefore, in the context of interval intuitionistic fuzziness, this paper proposes a threat assessment method based on Grey Correlation Analysis and Technique for Order Preference by Similarity to an Ideal Solution (GCA-TOPSIS) and three-way decisions. This method utilizes interval intuitionistic fuzzy entropy to calculate attribute weights. It simultaneously considers information on both similarity and correlation between targets. By introducing grey correlation coefficients to balance the similarity and correlation between targets and the ideal solution, the method computes threat degrees based on the information from both dimensions. Through fuzzy evaluation information, it constructs loss functions, calculates decision thresholds, and thereby determines the threat levels of the targets. This approach is better suited for the complex and dynamic battlefield environment, providing decision-makers with target threat levels. Finally, we conducted simulation experiments under both complete data and data anomaly conditions. The results indicate that when the data noise reaches 0.5 dB, the absolute error of GCA-TOPSIS is only 0.08. When 66.67% of the data is missing, the error is 0.16. In both scenarios, the error is much smaller than that of other threat assessment methods. This demonstrates the method's strong robustness and its suitability for complex battlefields.

Testicular histomorphometric patterns and spermatogenesis dynamics of Oecomys bicolor tomes, 1860 (Rodentia: Cricetidae).

Although the order Rodentia does not present a high risk of extinction compared to mammals as a whole, several families demonstrate high levels of threat and/or data deficiency, therefore highlighting the need for targeted research and the application of ecological and reproductive data to the development of conservation actions. The order Rodentia, the largest among mammals, includes 9 families, and the family Cricetidae is the most diverse of the Brazilian rodents. In Brazil, 12 of the 16 genera of Oecomys are found. Oecomys bicolor is known in Brazil as the 'arboreal rat' and is, found in dry, deciduous and tropical forests. The mean body weight of Oecomys bicolor was 35.8 g and the gonadal, tubular and epithelial somatic indexes were, 0.53%, 0.47% and 0.37%, respectively. Seminiferous tubules volume density was 89.72% and the mitotic and meiotic indexes corresponded to 8.59 and 2.45 cells, respectively, and the yield of spermatogenesis was 23.83 cells. The intertubular compartment represented 10.28% of the testis parenchyma and around 5% of the interstitial space was occupied by Leydig cells, whose number per gram of testis was 11.10 × 107 cells. By evaluating the biometric and histomorphometric characteristics of the testis, there is evidence that this species has a high investment in reproduction. Due to the high contribution of the seminiferous epithelium and the intertubular compartment in this species, compared to the others of the same family, it is possible to infer that the species Oecomys bicolor has a promiscuous reproductive behaviour.

Identification of Hotspots and Burnt Areas in Ogan Ilir District, South Sumatera Province

Ogan Ilir District is one of South Sumatra, Indonesia’s regencies, prone to forest and land fires. This study aims to identify hotspot distribution and analyze fire and land hazard levels from 2017 to 2022 in Ogan Ilir District using Landsat 8 imagery with the Normalized Burning Ratio (NBR) method. The study’s results show that from 2017 to 2022, 423 hotspots were recorded. Specifically, in 2017, there were 2 points; in 2018, 121 points; in 2019, 207 points; in 2021, 76 points; and in 2022, 17 points. North Indralaya is the sub-district with the highest level of forest and land fire vulnerability, with the number of events ranging from 80 to 164. West Pamulutan and Pamulutan are at a high hazard level, with incidents ranging from 33 to 79. Meanwhile, Indralaya and South Indralaya sub-districts have a medium level of danger, with events ranging from 19 to 32. The low threat level for forest and land fires is spread across all sub-districts in Ogan Ilir District, with the number of events ranging from 1 to 18.

A new communication approach to encourage lung cancer screening action in rural eligible populations

ObjectiveThe purpose of this study was to develop an effective communication approach to encourage lung cancer screening action within rural screening-eligible populations. MethodsAn iterative research approach using targeted engagement with the priority population was used. Findings were triangulated through multiple methods, including two surveys and concept testing interviews. The Health Belief Model and the Extended Parallel Process Model served as study frameworks. ResultsInitial findings suggest that threat levels are high in the priority population and an emphasis on barrier mitigation messaging may drive action. Health campaign posters integrating these findings were developed and tested with the priority population. The new health campaign posters were tested against examples of previously used health campaign posters. Findings suggest that the new health campaign posters were more effective in spurring lung cancer screening motivation and intention to act in the priority population compared to current health campaign poster examples. ConclusionMessaging focused on gain-framing, inoculation messaging, and barrier mitigation may be more effective in encouraging lung cancer screening action in rural eligible populations. InnovationThis project outlines a systematic process to developing effective, targeted communication approaches using behavior change and persuasive communication frameworks along with engagement from priority populations.