Action Decision Research Articles

Combining the Servqual and Kano Models to Find Out How Satisfied Customers are with Swab and PCR Services

Swabs and PCR are ways to track patients infected with COVID-19. One private swab and PCR service provider in Surabaya offers swab and PCR tests with fast results and is open 24 hours a day. This research aims to determine service quality performance, identify the causes of consumer dissatisfaction, and identify service attributes that must be maintained and improved for Swab and PCR services in Surabaya. This research uses an integration of the Servqual and Kano methods. The integration of Servqual and Kano determines the service attributes to be improved. Data was obtained from a questionnaire using the five-dimensional Servqual approach, then calculated to get a gap value and categorized using the Blauth formula. The Servqual gap and the Blauth formula's category values are combined to make action decisions. The results state that swab and PCR service providers still need to improve all factors used in this research. Three attributes fall into the weak and indifferent category, so the decision that needs to be made is to ignore them because they do not affect consumer satisfaction and are not a priority for improvement. The other twenty-one attributes fall into the weak and one-dimensional category, meaning companies must improve these attributes to satisfy consumers. Companies need to make improvements to ensure better service, including increasing the number of medical officers to reduce fatigue and queues and providing training on medical procedures and communication skills for medical officers.

Functioning in the hot seat: exploring the competencies of police incident commanders

PurposeIncident commanders (ICs) are senior police officials tasked with being the key operational decision-makers and leading a command team during major, critical and public order incidents (e.g. bomb threats, hostage situations and protests). Such events are often characterized by heavy time pressures and little information, requiring a highly skilled, integrated emergency response across multiple agencies and significant police planning, organizing and management. ICs must possess the necessary skills, traits and behaviors to deal with such incidents and their challenges. Therefore, the purpose of this study is to identify the competencies of ICs.Design/methodology/approachWe conducted a thematic analysis of thirty-eight (n = 38) in-depth interviews with police personnel who have professional experience as ICs.FindingsResults provided information on the competencies important for effective incident command, including a range of skills, traits and behaviors these police personnel should exhibit, such as command presence, decision-making, confidence, risk assessment, teamwork, task management, stress management, humility and others.Originality/valueWe provide a novel literature contribution by proposing a framework of police IC competencies and their interrelatedness based on first-hand interviews with experts in the field. Practitioners and policymakers need to know actionable strategies for developing standardized training and assessment curricula for ICs. The next steps are to delineate what skills, traits and behaviors are trainable and need to be selected for at the time of recruitment (e.g. occupational aptitude, personality). We provide the foundation upon which researchers and practitioners can make actionable decisions on moving forward to attain these important goals.

Fostering Creativity in Order to Develop Mental Model Templates for Planning in National Emergencies

National Emergencies set the need for quick responses and actions from all institutions that are responsible for national security and/or citizens’ health. Course of action development as part of mitigation planning in such situations, is a complex and difficult procedure because of the uncertainty of the future events, the risk associated with decisions for human actions and the time pressure because of the emergency. This means that planning for addressing national emergencies is not a common and simple task. Moreover, because emergencies appear seldom, most of the stakeholders have lack of experience. Thus, they need more time to assimilate the incoming information into their mission planning process and finally to propose the appropriate courses of actions. An antidote to the above difficulties can be the appropriate training in combination with the enhancement of the creativity of the stakeholders. In order to address that, we propose a novel methodology of creating mind map templates, based on creativity techniques, for specific operations that can be applied to national emergencies. Our methodology, called “MEMOS”, was developed according to the relative theoretical frameworks and then tested with a case study, including hypothetical security scenarios in national emergency situations. The proposed templates can be used as inspiration tools or idea tanks in order to guide and speed up the process of course of action development in mitigation planning for similar future security operations.

Predicting and Understanding Human Action Decisions: Insights from Large Language Models and Cognitive Instance-Based Learning

Large Language Models (LLMs) excel in tasks from translation to complex reasoning. For AI systems to help effectively, understanding and predicting human behavior and biases is essential. However, it remains an open question whether LLMs can achieve this goal. This paper addresses this gap by leveraging the reasoning and generative capabilities of LLMs to predict human behavior in two sequential decision-making tasks. These tasks involve balancing between exploratory and exploitative actions and handling delayed feedback, which is essential for simulating real-life decision processes. We compare the performance of LLMs with a cognitive instance-based learning (IBL) model, which imitates human experiential decision-making. Our findings indicate that LLMs excel at rapidly incorporating feedback to enhance prediction accuracy. In contrast, the IBL model better accounts for human exploratory behaviors and effectively captures loss aversion bias — the tendency to choose a sub-optimal goal with fewer step-cost penalties rather than exploring to find the optimal choice, even with limited experience. The results highlight the benefits of integrating LLMs with cognitive architectures, suggesting that this synergy could enhance the modeling and understanding of complex human decision-making patterns.

Translating science into actions to conserve Amazonian freshwaters

AbstractDespite the importance of freshwater ecosystems to social‐ecological systems of the Amazon, conservation in the region historically has focused on terrestrial ecosystems. Moreover, current information on pressing management and conservation needs specific to freshwaters is scattered across multiple disciplines and generally focused on particular threats, habitats, and taxa. This disparateness of information limits the ability of researchers and practitioners to set priorities and implement actions that comprehensively address challenges faced by freshwater ecosystems. To reduce this research‐implementation gap, we reviewed the scientific literature on Amazon freshwater conservation to identify pressing actions to be taken and potential directions for their implementation. We identified 63 actions gleaned from 174 publications. These were classified into six major themes: (i) implement environmental flows, (ii) improve water quality, (iii) protect and restore critical habitats, (iv) manage exploitation of freshwater organisms, (v) prevent and control invasive species, and (vi) safeguard and restore freshwater connectivity. Although each action may face different implementation challenges, we propose three guiding principles to support action planning and decisions on‐the‐ground. We conclude with a reflection on potential future directions to place freshwaters into the center of policies and agreements that target the conservation of the Amazon.

A-273 Rapid, Portable Invasive Fungal Infection Diagnostic and Candida Antimicrobial Susceptibility Testing

Abstract Background Traumatic wounds are associated with a higher risk of invasive fungal infections (IFI), which lead to a significant increase in amputation or death. Actionable treatment decisions are hampered because true infections can be difficult to differentiate from external wound contaminates, and tissue biopsy and quantification of fungal load is required to determine if treatment is necessary, which currently takes several days. GeneCapture is developing the CAPTURE 60-minute, portable infection identification platform to detect infectious levels of common fungi including the genera Aspergillus, Fusarium, and Scedosporium, the family Herpotrichiellaceae, and the order Mucorales. The company is also pursuing rapid identification and antimicrobial susceptibility testing for Candida species from multiple infection types. Methods This study seeks to determine the Limit of Detection (LoD), sensitivity and specificity of the CAPTURE ID assay for fungal pathogens. Since tissue biopsy samples must be used to assess the presence of IFI in wounds, GeneCapture has developed a manual process for the crude homogenization of muscle tissue to allow this matrix to be used as the starting sample for the ID assay. Mock samples were tested for inclusivity and exclusivity on a series of IFI ID panels against multiple strains of the included fungi, against fungi not yet specifically detected on the panel, and against bacteria that commonly infect wounds. While the LoD for yeasts may be determined in CFU/mL, there is no similar, easy-to-define metric for molds. GeneCapture has developed a quantitative PCR method to detect the single copy beta-tubulin gene to roughly correlate fungal dry mass and nuclei number to assay signal for molds cultured in Potato Dextrose Broth. Determining beta-tubulin copy numbers for extracts from mock samples then allowed detection of the progression of IFI over the course of infection. Lastly, antimicrobial susceptibility testing (AST) was performed on two species of Candida to validate utilizing GeneCapture’s rapid phenotypic AST method for fungal infections. Results To date, the CAPTURE ID panel has been tested against 27 included or excluded strains of fungi or bacteria with 97% sensitivity and 100% specificity. The current LoD for mold organisms varies from approximately 1,000 nuclei for Aspergillus species, to 100,000 nuclei for Fusarium species. Additional work to understand this range is underway. Lastly, we have correctly determined the susceptibility of Candida species using our novel approach within 4-6 hours. Conclusions GeneCapture’s ID and AST technology offer a unique solution to address the increasing prevalence of fungal infections. Our platform can identify the most common fungal components in a wound within 60 minutes of receiving a tissue biopsy sample. Candida infections occur across multiple matrices and rapidly identifying the species of Candida and then determining its phenotypic susceptibility profile will have a large impact on treating these difficult pathogens.

Life cycle assessment based optimization of scenarios of reusable glass bottles using context-specific key parameters

Reusable glass bottles are experiencing a resurgence, driven notably by societal concerns and regulations. While single-use glass bottles generally have higher environmental footprint compared to plastic bottles, reusable systems could reduce both impacts related to single-use (e.g., climate change, energy consumption) and plastics (e.g., microplastic pollution). The environmental benefits of reusable bottles can vary across systems and this can be overlooked by stakeholders who rely on generic results for communication and a limited number of parameters to design their systems. This study addresses this gap by developing a systematic analysis of the variability of life cycle assessment results, within the specific case study of a new beverage. As a result, a list of key parameters to consider for the specific case study is set, enabling to propose targeted mitigation strategies. The commonly used generic key parameters are complemented with context-specific key parameters, empowering stakeholders to develop efficient systems and communicate their environmental performance accurately. Different configurations are likely to be influenced by other key parameters, and require specific mitigation strategies. In this perspective, stakeholders need assistance in: (1) designing context-specific strategies, and (2) translating – complex and plural – life cycle assessment results into actionable decisions.

Ensuring the reasonableness of criminal proceedings’ terms

It is indicated that the current Criminal Procedure Code of Ukraine dated April 13, 2012 for the first time at the legislative level established such a principle of criminal proceedings as the reasonableness of terms. Yes, in accordance with Article 28 of the Criminal Code of Ukraine during criminal proceedings, each procedural action or procedural decision must be performed or made within a reasonable time. The article is devoted to the analysis of criminal proceedings’ principle “reasonable terms”. During criminal proceedings, each procedural action or procedural decision must be performed or adopted within a reasonable terms. Terms that are objectively necessary for the execution of procedural actions and the adoption of procedural decisions are considered reasonable. Reasonable terms cannot exceed the terms of execution of individual procedural actions or adoption of individual procedural decisions provided for by the CPC of Ukraine. The pre-trial investigation is carried out within a reasonable terms by the prosecutor, the investigating judge (with regard to the time frame for consideration of issues falling within his competence), and the court conducts the court proceedings. The criteria for determining the reasonableness of criminal proceedings terms are: 1) the complexity of criminal proceedings, which is determined taking into account the number of suspects, accused persons and criminal offenses in respect of which the proceedings are being carried out, the volume and specifics of procedural actions necessary for conducting a pre-trial investigation, etc.; 2) behavior of participants in criminal proceedings; 3) the manner in which investigators, prosecutors, and courts exercise their powers. Criminal proceedings against a person in custody, a minor or a criminal offense committed against a minor must be carried out immediately and considered in court as a matter of priority. It is important to ensure the reasonableness of criminal proceedings terms to study this principle not only in science, but also in judicial practice, in particular, the practice of the European Court of Human Rights. Adhering to the reasonableness of the terms of criminal proceedings will contribute to the exercise of a person’s right to judicial protection, will ensure an effective and prompt investigation and trial, and thus will ensure the fulfillment of criminal proceedings’ tasks.

Noradrenergic modulation of saccades in Parkinson's disease.

Noradrenaline is a powerful modulator of cognitive processes, including action decisions underlying saccadic control. Changes in saccadic eye movements are common across neurodegenerative diseases of ageing, including Parkinson's disease. With growing interest in noradrenergic treatment potential for non-motor symptoms in Parkinson's disease, the temporal precision of oculomotor function is advantageous to assess the effects of this modulation. Here, we studied the effect of 40 mg atomoxetine, a noradrenaline reuptake inhibitor, in 19 people with idiopathic Parkinson's disease using a single dose, randomized double-blind, crossover, placebo-controlled design. Twenty-five healthy adult participants completed the assessments to provide normative data. Participants performed prosaccade and antisaccade tasks. The latency, velocity and accuracy of saccades, and resting pupil diameter, were measured. Increased pupil diameter on the drug confirmed its expected effect on the locus coeruleus ascending arousal system. Atomoxetine altered key aspects of saccade performance: prosaccade latencies were faster and the saccadic main sequence was normalized. These changes were accompanied by increased antisaccade error rates on the drug. Together, these findings suggest a shift in the speed-accuracy trade-off for visuomotor decisions in response to noradrenergic treatment. Our results provide new evidence to substantiate a role for noradrenergic modulation of saccades, and based on known circuitry, we advance the hypothesis that this reflects modulation at the level of the locus coeruleus-superior colliculus pathway. Given the potential for noradrenergic treatment of non-motor symptoms of Parkinson's disease and related conditions, the oculomotor system can support the assessment of cognitive effects without limb-motor confounds on task performance.

The driving mechanism of citizens’ protective behaviors for rainstorm flood disasters in China: an empirical study based on the protection motivation theory and protective action decision model

[Background/significance]Rainstorm floods have become a high-impact natural disaster and are expected to become more extreme shortly, seriously threatening human safety. Although the government issues timely and precise rainstorm flood warning information, citizens remain indifferent and engage in maladaptive behavior. Therefore, understanding the relationship between emergency information, psychological cognition, individual characteristics, and protective behavior is crucial for effective risk information communication and evacuation guidance. [Method/process]This study utilizes the protection motivation theory (PMT) and protective action decision model (PADM) to develop a structural equation model (SEM) that evaluates the factors driving both protective and non-protective behaviors of individuals to rainstorm flood disasters. [Result/conclusion]The findings indicate that the disaster experience and emergency information received significantly shape how individuals perceive risks, their ability to manage them, and who should be accountable for the disaster. The findings further indicate that how people view their ability to handle a risk situation (perceived coping ability) and who they think is responsible for the situation (perceived attribution of responsibility) directly influence whether they will take protective behaviors. Based on these results, this study puts forward policy recommendations for emergency information release strategies to enhance citizens' willingness to adopt protective behaviors.

Perancangan Mesin Pengupas Singkong dengan Metodologi NIDA-QFD untuk Industri Keripik Singkong ABC Banyuwangi

Banyuwangi produces potential cassava chips. However, due to slow manual stripping, production capacity is low, market demand is high, and product quality decreases. This study develops an optimized peeling machine using NIDA-QFD to meet user needs and increase innovation. Experimental design model and 5 alternative actions of cassava peeling machine. ABC Banyuwangi Industry with 10 respondents, including owners and employees, was given intervention in the action decision. NIDA-QFD developed a cassava peeling machine design that is efficient and minimizes risk. Alternative 3 was chosen, with user body dimensions (height 110-180 cm), using sturdy materials (steel angle profile, stainless steel plate), and having 5 peeling rolls (diameter 80 mm, length 910 mm) for an effective and efficient stripping process. The 220 volt 1/2 PK AC drive system ensures the roll rotates with optimal speed and torque. The cassava skin remover is made of stainless steel which is rust-resistant and easy to clean, so it is feasible to overcome the problem of manual peeling of cassava and opportunities for progress in the cassava chips industry.

A stochastic model-based control methodology for glycemic management in the intensive care unit

Introduction: Intensive care unit (ICU) patients exhibit erratic blood glucose (BG) fluctuations, including hypoglycemic and hyperglycemic episodes, and require exogenous insulin delivery to keep their BG in healthy ranges. Glycemic control via glycemic management (GM) is associated with reduced mortality and morbidity in the ICU, but GM increases the cognitive load on clinicians. The availability of robust, accurate, and actionable clinical decision support (CDS) tools reduces this burden and assists in the decision-making process to improve health outcomes. Clinicians currently follow GM protocol flow charts for patient intravenous insulin delivery rate computations.Methods: We present a mechanistic model-based control algorithm that estimates the optimal intravenous insulin rate to keep BG within a target range; the goal is to develop this approach for eventual use within CDS systems. In this control framework, we employed a stochastic model representing BG dynamics in the ICU setting and used the linear quadratic Gaussian control methodology to develop a controller.Results: We designed two experiments, one using virtual (simulated) patients and one using a real-world retrospective dataset. Using these, we evaluated the safety and efficacy of this model-based glycemic control methodology. The presented controller avoids hypoglycemia and hyperglycemia in virtual patients, maintaining BG levels in the target range more consistently than two existing GM protocols. Moreover, this methodology could theoretically prevent a large proportion of hypoglycemic and hyperglycemic events recorded in a real-world retrospective dataset.Discussion: The current version of the methodology shows potential usefulness in GM of ICU patients. However, it is limited to a subgroup of the ICU patient population, who are fed through and enteral tube and delivered intravenous insulin. After extending to a broader ICU patient population who can consume oral nutrition and are delivered subcutaneous insulin for GM, the methodology could be tested with pilot studies and clinical trials for eventual use as a CDS tool.

Judgmental adjustment of demand forecasting models using social media data and sentiment analysis within industry 5.0 ecosystems

Industry 5.0 ecosystems focus on a human-centric approach to operations and supply chain management by integrating stakeholders, advanced technologies, and processes. While incorporating social media (SM) information into demand forecasting can significantly improve accuracy, it also brings about several challenges. This paper proposes an approach to leverage Big Data originating from SM networks combined with human judgment to build demand forecasts for new products. The structured methodology is demonstrated to improve forecast accuracy in a real case of a F&B company while providing several insights into the challenges and opportunities of integrating advanced information technology into the demand forecasting process. The main challenges include effectively categorising the impact factors of SM on demand forecasting, translating insights from SM into actionable decisions, and ensuring the accuracy and reliability of the data obtained from SM networks. Future studies should involve collaborative expert input and validating the approach across various companies and industries.

Predicting households’ attitudes and product adoption intentions

PurposeThe present study aims to examine the households’ attitudes and intentions to adopt an indoor air purifier against the smog crisis in India by using a comprehensive theoretical framework based on the combination of the Protective Action Decision Model (PADM) and the Theory of Planned Behavior (TPB). The United Nations Sustainable Development Goals (SDGs) 2030 also emphasized ensuring a healthy and safe life, especially by achieving SDG-3, SDG-11 and SDG-13.Design/methodology/approachUsing purposive sampling, the data were collected through a survey questionnaire distributed to 382 households, and study hypotheses were assessed by using partial least squares structural equation modeling employing SmartPLS.FindingsThe results revealed that mental health risk perception (MHRP) was the most influential determinant of households’ attitudes toward adopting air purifiers, followed by smog knowledge, physical health risk perception (PHRP), information seeking and product knowledge. Notably, results revealed that households’ attitude is a leading determinant of their adoption intention toward the air purifier compared to subjective norms (SN) and perceived behavioral control (PBC).Originality/valueTo the best of the authors’ knowledge, the present study is the first to provide new insights into an individual’s protective behavior response toward ecological hazards by examining the households’ adoption intention toward the air purifier against the smog crisis using PADM and TPB model inclusively. In addition, the present study analyzes the impact of both PHRP and MHRP on individuals’ protective behavior separately. Also, this study provides theoretical contributions and important practical implications for the government, manufacturers and air purifier sellers.

Community preparedness for natural hazards in two Chilean coastal cities

Chile is a country with high exposure to earthquakes and tsunamis. However, cities present different levels of community preparedness. Understanding the decision-making process for adopting preparedness measures is essential to motivating community participation while considering the local needs of each city. Considering the Protective Action Decision Model (PADM) to understand community preparedness, this study explores the role of risk perception, risk awareness, and trust in authorities in community preparedness in two coastal cities in Chile. A sample of 1093 inhabitants of two coastal cities, Valparaíso and Concepción, participated in the study. The results indicate significant differences between coastal cities' preparedness levels and their determinants, particularly risk perception and awareness. Despite these differences, our results show that trust in authorities is related to Chile's community preparedness levels in both locations.

A Method for Multi-AUV Cooperative Area Search in Unknown Environment Based on Reinforcement Learning

As an emerging direction of multi-agent collaborative control technology, multiple autonomous underwater vehicle (multi-AUV) cooperative area search technology has played an important role in civilian fields such as marine resource exploration and development, marine rescue, and marine scientific expeditions, as well as in military fields such as mine countermeasures and military underwater reconnaissance. At present, as we continue to explore the ocean, the environment in which AUVs perform search tasks is mostly unknown, with many uncertainties such as obstacles, which places high demands on the autonomous decision-making capabilities of AUVs. Moreover, considering the limited detection capability of a single AUV in underwater environments, while the area searched by the AUV is constantly expanding, a single AUV cannot obtain global state information in real time and can only make behavioral decisions based on local observation information, which adversely affects the coordination between AUVs and the search efficiency of multi-AUV systems. Therefore, in order to face increasingly challenging search tasks, we adopt multi-agent reinforcement learning (MARL) to study the problem of multi-AUV cooperative area search from the perspective of improving autonomous decision-making capabilities and collaboration between AUVs. First, we modeled the search task as a decentralized partial observation Markov decision process (Dec-POMDP) and established a search information map. Each AUV updates the information map based on sonar detection information and information fusion between AUVs, and makes real-time decisions based on this to better address the problem of insufficient observation information caused by the weak perception ability of AUVs in underwater environments. Secondly, we established a multi-AUV cooperative area search system (MACASS), which employs a search strategy based on multi-agent reinforcement learning. The system combines various AUVs into a unified entity using a distributed control approach. During the execution of search tasks, each AUV can make action decisions based on sonar detection information and information exchange among AUVs in the system, utilizing the MARL-based search strategy. As a result, AUVs possess enhanced autonomy in decision-making, enabling them to better handle challenges such as limited detection capabilities and insufficient observational information.

Solid Waste in Urban Areas: A Multidimensional Statistical Approach on Irregular Disposal and Burning in the Municipality of Governador Valadares, Minas Gerais

The improper disposal of urban waste is a global concern, especially in large cities considering aspects of environmental and visual pollution. This study provides a detailed analysis of the municipality of Governador Valadares, Minas Gerais, identifying local nuances and a better understanding of this issue to support decisions for corrective actions. It assesses the persistence and incidence of waste burning at irregular disposal sites in the municipality, emphasizing its environmental and health impacts. This work utilized a combined approach of georeferenced mapping with Google Earth Pro images, complemented by in-situ checks with GPS devices. The statistical analysis of the collected data was performed using the PSPP software. Statistical analyses were supported by contingency tables, the application of the chi-square test, Phi, Cramer's V, and Odds Ratio, evaluating the characteristics of the associations. A strong association was identified between the persistent disposal of solid waste in undeveloped areas and the presence of tree pruning and gardening waste. The research also demonstrated a significant association of areas with signs of burning that were located in public spaces. Additionally, a significant statistical association was confirmed at sites where paper and plastic disposals and burning were identified. This research expands the understanding of disposal practices in urban contexts and provides a replicable model of combined georeferenced analysis with physical checks, in addition to the risks to public health and the environment. The results obtained demonstrate direct implications for waste management policies, raising awareness of the consequences of improper disposal and burning.

Gateway community stakeholders’ perceived impacts of protected area management actions: The case of North Carolina (U.S.) state parks

Many protected area managers contend with increasing demand and insufficient funding (e.g., overcrowding, overuse, maintenance shortfalls, and staffing shortages). To combat these challenges, managers are exploring management actions (i.e., differential pricing, amenity pricing, reservation systems, and demand-based pricing) to increase revenue and distribute or reduce visitor use during peak times. However, implementation of these management actions may displace visitors, affecting gateway community stakeholders (e.g., park staff, affiliated nonprofits, tourism operators, destination management/marketing organizations (DMO), and elected officials) who benefit from state parks. Therefore, it is crucial to understand the effects these actions may have on gateway community stakeholders. Utilizing Weber's theory of formal and substantive rationality (WTFSR) coupled with the triple bottom line (economic, environmental, and social impacts), we conducted a concurrent, nested mixed methods study with 25 gateway community stakeholders of North Carolina State Parks (NCSP). Analysis of 25 semi-structured interviews and embedded rating and ranking questions provided a deeper understanding of stakeholders' preferred management actions, motivations for those preferences, and perceived impacts of NCSP management actions. Apart from demand-based pricing, gateway community stakeholders expressed overall positive economic, environmental, and social sentiments towards the proposed management actions, suggesting a suite of actions may be ideal for increasing revenue and distributing or reducing visitor use during peak times in protected areas. Management implications•Gateway community stakeholders can effectively differentiate between suites of management options to enhance environmental protections, community benefits, and profits.•State resident discounts, amenity pricing, and reservation systems were all highly ranked across multiple stakeholder groups, suggesting NCSP has multiple options to increase revenue and distribute or reduce visitor use during peak times. However, demand-based pricing had limited support from stakeholders suggesting NCSP should prioritize other management actions. The varying levels of support for management actions makes it crucial for NCSP to communicate their management action decisions with stakeholders.•Protected area managers must sustain relationships with gateway community stakeholders to be able to understand stakeholders' perspectives on the impacts of management actions.•Beyond NC, this study provides a strategy for protected areas facing similar challenges to assess how management actions may impact gateway community stakeholders or other key stakeholders (e.g., park users, underserved communities).

Understanding residents’ risk information seeking, processing and sharing regarding waste incineration power projects

Waste incineration power projects (WIPP) may face suspicion and resistance due to potential environmental and health risks. Information behavior has become a crucial way for residents to manage the risks. By integrating the risk information seeking and processing (RISP) model with the protective action decision model (PADM), the study develops a four-stage model that incorporates information acquisition and perceived benefits to understand the determinants of residents’ information behaviors regarding WIPP. A total of 1726 respondents were interviewed. The results indicate that 77.5 % respondents frequently use social media. Of the twenty-five hypothesized paths, twenty-one were found to be significant. Information acquisition from social media plays a larger predictive role than that from official media. Perceived risks, benefits, and knowledge positively predict information sharing, systematic processing, and information seeking, respectively. Perceived knowledge has the strongest direct influence on information insufficiency (β = 0.24, p < 0.001) with the explained variance of systematic processing being the highest (R2 = 0.51). Interesting, the relationship between information insufficiency and information sharing, as well as between relevant channel beliefs and information sharing, are negative. Theoretical insights into extending the PADM and the RISP model are provided, as well as managerial implications for risk communication about WIPP.

The Role of Microbiota in Animal Physiology: An Integrative Review

This review examines a broad range of microbiota functions in terms of animal physiology, including its effect on digestion, immunological capabilities, metabolism, reproductive regulation, and nervous system. Its purpose is to provide a systematic overview of on-going research, determine the gap of knowledge and evaluate how environmental factors and the alteration of the microbiome can help to improve the health of animals and contribute to the conservation effort. This study describes the roles of microflora in digestion and absorption of nutrients, modulation of the immune system, and reproduction components and newborn development. Alongside this, it reports the interplay between the bacteria and the central nervous system, which underpins the behavior and mental health. This mission of the review is to offer an integrated overall comprehension of microbiota, which will be used to detect applicable insights and make actionable decisions for future research, veterinary care, and conservation efforts.