High Level Of Confidence Research Articles

Proposing the Model to Accelerate SMEs to Apply Green Economy Practices Through the Utilization of Social Crowdfunding

Following Indonesia's commitment to promoting the achievement sustainable consumption and production practices (RCP- SDGs Number 12), a plan must be put in place to motivate important players (SMEs) to support the green economy. The limitations of SMEs in terms of funding to be able to implement green economic practices are accommodated through access to financial technology, namely social crowdfunding. To gain insight into how SMEs implement green economic practices by utilizing social crowdfunding, a survey was conducted on 75 SMEs use descriptive research design. The results of the descriptive analysis found that some SMEs have not been able to take advantage of social crowdfunding due to several reasons: not being able to access the right website, having requirements that are difficult to fulfill and their technology skills are not yet good. An interesting insight that was extracted from the results of this survey is the high level of confidence among SMEs that implementing green economic practices using social crowdfunding can improve business performance and are confident that they can overcome all difficulties. The proposed conceptual model can apparently be supported by research results which produce the proposition namely:" willingness to participate in implementing green economic practices using social crowdfunding needs to be driven by creating strong awareness and interest by triggering 3 important determinants, namely stakeholder management, community engagement and entrepreneurship strategy”. In the future, this conceptual modeling can be used to conduct quantitative research so that it can explore the facts in the field in a comprehensive manner.

The implementation and evaluation of a mock trial using a flipped classroom pedagogy in practical nursing education.

Background: This quality improvement study explores the implementation and evaluation of a mock trial within a flipped classroom pedagogy to help first-year practical nursing learners meet the class objectives. Methods: Sixty-two (N=62) practical nursing learners participated in a mock trial as part of their first year Nursing Arts course at Bow Valley College in July 2022. The mock trial was evaluated using qualitative and quantitative data collection. Results: The thematic analysis suggested that a mock trial using a flipped classroom pedagogy may be an effective way of teaching course objectives. The learners reported a moderate to high level of confidence in managing challenging situations after participating in the mock trial. Conclusions: The study highlights the potential benefits of incorporating a mock trial using a flipped classroom pedagogy in practical nursing education.

Cognitive assessment of nursing home residents: Survey data on tools used and perceptions of use among social service professionals in one U.S. state.

Background: Social service professionals routinely use screening tools to assess for cognitive decline or identify suspected dementia in nursing home residents. Published literature lacks details about the specific tools used and how professionals use and perceive them in practice. The aim of this study is to better understand cognitive screening roles performed by nursing home social service professionals and how they view their use and efficacy.Methods: An online survey was administered to all 230 nursing homes in the US state of Alabama between October 2021 and March 2022. Fifty-three social service professionals who conduct resident cognitive screenings responded to the survey.Results: In addition to completing the US-mandated Brief Interview of Mental Status (BIMS) quarterly, 75% of participants reported using additional tools, most notably the Mini Mental Status Examination (MMSE). Participants reported using different tools for varied purposes. Those who used both the BIMS and MMSE rated the BIMS significantly higher on ease and time to administer while rating the MMSE higher on reliability and validity. Although most participants reported high levels of confidence using the tools, over half of participants indicated interest in further training in cognitive assessment tools.Discussion: Findings provide evidence regarding who administers nursing home cognitive screenings, which tools are used, and their experiences using those tools. Participant responses reveal the value of using multiple screening tools for improved detection of cognitive status and decline for residents as well as a need for additional training in cognitive assessment. Findings also suggest that the primary tool used for cognitive screening may be quick and easy to use at the expense of perceived reliability and validity. Further evaluation of nursing home cognitive assessment is needed.

Effects of acupuncture on shoulder impingement syndrome: A systematic review and meta-analysis.

Shoulder impingement syndrome (SIS) is a common condition that causes chronic shoulder pain. The effectiveness of acupuncture in treating chronic shoulder pain has been documented in previous studies; however, existing systematic reviews and meta-analyses have often excluded Chinese databases and combined different types of acupuncture interventions, such as electroacupuncture, warm acupuncture, pharmacopuncture, and acupotomy. Thus, this study specifically examines the exclusive impact of manual acupuncture on SIS. Several databases, including PubMed, Cochrane Central, Embase, 1 Chinese database (China National Knowledge Infrastructure), and 5 Korean databases (ScienceON, Oriental Medicine Advanced Searching Integrated System, KoreaMed, Korean Studies Information Service System, and KMBASE), were systematically searched for relevant studies. The quality of the included studies was evaluated using the Cochrane Assessment Tool for Risk of Bias Version 2. Data collected from the selected studies were synthesized for meta-analysis. The primary outcome was a pain scale score, and the secondary outcomes were shoulder function and disability. This study included 5 randomized controlled trials. The primary outcome assessment revealed significantly reduced pain (standardized mean difference [SMD] = -0.50, 95% confidence interval [CI] = -0.74 to -0.27) and improvements in shoulder function and disability (SMD = -0.57, 95% CI = -0.96 to -0.19). A subgroup analysis based on treatment duration indicated that short-term acupuncture treatment (≤4 weeks) exhibited a high level of confidence with low heterogeneity (SMD = -0.37, 95% CI = -0.73 to -0.02). Manual acupuncture is effective for relieving pain and improving shoulder function and disability in patients with SIS. However, further research is necessary to validate these findings owing to the limited number of patients and heterogeneity among the studies reviewed.

Online Supercritical Fluid Chromatography Hyphenated to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry with Quadrupole Detection for Microalgae Bio-Oil Characterization.

Microalgae are an attractive feedstock for biofuel production thanks to their renewable nature, high growth rate, and ability to use anthropogenic CO2. The conversion of microalgae by hydrothermal liquefaction (HTL) leads to a solid residue, a gaseous phase, and a biocrude. However, the bio-oil is rich in heteroatoms and requires upgrading processes to be used as biofuels. For these treatments to be effective, detailed knowledge of the sample is crucial. The bio-oil was characterized by direct introduction into a Fourier transform ion cyclotron resonance mass spectrometer (DI-FTICR MS) with an electrospray ionization source (ESI). Thousands of molecular formulas were assigned with a high level of confidence, mainly compounds with nitrogen and oxygen atoms. Additionally, the bio-oil was analyzed by coupling supercritical fluid chromatography (SFC) and FTICR to combine the separation power of SFC to the high performances of a 12 T FTICR. Quadrupole detection (2ω) was used in FTICR to have a high resolving power with a lower transient time. The coupling allowed the separation of many isomers along the chromatogram, showing the isomeric complexity of microalgae bio-oils. Moreover, classes of compounds were separated according to their heteroatom class thanks to the SFC separation. In this work, the advantages of DI-FTICR MS and SFC-FTICR MS proved complementary, and DI was useful to study the bio-oil at the molecular scale thanks to the high performances, while SFC proved useful for the characterization at the isomeric scale. This demonstrated the significant potential of this new online hyphenated technique for the characterization of complex matrices.

Accuracy of stochastic finite element analyses for the safety assessment of unreinforced masonry shear walls

ABSTRACT To examine structural safety and reliability, an accurate prediction of the variability of structural resistance must first be determined. This may be achieved through extensive physical testing or, more commonly in modern research, synthetic data generation, such as stochastic finite element analyses (SFEAs). Due to the prevalence and versatility of such techniques, and the need for a high level of confidence when performing a safety assessment, an understanding of the accuracy of data derived from SFEAs is essential. In this paper, SFEA models have been developed to predict the responses of 16 unreinforced masonry walls tested in a laboratory under cyclic in-plane lateral loading. Each SFEA has been developed to reflect the as-built conditions of these experimental specimens and focus on predicting the shear capacity of the failure mechanisms that unreinforced masonry shear walls are susceptible to. From the results of these SFEAs, the accuracy (quantified as model error) of this modelling strategy has been estimated by comparing the peak in-plane shear resistances of the laboratory and numerical models.

Automatic target detection in vehicle images based on YOLOv10 deep learning algorithm

In this paper, we explore the effect of its application in vehicle image detection based on the latest YOLOv10 model.YOLOv10, as the latest version in the YOLO series, inherits and optimises the advantages of the previous generations of models, aiming to provide higher detection accuracy and faster inference speed. In our experiments, we firstly divided the dataset reasonably and trained the YOLOv10 model with data from the training set. By analysing the Precision-Recall curve, we found that the area below the PR curve is larger, which indicates that the AUC value of the model is close to 1, thus reflecting the superiority of the model in classification performance. In addition, from the F1-confidence curve, the model is still able to maintain good classification results at higher confidence levels and maintains high F1 scores in most confidence intervals, which further validates the reliability of the model. Test results show that the trained YOLOv10 model is able to accurately recognise vehicles and effectively predict vehicle types. This enables the model to monitor the vehicle conditions on the road in real time and achieve accurate detection and classification of road traffic targets. Therefore, this paper demonstrates the powerful ability of YOLOv10 in the field of vehicle detection, which provides an important reference for the development of future intelligent transport systems. Overall, this study not only verifies the effectiveness of YOLOv10 in practical applications, but also lays the foundation for further improvement of target detection technology.

One-index vector quantization based adversarial attack on image classification

To improve storage and transmission, images are generally compressed. Vector quantization (VQ) is a popular compression method as it has a high compression ratio that suppresses other compression techniques. Despite this, existing adversarial attack methods on image classification are mostly performed in the pixel domain with few exceptions in the compressed domain, making them less applicable in real-world scenarios. In this paper, we propose a novel one-index attack method in the VQ domain to generate adversarial images by a differential evolution algorithm, successfully resulting in image misclassification in victim models. The one-index attack method modifies a single index in the compressed data stream so that the decompressed image is misclassified. It only needs to modify a single VQ index to realize an attack, which limits the number of perturbed indexes. The proposed method belongs to a semi-black-box attack, which is more in line with the actual attack scenario. We apply our method to attack three popular image classification models, i.e., Resnet, NIN, and VGG16. On average, 55.9 % and 77.4 % of the images in CIFAR-10 and Fashion MNIST, respectively, are successfully attacked, with a high level of misclassification confidence and a low level of image perturbation.

Perceptions, Expectations, Reality, and Public Confidence Regarding the Role of Pharmacists in Pharmacy Services in Bandung

Background: The shifting from the old paradigm to the new paradigm with the philosophy of pharmaceutical care demands pharmacists to enhance the quality of pharmaceutical services. However, this role has not been optimally fulfilled, especially in the community setting.Objectives: This study aimed to identify the perceptions and expectations, the gap between expectations and reality, and public confidence as well as to analyze the relationship between sociodemographic factors and the perceptions, expectations, and public confidence in Bandung City regarding the role of pharmacists in pharmaceutical services.Methods: A cross-sectional study was conducted using a validated survey instrument with 440 respondents in Bandung, West Java, from March to April 2023. The survey data were analyzed descriptively and through inferential statistics.Results: The analysis showed that 58.41% of the community had a positive perception, 56.82% had high expectations, the average gap between expectations and reality was 14.04%, and more than 51.36% had a high level of public confidence in pharmacists. Sociodemographic factors influencing perceptions were age and the highest level of education (p = 0.005; p = 0.003), factors influencing public confidence were age, the highest level of education, residence address according to ID card (KTP), and occupation (p < 0.001; p = 0.034; p = 0.001; p = 0.001), and the factor influencing expectations was the residence address according to ID card (KTP) (p = 0.043). A correlation was found between the dimensions of perceptions, expectations, and public confidence.Conclusion: Most participants held a positive perception, had high expectations, and shown high confidence in the pharmacist's position, despite the existence of a disparity between expectations and the actual provision of pharmacy services. The elements of perception, expectations, and confidence are interrelated.

Enhancing quantitative capacity for the health sector in post-Ebola Liberia, a tracer study of a locally developed and owned coding and biostatistics program

Background Despite the demonstrated value of quantitative research in understanding and responding to public health events, analytics capability is not always prioritized or available in settings that would greatly benefit from it. In Liberia, there are no university degree-granting programs in biostatistics or mathematical modeling, promoting dependence on external technical assistance. To address the gap, a local NGO, Quantitative-Data for Decision-Making (Q4D), was founded to enhance capacity and opportunities for analyzing quantitative data among Liberians. Methods To understand the relevance, utility, and impact of the skills being taught at Q4D, a tracer study was undertaken with current and former students. Participants completed an online survey that evaluated how often and in what ways they are applying course skills, as well as any personal or professional advancement they have attributed to their learning of coding and/or biostatistics through the program. Results Among 43 participants, 81% reported a high level of confidence in independently applying skills learned through Q4D classes in their jobs and/or academic programs. Most participants (81%) responded that they were actively demonstrating the skills they acquired; 74% were teaching the skills to others. Among the 83% of employed participants who reported using the skills currently in their jobs, 56% rated the skills they learned as very or extremely useful in their current positions. Several students attributed salary increments, consultancy opportunities, and scholarships to the skills gained through the program. Conclusions Program skills are being applied by students employed in health-related sectors, suggesting that the training content is relevant and useful for addressing some of the workforce’s analysis needs. Moreover, skills built through the program have positively impacted students by preparing them with the skills required for additional employment and training opportunities to advance in-country health research capacity and reduce inequities.

Exploration of network facilitator experiences implementing payer-partner programs within a nationwide clinically integrated network

BackgroundThe Community Pharmacy Enhanced Services Network (CPESN) is a clinically integrated network (CIN) of approximately 3500 community-based pharmacies in 48 local networks across the United States. CPESN USA promotes expansion of innovative programs within community-based pharmacies including value-based contracting for patient care services. As opportunities grow, it is important to define strategies and tools needed to implement payer-partner programs. ObjectiveThis study aimed to explore strategies and resources used when implementing payer-partner programs within a CIN. MethodsThis cross-sectional electronic survey was e-mailed to 48 managing network facilitators (MNFs) representing 48 local CPESN networks across the United States. An electronic survey was e-mailed to the MNF of each local CPESN network. Fourteen questions collected the MNFs experience with (1) opportunities at the local network, (2) resources found helpful for implementing payer-partner programs, (3) barriers to implementing payer-partner programs, (4) confidence with tasks related to payer-partner program implementation, and (5) reporting what types of teammates they work with or manage when implementing a payer-partner program. The survey was open for data collection for 65 days. Data were analyzed using descriptive statistics. ResultsA total of 42 completed surveys were returned (response rate, 87.5%). MNFs ranked the barriers most frequently experienced as buy-in effect (n = 16, 41.0%) and management of pharmacy/network follow-through (n = 11, 28.2%). MNFs reported helpful resources for program implementation as peer-to-peer guidance (n = 31, 79.5%) and program handouts/guides (n = 30, 76.9%). MNFs reported additional resources needed as subject matter experts (n = 23, 59.0%) and templated communications (n = 22, 56.4%). MNFs expressed their highest levels of confidence in tasks related to leadership management (n = 30, 76.9%) and implementing programs (n = 28, 71.8%). ConclusionBarriers to payer-partner program implementation within the CIN were buy-in effect, management of pharmacy/network follow-through, management of peers, and management of pharmacy/network implementation. Leaders within the CIN reported desires for a toolkit that iterates successful strategies and education on building community and accountability within local networks. Development of tailored support and resources can enhance the capacity of network leaders to scale payer-partner programs within community-based pharmacies.

Spatial identification of public spaces’ functions: a case study of Bach Dang Wharf Park in Ho Chi Minh City, Vietnam

Abstract Urban public spaces serve various functions and roles, such as physical, symbolic, ecological, economic, political, social, psychological, and aesthetic. Each function has specific design requirements and holds different meanings for space users. This study aims to identify the location of various functions within Bach Dang Wharf Park, one of the famous central riverside parks of Ho Chi Minh City, Vietnam, and test hypotheses about the concentration of hotspots for each function. To achieve these, we combined participatory GIS methods and face-to-face interviews using quantitative questionnaires and then used SPSS software to examine the relationship between park users’ identification of functions and other factors. We conducted two surveys, each lasting one week, in June 2022 and April 2023, with a total of 223 respondents and 1,413 marked points for park functions. The results showed that how people perceive park functions significantly relates to the characteristics of their park visitation rather than personal information. The hotspots of physical, symbolic, ecological, economic, and political functions appeared with high confidence levels and differed in size and location between the survey times. Meanwhile, in the 2022 survey, hotspots of social function appeared at the old pier near the high-speed boat station and opposite Nguyen Hue walking street. Later in 2023, these areas were mostly concentrated by markers of psychological function. At the same time, hotspots of aesthetic function were recorded in the space in front of the ASEAN flagpole. This approach effectively promotes community involvement in urban planning by better understanding citizens’ needs for public space.

Fingerprinting of emerging contaminants in L'Albufera natural park (Valencia, Spain): Implications for wetland ecosystem health

Wetlands are crucial ecosystems that are increasingly threatened by anthropogenic activities. L'Albufera Natural Park, the second-largest coastal wetland in Spain, faces significant pressures from surrounding agricultural lands, industrial activities, human settlements, and associated infrastructures, including treated wastewater inputs. This study aimed at (i) establishing pathways of emerging pollutants entering the natural wetland using both target and non-target screening (NTS) for management purposes, (ii) distinguishing specific contamination hotspots through Geographic Information System (GIS) and (iii) performing basic ecological risk assessment to evaluate ecosystem health. Two sampling campaigns were conducted in the spring and summer of 2019, coinciding with the start and end of the rice cultivation season, the region's primary agricultural activity. Each campaign involved the collection of 51 samples. High-resolution mass spectrometry (HRMS) was employed, using a simultaneous NTS approach with optimized gradients for pesticides and moderately polar compounds, along with complementary NTS methods for polar compounds, to identify additional contaminants of emerging concern (CECs). Quantitative analysis revealed that fungicides comprised a substantial portion of detected CECs, constituting approximately 50% of the total quantified pesticides. Tebuconazole emerged as the predominant fungicide, with the highest mean concentration (>16.9 μg L−1), followed by azoxystrobin and tricyclazole. NTS tentatively identified 16 pesticides, 43 pharmaceuticals and personal care products (PPCPs), 24 industrial compounds, and 12 other CECs with high confidence levels. Spatial distribution analysis demonstrated significant contamination predominantly in the southwestern region of the park, gradually diminishing towards the north-eastern outlet. The composition of contaminants varied between water and sediment samples, with pharmaceuticals predominating in water and industrial compounds in sediments. Risk assessment, evaluated through risk quotient calculations based on parent compound concentrations, revealed a decreasing trend towards the outlet, suggesting wetland degradation capacity. However, significant risk levels persist throughout much of the Natural Park, highlighting the urgent need for mitigation measures to safeguard the integrity of this vital ecosystem.

Relationship between Data Privacy Regulations and Consumer Trust in E-Commerce Platforms in Vietnam

Purpose: The aim of the study was to assess the relationship between data privacy regulations and consumer trust in e-commerce platforms in Vietnam. Materials and Methods: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that stringent data privacy regulations positively influence consumer trust in e-commerce platforms. When consumers perceive that their data is adequately protected, they are more likely to trust the platform, resulting in higher confidence levels and increased willingness to engage in online transactions. Moreover, compliance with these regulations can differentiate e-commerce platforms in competitive markets, as consumers tend to prefer platforms that prioritize data privacy and security. This relationship underscores the pivotal role of regulatory frameworks in shaping consumer perceptions and behaviors in the digital marketplace, emphasizing the importance of maintaining robust data protection standards to foster trust and sustainable business relationships. Implications to Theory, Practice and Policy: Trust theory, regulation theory and technology acceptance model may be used to anchor future studies on assessing the relationship between data privacy regulations and consumer trust in e-commerce platforms in Vietnam. E-commerce platforms should prioritize enhancing data transparency and accountability to build consumer trust. Policymakers should work towards harmonizing international data privacy standards to create a cohesive regulatory environment.

Technical note: assessing GPS sensor accuracy using real-time kinematic device for livestock tracking.

The technical aspects of global positioning system (GPS) sensors have been improved substantially over the years, making them valuable and popular tools for livestock tracking. Using GPS sensors allows producers and researchers to locate grazing livestock, monitor their behavior and distribution, and gather referencing information about the health status of the animals and pastures. However, interpreting the behavior of grazing livestock, such as cattle, from GPS data can be difficult due to positioning inaccuracies. Without knowing the positioning accuracy range of GPS sensors, achieving high-level confidence in determining grazing densities and identifying abnormal livestock movement patterns is challenging. In this study, the positioning accuracy of 3 different types of commercial GPS sensors was assessed using a survey-grade real-time kinematics (RTK) device. We outlined the procedures and essential equations and compared the recorded locations from the GPS sensors with reference locations collected from the RTK device. The results demonstrated statistically significant differences (P < 0.05) in positioning accuracy between different types of GPS sensors. The circular error probable (CEP) at 95% probability levels (CEP95) of the 3 sensors ranged from 2.46 to 11.06 m. This accuracy varied among individual sensors within the same brand and across different brands, which underscores the importance of evaluating the positioning accuracy of GPS sensors in livestock tracking. This study provides significant insights for animal scientists, ecologists, and livestock producers engaged in GPS sensor-related research and practices.

Modeling and design optimization of the performance of stone matrix asphalt mixtures containing low-density polyethylene and waste engine oil using the response surface methodology

In recent years, the use of waste plastic materials such as low-density polyethylene (LDPE) to modify asphalt binders and enhance mixture performance has garnered significant attention. One major concern with using such materials is the higher production temperature required, which necessitates the use of a bitumen extender agent, such as waste engine oil (WEO), to reduce the viscosity and mixing temperature. Therefore, using these stabilizing additives can reduce the consumption of virgin binder, especially for Stone Matrix Asphalt (SMA) mixtures, which require higher asphalt content. This study aimed to optimize the design of SMA modified by LDPE and WEO to minimize the optimum asphalt content (OAC) and mixing temperature while maximizing SMA performance. To achieve this, Response Surface Methodology (RSM) was utilized to develop the necessary models for optimizing design and predicting performance. The selected independent variables (factors) for the design include LDPE content, WEO content, OAC, and mixing temperature. Meanwhile, the responses (dependent variables) consist of Marshall stability, rut depth, tensile strength ratio, and resilient modulus, which were used to determine the best mix design. The findings demonstrated that the suggested models for the output variables can predict performance with a higher level of confidence. The Analysis of variance (ANOVA) demonstrated that predictive models were significant and well-fitted, with a coefficient of determination (R2) of higher than 0.80, an adequate precision value of greater than 4, and a low p-value (less than 0.05). The error percentage between the RSM-predicted and actual values was less than 5 %, indicating that RSM-established models can accurately and efficiently predict the SMA performance. The best mix design of the SMA mixture modified by LDPE and WEO was found to be 10 % LDPE, 3.91 % WEO, 5.92 % OAC, and mixing temperature of 152.24°C with a combined desirability of 82.8 %.

A refined empirical model of steady-state downburst based on high-resolution wind speed data obtained from wind tunnel tests

A slice of research pertinent to the analytical or empirical models of downburst winds was available, but the current validation was usually based on sampled wind velocities at several typical positions in the experimental measurements rather than the whole-flow domain information. Therefore, the capability of existing analytical or empirical models to reproduce the whole development of downbursts at different stages remains questionable. This paper aims to refine the empirical model of downbursts based on high-resolution wind speed data obtained from wind tunnel tests, which renders the well-established empirical model to simulate the maximum wind speed of the vortex ring and to obtain the more accurate wind profiles in the outflow regime. To overcome the bottleneck problem that lay in the lack of experimental results for whole-flow domain information, a comprehensive experimental study based on the impinging jet simulator was conducted and the spatial variations of downburst winds were systematically measured. Then, the empirical model considering the nonlinear growth of boundary layer thickness is refined according to the experimental results, so that two new empirical functions, which could rationally represent the spatial variation of horizontal wind velocities in the whole-flow domain, have been proposed. The refined empirical model can be used to facilitate the safety analysis of structures and buildings under downburst winds with a higher confidence level.

Model based on Machine Learning for the classification of banking transactions carried out through PSE

The financial sector, and specifically banking entities, have experienced changes in recent years thanks to technology, such as the digitization of transactions and the creation of applications such as digital wallets and PFM (Personal Finance Manager), generating gigabytes of information. Managing knowledge becomes essential to face new competitors, provide better services, understand the financial behavior of clients and face great challenges when processing and analyzing the volume of information available, which in most cases requires a complex preprocessing process and data quality. This is the case of banking transactions, which include free text information in their observation fields, making analysis and classification difficult, preventing the bank and its clients from analyzing financial behavior over a period of time. To solve this problem, the use of Machine Learning techniques was proposed to automate the transaction classification process based on text written in natural language, and provide the information that allows an analysis of the financial behavior and personal expenses of each user. Once the training, evaluation and comparison of different models was completed, using the CRISP-DM methodology as a development framework, an optimized solution was reached that solves the classification problem using the KNN algorithm, with an accuracy close to 96%. The results showed a high level of confidence when classifying a transaction, based on a description, into a category.

Did we achieve what we aimed for? Assessing the outcomes of a human–carnivore conflict mitigation and coexistence project in Europe

Monitoring and evaluation practices, demanded by nature conservation project donors, often focus on practical outputs, leaving the assessment of intended short and medium‐term outcomes and long‐term impacts challenging. This study employs a merger of the conflict intervention triangle model (CITM) and its three dimensions relationship, substance, and process, together with the logical framework approach (LFA) within the context of a human–wildlife conflict and coexistence (HWCC) project (LIFE EuroLargeCarnivores) in order to assess project correlated outcomes on stakeholder level over time.Two stakeholder surveys were conducted across 14 project partner countries, capturing baseline perceptions in 2018 and assessing changes in 2021. To assess the actual influence of the project with its focus on conflict mitigation, we applied an ex post counterfactual analysis. Results indicate positive developments in all dimensions of the CITM. The influence of the project is demonstrated by statistically significant differences in response behavior between participants and non‐participants of project interventions. The overall outcome regarding beliefs in satisfactory future management of increasing large carnivore populations, is more intricate. Significant differences are observed among three selected main stakeholder categories over the project's timeframe. While nature conservationists maintain high confidence levels, confidence of hunters and livestock raisers declined. However, results for participants of project interventions depict a significantly lower decline in confidence compared to non‐participants. Based on our findings, we provide insights how to efficiently evaluate outcomes of HWCC projects, offering recommendations for wildlife conservation practitioners. We conclude that HWCC projects are important also and especially in times of unfavorable frame conditions. Rigorous evaluation methods are essential to ensure efficient use of resources in order to maximize the outcomes of HWCC projects. The study highlights the need for long‐term evaluation to assess broader impacts at country, regional, and sector levels.

Advance personal planning knowledge, attitudes, and participation amongst community-dwelling older people living in regional New South Wales, Australia: A cross-sectional survey.

Advance personal planning (APP) involves planning for future periods of incapacity, including making legal decisions and documents. APP ensures that a person's values and preferences are known and respected. This study aimed to examine knowledge of APP, attitudes and confidence towards APP, and participation in APP activities among older people residing in regional and rural areas. A cross-sectional survey was conducted with people aged over 65 years residing in and around regional towns in New South Wales, Australia. Participants responded to a social media advertisement or information provided through a community organisation. Data was collected via pen and paper survey or an online survey. The survey was developed for the study and included questions about the participant and their experiences with APP. Poisson regression modelling was conducted to explore the relationship between APP participation and APP knowledge, confidence and attitudes as well as the participant characteristics associated with APP participation. Overall, 216 people completed the survey. Most participants had a will (90%) but only a third (32%) had documented an advance care directive. Knowledge of APP was low with only 2.8% of participants correctly answering all 6 knowledge questions. Participants had a positive attitude towards APP and high level of confidence that they could discuss APP issues with important people in their life. Those with increased knowledge, confidence and attitude towards APP were significantly more likely to participate in APP activities. Older age and having private health insurance were significantly associated with engaging in APP activities. Increased frailty and the presence of health conditions were not associated with increased APP participation. There is a need to increase engagement with APP particularly among those who may be considered frail or have chronic health conditions. Increasing knowledge of, confidence and attitudes towards, APP could help to increase engagement in APP activities.