Training Evaluations Research Articles

Evaluation of pilot-scale drinking water treatment trains using a panel of bioassays

ABSTRACT Chemical water quality monitoring is increasingly complemented with bioassays. In this study, the performance of drinking water treatment technologies was evaluated with bioassays. CALUX reporter gene bioassays and the Ames fluctuation bioassay for mutagenicity were used to analyze the responses of raw feed water with and without a spiking mixture of organic contaminants in five different pilot-scale water treatment trains applying advanced oxidation processes, reverse osmosis and filtration with (biological) activated carbon for the preparation of drinking water. In general, CALUX responses in the spiked feed water were in the same range as in the unspiked feed water, indicating that spiking did not significantly elevate the activity measured in the feed water. This observation was in line with a calculation of the combined additive behavior of the spiking mixture using bioactivities of the spiked chemicals in analog bioassays from ToxCast. This calculation gave no indication of a measurable response in the bioassays to be expected by the spiking, except for oxidative stress. Responses in the Ames fluctuation assay in most feed water were in some cases increased by AOP and mostly removed by active concentrations. The bioassay responses demonstrate the removal of emerging chemicals with different mechanisms of action by different water treatment technologies.

Sensory Characteristics and Volatile Organic Compound Profile of Wild Edible Mushrooms from Patagonia, Argentina

The Andean–Patagonian forests of South America offer a great variety of wild edible mushrooms, many with ancestral use and others linked to new mycogastronomic offers. However, their sensory properties and detailed characterizations have not yet been deeply explored and described, nor have their alterations due to cold storage. The aims of this work were to perform a sensory characterization through a trained panel evaluation, perform target volatile compounds analysis and evaluate post-harvest preservation methods effects on nine species of wild edible mushrooms with different trophic habits (Cortinarius magellanicus, Panus dusenii, Fistulina antarctica, F. endoxantha, Gloeosoma vitellinum, Grifola gargal, Lepista nuda, Ramaria patagonica, and Cyttaria hariotii). The sensory description of dehydrated specimens through quantitative descriptive analysis showed that panelists were a significant source of variation; F. antarctica and R. patagonica registered distinct sweet flavor/spice odor and wood/sweet flavor, respectively, and different textures. Refrigeration produced a rapid loss of sensory characteristics, whereas freezer conservation satisfactorily maintained the characteristics in F. anctartica, R. patagonica, G. vitellinum, and C. hariotti for at least four months. A total of 60 target volatile organic compounds were detected, corresponding to grass, mushroom, alkane, and pungent odors in F. anctartica, R. patagonica, and G. vitellinum. The detailed sensory characterization and post-harvest conservation options of these novel products constitute crucial information to promote their sustainable use and local development through innovative activities linked to tourism, such as mushroom gastronomy and mycotourism.

Evaluating suicide prevention gatekeeper training designed to identify and support people from asylum-seeking and refugee backgrounds

BackgroundSuicide-related behaviours and individual risk factors for suicide differ between ethnicities and demonstrate additional variation based on voluntary and forced migration. People forcibly displaced by violence and conflict, such as those seeking asylum and refugees, are likely to face stressors that can increase suicide risk. Research into evidenced-based suicide prevention strategies among people from asylum-seeking and refugee backgrounds is scarce. However, early, contextually-appropriate, identification and intervention may be a promising way to facilitate support for people in these groups. This research proposes that a contextually-responsive gatekeeper training is an appropriate strategy to increase the identification and support for people from asylum-seeking and refugee backgrounds.MethodsThe present article relates to the statistical findings of a larger mixed-method study used to validate and refine a contextually-responsive gatekeeper training program. The qualitative results of this research will be published separately. The outcome measures – knowledge about suicide in multicultural contexts, attitudes towards suicide and prevention, and self-efficacy to intervene were measured quantitatively, adopting a similar pre- and post-training procedure used in previous training evaluations. Using Generalised Estimating Equations, statistical comparisons were made between three identical self-report surveys completed by participants across three consecutive time points – pre-training, immediately post-training, and three months following training completion – known in this investigation as time-point zero (T0), time-point one (T1), and time-point two (T2). Lastly, during the T2 follow-up, additional open-ended questions were included to understand which areas of training they feel prepared them effectively and how the program could have better prepared them to intervene.ResultsA total of 28 participants took part in the study. Quantitative analysis indicated the program’s capacity to exert a significant favourable and lasting influence on knowledge about suicide and self-efficacy to intervene. In addition, follow-up measurements suggest that the content delivered to participants transferred effectively into real-world suicide prevention behaviours.ConclusionsFindings suggest that tailored suicide prevention training can have a significant influence on knowledge about suicide in multicultural contexts, self-efficacy to intervene in a crisis, and that course content translates effectively into real-world suicide prevention behaviour. Modifying training practices, based on feedback from contextually-experienced attendees, appears to be a pivotal factor in promoting the support of people from asylum-seeking and refugee backgrounds.

Feature Selection as Deep Sequential Generative Learning

Feature selection aims to identify the most pattern-discriminative feature subset. In prior literature, filter (e.g., backward elimination) and embedded (e.g., LASSO) methods have hyperparameters (e.g., top- k , score thresholding) and tie to specific models, thus, hard to generalize; wrapper methods search a feature subset in a huge discrete space and is computationally costly. To transform the way of feature selection, we regard a selected feature subset as a selection decision token sequence and reformulate feature selection as a deep sequential generative learning task that distills feature knowledge and generates decision sequences. Our method includes three steps: (1) We develop a deep variational transformer model over a joint of sequential reconstruction, variational, and performance evaluator losses. Our model can distill feature selection knowledge and learn a continuous embedding space to map feature selection decision sequences into embedding vectors associated with utility scores. (2) We leverage the trained feature subset utility evaluator as a gradient provider to guide the identification of the optimal feature subset embedding; (3) We decode the optimal feature subset embedding to autoregressively generate the best feature selection decision sequence with autostop. Extensive experimental results show this generative perspective is effective and generic, without large discrete search space and expert-specific hyperparameters. The code is available at http://tinyurl.com/FSDSGL .

Training an infectious disease unit in palliative care during and post COVID-19: a qualitative longitudinal study.

To understand palliative care needs and their changes perceived by health professionals (HPs) of the Infectious Diseases Unit who participated in palliative care (PC) intensive training during the pandemic and behind/during the pandemic and one year after the outbreak. A longitudinal qualitative study. Thematic analysis and meaning shift were two months after training to one year. This specific thematic approach enabled the researchers to fully understand the experiences of the HPs after they participated in the intensive PC training program during the pandemic. Participant validation meeting with the ward's staff one year after the end of the course was performed. The two last validation meetings were used as a triangulation source to plan the new education projects. From March 9 to 28, 2020, the Palliative Care Services (PCS) developed intensive experiential training. Thirty-one HPs of the Infectious Diseases Unit (physicians and nurses) who were facing the COVID-19 emergency participated in the training. We conducted eight semi-structured interviews with HPs who participated in intensive training during the first wave of the pandemic (T0), two months (T1) after training and after one year (T2), during the second wave. Two validation meetings were performed as suggested by the best practices in medical education. Twenty-two infectious disease staff members participated, 8 physicians and 14 nurses. Our data show a meaning shift on five overarching themes (defined within the sub-themes): (1) Recognizing patients' palliative care needs; (2) Responses to palliative care needs; (3) Increasing attention to intervention and care choices; (4) The suffering of health professionals; (5) Training evaluations and future expectations. At the end of Pandemic period, new training needs and acquisition have emerged. Palliative care needs changed over time: the COVID-19 themes are now far from their perception, and somehow the skills acquired during the intensive training are less present. The pandemic led to a rapid acquisition of competencies and changes in the professionals' behaviors, maintenance of professionals' knowledge and competencies at two months and one year. COVID has improved relationships and increased interactions with the infectious world but that it has not been enough. The integration between PC and Infectious world needs models of integration to implement.

Developing Models for Measuring and Evaluating Success in Vocational and Professional Education and Training. An Empirical Study

This study aimed to evaluate the performance of vocational high schools by developing and applying a comprehensive assessment instrument. The focus was on the actual processes occurring within these institutions, rather than solely relying on document-based evaluations. By analyzing factors affecting school performance, constructing a valid instrument, and conducting a thorough evaluation, the study found that the investigated vocational high schools demonstrated satisfactory performance in general management and academic management. Most of the evaluations of education, training and performance carried out in vocational high schools focus on documents or passive data, rather than on the processes taking place in the secondary schools themselves. Recognizing the need to study precisely these processes, this study focuses on the performance evaluation of secondary schools. The study begins with the identification of constructs and the development of instruments to assess the performance of vocational high schools. Based on the problems found in the field, before conducting the evaluation, the researcher must first develop the evaluation tool through three stages of development. The first one is to analyze the concepts related to evaluation by examining the factors affecting the performance of vocational high schools. In the second, instrument development and instrument analysis (content validation of selected criteria) are conducted with the help of experts. The third one, entailed a rigorous evaluation of the effectiveness of vocational secondary schools. Based on the evaluation findings, the investigated vocational high schools demonstrated commendable performance in both general management and academic management.

USING PREDICTIVE ANALYTICS TO IMPROVE SURVEILLANCE OF HEAT-RELATED ILLNESS DURING MILITARY TRAINING

Background: Heat-related illnesses are a critical concern for military personnel, especially those unfamiliar with hot climate regions. The Royal Thai Army (RTA) implements a 10-week military training program encompassing four phases: (1) Heat acclimatization training, (2) Combat fundamentals and unarmed combat training, (3) Armed combat training and tactical training, and (4) Field training exercise and evaluations. Objective: This study aimed to conduct a predictive analysis of heat-related illnesses to enhance prevention programs. Methods: The study utilized secondary data from the RTA Medical Department, incorporating variables such as age, occupation, education, underlying diseases, smoking and alcohol consumption, sleep duration, exercise, medication history, body mass index (BMI), weight loss, body temperature, dark urine, heat rash, and environmental humidity. Multiple machine learning algorithms were employed to develop predictive models. Results: The samples comprised 809 male recruits (103,051 encounters) with an average age of 22. Approximately 12% of the recruits had a BMI ≥30 kg/m2, while nearly 70% and 90% reported tobacco use and alcohol consumption in the past 12 months, respectively. Among the recruits, 16% reported substance use within the preceding 30 days. The eXtreme Gradient Boosting (XGB) model achieved 91% accuracy in predicting heat-related illnesses before Phase 2. The top five predictive variables were Lopburi Province (central region), Songkhla Province (southern region), and Bangkok (capital city), sleep duration before joining military training (hours), and age (years). Conclusion: This study, which applied machine learning techniques to predict heat-related illnesses among Thai recruits, can potentially impact the health and training of military personnel. The comparative analysis of various algorithms identified the XGB model as the optimal performer in predicting heat-related illnesses during the combat fundamentals and unarmed combat training phase. However, it is essential to note that further study is needed to enhance the applicability of our predictive model, which includes expanding its use to new cohorts of Thai conscripts, underscoring our research’s ongoing nature.

Brief psychological intervention for suicide prevention based on problem-solving applied in different formats to people over 50 years old: protocol for a randomized controlled trial

BackgroundSuicide is a major public health problem, especially among individuals over 50 years old. Despite the suitability of this life stage for prevention, research on the efficacy of psychological interventions is scarce and methodologically limited, affecting their clinical utility and efficacy. Brief, flexible interventions that can be applied both in-person and remotely are needed. This study aims to evaluate the efficacy of a brief problem-solving-based suicide prevention program applied through various modalities to individuals over 50 years old.MethodsA randomized controlled trial will be conducted. A sample of 212 adults aged 50 or older with suicidal ideation will be randomly assigned to a problem-solving-based psychological intervention administered face-to-face (PSPI-P; n = 53), by telephone multiconference (PSPI-M; n = 53), via a smartphone app (PSPI-A; n = 53), or to a usual care control group (UCCG; n = 53). The intervention will be delivered in 7 sessions or modules of 90 min each. Blind trained evaluators will conduct assessments at pre-intervention, post-intervention, and follow-ups at 3, 6, and 12 months. The primary outcome will be suicidal ideation evaluated using the Suicidal Ideation Scale (SSI) and the Columbia Suicide Severity Rating Scale (C-SSRS). Secondary outcomes will include hopelessness, anxiety and depression symptoms, reasons for living, impulsivity, problem-solving skills, social support, anger syndrome, gratitude, personality, dropouts, treatment adherence, and satisfaction with the intervention.DiscussionThis study will provide evidence of the efficacy of a brief problem-solving-based intervention for suicide prevention in individuals over 50 years old, administered face-to-face, by telephone multiconference, and via a smartphone app. If results are favorable, it will indicate that an effective, accessible, clinically and socially useful suicide prevention intervention has been developed for affected individuals, families, and communities.Trial registrationClinicalTrials.gov NCT06338904. Registered April 1, 2024.

THE EFFECTIVENESS OF SCHOOL PRINCIPAL LEADERSHIP IN ENHANCING TEACHER PROFESSIONAL COMPETENCE AT SMK MIFTAHUL ULUM TUMPENG WONOSARI, BONDOWOSO

Effective leadership of school principals is considered a crucial factor in creating a supportive learning environment. This study aims to investigate the effectiveness of the principal's leadership in enhancing teachers' professional skills at SMK Miftahul Ulum Tumpeng Wonosari, Bondowoso. The method used is a qualitative descriptive approach, utilizing data collection techniques through observation, interviews, and documentation. The researcher observed the effectiveness of the principal's leadership by taking notes and recordings. Additionally, the researcher conducted interviews with the principal, teachers, and administrative staff at SMK Miftahul Ulum. Once the data was collected, the researcher performed data reduction, classification, validation, and coding based on the data types, followed by interpretation. The results showed that there were three aspects observed in the principal's leadership at SMK Miftahul Ulum, namely strategies to improve teachers' professional competence, challenges faced in this process, and the impact of the principal's leadership on enhancing teachers' professional competence. The strategies to enhance teachers' competence include training programs, workshops, performance assessments, and evaluations. Meanwhile, the challenges faced include global competition and changes in the educational curriculum. The positive impact of the principal's leadership is evident in the improvement of teachers' teaching quality, the creation of a conducive work environment, and the enhancement of students' academic achievements. Thus, this study concludes that the principal's leadership at SMK Miftahul Ulum Tumpeng has proven effective in improving teachers' professional competence. These findings provide practical implications for other educational institutions in efforts to improve education quality by focusing on teacher competence development. The suggested recommendations include increasing policy support, allocating adequate resources, and enhancing the frequency and quality of professional development programs.

Enhancing references evapotranspiration forecasting with teleconnection indices and advanced machine learning techniques

After precipitation, reference evapotranspiration (ETO) plays a crucial role in the hydrological cycle as it quantifies water loss. ETO significantly impacts the water balance and holds great importance at the basin level because of the spatial distribution of managing water resources. Large scale teleconnection indices (LSTIs) play a vital role by influencing climatic variables and can be pivotal in determining ETO and its predictive variables. This study aimed to model and forecast annual ETO in Iran’s basins by utilizing LSTIs and employing various machine learning models (MLMs) such as least squares support vector machine, generalized regression neural network, multi-linear regression (MLR), and multi-layer perceptron (MLP). Initially, climate data from 122 synoptic stations covering six and 30, main and sub basins were collected, and annual ETO values were computed using the Food and Agriculture Organization 56 (PMF 56) Penman–Monteith equation. The correlations between these values and 37 LSTIs were examined within lead times ranging from 7 to 12 months. Through a stepwise approach, the most influential predictor indices (LSTIs) were selected as input datasets for the MLMs. The findings revealed the significant influence of factors such as carbon dioxide (CO2), Atlantic multidecadal oscillation, Atlantic Meridional Mode, and East Atlantic on annual ETO. Overall, all MLMs performed well in terms of the Scatter Index during both training and testing phases across all sub-basins. Furthermore, the MLP and MLR models displayed superior performance compared to other models in the training and testing evaluations based on various assessment metrics.

Adaptive stepsize forward–backward pursuit and acoustic emission-based health state assessment of high-speed train bearings

Compressed sensing (CS) is a promising tool for data compression reconstruction. However, fault diagnosis methods for high-speed train bearings based on CS and acoustic emission (AE) technologies have not been reported yet. Notably, the accuracy and speed of CS two-stage reconstruction methods are affected and restricted by prior initial conditions. Therefore, this article proposes adaptive dynamic thresholds applicable to adaptive stepsize forward–backward pursuit (ASFBP), and bearing health state assessment method. First, the adaptive dynamic thresholds for atom selection and deletion are constructed based on the residual feedback mechanism and the atom quality distribution law, which enables ASFBP to realize high-precision rapid reconstruction of signal without any atom priori initial conditions. Second, the initial dictionary length is improved based on the AE hit characteristics. Furthermore, a damage state comprehensive evaluation index (DSCEI) is established using principal component analysis based on AE time-domain hit parameters and compression-domain energy parameter. Compared with the kurtosis index and permutation entropy index, the DSCEI demonstrates better monotonicity and stability in the quantitative evaluation of high-speed train bearing condition. Finally, the validity and stability of the method are verified by testing under complex test conditions resembling actual high-speed train lines, providing valuable insights for the CS-based data-driven bearing fault diagnosis.

The Development and Execution of An Orthopaedic Sports Medicine Fellowship Surgical Skills Assessment

Background: Assessment of orthopaedic surgery trainees is traditionally based on subjective evaluation by faculty. The recent push for value-based health care has placed a premium on improving patient outcomes. As a result, surgical training evaluations for orthopaedic trainees are evolving to include more objective measures to evaluate competency. Purpose: To develop and subsequently demonstrate the efficacy of a novel surgical skills assessment for orthopaedic sports medicine fellows. Study Design: Case series; Level of evidence, 4. Methods: A team of 14 fellowship-trained orthopaedic sports medicine surgeons developed objective scoring rubrics for anterior cruciate ligament reconstruction (ACLR) and rotator cuff repair (RCR) using a modified Delphi process. Rubrics were designed based on 10 surgical steps with a grading scale (1-5) based on core competencies with a maximum summative score of 50. Fourteen orthopaedic fellows across a regionally diverse group of sports medicine–accredited fellowship programs were invited to complete both an ACLR and RCR in a surgical skills laboratory at the beginning and end of their fellowship year. Individual surgical steps, overall performance, and total procedure time were evaluated by a single sports medicine surgeon for both sessions. Results: Thirteen of 14 fellows completed both pre- and post-fellowship assessments. For the ACLR procedure, the pre-fellowship mean summative score was 25.4 (SD, 4.4) and the post-fellowship mean summative score was 38.6 (SD, 4.1), which was a statistically significant improvement (P < .001). For the RCR procedure, the pre-fellowship mean summative score was 26.6 (SD, 5.4) and the post-fellowship mean summative score was 38.8 (SD, 4.3), which was also a statistically significant improvement (P < .001). The mean time to completion for the ACLR procedure was 82.3 minutes (SD, 4.3 minutes) pre-fellowship, which improved to 69.7 minutes (SD, 11.6 minutes) post-fellowship (P = .002). The mean time to completion for the RCR procedure was 85.5 minutes (SD, 5.0 minutes) pre-fellowship, which improved to 76.4 minutes (SD, 7.0 minutes) post-fellowship (P < .001). Conclusion: This surgical skills program represents the first standardized and reproducible instrument for the evaluation of 2 arthroscopic sports medicine procedures in the United States. Orthopaedic sports medicine fellows improved significantly in aggregate over their fellowship year with regard to the ACLR and RCR. The described program has the potential to serve as both a training tool and formal orthopaedic sports medicine fellow assessment.

What is the Status of the Scientific Association of Midwifery in Iran based on the Criteria of the International Confederation of Midwives?

Introduction: Scientific midwifery associations can play a leading role in improving maternal health policies and practices. This study aimed to evaluate the Iran Scientific Association of Midwifery (ISAM) using a translated valid version of the Member Association Capacity Assessment tool (MACAT) and also to explain the needs and propose the related strategies and actions to improve ISAM capacities. Methods: This was a mixed sequential (Quantitative-Qualitative) explanatory research in 2022. The study was performed in three phases based on the study's objectives. In the first phase, the MACAT of the International Confederation of Midwives (ICM) was translated into Persian. Then, the validity of MACAT was assessed by 10 experts. After the validity approval of the Persian version of the MACAT, in the second phase, which was a descriptive study, the capacity of ISAM was assessed by two trained evaluators using MACAT. In the third phase of the study, with a qualitative research and using a focused group discussion and six in-depth individual interviews with 14 key informants, the demonstrated challenges in the first phase of the study and the related suggestions for the problem solutions were discussed. The data from the qualitative phase of the study were analyzed using directed Qualitative content analysis. Lincoln and Guba’s criteria were used to confirm the trustworthiness of the data. Then the needs were explained, and the strategies and actions were suggested to improve ISAM capacities in the seven dimensions of MACAT, including governance, management, financial resources, functions, communication, collaboration, and visibility. Results: In the first phase of the study, the MACAT was translated into Persian, and its validity assessment showed S-CVI= 0.91 and I-CVI= 0.89. CVR scores of all items were also above 0.62 and so acceptable. In the second phase of the study, the document review and the observations showed 88 out of 96 items scored 1 (91 percent) while 8 items scored zero. In the third phase of the study, 83 codes in the 6 dimensions were categorized from directed content analysis. Then, 53 actions were proposed for seven main strategies for improving the governance, enhancing the management practices and leadership methods, increasing functions, increasing collaboration, partnership, and networks, and expanding visibility and increasing sustainability to improve ISAM capabilities. Conclusion: The Scientific Midwifery Association obtained 91 percent of the scores. The most important challenges of the ISAM were (1) low advocacy, (2) a shortage of human and financial resources and sponsors, and (3) low contribution in policy and decision-making in midwifery affairs. The most necessary actions for the ISAM capacity improvement were suggested to be (1) considering more independence in a culturally and politically-based context governance, (2) paying attention to infrastructure improvement, and (3) defining the mechanisms in communication with the other midwifery-related sectors, other NGOs, and potential sponsors; (4) the ISAM involvement in making macro policies and midwifery affairs, and (5) using the ISAM capacity for participating in mega health projects for fundraising.

Quality Indicators of Colonoscopy: Are we meeting the standards in Nepal?

BACKGROUND Colonoscopy is an important tool for management of colorectal disorders. Performance of quality colonoscopy requires a trained endoscopist, adequate resources, preparation and evaluation parameters for good outcomes. We conducted this study to emphasize the importance of quality practice in colonoscopy in our country as there is lack of standardization. METHODS This is a retrospective observational study done at a referral center in Western Nepal. All the colonoscopies were done without sedation with two sachets of peglec powder 137.15 grams, each containing polyethylene glycol (118grams) dissolved in 2 liters of clean water each. Data of 1052 colonoscopies done during three years were retrieved from colonoscopy record section and analysed for important quality measures in use. Data entry and analysis was done in Microsoft Excel. RESULTS A total of 1052 colonoscopies were included in this study. Pain abdomen (70.6%) was the commonest indication for colonoscopy and majority were male patients (53.4%). Good bowel preparation was achieved by split dosing of commercially available polyethylene glycol. Cecal and ileal intubation was achieved in 98% and 96% colonoscopies respectively, meeting the current recommendations set by the gastroenterology societies. No major complications occurred during the procedure. CONCLUSION Important quality indicators could be achieved with colonoscopy done without sedation in resource limited settings also. Screening colonoscopy should be promoted for early detection and management of colorectal cancers in low-income countries like Nepal. Quality should be standardized and practiced in routine colonoscopy examination taking into consideration of patient comfort.

Assessing self-reported public health emergency competencies for civil aviation personnel in China: a pilot study

IntroductionCOVID-19 has demonstrated the importance of competent staff with expertise in public health emergency preparedness and response in the civil aviation system. The civil aviation system is a critical sentinel and checkpoint to prevent imported cases and slow the spread of communicable diseases. Understanding the current competencies of staff to deal with public health emergencies will help government agencies develop targeted training and evidence-based policies to improve their public health preparedness and response capabilities.MethodsThis cross-sectional pilot study was conducted from November 2022 to October 2023, involving 118 staff members from various positions within China’s civil aviation system. A 59-item questionnaire was translated and developed according to a competency profile. Data were collected using the self-report questionnaire to measure the workforce’s self-perceptions of knowledge and skills associated with public health emergency proficiency, categorized into (1) general competency, (2) preparedness competency, (3) response competency, and (4) recovery competency. KMO & Bartlett test and Cronbach’s α reliability analysis were used to test the reliability and validity of the questionnaire. Descriptive statistics, independent sample T-test, ANOVA, and linear regression models were performed to analyze the competencies.ResultsA total of 107 staff members from the aviation system were surveyed in this study. The KMO & Bartlett test, (KMO = 0.919, P < 0.001) and Cronbach’s α coefficients (α = 0.985) for this questionnaire were acceptable. The results suggested that respondents scored a mean of 6.48 out of 9 for the single question. However, the staff needed to acquire more knowledge in investigating epidemic information (5.92) and case managing (5.91) in the response stage. Overall, males scored higher (409.05 ± 81.39) than females (367.99 ± 84.97), with scores in the medical department (445.67 ± 72.01) higher than management (387.00 ± 70.87) and general department (362.32 ± 86.93). Additionally, those with completely subjective evaluation (425.79 ± 88.10) scored higher than the general group (374.39 ± 79.91). To predict the total score, female medical workers were more likely to have lower scores (β = -34.5, P = 0.041). Compared with those in the medical department, the management workers (β = -65.54, P = 0.008) and general workers (β = -78.06, P < 0.001) were associated with a lower total score.ConclusionsThere was still a gap between the public health emergency competencies of the civil aviation system and the demand. Staff in China’s civil aviation systems demonstrated overall competence in public health emergency preparedness and response. However, there was a need to enhance the accumulation of practical experience. Implementing effective training programs for public health emergencies was recommended to mitigate knowledge gaps. Meanwhile, regular training evaluations were also recommended to give comprehensive feedback on the value of the training programs.

Interpretation and explanation of computer vision classification of carambola (Averrhoa carambola L.) according to maturity stage

The classification of carambola, also known as starfruit, according to quality parameters is usually conducted by trained human evaluators through visual inspections. This is a costly and subjective method that can generate high variability in results. As an alternative, computer vision systems (CVS) combined with deep learning (DCVS) techniques have been introduced in the industry as a powerful and an innovative tool for the rapid and non-invasive classification of fruits. However, validating the learning capability and trustworthiness of a DL model, aka black box, to obtain insights can be challenging. To reduce this gap, we propose an integrated eXplainable Artificial Intelligence (XAI) method for the classification of carambolas at different maturity stages. We compared two Residual Neural Networks (ResNet) and Visual Transformers (ViT) to identify the image regions that are enhanced by a Random Forest (RF) model, with the aim of providing more detailed information at the feature level for classifying the maturity stage. Changes in fruit colour and physicochemical data throughout the maturity stages were analysed, and the influence of these parameters on the maturity stages was evaluated using the Gradient-weighted Class Activation Mapping (Grad-CAM), the Attention Maps using RF importance. The proposed approach provides a visualization and description of the most important regions that led to the model decision, in wide visualization follows the models an importance features from RF. Our approach has promising potential for standardized and rapid carambolas classification, achieving 91 % accuracy with ResNet and 95 % with ViT, with potential application for other fruits.

Pelatihan Pengelolaan Emosi pada Anggota Bintara Remaja di Polresta Surakarta

Teenage non-commissioned officers face several challenges in managing their emotions, which can hinder their ability to perform their duties optimally. One of the main challenges is lack of experience. As newcomers, young non-commissioned officers may not be used to dealing with various stressful, dangerous situations or involving interactions with the public. Emotion management training is expected to provide a number of important benefits for juvenile non-commissioned officers and the police institution as a whole. One of the main benefits is increased performance. To achieve the expected goals and benefits, the implementation of emotion management training must be carried out systematically and continuously. Training can begin with an introductory session on the importance of managing emotions, followed by practical training on communication skills, problem solving, and relaxation techniques. In addition, training should include simulations of real situations that youth NCOs may encounter, so that they can apply the skills learned in relevant contexts. Training evaluations must be carried out periodically to ensure that training objectives are achieved and the expected benefits can be felt. Evaluation can be done through knowledge tests, performance observations, and participant satisfaction surveys. Overall, this emotion management training provides short-term benefits in the form of reduced stress and improved performance, while also providing youth non-commissioned officers with skills that are crucial for their long-term careers in the police force. Thus, investment in the development of these skills not only improves operational efficiency but also supports the psychological well-being and professionalism of future police officers.

Teachers Views on Teachers Evaluation in Medical Colleges of Bangladesh

Teacher evaluation (TE) is systematic, periodic evaluation of a teacher with respect to his/her performance on job and his/her potential for development. This descriptive type of cross sectional study was conducted from July/22 to June/23 at four governments and four non-govemment medical colleges selected conveniently, to explore the views of the teachers regarding TE, sources of TE, merits and demerits of different sources, challenges and suggestion to overcome challenges to implement TE in medical colleges of Bangladesh. A total of 227 conveniently selected medical teachers were enrolled. Data were collected through a self-administered semi-structured questionnaire from teachers. Study revealed that majority of the teachers (89.4%) were in favor of TE, around 52% teachers agreed TE may be done once in a year. Areas to be evaluated are teacher’s teaching performance and depth of knowledge with a number of other areas. Sources of information, in order of preferences are student, trained evaluator, senior teacher, self and peer. Challenges of TE are training of the evaluator (86%), motivation of the teachers (82%), creation of unhealthy competition among the teachers (63%) etc. Study suggested for collaboration between medical educationist, teachers and policymakers (84%); inclusion of TE in faculty development program (83%), formulation of a legal frame (81%), introduction of a standard evaluation tool by DGME (82%) and may be started initially as a pilot program (80%). Study concluded and recommended that TE should be initiated and may be once a year. Areas to be evaluated are teaching skill, class room performance, depth of knowledge, unbiased assessment, research work, publication and other parameters. Sources may students, trained evaluator, senior teachers, self and peer. Proper guidelines should be developed for TE by the respective authority. Standard evaluation tools should be developed and TE may be linked with faculty development program. CME J 2024; 3(2); 20-30

The use of mixed reality in the preoperative planning of colorectal surgery: Preliminary experience with a narrative review

New advanced technologies have recently been developed and preliminarily applied to surgery, including virtual reality (VR), augmented reality (AR) and mixed reality (MR). We retrospectively review all colorectal cases in which we used holographic 3D reconstruction from February 2020 to December 2022. This innovative approach was used to identify vascular anomalies, pinpoint tumor locations, evaluate infiltration into neighboring organs and devise surgical plans for both training and educating trainee assistants. We have also provided a state-of-the-art analysis, briefly highlighting what has been stated by the scientific literature to date. VR facilitates training and anatomical assessments, while AR enhances training and laparoscopic performance evaluations. MR, powered by HoloLens, enriches anatomic recognition, navigation, and visualization. Successful implementation was observed in 10 colorectal cancer cases, showcasing the effectiveness of MR in improving preoperative planning and its intraoperative application. This technology holds significant promise for advancing colorectal surgery by elevating safety and reliability standards.

Research on the Evaluation of Baijiu Flavor Quality Based on Intelligent Sensory Technology Combined with Machine Learning

Baijiu, one of the world’s six major distilled spirits, has an extremely rich flavor profile, which increases the complexity of its flavor quality evaluation. This study employed an electronic nose (E-nose) and electronic tongue (E-tongue) to detect 42 types of strong-aroma Baijiu. Linear discriminant analysis (LDA) was performed based on the different production origins, alcohol content, and grades. Twelve trained Baijiu evaluators participated in the quantitative descriptive analysis (QDA) of the Baijiu samples. By integrating characteristic values from the intelligent sensory detection data and combining them with the human sensory evaluation results, machine learning was used to establish a multi-submodel-based flavor quality prediction model and classification model for Baijiu. The results showed that different Baijiu samples could be well distinguished, with a prediction model R2 of 0.9994 and classification model accuracy of 100%. This study provides support for the establishment of a flavor quality evaluation system for Baijiu.