Evaluation Approach Research Articles

Landslide susceptibility and building exposure assessment using machine learning models and geospatial analysis techniques

Landslides are among the most dangerous hazards in Asia, posing a significant threat to human lives, infrastructure, and sustainable development. Landslide susceptibility maps provide useful insights into hazard potential but lack quantitative exposure assessments to develop targeted mitigation strategies and resource allocation. This study aims to propose an integrated approach for landslide hazards and exposure evaluation using machine learning models on the Google Earth Engine environment and geospatial analysis techniques. A geospatial database was established to predict hazards and evaluate exposure, including data on topography, geology, hydrology, climate features, land use, and building data. The landslide susceptibility map was created with advanced machine-learning algorithms, including Classification And Regression Tree (CART), Random Forest (RF), Gradient Boosting (GB), and Support Vector Machine (SVM). The ROC curve and the Wilcoxon signed-rank test were employed to evaluate the performance differences among the CART, GB, RF, and SVM models. The results indicated that the RF model demonstrated the highest performance, leading to its selection for creating a landslide susceptibility map. Landslide exposure was evaluated by overlaying the landslide susceptibility map with building data to quantify the number of affected houses by landslides across districts and communes. The analysis results identified the Cho Don district as the most exposed, with 46,237 households located in high and very high landslide susceptibility zones, followed by Ba Be district (39,631 households), Bac Kan city (37,266 households), Bach Thong district (28,495 households), Cho Moi district (28,436 households), Na Ri district (17,723 households), Ngan Son district (14,142 households), and Pac Nam district (13,034 households). These findings enable the identification of the potential consequences of landslides on infrastructure, human settlements, and livelihoods, contributing to the promotion of disaster reduction and prevention strategies.

Integrated approach for seismic wave prediction and structural evaluation of Oya tuff quarry underground spaces: Field observations and numerical modeling

This study evaluates the structural stability of large underground spaces in seismic conditions, represented by the Oya underground stone mining plant. By directly monitoring the seismic response of the underground mining site, significant earthquake activities at the plate boundaries of the Tokyo region and Ibaraki Prefecture offshore area were observed. Additionally, through an in-depth analysis of seismic records from different locations within the underground structure, the dynamic characteristics and motion patterns of the Oya underground stone mining plant were revealed, revealing its movement trajectory during earthquakes. Additionally, this study innovatively applied seismic waves measured at the original site as input parameters and artificially generated seismic waves based on their response spectra. A numerical analysis was performed after ensuring the model's high correlation with the original site was met. The findings demonstrate that the results of both parameter input methods are confirmable and valuable. Under severe seismic conditions, instability was observed in some regions of the underground mining site. The study also discusses the location and damage mechanisms of the mining site's structure under seismic effects, providing valuable insights for the safety assessment of similar large underground spaces and proposing new approaches for selecting input parameters in seismic analysis.

Fusion of spectra and texture features of hyperspectral imaging for quantification and visualization of characteristic amino acid contents in beef

Characteristic amino acids is an important indicator for evaluating the nutritional value and flavor parameter of beef. To accurately quantify and visualize of arginine and alanine content in beef, the feasibility of visible near-infrared hyperspectral multivariate calibration analysis and data fusion was explored. Three methods were used to select the optimal feature wavelength and fusion multi-level texture information, and to develop the prediction performance of linear, non-linear and neural network models in different signals. Compared to all models, the linear model demonstrated superior performance in terms of characteristic spectral and fused spectral. Among, the more effective prediction performances emerged from CARS-ASM-ENT-PLSR model with RP2 = 0.9211, RMSEP = 0.1252 mg/100 g and RPDp = 3.49 for alanine. The UVE-ASM-ENT-HOM-COR-PLSR model for arginine prediction achieved a good performance of RP2 = 0.8596, RMSEP = 0.8596 mg/100 g and RPDp = 2.62. Finally, visualization plots of arginine and alanine content distribution were generated. This study shows that the data fusion method provides a new approach for rapid evaluation of CAA content.

Strategizing emissions reduction investment for a livestock production farm amid power demand pattern: A path to sustainable growth under the carbon cap environmental regulation

Livestock production companies come under increasing responsibility to reduce their environmental impact, and thereby, the simultaneous decision-making of inventory replenishment and emissions reduction investment has become essential for ensuring sustainable development in the livestock farming business. This study investigates, for the first time, the best investment strategy for a livestock farming business under the carbon cap (CC) environmental legislation, taking into account both the edible and non-edible parts of slaughtering mature growing items (GIs) after procuring and feeding baby GIs. By fusing economic and environmental factors, this study aims to shed light on two crucial issues: (i) figuring out the appropriate level of investment needed for the farm to adhere to the CC environmental regulation; and (ii) evaluating the effect of the investment decision on the farm's expenses and emissions levels. To deal with these insights, a thorough analytical framework integrating mathematical modeling methodology, economic evaluation, and carbon accounting approaches is employed. By analyzing the interaction between the farm's emissions reduction investments and replenishment choices, the cost-effective investment level is determined that enables the farm to satisfy the carbon cap obligation while guaranteeing maximum operational efficiency. The results of this study have important ramifications for livestock farming businesses trying to make their way through the stringent CC emission law. The results indicate that in order to keep the business feasible when the cap of the CC guideline is low, the livestock-producing farm should give priority to investing in minimizing feed emissions and using cutting-edge manure treatment methods.

Effectiveness of physical rehabilitation for physical functioning and quality of life in long-term care residents with dementia: a systematic review and meta-analysis.

The objective of this review was to evaluate the effectiveness of physical rehabilitation vs non-rehabilitation comparators for physical functioning and quality of life in long-term care (LTC) residents with dementia. LTC residents living with dementia often have impaired physical functioning and quality of life. Physical rehabilitation can improve physical functioning and quality of life for individuals living with dementia; however, many LTC residents with dementia do not receive physical rehabilitation and providers are unsure what interventions to employ. A synthesis of studies examining physical rehabilitation will help guide practice in the LTC sector where most residents live with dementia. Previous syntheses have focused on all residents in LTC, specific professions, interventions, or people with dementia in the community. Our review focused on LTC residents with dementia and used a broader definition of physical rehabilitation. This review included studies that evaluated physical rehabilitation in comparison with non-rehabilitation controls among LTC residents with any severity of dementia. We included experimental and quasi-experimental studies that measured the effect on activities of daily living, performance-based physical functioning, and self- or proxy-rated quality of life. Searches were conducted in APA PsycINFO (EBSCOhost), CINAHL (EBSCOhost), PubMed (National Library of Medicine), Embase, Scopus, and the Cochrane CENTRAL database with no date or language limitations. Two independent reviewers assessed the studies against the inclusion criteria. Two independent reviewers extracted data and conducted a methodological quality assessment using standardized checklists from JBI. Certainty of evidence was ascertained using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Where possible, studies were pooled in meta-analyses; otherwise, a narrative synthesis was presented. Thirty-three studies were included (n=3072 participants); 27 were randomized controlled trials and (RCTs) the remaining 6 were non-randomized trials. The overall risk of bias of the included studies was low to unclear. Many of the included studies focused on increasing activity or walking, while few were individually tailored or at an intensity appropriate to induce therapeutic effects on physical function. Physical function was measured via several outcome measures, limiting our ability to pool results. There was low-certainty evidence that physical rehabilitation improved activities of daily living assessed with multiple instruments (12 RCTs, 1348 participants, standardized mean difference [SMD] 0.78; 95% CI 0.27 to 1.30) and lower extremity function assessed with the Short Physical Performance Battery Score (3 RCTs, 258 participants, mean difference [MD] 3.01 points; 95% CI 1.37 to 4.66), compared with non-rehabilitation interventions. There was very low- to moderate-certainty evidence that physical rehabilitation demonstrated no change in the 30-Second Sit to Stand Test (2 RCTs, 293 participants, MD 0.79 repetitions; 95% CI -0.45 to 2.03), 6-Minute Walk Test (4 RCTs, 363 participants, MD 17.32 meters; 95% CI -29.41 to 64.05), Timed Walk Test (4 RCTs, 400 participants, MD 0.10 meters/seconds; 95% CI -0.02 to 0.22), Timed Up and Go Test (3 RCTs, 275 participants, MD -2.89 seconds; 95% CI -6.62 to 0.84), or quality of life (4 RCTs, 419 participants, SMD 0.20; 95% CI -0.08 to 0.47). This review demonstrates that physical rehabilitation may improve activities of daily living for LTC residents living with dementia, although the evidence is of low certainty. The effect of physical rehabilitation on specific functional tasks, such as gait speed and quality of life, are less clear. Future research should examine the effects of individualized, progressive interventions on outcome measures that reflect the capacity and preferences of LTC residents with more advanced dementia. PROSPERO CRD42022308444.

Economic evaluations of neglected tropical disease interventions in low- and middle-income countries: a systematic review protocol.

The objective of this systematic review is to provide an overview of economic evaluation studies of interventions for neglected tropical diseases in low- and/or middle-income countries. The majority of people most susceptible to neglected tropical diseases reside in low- and middle-income countries and suffer significant economic impact due to these diseases. The World Health Organization suggests utilizing a systematic and cross-cutting approach with multiple interventions to lessen the neglected tropical disease burden. Studies will be eligible for inclusion if they include economic evaluations of interventions for neglected tropical diseases and are conducted in low- and/or middle-income country settings. A preliminary search of MEDLINE (PubMed) was undertaken using MeSH terms, such as neglected tropical disease, economic evaluation, therapeutics, low- and/or middle-income countries . Two reviewers will screen titles and abstracts independently, followed by a full-text review against the inclusion criteria. Disagreements will be resolved by discussion or with a third reviewer. To assess methodological quality, the JBI checklist for economic evaluations will be used. For economic evaluations, data will be extracted using the standardized JBI data extraction form. The Dominance Ranking Matrix will be used to summarize and compare the results of different types of economic evaluations. Cost per quality adjusted life year gained and cost per disability adjusted life year averted will be measures for economic evaluation. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach will be used to assess the certainty of economic evidence, such as resource use and costs. PROSPERO CRD42017070386.

Beyond competence and retention: Developing a comprehensive evaluation framework for a rural primary care nurse practitioner residency program.

With the rise in nurse practitioner (NP) residency programs, evaluations have largely focused on retention and competency completion for residents. There is a need for expanded evaluation to ensure the sustainability of NP residency programs, to ensure timely adaptations to address resident satisfaction, and to solidify a long-term pathway of NPs well prepared for rural practice. We created a family nurse practitioner (FNP) residency program with a comprehensive evaluation framework to prepare residents for practice in rural settings. The evaluation framework was developed through collaborative engagement of an external evaluation team, program leadership, and clinical site representatives. The evaluation framework of the FNP residency program combined resident assessment and holistic program evaluation, using a rapid continuous quality improvement (QI) approach. The evaluation considered three distinct perspectives: the resident, the peer coach, and the clinical site. The rapid continuous QI approach allowed program leadership to respond swiftly to programmatic challenges, improve the residency program in response to residents' reported experiences, and emphasize sustainability for continued program impact, while assessing residents' learning and performance. The program's data-driven evaluation approach has demonstrated its success in meeting the goals of the Health Resources and Services Administration funding by increasing the number of primary care providers in rural settings. The program's expansion and continued success have further validated the efficacy of this evaluation framework in assessing, improving, and ensuring the sustainability of APRN residency programs. This article calls for the adoption of similar evaluation strategies in future residency programs to promote their long-term success and impact in rural health care settings.

Medical assistance in dying for mental illness: a complex intervention requiring a correspondingly complex evaluation approach: commentary, Malhi et al.

Medical assistance in dying for mental illness: a complex intervention requiring a correspondingly complex evaluation approach: commentary, Malhi et al.

An anomaly detection model for multivariate time series with anomaly perception

Multivariate time series anomaly detection is a crucial data mining technique with a wide range of applications in areas such as IT applications. Currently, the majority of anomaly detection methods for time series data rely on unsupervised approaches due to the rarity of anomaly labels. However, in real-world scenarios, obtaining a limited number of anomaly labels is feasible and affordable. Effective usage of these labels can offer valuable insights into the temporal characteristics of anomalies and play a pivotal role in guiding anomaly detection efforts. To improve the performance of multivariate time series anomaly detection, we proposed a novel deep learning model named EDD (Encoder-Decoder-Discriminator) that leverages limited anomaly samples. The EDD model innovatively integrates a graph attention network with long short term memory (LSTM) to extract spatial and temporal features from multivariate time series data. This integrated approach enables the model to capture complex patterns and dependencies within the data. Additionally, the model skillfully maps series data into a latent space, utilizing a carefully crafted loss function to cluster normal data tightly in the latent space while dispersing abnormal data randomly. This innovative design results in distinct probability distributions for normal and abnormal data in the latent space, enabling precise identification of anomalous data. To evaluate the performance of our EDD model, we conducted extensive experimental validation across three diverse datasets. The results demonstrate the significant superiority of our model in multivariate time series anomaly detection. Specifically, the average F1-Score of our model outperformed the second-best method by 2.7% and 73.4% in both evaluation approaches, respectively, highlighting its superior detection capabilities. These findings validate the effectiveness of our proposed EDD model in leveraging limited anomaly samples for accurate and robust anomaly detection in multivariate time series data.

Best Sales Selection Using a Combination of Reciprocal Rank Weighting Method and Multi-Attribute Utility Theory

The best salespeople are individuals who are not only able to meet or exceed sales targets, but also demonstrate exceptional skills in building relationships with customers, understanding their needs, and offering effective solutions. The problem of selecting the best salespeople often involves the challenge of an objective and fair assessment, as diverse evaluation criteria can affect the final result. One of the main obstacles is the presence of subjectivity in judgment, which can arise from personal preferences or pressure to maintain good relationships. This study aims to implement a sales performance evaluation model that combines the Reciprocal Rank Weighting and Multi-Attribute Utility Theory (MAUT) methods to obtain a more accurate and objective assessment of sales performance. This research contributes to the management literature and decision support systems by offering a new approach in sales performance evaluation. This opens up opportunities for further research and practical applications in the field of performance evaluation and salesforce management. Based on the final score calculated using the MAUT method, the salesperson rank from best to lowest is as follows: Sales 7 is ranked top with a value of 0.646, indicating the best overall performance. Sales 3 followed in second place with a value of 0.6125, followed by Sales 9 with a value of 0.5604 in third position.

Lipid-lowering therapies and long-term stroke prevention in East Asians: A systematic review and meta-analysis of randomized controlled trials.

Stroke prevention is a pressing global health priority, with reducing elevated lipids recognized as a key strategy. East Asians, constituting more than 1.6 billion individuals and the largest racial group worldwide, are a key demographic in this effort. Yet, the effectiveness of lipid-lowering therapies for stroke prevention in this population remains uncertain. We conducted a systematic review and meta-analysis of large-scale randomized controlled trials (RCTs) with at least 3 years of follow-up to evaluate the long-term impact of lipid-lowering therapies on stroke incidence in East Asians. We systematically searched four electronic databases up to 11 January 2024. The association was quantified using relative risk (RR) with a 95% confidence interval (CI), and between-study heterogeneity was evaluated using the I2 statistic. In addition, we utilized the Cochrane Risk of Bias Tool to assess the risk of bias in each included RCT and applied the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach to evaluate the certainty of the evidence. This study incorporated data from nine large-scale RCTs involving 54,354 participants. Our findings of overall analyses revealed that lipid-lowering therapies did not significantly affect the long-term incidence of all strokes (9 RCTs; 54,354 participants; RR = 0.98 (95% CI = 0.87-1.10); P = 0.75), ischemic stroke (7 RCTs; 52,059 participants; RR = 0.91 (95% CI, = 0.79-1.04); P = 0.16), or hemorrhage stroke (7 RCTs; 52,059 participants; RR = 1.24 (95% CI = 0.97-1.59); P = 0.09) in East Asians. Notably, there was no evidence of heterogeneity or publication bias, and the quality of evidence assessed using GRADE methodologies was rated as high. Sensitivity analyses confirmed the robustness of our results, with no single study significantly affecting the overall findings. Furthermore, subgroup analyses consistently supported the conclusions, further bolstering the reliability of our study. Lipid-lowering therapies did not demonstrate any beneficial effects on long-term stroke prevention among East Asians.

A STUDY TO ASSESS THE EFFECTIVENESS OF STRUCTURED TEACHING PROGRAM ON KNOWLEDGE REGARDING HEALTH HAZARDS OF ELECTRONIC DEVICES AMONG ANTENATAL MOTHERS AT SELECTED MATERNITY HOSPITALS, BANGALORE

Background of the Study:Electronic devices are components for controlling the flow of electrical currents for the purpose of information processing and system control. Prominent examples include transistors and diodes. Electronic devices are usually small and can be grouped together into packages called integrated circuits. Electronic devices are now an integral part of modern life. In many countries over half the population use electronic devices and the market is growing very rapidly. The electromagnetic field radiations impart an adverse effect on physical, mental and the emotional state of a pregnant mother and deeply affect the brain cells of mother and her unborn child. It affects level of melatonin, a sleep- controlling hormone which causes sleep disturbances in mothers, that pass to unborn babies through the placenta resulting in growth retardation. Objectives: 1. To assess the level of knowledge regarding health hazards of electronic devices during pregnancy among antenatal mothers in selected maternity Hospitals, Bangalore. 2. To evaluate the effectiveness of structured teaching program on knowledge regarding health hazards of electronic devices during pregnancy among antenatal mothers attending in selected maternity Hospitals, Bangalore. 3. To determine the association between knowledge score with selected demographic variables among antenatal mothers attending in selected maternity Hospitals, Bangalore. Methods:The research approach adopted was an evaluative research approach and research design adopted for this study was Pre experimental one group pretest and post-test research design. Simple random sampling technique was used to collect 60 antenatal mother sample. Data was collected over a period of one month. Structured knowledge questionnaire used as a tool to assess knowledge regarding the health hazards of electronic devices. Data obtained was analysed in terms of objectives which was calculated and tabulated. Results:In pretest, out of 60 antenatal mothers, 33.3% had inadequate knowledge and 66.7% had moderately adequate knowledge and none of the antenatal mothers had adequate knowledge. In post-test, out of 60 antenatal mothers, 73.3% had adequate knowledge, 26.7% had moderately adequate knowledge and none of the antenatal mother had inadequate knowledge. Over all knowledge the paired mean difference was 11.08 and SD of difference was 0.263 and enhancement mean percentage was 37 It was found significant (t=24.464, df=59) (i.e, p<0.05). The paired t-test was also worked out and it was found to be invariably significant (i.e p<0.05). The present study found the significant association between knowledge regarding health hazards of electronic devices at selected demographic variables of antenatal mothers. Interpretation and Conclusion: The study concluded that the post-test knowledge of antenatal mothers was improved after undergone Structured teaching programme regarding health hazards of electronic devices. The overall findings of the study clearly showed that the structured teaching programme was effective in improving the knowledge level of antenatal mothers regarding health hazards of electronic devices.

An In Silico Approach for Evaluation of ITS, rbcL, and psbA-trnH for DNA Barcoding of Eugenia spp.

The genus Eugenia is known to be complex with intricate synonyms and taxonomy, and morphological identification is often unreliable due to overlapping characteristics and environmental influences, particularly in the flowers. DNA barcoding provides a way around this problem, as it can identify specimens using very short gene sequence fragments obtained from a small number of tissues. The method used in this research is the in silico dengan menggunakan barcode DNA ITS, rbcL, dan psbA-trnH dari spesies Eugenia spp yang ditemukan di NCBI GenBank. The successful reconstruction of the phylogenetic tree from the three regions, including ITS, rbcL, and psbA-trnH shows that several species of Eugenia spp. are divided into 2 clades. Research successfully analyzed Eugenia plant relationship with using the ITS, rbcL, and psbA-trnH gene sequences in silico based shows that several species of Eugenia spp. are divided into 2 clades. In general, high bootstrap values are shown by phylogenetic trees based on the ITS region.ABSTRAK: Genus Eugenia dikenal kompleks dengan sinonim dan taksonomi yang rumit, serta identifikasi morfologis yang sering tidak dapat diandalkan karena karakter yang tumpang tindih dan dipengaruhi oleh lingkungan, terutama pada bagian bunga. Barcoding DNA memberikan jalan keluar dari masalah ini, karena dapat mengidentifikasi spesimen menggunakan fragmen urutan gen yang sangat pendek yang diperoleh dari sejumlah kecil jaringan. Metode yang digunakan dalam penelitian ini adalah in silico dengan menggunakan barcode DNA ITS, rbcL, dan psbA-trnH dari spesies Eugenia spp yang ditemukan di NCBI GenBank. Keberhasilan rekonstruksi pohon filogenetik dari tiga wilayah antara lain ITS, rbcL, dan psbA-trnH menunjukkan bahwa beberapa spesies Eugenia spp. dibagi menjadi 2 clade. Penelitian yang berhasil menganalisis hubungan tanaman Eugenia dengan menggunakan rangkaian gen ITS, rbcL, dan psbA-trnH secara silico menunjukkan bahwa beberapa spesies Eugenia spp. dibagi menjadi 2 clade. Secara umum nilai bootstrap yang tinggi ditunjukkan oleh pohon filogenetik berdasarkan wilayah ITS.

KHI XẾP HẠNG TRỞ THÀNH MỤC TIÊU: PHÂN TÍCH QUY LUẬT GOODHART TRONG XẾP HẠNG ĐẠI HỌC Ở VIỆT NAM

Goodhart's Law describes the phenomenon where a measure becomes a target, leading to behaviors aimed at optimizing that measure rather than achieving the true underlying goals. In the context of university rankings, excessive focus on attaining higher ranks can incentivize universities to manipulate metrics rather than genuinely improving educational quality. Analyzing this behavioral shift, research highlights the negative impacts of Goodhart's Law in higher education, particularly in Vietnam. Instead of enhancing teaching and research quality, universities often prioritize ranking advancement through opaque methods. This competitive race results in high costs for students and families without commensurate educational benefits. Addressing these issues requires raising awareness, establishing new evaluation approaches, and promoting genuine educational practices. Keywords: Goodhart; university; ranking; quality.

The Role of Genetics, Neurobiology, and Psychosocial Factors in the Development and Treatment of Eating Disorders: A Systematic Review

Eating disorders are severe complications affecting peoples’ eating patterns, with erratic practices like purging behaviors, binge eating, and avoidance of food. These disorders result from different causes, including neurotransmitter imbalance, psychological factors like body-shaming, and genetic inheritance. The present review focuses on genetic, neurobiology and psychological factors to provide an understanding of the development of eating disorders and subsequent treatment. The present review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist that guided the evidence collection in the review to ascertain high quality. The Participant, Interventions, Comparison, Outcomes, and Studies (PICOS) protocol guided the establishment of potential studies' inclusion criteria. The Grading of Recommendations, Assessments, Development, and Evaluation (GRADE) approach was used to assess the certainty of evidence from the individual studies. Two independent reviewers were tasked with study selection, data collection, and study risk of bias assessed. The reviewers used the Cochrane risk of bias tool to assess the risk of bias in the included studies. Fifteen studies met the eligibility tests and were included in the review. A review of the evidence obtained from the included studies revealed that neurobiology, genetics and psychological factors influence the development of eating disorders like binge eating disorders, anorexia nervosa, and bulimia nervosa. In genetics, familial integration and heredity revealed the passing of the genes responsible for the development of anorexia nervosa in subsequent generations. Psychological factors and neurobiology affect self-esteem or body shaming and affect the balance of neurotransmitters in the brain, respectively. The treatment interventions aim to restore neurotransmitter levels and confidence after losing confidence and self-body hate due to bad shape. Genetics, neurobiological factors and psychological status are responsible for the development of eating disorders. Bulimia nervosa, binge eating disorder and purging behaviors result from unregulated 5-HT depletion, can be inherited or can result from body shaming. The evidence shows that eating disorders can be treated based on the aetiologies and pathophysiology. Keywords: Eating disorders, treatment, neurobiological factors, genetics, binge eating disorder, bulimia nervosa.

Paediatric postoperative acute kidney injury after non-cardiac surgery: Protocol for a systematic review and meta-analysis.

Paediatric acute kidney injury (AKI) is associated with significant adverse outcomes such as increased mortality, progression to chronic kidney disease and longer length of stay in hospital. Postoperative AKI is a common and recognized complication after surgery in adults. In the paediatric population, AKI postoperatively to cardiac surgery has been extensively studied. However, the incidence of postoperative AKI after non-cardiac surgery is less clear. Therefore, we aim to assess the available literature on this topic. We will conduct a systematic review of observational and randomized controlled trials assessing the incidence of paediatric postoperative AKI after non-cardiac surgery. Pairs of reviewers will independently screen the literature and extract data and assess risk of bias from eligible studies. The databases Pubmed, Cochrane and Web of Sciences will be searched. We will conduct the review in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and the Grading of Recommendation, Assessment, Development and Evaluation (GRADE) approach. If sufficient homogeneity within the included trials we will conduct meta-analyses. This systematic review aims to investigate the incidence of postoperative AKI in the paediatric non-cardiac surgery population. The results of this review will provide a foundation for future research in the field of paediatric postoperative AKI.

An Exploration of Unique Mental Health Challenges and Resilience Factors within the LGBTQ+ Community: A Systematic Review

Mental health challenges in the LGBTQ+ community pressing issues as it impact the overall health status. Despite the concerns raised on the discrimination, bias and stereotypes, new challenges arise, implicating challenges to the health sector. The present review of evidence focuses on the resilience factors and the unique mental health challenges faced by members of the LGBTQ+ community. The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) were used to identify, select, appraise and synthesize evidence in the present review, whereas the Sample, phenomenon of Interest, Design, Evaluation and Research type (SPIDER) protocol guided the selection of eligible studies to be reviewed. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was used to rate the certainty of evidence about the unique mental health challenges and resilience factors within the lesbian, gay, bisexual, transgender, queer, intersex, and asexual (LGBTQ+) community. Initial article search was limited to English publications and performed on electronic databases, including Google Scholar, ProQuest, PubMed, and Web of Science. The Cochrane risk of bias assessment tool was used to examine the risk of bias in the individual studies. Risk of bias assessment was performed on the domains, including due to the randomization process, bias due to deviations from intended interventions, bias due to missing outcome data, bias in the measurement of the outcomes, bias in the selection of the reported result, and the overall risk of bias, reflecting the overall risk of bias of the included studies. A qualitative synthesis of results was considered in the present systematic review. The evidence was contrasted and compared against the existing knowledge and theoretical orientation. The present review found that poor dissemination of interventions and implementations are unique mental health challenges among the LGBTQ+ community. The poor implementation and dissemination of interventions substantiate psychological distress, anxiety, depression, and suicidal thoughts and deteriorates quality of life. The web or internet-based implementation of cognitive behavioral therapy emerged as effective resilience factor in the management of mental conditions among members of the LGBTQ+ community. Keywords: LGBTQ+, mental health, treatment, cognitive behavioral therapy, resilience factors, anxiety, depression, and interventions

Plan evaluation for heat resilience: complementary methods to comprehensively assess heat planning in Tempe and Tucson, Arizona

Abstract Escalating impacts from climate change and urban heat are increasing the urgency for communities to equitably plan for heat resilience. Cities in the desert Southwest are among the hottest and fastest warming in the U.S., placing them on the front lines of heat planning. Urban heat resilience requires an integrated planning approach that coordinates strategies across the network of plans that shape the built environment and risk patterns. To date, few studies have assessed cities’ progress on heat planning. This research is the first to combine two emerging plan evaluation approaches to examine how networks of plans shape urban heat resilience through case studies of Tempe and Tucson, Arizona. The first methodology, Plan Quality Evaluation for Heat Resilience, adapts existing plan quality assessment approaches to heat. We assess whether plans meet 56 criteria across seven principles of high-quality planning and the types of heat strategies included in the plans. The second methodology, the Plan Integration for Resilience Scorecard™ (PIRS™) for Heat, focuses on plan policies that could influence urban heat hazards. We categorize policies by policy tool and heat mitigation strategy and score them based on their heat impact. Scored policies are then mapped to evaluate their spatial distribution and the net effect of the plan network. The resulting PIRS™ for Heat scorecard is compared with heat vulnerability indicators to assess policy alignment with risks. We find that both cities are proactively planning for heat resilience using similar plan and strategy types, however, there are clear and consistent opportunities for improvement. Combining these complementary plan evaluation methods provides a more comprehensive understanding of how plans address heat and a generalizable approach that communities everywhere could use to identify opportunities for improved heat resilience planning.

Measuring museum sustainability in China: a DSR model-driven approach to empower sustainable development goals (SDGs)

In the past few years, sustainable development has undoubtedly become an essential perspective for museums. Museums have been committed to raising social awareness around ecological conservation and cultural diversity through various exhibitions, education and research projects, and public engagement. However, the concepts, approaches, and practises of “sustainability” differ across nations and regions, and there is a lack of sufficient quantitative research on sustainable development by and within museums. This article aims to establish an evaluation framework and evaluation approach for museum sustainability in China. Its framework is initially based on the DSR model, in which “D” delineates seven deeds of museum visitors, “S” characterizes the status of sustainable practises within museums, and “R” involves presenting sustainability strategies pertinent to Chinese museums by integrating Sustainable Development Goals (SDGs). A fuzzy QFD model is then used to develop an evaluation approach for analyzing the Zhejiang Natural History Museum (ZNHM)’s sustainable development strategies, using data from surveys and in-depth interviews. As a result of this study, significant opportunities for deepening sustainable practises were identified for ZNHM, which include updating the collection system, enhancing professionalism in exhibitions and educational projects, and securing funding policies. ZNHM’s sustainability efforts prioritize enhancing social awareness, and internal reforms related to social value, governance, and professional capabilities. With these foundations in place, international cooperation among museums may be the next step towards a sustainable future.

Retraction Note: Evaluation of the anticancer potential of CD44 targeted vincristine nanoformulation in prostate cancer xenograft model: a multi-dynamic approach for advanced pharmacokinetic evaluation

Retraction Note: Evaluation of the anticancer potential of CD44 targeted vincristine nanoformulation in prostate cancer xenograft model: a multi-dynamic approach for advanced pharmacokinetic evaluation