Evaluation Process Research Articles

Placebo treatment affects brain systems related to affective and cognitive processes, but not nociceptive pain

Drug treatments for pain often do not outperform placebo, and a better understanding of placebo mechanisms is needed to improve treatment development and clinical practice. In a large-scale fMRI study (N = 392) with pre-registered analyses, we tested whether placebo analgesic treatment modulates nociceptive processes, and whether its effects generalize from conditioned to unconditioned pain modalities. Placebo treatment caused robust analgesia in conditioned thermal pain that generalized to unconditioned mechanical pain. However, placebo did not decrease pain-related fMRI activity in brain measures linked to nociceptive pain, including the Neurologic Pain Signature (NPS) and spinothalamic pathway regions, with strong support for null effects in Bayes Factor analyses. In addition, surprisingly, placebo increased activity in some spinothalamic regions for unconditioned mechanical pain. In contrast, placebo reduced activity in a neuromarker associated with higher-level contributions to pain, the Stimulus Intensity Independent Pain Signature (SIIPS), and affected activity in brain regions related to motivation and value, in both pain modalities. Individual differences in behavioral analgesia were correlated with neural changes in both modalities. Our results indicate that cognitive and affective processes primarily drive placebo analgesia, and show the potential of neuromarkers for separating treatment influences on nociception from influences on evaluative processes.

MEDICAL EVALUATION FOR RESPIRATOR USE- UPDATED APPROACHES.

Respirator medical evaluations are an important component of occupational health practice. Concepts and practices were established 25-50 years ago.METHODWe suggest analysis and discussion of three areas warranting update. a) Shifting from disease-based decisions to evaluating 12 specific domains- cardiopulmonary, sudden change in condition, thermal, work interference, exacerbating existing condition, donning/doffing, dermatologic, proper utilization, fit testing interference, cultural/religious, arms/legs, subjective responses. Two distinct evaluation processes are advised-"algorithmic" for the frequent straightforward evaluations and "specialist" for the more complex. b) Acknowledging the importance of subjective responses and clarifying the underlying causes - external stimulus, sensation, perception, interpretation, acceptability, and emotional response. c) Optimizing the organizational structures by explicitly defining the scope of evaluations, modifying the sequencing of assessment, and specifying qualifications of clinicians performing assessments. Reassessing respirator medical evaluation methods is needed.

Hygrothermal Degradation of Epoxy Electrical Insulating Material—Testing and Mathematical Modeling

The degradation of electrical insulating materials has been a subject of interest for decades as they are commonly applied in many fields of electrical engineering. Suitably modeling such a process is important since the known and well-described degradation process reveals the effect of ambient conditions, and this allows us to possibly estimate a material’s remaining useful life. However, not many studies are dealing with the effect of the hygrothermal degradation of impregnating mono-component epoxy resins in the context of electrical engineering. Therefore, this study deals with this issue and discusses both the dielectric response (based on the measurement of relative permittivity, dissipation factor, and dielectric strength) and the mechanical response (based on measurements of tensile strength and Shore D hardness) to a hygrothermal degradation experiment. In addition, the results of thermal analyses are presented for the evaluation of the pristine specimen manufacturing process and possible post-curing processes. Furthermore, this study presents several methodologies for modeling the degradation process, including a novel methodology in this area based on Bayesian experimental design. As an outcome, mechanical parameters are proven to be specific in terms of the actual condition of the material and the Bayesian enhanced degradation model seems to be superior to the conventional evaluation methods in this particular study.

CONTINUOUS PERFORMANCE EVALUATION OF EMPLOYEES USING AHP AND MODIFIED PUGH MATRIX METHOD: CONTRASTING WITH TOPSIS, PROMETHEE AND VIKOR

Applications of the AHP for employee performance evaluation in organizations are widely discussed in the literature. Contemporary organizations are increasingly discarding the traditional periodic appraisal systems and moving towards a real-time continuous process of evaluation. The existing multi-criteria decision making method (MCDM)-based employee performance evaluations are not suitable for such continuous evaluations, due to the complexity of the MCDM method. The current appraisal system is notoriously difficult to administer which prevents organizations from using it as an ongoing evaluation. There is a need for a simple yet robust multi-criteria decision making method for continuous performance evaluation of employees (CPEE). In this article, a modified version of the Pugh Matrix Method (MPMM) is proposed as a robust outranking method. The MPMM in combination with the AHP can function as an effective tool for CPEE. The MPMM is compared with other established and popular methods including TOPISIS, PROMETHEE and VIKOR. A statistical comparison using correlation validates the evaluation by the MPMM. There appears to be no significant difference in the evaluation of the MPMM with the other MCDM methods. Owing to its robustness and ease of use, the MPMM can easily be adopted by organizations for CPEE. The managerial implications and agenda for future research are also discussed.

Epidemiological analysis of blood donors from college students in Hefei city.

College students represent a unique demographic group as they are adults no longer under direct parental care, yet often lack the institutional health support available to more established members of society, which can lead to their health needs being neglected, despite their substantial contributions to blood donation. The objective of this study is to shed light on the health status of college students in Hefei, with a specific focus on transfusion-transmitted diseases. Based on the detailed data analysis, the implementation of some constructive strategies will play a good warning role in improving clinical blood safety and promoting better health monitoring of this population in the future. The study aims to achieve two main objectives: On the one hand, to deepen our understanding of college students' participation in blood donation activities. On the other hand, to propose effective strategies for increasing youth involvement. Additionally, such research aims to afford recommendations for ensuring the safety of clinical blood supplies. Although the strategies and suggestions presented are speculative, they are grounded in the logical analysis of data and relevant theoretical frameworks. Therefore, these recommendations serve as a basis for potential future testing and implementation. The evaluation process for blood samples at the Hefei Blood Bank involves thorough serological testing for hepatitis B and C, HIV, and Treponema pallidum using both Enzyme-Linked Immunosorbent Assay (ELISA) and Nucleic Acid Testing (NAT). HIV reactive samples were further confirmed using Western Blot techniques at an external specialized laboratory. To ensure accuracy, each sample was tested with reagents from two different manufacturers. Moreover, any initially reactive sample was retested with the same reagent to eliminate potential false positives. In cases of conflicting results, alternative reagent kits are utilized for further confirmatory tests. Only samples that consistently show reactive results in consecutive tests are considered positive confirmation samples. Upon analysis of the data set, it was found that out of the total 663,105 donors, 177,089 (26.7%) were identified as college students, with the remaining 486,016 categorized as noncollege students. Our study demonstrated a notably lower prevalence of blood-transmitted infections among college students (0.48%) in contrast to the wider donor population (1.23%), underscoring their potential as safe blood donors. To uphold this level of safety and protect public health, it is crucial to increase disease prevention awareness and advocate for responsible donation practices within this specific demographic. Strengthening confidentiality protocols and expanding education on safe sexual behaviors in university settings are vital actions to cultivate an environment that promotes informed and secure blood donation. The overall group had prevalence rates of 0.44% for hepatitis B, 0.15% for hepatitis C, 0.02% for HIV, and 0.42% for Treponema pallidum. When focusing on the student cohort, the prevalence rates were 0.17% for hepatitis B, 0.04% for hepatitis C, 0.02% for HIV, and 0.23% for Treponema pallidum. Transmissibility through blood transfusion All donors (%) Students (%) Non-students (%) Any infection 1.23 0.48 1.51 HbsAg 0.44 0.17 0.54 Anti-HCV 0.15 0.04 0.19 HIV Ag/Ab 0.02 0.02 0.02 Anti-TP 0.42 0.23 0.49 Individuals with two or more infectious agents occur more than once in all categories. While it leads to numerical over-representation, such overlap is minimal and statistically insignificant.

Cu-alginate hydrogels in microfluidic systems: a sustainable catalytic approach for click chemistry

This work explores the innovative use of copper-alginate (Cu-alginate) hydrogels within microfluidic systems to catalyze dipolar cycloaddition reactions, emphasizing green chemistry principles and process intensification. Utilizing naturally occurring biopolymers, such as alginates, provides an environmentally friendly alternative to conventional catalyst supports due to their biocompatibility, biodegradability, and effective metal ion immobilization capabilities. The integration of these biopolymer-based catalysts into microfluidic devices allows for precise control over reaction conditions, leading to enhanced reaction kinetics and mass transfer efficiencies. Our results demonstrate that Cu-alginate hydrogels effectively catalyze the formation of 1,4-disubstituted 1,2,3-triazoles through [3 + 2] dipolar cycloaddition reactions with high regioselectivity and conversion. The microfluidic setup ensures rapid and efficient synthesis, surpassing traditional batch reaction methods in both reaction rate and environmental impact by reducing solvent usage and waste generation. Furthermore, the use of microfluidics contributes to the reproducibility and scalability of the synthesis process, important for industrial applications. The model-based design and its simulations have been employed to further understand and optimize the reaction system. Diffusion through the gel layer and catalytic reaction kinetics estimated from experimental data were included in the model, providing a theoretical foundation for a comprehensive process evaluation. This study not only advances the field of sustainable catalysis by demonstrating the practical utility of biopolymer-supported catalysts in microfluidic systems, but also sets the stage for further research into biopolymer applications in complex chemical syntheses.

Implementing the Effective Coach2Move Approach for Community-Dwelling Older Adults with Mobility Limitations in Physical Therapist Practice: A Multi-Methods Process Evaluation.

The aims of this study were to evaluate the adoption of and fidelity to the Coach2Move approach; identify differences between physical therapists with a specialization in geriatrics and physical therapists without a specialization; explore if level of adoption and specialization explain variances in effectiveness; and explore group differences in attitudes and experiences with implementation. A multi-methods process evaluation of Coach2Move implementation through 2 education days, 3 peer-assessment meetings, and an adapted electronic health record was performed alongside a cluster randomized stepped-wedge trial comparing regular care physical therapy with Coach2Move. Participants were 36 physical therapists with a specialization (n = 17) and without a specialization (n = 19) who treated 292 community-dwelling older adults. Level of adoption and fidelity were analyzed by comparing pre-implementation scores with scores 1year later. Coach2Move adoption was measured by e-assessment scores and fidelity through health record indicators. The impact of specialization and adoption on health outcomes was examined using a mixed-model ANOVA. Therapists' attitudes and experiences were collected through a survey based on semi-structured interviews. Mean total indicator scores on the e-assessment (adoption of a Coach2Move mindset) increased from baseline 17% (SD = 5%) to 47% (SD = 9%) at follow-up. Physical therapists with a specialization in geriatrics scored higher than physical therapists without (54% [SD = 6%] vs 41% [SD = 6%]). Mean indicator scores on health records (fidelity) increased from 35% (SD = 12%) at baseline to 47% (SD = 15%) at follow-up. Mean scores of physical therapists with a specialization in geriatrics were higher. Level of adoption and specialization (yes/no) did not explain the variance in effectiveness. Physical therapists identified important facilitators, including tailored education and peer-assessment meetings, while adequate reimbursement for the extra time investment was considered a necessity. Different workflows in practices were perceived as a barrier. Implementation led to increased adoption and fidelity of the Coach2Move intervention by physical therapists but shows room for improvement. Attitudes towards the approach and its implementation were positive. Future implementation efforts on adoption could be improved by focusing on a fair compensation structure by third party payers and insurance companies and optimizing organizational and financial context within practices. This study evaluated the implementation of Coach2Move, a clinical reasoning approach designed to increase physical activity and improve self-efficacy in older adults. Overall, the study demonstrates the potential of Coach2Move to be effectively adopted by physical therapists. However, addressing therapist compensation and adapting to practice workflows are important considerations for successful large-scale implementation.

Barriers and facilitators for implementation of OptiBreech collaborative care: A qualitative study as part of an implementation process evaluation

ProblemLack of opportunity for breech training and clinical experience reduced professional confidence and expertise in supporting vaginal breech birth. BackgroundOptiBreech collaborative care is a care pathway for breech presentation at term that aims to enable improve safety through person-centred care and improved training opportunities for maternity professionals, within dedicated clinics and intrapartum support. In feasibility work, barriers and facilitators to team implementation were observed by team members. AimThis study sought to describe factors affecting optimal future implementation and safety of OptiBreech care. MethodsSemi-structured interviews were conducted with staff members at 13 OptiBreech trial sites (17 midwives and 4 obstetricians, n=21), via video conferencing software. The Theoretical Domains Framework (TDF) was used to identify factors impacting team implementation. Themes identified in the TDF were refined in reflexive discussion and grouped into key facilitators, key barriers, and dynamic factors (which span both barriers and facilitators). The interviews were then coded, analysed, and interpreted according to the refined framework. FindingsThe key facilitators were broadly categorised within skill development, beliefs about capabilities, and social support from the wider multidisciplinary team. Key barrier categories were resources, social obstacles, and fears about consequences. Dynamic factor categories were individual responsibility, training, and attending births. ConclusionWhile some factors affecting implementation were specific to the individuals and cultures of certain Trusts, recommendations emerged from analysis that are more widely applicable across multiple settings. These should be considered going forward for future service implementation, and in the next stage of OptiBreech clinical trials.

Promoting healthy sleep in 0-2-year-old infants: a study protocol for the development and mixed method evaluation of a sleep health program tailored to Dutch youth healthcare regions

BackgroundSleep problems are common among infants and can have a serious impact on the health and wellbeing of both child and parents. To sustainably promote infant sleep on a population level, it is necessary to develop evidence-based programs that can be implemented on a large scale. The Youth Health Care setting, with its focus on prevention, child health promotion and services widely available for parents, can be a suitable setting to do so. Currently however, sleep health promotion in this setting seems to be suboptimal. To promote healthy infant sleep on a population level, programs need to be accessible and comprehensible for all parents, including parents with limited (health) literacy. Therefore, this study aims to develop, implement and evaluate a program called ‘Sleep on number 1’, that is tailored to Dutch Youth Health Care, to sustainably promote healthy sleep in 0-2-year-old infants.MethodsThe program was developed based on co-creation with parents and Youth Health Care professionals, evidence-based behaviour change theories and sleep health promotion methods. Program effectiveness is investigated with a quasi-experimental study design comparing the program group with the care as usual control group. Participants consist of parents of 0-2-year-old children. Primary outcome is infant sleep quality at the age of 10 weeks and 6, 9, 14 and 24 months, measured with a sleep diary. The primary data analysis focuses on night awakenings at 9 months. Secondary outcomes focus on parental behaviour regarding infant sleep, related behavioural determinants and parental satisfaction with Youth Health Care sleep advice. Program effectiveness is analysed using a linear mixed-model in case of data clustering, and an independent samples T-test or linear regression in case no substantial clustering effects are found. A mixed methods process evaluation is performed with parents and Youth Health Care professionals, assessing program reach, adoption, implementation, maintenance and working mechanisms.DiscussionThe ‘Sleep on number 1’ program is an evidence-based sleep health program for 0-2-year-old children, tailored to Dutch Youth Health Care. If effective, this program has the potential to improve infant sleep on a population level.Trial registrationISRCTN, ISRCTN27246394, registered on 10/03/2023. https://www.isrctn.com/ISRCTN27246394.

Optimizing short-term in-class process evaluation: analyzing the effectiveness of teaching interventions in pharmaceutical education using repeated measures analysis

BackgroundThe assessment of the effectiveness of teaching interventions in enhancing students’ understanding of the Pharmaceutical Care Network Europe (PCNE) Classification System is crucial in pharmaceutical education. This is especially true in regions like China, where the integration of the PCNE system into undergraduate teaching is limited, despite its recognized benefits in addressing drug-related problems in clinical pharmacy practice. Therefore, this study aimed to evaluate the effectiveness of teaching interventions in improving students’ understanding of the PCNE Classification System in pharmaceutical education.MethodsUndergraduate pharmacy students participated in a series of sessions focused on the PCNE system, including lectures (t1), case analyses (t2), and practical implementation (t3). The levels of understanding were evaluated using time-course questionnaires. Initially, paired samples t-Tests were used to compare understanding levels between different time points. Subsequently, Repeated Measures Analysis (RMA) was employed. Pearson correlation analysis was conducted to examine the relationship between understanding levels and the usability and likelihood of using the PCNE system, as reported in the questionnaires.ResultsThe paired samples t-Tests indicated insignificant differences between t2 and t3, suggesting limited improvement following the practical implementation of the PCNE system. However, RMA revealed significant time effects on understanding levels in effective respondents and the focused subgroup without prior experience (random intercept models: all p < 0.001; random slope models: all p < 0.001). These results confirmed the effectiveness of all three teaching interventions. Pearson correlation analysis demonstrated significant positive correlations between understanding levels and the usability and likelihood of using the PCNE system at all examined time points. This finding highlighted the reliability of the understanding levels reported in the questionnaires. The homework scores were used as external calibration standards, providing robust external validation of the questionnaire’s validity.ConclusionThe implementation of RMA provided robust evidence of the positive impact of time on understanding levels. This affirmed the effectiveness of all teaching interventions in enhancing students’ comprehension of the PCNE Classification System. By utilizing RMA, potential errors inherent in common statistical methods, such as t-Tests, were mitigated. This ensured a more comprehensive and accurate assessment of the effectiveness of the teaching interventions.

Assessing urban renewal opportunities by combining 3D building information and geographic big data

ABSTRACT The assessment of urban renewal (UR) potential aims to prioritize areas for UR, which are essential for sustainable urban revitalization. However, conventional data sources often fall short in encompassing diverse urban characteristics in the evaluation process, such as urban three-dimensional (3D) building information and the intensity of human activities. To address this gap, this study integrated 3D building data and geographic data to create a comprehensive set of 28 indicators spanning four dimensions: natural environmental conditions, land use, socio-economic factors, and building conditions. These indicators take into account vertical dimensions, dynamic aspects, and fine-scale details. Leveraging the existing UR practices as a positive example, we established an UR potential assessment model at street block scale using Presence and Background Learning combined with extreme gradient boosting algorithms (PBLXGBoost). Our findings revealed that the highest accuracy in evaluating industrial UR potential was achieved in Shenzhen (F pb _ avg = 0.80, RMSE avg = 0.21), followed by residential and commercial UR potential assessments. Conversely, other type UR exhibit lower accuracy. Street blocks with significant UR potential are predominantly located in Bao’an, Longgang, and Longhua Districts. Furthermore, employing the SHAP model to elucidate the evaluation results uncovered intricate hierarchical, positive-negative, and overlapping relationships among various factors and different UR types, where geographic big data and 3D building information showed strong correlations. The methodology proposed in this study enables objective and precise assessments of UR potential, offering valuable support for UR practice and sustainable urban development.

Assessment of innovativeness, and price and reimbursement negotiation of medicines: recommendations of an expert panel

This paper illustrates the recommendations of a Working Group (WG) on the assessment of drugs innovativeness and the negotiation of price and reimbursement. The WG included researchers, institutions, clinicians, patient representatives and pharmaceutical companies. The first part of the contribution summarizes the literature on drug pricing models, which was considered in the WG, and, in particular, the pricing criteria, the evaluation and negotiation processes, the management of the uncertainty of the evidence, the use of cross-reference pricing and price negotiation for new indications of existing drugs. The second part illustrates the results of the WG with a focus on innovativeness assessment, value framework and price negotiation. The main recommendations of the WG are: to define more specific criteria for the identification of comparators and endpoints for macro therapeutic areas/settings; to produce guidelines on the use of indirect comparisons and studies supporting this evidence; to consider the drug value as the main driver of price and reimbursement negotiation; to maintain flexibility in the negotiation process, but, at the same time, to give greater structure and predictability in the assessment of value for money, with a more qualified role of cost-effectiveness and a range of threshold values for the incremental cost-effectiveness ratio; to selectively reintroduce Managed Entry Agreements and the Indication-based pricing model; to implement an early dialogue between the Italian Medicine Agency and the pharmaceutical companies in order to optimize the negotiation process, and a structured involvement of scientific societies and patient representatives.

An Innovative Method for Deterministic Multifactor Analysis Based on Chain Substitution Averaging

The aims of this paper are to present the methodology, derived mathematical expressions for determining the individual factor influences and the adaptation for the conditions of dynamic deterministic factor analysis and the results of the application of the developed new method for deterministic factor analysis, called the averaged chain substitution method. After formulating the concept of the considered approach, all mathematical expressions used to create models containing up to four factor variables are presented and summarized. The scientific novelty of the study is in the obtained new equations for determining the individual factor influences by the method of averaged chain substitution and the method of analogy for five-factor additive or difference-multiplicative and for five-factor additive or difference-multifactor models with an additive or different part in the numerator of the factor model. The presented mathematical expressions accurately and unambiguously quantify the impact of individual factor influences for all types of factor models and thus significantly expand the applicability of the averaged chain substitution method in the theory and practice of financial-economic analysis. The proposed formalization and algorithmization of the evaluation process makes the method easy to apply by all economic and financial analysts for the purposes of deterministic factor analysis. The methodology was applied to perform a dynamic deterministic factor analysis of the total liquidity of Monbat AD and ELHIM-ISKRA AD for the period 2017–2021, based on the consolidated annual financial statements of the companies, available on the website of the Bulgarian Stock Exchange.

Green Bonds as A New Investment Tool For Sustainable Development In India

The present paper conceptualizes the meaning, need and importance of green bonds as an initiative towards investment tool and sustainable development in India. A green bond is a type of investment that provides financial support for particular projects related to sustainability issue of climate change and control. Indian Companies have incorporated investment in green bonds as a part of climate finance strategy. The ICMA issued principles of green bonds investment and voluntary process guidelines for issuing green bonds in 2021. The four principles are: use of proceeds, process for project evaluation and selection, management of proceeds and reporting. The SEBI has issued several rules for green bonds securities in India including disclosure requirements, monitoring and third-party review. The private bank of India i.e. Yes bank was the first issuer of green bonds in India in the year 2015. Indian green bond issuance has grasped a total of $21 billion as on February 2023. The scenario of green bond market in India for the year 2021 shows that the Utilities sector has more share of green bonds followed by corporates, Renewable Energy sector and Financials. The least share is with local government in India.

Practical evaluation and theoretical modeling of charging process for Lead Acid batteries in PV systems

Practical evaluation and theoretical modeling of charging process for Lead Acid batteries in PV systems

Late Positive Potential Elicited by Monetary Reward Feedback Predicts Changes of Disordered Eating From Age11 to Age 12 in Community-Dwelling Girls.

Early adolescence is marked by elevated psychopathology, including disrupted eating attitudes and behaviors. Reward processing is an identified mechanism in portending eating pathology, that is, aberrant reward responsivity may contribute to disrupted reward-seeking behaviors (e.g., food consuming). This literature has focused on adults or mid-to-late adolescents, with little work done on early adolescence. We examined the linkages between reward feedback processing, indexed by event-related potentials (ERPs), and changes of emerging disordered eating in community-dwelling early adolescents. At T1, 115 youths (66 girls, mean/SD age = 11.00/1.16 years) completed an EEG monetary reward Doors task. Youths completed the Eating Disorder Examination-Questionnaire Short at T1 and ~6 months (T2) and ~12 months (T3) after T1. In the ERP data, we isolated a reward positivity (RewP) and a late positive potential (LPP) via principal component analysis. We applied multilevel modeling to examine whether baseline ERPs interacted with Time in predicting disordered eating and whether these interactions varied by sex. We found a significant Time × LPP interaction in girls but not boys. Among girls, only those with a smaller LPP toward the losses (versus wins), which might reflect suboptimal evaluation and regulatory processes in undesired situations, showed increases in disordered eating from T1 to T3. We provided preliminary yet novel evidence concerning the prospective associations between reward processing and changes of disordered eating in early adolescents. Future studies along this line will be critical for understanding the early mechanisms of eating pathology, identifying youths at risk, and developing prevention strategies.

A quantitative analysis of the security of PoW-based blockchains

AbstractThis study analyzes the security implications of Proof-of-Work blockchains with respect to the stale block rate and the lack of a block verification process. The stale block rate is a crucial security metric that quantifies the proportion of rejected blocks in the blockchain network. The absence of a block verification process represents another critical security concern, as it permits the potential for invalid transactions within the network. In this article, we propose and implement a quantitative and analytical model to capture the primary operations of Proof-of-Work blockchains utilizing the Performance Evaluation Process Algebra. The proposed model can assist blockchain designers, architects, and analysts in achieving the ideal security level for blockchain systems by determining the proper network and consensus settings. We conduct extensive experiments to determine the sensitivity of security to four aspects: the number of active miners and their mining hash rates, the duration between blocks, the latency in block propagation, and the time required for block verification, all of which have been shown to influence the outcomes. We contribute to the findings of the existing research by conducting the first analysis of how the number of miners affects the frequency of stale block results, as well as how the delay in block propagation influences the incentives received by rational miners who choose to avoid the block verification process.

Semantic distance of icons: Impact on user cognitive performance and a new model for semantic distance classification

With the continuous development of human-computer interaction technologies and the widespread use of graphical interfaces, icons that represent various objects and functions have a particularly important role. This study investigates the effect of semantic distance of icons on cognitive performance through an eye-movement-based experiment which involves a visual search for icons. The findings show that the semantic distance of icons has a significant effect on cognitive performance. A higher cognitive performance is found with semantically close icons which can better capture user attention. In addition, we use eye-movement indicators that are highly correlated with semantic distance, including mean pupil diameter, mean gaze duration and initial gaze time of an AOI, and analyze the objective relationship between these three eye-movement indicators and the semantic distance of icons to establish a dataset. The dataset is used as input for a Gradient Boosting Decision Tree (GBDT), which is a machine learning-based method for classifying the semantic distance of the icons in this study. The output of the GBDT model is classifying the semantic distance as far and close, and the experimental results show that the accuracy of the model reaches 84.28% after a comparison with other types of classifiers, which is in good agreement with the experimental results. Therefore, the model can address the relevant application requirements and simplify the evaluation process of icons to a certain extent, which has great significance in the field of icon design.

Evaluating a model of best practice in primary care led post-diagnostic dementia care: feasibility and acceptability findings from the PriDem study

ObjectivesTo evaluate the feasibility and acceptability of a primary care-based intervention for improving post-diagnostic dementia care and support (PriDem), and implementation study procedures.DesignA non-randomised, mixed methods, feasibility study.SettingSeven general practices...

Proactive safety hazard identification using visual–text semantic similarity for construction safety management

Automated safety management in construction can reduce injuries by identifying hazardous postures, actions, and missing personal protective equipment (PPE). However, existing computer vision (CV) methods have limitations in connecting recognition results to text-based safety rules. To address this issue, this paper presents a multi-modal framework that bridges the gap between construction image monitoring and safety knowledge. The framework includes an image processing module that utilizes CV and dense image captioning techniques, and a text processing module that employs natural language processing for semantic similarity evaluation. Experiments showed a mean average precision of 49.6% in dense captioning and an F1 score of 74.3% in hazard identification. While the proposed framework demonstrates a promising multi-modal approach towards automated safety hazard identification and reasoning, improvements in dataset size and model performance are still needed to enhance its effectiveness in real-world applications.