bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measuring the Effects of Power System Reform in Jiangsu Province, China from the Perspective of Social Cost Benefit Analysis
Authors: Li Tianyu , Gao Ciwei , Pollitt Michael G. , Chen Tao , Ming Hao 
Published: November 2024

The paper uses a social cost benefit analysis (SCBA) approach to measure the effects of the power system reform starting from 2015 in Jiangsu province, China. We review the background of Jiangsu power system and summarize the implemented policies since the publication of “Document #9.” Then we pick the average industrial and commercial retail price and analyze the sources of price reductions. We show that the nominal industrial and commercial price fell by 21.3 percent between January 2012 and May 2021. We then analyze the likely overall welfare change facing industrial and commercial customers using SCBA and conclude that there is a permanent gain equivalent to 9.1% lower prices per year mainly because of the reform. This figure is a significantly more positive consumer gain than that calculated in previous SCBAs of electricity reform in other countries. JEL Classification: L94, Q48
Bonevoyage: Navigating the depths of osteoporosis detection with a dual-core ensemble of cascaded ShuffleNet and neural networks
Authors: Srinivasan Dhamodharan , Kiran Ajmeera , Parameswari S. , Vellaichamy Jeevanantham 
Published: November 2024

Background Osteoporosis (OP) is a condition that significantly decreases bone density and strength, often remaining undetected until the occurrence of a fracture. Timely identification of OP is essential for preventing fractures, reducing morbidity, and enhancing the quality of life. Objective This study aims to improve the accuracy, speed, and reliability of early-stage osteoporosis detection by integrating the compact architecture of Cascaded ShuffleNet with the pattern recognition prowess of Artificial Neural Networks (ANNs). Methods BoneVoyage leverages the efficiency of ShuffleNet and the analytical capabilities of ANNs to extract and analyze complex features from bone density scans. The framework was trained and validated on a comprehensive dataset containing thousands of bone density images, ensuring robustness across diverse cases. Results This model achieving an accuracy of 97.2%, with high sensitivity and specificity. These results significantly surpass those of existing OP detection methods, highlighting the effectiveness of the BoneVoyage framework in identifying subtle changes in bone density indicative of early-stage osteoporosis. Conclusions BoneVoyage represents a significant advancement in the early detection of osteoporosis, offering a reliable tool for healthcare providers to identify at-risk individuals prematurely. The early detection facilitated by BoneVoyage allows for the implementation of preventive measures and targeted treatments.
MRI classification and discrimination of spinal schwannoma and meningioma based on deep learning
Authors: Liu Yidan , Zhou Zhenhua , Wang Yuanjun 
Published: November 2024

Backgroud: Schwannoma (SCH) and meningiomas (MEN) are the two most common primary spinal cord tumors. Differentiating between them preoperatively remains a clinical challenge due to the substantial overlap in their clinical presentation and imaging characteristics. Objective: The objective of this study is to facilitate early diagnosis of patients and reduce clinician stress by constructing a deep learning-based classification model for automatic diagnosis of schwannoma and meningiomas using magnetic resonance images (MRI). Methods: We retrospectively collected MRI images of 74 patients with pathologically confirmed schwannoma and meningiomas from 2015 to 2020 at a local hosipital, and constructed a CNN model based on the PyTorch's deep learning framework for the discrimination between the two. First, a modified feature fusion CNN model (ResNet34-SKConv) was trained by introducing a selective convolutional kernel module into the original CNN model. The introduction of the selective convolutional kernel module enhances the network's focus on tumor features and effectively improves the network's performance. Finally, the trained model was used to process all the MRI image slices to achieve the classification of SCH and MEN patients by the voting prediction method. Results: Using the 5-fold cross-validation method, this new ResNet34-SKConv model achieves a classification accuracy of 92.32%, a specificity of 95.87%, and a F1-score of 93.54, respectively. Conclusion: This study demonstrated that a classification model using a deep learning network can be effective in achieving differential diagnosis of SCH and MEN. Thus, the new method has great potential for developing new computer-aided diagnosis and applications with future clinical practice.
Digital Coaching to Address Health, Wellness, and Burnout Among Healthcare Workers: Pilot Study Results
Authors: L’Engle Kelly , Trejo Evelin , Coutinho Anastasia J. 
Published: November 2024

Background: Healthcare worker (HCW) well-being is essential for safe, high-quality patient care, but clinicians and front-line staff continue to experience alarming rates of burnout. This pilot study evaluated a novel 6-week program of remote wellness coaching supported by daily digital messaging to reduce burnout and increase well-being among HCWs. Methods: In spring 2023, staff from a large community health center in California were invited to participate in this single-group pretest–posttest study in an academic-practice partnership. Thirty-four participants who were mostly female (91%), Latina (77%), 36 years old on average (range = 20–61), and represented all major job categories provided informed consent and completed the baseline survey. Of these, 17 completed 6 weekly 20-minute coaching sessions; received daily messages about stress management, self-care, workplace well-being, social connections, and lifestyle and health behaviors, and completed follow-up data collection. The Wilcoxon matched pair signed-rank tests assessed changes from baseline to 2-months follow-up. Results: Self-reported burnout decreased from 59% at baseline to 35% at follow-up. Work exhaustion ( p < .05), stress ( p < .05) and sleep problems ( p < .01) reduced significantly, and wellness practices ( p < .05), moderate physical activity ( p < .01), and healthy daily eating ( p < .05) improved. Conclusions/Applications to Practice: Our pilot study suggests that a brief digital wellness program may address burnout and increase health and well-being among front-line staff and clinicians. Healthcare settings should consider this type of program for their workers, especially given the added burden of COVID-19 on the healthcare system.
Orthostatic blood pressure reactions and resting heart rate in relation to lung function - the Swedish CArdioPulmonary bioImage Study (SCAPIS)
Authors: Casselbrant Andreas , Zambach Christian , Fedorowski Artur , Engström Gunnar , Wollmer Per , Hamrefors Viktor 
Published: November 2024

Abstract
Background
There is a well-known comorbidity between chronic obstructive pulmonary disease (COPD) and coronary artery disease (CAD) which is only partially explained by common risk factors. Markers of cardiovascular autonomic dysfunction (CVAD), such as orthostatic hypotension and increased resting heart rate, are strongly associated with CAD. The autonomic nervous system also innervates the airways, and several studies have shown an association between autonomic dysfunction and COPD. However, less is known about whether CVAD and impairment of respiratory capacity are related in the population. We thus aimed to assess the relationship between markers of subtle CVAD and lung function in middle-aged subjects.

Methods
In this cross-sectional study, we analysed data from CVAD assessment (orthostatic blood pressure and heart rate measurements) and pulmonary function tests from 5886 individuals from the Swedish CArdioPulmonary bioImage Study (SCAPIS). Subjects were middle aged and randomly selected from the Swedish population. Linear regression models and ANOVA analyses were used to relate orthostatic blood pressure and resting heart rate to lung function parameters (forced vital capacity (FVC), forced expiratory volume in one second (FEV1), FEV1/FVC-ratio, diffusion capacity for carbon monoxide (DLCO), respiratory resistance at 5 Hz (R5), respiratory resistance at 20 Hz (R20), decrease in resistance from R5 to R20 (R5-R20), reactance in distal airways (X5), resonant frequency (Fres) and reactance area (AX)).

Results
Increasing systolic orthostatic blood pressure, decreasing diastolic orthostatic blood pressure, and increased resting heart rate associated with lower FVC (all p < 0.001) and FEV1 (p = 0.001; p = 0.005; p < 0.001, respectively) in models including age, sex and height. Apart from diastolic orthostatic blood pressure and FEV1, all relationships remained significant after adjustment for possible confounders. Increased resting heart rate was associated with reduced DLCO (p < 0.001).

Conclusions
Increasing systolic orthostatic blood pressure, decreasing diastolic orthostatic blood pressure, and increased resting heart rate are associated with lower lung function, after adjustments for age, sex and height. These finding indicates associations between signs of cardiovascular autonomic dysfunction and lower lung function in the general population. However, the observed differences in lung function were small and the clinical application is unclear.
Control of hyperhydricity of Pistacia khinjuk stocks in vitro shoots
Authors: Ersali Yusuf 
Published: November 2024

AbstractHyperhydricity is the most extensive physiological disorder during in vitro propagation. This disturbance can induce anatomical, morphological and physiological problems that cause serious damage. The factors that cause hyperhydricity are the composition of nutrient media and cultures conditions. To reduce the hyperhydricity of Pistacia khinjuk, ammonium nitrate (NH4NO3), calcium chloride (CaCl2·2H2O), cytokinins of meta-topolin (mT) and 6-benzylaminopurine (BAP) at different concentrations were investigated in Murashige and Skoog (MS) medium. The lowest percentage of hyperhydricity (34.30%) were obtained from the medium containing 1650 mg/L NH4NO3, 110 mg/L CaCl2·2H2O and1 mg/L mT; the highest percentage of hyperhydricity (68.42%) were obtained from the medium containing 206.25 mg/L NH4NO3, 440 mg/L CaCl2·2H2O and 0.5 mg/L BAP. The maximum average number of shoots per explant (2.45), average shoots length (18.47 mm) and proliferation rate (85%) were obtained from the medium containing 1650 mg/L NH4NO3, 110 mg/L CaCl2·2H2O of MS and 1 mg/L mT. In addition, when soluble protein (2.12 mg/g) and total chlorophyll a, b (0.96 mg/g) value of normal (non-hyperhydric) shoots were higher than hyperhydric shoots, carotenoid (11.75 µg /g) and water content (78.70%) value of normal shoots were lower than hyperhydric shoots. This study concludes that the hyperhydricity percentage of in vitro P. khinjuk shoots was reduced (12.8%) on modified MS medium with NH4NO3, CaCl2·2H2O and mT according to standard MS medium.
A novel blended and interprofessional approach to pediatric emergency training: self-assessment, perception, and perceived long-term effects
Authors: Lehmann Ronny , Klinke Petrowsky Michaela , Seitz Anke , Meyburg Jochen , Eppich Walter , Hoffmann Georg F. , Tönshoff Burkhard , Huwendiek Sören 
Published: November 2024

Abstract
Background
We developed a blended training program at a tertiary pediatric center based on hospital-specific emergency guidelines, profession-specific Virtual Patients (VPs), and interprofessional team training. Using this novel approach, we addressed differing educational needs of medical and nursing staff and intrinsic cognitive overload among participants, aiming for harmonization of in-house emergency proceedings.

Methods
Self-assessments of pediatric emergency knowledge and skills were conducted before (T1) and after (T2) preparation using VPs, as well as after the team training day (T3). At T3, participants completed questionnaires on the training approach, its components, and learning impact. Ten months after the training, a follow-up survey (T4) queried perceived benefits within and beyond emergency situations.

Results
A total of 56 medical staff and 56 nursing staff members participated in the pilot phase. Of these, N = 55 (98%) and N = 48 (85%), respectively, returned self-assessments; questionnaires were completed by N = 55 (98%) and N = 51 (91%), respectively. In both groups, 57 participants (50.9%) completed the follow-up survey. After team training (T3), both groups had statistically significant increased knowledge and skill scores compared with those at T1. Regarding the blended approach and its components, medical and nursing staff alike rated the entire course and its guidelines, the preparatory VPs, and the team training very highly. Participants felt being better prepared for pediatric emergencies. Perceived strengths of the training approach were in the triangulation of teaching methods and its interprofessionalism. More training scenarios were requested, as well as recurrent training. In the follow-up, participants reported improved confidence and calmness, as well as improved communication and collaboration when involved in an emergency. Beyond emergencies, benefits were reported in daily routines.

Conclusions
Our blended approach was perceived as being effective in improving preparedness among medical and nursing house staff. This approach permits customization of content and deliberate practice to improve pediatric critical care.
Perception, concerns, and practice of ChatGPT among Egyptian pharmacists: a cross-sectional study in Egypt
Authors: Taha Taha Abd-ElSalam Ashraf , Abdel-Qader Derar H. , Alamiry Kareem R. , Fadl Zeyad A. , Alrawi Aya , Abdelsattar Nada K. 
Published: November 2024

Abstract
Background
The emergence of large language models (LLMs) like ChatGPT attracted significant attention for their potential to revolutionize pharmacy practice. While artificial intelligence (AI) offers promising benefits, its integration also presents unique challenges.

Objectives
This cross-sectional study aimed to explore the current Egyptian pharmacists’ perceptions, practices, and concerns regarding ChatGPT in pharmacy practice.

Methods
The study questionnaire was shared with pharmacists during March and April 2024. We included pharmacists licensed by the Egyptian Ministry of Health and Population. We adapted a convenient sampling technique by sending the research questionnaire via emails, student networks, social media (Facebook and WhatsApp), and student organizations. Any pharmacist interested in participating followed a link to review the study description and was asked to provide electronic consent before continuing with the study. Data were analyzed using SPSS software, employing Chi-square tests for categorical variables and Spearman’s correlation for continuous variables. Statistical significance was set at p < 0.05.

Results
The study sample size included 428 pharmacists from the main economic regions of Egypt. The results revealed a strong recognition (73.6%) among participants of ChatGPT’s anticipated benefits within pharmacy practice. Around two-thirds of the participants (65.9%) expressed disagreement or neutrality regarding the application of ChatGPT for analyzing patients’ medical inputs and providing individualized medical advice. Regarding factors affecting perception, we found that the region is the only factor that significantly contributed to the level of perception among pharmacists (P = 0.011) with Greater cairo region showing the highest perception level. We found that 73.6% of participants who have heard about ChatGPT reported high levels of concern. One-third of participants never use ChatGPT in their pharmacy work, and 20% rarely use it. Using Spearman’s correlation test, there was no significant correlation between anticipated advantages, concerns and practice level (P > 0.05).

Conclusion
This study reveals a generally positive perception of ChatGPT’s potential benefits among Egyptian pharmacists, despite existing concerns regarding accuracy, data privacy, and bias. Notably, no significant associations were found between demographic factors and pharmacists’ perceptions, practices, or concerns. This underscores the need for comprehensive educational initiatives to promote informed and responsible ChatGPT utilization within pharmacy practice. Future research should explore the development and implementation of tailored training programs and guidelines to ensure the safe and effective integration of ChatGPT into pharmacy workflows for optimal patient care.
Individual and unit level insights from hospital staff ratings on structural empowerment, leadership-management performance, well-being, and quality of care
Authors: Lundin Karin , Engström Maria , Skytt Bernice , Strömberg Annika , Silén Marit 
Published: November 2024

Abstract
Background
Leadership and access to structural empowerment are known to influence the work life experiences of staff and quality of care. Knowledge about relationships between specific factors of structural empowerment, leadership and management, staff well-being and quality of care at both an individual and unit level is scarce.

Aim
To study the relationship between staff-rated access to empowering structures, leadership and management performance, well-being, and quality of care in hospital settings measured at the individual level and aggregated at the unit level.

Methods
A cross-sectional correlative design was applied. Questionnaire data from 331 randomized hospital nursing staff working at 38 units in 25 hospitals in Sweden were analyzed using bivariate correlations and general estimation equation (GEE) models.

Results
Results from the bivariate analysis of relationships confirmed earlier research. In the GEE models, some unexpected results were found and differences between the individual and unit levels. Adding management and leadership as independent factors in the second model showed few relationships of significance to the outcome variables.

Conclusion
Results confirm the importance of staff access to empowering structures in relation to well-being and quality of care. Differences and similarities were shown when studying these relationships at both the individual and unit level. The findings feature implications for hospital management to promote staff access to empowering structures. The findings provide information on how these structures relate to the individual and the unit; information that could be useful when planning or implementing strategies with the aim to promote staff well-being and care quality. The non-significant results for leadership and management in relation to staff outcomes in the GEE-models, raise questions for further research where a shift from individual to organizational focused performances within the field of leadership is implied.
Retention in primary care among unstably housed residents of a low-income, inner-city neighborhood with a high prevalence of substance use and related disorders
Authors: Gumprich M. , Zhang W. , Li J. , Salters K. , Barrios R. , Sereda P. , Stanley C. , Joe R. , Hall D. , Lima V. , Sincraian G. , Changir A. Marante , Parry R. , Fulton C. , Wesseling T. , Montaner J. , Parashar S. , Moore David M. 
Published: November 2024

Abstract
Introduction
Access to and engagement with primary healthcare can be difficult for marginalized low-income populations residing in inner cities in high-income countries. We designed a study to examine retention in primary care among clients of a novel interdisciplinary primary care clinic in the Downtown Eastside of Vancouver, Canada who did not previously have access to care.

Methods
Beginning in June 2021, clients of the Hope to Health clinic were offered enrolment in a cohort study which involved a baseline and follow-up surveys every six months, and linking their data to information from the clinic’s electronic medical records. We used Chi-square or Fisher’s Exact test and Wilcoxon rank sum test to compare clients who were lost to follow-up (LTFU) or deceased, with clients who were retained in care at the end of follow-up, Cox proportional hazards modeling was used to examine independent associations with mortality or LTFU.

Results
Among 425 participants enrolled, the median age was 50 years (IQR 40–59), 286 (67.3%) participants were men and 128 (25.4%) were unstably housed at enrollment. Among 338 participants with at least six months of follow-up after enrolment, 262 participants (67.5%) were retained in care, 20 (5.2%) had moved, 57 (14.7%) were classified as LTFU, and 28 (7.2%) had died with a median of 19.9 months of follow-up time. The risk of death or LTFU was independently associated diagnosed with alcohol use disorder (AUD) (adjusted hazard ratio [AHR] = 2.23 vs. not; 1.38–3.60), frequency of medical doctor visits (AHR = 0.69 per visit per 3 months; 0.60–0.79) and social work visits (AHR = 0.73 per visit per 3 months; 0.59–0.90. Stimulant use disorder or asthma were not significantly associated with retention in care.

Conclusion
We found that a primary healthcare model of care was successful in retaining over two-thirds of clients in primary healthcare after more than 18 months of follow-up. Additional supports for those diagnosed with alcohol use disorder are needed to retain them in care.
Development of the 10-question household foodwork interactional assessment questionnaire (FIA-Q10)
Authors: Cahill Leah E. , Kirkpatrick Sharon I. , Mah Catherine L. , Protudjer Jennifer LP. , Kendell Cynthia , Jung Mary E. , Wong Helen , Crumley Ellen T. , Day Meghan , Tang Karen T. Y. , Huang Yan , Sihag Jyoti , Brady Laura , Tennankore Karthik K , Tangri Navdeep , Mollard Rebecca C. , MacKay Dylan 
Published: November 2024

Abstract
Background
Public health nutrition recommendations and clinical dietary interventions emphasize eating healthy food at home, implicitly requiring household foodwork. Household foodwork is defined as the physical and mental tasks a household does for eating meals and snacks. Because no tools exist to measure it, how much time people spend doing household foodwork and the foodwork barriers they experience remain unknown. The objective of the present research was to develop the first stand-alone household foodwork assessment tool.

Methods
Through informal interviews with partners with lived experience, clinicians, and researchers, a literature review, a stakeholder meeting of advisors, and a two-round electronic Delphi process including face/content validation by expert panelists (n = 21), we developed the 10-question household foodwork interactional assessment questionnaire (FIA-Q10). An optional accompanying module was developed to collect self-identified demographic data to provide context for understanding how social-structural positionality factors may interact to influence foodwork.

Results
The FIA-Q10 assesses the domains of household composition, frequency of eating at home, special diets within a household, foodwork stress intensity, foodwork barriers, desired supports related to foodwork, and time use for foodwork. The FIA-Q10 measures time use for four subdomains of foodwork among individuals and their households: (1) planning, (2) getting, (3) preparing/cooking, and (4) cleaning up food. In the second Delphi round, the FIA-Q10 scored 95% for language appropriateness, 67% for visual appropriateness, 95% for relevance, 95% for representativeness, and 95% for distribution. Suggested improvements were implemented. All Delphi panelists (100%) reported they would consider using the FIA-Q10.

Conclusions
The FIA-Q10’s development is the first step towards a standardized assessment of foodwork, enabling examination of challenges in foodwork that may impact nutrition and nutrition equity. Future research will focus on FIA-Q10 validation in multiple populations.