Limited Body Research Articles

A Strike from the Air: Cerebral Hemorrhage after a Lightning Strike

AbstractLightning strikes pose a rare but catastrophic risk for a variety of injuries, including damage to the central nervous system. We present the case of a 79-year-old farmer who survived a lightning strike directly in the chest resulting in an intracerebral hemorrhage in the region of the left basal ganglia. The patient was initially comatose with right-sided paralysis and central facial palsy but displayed gradual improvement with supportive medical therapy. This unique case highlights the potential for lightning strikes to cause rare and severe neurological complications, including intracerebral hemorrhage. A review of the literature proposes possible pathophysiology of lightning-induced intracerebral hemorrhage, but the exact mechanism is yet to be found. Early diagnosis, classification, and treatment of neurological symptoms are crucial for optimal patient outcomes following lightning strikes. This case report adds valuable information to the limited body of literature on lightning strike-induced central nervous system injuries, emphasizing the importance of prompt medical intervention and multidisciplinary care for lightning strike survivors. Further research is needed to better understand the mechanisms underlying lightning-induced intracerebral hemorrhage and to develop optimal treatment strategies for these rare but potentially devastating events.

A Case Report of Mixed Connective Tissue Disease Predominantly Manifesting as Systemic Sclerosis in a Middle-Aged Nepali Woman

Introduction: Mixed connective tissue disease (MCTD) is a rare systemic autoimmune disorder, first described in 1972, that presents with overlapping features of systemic lupus erythematosus, systemic sclerosis, and polymyositis. The diagnosis of MCTD is complex and often delayed due to its varied clinical manifestations and the requirement of serological confirmation, particularly the presence of anti-U1 RNP antibodies. Despite its global prevalence, data on MCTD are limited, especially in the South Asian population.  Case Report: We present the case of a 42-year-old Nepali woman with a decade-long history of myalgia, muscle weakness, and joint pain, initially misdiagnosed as rheumatoid arthritis. Over time, she developed Raynaud phenomenon, dysphagia, and progressive muscle weakness, which prompted further investigation. Serological testing revealed elevated levels of anti-U1 RNP antibodies and a positive antinuclear antibody (ANA) titer, confirming the diagnosis of MCTD according to the Alarcón-Segovia criteria. The patient was successfully managed with a regimen of corticosteroids, hydroxychloroquine, and nifedipine, resulting in significant symptomatic improvement.  Discussion: This case underscores the diagnostic challenges associated with MCTD, a condition that may present with nonspecific symptoms and mimic other rheumatic diseases. The prolonged diagnostic journey of this patient highlights the need for heightened clinical suspicion and comprehensive serological testing in patients with overlapping connective tissue disease features. Furthermore, the case contributes to the limited body of literature on MCTD in the South Asian population, emphasizing the importance of early recognition and tailored management strategies to improve patient outcomes.  Conclusion: MCTD is a complex and under-recognized autoimmune disorder, particularly in the South Asian context. This case report highlights the importance of considering MCTD in the differential diagnosis of patients with multi-systemic involvement and underscores the role of serological testing in confirming the diagnosis. Early diagnosis and appropriate management are crucial in mitigating disease progression and improving the quality of life for patients with MCTD.

The Effect of Photobiomodulation on Third Molar Wound Recovery: A Systematic Review with Meta-Analysis.

Objectives: This study addresses the limited body of literature concerning the impact of photobiomodulation on complications following mandibular third molar extractions. Methods: A systematic literature review and meta-analysis of clinical studies that reported the use of photobiomodulation after mandibular third molar surgery was conducted based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. The formulation of research questions followed the PICO model, and comprehensive strategies for record search and study selection were devised. The protocol was registered on PROSPERO (The Prospective Register of Systematic Reviews; no CRD42024511892). Two independent reviewers consulted four databases during the literature search: MEDLINE/PubMed, Google Scholar, Clinicaltrial.gov, and Cochrane Library databases without imposing any date restrictions. A search on the grey literature was carried out too (OpenGrey). Duplicate articles were eliminated. Results: After the initial screening, 18 studies were retained to be screened by the reviewers. The full texts of the identified studies were scrutinized for original data, and their related references were manually retrieved and checked for additional relevant studies. The available studies exhibit considerable heterogeneity, exploring various factors related to postoperative outcomes. Our meta-analysis primarily focuses on three key aspects: the incidence of alveolar osteitis (AO), mucosa repair/alveolar pocket healing, and bone repair. The resultant CI of the VAS scale was 98 to 99%. Conclusions: This meta-analysis underscores the need for further research in this domain, highlighting the existing heterogeneity among studies and the importance of a nuanced understanding of photobiomodulation's multifaceted effects on postoperative complications.

Immersive Photorealistic Three-Dimensional Neurosurgical Anatomy of the Cerebral Arteries: A Photogrammetry-Based Anatomic Study.

Neurosurgeons need a profound knowledge of the surgical anatomy of the cerebral arteries to safely treat patients. This is a challenge because of numerous branches, segments, and tortuosity of the main blood vessels that supply the brain. The objective of this study was to create high-quality three-dimensional (3D) anatomic photorealistic models based on dissections of the brain arterial anatomy and to incorporate this data into a virtual reality (VR) environment. Two formaldehyde-fixed heads were used. The vessels were injected with radiopaque material and colored silicone and latex. Before the dissections, the specimens were computed tomography scanned. Stratigraphical anatomic dissection of the neck and brain was performed to present the relevant vascular anatomy. A simplified surface scanning method using a mobile phone-based photogrammetry application was used, and the data were incorporated into a VR 3D modeling software for post-processing and presentation. Fifteen detailed layered photorealistic and two computed tomography angiography-based 3D models were generated. The models allow manipulation in VR environment with sufficient photographic detail to present the structures of interest. Topographical relevant anatomic structures and landmarks were annotated and uploaded for web-viewing and in VR. Despite that the VR application is a dedicated 3D modeling platform, it provided all necessary tools to be suitable for self-VR study and multiplayer scenarios with several participants in one immersive environment. Cerebral vascular anatomy presented with photogrammetry surface scanning method allows sufficient detail to present individual vessel's course and even small perforating arteries in photorealistic 3D models. These features, including VR visualization, provide new teaching prospects. The whole study was done with simplified algorithms and free or open-source software platforms allowing creation of 3D databases especially useful in cases with limited body donor-based dissection training availability.

The Amfioen Societëit (1745–1794): Opium, intra-Asian trade and the commercial world of Batavia in the eighteenth century

This article analyses the emergence of the Amfioen Societëit (1745–1794) and its impact on the market for opium in eighteenth-century Java. It engages with a limited body of historiography to challenge assumptions that the Societëit was a wholly colonial institution designed to serve an elite – namely, European – set of interests. In reassessing how the Societëit worked in theory and in practice, it is argued that this institution was born from the necessary collaborative engagement of a European and a local commercial class with different but vested interests in the opium trade. Moreover, the article situates the Societëit among other finance institutions that existed in eighteenth-century Java to serve the credit needs of the local commercial milieu. In doing so, it lays the foundations for a deeper and more nuanced history of the opium trade and the local economy of early modern Java in a period about which very little is known.

Social Media Use: A Cognitive Dissonance Analysis of Heavy Users and Engagement Dynamics

Abstract Purpose – This research investigates the correlation between the utilization of social networking sites, user engagement, and cognitive dissonance. It explores the mediating influence of e-compulsive buying behavior (ECBB) in the connection between SNS use, user engagement, and cognitive dissonance, while also examining the moderating impact of self-esteem on SNS use, user engagement, and ECBB. Methodology – Utilizing purposive sampling, this study collected cross-sectional data from 232 female participants actively engaged in social networking sites (SNSs) and who had made 4-5 online purchases during the last six months. Data were gathered through an electronically administered questionnaire. Descriptive data analysis was conducted using SPSS version 21, while SmartPLS version 4.0 was employed to test the proposed hypotheses. Findings – The findings indicate a significant association between the utilization of social networking sites (SNSs) and user engagement with cognitive dissonance and ECBB. Additionally, it was observed that self-esteem played a moderating role in the relationship between SNS use, user engagement, ECBB, and cognitive dissonance, revealing a heightened impact of cognitive dissonance at lower levels of self-esteem. Practical Implications – These results carry implications for implementing interventions aimed at mitigating the adverse consequences associated with social networking site (SNSs) use, thereby fostering favorable mental health outcomes within the community. Moreover, this study offers valuable insights for managers seeking to enhance their social media strategies by analyzing the varied impacts of social media content and understanding the dynamics between posts to engage both active and passive users effectively. Originality/Value – This study contributes to the limited body of empirical research by examining the correlation between social networking site (SNSs) use, user engagement, and cognitive dissonance through the lens of ECBB. Additionally, in response to recent calls from various empirical studies in this field, the inclusion of self-esteem as a moderating variable predicting cognitive dissonance enhances the novelty of this research.

GENDERED RESILIENCE: ISLAMIC LEGAL MAXIMS AND PANDEMIC RESPONSES AMID INDONESIA’S ENVIRONMENTAL AND SOCIETAL CHALLENGES

Objective: This study aims to explore the intersection of gendered resilience, Islamic legal maxims, and pandemic responses within the context of Indonesia's environmental and societal challenges. It seeks to understand how Islamic jurisprudence and gender dynamics can shape effective responses to crises, particularly in a nation grappling with diverse socio-environmental issues. Theoretical Framework: The research is grounded in the theoretical framework of gender studies and Islamic legal theory. It employs a gender-sensitive lens to examine how Islamic legal principles (maqasid al-sharia) can be applied to foster resilience amidst crises. The study also incorporates environmental sociology to contextualize the socio-ecological challenges faced by Indonesia. Method: Through qualitative methods, including content analysis of religious, legal texts, and case studies, the research examines practical applications of Islamic legal principles in crisis response. Results and Discussion: Findings reveal that gender-sensitive interpretations of Islamic legal maxims improve community resilience and pandemic responses by fostering equitable resource distribution. The study highlights successful case studies and discusses integration challenges in policymaking. Research Implications: Integrating gender perspectives into Islamic legal frameworks can enhance policy and resilience strategies, offering a model for similar contexts in Muslim-majority countries. Originality/Value: This study contributes to the limited body of literature on the nexus of gender, religion, and crisis management in Indonesia. It offers a novel perspective by integrating Islamic legal theory with gender studies, providing valuable insights for scholars, and practitioners aiming to enhance resilience through culturally relevant frameworks.

The outcome of haematopoietic stem cell transplantation in a patient with STAT1 gain-of-function: a case report

Background: The human signal transducer and activator of transcription 1 (STAT1) is a latent cytoplasmic transcription factor and one of seven members of the STAT family. Autosomal dominant (AD) STAT1 gain-of-function (GOF), characterized by enhanced phosphorylation of the tyrosine-701 residue and STAT1 activation, is commonly associated with chronic mucocutaneous candidiasis (CMCC), immunodeficiency, aneurysms, malignancies, and autoimmune phenomena. The best management strategies for patients with STAT1 GOF remain unclear. Typically, the standard care includes supportive treatments such as antimicrobial prophylaxis, either alone or combined with immunoglobulin replacement therapy. Biological therapies such as JAK inhibitors have been shown to alleviate symptoms of infection and autoimmune disorders in patients with STAT1 GOF mutations. However, there is a lack of long-term outcome data for JAK inhibition. Hematopoietic stem cell transplantation (HSCT) is an alternative treatment option for a subset who experience a persistent disease course despite conventional therapy. However, the effectiveness of HSCT for this condition is not yet well established. Methods: Our patient’s medical records were analyzed retrospectively, including her medical history. Results: We present the outcome of HSCT performed on a 27-year-old female with STAT1 GOF, conducted as a treatment for acute myeloid leukemia (AML). Conclusion: HSCT may serve as an alternative and potentially curative treatment for certain STAT1 GOF patients with progressive, life-threatening conditions that do not respond to conventional therapies. Additional research is needed to improve the management of these patients. Statement of Novelty: We present a novel case study of HSCT as a treatment for AML in a 27-year-old patient with STAT1 GOF, highlighting the potential for curative outcomes in progressive, life-threatening conditions unresponsive to conventional therapies. This case contributes to the limited body of evidence supporting the efficacy and challenges of HSCT in STAT1 GOF patients.

Total knee replacement with an accelerometer-based, hand-held navigation system improves knee alignment: reliable in all patients.

Achieving adequate alignment has traditionally been an important goal in total knee arthroplasty to achieve long-term implant survival. While accelerometer-based hand-held navigation systems (ABN) has been introduced as a way to achieve alignment, there is a limited body of evidence on its accuracy, especially in patients under 65 years with differing etiologies for knee arthritis. This study aimed to assess the precision of a specific ABN system in restoring the mechanical axis and report surgical variables and complications, with particular attention to younger patients. We conducted a retrospective review of 310 primary TKA performed with ABN from May 2016 to February 2021. The mean patient age was 67.4 (SD 8.9) years, with 43% under 65 years and mean body mass index of 33.2 (SD 6.8). The average surgical time was 96.8min (57-171) and the average follow-up was 3.3 years (1.9-6.7). Data regarding length of stay, pain, range of motion (ROM), complications, and reinterventions were collected from the institutional joint arthroplasty registry and the medical records. Preoperative mechanical axis measurements and postoperative radiological data, including mechanical axis, component alignment and mechanical alignment outliers were analyzed. The mean preoperative mechanical axis was 175.4° (SD 7.6), with 248 knees (80%) in preoperative varus. The mean postoperative mechanical axis was 179.5° (SD 1.96) with 98% of knees falling within ± 3° of the neutral mechanical axis. Only 6 knees (2 varus, 4 valgus) fell outside the ± 3° range. And 3 knees (1 varus, 2 valgus) fell outside the ± 5° range. In the sagittal plane, 296 knees (95.5%) knees were within ± 3° of goal of 3 degrees of femoral flexion and 302 (97.4%) knees were within ± 2° of goal 1° of slope for tibial component. Far outliers (alignment outside ± 5° of targeted position) were found in 3 knees. Factors such as posttraumatic arthrosis, previous surgery, presence of retained hardware, and age below 65 years were not associated with increase in alignment outliers and far outliers. No complications related to the navigation system were observed. There were 22 complications and 20 reoperations, including 2 revisions for periprosthetic joint infection and 1 revision for flexion instability. Patients that required knee manipulation achieved an ultimate flexion of 110° (SD 14.1). The ABN system proved to be user-friendly and accurate in reducing alignment outliers in both coronal and sagittal planes in all patient populations. It offers a straightforward navigation solution while preserving surgeon autonomy and the use of traditional surgical tools. These findings advocate for the integration of this navigation system as a valuable tool to enhance the precision of TKA surgery in all patient groups.

Pedestrian behavior among Chinese seniors: Insights from factor analysis and structural equation modeling

Pedestrians contribute significantly to the total number of road fatalities and injuries, with their behavior playing a pivotal role in traffic mishaps. Despite this, a limited body of research has delved into the walking behaviors of Chinese seniors. Given this gap, our study rigorously examines the patterns of seniors’ walking behaviors and their influencing factors. We employed exploratory factor analysis to decipher the intrinsic component structures of seniors' walking patterns in China. Subsequently, structural equation modeling was utilized to analyze the impact of demographic attributes and personality characteristics on these behaviors. The findings revealed a four-dimensional structure for senior walking behaviors: transgression, inattention, aggression, and positive behaviors. Introducing personality traits as variables notably enhanced the explanatory power of our model. Specifically, anger, altruism, and normlessness significantly influenced certain dimensions of walking behaviors, while sensation-seeking did not exhibit any notable effect. This study not only highlights the complexity and diversity of elderly walking behaviors but also underscores the importance of tailored interventions to improve walking safety and quality of life for seniors.

Innovation Off the Bat: Bridging the ChatGPT Gap in Digital Competence among English as a Foreign Language Teachers

This research explores the guided experimental implementation of ChatGPT as a tool for developing teachers’ skills in teaching English. The intervention involved 24 in-service English as a Foreign Language (EFL) teachers who engaged in crafting activities and assessments using researcher-designed prompts. Utilizing a mixed-methods approach, the researchers assessed the participants’ ChatGPT integration proficiency through a custom-designed assessment tool aligned with the technological pedagogical content knowledge framework. The eight-week intervention introduced educators to various applications of ChatGPT in EFL teaching, including lesson planning. A quantitative analysis revealed statistically significant improvements in the teachers’ ChatGPT integration proficiency across all measured dimensions. The qualitative findings highlight the perceived benefits, challenges, and future prospects of ChatGPT in EFL education. While the practical significance of the improvement was modest, the results suggest that the guided integration of generative chatbots can bolster teachers’ ability to leverage this technology appropriately. This study contributes to the limited body of empirical research on integrating large language models into teaching and offers insights into the practical applications and challenges of using ChatGPT in EFL contexts.

Transforming Hospitality with Virtual Reality

The hospitality industry plays a crucial role in promoting sustainable community resilience. However, the potential of Virtual Reality (VR) technology to enhance this resilience within the hospitality sector remains underexplored. This study aims to bridge this research gap by investigating the applications of VR in the hospitality industry and its impact on sustainable community resilience. A qualitative methodology was employed, involving in-depth interviews with hospitality industry professionals and technology experts. Thematic analysis techniques were applied to analyze the data and identify key themes.The findings reveal that VR implementation in the hospitality sector has significant potential to enhance guest experiences, operational efficiency, and employee training. Notably, the study highlights VR's capacity to serve as a platform for promoting sustainable and inclusive tourism, thereby fostering community resilience. Furthermore, VR can be utilized to develop comprehensive training programs for individuals with specific needs, enhancing accessibility and inclusivity within the hospitality industry. This research underscores the importance of adopting VR technology in the hospitality sector to strengthen sustainable community resilience. The findings provide valuable insights for stakeholders in the hospitality and tourism industry to develop innovative and sustainable strategies. By addressing the research gap, this study contributes to the limited body of knowledge on VR's role in promoting sustainable community resilience within the hospitality context.

The AP-2 Family of Transcription Factors-Still Undervalued Regulators in Gastroenterological Disorders.

Activating enhancer-binding protein 2 (AP-2) is a family of transcription factors (TFs) that play crucial roles in regulating embryonic and oncogenic development. In addition to splice isoforms, five major family members encoded by the TFAP2A/B/C/D/E genes have been identified in humans, i.e., AP-2α/β/γ/δ/ε. In general, the first three TFs have been studied more thoroughly than AP-2δ or AP-2ε. Currently, there is a relatively limited body of literature focusing on the AP-2 family in the context of gastroenterological research, and a comprehensive overview of the existing knowledge and recommendations for further research directions is lacking. Herein, we have collected available gastroenterological data on AP-2 TFs, discussed the latest medical applications of each family member, and proposed potential future directions. Research on AP-2 in gastrointestinal tumors has predominantly been focused on the two best-described family members, AP-2α and AP-2γ. Surprisingly, research in the past decade has highlighted the importance of AP-2ε in the drug resistance of gastric cancer (GC) and colorectal cancer (CRC). While numerous questions about gastroenterological disorders await elucidation, the available data undoubtedly open avenues for anti-cancer targeted therapy and overcoming chemotherapy resistance. In addition to gastrointestinal cancers, AP-2 family members (primarily AP-2β and marginally AP-2γ) have been associated with other health issues such as obesity, type 2 diabetes, liver dysfunction, and pseudo-obstruction. On the other hand, AP-2δ has been poorly investigated in gastroenterological disorders, necessitating further research to delineate its role. In conclusion, despite the limited attention given to AP-2 in gastroenterology research, pivotal functions of these transcription factors have started to emerge and warrant further exploration in the future.

What has brain diffusion magnetic resonance imaging taught us about chronic primary pain: a narrative review.

Chronic pain is a pervasive and debilitating condition with increasing implications for public health, affecting millions of individuals worldwide. Despite its high prevalence, the underlying neural mechanisms and pathophysiology remain only partly understood. Since its introduction 35 years ago, brain diffusion magnetic resonance imaging (MRI) has emerged as a powerful tool to investigate changes in white matter microstructure and connectivity associated with chronic pain. This review synthesizes findings from 58 articles that constitute the current research landscape, covering methods and key discoveries. We discuss the evidence supporting the role of altered white matter microstructure and connectivity in chronic primary pain conditions, highlighting the importance of studying multiple chronic pain syndromes to identify common neurobiological pathways. We also explore the prospective clinical utility of diffusion MRI, such as its role in identifying diagnostic, prognostic, and therapeutic biomarkers. Furthermore, we address shortcomings and challenges associated with brain diffusion MRI in chronic primary pain studies, emphasizing the need for the harmonization of data acquisition and analysis methods. We conclude by highlighting emerging approaches and prospective avenues in the field that may provide new insights into the pathophysiology of chronic pain and potential new therapeutic targets. Because of the limited current body of research and unidentified targeted therapeutic strategies, we are forced to conclude that further research is required. However, we believe that brain diffusion MRI presents a promising opportunity for enhancing our understanding of chronic pain and improving clinical outcomes.

Nicotinamide N-methyltransferase inhibition mitigates obesity-related metabolic dysfunction.

To assess the effects of a small-molecule nicotinamide N-methyltransferase (NNMT) inhibitor, 5A1MQ, on body composition, metabolic variables, fatty liver pathologies, and circulating biomarkers in diet-induced obese (DIO) mice, and characterize its plasma pharmacokinetics (PK) and tissue distribution in vivo. DIO mice were administered vehicle or 5A1MQ once daily for 28 days. Longitudinal measures of body composition, blood glucose and plasma insulin levels, and terminal measures of liver histopathology and serum markers, were evaluated. Plasma and tissue PK were established in age- and strain-matched mice after intravenous, oral, and subcutaneous dosing of 5A1MQ. 5A1MQ treatment dose-dependently limited body weight and fat mass gains, improved oral glucose tolerance and insulin sensitivity, and suppressed hyperinsulinaemia in DIO mice. Liver histology from 5A1MQ-treated DIO mice showed attenuated hepatic steatosis and macrophage infiltration, and correspondingly reduced liver weight, size, and triglyceride levels. 5A1MQ treatment normalized circulating levels of alanine transaminase, aspartate transaminase, and ketone bodies, supporting an overall improvement in liver and metabolic functions. The pharmacodynamic effects of 5A1MQ were further corroborated by its high systemic exposure and effective distribution to metabolically active tissues, including adipose, muscle and liver, following subcutaneous dosing of mice. This work validates NNMT inhibition as a viable pharmacological approach to ameliorate metabolic imbalances and improve liver pathologies that develop with obesity.

Exploring artificial intelligence (AI) chatbots adoption among research scholars using unified theory of acceptance and use of technology (UTAUT)

The use of artificial intelligence (AI) tools, such as chatbots, has significantly increased in academia and research. The present study seeks to determine the key factors influencing chatbot adoption, as well as attempts to validate the unified theory of acceptance and use of technology (UTAUT) in the context of AI chatbots adoption among research scholars. The data for this study were collected through purposive sampling using a cross-sectional survey. The population of the study comprised research scholars enrolled in three public sector universities in Pakistan. The eight-factor proposed measurement model was estimated using confirmatory factor analysis (CFA) based on 30 valid items. The goodness of fit indices suggest a favourable fit for the model χ2 = 1.710, DF = 381; p = 0.000; IFI = .902; TLI = 0.886, CFI = 0.900, RMSEA = 0.056. Our research affirms that social influence, trust, and facilitating conditions play pivotal roles as primary predictors of behavioural intentions for AI chatbots adoption among scholars. The study suggests that the perceived risks associated with using AI chatbots due to their potential misuse can be minimized by effectively implementing AI user guidelines, and developing AI literacy among scholars. Information professionals and ethical libraries can play an important role in “building the bridge” between cutting-edge technology capabilities and information users’ needs and rights. The proposed eight-factor AI chatbots adoption model holds substantial potential in understanding the influence of performance expectancy, effort expectancy, social influence, trust, perceived risk, and facilitating conditions on behavioural intention to AI chatbots adoption. This study contributes to the limited body of research investigating the factors influencing AI chatbot adoption among research scholars using the UTAUT model with additional constructs for trust and perceived risk.

Temporal shifts in sources and composition of particulate metals in an environmental justice community: Impacts of continued emission reductions, COVID-19, and wildfires

In this study, we evaluated trends in the composition and source contributions of ambient particulate metals, many of which are toxic air contaminants, in Paramount, California. Paramount is an environmental justice community disproportionately impacted by air pollution from multiple emission sources near sensitive receptors. Concentrations of ambient metals bound to total suspended particulates (TSP) were measured hourly using a Xact 625 ambient metal monitor between 2017 and 2020. The Positive Matrix Factorization (PMF) model identified traffic, industry, and soil dust as major contributors. Results showed that contributions of traffic and soil dust noticeably declined during the COVID-19 lockdown period (March–April 2020) due to reduced human activities but reverted to normal levels within a few months. Industry-related factors, however, dropped significantly during this period and remained low throughout the year. Contributions from industry-related sources in Paramount began declining even before 2020, despite no similar trend in regional levels, implying local emission reductions. These reductions resulted from tariffs, decreased demand, regulatory actions by the South Coast Air Quality Management District, and voluntary controls by local facilities. Consequently, Paramount is experiencing drastically lower levels of metals (up to 80%, depending on the metal and source) from metal-processing facilities and related sources. Moreover, we observed markedly elevated concentrations of several metals (e.g., Ba, Ca, Mn, K, etc.) during the unprecedented September 2020 wildfires that engulfed much of the western US, adding to the limited body of studies on this phenomenon and emphasizing the considerable impact of massive wildfires on ambient levels of particulate metals.

Empowerment Evaluation’s Practice and Principle Effects on Psychological Empowerment and Self-Determination Outcomes

This study contributed to a limited body of research on empowerment evaluation by examining its processes, principles, and outcomes. Objectives included: 1) determining implementation fidelity to the three empowerment evaluation models; 2) determining evidence of empowerment evaluation process principles; 3) determining whether empowerment evaluation outcome principles resulted from the evaluations reported on; and 4) determining whether variation in empowerment and self-determination was explained by the interaction between model fidelity and percentage of steps implemented, process principles in evidence, outcome principles in evidence, and evaluator characteristics. Results indicated individual empowerment and self-determination were likely outcomes of evaluations reported on; evidence of all ten empowerment evaluation principles indicated they were empowerment evaluations; evaluators adhered with fidelity to all three models, no model was privileged over another, and steps were chosen from across all three models. Empowerment and self-determination are more likely when empowerment evaluations are conducted by female evaluators living and working in an African country and SEEPPO was a successful first attempt at assessing the process and outcomes of empowerment evaluation work.

ESG Risk and Firm’s Performance

This study aims to explore the link between market, financial, and operational performance and environmental, social, and governance (ESG) risk. This quantitative study is based on data analysis from up to 100 observations collected between 2019 and 2023. Companies listed on the Indonesia Stock Exchange IDX LQ45 throughout the observation period serve as the study's samples. Purposive sampling was used to choose the sample, and it was done so based on particular research-relevant criteria. The performance of the company is examined in relation to ESG risks using the robust standard errors model. Stakeholder theory, which highlights the significance of corporate management taking into account the interests of all stakeholders, serves as the foundation for the theoretical model of this work. The dependent variables in the practical model are ROA, ROE, and Tobin's Q, whereas the independent variable is the ESG risk rating. The conclusions drawn from the empirical data demonstrate that market and financial performance are significantly harmed by ESG risk. Nonetheless, operational performance is not significantly impacted by ESG risk. This research adds to the limited body of knowledge about the risk associated with sustainability reporting and how it affects a company's capacity to perform financially and on the market. Organizations that effectively handle environmental, social, and governance (ESG) risks can reap enduring advantages such as enhanced standing and stable finances. A crucial first step toward ensuring sustainability and competitiveness in the future is the incorporation of ESG into company strategy.

Clinical application of convolutional neural network lung nodule detection software: An Australian quaternary hospital experience.

Early-stage lung cancer diagnosis through detection of nodules on computed tomography (CT) remains integral to patient survivorship, promoting national screening programmes and diagnostic tools using artificial intelligence (AI) convolutional neural networks (CNN); the software of AI-Rad Companion™ (AIRC), capable of self-optimising feature recognition. This study aims to demonstrate the practical value of AI-based lung nodule detection in a clinical setting; a limited body of research. One hundred and eighty-three non-contrast CT chest studies from a single centre were assessed for AIRC software analysis. Prospectively collected data from AIRC detection and characterisation of lung nodules (size: ≥3 mm) were assessed against the reference standard; reported findings of a blinded consultant radiologist. One hundred and sixty-seven CT chest studies were included; 52% indicated for nodule or lung cancer surveillance. Of 289 lung nodules, 219 (75.8%) nodules (mean size: 10.1 mm) were detected by both modalities, 28 (9.7%) were detected by AIRC alone and 42 (14.5%) by radiologist alone. Solid nodules missed by AIRC were larger than those missed by radiologist (11.5 mm vs 4.7 mm, P < 0.001). AIRC software sensitivity was 87.3%, with significant false positive and negative rates demonstrating 12.5% specificity (PPV 0.6, NPV 0.4). In a population of high nodule prevalence, AIRC lung nodule detection software demonstrates sensitivity comparable to that of consultant radiologist. The clinical significance of larger sized nodules missed by AIRC software presents a barrier to current integration in practice. We consider this research highly relevant in providing focus for ongoing software development, potentiating the future success of AI-based tools within diagnostic radiology.