bluuebunny/crossref_metadata_2025 huggingface dataset:
Does tight monetary policy threaten the soundness of Korean banks?
Authors: Seo Ji‐Yong
Published: November 2024

This study analysed the relationship between the implementation of the Central Bank of Korea's tight monetary policy due to the recent deepening of inflation and the soundness of Korean banks. This study focused on the fact that the recently published research results of Jung (2023) were different from previous research results. The traditional result is that tight monetary policy reduces loan defaults by shrinking banks' lending capacity. However, Jung (2023), who analysed banks in the EU, claims that loan defaults do not increase despite easing monetary policy. This study empirically analysed the risk indicators that evaluate the financial soundness of banks by dividing them into the financial insolvency, financing costs, recapitalization, and risk holding. The research results are as follows. First, tight monetary policy reduces banks' loan defaults in line with Gambacorta and Mistrulli (2004) instead of Jung (2023). Second, banks' financing costs increased due to the tight monetary policy with same context to the claims of Borio and Hofmann (2017) and Jung (2023). Third, banks' recapitalization level actually decreased due to tight monetary policy as argument of Jung (2023). Fourth, tight monetary policy had no significant relationship with banks' risk taking behaviour in consistent with Diamond and Rajan (2011) and Jimenez et al. (2012). In conclusion, tight monetary policy reduces insolvency of loans, but increases potential risk factors such as increased financing costs and reduced recapitalization in the future. Therefore, this study suggests novel findings and policy challenges.
The Lived Experience of People With Intellectual Disability in Community Settings: A Comparison of Self‐Reports and Staff Reports
Authors: Smith Elizabeth , Sumner Petroc , Powell Georgina
Published: November 2024

Background

There is a need for more qualitative research focusing on the lived experiences of people with an intellectual disability and a better understanding of how these experiences align with other voices in their lives, such as family and support staff.

Methods

In this qualitative study, we asked people with an intellectual disability (N = 87) and their support workers (N = 120) similar questions about factors contributing positively and negatively to the lives of those with an intellectual disability. We conducted a thematic analysis combining data across respondents, while also identifying areas of similarities and divergence between self‐reports and staff reports. The setting was community‐supported living schemes and group homes in the UK.

Findings

Qualitative themes, representing key positive and negative factors in the lives of people with an intellectual disability, were (1) Positive impact of social relationships on well‐being, (2) positive impact of participation and roles on self‐determination and well‐being and (3) negative impacts of difficulties affecting day‐to‐day life. These three themes are all linked to a broader sense of identity, purpose and self‐determination. These were broadly consistent across self‐reports and staff reports, although there were some points of divergence, particularly in Theme 3.

Conclusions

These findings reveal areas that are key to maximising the quality of life of people with an intellectual disability and suggest that self‐reports and proxy reports can sometimes offer unique perspectives. Our findings can be used to ensure that the priorities of people with an intellectual disability are considered in their care.
Compound 4a induces paraptosis in liver cancer through endoplasmic reticulum stress mediated by the calreticulin protein
Authors: Wang Chunmiao , Liang Dandan , Shen Xiaoyan , Chen Xuyang , Lai Linfang , Hou Huaxin
Published: November 2024

Background and Purpose

Emerging evidence has highlighted that paraptosis may be an effective strategy for treating liver cancer. In our previous studies, Compound 4a induced paraptosis in cancer cells. Here, the characteristics of Compound 4a–induced paraptosis were further revealed and, for the first time, the target and related molecular mechanisms of Compound 4a–induced paraptosis in liver cancer were defined.

Experimental Approach

The effects and mechanism of Compound 4a in liver cancer cells were studied in in vitro and in vivo (BALB/c‐nude xenograft model) experiments, and the targets of Compound 4a that trigger paraptosis were identified and confirmed via mass spectrometry–based drug affinity responsive target stability (DARTS) analyses, siRNA experiments and a cellular thermal shift assay (CETSA). The function and distribution of calreticulin (CRT) protein were detected via Cal‐520 AM and immunofluorescence staining, respectively.

Key Results

Compound 4a effectively induced paraptosis‐like cell death in liver cancer, both in vitro and in vivo, and its effect was comparable with the first‐line anti–liver cancer drug oxaliplatin but with a higher safety profile. We identified the CRT protein as a target of Compound 4a, which caused cellular endoplasmic reticulum stress (ERS) and calcium overload. CRT knockdown weakened the anti–liver cancer activity of Compound 4a, which may be related to the inhibition of paraptosis.

Conclusion

Compound 4a represents a potentially safe and effective agent for the treatment of liver cancer. The characteristics of Compound 4a–triggered paraptosis was clarified and a unique function of CRT in paraptosis was revealed.
Caregivers' cognitions about infants' mental and emotional states
Authors: Garon‐Bissonnette Julia , Bailes Lauren G. , Kwasneski Kate , Lempres Sarah , Takemoto Sydney , Li Lu , DeLuca Julia , Salo Virginia C. , Humphreys Kathryn L.
Published: November 2024

Given the relevance of caregivers' perceptions, cognitions, and emotions about their child's mental states for caregiving behavior and children's development, researchers from multiple theoretical perspectives have developed constructs to assess caregivers' cognitions, resulting in a large but scattered body of literature. In this article, we highlight the conceptual overlap among and uniqueness of six constructs assessing caregivers' cognitions about their child at 36 months and younger: infant intentionality, mental representations, mind‐mindedness, parental embodied mentalizing, parental empathy, and parental reflective functioning. We define constructs, present approaches to measurement, and propose elements of importance that fall under the umbrella of caregivers' cognitions and that may be associated differentially with children's early cognitive and social–emotional development. We conclude with recommendations for researchers aiming to capture caregivers' cognitions about their child's mental states, whether focusing on one of the six reviewed constructs or on specific elements (e.g., awareness of the child's mind or accuracy of caregivers' perceptions of their child) under the umbrella of caregivers' cognitions.
Examining the Impact of Pandemic Stressors on Parental Stress in Sub‐Saharan Africa: A Double ABC‐X and Moderated Mediation Model Analysis of Family Mechanisms
Authors: Brik Anis Ben
Published: November 2024

This study investigated family mechanisms through which pandemic stressors affect parental stress using the Double ABC‐X model of family stress and adaptation. Specifically, this study examines the moderated mediation effects to test the conditional indirect influence of a moderating variable (i.e., family resilience beliefs) on the relationship between a predictor (i.e., stressor pile‐up) and an outcome variable (i.e., stress) through potential mediators (i.e., family satisfaction and relationship satisfaction). The analytic sample included 9269 participants from 10 sub‐Saharan countries. The findings do not support the hypothesis predicting a second‐stage moderating mediation model where family resiliency beliefs would moderate the second‐stage indirect paths of family satisfaction and relationship satisfaction, creating conditional indirect effects. The findings suggest that interventions should involve community‐based programmes that emphasize family support and access to resources while recognizing the complex interplay between family resilience beliefs, cultural values and beliefs of African families.
Operationalisation of post‐COVID condition case definition in a comprehensive research protocol
Authors: Masserini Federico , Nicotra Alessia , Forgione Arianna , Calcaterra Francesca , Perdixi Elena , Di Vito Clara , Carletti Anna , Gallo Chiara , Doneddu Pietro Emiliano , Terenghi Fabrizia , Pomati Simone , Nobile‐Orazio Eduardo , Riva Agostino , Mavilio Domenico , Pantoni Leonardo
Published: November 2024

Background and purpose

Post‐COVID‐19 condition (PCC) is a prevalent and high‐burden sequela of SARS‐CoV‐2 infection. Because of the complexity of its manifestations, PCC case definition currently lacks standardisation and reproducibility. We aimed to devise a simple screening tool to boost reproducibility and comparability of PCC case definition across PCC studies, and to provide a framework in which to reliably identify suspected PCC cases. We also developed a comprehensive assessment protocol based on the most frequently reported PCC characteristics.

Methods

Within a European multi‐centre study and based on the conclusions of a previous systematic review, we devised a checklist to assess the presence of PCC‐associated symptoms and their temporal relationship with COVID‐19.

Results

The checklist was developed to include three symptom cores (cognitive, psychiatric, and general). For each symptom, onset is assessed within 3 months after COVID‐19 resolution and persistence for at least 2 months. Any symptom fulfilling this criterion is sufficient to prompt suspicion of PCC. At least one symptom is required in the cognitive or psychiatric domains to suspect PCC with neuropsychiatric involvement. Our protocol features an extensive neuropsychological evaluation and self‐administered scales for mood, anxiety, stress‐related symptoms, sleep disorders, quality of life, disability, mental health, and personality traits; scales for quantitative assessment of fatigue and headache are also included.

Conclusions

Consistent identification of PCC cases is crucial to correctly include patients in research and clinical studies. We propose a simple, reproducible, and flexible screening tool and a proposal for a comprehensive assessment that could be employed to enhance standardisation and comparability.
The association between marital satisfaction and perceived coparenting in infancy: A longitudinal dyadic approach
Authors: Wusirige  , Liang Xi , Wang Zhengyan
Published: November 2024

Healthy marital relationships and coparenting are vital elements of a well‐functioning family, serving as the foundation for promoting optimal child development. By analyzing four waves of dyadic data collected from 236 Chinese parents during the early years of their child's life, our study sought to (a) examine the links between marital satisfaction and coparenting and (b) explore the actor and partner effects between fathers and mothers by constructing corresponding time‐averaged and time‐specific components of these two variables. Our study revealed that there might be bidirectional associations between marital satisfaction and coparenting. Furthermore, we found that fathers and mothers influence each other in terms of their marital satisfaction and coparenting, both at the average level over time and to some extent at specific time points. This highlights the need for interventions and support programs that address both marital satisfaction and coparenting, as improving one aspect can potentially have a positive impact on the other.
Future Trends in Angler Behavior Based on a Delphi Study in the Nordic Countries
Authors: van den Heuvel Lotte , Aas Øystein , Agnarsson Sveinn , Björkvik Emma , Blicharska Malgorzata , Blyth Samuel , Gundelund Casper , Husa Miikka , Olaussen Jon Olaf , Pellikka Jani , Rönnbäck Patrik , Stensland Stian , Vehanen Teppo , Skov Christian
Published: November 2024

Recreational fisheries are dynamic social‐ecological systems. Identification of anticipated future trends supports the design of policies and management to deliver outcomes for fisheries resources, users, and communities. To this end, we applied a forecasting method (i.e., Delphi survey) to recreational fisheries in five Nordic countries. The survey consisted of three rounds and included 20 diverse experts from each country. The study focused on expert perceptions of future trends in angler behaviors linked to specific angling activities (e.g., gear used, species targeted), and more general behavior (e.g., social media use, stewardship). Experts unanimously expected increases in fly fishing, stewardship, and use of angling‐related technologies and social media platforms in the upcoming decade. Results can guide future research, management, and collaboration related to recreational fishing in the Nordic countries and beyond.
Association between cardiovascular disease risk and sarcopenia in community‐dwelling Japanese older adults
Authors: Nishimoto Kazuhei , Tsutsumimoto Kota , Nakakubo Sho , Kiuchi Yuto , Misu Yuka , Ohata Tomoka , Shimada Hiroyuki
Published: November 2024

Aim

Sarcopenia's high prevalence in older adults with cardiovascular disease (CVD) suggests that the risk of comorbidity in sarcopenia might also be increased during the at‐risk phase of CVD. However, the relationship between CVD risk and sarcopenia has not been elucidated. Therefore, the purpose of this cross‐sectional study was to investigate the association between CVD risk and sarcopenia in community‐dwelling Japanese older adults.

Methods

The participants in this cross‐sectional study included 14 923 community‐dwelling Japanese older adults (mean age 73.2 ± 5.6 years). The present study estimated the CVD risk using the revised World Health Organization risk chart, and classified CVD risk into “low” (<10%) and “mid‐high” (≥10%). Assessments of sarcopenia, muscle mass, muscle strength and gait speed were measured based on the clinical definitions.

Results

Among the participants, 654 people (4.4%) had sarcopenia, and 4857 (32.6%) had CVD mid‐high risk. A multiple logistic model showed that the CVD mid‐high risk was associated with sarcopenia (odds ratio [OR] 1.55, 95% confidence interval [CI] 1.28–1.89). In addition, CVD mid‐high risk was associated with low muscle mass (OR 1.74, 95% CI 1.50–2.01), low muscle strength (OR 1.25, 95% CI 1.14–1.37) and slow gait speed (OR 1.17, 95% CI 1.07–1.27) in the adjusted model.

Conclusions

Among community‐dwelling older adults, high or moderate CVD risk was associated with an increased risk of sarcopenia. Our findings could help identify older adults with a future high risk for sarcopenia. Geriatr Gerontol Int 2024; 24: 1328–1334.
Moral sensitivity, spiritual care perception, and compassion fatigue of nurses caring for earthquake victims
Authors: Karaca Turkan , Aydin Ozkan Semiha
Published: November 2024

Background

Two major earthquakes occurred within 10 hours in Kahramanmaraş on February 6, 2023, which resulted in thousands of deaths and injured people within Turkey.

Aim

To determine the relationship between moral sensitivity, spiritual care perception, and compassion fatigue among nurses caring for earthquake victims.

Methods

The study population consisted of 483 nurses working in public, private, and university hospitals in earthquake‐affected areas in Turkey. The sociodemographic characteristics form, moral sensitivity questionnaire, spirituality and spiritual care rating scale, and compassion fatigue short scale were used for data collection.

Results

There was a statistically significant negative relationship between nurses' moral sensitivity and compassion fatigue; in other words, as compassion fatigue increases, nurses' moral sensitivity decreases. A statistically significant negative relationship was found between nurses' perception of spiritual care and their compassion fatigue; in other words, as compassion fatigue increases, nurses' perception of spirituality and spiritual care decreases.

Conclusion

This study provides valuable insights into moral sensitivity, perceptions of spiritual care, and compassion fatigue among nurses caring for earthquake victims.

Implications for nursing and health policy

Minimizing nurses' compassion fatigue improves quality patient care, increases patient and employee satisfaction, and maintains commitment to the profession. To achieve this goal, it is essential to offer in‐service training, conferences, or seminar programs to nurses focused on fostering a sense of compassion. Nurses should be provided with environments that will improve their self‐care, and institutional policies and strategies should be developed to cope effectively with this situation.
Integration analysis using bioinformatics and experimental validation on cellular signalling for sex differences of hypertrophic cardiomyopathy
Authors: Kuang Hongyu , Xu Yanping , Liu Guangliang , Wu Yuhao , Gong Zhiyan , Yin Yuehui
Published: November 2024

There is a paucity of research examining the molecular mechanisms underlying sex differences of clinical phenotypes and the prognosis in hypertrophic cardiomyopathy (HCM). The dataset GSE36961 was retrieved from Gene Expression Omnibus (GEO) database and comprehensive bioinformatics was employed to identify the core genes linked to sex differences in HCM patients. Additionally, gene set enrichment analysis (GSEA) was conducted to detect downstream signalling pathways. Furthermore, experimental validation was carried out using hearts from spontaneously hypertensive rats (SHRs). A comprehensive analysis revealed the identification of 208 differentially expressed genes (DEGs) in female patients with HCM with a notable downregulation of seven core genes. Notably, there were sex differences in the expression of ras dexamethasone‐induced protein 1 (RASD1) and myosin 6 (MYH6) in HCM. Gene ontology (GO) analysis and GSEA demonstrated an enrichment of autophagy‐related processes in disease progression in HCM females. Specifically, spearman's correlation analysis revealed a positive correlation between nicotinamide phosphoribosyl transferase (NAMPT) and RASD1 levels, particularly among female patients (R = 0.569, p < 0.001). Additionally, animal models confirmed that cardiac hypertrophy was more pronounced in SHR females compared to males. SHR females exhibited lower mRNA and protein expressions of RASD1 and NAMPT, which were associated with impaired autophagy. In this study, bioinformatics and validation using external data sets and animal models of left ventricular hypertrophy suggested that the RASD1/NAMPT axis is potentially a crucial mechanism underlying the elevated risk of cardiovascular disorders in HCM females, also pointing potentially prognostic biomarkers.
The development of a dyadic family life review intervention for the Asian diaspora: A practice article
Authors: Chou Fred , Black Tim , Huang Carmen , Tran Adam , Yan Macayla , Boothroyd Sydney
Published: November 2024

Intergenerational family conflict is a commonly identified issue in the Asian diaspora; however, there are limited interventions designed to address this concern. Given this gap in the literature, the authors present a practice article outlining the conceptualization, development, and delivery of a dyadic life review intervention called (Re)Cultivating Family Stories (RFS). RFS is a clinician‐facilitated family intervention designed to promote connection and foster successive communication through the joint activity of developing a family story. Life review is a structured approach for reminiscing and evaluating one's life experiences and includes dyadic variants. RFS builds on dyadic life review by facilitating collaborative dialogs between a parent and adult offspring, incorporating culturally responsive elements, and focusing on developing family stories. This article provides an overview of the intervention and its theoretical foundations, along with formative feedback from a field test. Considerations for future implementation and research directions are described.
The Association Between Temporomandibular‐Related Quality of Life and Oral Behaviours: A Cross‐Sectional Study in Patients With Temporomandibular Disorders
Authors: Xiao Chu‐Qiao , Zhang Jing , Luo Wen‐Xin , Jiang Nan , Zhang Li‐Ming , Yang Hao‐Lun , Wang Xiao‐Yi , Yue Yuan , Xiong Xin
Published: November 2024

Objectives

Oral behaviours (OB) are some oral overuse behaviours which could be observed in patients with temporomandibular disorders (TMD). This study aims to investigate the association between TMD‐related quality of life and OB to enhance understanding of these behaviours.

Methods

A total of 319 participants diagnosed with TMD were included in this research. According to the diagnostic criteria for TMD, patients were divided into three subgroups: pain‐related TMD (PT, n = 71), intra‐articular TMD (IT, n = 91) and combined TMD (CT, n = 157). Participants completed the oral behaviour checklist (OBC), the oral health impact profile for TMD (OHIP‐TMD), the generalised anxiety disorder 7‐item (GAD‐7) and the patient health questionnaire 9‐item (PHQ‐9), and demographic characteristics were collected from medical records.

Results

TMD patients with high OBC scores (25–84 points) had higher scores in six of the seven OHIP‐TMD domains (all p < 0.05). Logistic regression analysis indicated that OHIP‐TMD scores (OR = 1.03), younger age (OR = 0.95), education (OR = 2.80–3.10), and PHQ‐9 scores (OR = 1.14) were significantly positively correlated with OBC scores (p < 0.05). After adjusting for confounding factors, the psychological discomfort (OR = 1.09) and psychological disability (OR = 1.10) domains of the OHIP‐TMD were identified as independent factors associated with higher OBC scores.

Conclusions

Patients with more frequent OB exhibited a lower quality of life across nearly all OHIP‐TMD domains. Higher OHIP‐TMD scores and specific psychological domains were independently associated with a higher frequency of OB. The causal relationship between quality of life and OB in TMD patients requires further investigation.
The relationship between sleep difficulties and externalizing and internalizing problems in children and adolescents with mental illness
Authors: van Tetering Emilie M. A. , Mies Gabry W. , Klip Helen , Pillen Sigrid , Muskens Jet B. , Polderman Tinca J. C. , van der Mheen Malindi , Staal Wouter G. , Pieters Sara
Published: November 2024

Sleep difficulties are presumably a transdiagnostic factor in the complex aetiology of psychiatric disorders in youth. This study assessed the prevalence of sleep difficulties in children and adolescents seeking specialized psychiatric care, examined the relationships of internalizing and externalizing problems, and considered the moderating role of sex and age on these relationships. Parent‐reported data on difficulties initiating sleep, difficulties maintaining sleep, early morning awakenings and daytime fatigue from a large sample of children and adolescents referred for specialized psychiatric care (n = 4638; < 18 years) were used to estimate prevalence rates. To examine associations between these sleep difficulties and internalizing/externalizing problems, multiple linear regression analyses were conducted on available data (n = 3768) stratified in three age groups (1.5–5 years; 6–11 years; 12–18 years). Overall prevalence, i.e. at least one sleep difficulty was reported to be often or always present, was 65%. Difficulties initiating sleep occurred the most, closely followed by daytime fatigue. In all age groups, sleep difficulties were positively related to internalizing and externalizing problems. In young children and school‐age children, age moderated the interaction between sleep difficulties and internalizing problems. To conclude, prevalence rates of sleep difficulties in children with mental illness appear higher than it has been reported in the general youth population, especially difficulties initiating sleep and daytime fatigue. We observed that the associations between internalizing problems and sleep difficulties in young children and school‐age children seemed to be amplified with age, suggesting a negative, bidirectional, spiral in development.
The Single‐Dose Pharmacokinetics of a Compounded Levetiracetam Formulation and Bioequivalence to a Commercial Formulation in Healthy Dogs
Authors: Paushter Aaron M. , Foss Kari D. , Reinhart Jennifer M. , Forsythe Lauren E. , Hague Devon W.
Published: November 2024

Levetiracetam (LEV) is an anti‐epileptic drug used extra‐label in dogs. Commercially available extended‐release formulations (LEV‐ER), administered twice daily, cannot be crushed or split, limiting their use in small dogs. A compounded LEV‐ER formulation (PO‐COMP) can purportedly be partitioned without loss of extended‐release properties. The aims of this study were to establish the pharmacokinetic parameters of PO‐COMP, divided at the tablet score, and determine the bioequivalence of partitioned PO‐COMP to an intact commercially available Food and Drug Administration‐approved human oral generic formulation of LEV‐ER (PO‐COMM). In a randomized crossover design, 12 healthy dogs received a single IV dose (30 mg/kg) of IV‐COMM, a single oral dose (500 mg) of intact PO‐COMM, or a single oral dose (500 mg) of partitioned PO‐COMP and underwent serial measurement of plasma LEV concentrations over 24 h. PO‐COMP was bioequivalent to PO‐COMM using the 90% confidence interval method for maximum concentration (−3.2% difference [CI −7.4% to −1.1%]) and area under the curve (−14.4% difference [CI −17.8% to 10.8%]). PO‐COMP may improve medication adherence and seizure control relative to immediate‐release LEV, which requires three times daily dosing. Efficacy studies of PO‐COMP are warranted.
Influencing Factors of Nurses’ Well‐Being in Critical Care During Pandemic Era: A Systematic Review
Authors: Musio Maria Emma , Russo Marta , Barbieri Martina , Moro Andrea , Zanini Milko , Sasso Loredana , Bagnasco Annamaria , Catania Gianluca
Published: November 2024

Aim

To identify factors protecting and hindering the well‐being of critical care nurses during the COVID‐19 pandemic.

Background

The unique work challenges of critical care nurses can undermine their professional and mental well‐being; as evidenced by the prevailing literature on burnout, compassion fatigue, and moral distress. The COVID‐19 pandemic has seen these professionals on the front lines and has raised many questions about professional well‐being. Identifying the factors that protect and hinder the well‐being of critical care nurses would help to develop the strategies necessary to reduce worrying phenomena associated with professional malaise.

Evaluation

A systematic review was conducted using electronic databases including PubMed, CINAHL, Scopus, Cochrane, PsycINFO, and Web on Science.

Key issues

After full text analysis, 25 papers were included in the current systematic review. Factors influencing the well‐being of critical care nurses have been grouped into “Protective” and “Hindering.”

Conclusions

This review shows that critical care nurses’ well‐being is influenced by factors like personal resilience and supportive work environments, which enhance their experience. Challenges include sociodemographic issues and the COVID‐19 pandemic's impact. Addressing these factors is crucial for their well‐being and the effectiveness of healthcare systems.

Implications for clinical practice

The well‐being of nurses is intricately linked to the quality and security of patient care, ultimately influencing clinical outcomes. This review delves deeply into the multifaceted factors that affect the professional well‐being of critical care nurses during the COVID‐19 pandemic. Recognizing these elements is critical for directing health policy toward the development of initiatives that bolster healthcare workers’ welfare. Prioritizing the professional well‐being of nurses is imperative, as it is fundamental in mitigating the increasing inclination towards job turnover, a challenge that is profoundly impacting the healthcare sector.
Legal status and refugees' perceptions of institutional justice: The role of communication quality
Authors: Frank Emily , Nivorozhkin Anton
Published: November 2024

What factors influence refugees' perceptions of justice in bureaucratic institutions? As global migration movements draw increasing attention, migrants' experiences as constituents in destination countries merit further research. Drawing evidence from the 2018 survey of refugees participating in the German Socio‐Economic Panel, this article examines the role of legal status in shaping perceptions of justice at government offices. Our findings highlight a stark contrast: refugees with unstable legal statuses often perceive bureaucratic proceedings as less just compared to those with firmer legal standings. However, refugees' perceptions of a more positive encounter their encounters with street‐level bureaucrats can act as a buffer against the negative effects of legal status on perceptions of justice at government offices. These insights underscore a pressing policy implication: asylum procedures, currently marked by ambiguity and delays, could benefit significantly from enhanced communication quality on the part of street‐level bureaucrats.
Pilot Free Trade Zone Establishment and New Firm Entry: Evidence from China
Authors: Jiang Lingduo , Lu Jing , Yang Yang
Published: November 2024

This article investigates the effect of pilot free trade zones (FTZs) on new firm entry. Using firm registration data in China from 2003 to 2020, we find that the establishment of FTZs has a significant and persistent positive impact on new firm entry, and it is attributed to the capital and talent agglomeration induced by FTZs. Heterogeneous analyses show that FTZs primarily stimulate the entry of firms in high‐tech industries and domestic private firms, and the effect of FTZs is more pronounced in prefectures with higher institutional innovation and those in coastal areas. Moreover, FTZs exhibit positive spillover effects on the emergence of new firms in surrounding regions, suggesting that the establishment of FTZs has empowered coordinated regional development.
Evolved Structures: Primification Using Load Lines
Authors: Sadler Elliot , McClelland Ryan , Ho Nhut , Li Bingbing
Published: November 2024

In this study, the simplification of complex AI generated geometry for increasing compatibility with legacy analysis tools is explored. Beginning with a general discussion on the problems facing engineers in the production of non-uniform parts as well as problems with testing complex geometries with conventional FEA tools, it is established that analysis sectors can benefit from part geometry that not only simplifies and unifies its shape, but also reduces it into its primary load paths. The workflow used to convert entities from complex into primitives is explored, as well as the result of FEA testing on both a baseline and a modified structure. The importance of 3D sketches and their use in both testing scenarios and fabrication efforts is discussed, and the generation of these 3D sketches is shown as a part of the workflow. The adaptation of part geometry from organic generative design to simple load path to easily manufacturable node and tube structures is shown. The workflow for developing a 3D load path sketch is shown, and an example of an application of the process is explored, from generation of the evolved structure to its transformation to a carbon fiber tube and node configuration.
Ontology-Based Context-Aware Data Analytics in Additive Manufacturing
Authors: Park Yeun , Witherell Paul , Cho Hyunbo
Published: November 2024

Recent advances in Additive Manufacturing (AM), particularly in production scenarios, have been largely driven by insights achieved through data analytics. AM has greatly benefited from the increasingly large amounts of data generated during the design to product transformation. Despite the large amounts of data that can be generated from each build, the variations that can occur between builds create challenges in data reuse.

Advances in data analytics are coming in the form of advanced machine learning algorithms, and are often associated with deep learning, where large amounts of data are analyzed, and interpretations are made. While such algorithms are increasingly adept at solving complex problems, solutions are highly dependent on the data used to train the algorithms and thus often subject to unwanted bias. Contextualization of data can help limit unintended bias and improve the probability of attaining viable results.

Data contextualization often comes through domain context. This work describes the development of an AM ontology to support context-aware data analytics. The Additive Manufacturing Data Analytics Ontology, or AMDA Ontology, is developed to facilitate the contextualization of AM data through the representation of explicit AM concepts throughout the design to product transformation and the encoding of inhering relationships within the concepts. The AM concepts are accompanied by a suite of concepts representative of the necessary modeling, simulation, and analytics terms to create links between AM data, AM data analytics opportunities, and appropriate machine learning algorithms. The early results indicate that AMDA ontology has the ability to facilitate key correlations between AM data and the analytic opportunities to enhance the design to product transformation of AM parts.
Dynamic Modeling, Simulation, and Experimental Validation of the Power Take-Off Mechanism of an Oscillating Hydrofoil-Based Hydrokinetic Energy Converter
Authors: Vijayasankar Vishnu , Zhu Joseph , Bart-Smith Hilary , Zuo Lei
Published: November 2024

The study introduces the dynamic analysis of the Power Take-Off (PTO) mechanism of a Bio-Inspired Renewable Energy (BIRE) device aimed at revolutionizing riverine power generation. Inspired by the dynamics of fish swimming, an oscillating hydrofoil is utilized to harvest energy, which is converted via a Mechanical Motion Rectifier (MMR). This innovative PTO mechanism transmutes oscillatory motion into unidirectional rotation, ensuring high conversion efficiency. A ball screw-based MMR PTO was comprehensively examined using dry lab tests on an Instron machine and compared with a rack and pinion-based MMR PTO. The model prediction showed a commendable match with experimental data, with a primary focus on capturing frictional behaviors. Crucial findings indicated the prominence of dry friction, attributed to possible gear misalignments, which, when addressed, can significantly bolster the system’s mechanical efficiency. At an optimal load of 1 Ω, the PTO achieved an efficiency of 75%. Additionally, the distinct orientation of the force vs. displacement loop sheds light on inherent system dynamics, suggesting avenues for future refinements. This research lays the groundwork for a highly efficient and adaptable mechanism designed for harnessing riverine hydrokinetics.
Multi-Trip Algorithm for Multi-Depot Rural Postman Problem With Rechargeable Vehicles
Authors: Sathyamurthy Eashwar , Azarm Shapour , Herrmann Jeffrey W.
Published: November 2024

Autonomous vehicles have emerged as transformative technologies with vast implications across various domains, including surveillance. However, they are constrained by battery limitations, which can hinder their usability and efficiency. Designing algorithms to efficiently utilize them optimizing their battery usage, is crucial to unlocking their full potential. This paper addresses this challenge by studying an extension of the rural postman problem with multiple depots and rechargeable and reusable vehicles that can make multiple trips but have limited battery capacity. It presents a new Mixed Integer Linear Programming (MILP) formulation to find optimal solutions to the problem and proposes a new heuristic called the multi-trip (MT) algorithm. The paper describes the results of a study that tested the MT algorithm, other heuristics, and the MILP formulation on both benchmark instances and larger, real-world instances generated from road maps. Our results show that the MT algorithm found feasible solutions for every instance and produced better solutions than heuristics from the literature on 38 of the 39 instances that were tested. Due to its requirements for memory and computing time, the Gurobi optimizer used for solving the MILP formulation could not find optimal solutions for the largest instances that we tested. This research contributes to enhancing the efficiency and effectiveness of battery-operated unmanned by developing new heuristics to address the challenge of battery limitations.
Fast Computation of Collision-Free Cutter Postures Using Discrete Representation of Workpiece Shape
Authors: Inui Masatomo , Umezu Nobuyuki
Published: November 2024

In the manufacturing of complex-shaped parts, particularly using simultaneous 5-axis machining technology, as machining progresses, excess material is removed, and the workpiece shape becomes smaller. Therefore, the holder and workpiece are less likely to collide, and the range of possible tool postures increases. However, in the quest for automation, incorporating such a tool posture “margin” into calculating machining commands has not yet been possible. The final goal of this research is to realize a software system that can automatically generate commands for the 5-axis machining considering the shape change of the workpiece. The workpiece shape in the machining process can be computed using a geometric machining simulation. In the simulation, discrete methods, such as voxel or dexel models, are commonly used to represent the workpiece shape. This study developed a fast method to calculate a safe tool posture for such a discrete workpiece model without holder collisions. Our method uses the parallel processing function of the graphics processing unit to accelerate the computation. The software was successfully developed and its effectiveness was verified through several computational experiments.
A Novel Connectivity Index for Microstructures Imperfection Detection and Rectification in Multiscale Structure Design
Authors: Rastegarzadeh Sina , Huang Jida
Published: November 2024

Inspired by natural designs, microstructures exhibit remarkable properties, which drive interest in creating metamaterials with extraordinary traits. However, imperfections within microstructures and poor connectivity at the microscale level can significantly impact their performance and reliability. Achieving proper connectivity between microstructural elements and detecting structural imperfections within the microstructures pose challenges in multiscale design optimization. While using a connectivity index (CI) to quantify the topological connectivity between microstructures has been explored previously, prior approaches have limitations in identifying microstructures with complex curved geometries between adjacent units. To alleviate this issue, we present a novel CI in this study. The proposed CI goes beyond conventional methods by focusing on surface interfaces and internal microstructural irregularities. Through numerical investigations, we successfully connected distinct types of microstructures well by integrating the introduced CI with the functional-gradation scheme. We also demonstrate that the presented CI can serve as a metric to identify sharp changes or imperfections within microstructures. We evaluate the performance of the introduced index against other connectivity indices using diverse microstructural examples. Experimental findings provide valuable insights into the fundamental aspects of imperfection detection and rectification in microstructures within the multiscale design, paving the way for developing more robust and reliable materials in engineering applications.
Finite-Volume Physics-Informed U-Net for Flow Field Reconstruction With Sparse Data
Authors: Zhu Tong , Liu Dehao , Lu Yanglong
Published: November 2024

Fluid dynamics is governed by partial differential equations (PDEs) which are solved numerically. The limitations of traditional methods in data assimilation hinder their effective engagement with experiments. Physics-informed neural network (PINN) has emerged as a hybrid data-physics-driven model for convective problems. However, the approach suffers from low accuracy and poor efficiency due to the way of incorporating PDEs. In this work, a novel convolutional neural network framework integrating finite volume method (FVM) is developed to address the challenge. The interface variables of the grid are predicted by the neural network for the first time, rather than a complex procedure in FVM. The physical law is then learned by minimizing the residual of the discretized conservative form of PDEs. A comparison between this model and the original PINN regarding prediction accuracy demonstrates the superiority of embedding PDEs through FVM. The effects of sampling strategies and quantities are studied. The result confirms the model’s capability to utilize sparsely available internal measurement data. Furthermore, the model performs well even in scenarios where partial initial and boundary conditions are absent.
Towards Domain-Adaptive, Resolution-Free 3D Topology Optimization With Neural Implicit Fields
Authors: Heyrani Nobari Amin , Regenwetter Lyle , Ahmed Faez
Published: November 2024

Topology optimization is a ubiquitous task in engineering design, involving the optimal distribution of material in a prescribed spatial domain. Recently, data-driven methods such as deep generative AI models have been proposed as an alternative to iterative optimization methods. However, existing data-driven approaches are often trained on datasets using fixed grid resolutions and domain shapes, reducing their applicability to different resolutions or different domain shapes.

In this paper, we introduce two key innovations — a fast TO solver and a neural implicit field architecture to address these limitations.

First, we introduce a fast, parallelizable, iterative GPU-based TO solver optimized for high-throughput dataset generation for 3D unstructured meshes. Our solver generated 122K optimized 3D topologies, an order of magnitude more than the largest existing public dataset. Second, we introduce a new resolution-free data-driven method for 3D topologies using neural fields, called NITO-3D. A single NITO-3D model trains and predicts for a variety of resolutions and aspect ratios. By also eliminating the need for computationally intensive physical field conditioning, NITO-3D offers a faster, more flexible alternative for 3D topology optimization. On average, NITO-3D generates topologies roughly 2000 times faster and with only 0.3% higher compliance than state-of-the-art iterative solvers. With 10 steps of iterative fine-tuning, NITO-3D is on average 15 times faster and generates topologies that are under 0.1% more compliant than SIMP’s. We open-source all data and code associated with this work.
Performance Analysis of AutomataScales to Support Early Design Decisions
Authors: Chaisiriroj Pongchalat , Stone Robert B.
Published: November 2024

In this paper, we present a comprehensive study and performance analysis on the AutomataScales simulations method focusing on electric propulsion systems for deep space missions. These applications require precise and time efficient simulations. However, traditional simulation methods such as Particle-In-Cell (PIC) method facing challenges from computationally intensive (2.5–21 days), memory demands (random-access memory or RAM and CPU), and steep learning curve for researchers. These limitations reduce their effectiveness in resource-constrained environments. For instance, each GB of RAM consumes approximately 0.1875 watts which resulting in more power consumption ranging from 87.1 to 145.2 MW per simulation run. The AutomataScales method combines discretization techniques with cellular automata and a multi-layer, multi-resolution approaches. This method offers a powerful tool to model complex multiphysics interactions and utilizing hybrid numerical scheme (discrete and continuous) with lower computational time and memory usage. The method depicts intricate and accurate behaviors in various types of particle trajectory (ionized particles, primary and secondary electrons) and plasma physics (particle collision and ionization). It provides a scalable and adaptable framework for multiphysics simulations with almost real-time simulation (0.1 second per time step). A key aspect of our research is the computational efficiency of AutomataScales. Our results show that the method can achieve up to 36.9 times faster, and 2.1 times less physical memory (RAM) compared to commercial simulation tools such as COMSOL Multiphysics® software. This substantial reduction in computational resources make AutomataScales more efficient and accessible for researchers to explore broader design variables in their early design process with or without computational constraints.
Simulation of Cutting Face-Hobbed Bevel Gears Based on a Ring-Dexel Model
Authors: Shih Yi-Pei , Sheen Bor-Tyng , Wei Yu-Hsien , Wei Bo-Lin
Published: November 2024

The face hobbing method, renowned for its high precision and production efficiency, is a primary technique for mass-producing hypoid gears in automatic industrial applications. This method can be implemented effectively on a modern six-axis CNC bevel gear-cutting machine. However, due to the complicated machining movement of multiple nonlinear axes, it is challenging but essential to conduct cutting simulations to validate the accuracy of the given machining positions. Even some commercial software can do cutting simulations for face hobbing machining; the settings are very complicated, and thus, integrating them into the human machine interface program of CNC machine presents many challenges. Additionally, the cutting feed rates provided by the ongoing CNC codes may not be optimal, necessitating manual adjustments by an engineer to improve machining efficiency. Material removal rate (MRR) is closely related to machining power, making it a valuable metric for optimizing cutting feed rates. However, there have been few studies in this area due to the complexity of face-hobbing processing. This paper aims to establish a mathematical model for face hobbing simulation based on a modified ring-dexel model. Many rings are arranged in the model to discretize the gear blank and to solve the tooth surface cutting points. These points can be used further to construct the surface geometry of the produced gear using triangle meshes. The volume of material removed is determined, enabling the calculation of the volume removal rate as a basis for optimizing cutting feed rates.
Applications With Autonomous Mobile Platforms and Robotic Arms for Experiential Learning and Research in Indoor and Outdoor Settings
Authors: Nagchaudhuri Abhijit , Pandya Jesuraj , Ward Lance , Butler Brian , Cuppett Jackson , Wilson Parker
Published: November 2024

Automation and robotics have been a dominant theme in the funded project efforts with acronyms ECPA (Environmentally Conscious Precision Agriculture), AIRSPACES (Autonomous Instrumented Robotic Sensory Platforms to Advance Creativity and Engage Students), and more recently DREAM (Developing Robotic Explorations with Agrobots and Moonbots). These projects have engaged undergraduate and graduate students from STEM disciplines. Robotic applications within and outside the laboratory have played a pivotal role in engaging the students and driving the educational and research objectives of the proposed projects. This paper will highlight some of the efforts undertaken by the project team for developing and utilizing mobile robots and fixed-base robotic arms.