bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on green innovation efficiency measurement and influencing factors in the three major coastal urban agglomerations in China
Authors: Ying Shuli , Fang Qiquan , Ji Yanting
Published: October 2023

Introduction: Behind China’s booming economy lies a series of environmental and resource consumption issues. After continuous research and exploration, scholars generally agree that green innovation is a crucial way to solve this problem. As the core regions of China’s economic development, studying the green innovation level of the three major urban agglomerations can help understand China’s progress in this area. It can provide beneficial experience and inspiration for other urban agglomerations and the formulation of relevant policies in the future.

Methods: This paper selects the panel data of 40 cities in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) urban agglomerations from 2010 to 2020 as the research object. The super-efficiency SBM (slack-based measure) model and Malmquist-Luenberger (ML) index are used to measure the green innovation efficiency (GIE) and its dynamic evolution rules, and the Tobit regression model is constructed to analyze the influencing factors of GIE.

Results: The PRD urban agglomeration has the highest GIE level, while the GIE level in BTH and YRD shifted around 2015. Technical efficiency and technological progress together lead to increased GIE, with technological progress having a higher impact than technical efficiency. The regression coefficients of urbanization level, industrial structure, and science and technology level are 0.0078, 0.0071, and 0.0616, respectively, significantly promoting GIE. The coefficients of economic development level, foreign direct investment, environmental regulations, and SO2 emissions are −0.2198, −0.1163, −0.005, and −0.011, respectively, significantly inhibiting GIE. The coefficient of vegetation cover of 0.0228 has no significant effect on GIE.

Conclusions: The overall GIE of the three major urban agglomerations is relatively high. Still, there is spatial variability in GIE among different cities, accompanied by the phenomenon of two-level differentiation. The study suggests that improving GIE requires enhanced interventions at both the city level and the level of influencing factors. This study enriches the theoretical results on the meso-level of GIE and provides theoretical guidance and practical directions for promoting green innovation in urban agglomerations, achieving peaking carbon and carbon neutrality, and promoting green and high-quality development.
Medical students’ interest in research: changing trends during university training
Authors: Sanabria-de la Torre Raquel , Quiñones-Vico María I. , Ubago-Rodríguez Ana , Buendía-Eisman Agustín , Montero-Vílchez Trinidad , Arias-Santiago Salvador
Published: October 2023

Introduction

Research is an important aspect of medical training and plays a vital role in the advancement of evidence-based medicine. However, little is known about medical students’ attitudes towards research. So, the aim of this study was to assess the opinion of medical students on scientific research.

Methods

A cross-sectional study was designed that included students from the Faculty of Medicine of the University of Granada (UGR), Granada, Spain. A survey was distributed to assess their interest about research during undergraduate studies (1) and following graduation (2), participation in research activities (3), barriers towards research (4), expectation values and self-perceived skills (5). The opinions of students who had not taken clinical subjects (2nd year students) and students who had taken clinical subjects (4th and 6th year students) were compared.

Results

91 students were included in the study (32 were 2nd year students and 59 were 4th and 6th year students). More 4th and 6th year students showed no interest in research (50.4% vs. 28.1%, p = 0.042) or in pursuing a doctoral thesis (75% vs. 50.9%, p = 0.079) than 2nd year students. In addition, more 4th and 6th year students felt that they did not have sufficient skills to engage in scientific research (52.4% vs. 18.9%, p = 0.002). Likewise a greater number of 4th and 6th year students considered that the professors did not encourage scientific research activities (74.6% vs. 40.6%, p = 0.002). Generally, students do not participate in scientific dissemination events. The main barriers to research identified were lack of funding and lack of awareness of opportunities.

Conclusion

Interest in research among medical students seems to decrease as the academic years progress. More research promotion could be implemented during the years of university studies.
Phylogenomics of Acinetobacter species and analysis of antimicrobial resistance genes
Authors: Migliaccio Antonella , Bray James , Intoccia Michele , Stabile Maria , Scala Giovanni , Jolley Keith A. , Brisse Sylvain , Zarrilli Raffaele
Published: October 2023

Introduction

Non-baumannii Acinetobacter species are increasingly isolated in the clinical setting and the environment. The aim of the present study was to analyze a genome database of 837 Acinetobacter spp. isolates, which included 798 non-baumannii Acinetobacter genomes, in order to define the concordance of classification and discriminatory power of 7-gene MLST, 53-gene MLST, and single-nucleotide polymorphism (SNPs) phylogenies.

Methods

Phylogenies were performed on Pasteur Multilocus Sequence Typing (MLST) or ribosomal Multilocus Sequence Typing (rMLST) concatenated alleles, or SNPs extracted from core genome alignment.

Results

The Pasteur MLST scheme was able to identify and genotype 72 species in the Acinetobacter genus, with classification results concordant with the ribosomal MLST scheme. The discriminatory power and genotyping reliability of the Pasteur MLST scheme were assessed in comparison to genome-wide SNP phylogeny on 535 non-baumannii Acinetobacter genomes assigned to Acinetobacter pittii, Acinetobacter nosocomialis, Acinetobacter seifertii, and Acinetobacter lactucae (heterotypic synonym of Acinetobacter dijkshoorniae), which were the most clinically relevant non-baumannii species of the A. baumannii group. The Pasteur MLST and SNP phylogenies were congruent at Robinson-Fould and Matching cluster tests and grouped genomes into four and three clusters in A. pittii, respectively, and one each in A. seifertii. Furthermore, A. lactucae genomes were grouped into one cluster within A. pittii genomes. The SNP phylogeny of A. nosocomialis genomes showed a heterogeneous population and did not correspond to the Pasteur MLST phylogeny, which identified two recombinant clusters. The antimicrobial resistance genes belonging to at least three different antimicrobial classes were identified in 91 isolates assigned to 17 distinct species in the Acinetobacter genus. Moreover, the presence of a class D oxacillinase, which is a naturally occurring enzyme in several Acinetobacter species, was found in 503 isolates assigned to 35 Acinetobacter species.

Conclusion

In conclusion, Pasteur MLST phylogeny of non-baumannii Acinetobacter isolates coupled with in silico detection of antimicrobial resistance makes it important to study the population structure and epidemiology of Acinetobacter spp. isolates.
Optimal systolic and diastolic blood pressure threshold that associated with lower risk of white matter hyperintensity progression
Authors: Liu Sibo , Wang Mengxing , Gu De’an , Li Yanzhao , Zhang Xin , Li Hang , Ji Chenhua , Nie Ximing , Liu Jinjie
Published: October 2023

Background

The optimal control thresholds for systolic blood pressure (SBP) and diastolic blood pressure (DBP) in patients with white matter hyperintensity (WMH) are still unclear.

Method

A longitudinal retrospective study of patients with brain magnetic resonance imaging (MRI) scans with intervals of more than 3  years was conducted. Blood pressure records during hospitalization and from outpatient visits between baseline and the last MRI scan were collected. The outcome was the change in total WMH from baseline to the final visit.

Results

Among the 965 patients with MRI scans, 457 patients with detailed longitudinal blood pressure records were ultimately included and classified into the WMH absent group (n = 121), mild WMH group (n = 126), and moderate to severe WMH group (n = 210). Both baseline and longitudinal mean SBP, DBP, and SBP SD were significantly associated with WMH severity (p < 0.05). An average SBP of 130-140 mmHg [vs. <130 mmHg, aOR, 1.80, (95% CI, 1.05–3.07), p = 0.03] was associated with a higher risk of WMH progression. DBP ≥ 90 mmHg [vs. <80 mmHg, OR, 1.81, (95% CI, 0.88–3.74), p = 0.02, aOR, 1.54, (95% CI, 0.66–3.53), p = 0.32] was associated with a higher risk of WMH progression, but was not after adjusted for other covariates. Longitudinal BP variability was not significantly associated with WMH progression.

Conclusion

Both SBP and DBP had a stronger relationship with the severity of WMH. A target mean SBP of <130 mmHg and mean DBP of <80 mmHg was associated with a lower risk of WMH progression.
Prefrontal event-related potential markers in association with mild cognitive impairment
Authors: Eyamu Joel , Kim Wuon-Shik , Kim Kahye , Lee Kun Ho , Kim Jaeuk U.
Published: October 2023

Background

Alzheimer’s disease (AD) is among the leading contributors of dementia globally with approximately 60–70% of its cases. Current research is focused on the mild cognitive impairment (MCI), which is associated with cognitive decline but does not disrupt routine activities. Event-related potential (ERP) research is essential in screening patients with MCI. Low-density channel electroencephalography (EEG) is frequently used due to its convenience, portability, and affordability, making it suitable for resource-constrained environments. Despite extensive research on neural biomarkers for cognitive impairment, there is a considerable gap in understanding the effects on early stages of cognitive processes, particularly when combining physiological and cognitive markers using portable devices. The present study aimed to examine cognitive shortfalls and behavioral changes in patients with MCI using prefrontal selective attention ERP recorded from a prefrontal two-channel EEG device.

Methods

We assessed cognitive decline using the Mini-Mental State Examination (MMSE) and the Seoul Neuropsychological Screening Battery (SNSB). We administered auditory selective attention tasks to 598 elderly participants, including those with MCI (160) and cognitively normal (CN) individuals (407). We conducted statistical analyses such as independent t-tests, Pearson’s correlations, and univariate and multiple logistic regression analyses to assess group differences and associations between neuropsychological tests, ERP measures, behavioral measures, and MCI prevalence.

Results

Our findings revealed that patients with MCI demonstrated slower information-processing abilities, and exhibited poorer task execution, characterized by reduced accuracy, increased errors, and higher variability in response time, compared to CN adults. Multiple logistic regression analyses confirmed the association between some ERP and behavioral measures with MCI prevalence, independent of demographic and neuropsychological factors. A relationship was observed between neuropsychological scores, ERP, and behavioral measures.

Discussion

The slower information processing abilities, and poor task execution in the MCI group compared to the CN individuals suggests flawed neurological changes and reduced attentional maintenance during cognitive processing, respectively. Hence, the utilization of portable EEG devices to capture prefrontal selective attention ERPs, in combination with behavioral assessments, holds promise for the identification of mild cognitive deficits and neural alterations in individuals with MCI. This approach could potentially augment the traditional neuropsychological tests during clinical screening for MCI.
Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running
Authors: Wilson Taylor J. , Mangalam Madhur , Stergiou Nick , Likens Aaron D.
Published: October 2023

Introduction: The seemingly periodic human gait exhibits stride-to-stride variations as it adapts to the changing task constraints. The optimal movement variability hypothesis (OMVH) states that healthy stride-to-stride variations exhibit “fractality”—a specific temporal structure in consecutive strides that are ordered, stable but also variable, and adaptable. Previous research has primarily focused on a single fractality measure, “monofractality.” However, this measure can vary across time; strideto-stride variations can show “multifractality.” Greater multifractality in stride-tostride variations would highlight the ability to tune and adjust movements more.

Methods: We investigated monofractality and multifractality in a cohort of eight healthy adults during self-paced walking and running trials, both on a treadmill and overground. Footfall data were collected through force-sensitive sensors positioned on their heels and feet. We examined the effects of self-paced walking vs. running and treadmill vs. overground locomotion on the measure of monofractality, α-DFA, in addition to the multifractal spectrum width, W, and the asymmetry in the multifractal spectrum, WAsym, of stride interval time series.

Results: While the α-DFA was larger than 0.50 for almost all conditions, α-DFA was higher in running and locomoting overground than walking and locomoting on a treadmill. Similarly, W was greater while locomoting overground than on a treadmill, but an opposite trend indicated that W was greater in walking than running. Larger WAsym values in the negative direction suggest that walking exhibits more variation in the persistence of shorter stride intervals than running. However, the ability to tune and adjust movements does not differ between treadmill and overground, although both exhibit more variation in the persistence of shorter stride intervals.

Discussion: Hence, greater heterogeneity in shorter than longer stride intervals contributed to greater multifractality in walking compared to running, indicated by larger negative WAsym values. Our results highlight the need to incorporate multifractal methods to test the predictions of the OMVH.
Case report: De novo variant of SETD1A causes infantile epileptic spasms syndrome
Authors: Lan Mingping , Wang Yanjuan , Li Sixiu , Zhao Lili , Liu Ping , Hu Wenguang
Published: October 2023

Infantile epileptic spasms syndrome (IESS) is one of the most common epileptic encephalopathies of infancy, with typical clinical features defined by a triad of epileptic spasms, hypsarrhythmia, and developmental delay. Genetic factors are important causes of IESS. The SETD1A (SET Domain Containing 1A) gene encodes a histone lysine methyltransferase that activates gene transcription through histone H3 lysine K4 methylation. Mutations in the SETD1A gene have been associated with schizophrenia, and some have been reported to cause seizures. Herein, we report a case of IESS caused by a SETD1A gene mutation. Video electroencephalography showed hypsarrhythmia. No specific findings were obtained after brain MRI and metabolic work-up. The seizures disappeared after treatment with adrenocorticotropic hormone, vitamin B6, and valproic acid during hospitalization. Genetic testing revealed that the child had a variant (NM_014712.3:c.3005_3,006 delAG, p.Glu1002Glyfs*20) in exon 12 of the SETD1A gene, representing a de novo mutation. There have been no previous reports on the SETD1A gene causing infantile spasms. We also summarize the existing literature on SETD1A gene–related epilepsy to provide a reference for clinical diagnosis and treatment.
Comparative analysis of group information-guided independent component analysis and independent vector analysis for assessing brain functional network characteristics in autism spectrum disorder
Authors: Jing Junlin , Klugah-Brown Benjamin , Xia Shiyu , Sheng Min , Biswal Bharat B.
Published: October 2023

Introduction

Group information-guided independent component analysis (GIG-ICA) and independent vector analysis (IVA) are two methods that improve estimation of subject-specific independent components in neuroimaging studies. These methods have shown better performance than traditional group independent component analysis (GICA) with respect to intersubject variability (ISV).

Methods

In this study, we compared the patterns of community structure, spatial variance, and prediction performance of GIG-ICA and IVA-GL, respectively. The dataset was obtained from the publicly available Autism Brain Imaging Data Exchange (ABIDE) database, comprising 75 healthy controls (HC) and 102 Autism Spectrum Disorder (ASD) participants. The greedy rule was used to match components from IVA-GL and GIG-ICA in order to compare the similarities between the two methods.

Results

Robust correspondence was observed between the two methods the following networks: cerebellum network (CRN; |r| = 0.7813), default mode network (DMN; |r| = 0.7263), self-reference network (SRN; |r| = 0.7818), ventral attention network (VAN; |r| = 0.7574), and visual network (VSN; |r| = 0.7503). Additionally, the Sensorimotor Network demonstrated the highest similarity between IVA-GL and GIG-ICA (SOM: |r| = 0.8125). Our findings revealed a significant difference in the number of modules identified by the two methods (HC: p < 0.001; ASD: p < 0.001). GIG-ICA identified significant differences in FNC between HC and ASD compared to IVA-GL. However, in correlation analysis, IVA-GL identified a statistically negative correlation between FNC of ASD and the social total subscore of the classic Autism Diagnostic Observation Schedule (ADOS: pi = −0.26, p = 0.0489). Moreover, both methods demonstrated similar prediction performances on age within specific networks, as indicated by GIG-ICA-CRN (R2 = 0.91, RMSE = 3.05) and IVA-VAN (R2 = 0.87, RMSE = 3.21).

Conclusion

In summary, IVA-GL demonstrated lower modularity, suggesting greater sensitivity in estimating networks with higher intersubject variability. The improved age prediction of cerebellar-attention networks underscores their importance in the developmental progression of ASD. Overall, IVA-GL may be appropriate for investigating disorders with greater variability, while GIG-ICA identifies functional networks with distinct modularity patterns.
Recent advances in genetic etiology of non-syndromic deafness in children
Authors: Feng Yawei , Hu Sunyi , Zhao Shen , Chen Ming
Published: October 2023

Congenital auditory impairment is a prevalent anomaly observed in approximately 2–3 per 1,000 infants. The consequences associated with hearing loss among children encompass the decline of verbal communication, linguistic skills, educational progress, social integration, cognitive aptitude, and overall well-being. Approaches to reversing or preventing genetic hearing loss are limited. Patients with mild and moderate hearing loss can only use hearing aids, while those with severe hearing loss can only acquire speech and language through cochlear implants. Both environmental and genetic factors contribute to the occurrence of congenital hearing loss, and advancements in our understanding of the pathophysiology and molecular mechanisms underlying hearing loss, coupled with recent progress in genetic testing techniques, will facilitate the development of innovative approaches for treatment and screening. In this paper, the latest research progress in genetic etiology of non-syndromic deafness in children with the highest incidence is summarized in order to provide help for personalized diagnosis and treatment of deafness in children.
Discrepancies in tumor mutation burden reporting from sequential endobronchial ultrasound transbronchial needle aspiration samples within single lymph node stations - brief report
Authors: Fielding David , Dalley Andrew J. , Singh Mahendra , Nandakumar Lakshmy , Lakis Vanessa , Chittoory Haarika , Fairbairn David , Patch Ann-Marie , Kazakoff Stephen H. , Ferguson Kaltin , Bashirzadeh Farzad , Bint Michael , Pahoff Carl , Son Jung Hwa , Ryan Kimberley , Hodgson Alan , Sharma Sowmya , Pearson John V. , Waddell Nicola , Lakhani Sunil R. , Hartel Gunter , Simpson Peter T. , Nones Katia
Published: October 2023

Introduction

Tumour Mutation Burden (TMB) is a potential biomarker for immune cancer therapies. Here we investigated parameters that might affect TMB using duplicate cytology smears obtained from endobronchial ultrasound transbronchial needle aspiration (EBUS TBNA)-sampled malignant lymph nodes.

Methods

Individual Diff-Quik cytology smears were prepared for each needle pass. DNA extracted from each smear underwent sequencing using large gene panel (TruSight Oncology 500 (TSO500 - Illumina)). TMB was estimated using the TSO500 Local App v. 2.0 (Illumina).

Results

Twenty patients had two or more Diff-Quik smears (total 45 smears) which passed sequencing quality control. Average smear TMB was 8.7 ± 5.0 mutations per megabase (Mb). Sixteen of the 20 patients had paired samples with minimal differences in TMB score (average difference 1.3 ± 0.85). Paired samples from 13 patients had concordant TMB (scores below or above a threshold of 10 mutations/Mb). Markedly discrepant TMB was observed in four cases, with an average difference of 11.3 ± 2.7 mutations/Mb. Factors affecting TMB calling included sample tumour content, the amount of DNA used in sequencing, and bone fide heterogeneity of node tumour between paired samples.

Conclusion

TMB assessment is feasible from EBUS-TBNA smears from a single needle pass. Repeated samples of a lymph node station have minimal variation in TMB in most cases. However, this novel data shows how tumour content and minor change in site of node sampling can impact TMB. Further study is needed on whether all node aspirates should be combined in 1 sample, or whether testing independent nodes using smears is needed.
The role of attention and health goals in nudging healthy food choice
Authors: Gillebaart Marleen , Blom Stephanie S. A. H. , Benjamins Jeroen S. , de Boer Femke , De Ridder Denise T. D.
Published: October 2023

Introduction

Nudging is a promising intervention technique that supports people in pursuing their healthy eating goals. Recent research suggests that, despite previous assumptions, disclosure of the presence of a nudge does not compromise nudge effectiveness. However, it is unknown whether attention to a nudge affects nudge effects. We assessed the role of attention systematically, by examining explicit and implicit attention to nudges, while also exploring healthy eating goals as a potential moderator.

Methods

Participants were assigned to a nudge (i.e., a shopping basket inlay with pictures of healthy items) or control condition (i.e., a shopping basket inlay with neutral pictures) and chose a snack in an experimental supermarket field study. Explicit and implicit attention (with a mobile eye-tracker) to nudges, healthiness of snack choice, and healthy eating goals were assessed.

Results

Results showed that attention to the nudge did not hamper the nudge’s effect. Furthermore, individuals with strong healthy eating goals made healthier food choices in the nudge condition. Individuals with weak to non-existent healthy eating goals were not influenced by the nudge.

Discussion

Findings are in line with the viewpoint that nudging does not by definition work ‘in the dark’, and suggests that nudges support people in adhering to their healthy eating goal.
Malaria in pregnancy in India: a 50-year bird’s eye
Authors: Kojom Foko Loick Pradel , Singh Vineeta
Published: October 2023

Introduction

In 2021, India contributed for ~79% of malaria cases and ~ 83% of deaths in the South East Asia region. Here, we systematically and critically analyzed data published on malaria in pregnancy (MiP) in India.

Methods

Epidemiological, clinical, parasitological, preventive and therapeutic aspects of MiP and its consequences on both mother and child were reviewed and critically analyzed. Knowledge gaps and solution ways are also presented and discussed. Several electronic databases including Google scholar, Google, PubMed, Scopus, Wiley Online library, the Malaria in Pregnancy Consortium library, the World Malaria Report, The WHO regional websites, andClinicalTrials.govwere used to identify articles dealing with MiP in India. The archives of local scientific associations/journals and website of national programs were also consulted.

Results

Malaria in pregnancy is mainly due toPlasmodium falciparum(Pf) andP. vivax(Pv), and on rare occasions toP. ovalespp. andP. malariaetoo. The overall prevalence of MiP is ~0.1–57.7% for peripheral malaria and ~ 0–29.3% for placental malaria. PeripheralPfinfection at antenatal care (ANC) visits decreased from ~13% in 1991 to ~7% in 1995–1996 in Madhya Pradesh, while placentalPfinfection at delivery unit slightly decreased from ~1.5% in 2006–2007 to ~1% in 2012–2015 in Jharkhand. In contrast, the prevalence of peripheralPvinfection at ANC increased from ~1% in 2006–2007 to ~5% in 2015 in Jharkhand, and from ~0.5% in 1984–1985 to ~1.5% in 2007–2008 in Chhattisgarh. Clinical presentation of MiP is diverse ranging from asymptomatic carriage of parasites to severe malaria, and associated with comorbidities and concurrent infections such as malnutrition, COVID-19, dengue, and cardiovascular disorders. Severe anemia, cerebral malaria, severe thrombocytopenia, and hypoglycemia are commonly seen in severe MiP, and are strongly associated with tragic consequences such as abortion and stillbirth. Congenital malaria is seen at prevalence of ~0–12.9%. Infected babies are generally small-for-gestational age, premature with low birthweight, and suffer mainly from anemia, thrombocytopenia, leucopenia and clinical jaundice. Main challenges and knowledge gaps to MiP control included diagnosis, relapsing malaria, mixedPlasmodiuminfection treatment, self-medication, low density infections and utility of artemisinin-based combination therapies.

Conclusion

All taken together, the findings could be immensely helpful to control MiP in malaria endemic areas.
Medical service pricing and pharmaceutical supply chain coordination contracts under the zero-markup drug policy
Authors: Zhou Nan , Li Shiyang , Zhao Gang , Li Chengjiang , Yu Na
Published: October 2023

To implement state policies of zero-markup drug policy and medical service fee adjustment for public hospitals, this study constructed game models of the pharmaceutical supply chain, consisting of a drug supplier and a public hospital. The study obtained the optimal medical service level and pricing under the new state drug policies. In addition, it analyzed the impacts of the degree of public benefit of hospitals on the medical service level, the medical service price, and the drug price. Finally, from the perspective of cooperation between drug suppliers and public hospitals, the specialized coordination contract was designed to maximize overall social welfare. This study found an anomalous but meaningful conclusion: in the background of the zero-markup drug policy, a higher public benefit of hospitals could increase the drug prices, but it could reduce the medical service prices further to cut down on the overall treatment fees for the patients. The novel coordination contract can optimize the pharmaceutical supply chain and achieve a win-win situation for the drug suppliers, public hospitals, and patients. When the public benefit of hospitals is higher, the profit of a decentralized decision-making supply chain is greater than a centralized one, while the pharmaceutical supply chain will not coordinate itself.
Epidemiology of neurocognitive disorders in adults from urban-marginalized areas: a door-to-door population-based study in Puente Piedra, Lima, Peru
Authors: Herrera-Perez Eder , Custodio Nilton , Diaz Monica , Montesinos Rosa , Chang Alexandra , Villafuerte Mirla , Lanata Serggio
Published: October 2023

Background

In Latin America (LA), the prevalence of dementia is expected to triple to 150 million people by 2050. The 2020 Lancet Commission report identified several modifiable dementia risk factors, yet few social and environmental factors, most relevant to vulnerable regions of LA, were highlighted in this report. We sought to assess the epidemiology of neurocognitive disorders (NCD) in Puente Piedra, one of the most socially and economically vulnerable districts of Lima, the capital of Peru.

Methodology

This was a cross-sectional door-to-door observational study that used two-stage household sampling. One young adult (30–59 years) and one older adult (>60 years) per household were enrolled. We collected demographic, clinical, and neurocognitive data. Addenbrooke’s Cognitive Examination (young adults) and the RUDAS-PE (older adults) were used, classifying participants as cognitively normal, possible mild NCD, or possible major NCD.

Results

We enrolled 247 participants (median age 46 years; 67% female). One-fourth had not completed secondary school and more than 50% completed only secondary school. Most participants were housewives (46%) and 21% did not have health insurance. The overall prevalence of possible NCD was 30% (25.6 and 41.8% among younger adults and older adults, respectively). Among younger adults, those ages 55–59 years more frequently had NCD (70%) compared to younger age ranges. Among older adults, only 3 subjects (4.5%) had major NCD.

Conclusion

We found a high frequency of possible NCDs in a socially and economically vulnerable community in Lima, Peru, with younger adults showing levels of NCD higher than expected. Our findings support the need for health systems to incorporate cognitive screenings programs for NCD in younger ages. Future research on NCD would include younger populations, particularly in vulnerable communities.
Psychosocial impact of COVID-19 pandemic: experience of healthcare workers in Qatar
Authors: Al-Qudimat Ahmad R. , Singh Kalpana , Mustafa Emad , Nashwan Abdulqadir J. , Al-Zoubi Raed M. , Yassin Aksam , Aboumarzouk Omar M. , Al-Ansari Abdulla
Published: October 2023

Background

The COVID-19 pandemic has had a profound and global impact on healthcare systems worldwide, presenting unprecedented challenges for healthcare workers (HCWs) on the front. We aimed to evaluate the prevalence of anxiety and depression symptoms during the coronavirus pandemic among healthcare professionals in Qatar.

Methods

A cross-sectional study where an electronic questionnaire containing demographics, and psychosocial questions were made on Google Docs and Microsoft Team, and were sent through email and WhatsApp to healthcare workers, including doctors, nurses, allied health and others working at Hamad Medical Corporation in Qatar, from June 1, 2021, to January 1st 2023. ANOVA, t-test and multiple linear regression were used to see the association between the psychological factors and sociodemographic variables using STATA version 17 software.

Results

A total of 829 participants were included in this study (response rate: 55%). The average age of the participants is 36.0 ± 7.1; 65.9% were males; 2.3% were doctors and 53% were nurses, 38.7% were allied healthcare professionals and 6% were others. Psychological, social effects, and workplace were shown to significantly related to their marital status, career, and hospital setting (p < 0.01 for each). Similar to this, dealing with COVID-19 patients and their education level with the length of time working at the designated facility were all connected with the health professional safety score (p < 0.05).

Conclusion

During the COVID-19 epidemic, healthcare workers in Qatar experienced a high incidence of negative psychosocial symptoms. To alleviate these outcomes, it would be useful to implement screening procedures for such symptoms and to devise preventive measures accordingly.
Deep skin diseases diagnostic system with Dual-channel Image and Extracted Text
Authors: Li Huanyu , Zhang Peng , Wei Zikun , Qian Tian , Tang Yiqi , Hu Kun , Huang Xianqiong , Xia Xinxin , Zhang Yishuang , Cheng Haixing , Yu Fubing , Zhang Wenjia , Dan Kena , Liu Xuan , Ye Shujun , He Guangqiao , Jiang Xia , Liu Liwei , Fan Yukun , Song Tingting , Zhou Guomin , Wang Ziyi , Zhang Daojun , Lv Junwei
Published: October 2023

Background

Due to the lower reliability of laboratory tests, skin diseases are more suitable for diagnosis with AI models. There are limited AI dermatology diagnostic models combining images and text; few of these are for Asian populations, and few cover the most common types of diseases.

Methods

Leveraging a dataset sourced from Asia comprising over 200,000 images and 220,000 medical records, we explored a deep learning-based system for Dual-channel images and extracted text for the diagnosis of skin diseases model DIET-AI to diagnose 31 skin diseases, which covers the majority of common skin diseases. From 1 September to 1 December 2021, we prospectively collected images from 6,043 cases and medical records from 15 hospitals in seven provinces in China. Then the performance of DIET-AI was compared with that of six doctors of different seniorities in the clinical dataset.

Results

The average performance of DIET-AI in 31 diseases was not less than that of all the doctors of different seniorities. By comparing the area under the curve, sensitivity, and specificity, we demonstrate that the DIET-AI model is effective in clinical scenarios. In addition, medical records affect the performance of DIET-AI and physicians to varying degrees.

Conclusion

This is the largest dermatological dataset for the Chinese demographic. For the first time, we built a Dual-channel image classification model on a non-cancer dermatitis dataset with both images and medical records and achieved comparable diagnostic performance to senior doctors about common skin diseases. It provides references for exploring the feasibility and performance evaluation of DIET-AI in clinical use afterward.
Motion Analysis of Wire Rope Maintenance Device
Authors: Wang Wei , Yang Hao , Chen Yan , Huang Xudong , Cao Jinlong , Zhang Weilun
Published: October 2023

This work outlines a design for a wire rope maintenance device that is based on commonly used, low-dropping point lubricating grease for wire rope lubrication and operates along the strand’s twist direction. Unlike similar existing devices, this device scrapes abrasives from the wire rope’s surface along the strand’s twist direction and applies lubricating grease in the same direction. It addresses issues related to the accumulation of old lubricating grease between strands, as well as the problems of a heavy weight, high traction force requirements, complex operation, unstable motion, potential surface damage to the wire rope, and the strong pollution found in existing products. The wheel system of this device was kinematically modeled and subjected to force analysis, and its accuracy was verified through simulations and experiments. Test results show that when this device is used for cleaning and lubricating wire ropes, it requires less than 150 N of traction force, maintains a stable speed of 0.6 m/s, and ensures coaxiality within ±0.1 mm, thus meeting the maintenance requirements of ropeway wire ropes. In future work, the effects of different factors, such as changes in scraper shape and size, lubricating grease application speed, and temperature and pressure inside the grease storage chamber can be studied to understand their influence on the application of grease to wire ropes.
Orthodontic Relapse after Fixed or Removable Retention Devices: A Systematic Review
Authors: Inchingolo Francesco , Inchingolo Angelo Michele , Ceci Sabino , Carpentiere Vincenzo , Garibaldi Mariagrazia , Riccaldo Lilla , Di Venere Daniela , Inchingolo Alessio Danilo , Malcangi Giuseppina , Palermo Andrea , Tartaglia Francesco Carlo , Dipalma Gianna
Published: October 2023

Retention constitutes a fundamental phase of orthodontic treatment, of which the patient must be made aware from the outset. Retention, which can be fixed or movable, has the task of maintaining over time and stabilising the results obtained during treatment. This study assessed the efficacy of using removable restraints versus fixed solutions for maintaining long-term outcomes. A comprehensive search across major databases—Pubmed, Web of Science, Scopus—used ‘relapse’ and ‘orthodontic’ as keywords to gather articles on relapse discussions. The primary focus was relapsed cases in post-fixed orthodontic therapy. Both fixed and removable retainer systems prove effective in preserving orthodontic achievements. While fixed devices require regular wire integrity checks, mobile devices require patient compliance, proper usage, and a recommended wear time. Studies indicate that fixed retainers are generally successful, with relapse rates varying based on the retainer type. Full-time use of removable devices surpasses night-only wear. Vacuum-formed and Hawley retainers offer similar effectiveness. Fixed retainers excel in long-term alignment stability, whereas removable ones have higher failure rates yet remain beneficial.
Stress Intensity Factors for Pressurized Pipes with an Internal Crack: The Prediction Model Based on an Artificial Neural Network
Authors: Seenuan Patchanida , Noraphaiphipaksa Nitikorn , Kanchanomai Chaosuan
Published: October 2023

During pipeline operation, internal cracks may occur. The severity around the crack tip can be quantified by the stress intensity factor (KI), which is a linear–elastic fracture mechanics parameter. For pressurized pipes featuring infinitely long internal surface cracks, KI can be interpolated from a function considering pressure, geometry, and crack size, as presented in API 579-1/ASME FFS-1. To enhance KI prediction accuracy, an artificial neural network (ANN) model was developed for such pressurized pipes. Predictions from the ANN model and API 579-1/ASME FFS-1 were compared with precise finite element analysis (FEA). The ANN model with an eight-neuron sub-layer outperformed others, displaying the lowest mean squared error (MSE) and minimal validation discrepancies. Nonlinear validation data improved both MSE and testing performance compared to uniform validation. The ANN model accurately predicted normalized KI, with differences of 2.2% or lower when compared to FEA results. Conversely, API 579-1/ASME FFS-1′s bilinear interpolation predicted inaccurately, exhibiting disparities of up to 4.3% within the linear zone and 24% within the nonlinearity zone. Additionally, the ANN model effectively forecasted the critical crack size (aC), differing by 0.59% from FEA, while API 579-1/ASME FFS-1′s bilinear interpolation underestimated aC by 4.13%. In summary, the developed ANN model offers accurate forecasts of normalized KI and critical crack size for pressurized pipes, providing valuable insights for structural assessments in critical engineering applications.
Long-Term Dynamics of Persistent Organic Pollutants in Water Bodies of the Aral Sea–Syrdarya Basin
Authors: Amirgaliyev Nariman , Opp Christian , Askarova Maulken , Ismukhanova Laura , Madibekov Azamat , Zhadi Askhat
Published: October 2023

The huge decrease in water volume in the Aral Sea, which was caused predominately by enormous water withdrawals from the Aral Sea tributaries, has changed the former world’s fourth-biggest inland lake into a new desert called Aralkum. Due to its long-term use in agriculture, persistent organic pollutants (POPs), including organochlorine pesticides (OCPs), and polychlorinated biphenyls (PCBs) play a special role in the pollution of the Aral Sea tributaries and in the Aral Sea itself. For the first time, POPs, OCPs, and PCBs were studied in the Large Aral Sea, Small Aral Sea, and the Syrdarya River. PCBs and OCPs in the collected water samples were analyzed using gas chromatography. The results of long-term and inter-annual analyses of POPs in water resources of the Kazakh part of the Aral Sea–Syrdarya Basin are presented. The analyses covered the Large and Small Aral Seas, the Syrdarya River, reservoirs, lakes of the river delta, and drainage water of the collectors from irrigation areas. The inflow to the Syrdarya River that came from the collector–drainage water was the main cause of water pollution. The pollution levels of toxic compounds, including the trends of temporal and spatial changes in pollutant concentrations, were analyzed and assessed. The latest studies from 2021 and 2022 show a decrease in pesticide concentrations by tens and hundreds of times.
Mobilization, Speciation, and Transformation of Organic and Inorganic Contaminants in Soil–Groundwater Ecosystems
Authors: Sheng Yizhi , Jiang Wanjun , Zhang Min
Published: October 2023

The delicate balance of our ecosystems is under threat from the unrelenting release of contaminants into the environment [...]
Cardiac Electrophysiology Meshfree Modeling through the Mixed Collocation Method
Authors: Mountris Konstantinos A. , Pueyo Esther
Published: October 2023

We present the meshfree mixed collocation method (MCM) for cardiac electrophysiology simulation. Capitalizing on the meshfree property of MCM, we introduce an immersed grid approach for automated generation of meshfree node grids from medical image data. This approach allows us to avoid the time-consuming mesh generation and processing that mesh-based methods like the finite element method (FEM) require. We employ the MCM to solve the cardiac monodomain model considering electrical propagation in 2D tissue sheets, 3D tissue slabs, and a realistic biventricular anatomy. We demonstrate that the solutions obtained by the MCM are in good agreement with the FEM, particularly when immersed grid is used. These findings confirm the suitability of the MCM for cardiac electrophysiology simulation and make the MCM a promising alternative to the FEM for cardiac electrical investigations.
Self-Excited Thermoacoustic Instability Behavior of a Hedge Premixed Combustion System with an Asymmetric Air/Fuel Supply or Combustion Condition
Authors: Du Yongbo , Zhang Yuanhang , Li Xiaojin , Zhang Jingkun , Da Yaodong , Jia Yun , Che Defu
Published: October 2023

Self-excited thermoacoustic instability (SETAI) is an undesirable and dangerous phenomenon in combustion systems. However, its control is difficult, thus greatly limiting the development of combustion technology. Our previous works clarified how the premixed chamber length (LP) and equivalence ratio (φ) influence SETAI behavior in a symmetrical hedge premixed combustion system. On real-world sites, however, the supply structure or combustion condition in a multi-flame system could be asymmetric due to space limitations or combustion adjustment needs. This paper aims to clarify the SETAI behavior of a combustion system with an asymmetric supply structure or an asymmetric combustion condition. The results indicate that the sound pressure amplitude under strong oscillation can reach 160 dB, which is about 5% of the total pressure. The SETAI state under the asymmetric condition is determined by the coupling between the heat release oscillation and sound pressure oscillation on each side and their cooperation. The asymmetric supply structure leads to asynchronous heat release oscillations between the two sides; it may be that one promotes oscillation and that the other suppresses it, or that both have a promotion effect but with asynchronous action, thus partly canceling each other out to lower the system’s oscillation intensity. This brings an advantage for controlling SETAI, which can be achieved by only changing one side of the structure. The oscillation amplitude can be reduced by 80–90% by appropriately changing one LP only by ~20%. Under an asymmetric combustion condition with φ differing between the two sides, the heat release oscillation on each side is dependent on the local φ but not the global φ. Consequently, SETAI can also be controlled by changing the distribution but maintaining a constant fuel feeding rate and φ. The concepts identified in this paper demonstrate that SETAI can be effectively controlled by adopting an asymmetric φ distribution or an asymmetric structure of the supply system. This provides a convenient SETAI control approach without affecting the equipment’s thermal performance.
Experimental Study on the Electrical Resistivity Characteristics of Uniformly Graded Calcareous Sand
Authors: Hou Heying , Han Wei , Li Tianxiang , Wang Haiyuan , Du Xiaolong , Liu Zhe , Wang Linhao
Published: October 2023

The resistivity of calcareous sand is one of its inherent physical characteristic parameters, and the study of the resistivity characteristics of calcareous sand is of great significance in the subsequent study of the relationship between the resistivity of calcareous sand under different loads and its mechanical properties. This study uses alternating current (AC) electrical resistance testing equipment based on the two-electrode method to study the effects of pore water, temperature, relative density, saturation, and other factors on the resistivity of calcareous sand. We used the experimental results to analyze in detail the effects of various influencing factors on the resistivity of calcareous sand and established a relationship between them. Research has shown that as the temperature increases, the conductivity of the medium in the solution increases and the resistivity decreases. The resistivity of the calcareous sand of the three size fractions decreases with increasing saturation, and the relationship between them is a power function. The resistivity of saturated calcareous sand with three size fractions increases with increasing density, and the two show a good linear relationship. The results of this research can provide support for the study of the relationship between the resistivity and mechanical properties of calcareous sand under different loads.
Optimization Strategy for Electric Vehicle Routing under Traffic Impedance Guidance
Authors: Li Jingyu , Tian Shiyuan , Zhang Na , Liu Guangchen , Wu Zhaoyuan , Li Wenyi
Published: October 2023

Electric vehicles (EVs) not only serve as significant loads for the power grid but also play a crucial role in the operation of the traffic. Their travel and charging behaviors have an impact on both the power grid and the road network. In order to address the potential impacts of a large-scale deployment of EVs on the power grid and the exacerbation of traffic congestion, this paper first establishes a dynamic road network model based on graph theory and time-varying traffic data combined with a road impedance model. Then, the spatio-temporal distribution characteristics of EV travel are modeled. Furthermore, by incorporating real-time road network data, the traditional Dijkstra’s algorithm for finding the optimal path is improved. At each node, the current real-time road impedance is used as the objective for EV path updates, thus accurately capturing the energy consumption of the EVs. Finally, using a standard testing problem on a typical working day based on data from a real case, the impacts of EV travel and charging behaviors on power distribution network operation and traffic congestion are analyzed under scenarios with no guidance and guidance for the shortest travel time. The results show that this method can significantly reduce the time cost by approximately 18% in travel time, which is of particular concern to users. This method balances the load of the charging stations, elevates the voltage level within the safety requirement of 7%, and simultaneously alleviates traffic congestion near the stations.
Special Issue on Deep Learning for Electroencephalography (EEG) Data Analysis
Authors: Prevete Roberto , Isgrò Francesco , Donnarumma Francesco
Published: October 2023

Brain–computer interfaces (BCI) have emerged as a groundbreaking and transformative technology enabling communication between humans and computers through neural systems, primarily electroencephalography (EEG) [...]