bluuebunny/crossref_metadata_2025_split huggingface dataset:
A theoretical comparison among macroseismic scales used in Italy
Authors: Vannucci Gianfranco , Lolli Barbara , Gasperini Paolo 
Published: October 2023

Abstract

A recent work evidenced some empirical discrepancies between the macroseismic intensity estimates in Italy in the last decade with respect to those made previously. A possible reason might be the progressive adoption by Italian researchers of the European Macroseismic Scale (EMS) in place of the Mercalli Cancani Sieberg (MCS) scale mostly used up to 2009. In theory, in modern settlement where reinforced concrete (RC) buildings are increasingly replacing those in masonry, EMS should overestimate MCS because the former accounts for the lower vulnerability of RC whereas the latter does not because RC buildings were not considered at all by the MCS scale since they were almost absent at the time (1912–1932) when it was compiled by Sieberg. However, such theoretical inference is contradicted by the empirical evidence that, on average, MCS intensities really estimated in Italy over the past decade slightly overestimate EMS and not vice versa as it should be. A possible explanation is that the EMS scale had not been well calibrated to reproduce the MCS, as its authors intended to do. Another possible reason of the discrepancies between the last decade and the previous ones might be that the MCS scale applied today is not the same as that defined by Sieberg at the beginning of XX century. In order to better understand the possible causes of such discrepancies, we present here a formal comparison between the definitions of the different degrees of such macroseismic scales.
Association between physical activity and healthcare costs by weight status in middle age: Evidence from the Northern Finland Birth Cohort 1966
Authors: Junttila Hanna , Vaaramo Mikko , Nerg Iiro , Huikari Sanna , Kari Jaana , Leinonen Anna-Maiju , Nurkkala Marjukka , Korpelainen Raija , Korhonen Marko 
Published: October 2023

Abstract
Objectives
To study the association of physical activity (PA) with individual-level outpatient primary healthcare (PHC) costs in midlife according to body mass index (BMI) categories.
Methods
The study population comprised 4 076 participants from the Northern Finland Birth Cohort 1966. The probability of having PHC costs and the previous year PHC cost levels at age 46 according to BMI and self-reported PA and their joint interactions were estimated using a two-part model. The BMI categories were healthy weight, overweight, and obesity at ages 31 and 46, and weight gain between such ages. The PA categories were inactive and active at ages 31 and 46, and turning inactive and turning active between such ages. The adjusted predicted annual individual-level PHC costs (€) for the combined BMI and PA categories were estimated.
Results
The participants with obesity had a significantly higher probability of having PHC costs (OR = 3.15, 95%CI 1.23–8.02 for females; OR = 3.77, 95%CI 1.31–10.85 for males) than the participants with healthy weight. The participants with obesity (OR = 1.33, 95%CI 1.01–1.75), and those with weight gain (OR = 1.22, 95%CI 1.03–1.44) had significantly higher PHC costs than the participants with healthy weight among females, but not among males. Joint associations of any of the BMI and PA categories with the probability of having PHC costs or cost levels were not found. Among females, the inactive participants with weight gain had 25% higher predicted costs than the inactive participants with healthy weight; and among the participants who turned active, those with weight gain had 65% higher predicted costs than those with healthy weight. Among males with healthy weight, the inactive ones had 38% higher predicted costs than the active participants.
Conclusions
Reaching the current PA recommendations does not mitigate the impact of obesity and weight gain on outpatient PHC costs in midlife.
Adolescent, parent, and provider attitudes toward a machine-learning based clinical decision support system for selecting treatment for youth depression
Authors: Gunlicks-Stoessel Meredith , Liu Yangchenchen , Parkhill Catherine , Morrell Nicole , Choy-Brown Mimi , Mehus Christopher , Hetler Joel , August Gerald 
Published: October 2023

Abstract
Background
Machine-learning based clinical decision support systems (CDSSs) have been proposed as a means of advancing personalized treatment planning for disorders, such as depression, that have a multifaceted etiology, course, and symptom profile. However, machine-learning based models for treatment selection are rare in the field of psychiatry. They have also not yet been translated for use in clinical practice. Understanding key stakeholder attitudes toward machine learning-based CDSSs is critical for developing plans for their implementation that promote uptake by both providers and families.
Methods
In Study 1, a machine-learning based Clinical Decision Support System for Youth Depression (CDSS-YD) was demonstrated to focus groups of adolescents with a diagnosis of depression (n = 9), parents (n = 11), and behavioral health providers (n = 8). Qualitative analysis was used to assess their attitudes towards the CDSS-YD. In Study 2, behavioral health providers were trained in the use of the CDSS-YD and they utilized the CDSS-YD in a clinical encounter with 6 adolescents and their parents as part of their treatment planning discussion. Following the appointment, providers, parents, and adolescents completed a survey about their attitudes regarding the use of the CDSS-YD.
Results
All stakeholder groups viewed the CDSS-YD as an easy to understand and useful tool for making personalized treatment decisions, and families and providers were able to successfully use the CDSS-YD in clinical encounters. Parents and adolescents viewed their providers as having a critical role in the use the CDSS-YD, and this had implications for the perceived trustworthiness of the CDSS-YD. Providers reported that clinic productivity metrics would be the primary barrier to CDSS-YD implementation, with the creation of protected time for training, preparation, and use as a key facilitator.
Conclusions
The CDSS-YD has the potential to be a widely accepted and useful tool for personalized treatment planning. Successful implementation will require addressing the system-level barrier of having sufficient time and energy to integrate it into practice.
An improved adaptive neuro-fuzzy inference framework for Lung Cancer Detection &amp; Prediction on Internet of Medical things platform
Authors: Shabu S. L. Jany , Refonaa J. , Mallik Saurav , Dhamodaran D. , Grace L. K.Joshila , Shah Mohd Asif 
Published: October 2023

Abstract
It has become increasingly difficult for medical practitioners to recognize illness in recent years due to the emergence of new diseases from their myriad causes on a daily basis. Due in large part to inadequate diagnostic and monitoring infrastructure, a substantial amount of illness and death are associated with lung cancer (LC). The aim of the paper is to find lung cancer early and help patients receive curative treatment, quitting smoking or never starting is the best way to mitigate the potential for disease-related death. As a result, cutting-edge detection and monitoring technologies must be developed to enable rapid, accurate, and timely diagnosis. Fuzzy logic (FL) is one of the best approaches to modeling complex and uncertain systems; therefore it helps us deal with these challenges. Fuzzy expert system for lung cancer [FES-LC] detection and prediction on Internet of Medical things (IoMT) is employed to overcome the challenges. Hence enhanced adaptive neuro-fuzzy inference framework [ANF-IF] is proposed in the current research. The cloud-based application of an adaptive neuro-fuzzy inference system yields four risk categories: not at risk, slightly at risk, moderately at risk, and severely at risk. New methods and theoretical frameworks have made it possible to diagnose LC in its earliest stages with the help of magnetic nanoparticles (MNPs), which allow researchers to overcome the limitations of conventionally slow diagnostic efficiency. The proposed system exhibits a precision of 93.4%, accuracy of 95.1%, specificity of 90.6%, sensitivity of 92.8%, False positive rate of 0.22%, false negative ratio of 0.18%, and classification accuracy of 98.2%. The proposed method outperforms all methods and provides better lung cancer detection accuracy than others.
A Catalogue of Structural Variation across Ancestrally Diverse Asian Genomes
Authors: Bertin Nicolas , Tan Joanna , Li Zhihui , Gonzalez-Porta Mar , Rajaby Ramesh , Jimenez Rodrigo , Lim Weng Khong , Tan Ye An , Teo Renyi , Hebrard Maxime , Ow Jack Ling , Ang Shimin , Jeyakani Justin , Chong Yap Seng , Lim Tock Han , Goh Liuh Ling , Tham Yih-Chung , Leong Khai Pang , Chin Calvin , Davila Sonia , Gilmore neer , Cheng Ching-Yu , Chambers John , Tai E Shyong , Liu Jianjun , Sim Xueling , Sung Wing-Kin , Prabhakar Shyam , Tan Patrick , Chai Jin-Fang , Lee Jimmy , Lee Eng Sing , Ngeow Joanne , Elliott Paul , Riboli Elio , Ng Hong Kiat , Mina Theresia , Tay Darwin , Sadhu Nilanjana , Jain Pritesh Rajesh , Low Dorrain , Wang Xiaoyan , Yeo Khung Keong , Cook Stuart Alexander , Pua Chee Jian , Yang Chengxi , Wong Tien , Sabanayagam Charumathi , Raghavan Lavanya , Aung Tin , Chee Miao Ling , Chee Miao , Li Hengtong , Dam Rob van , Teo Yik-Ying , Lim Chia Wei , Tsai Pi Kuang , Chew Wen Jie , Sim Wey Ching , Toh Li-xian Grace , Eriksson Johan , Gluckman Peter , Lee Yung Seng , Yap Fabian , Tan Kok Hian 
Published: October 2023

Abstract
Structural variants (SVs) are significant contributors to inter-individual genetic variation associated with traits and diseases. Current SV studies using whole-genome sequencing (WGS) have a largely Eurocentric composition, with little known about SV diversity in other ancestries particularly from Asia. Here, we present a WGS catalogue of 152,655 SVs from 8,392 Singaporeans of East Asian, Southeast Asian and South Asian ancestries, of which ~75% (113,446 SVs) are novel. We show that Asian populations can be stratified by their global SV patterns and identified 82,003 novel SVs that are specific to Asian populations. 38% of these novel SVs are restricted to one of the three major ancestry groups studied (Indian, Chinese or Malay). We uncovered SVs affecting ACMG-defined clinically actionable loci. Lastly, by identifying SVs in linkage disequilibrium with single-nucleotide variants, we demonstrate the utility of our SV catalogue in the fine-mapping of Asian GWAS variants and identification potential causative variants. These results augment our knowledge of structural variation across human populations, thereby reducing current ancestry biases in global references of genetic variation afflicting equity, diversity and inclusion in genetic research.
Synthetic inlet conditions for inhomogeneous flows from filters, packed beds, or sinter plates
Authors: Baik Seung-Jin , Martins Fabio J. W. A. , Beyrau Frank , Kempf Andreas 
Published: October 2023

Abstract
A practical method is presented to generate inflow boundary conditions for the laminar but spatially inhomogeneous flow out of filters, packed beds, or sinter plates. A synthetic velocity field that statistically reproduces the outflow characteristics is created based on digitally filtered random noise by the integral lengthscale of the investigated flow at a low computational cost. The method is tested to reproduce a real flow downstream of a sinter plate, which has its velocity measured using a hot-wire anemometer. Results demonstrate that the present method can efficiently generate synthetic inflow fields.
Credit card fraud recognition based on width and depth neural networks
Authors: Jiang Shan , Feng Yuming , Liao Xiaofeng , Onasanya B. O. 
Published: October 2023

Abstract
Credit card fraud identification is an important issue in risk prevention and control for banks and financial institutions. In order to establish credit card fraud identification model, This paper studies the feature extraction of fraud identification and the correlation analysis of influencing factors, the basic principles of deep neural network models were studied, and the basic principles of wide neural network models were studied, at the same time. On this basis, this paper proposes a credit card fraud identification model combining width neural network and depth neural network. The model was trained using a random gradient descent method. On the test set, the method proposed in this paper achieved an F1 score of 95.6%, and the method has good fraud identification performance. After comparison, the method proposed in this article is superior to traditional machine learning models such as KNN, decision tree, and Bayesian network.
The PpMYB75-PpDFR module reveals the difference between ‘SR’ and its Bud Variant ‘RMHC’ in Peach Red Flesh
Authors: Xu Chao , Xue Xiaomin , Li Zhixing , Chen Mingguang , Wang Siyu , Yang Yating , Shang Mingrui , Qiu Lei , Zhao Xianyan , Hu Wenxiao 
Published: October 2023

Abstract
‘Red Meat Honey Crisp (RMHC)’ has been widely cultivated by growers in recent years due to its early maturity, and red meat type characteristics. As a bud variant of ‘Super Red (SR)’ peach, red flesh is the most distinctive characteristic of ‘Red Meat Honey Crisp (RMHC)’. However, the mechanism of red flesh formation in ‘RMHC’ remains unclear. In this study, 79 differentially produced metabolites were identified by metabolomics analysis. The anthocyanin content in ‘RMHC’ was significantly higher than that in ‘SR’ during the same period, such as cyanidin O-syringic acid and cyanidin 3-O-glucoside. Other flavonoids also increased during the formation of red flesh, including flavonols (6-hydroxykaempferol-7-O-glucoside, hyperin), flavanols (protocatechuic acid, (+)-gallocatechin), and flavonoids (chrysoeriol 5-O-hexoside, tricetin). In addition, transcriptomic analysis and RT-qPCR showed that the expression levels of the flavonoid synthesis pathway transcription factor MYB75 and some structural genes, such as PpDFR, PpCHS, PpC4H, and PpLDOX increased significantly in ‘RMHC’. Subcellular localization analysis revealed that MYB75 was localized to the nucleus. Yeast single hybridization assays showed that MYB75 bound to the cis-acting element CCGTTG of the PpDFR promoter region. The MYB75-PpDFR regulatory network was identified to be a key pathway in the reddening of ‘RMHC’ flesh. Moreover, this is the first study to describe the cause for red meat reddening in ‘RMHC’ compared to ‘SR’ peaches using transcriptomics, metabolomics and molecular methods. Our study identified a key transcription factor involved in the regulation of the flavonoid synthetic pathway and contributes to peach breeding-related efforts as well as the identification of genes involved in color formation in other species.
HDAC6-selective inhibitor CAY10603 ameliorates cigarette smoke-induced small airway remodeling by regulating epithelial barrier dysfunction and reversing EMT
Authors: Zhang Qin , Yan Liming , Lu Ye , Liu Xiaodong , Yin Yan , Wang Qiuyue , Gu Xiu , Zhou Xiaoming 
Published: October 2023

Abstract
Background: Small airway remodeling is one of the vital characteristics of chronic obstructive pulmonary disease (COPD), which is mainly caused by epithelial barrier dysfunction and epithelial mesenchymal transition (EMT). Recent studies have indicated that Histone deacetylase 6 (HDAC6) plays an important role in epithelial function and dysregulation. In this study, we investigated the therapeutic effect of an inhibitor with high selectivity for HDAC6 on COPD and its mechanism.
Methods: Cigarette smoke (CS) exposure was used to establish a CS-induced COPD mouse model. CAY10603 at doses of 2.5 and 10 mg/kg was injected intraperitoneally on alternate days. The protective effects of CAY10603 on the morphology of CS-induced emphysema, epithelial barrier function and small airway remodeling were evaluated using Hematoxylin-eosin (H&E) staining, Masson trichrome (MT) staining, immunohistochemical staining, and western blot. Human lung bronchial epithelial cell line (HBE) was used to elucidate the underlying molecular mechanism of CAY10603.
Results: Compared to the CS group, the mean linear intercept (MLI) of CAY10603 treatment groups was decreased and mean alveolar number (MAN) was increased. Collagen deposition was reduced in the groups with CAY10603 treatment. The expression of α-SMA was markedly upregulated in the CS group, which could be reversed by CAY10603 treatment. Conversely, expression of E-cadherin in CS group was further downregulated and was reversed by CAY10603 treatment. CAY10603 could affect tight junction protein expression of ZO-1 and Occludin. The expressions of ZO-1 and Occludin were markedly downregulated in the CS group. After CAY10603 intervention, the protein expression level of ZO-1 and Occludin increased significantly. In HBE cells, CAY10603 significantly attenuated the E-cadherin levels induced by TGF-β1, while concurrently increasing α-SMA expression. This effect was achieved through the suppression of Smad2 and Smad3 phosphorylation. Furthermore, CAY10603 inhibited the TGF-β1-induced cell migration. CAY10603 could reverse EMT by regulating TGF-β1 pathway and improve CS-exposed emphysema in mice.
Conclusions: These findings suggested that CAY10603 inhibited cigarette smoke induced small airway remodeling by regulating epithelial barrier dysfunction and reversing EMT via TGF-β1/Smad2/3 signaling pathway.
Amide proton transfer weighted imaging and diffusion kurtosis imaging in differentiating malignant from benign breast tumors compared with BI-RADS
Authors: Ma Yingying , Wang Peng , Shao Lin , Ge Yuxi , Qiao Hongyan , Yang Xiao , Hu shudong 
Published: October 2023

Abstract

Background: The present study aims to evaluate the diagnostic performance of amide proton transfer weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) in terms of differentiating malignant from benign breast lesions and to compare them with the Breast Imaging Reporting and Data System (BI-RADS) independently or jointly.
Methods: In this prospective study, participants with no previous treatment and lesions larger than 10 mm were enrolled from September 2022 to June 2023. All participants underwent APTWI and DKI preoperatively. The APTWI derived MTRasym and DKI parameters of mean kurtosis (MK) and mean diffusivity (MD) values were measured independently by two radiologists. The BI-RADS was scored by another two radiologists. Receiver operating characteristic (ROC) curves were separately generated to evaluate the diagnostic performance of each individual parameter and the combination of all parameters. Pathologic analysis results were used as the gold standard.
Results:Totally, 67 participants (48 malignant lesions vs. 19 benign lesions) were evaluated. Malignant lesions showed higher MTRasym value, lower MD value and higher MK value than benign lesions. The resultant areas under the ROC curves (AUC) were 0.836 for MTRasym, 0.970 for MD, 0.905 for MK, and 0.690 for BI-RADS in differentiating malignant from benign breast lesions. Moreover, with the combination of quantitative parameters of the two quantitative MRI techniques, the diagnostic performance and specificity of BI-RADS were improved.
Conclusion: APTWI and DKI have been demonstrated as potentially promising quantitative techniques for distinguishing the characteristics of breast lesions and may augment the diagnostic performance of BI-RADS.
Revolutionizing Drilling Operations: Unveiling the Power of Advanced Ultrasound Technologies for Integrity Inspection of Drilling Risers
Authors: Beltrão Bruno D'Almeida , Ferreira Carlos Alberto Martins , Antonio Marcelo Musci Musci Zaib 
Published: October 2023

Abstract
Integrity inspection is crucial in ensuring drilling risers’ reliable operation in the offshore oil and gas industry. This article explores the application of advanced ultrasound technologies, specifically Phased Array and Time of Flight Diffraction (TOFD), for inspecting drilling risers. Traditional inspection methods, such as visual, magnetic particle testing and conventional ultrasound, have limitations in detecting and characterising internal defects. In contrast, Phased Array and TOFD offer enhanced accuracy, sensitivity, and coverage capabilities. The article delves into Phased Array and TOFD principles and mechanisms, highlighting their advantages over conventional ultrasound by using these advanced ultrasound techniques to inspect welds, corrosion, and other potential integrity issues in riser components. Additionally, it addresses the challenges associated with inspecting fully assembled risers and presents solutions to overcome them. Furthermore, the article presents case studies demonstrating the effectiveness of Phased Array and TOFD in identifying critical defects, such as fatigue cracks and wall thinning. It emphasises the importance of a comprehensive inspection strategy combining multiple techniques to assess drilling riser integrity comprehensively. Lastly, the article discusses the integration of advanced ultrasound technologies into existing inspection programs, including considerations for equipment selection, personnel training, and data analysis. Overall, this article highlights the significant advancements made in the integrity inspection of drilling risers through the use of advanced ultrasound technologies. It underscores the potential for improved safety, reduced inspection time, logistics and enhanced operational efficiency in the offshore drilling industry.
The post-treatment follow-up compliance related factors and relationship with survival in stage Ⅱ/Ⅲ colorectal cancer patients
Authors: He Xiaofeng , Wen Feng , Lv Min , Du Xuemei , He Jun , Yang Yang , Yuan Jin , Tang Dan , Li Qiu 
Published: October 2023

Abstract
Purpose: There is no standard precise surveillance strategy for stage Ⅱ/Ⅲ colorectal cancer (CRC) patients after curative treatment and patient’ adherence varies significantly. This study aimed to assess the associated factors and relationship with survival in CRC patients after radical therapy.
Methods: Stage Ⅱ/Ⅲ CRC patients with curative therapy between January 2016 and December 2021 were retrospectively collected. Univariate and multivariable analyses were used to evaluate the associated variables. Kaplan-Meier survival analysis was used to explore the survival benefits.
Results: A total of 662 CRC patients after curative therapies were collected, and 477 patients were eligible. Median follow-up time was 46 months. The 3-year follow-up compliance was 38.8%. Medical insurance, educational attainment, and adjuvant therapy were independently associated with follow-up compliance (P < 0.05). There was a trend of disease-free survival (DFS) (P = 0.085) and overall survival (OS) (P= 0.080) benefit in patients with good follow-up compliance. And in the subgroup analysis of age under 65 group, patients with good follow-up compliance got a statistically significant survival benefits for DFS (P = 0.009) and OS (P = 0.014). However, there was no survival benefit in patients with intensive follow-up.
Conclusions: The follow-up compliance in stage Ⅱ/Ⅲ CRC patients following their curative treatment was generally poor, and medical insurance, education as well as adjuvant therapy were the main influence factors. Good follow-up compliance yielded a survival benefit in patients under 65 years old. However, intensive follow-up did not result in survival benefits in stage Ⅱ/Ⅲ CRC patients.