bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms
Authors: Zulueta Mirella , Gallardo-Rincón Héctor , Martinez-Juarez Luis Alberto , Lomelin-Gascon Julieta , Ortega-Montiel Janinne , Montoya Alejandra , Mendizabal Leire , Arregi Maddi , Martinez-Martinez María de los Angeles , Camarillo Romero Eneida del Socorro , Mendieta Zerón Hugo , Garduño García José de Jesús , Simón Laureano , Tapia-Conyer Roberto
Published: April 2023

Introduction

Gestational diabetes mellitus (GDM) is underdiagnosed in Mexico. Early GDM risk stratification through prediction modeling is expected to improve preventative care. We developed a GDM risk assessment model that integrates both genetic and clinical variables.

Research design and methods

Data from pregnant Mexican women enrolled in the ‘Cuido mi Embarazo’ (CME) cohort were used for development (107 cases, 469 controls) and data from the ‘Mónica Pretelini Sáenz’ Maternal Perinatal Hospital (HMPMPS) cohort were used for external validation (32 cases, 199 controls). A 2-hour oral glucose tolerance test (OGTT) with 75 g glucose performed at 24–28 gestational weeks was used to diagnose GDM. A total of 114 single-nucleotide polymorphisms (SNPs) with reported predictive power were selected for evaluation. Blood samples collected during the OGTT were used for SNP analysis. The CME cohort was randomly divided into training (70% of the cohort) and testing datasets (30% of the cohort). The training dataset was divided into 10 groups, 9 to build the predictive model and 1 for validation. The model was further validated using the testing dataset and the HMPMPS cohort.

Results

Nineteen attributes (14 SNPs and 5 clinical variables) were significantly associated with the outcome; 11 SNPs and 4 clinical variables were included in the GDM prediction regression model and applied to the training dataset. The algorithm was highly predictive, with an area under the curve (AUC) of 0.7507, 79% sensitivity, and 71% specificity and adequately powered to discriminate between cases and controls. On further validation, the training dataset and HMPMPS cohort had AUCs of 0.8256 and 0.8001, respectively.

Conclusions

We developed a predictive model using both genetic and clinical factors to identify Mexican women at risk of developing GDM. These findings may contribute to a greater understanding of metabolic functions that underlie elevated GDM risk and support personalized patient recommendations.
Effect of the interaction between advanced maternal age and pre-pregnancy BMI on pre-eclampsia and GDM in Central China
Authors: Sun Mengting , Luo Manjun , Wang Tingting , Wei Jianhui , Zhang Senmao , Shu Jing , Zhong Taowei , Liu Yiping , Chen Qian , Zhu Ping , Qin Jiabi
Published: April 2023

Introduction

To investigate the independent and combined effects of advanced maternal age and pre-pregnancy body mass index (BMI) on the risk of pre-eclampsia and gestational diabetes mellitus (GDM).

Research design and methods

Logistic regression models were used to estimate the OR and 95% CIs of pre-eclampsia and GDM with advanced maternal age and pre-pregnancy BMI, respectively, and the interaction between advanced maternal age and pre-pregnancy BMI. We also used causal mediation analysis to assess the mediating role of pre-pregnancy BMI on maternal age–pre-eclampsia/GDM associations.

Results

In this study, 788 cases (2.31%) were diagnosed with pre-eclampsia and 5430 cases (15.92%) were diagnosed with GDM. We found that advanced maternal age was associated with a higher risk for pre-eclampsia and GDM, with adjusted ORs (aORs) of 1.74 (95% CI 1.49–2.05) and 1.76 (95% CI 1.65–1.89) after adjusting for potential confounders, respectively. In addition, maternal pre-pregnancy overweight/obesity was associated with the risk of pre-eclampsia and GDM, with the corresponding aORs of 3.64 (95% CI 3.12–4.24) and 1.71 (95% CI 1.60–1.85), respectively. We also observed the interaction between maternal age and pre-pregnancy BMI for the risk of pre-eclampsia/GDM (all p for interaction <0.001). In the mediating effect analysis, we found that maternal pre-pregnancy BMI mediated the associations between maternal age and the development of pre-eclampsia and GDM.

Conclusions

Advanced maternal age and pre-pregnancy BMI were respectively associated with the risk of pre-eclampsia/GDM, and there was an interaction between the two risk factors. In addition, we found that pre-pregnancy BMI served as a mediator of the association between advanced maternal age and the risk of pre-eclampsia/GDM, providing an essential target for the prevention of maternal overweight/obesity.
First reports of clinical effects of transjugular intrahepatic portosystemic shunt in four patients with cirrhotic ascites refractory to tolvaptan
Authors: Tsuruya Kota , Koizumi Jun , Sekiguchi Yuka , Ono Shun , Sekiguchi Tatsuya , Hara Takuya , Mishima Yusuke , Arase Yoshitaka , Hirose Shunji , Shiraishi Koichi , Kagawa Tatehiro
Published: April 2023

Objective

Ascites in patients with decompensated cirrhosis can lead to abdominal distention and decrease quality of life. Tolvaptan, a vasopressin V2 receptor antagonist, is an effective agent in the treatment of ascites, whereas some patients are refractory to tolvaptan. The efficacy of transjugular intrahepatic portosystemic shunt (TIPS) for these patients is not known. In this study, we performed TIPS for tolvaptan-refractory cirrhotic patients and analysed its efficacy and safety in these patients.

Design

This retrospective analysis included patients with liver cirrhosis who received TIPS for ascites or hydrothorax refractory to tolvaptan therapy along with conventional diuretics between January 2015 and May 2018 at Tokai University Hospital. We evaluated the efficacy and safety of TIPS.

Results

This study included four patients. All patients presented with Child-Pugh class B liver cirrhosis and model for end-stage liver disease-sodium scores were 10/12/14/16. TIPS was generated successfully without any major complications in all patients. The body weight decreased by a mean of 4.7 (SD=1.0) kg and estimated glomerular filtration rate improved from a mean of 38.2 (SD=10.3) to 59.5 (SD=25.0) mL/min/1.73 m2in a month after TIPS procedure.

Conclusion

TIPS is an effective potential treatment for ascites in patients with tolvaptan refractory condition. In appropriate patients who can tolerate TIPS, the treatment may lead towards renal function improvement.
The WHO’s 75th anniversary: WHO at a pivotal moment in history
Authors: Gostin Lawrence O , Chirwa Danwood Mzikenge , Clark Helen , Habibi Roojin , Kümmel Björn , Mahmood Jemilah , Meier Benjamin Mason , Mpanju-Shumbusho Winnie , Reddy K Srinath , Waris Attiya , Were Miriam K
Published: April 2023

The World Health Organisation (WHO) was inaugurated in 1948 to bring the world together to ensure the highest attainable standard of health for all. Establishing health governance under the United Nations (UN), WHO was seen as the preeminent leader in public health, promoting a healthier world following the destruction of World War II and ensuring global solidarity to prevent disease and promote health. Its constitutional function would be ‘to act as the directing and coordinating authority on international health work’. Yet today, as the world commemorates WHO’s 75th anniversary, it faces a historic global health crisis, with governments presenting challenges to its institutional legitimacy and authority amid the ongoing COVID-19 pandemic. WHO governance in the coming years will define the future of the Organisation and, crucially, the health and well-being of billions of people across the globe. At this pivotal moment, WHO must learn critical lessons from its past and make fundamental reforms to become the Organisation it was meant to be. We propose reforms in WHO financing, governance, norms, human rights and equity that will lay a foundation for the next generation of global governance for health.
Experiences and support needs of informal long-distance caregivers at the end of life: a scoping review
Authors: Ülgüt Rojda , Stiel Stephanie , Herbst Franziska A
Published: April 2023

Objectives

There is a lack of research on the specific experiences and needs of geographically distant kin caregivers in end-of-life situations. Clinicians and researchers would benefit from a systematic overview. The scoping review aimed at examining the international literature on the experiences and needs of informal long-distance (LD) caregivers at the end of life, to address gaps in the evidence base, and to make recommendations for further research.

Design

The scoping review was conducted according to the methodological framework of Arksey and O’Malley. Studies of various designs involving kin caregivers were analysed narratively.

Data sources

A highly sensitive strategy was used to search CINAHL, Google Scholar, PsycInfo, PubMed and Web of Science Core Collection, from inception to 8 November 2021, with searches rerun in CINAHL, PsycInfo and PubMed on 31 January 2023. An additional hand search of the reference lists of the identified articles was performed.

Results

Two authors independently assessed the titles and abstracts of 3827 scientific papers. As a result, 89 full texts were reviewed and 20 articles plus one review were included in the review. Five major themes were identified: (1) LD as a barrier to caregiving, (2) communication difficulties and the role of video and telephone calls, (3) the burdens and benefits of LD caregiving, (4) interaction and conflict with local caregivers and (5) LD caregivers’ wishes and needs for support.

Conclusions

Further quantitative and mixed-methods studies should be undertaken to improve our understanding of LD caregiving for relatives at the end of life. Studies to explore the feasibility and implementation of communication technologies in end-of-life LD caregiving are also needed.
Effectiveness of interventions designed to mitigate the negative health outcomes of informal caregiving to older adults: an umbrella review of systematic reviews and meta-analyses
Authors: Kirvalidze Mariam , Abbadi Ahmad , Dahlberg Lena , Sacco Lawrence B , Morin Lucas , Calderón-Larrañaga Amaia
Published: April 2023

Objectives

This umbrella review aimed to evaluate whether certain interventions can mitigate the negative health consequences of caregiving, which interventions are more effective than others depending on the circumstances, and how these interventions are experienced by caregivers themselves.

Design

An umbrella review of systematic reviews was conducted.

Data sources

Quantitative (with or without meta-analyses), qualitative and mixed-methods systematic reviews were included.

Eligibility criteria

Reviews were considered eligible if they met the following criteria: included primary studies targeting informal (ie, unpaid) caregivers of older people or persons presenting with ageing-related diseases; focused on support interventions and assessed their effectiveness (quantitative reviews) or their implementation and/or lived experience of the target population (qualitative reviews); included physical or mental health-related outcomes of informal caregivers.

Data extraction and synthesis

A total of 47 reviews were included, covering 619 distinct primary studies. Each potentially eligible review underwent critical appraisal and citation overlap assessment. Data were extracted independently by two reviewers and cross-checked. Quantitative review results were synthesised narratively and presented in tabular format, while qualitative findings were compiled using the mega-aggregation framework synthesis method.

Results

The evidence regarding the effectiveness of interventions on physical and mental health outcomes was inconclusive. Quantitative reviews were highly discordant, whereas qualitative reviews only reported practical, emotional and relational benefits. Multicomponent and person-centred interventions seemed to yield highest effectiveness and acceptability. Heterogeneity among caregivers, care receivers and care contexts was often overlooked. Important issues related to the low quality of evidence and futile overproduction of similar reviews were identified.

Conclusions

Lack of robust evidence calls for better intervention research and evaluation practices. It may be warranted to avoid one-size-fits-all approaches to intervention design. Primary care and other existing resources should be leveraged to support interventions, possibly with increasing contributions from the non-profit sector.

PROSPERO registration number

CRD42021252841; BMJ Open: doi:10.1136/bmjopen-2021-053117.
Effects of a management team training intervention on the compliance with a surgical site infection bundle: a before–after study in operating theatres in the Netherlands
Authors: van Dijk Manon D , van Beeck Ed F , Huis Anita , van der Gun Bernardina TF , Polinder Suzanne , van Eijsden Rianne AM , Burdorf Alex , Vos Margreet C , Erasmus Vicki
Published: April 2023

Objectives

To assess the effects of a quality improvement (QI) team training intervention, by measuring the intervention fidelity and the compliance with a surgical site infection (SSI) bundle in the operating theatre (OT).

Design

Multicentre before–after study.

Setting

This study was performed in four Dutch hospitals.

Intervention

The QI team training intervention consisted of four sessions per hospital and stimulated participants to set culture norms and targets, identify barriers, and formulate management activities to improve compliance with four standard operating procedures (SOPs) of a SSI bundle in the OT. Participants were executive board members, top-level managers, leading clinicians and support staff. The four SOPs were: (1) reducing door movements; (2) preoperative antibiotic prophylaxis prescribing; (3) preoperative shaving; and (4) postoperative normothermia.Poissonand logistic regression analyses were performed to analyse the effect of the intervention on compliance with the individual SOPs (primary outcome measure) and on the influence of medical specialty, time of day the procedure took place and time in the OT (secondary outcome measures).

Results

Not all management layers were successfully involved during all sessions in the hospitals. Top-level managers were best represented in all hospitals, leading clinicians the least. The number of implemented improvement activities was low, ranging between 2 and 14. The team training intervention we developed was not associated with improvements in the compliance with the four SOP of the SSI bundle. Medical specialty, time of day, and time in OT were associated with median number of door movements, and preoperative antibiotic prophylaxis administration.

Conclusion

This study showed that after the QI team training intervention the overall compliance with the four SOPs did not improve. Minimal involvement of leading clinicians and a low number of self-initiated activities after the team training were important barriers for compliance.
Colombian Ocular Diseases Epidemiology Study (CODES): incidence and sociodemographic characterisation of keratoconus between 2015 and 2020
Authors: Mejia-Salgado Germán , Cifuentes-González Carlos , Rojas-Carabali William , Zarate-Pinzón Laura , Peña-Pulgar Luisa Fernanda , Polania Diego , Cruz-Reyes Danna Lesley , de-la-Torre Alejandra
Published: April 2023

Objective

To estimate the incidence and describe the demographic characteristics of keratoconus (KC) in Colombia using national health registry data between January 1st 2015 and December 31th 2020.

Methods and analysis

We conducted a nationwide, population-based study using the Integrated Social Protection Information System from the Colombian Ministry of Health, the unique official database in the country. We used the International Classification of Diseases code for KC (H186) to identify the number of new cases of KC and estimate the incidence rates both overall and according to age and sex. We made a standard morbidity ratio map to graph Colombia’s morbidity risk of KC onset.

Results

Of 50 372 424 subjects, 21 710 had KC between 2015 and 2020. However, due to the COVID-19 pandemic, all the incidence rates of this study were based on the 18 419 reported until 2019. The incidence rate in the general population was 10.36 (95% CI 10.08 to 10.64) per 100 000 inhabitants. The incidence peak among males was in their early 20s and females in their late 20s. The overall male to female incidence rate ratio was 1.60. Regarding the distribution of the disease, most cases were reported in Bogotá (48.64%), Antioquia (14.04%) and Cundinamarca (10.38%).

Conclusion

We performed the first nationwide, population-based study of KC in Latin America, finding distribution patterns similar to those reported in the literature. This study provides valuable information on the epidemiology of KC in Colombia, which is helpful in the development of policies for the diagnosis, prevention and treatment of the disease.
Impact of prophylactic and ‘rescue pack’ antibiotics on the airway microbiome in chronic lung disease
Authors: Rofael Sylvia A D , Brown James , Lipman Marc C I , Lowe David M , Spratt David , Quaderi Shumonta , Hurst John R , McHugh Timothy D
Published: April 2023

The management of many chronic lung diseases involves multiple antibiotic prescriptions either to treat acute exacerbations or as prophylactic therapy to reduce the frequency of exacerbations and improve patients’ quality of life.

Aim

To investigate the effects of antibiotics on the homeostasis of bacterial communities in the airways, and how this may contribute to antimicrobial resistance (AMR) among respiratory pathogens and microbiota.

Methods

Within an observational cohort study, sputum was collected from 84 patients with chronic obstructive pulmonary disease and/or bronchiectasis at stable state: 47 were receiving antibiotic prophylaxis therapy. V3-V4 16S-rRNA sequencing on Illumina MiSeq, quantitative PCR for typical respiratory pathogens, bacteriology cultures and antimicrobial susceptibility testing of sputum isolates, resistome analysis on a subset of 17 sputum samples using MinION metagenomics sequencing were performed.

Finding

The phylogenetic α-diversity and the total bacterial density in sputum were significantly lower in patients receiving prophylactic antibiotics (p=0.014 and 0.029, respectively). Antibiotic prophylaxis was associated with significantly lower relative abundance of respiratory pathogens such asPseudomonas aeruginosa,Moraxella catarrhalisand members of family Enterobacteriaceae in the airway microbiome, but notHaemophilus influenzaeandStreptococcus pneumoniae. No major definite directional shifts in the microbiota composition were identified with prophylactic antibiotic use at the cohort level. Surveillance of AMR and resistome analysis revealed a high frequency of resistance to macrolide and tetracycline in the cohort. AMR expressed by pathogenic bacterial isolates was associated with antibiotics prescribed as ‘rescue packs’ for prompt initiation of self-treatment of exacerbations (Spearman’s rho=0.408, p=0.02).

Conclusions

Antibiotic prophylactic therapy suppresses recognised pathogenic bacteria in the sputum of patients with chronic lung disease. The use of antibiotic rescue packs may be driving AMR in this cohort rather than prophylactic antibiotics.
Dissecting tumor lymphocyte infiltration to predict benefit from immune-checkpoint inhibitors in metastatic colorectal cancer: lessons from the AtezoT RIBE study
Authors: Moretto Roberto , Rossini Daniele , Catteau Aurélie , Antoniotti Carlotta , Giordano Mirella , Boccaccino Alessandra , Ugolini Clara , Proietti Agnese , Conca Veronica , Kassambara Alboukadel , Pietrantonio Filippo , Salvatore Lisa , Lonardi Sara , Tamberi Stefano , Tamburini Emiliano , Poma Anello Marcello , Fieschi Jacques , Fontanini Gabriella , Masi Gianluca , Galon Jérôme , Cremolini Chiara
Published: April 2023

Background

Tumor immune cells influence the efficacy of immune-checkpoint inhibitors (ICIs) and many efforts aim at identifying features of tumor immune microenvironment able to predict benefit from ICIs in proficient mismatch repair (pMMR)/microsatellite stable (MSS) metastatic colorectal cancer (mCRC).

Methods

We characterized tumor immune cell infiltrate, by assessing tumor-infiltrating lymphocytes (TILs), Immunoscore, Immunoscore-IC, and programmed death ligand-1 (PD-L1) expression in tumor samples of patients with mCRC enrolled in the AtezoTRIBE study, a phase II randomized trial comparing FOLFOXIRI/bevacizumab/atezolizumab to FOLFOXIRI/bevacizumab, with the aim of evaluating the prognostic and predictive value of these features.

Results

Out of 218 patients enrolled, 181 (83%), 77 (35%), 157 (72%) and 162 (74%) specimens were successfully tested for TILs, Immunoscore, Immunoscore-IC and PD-L1 expression, respectively, and 69 (38%), 45 (58%), 50 (32%) and 21 (13%) tumors were classified as TILs-high, Immunoscore-high, Immunoscore-IC-high and PD-L1-high, respectively. A poor agreement was observed between TILs and Immunoscore or Immunoscore-IC (K of Cohen <0.20). In the pMMR population, longer progression-free survival (PFS) was reported for Immunoscore-high and Immunoscore-IC-high groups compared with Immunoscore-low (16.4 vs 12.2 months; HR: 0.55, 95% CI: 0.30 to 0.99; p=0.049) and Immunoscore-IC-low (14.8 vs 11.5 months; HR: 0.55, 95% CI: 0.35 to 0.85; p=0.007), respectively, with a significant interaction effect between treatment arms and Immunoscore-IC (p for interaction: 0.006) and a trend for Immunoscore (p for interaction: 0.13). No PFS difference was shown according to TILs and PD-L1 expression. Consistent results were reported in the overall population.

Conclusions

The digital evaluation of tumor immune cell infiltrate by means of Immunoscore-IC or Immunoscore identifies the subset of patients with pMMR mCRC achieving more benefit from the addition of the anti-PD-L1 to the upfront treatment. Immunoscore-IC stands as the most promising predictor of benefit from ICIs.
Histone chaperone SSRP1 is required for apoptosis inhibition and mitochondrial function in HCC via transcriptional promotion of TRAP1
Authors: Chen Xuyang , Li Mengxin , Wang Ding , Wang Qian , Wei Xiaodong , Liu Xiaorui , Yang Jiaying , Kalvakolanu Dhan V. , Guo Baofeng , Zhang Ling
Published: April 2023

Epigenetic regulation contributes to human health and disease, especially cancer, but the mechanisms of many epigenetic regulators remain obscure. Most research is focused on gene regulatory processes, such as mRNA translation and DNA damage repair, rather than the effects on biological functions like mitochondrial activity and oxidative phosphorylation. Here, we identified an essential role for the histone chaperone structure-specific recognition protein 1 (SSRP1) in mitochondrial oxidative respiration in hepatocellular carcinoma, and found that SSRP1 suppression led to mitochondrial damage and decreased oxidative respiration. Further, we focused on TNF receptor-associated protein 1 (TRAP1), the only member of the heat shock protein 90 (HSP90) family, which directly interacts with selected respiratory complexes and affects their stability and activity. We confirmed that SSRP1 downregulation caused a decrease in TRAP1 expression at both the mRNA and protein levels. A chromatin immunoprecipitation assay also showed that SSRP1 could deposit in the TRAP1 promoter region, indicating that SSRP1 maintains mitochondrial function and reactive oxygen species levels through TRAP1. Additionally, rescue experiments and animal experiments confirmed the mechanism of SSRP1 and TRAP1 interaction. In summary, we identified a new mechanism that connects mitochondrial respiration and apoptosis, via SSRP1.
A new model developed by multigene genetic programming for the temporal evolution of bridge pier scour
Authors: Zhang Wenjun , Rennie Colin D. , Nistor Ioan
Published: April 2023

Forecasting the time development of scour depth at bridge pier foundations is of great significance to mitigate or avoid the potential failure of bridges. Presently, several models have been developed to predict the scour depth at the base of bridge piers in the case of flood events. This study summarizes existing models for the temporal evolution of bridge pier scour and divides these studies into semiempirical models and empirical models, as well as artificial intelligence models. Several experimental data sets collected from previous studies, 665 points in total, are used to develop a new multigene genetic programming (MGGP) model for temporal scour depth at a circular bridge pier. In addition, independent data, 899 points in total, from previous studies and new physical modeling tests are applied to evaluate the behaviours of existing models, as well as the newly developed MGGP model. It is shown that the MGGP model has good prediction capability when compared with existing empirical and mathematical models.
An endophytic fungus Schizophyllum commune isolated from Panax ginseng enhances hairy roots growth and ginsenoside biosynthesis
Authors: Xie Xing-Guang , Zhang Zhen-Zhen , Chen Ling , Ming Qian-Liang , Sheng Ke-Xin , Chen Xi , Rahman Khalid , Feng Kun-Miao , Su Juan , Han Ting
Published: April 2023

Using endophytic fungal elicitors to increase the accumulation of valuable secondary metabolites in plant tissue culture is an effective biotechnology strategy. In this study, a collection of 56 strains of endophytic fungi were isolated from different organs of cultivated Panax ginseng, of which seven strains can be symbiotically co-cultured with the hairy roots of P. ginseng. Further experiments observed that strain 3R-2, identified as endophytic fungus Schizophyllum commune, can not only infect hairy roots but also promote the accumulation of specific ginsenosides. This was further verified because S. commune colonization significantly affected the overall metabolic profile of ginseng hairy roots. By comparing the effects of S. commune mycelia and its mycelia extract (EM) on ginsenoside production in P. ginseng hairy roots, the EM was confirmed to be a relatively better stimulus elicitor. Additionally, the introduction of EM elicitor can significantly enhance the expressions of key enzyme genes of pgHMGR, pgSS, pgSE, and pgSD involved in the biosynthetic pathway of ginsenosides, which was deemed the most relevant factor for promoting ginsenosides production during the elicitation period. In conclusion, this study is the first to show that the EM of endophytic fungus S. commune can be considered as an effective endophytic fungal elicitor for increasing the biosynthesis of ginsenosides in hairy root cultures of P. ginseng.
Structural properties of anisotropic stars in modified teleparallel gravity: a brief study via an embedding approach
Authors: Ashraf Asifa , Errehymy Abdelghani , Ditta Allah , Zhang Zhiyue , Tiecheng Xia , Daoud Mohammed
Published: April 2023

In this paper, we attempt to construct the anisotropic solution for compact stellar configurations using the observed mass and radius of compact stars from the literature under the influence of Rastall Teleparallel gravity. To investigate the crucial elements of spherically symmetric metric space, we employed the embedding class one spacetime paradigm with Karmarkar’s condition. The field equations have been computed under the gravitational action of Rastall Teleparallel gravity. However, the unknown constants were evaluated via junction conditions using the Schwarzschild metric as the outer geometry. The compact stars analysis’s crucial physical and mathematical requirements are all admitted and shared by the model, which is physically viable and supports the emergence of novel realistic stellar configurations in Rastall Teleparallel gravity. We fix the parameters of our model to compare with three compact stars (LMC X-4, Cen X-3, and EXO 1785-248) and find that it can be regular, robust, and stable.
Cryogenic ion mobility-mass spectrometry for the study of conformations of host-guest complexes
Authors: Ohshimo Keijiro , He Xi , Ito Ryosuke , Tsunoda Kengo , Tainaka Sota , Misaizu Fuminori
Published: April 2023

Variable-temperature cryogenic ion mobility-mass spectrometry (VT-Cryo-IM-MS) was developed to examine the conformations of host-guest complexes. The VT-Cryo-IM-MS consists of an electrospray ionization source, a quadrupole ion trap, a cryogenic ion drift tube, and a time-of-flight mass spectrometer. The ion drift tube was cooled to 83 K with liquid nitrogen. Two sets of ion funnels are installed at the source and the drift tube to focus the ion beam. We used Li+-encapsulated fullerene (Li+@C60) as a reference ion to examine the ion-mobility resolution of the VT-Cryo-IM-MS apparatus because this ion has a rigid structure with a single conformer. The temperature dependence of collision cross section (CCS) of Li+@C60and the resolution of the apparatus were determined at each temperature. We examined the conformations of host-guest complexes of a series of metal ions (M = Ca2+, Na+, Ag+, K+, Rb+, and Cs+) with dibenzo-24-crown-8 (DB24C8) by Cryo-IM-MS. All CCS distributions were fitted with two Gaussian functions which are assigned to closed and open conformers. These closed and open conformers have different distances between the two benzene rings of DB24C8. The abundance ratio of closed conformers for these M(DB24C8) complex ions depends on the guest M ion with an order, Ca2+ < Na+ < Ag+ < Cs+ < Rb+ < K+. The stability of the closed conformer of K+(DB24C8) originates from the benzene ring positional relationship which is quite close to that of the free benzene dimer. This special benzene dimer-like conformation produces the strongπ-πinteraction between the benzene rings of K+(DB24C8).
A novel multi-level image segmentation algorithm via random opposition learning-based Aquila optimizer
Authors: Cai Jia , Luo Tianhua , Xiong Zhilong , Tang Yi
Published: April 2023

Aquila optimizer (AO) is an efficient meta-heuristic optimization method, which mimics the hunting style of Aquila in nature. However, the AO algorithm may suffer from immature convergence during the exploitation stage. In this paper, two strategies are elegantly employed into conventional AO, such as random opposition-based learning and nonlinear flexible jumping factor, which can efficiently enhance the performance of conventional AO. Experiments on [Formula: see text] benchmark functions and image segmentation demonstrate the effectiveness of the proposed algorithm. Comparison with several state-of-the-art meta-heuristic optimization techniques indicates the efficacy of the developed method.
Visual-Inertial-Laser SLAM Based on ORB-SLAM3
Authors: Cao Meng , Zhang Jia , Chen Wenjie
Published: April 2023

At present, visual simultaneous localization and mapping is a hot topic in the field of unmanned systems, which is popular among academic workers because of its advantages of accurate localization, low cost, large amount of information, and wide range of applications, but it still has some problems, including the camera’s vulnerability to the number of feature points and the noise impact of the inertial measurement unit during uniform linear motion. In response to the above problem this paper carries out the research on multi-sensor fusion localization algorithm, the main work is as follows: Based on ORB-SLAM3, a visual-inertial-laser SLAM algorithm is designed. The relative motion of laser location between image frames is obtained from the data of 2D Lidar and laser height sensor. The relative motion of inertial measurement unit between image frames is obtained from inertial measurement unit preintegration. Based on the method of factor graph optimization, the pose of image frame is optimized by reprojection of map point, relative motion increment of inertial measurement unit, and relative motion increment of laser location. The algorithm improves the localization accuracy by about 24.4% over the ORB-SLAM3 visual mode and about 22.6% over the ORB-SLAM3 visual-inertial mode on the data of the UAV physical platform.
A hybrid geological map of Sibelius Crater on Mercury, and its associated ejecta and impact melt deposits
Authors: Canale Marc , Wright Jack , Rothery David A.
Published: April 2023

Using MESSENGER Mercury Dual Imaging System data, we produced three new maps of Sibelius Crater, Mercury. Geomorphological and spectral maps were combined into a single hybrid map containing units associated with ejecta deposits, crater floor landforms and impact melt ponding. Spatial measurement of these units shows that ∼50% of the mapped melt pond area lies within a large, degraded impact crater (crater B), beyond the significantly lower northern Sibelius rim, with a potential melt flow to a smaller, degraded impact structure further north (crater C). Freshly processed spectral data from the eight-colour Map Projected Multispectral Reduced Data Record data highlight the emplacement of multiple uplifted ejecta units with distinct spectral properties. A new, high-resolution digital elevation model was created to help define and analyse crater floor uplift features and disrupted crater rims and to create detailed cross-sections. These illustrate a proposed location of B's central uplift structure exposed in the northern wall slopes of Sibelius. Small features at the limit of visibility, such as a groove possibly associated with a rolling or sliding mega-boulder and lobate melt flow on the crater floor with accompanying channel opening, are highlighted for future investigations by BepiColombo's instruments once it reaches orbit.
Ethics as a Participatory and Iterative Process
Authors: Steen Marc
Published: April 2023

Facilitating ethical reflection, inquiry, and deliberation.
Development Use Cases for Semantics-Driven Modeling Languages
Authors: Broy Manfred , Rumpe Bernhard
Published: April 2023

Choosing underlying semantic theories and definition techniques must closely follow intended use cases for the modeling language.
How A Graduate Nursing Program Implemented a Virtual Oral Examination during the COVID-19 Pandemic
Authors: Williams Janice , Best Natasha , Carr Stacy , Wilson Candy , Seibert Diane
Published: April 2023

In 2020, as the entire world, including the U.S., experienced the rapid restraints and uncertainties of the COVID-19 pandemic, innovative teaching and assessment methods had to be utilized to achieve pre-pandemic goals and objectives of graduate education. This article describes how faculty implemented virtual oral exams as an assessment methodology to evaluate students' cumulative knowledge of essential women's health content. Course faculty administered a 25-minute virtual oral examination to students enrolled in a second-year advanced women's health course. All enrolled students (25 in 2020 and 19 in 2021) completed the virtual oral examination. The method was successfully implemented for two consecutive years, demonstrating the potential feasibility, applicability, and sustainability of implementing oral examinations utilizing the evaluation method in graduate education. This method assessed the students' critical thinking on essential aspects of care that they will eventually deliver to the public.
Locking Down Secure Open Source Software
Authors: Savage Neil
Published: April 2023

Can even secure open source software ever be considered truly safe?
Configure Your Federation: Hierarchical Attention-enhanced Meta-Learning Network for Personalized Federated Learning
Authors: Gao Yujia , Wang Pengfei , Liu Liang , Zhang Chi , Ma Huadong
Published: April 2023

Federated learning, as a distributed machine learning framework, enables clients to conduct model training without transmitting their data to the server, which is used to solve the dilemma of data silos and data privacy. It can work well on clients having similar data characteristics and distribution. However, it has some limitations where the dataset of clients may be different in distribution, quantity, and concept in many application scenarios. Personalized federated learning is a new federated learning paradigm that aims to guarantee client personalized models’ effectiveness when collaborating with the cloud server. Intuitively, providing further facilitated collaborations for the clients with similar data characteristics and distribution can benefit personalized model building. However, due to the invisibility of client data, it is challenging to extract client characteristics and define collaborative relationships among them from a fine-grained view. Moreover, a reasonable collaborative training approach needs to be designed for a distributed server–client framework. In this article, we design a Hierarchical Attention-enhanced Meta-learning Network (HAM) to address this issue. The main advantage of HAM is that it utilizes the meta-learning approach of taking model parameters as features and learns to learn an extra model for each client to analyze similarities according to their local dataset automatically. According to its two-layers framework, HAM can reasonably achieve a tradeoff between clients’ personality and commonality and provides a hybrid model with useful information from all clients. Considering there are two networks (HAM and base network) that need to learn for each client during the federated training process, we then provide an alternative learning approach to train them in an end-to-end fashion. To further clarify the approach, we describe the personalized federated learning settings framework as FedHAM where the HAM network is distributed deployed in each client. Extensive experiments based on two datasets prove that our method outperforms state-of-the-art baselines under different evaluation metrics.
A Method to Classify Data Quality for Decision Making Under Uncertainty
Authors: Simard Vanessa , Rönnqvist Mikael , Lebel Luc , Lehoux Nadia
Published: April 2023

Every decision-making process is subject to a certain degree of uncertainty. In sectors where the outcomes of the operations planned are uncertain and difficult to control such as in forestry, data describing the available resources can have a large impact on productivity. When planning activities, it is often assumed that such data are accurate, which causes a need for more replanning efforts. Data verification is kept to a minimum even though using erroneous information increases the level of uncertainty. In this context, it is relevant to develop a process to evaluate whether the data used for planning decisions are appropriate, so as to ensure the decision validity and provide information for better understanding and actions. However, the level of data quality alone can sometimes be difficult to interpret and needs to be put into perspective. This article proposes an extension to most data quality assessment techniques by comparing data to past quality levels. A classification method is proposed to evaluate the level of data quality in order to support decision making. Such classification provides insights into the level of uncertainty associated with the data. The method developed is then exploited using a theoretical case based on the literature and a practical case based on the forest sector. An example of how classified data quality can improve decisions in a transportation problem is finally shown.
TPoet: Topic-Enhanced Chinese Poetry Generation
Authors: Yang Liang , Shen Zhexu , Zhou Fengqing , Lin Hongfei , Li Junpeng
Published: April 2023

Chinese poetry generation has been a challenging part of natural language processing due to the unique literariness and aesthetics of poetry. In most cases, the content of poetry is topic related. In other words, specific thoughts or emotions are usually expressed regarding given topics. However, topic information is rarely taken into consideration in current studies about poetry generation models. In this article, we propose a topic-enhanced Chinese poetry generation model called
TPoet
in which the topic model is integrated into the Transformer-based auto-regressive text generation model. By feeding topic information to the input layer and heterogeneous attention mechanism, TPoet can implicitly learn the latent information of topic distribution. In addition, by setting multiple identifiers such as segment, rhyme, and tone, the model can explicitly learn the constraints of generated poems. Extensive experimental results show that the quality of TPoet-generated poems outperforms the current advanced models or systems, and the topic consistency and diversity in generated poems have been significantly improved as well.
A Bridge between Euclid and Buchberger: (An Attempt to Enhance Gröbner Basis Algorithm by PRSs and GCDs)
Authors: Sasaki Tateaki
Published: April 2023

This article surveys a very new method of enhancing Buchberger's Gröbner basis algorithm by the PRSs (polynomial remainder sequences) and the GCDs of multivariate polynomials. Let
F
= {
F
1
,...,
F

m
+1

} ⊂ K[
x
,
u
] be a given system, where (
x
) = (
x
1
,...,

x
m

) and (
u
) = (
u
1
,...,

u
n

). Currently, we treat only such
F
s that are "healthy" (see the text). Let [EQUATION], where [EQUATION], be the reduced Gröbner basis of ideal (
F
) w.r.t. the lexicographic order, to be abbreviated to GB(
F
). Let [EQUATION], be such that [EQUATION] is a small multiple of
G
1
, and the leading monomial of [EQUATION], is a multiple (hopefully small) of the leading monomial of

G
i

. Our method computes [EQUATION] first, then computes [EQUATION]. Finally, we will apply Buchberger's method to system [EQUATION]. Four new theorems are given. The first and second ones are to compute the lowest-order element of the ideal generated by relatively prime
G
,
H
∈ K[
x
,
u
], without computing any Spolynomial. The third theorem says that if
F
is healthy then [EQUATION]. We compute resultants in K[
u
], of
F
through different routes. Then, by Theorem 3, the resultants will be different multiples of
G
1
. Hence, the GCD of them will be a small multiple of
G
1
. In the elimination of
x
through different routes, we obtain sets of similar remainders such that the elements of each set have the same leading variable and nearly the same degrees. We call the leading coefficients of mutually similar remainders an "LCsystem". We eliminate the leading variables of suitably chosen LCsystems. The fourth theorem constructs a polynomial [EQUATION], such that the leading coefficient of [EQUATION] is the GCD of resultants of elements of an LCsystem chosen.
Adapting Simultaneous in Operando Electrochemical Quartz Crystal Microbalance and Electrochemical Impedance Spectroscopy to Studies of Solid Electrolyte Interface Layer Formation on Amorphous Silicon Anodes
Authors: Morris L. V. , Ortíz-Ledón C. A. , Hamers R. J.
Published: April 2023

Lithium-ion Batteries (LIBs) are the electrochemical energy storage technology of choice for an incredible range of technologies. The application of these batteries has, however, been limited by poor energy density, which is due to the low theoretical energy density of the graphite anodes that are standard in the field. Si has long been targeted as a higher energy density anode material, however uncontrolled electrolyte decomposition on its surface has caused poor cycle life and low columbic efficiencies in Si-containing cells. In this work, a new class of organosilicon (OS) additives were introduced to the Si anode literature and their effect on the first-cycle electrochemistry of model anode surfaces was explored using in operando electrochemical quartz crystal microbalancing (EQCM) and electrochemical impedance spectroscopy (EIS). X-ray photoelectron spectroscopy (XPS) was also used to investigate the differences in composition of solid electrolyte interface (SEI) layers formed in the presence and absence of additive. EQCM-EIS experiments demonstrated an increase in OS-treated cell impedance early in the cycle, which lead to the suppression of early electrolyte decomposition on the model anode surface. XPS revealed that OS-treated cells create thinner SEI layers that were richer in LiF and contained less organic material than cells without OS.
Development and Application of Visualization System of Gas Geological Dynamic Characteristics under Big Data Framework
Authors: Liu Xiao , Xu Sen , Lin Haixiao , Ni Xiaoming , Xuan Dequan
Published: April 2023

In this study, coal and gas outbursts are the “biggest killer” of mine safety production. With the deepening of mining, the mine gas disaster is becoming more and more serious. From the perspective of big data, the establishment of a dynamic visualization system of gas geology integrating gas geology, gas drainage, dynamic outburst prevention, and other information can effectively improving the defects of gas disaster prevention and control in the coal industry, such as insufficient advance, lack of systematic identification methods and backward information collection methods, which is of great significance to improve the ability of gas hazard identification. Based on the precise detection of geology, structure, and gas, this paper proposes to use information technology, the Internet of things, big data analysis, and other technologies to comprehensively analyze the changes in gas occurrence and coal seam occurrence on the basis of the causes of mine gas geological outburst, fully consider the logical relationship between different factors and outburst and adopt the disciplinary advantages of grey theory, fault tree theory, BP neural network, and so on. The tree of coal and gas outburst accidents with general significance is constructed by 24 relatively independent factors. The input vector is determined as the matrix composed of eight main factors affecting and controlling outburst, including gas pressure, coal mechanical strength, comprehensive characteristic coefficient of coal fragmentation, the permeability coefficient of coal, comprehensive characteristic coefficient of coal seam bifurcation and combination, comprehensive characteristic coefficient of coal thickness and coal thickness change, fault complexity coefficients and interlayer sliding comprehensive characteristic coefficient. The geological data affecting coal and gas outbursts are analyzed and calculated scientifically so that the gas geological data can be updated in time, and the change of gas geological laws is presented dynamically, so as to guide the mine to predict the gas disaster more scientifically and reliably.
Identification of Dry Bean Varieties Based on Multiple Attributes Using CatBoost Machine Learning Algorithm
Authors: Krishnan S. , Aruna S. K. , Kanagarathinam Karthick , Venugopal Ellappan
Published: April 2023

Dry beans are the most widely grown edible legume crop worldwide, with high genetic diversity. Crop production is strongly influenced by seed quality. So, seed classification is important for both marketing and production because it helps build sustainable farming systems. The major contribution of this research is to develop a multiclass classification model using machine learning (ML) algorithms to classify the seven varieties of dry beans. The balanced dataset was created using the random undersampling method to avoid classification bias of ML algorithms towards the majority group caused by the unbalanced multiclass dataset. The dataset from the UCI ML repository is utilised for developing the multiclass classification model, and the dataset includes the features of seven distinct varieties of dried beans. To address the skewness of the dataset, a Box-Cox transformation (BCT) was performed on the dataset’s attributes. The 22 ML classification algorithms have been applied to the balanced and preprocessed dataset to identify the best ML algorithm. The ML algorithm results have been validated with a 10-fold cross-validation approach, and during validation, the CatBoost ML algorithm achieved the highest overall mean accuracy of 93.8 percent, with a range of 92.05 percent to 95.35 percent.