bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnostic efficacy of data mining method based on multimodal ultrasound for papillary thyroid carcinoma
Authors: Xu Changyu , Zhang Liwei , Zhang Qiming , Wang Tianqi , Wu Yuqing , Yao Jinlai , Dong Xiaoqiu
Published: October 2024

Objective

The incidence of papillary thyroid caracinoma (PTC) is increasing year by year. Logistic regression model and Chi-squared automatic interaction (CHAID) decision tree based on multimodal ultrasound were established, and the diagnostic efficiency of the two models in PTC was compared.

Methods

The findings, features and data of routine ultrasound, shear wave elastography (SWE) and contrast-enhanced ultrasonography (CEUS) were prospectively collected in 203 patients. Including: echogenicity, aspect ratio, maximum diameter of tumor, boundary, morphology, focal hyperecho, blood flow grading, maximum elasticity (Emax), minimum elastcity (Emin), mean elasticity (Emean), enhancement degree, enhanced characteristics, distribution of contrast agent, contrast medium arrival time. According to the pathological results, they were divided into PTC group and non-PTC group. CHAID decision tree model and binary Logistic regression model were established, receiver operator characteristic (ROC) curves of the two models were drawn, and diagnostic effectiveness was evaluated by comparing area under curve (AUC).

Results

Logistic regression showed that hypoechoic or very hypoechoic, aspect ratio ≥1, microcalcification and high SWE value were risk factors for PTC (OR 8.604, 2.154, 2.297, 1.067, respectively, P < 0.05). The CHAID decision tree showed echo, aspect ratio, Emax, contrast agent distribution and infusion time combined to diagnose PTC. ROC curve showed that the AUC of PTC predicted by Logistic regression model and CHAID decision tree model was 0.878 and 0.883, respectively, with no statistical significance (z=0.325, P=0.7456).

Conclusion

Both Logistic regression model and CHAID decision tree model can play a good role in the diagnosis of PTC based on multi-modal ultrasound, but the diagnostic efficiency of both models is comparable. In conclusion, these two models provide new insights and ideas for PTC diagnosis.
Prognostic value of neutrophil to lymphocyte ratio for patients with bladder cancer undergoing radical cystectomy: a systematic review and meta-analysis
Authors: Chen Zhan , Zhang Yao , Chen Telei
Published: October 2024

Objectives

This study evaluated the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) for survival outcomes in bladder cancer patients treated with radical cystectomy.

Methods

Studies assessing NLR’s prognostic significance for bladder cancer after radical cystectomy were identified from PubMed, Embase, Web of Science, and Cochrane databases until April 2024. Survival outcomes analyzed included overall survival (OS), disease-free survival (DFS), relapse-free survival (RFS), cancer-specific survival (CSS), and progression-free survival (PFS).

Results

The meta-analysis comprised 15 cohort studies with 8,448 patients. Multivariate analysis showed significantly shorter OS, CSS, DFS, and RFS in the high NLR group compared to the low NLR group. However, no significant difference in PFS was observed between the groups.

Conclusions

NLR serves as an independent prognostic indicator for bladder cancer patients undergoing radical cystectomy, with elevated NLR associated with poorer survival. Further large-scale, prospective studies are warranted to validate the relationship between NLR and prognosis in bladder cancer.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024549573.
Incidence of prolonged transitional neonatal hypoglycemia and associated factors among neonatal admissions in South Gondar public hospitals, North-Central Ethiopia: a prospective cross-sectional study
Authors: Kebede Solomon Demis , Aytenew Tigabu Munye , Agmas Kindu , Asferie Worku Necho , Moges Natnael
Published: October 2024

Background

Unlike in developed countries, neonatal morbidity and mortality are the leading challenges associated with easily preventable and treatable disorders during the neonatal period in low- and middle-income countries. However, evidence-based data about prolonged transitional hypoglycemia and associated factors are highly limited in Ethiopia and resource-limited countries.

Methods

An institution-based prospective cross-sectional study was conducted at public hospitals in South Gondar in neonatal intensive care units (NICUs). The data were entered and analyzed using SPSS version 23. Descriptive statistics were used to summarize maternal characteristics. Multivariate binary logistic regression at a p value <0.05 was used.

Results

A total of 400 neonates, admitted to NICUs in public hospitals within 48–72 h of birth between October 2, 2021, and June 30, 2022, were included in the study. The incidence of prolonged transitional neonatal hypoglycemia (PTHG) was 23.5% (19.3%–28%). The factors associated with PTHG were hypothermia (AOR = 4.41; 95% CI = 2.72–10.92), preterm birth (AOR = 3.5; 95% CI = 1.69–11.97), perinatal asphyxia (AOR = 2.5; 95% CI = 1.34–9.67), and pathological jaundice (AOR = 2.3; 95% CI = 1.21–10.34). In contrast, spontaneous vaginal delivery (SVD) was a protective factor (AOR = 0.72; 95% CI = 0.35–0.88).

Conclusions

The incidence of (PTHG) was nearly one-fifth. Factors increasing the risk of PTHG were hypothermia, preterm birth, perinatal asphyxia (PNA), early onset of sepsis (EONS), and pathological jaundice. Spontaneous vaginal delivery (SVD) was also a protective factor. Preventing neonatal hypothermia was the main measure used to reduce PTHG in the study area. Special attention could be given to neonates with prematurity, early onset neonatal sepsis (EONS), birth asphyxia, and pathological jaundice, as monitoring their RBS could lead to a significant change in reducing PTHG.
Recent advances in the structures and bioactivities of benzopyrans derived from marine fungi: a review
Authors: Xi Yidan , Wang Huannan , Sun Lixiang , Ma Xueyang , Zhang Shuncun , Zhang Zhen
Published: October 2024

Marine fungi represent a treasure trove of bioactive secondary metabolites, with benzopyran compounds emerging as a significant class of these natural products. This review delves into the structural diversity, biological activities, and sources of benzopyran compounds, highlighting their isolation from marine fungi inhabiting diverse environments such as sponges, marine sediments, algae, mangroves, and corals. Our literature search, conducted from 2000 to 2023, has identified a wealth of benzopyran compounds, showcasing their potential as lead compounds in drug development. The characteristics of benzopyran from marine fungi are explored, encompassing various subclasses such as chromones, isocoumarins, citrinins, and other related compounds. These compounds exhibit a remarkable chemical diversity, which is crucial for their diverse biological activities. The potential of benzopyran compounds in drug development is also discussed, emphasizing their roles in anti-tumor, antibacterial, anti-inflammatory, and enzyme inhibitory activities. In recent years, a remarkable 210 bioactive benzopyran compounds have been isolated from the secondary metabolites of marine fungi. These findings underscore the importance of marine fungi as a source of novel bioactive compounds, offering a plethora of potential lead compounds for the development of marine-derived drugs. This review aims to provide a comprehensive overview of the current state of research on benzopyran compounds, setting the stage for future advancements in the field of marine natural products.
Research on the design of progressive addition multifocal defocused freeform lenses
Authors: Xiang Huazhong , Ma Lefei , Zhang Xin , Cheng Hui , Zheng Zexi , Chen Jiabi , Wang Cheng , Zhang Dawei , Zhuang Songlin
Published: October 2024

In this study, we developed a new method for designing progressive addition-multifocus defocused freeform lenses. We used two independent meridians and achieved a smooth gradient transition of additional optical power from the center to the peripheral area of the lens, along with an asymmetric distribution of additional optical power on the nasal-temporal side of the lens. To improve the optical performance of the lenses, we developed three different designs based on the distribution of the additional optical power on the meridians. We conducted simulations and processing on the three different designs. The lenses designed using improved logistic regression and sine functions for meridian optical power distribution exhibited stable optical performance in the central focus area. They also met the design requirements for additional optical power. However, significant distortion was still observed in the peripheral region, which required further optimization. Lenses designed using piecewise linear functions for meridian optical power distribution exhibited relatively poor optical performance with significant optimization potential. Thus, combining the optical power distribution and surface-type factors for optimization is necessary. The proposed method enabled designing of defocus-free curved mirror lenses that satisfy the optical performance requirements. Thus, this method provides a new approach for the design of progressive addition lenses.
Optimization of artificial intelligence in localized big data real-time query processing task scheduling algorithm
Authors: Sun Maojin , Sun Luyi
Published: October 2024

Introduction

The development of science and technology has driven rapid changes in the social environment, especially the rise of the big data environment, which has greatly increased the speed at which people obtain information. However, in the process of big data processing, the allocation of information resources is often unreasonable, leading to a decrease in efficiency. Therefore, optimizing task scheduling algorithms has become an urgent problem to be solved.

Methods

The study optimized task scheduling algorithms using artificial intelligence (AI) methods. A task scheduling algorithm optimization model was designed using support vector machine (SVM) and K-nearest neighbor (KNN) combined with fuzzy comprehensive evaluation. In this process, the performance differences of different nodes were considered to improve the rationality of resource allocation.

Results and Discussion

By comparing the task processing time before and after optimization with the total cost, the results showed that the optimized model significantly reduced task processing time and total cost. The maximum reduction in task processing time is 2935 milliseconds. In addition, the analysis of query time before and after optimization shows that the query time of the optimized model has also been reduced. The experimental results demonstrate that the proposed optimization model is practical in handling task scheduling problems and provides an effective solution for resource management in big data environments. This research not only improves the efficiency of task processing, but also provides new ideas for optimizing future scheduling algorithms.
Leukocyte telomere length and lung function: a mendelian randomization study in European population
Authors: Zhu Shenyu , Zheng Wenlong , Rao Dingyu , Tang Zhixian , Liao Xinhui
Published: October 2024

Background

The telomere has long been regarded as a dependable biomarker for cellular senescence. The lung function can reflect the function and status of the lungs. As individuals age beyond adulthood, there is a gradual decline in lung function. However, the existence of a associated between leukocyte telomere length (LTL) and lung function remains uncertain.

Methods

A two-sample Mendelian randomization (MR) analysis was used. The Single-nucleotide polymorphisms (SNPs) of LTL from the genome-wide association (GWAS) study were used as exposure instruments variable, and the lung function indicator including Forced expiratory volume in 1-s (FEV1), FEV1 Best measure, FEV1 predicted and Forced vital capacity (FVC) from the Neale Lab and MRC-IEU were used as outcomes. The associated between the exposures and outcomes was assessed using inverse-variance weighted (IVW), MR-Egger, and weighted median methods. Sensitivity analysis was conducted using Cochran’s Q-test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis, and Steriger test.

Results

Using the IVW method, a significant association was identified between genetically determined telomere length extension and enhanced lung function in FEV1, with ukb-a-336 (P = 0.127, OR = 1.028,95CI% = 1.003–1.042) and ukb-b-19657 (P = 7.26E-05, OR = 1.051,95CI% = 1.025–1.077),in FEV1 predicted, ukb-a-234 (P = 0.013, OR = 1.029,95CI% = 1.003–1.042), ukb-b-8428 (P = 0.001, OR = 1.032,95CI% = 1.012–1.052), in FEV1 best measure, ukb-a-231 (P = 7.24E-05, OR = 1.050,95CI% = 1.025–1.075), ukb-b-11141 (P = 1.40E-09, OR = 1.067,95CI% = 1.045–1.090).The sensitivity analysis did not reveal heterogeneity or horizontal pleiotropy.Meanwhile, the Steriger test results also indicate that the directionality between exposure and outcome is correct. Therefore, the results indicated robustness.

Conclusion

There is a correlation between longer LTL and better lung function in the European dataset.
Lipid metabolic profiling and diagnostic model development for hyperlipidemic acute pancreatitis
Authors: Ren Dongmei , Li Yong , Zhang Guangnian , Li Tiantian , Liu Zhenglong
Published: October 2024

Introduction

Hyperlipidemic acute pancreatitis (HLAP) is a form of pancreatitis induced by hyperlipidemia, posing significant diagnostic challenges due to its complex lipid metabolism disturbances.

Methods

This study compared the serum lipid profiles of HLAP patients with those of a healthy cohort using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to identify distinct lipid metabolites. Logistic regression and LASSO regression were used to develop a diagnostic model based on the lipid molecules identified.

Results

A total of 393 distinct lipid metabolites were detected, impacting critical pathways such as fatty acid, sphingolipid, and glycerophospholipid metabolism. Five specific lipid molecules were selected to construct a diagnostic model, which achieved an area under the curve (AUC) of 1 in the receiver operating characteristic (ROC) analysis, indicating outstanding diagnostic accuracy.

Discussion

These findings highlight the importance of lipid metabolism disturbances in HLAP. The identified lipid molecules could serve as valuable biomarkers for HLAP diagnosis, offering potential for more accurate and early detection.
Assessing fall armyworm (Spodoptera frugiperda) allochronic behavior as a predictor of local strain composition in United States populations
Authors: Miller Andie C. , Tessnow Ashley E. , Meagher Robert L. , Nagoshi Rodney N. , Gilligan Todd M. , Sword Gregory A.
Published: October 2024

The fall armyworm, Spodoptera frugiperda (J.E. Smith), is comprised of two genetically distinct strains that are morphologically identical yet exhibit differences in their behavior and physiology (C-strain and R-strain). Evidence of ongoing genetic differentiation between strains highlights the importance of considering strain identity in research and management of fall armyworm populations, but the logistical and technical burden of genotyping limits strain-specific applications. Controlled experiments with laboratory colonies have shown that the strains engage in allochronic (“allo” – different, “chronic” – time) mating behavior, with C-strain mating early in the evening (0–5 hours after sunset) and R-strain mating late in the evening (5–10 hours after sunset). Using temporal field collections and genotype data, we show that strain-specific variation in allochronic male mating behavior occurs across Texas and Florida fall armyworm populations, both of which act as primary source populations for annual migrations of this pest into the continental United States. Time of capture in pheromone traps was significantly different between strains in both Texas and Florida, with the R-strain males consistently being collected in the traps late in the night. The C-strain males were generally captured earlier in the night than their R-strain counterparts, though there was notable variation in the timing between nights and across locations. Allochronic behavior in field populations is consistent with previous laboratory studies reporting differences in the timing of mating between the strains, however increased variability in behavior within and across native populations was observed. Although allochronic behavior in local populations may partially contribute to reproductive isolation between the strains, the behavior is not consistent enough to serve as a complete reproductive barrier. Furthermore, the observed variability in behavior both within and between independent sampling events, especially in the C-strain, poses a challenge to the development of models that utilize time of capture as a predictive phenotype for monitoring strain identity in local populations.
Transcriptome analysis revealed that AcWRKY75 transcription factor reduced the resistance of kiwifruit to Pseudomonas syringae pv. actinidiae
Authors: Ye Lixia , Luo Minmin , Wang Yafang , Yu Mengqi , Wang Zhi , Bai Fuxi , Luo Xuan , Li Li , Huang Qiong , Peng Jue , Chen Qi , Chen Qinghong , Gao Lei , Zhang Lei
Published: October 2024

The kiwifruit canker disease caused by Pseudomonas syringae pv. actinidiae (Psa) seriously threatens the development of kiwifruit industry. So far, only a limited number of Psa-resistant kiwifruit varieties have been identified, and the underlying molecular mechanisms are still largely unknown. In this study, we evaluated the Psa resistance of six hybrid populations and screened a resistant segregation population R1F2. Then, transcriptome analysis on the Psa extremely high-resistant (HR) and extremely high-susceptible (HS) plants of the R1F2 population was performed. KEGG enrichment analysis revealed that differentially expressed genes (DEGs) were significantly enriched in plant hormone signal transduction pathways, including auxin, abscisic acid, zeatin, jasmonic acid and salicylic acid. Furthermore, several transcription factors (TFs), especially WRKY TFs, were identified among the DEGs. The qRT-PCR showed that AcWRKY75 was highly expressed in the HS plants. Additionally, AcWRKY75 was significantly induced in the HS cultivar ‘Hongyang’ after Psa inoculation. Sequence amplification analysis showed that there was polymorphism in the DNA sequence of AcWRKY75 gene, but no HR or HS-specific differences were observed. Subcellular localization and transcriptional activity analysis confirmed that AcWRKY75 functions as a nucleus-located transcriptional activator. Transient overexpression of AcWRKY75 in kiwifruit leaves reduced the resistance to Psa, while silencing AcWRKY75 by virus-induced gene silencing (VIGS) slightly enhanced the resistance to Psa. Furthermore, AcWRKY75 exhibited a weak interaction with the promoter of the ABA-related DEG AcBet V1 (Acc27163). Our findings elucidated that AcWRKY75 may negatively regulate the Psa resistance of kiwifruit through the hormone signaling pathway, which laid a foundation for the analysis of the disease resistance mechanism of kiwifruit canker.
Expertise-dependent visuocognitive performance of chess players in mating tasks: evidence from eye movements during task processing
Authors: Küchelmann Thomas , Velentzas Konstantinos , Essig Kai , Schack Thomas
Published: October 2024

Introduction

Visuocognitive performance is closely related to expertise in chess and has been scrutinized by several investigations in the last decades. The results indicate that experts’ decision-making benefits from the chunking process, perception and visual strategies. Despite numerous studies which link these concepts, most of these investigations have employed common research designs that do not use real chess play, but create artificial laboratory conditions via screen-based chess stimuli and obtrusive stationary eye tracking with or without capturing of decision-making or virtual reality settings.

Methods

The present study assessed the visuocognitive performance of chess novices, intermediates and experts in a real chess setting. Instead of check detection, find-the-best-move tasks or to distinguish between regions of a chessboard that were relevant or irrelevant to the best move in previous studies, we introduced n-mate tasks and sequentially manipulated their difficulty. Due to the complexity of the tasks, we monitored players’ visual strategies in a fine-graded initial phase (different time intervals instead of analysing a fixed number of first fixations) of task-solving and for complete trials, employing non-obtrusive mobile eye tracking, multi-sensor observation and full-automatic annotation of decision-making.

Results

The results revealed significant expertise-dependent differences in visuocognitive performance based on a circumstantial spatial and temporal analysis. In order to provide more detailed results, for the first time the analyses were performed under the special consideration of different time intervals and spatial scalings. In summary, experts showed a significantly higher number of fixations on areas of interest and empty squares between pieces in the task processing than less-skilled players. However, they had a strikingly low total number of fixations on the whole board and in complete trials.

Discussion

As a conclusion, experts apply different visual search strategies in problem-solving. Moreover, experts’ visuocognitive processing benefits from stored chunks of mating constellations.
In the shoes of junior doctors: a qualitative exploration of job performance using the job-demands resources model
Authors: Chua Jia Long , Mougammadou Zeenathnisa , Lim Raymond Boon Tar , Tung Joshua Yi Min , Sng Gerald Gui Ren
Published: October 2024

Background

This qualitative study aimed to explore the factors affecting job performance amongst junior doctors working for public healthcare institutions in Singapore. Within these institutions, junior doctors experience challenges with maintaining a balance in job demands and resources, leading to strain. Exploring the lived experiences of these junior doctors is essential when reviewing workplace and organizational factors that contribute to stress on an individual level, providing valuable insights to address these challenges effectively.

Method

Semi-structured interviews were conducted with 20 junior doctors in Singapore, ranging from house officers to senior residents. Framework analysis was performed on transcribed de-identified interviews to identify themes deductively based on the Job Demands-Resources (JD-R) Model.

Results

Themes were identified and contextualized based on the exiting JD-R model. These themes shed light on how work demands, resources and personal factors influence the job performance of junior doctors and job satisfaction.

Conclusion

The study offers valuable insights into the specific issues disrupting the job demands and resource balance in Singapore Public Healthcare Institutions and their correlation with job performance. Our data suggests that job performance may be associated with job satisfaction. By understanding these factors, targeted efforts can be developed to improve working conditions for junior doctors, fostering their growth and engagement within the public healthcare system.
Multilevel modeling of technology use, student engagement, and fitness outcomes in physical education classes
Authors: Cui Zhaohang , Song Yifan , Du Xiaojuan
Published: October 2024

Introduction

The integration of technology in educational settings, particularly in physical education, has shown potential in enhancing learning experiences and improving physical health outcomes. This study aims to investigate the effects of technology use on student engagement and fitness outcomes, considering the mediating role of student engagement and the moderating influence of personal attributes.

Methods

Utilizing a time-lagged design, the research collected data from 513 Chinese undergraduate students (52% male and, 48% female) aged between 18 and 24 years over three waves using structured questionnaires rated on a 5-point Likert scale.

Results

Results revealed a significant positive relationship between technology use and both student engagement (β = 0.68, p < 0.01) and fitness outcomes (β = 0.60, p < 0.01). Student engagement significantly mediated the relationship between technology use and fitness outcomes (β = 0.57, p < 0.01). Personal attributes moderated the effects of technology use on student engagement (β = 0.54, p < 0.01) and fitness outcomes (β = 0.52, p < 0.01), indicating varied benefits among students based on individual characteristics.

Discussion

These findings highlight the importance of tailoring technological applications in physical education to individual needs, suggesting that personalized approaches can significantly enhance the effectiveness of technology in improving fitness and engagement.
Investigating the follow-up discontinuation among people living with HIV in North Shoa Zone, Oromia, Ethiopia
Authors: Amhare Abebe Feyissa , Goyomsa Girma Garedew , Al Issa Yasmeen Moshtaq A.
Published: October 2024

Introduction

Follow-up discontinuation among people living with HIV can increase mortality and HIV spread within communities. This study investigates the impact of the COVID-19 on follow-up discontinuation among people living with HIV in Ethiopia.

Methods

This longitudinal study used retrospective document review to compare follow-up status of people living with HIV during the COVID-19 pandemic with their status from 2017 to 2019. Data from selected health facilities were collected using a checklist, entered and cleaned in Excel, and analyzed in Stata. Descriptive statistics were presented in tables and line graphs. Incidence risk (IR) and incidence rate ratios (IRR) were calculated.

Results

Between 2017 and 2021, a total of 7,447 people living with HIV were registered to begin ART at selected health facilities. Annual retention rates were consistent from 2017 to 2019, ranging from 0.941 to 0.949. During the COVID-19 pandemic, they dropped to 0.837 in 2020 and 0.840 in 2021. Retention rates were significantly correlated with loss to follow-up (r: −0.959, p ≤ 0.001), death (r: −0.968, p ≤ 0.001), and transfer-out (r: −0.979, p ≤ 0.001). Moreover, the incidence of loss to follow-up (IRR: 3.00, 95%CI: 2.71–3.33, p ≤ 0.001), death (IRR: 3.61, 95%CI: 3.13–4.16, p ≤ 0.001), poor adherence (IRR: 2.27, 95%CI: 2.14–2.40, p ≤ 0.001), and severe malnutrition (IRR: 2.32, 95%CI: 2.18–2.47, p ≤ 0.001) significantly increased during the COVID-19.

Conclusion

The study found that COVID-19 healthcare disruptions increased follow-up loss among people living with HIV and heightening the disease burden in Ethiopia.
Global burden of inflammatory bowel disease in the elderly: trends from 1990 to 2021 and projections to 2051
Authors: Liu Ying , Li Ju , Yang Guangxia , Meng Deqian , Long Xianming , Wang Kai
Published: October 2024

Background

This study aims to analyze the historical trends of inflammatory bowel disease (IBD) burden in the elderly from 1990 to 2021 and forecast future trends up to 2051.

Methods

Data from the Global Burden of Disease Study 2021 were utilized. Age-standardized rates (ASR) for incidence, prevalence, mortality, and disability-adjusted life years (DALYs) were calculated. Estimated annual percentage changes (EAPCs) were computed to quantify temporal trends. A Bayesian Age-Period-Cohort model was employed to project future trends.

Results

From 1990 to 2021, the global number of elderly IBD increased from 573,500 to 1,278,190. The age-standardized incidence rate (ASIR) rose from 8.01 to 8.77 per 100,000, while the age-standardized prevalence rate (ASPR) slightly decreased from 118.14 to 117.29 per 100,000. Death number increased from 14,400 to 33,490, but the age-standardized mortality rate decreased from 3.21 to 2.84 per 100,000. DALYs increased from 324,100 to 683,750, with the age-standardized DALYs rate declining from 68.78 to 60.88 per 100,000. Significant geographical variations were observed, with high Socio-demographic Index regions showing the highest burden. Projections suggest that by 2051, elderly IBD prevalence number may reach 2,316,000, with ASIR and ASPR potentially rising after 2035 and 2042, respectively. Deaths and DALYs are projected to increase to 75,000 and 1,401,000 respectively, despite continued declines in ASRs.

Conclusion

The absolute burden of IBD in the elderly population is projected to increase substantially by 2051, despite decreasing ASRs. These findings underscore the need for tailored healthcare strategies and resource allocation to address the growing challenge of elderly IBD globally.
Using Mathematics to Study How People Influence Each Other’s Opinions
Authors: Li Grace J. , Luo Jiajie (Jerry) , Peng Kaiyan , Porter Mason A.
Published: October 2024

People sometimes change their opinions when they discuss things with each other. Researchers can use mathematics to study opinion changes in simplifications of real-life situations. These simplified scenarios, which are examples of mathematical models, help researchers explore how people influence each other through their social interactions. In today’s digital world, these models can help us learn how to promote the spread of accurate information and reduce the spread of inaccurate information. In this article, we discuss a simple mathematical model of opinion changes that arise from social interactions. We briefly describe what opinion models can tell us and how researchers try to make them more realistic.
Research on Artificial Self-Recovery Technology in Engineering Practice
Authors: Pan Xin , Liang Jingyi , Ge Dehong , Lu Jiaqiao , Guo Yunpeng
Published: October 2024

With the development of mechanical systems in the industrial era, there is an increasing emphasis on the safety and reliability of mechanical equipment. The theory of artificial self-recovery technology has emerged, aiming to enable mechanical equipment to autonomously prevent and repair faults by simulating biological self-recovery mechanisms, thereby enhancing the safety and reliability of industrial production, reducing manual intervention, and promoting the intelligent development of manufacturing. The article mainly explores the application of artificial self-recovery theory in mechanical equipment, elaborating on the achievements in self-recovery technologies such as automatic balancing technology, compensation and self-protection technology for large systems, equipment health assistive technology, and active control technology for sealing devices and hydrostatic bearings, as well as self-repair and self-cleaning technologies. Finally, the paper looks forward to the future development of artificial self-recovery technology, believing that with technological advancements it will play an increasingly important role in the industrial field and promote the development of manufacturing towards self-recovery.
Hybrid Machine Learning and Reinforcement Learning Framework for Adaptive UAV Obstacle Avoidance
Authors: Skarka Wojciech , Ashfaq Rukhseena
Published: October 2024

This review explores the integration of machine learning (ML) and reinforcement learning (RL) techniques in enhancing the navigation and obstacle avoidance capabilities of Unmanned Aerial Vehicles (UAVs). Various RL algorithms are assessed for their effectiveness in teaching UAVs autonomous navigation, with a focus on state representation from UAV sensors and real-time environmental interaction. The review identifies the strengths and limitations of current methodologies and highlights gaps in the literature, proposing future research directions to advance UAV technology. Interdisciplinary approaches combining robotics, AI, and aeronautics are suggested to improve UAV performance in complex environments.
Deep Learning-Based Rapid Flow Field Reconstruction Model with Limited Monitoring Point Information
Authors: Wang Ping , Hu Guangzhong , Hu Wenli , Xue Xiangdong , Tao Jing , Wen Huabin
Published: October 2024

The rapid reconstruction of the internal flow field within pressure vessel equipment based on features from limited detection points was of significant value for online monitoring and the construction of a digital twin. This paper proposed a surrogate model that combined Proper Orthogonal Decomposition (POD) with deep learning to capture the dynamic mapping relationship between sensor monitoring point information and the global flow field state during equipment operation, enabling rapid reconstruction of the temperature field and velocity field. Using POD, the order of the tested temperature field was reduced by 99.75%, and the order of the velocity field was reduced by 99.13%, effectively decreasing the dimensionality of the flow field. Our analysis revealed that the first modal coefficient of the temperature field snapshot data, after modal decomposition, had a higher energy proportion compared to that of the velocity field snapshot data, along with a more pronounced marginal effect. This indicates that more modes need to be retained for the velocity field to achieve a higher total energy proportion. By constructing a CSSA-BP model to represent the mapping relationship between the modal coefficients of the temperature and velocity fields and the data collected from the detection points, a comparison was made with the BP method in reconstructing the temperature field of a shell-and-tube heat exchanger. The CSSA-BP method yielded a maximum mean squared error (MSE) of 9.84 for the reconstructed temperature field, with a maximum mean absolute error (MAE) of 1.85. For the velocity field, the maximum MSE was 0.0135 and the maximum MAE was 0.0728. The global maximum errors for the reconstructed temperature field were 4.85%, 3.65%, and 4.29%, respectively. The global maximum errors for the reconstructed velocity field were 17.72%, 11.30%, and 16.79%, indicating that the model established in this study has high accuracy. Conventional CFD simulation methods require several hours, whereas the reconstruction model proposed here can rapidly reconstruct the flow field within 1 min after training is completed, significantly reducing reconstruction time. This work provides a new method for quickly obtaining the internal flow field state of pressure vessel equipment under limited detection points, offering a reference for online monitoring and the development of digital twins for pressure vessel equipment.
Finite Element Simulations and Experimental Analysis for Efficient Mugwort Harvesting
Authors: Wang Siqi , Zhang Daode , Hu Xinyu , Lu Rui
Published: October 2024

When mugwort is mechanically harvested, problems such as a low efficiency and high crushing rate seriously affect the quality of mugwort and restrict the development of the mugwort industry. In order to improve the efficiency of mugwort harvesting and reduce the crushing rate, the finite element method simulation and experiment are combined to study the optimal harvesting method of mugwort. Firstly, the parameters of the components of mugwort, such as the mugwort culm, mugwort stalk, and mugwort leaf, were investigated by tensile and three-point bending methods to determine the values of density, the modulus of elasticity, and Poisson’s ratio, and to establish the material mechanics model of mugwort. Secondly, harvesting of mugwort was simulated through the established three-dimensional model of mugwort, combined with its material mechanics model and using display dynamics. Finally, by conducting harvesting tests on mugwort, the harvesting force of different harvesting directions and harvesting positions were measured to reveal the harvesting mechanism of mugwort and to determine the optimal harvesting direction and position of mugwort leaves. The experimental results showed that the harvesting force was lowest when the harvesting angle was 0° or 90°, and the leaves were least damaged when the harvesting position was close to the stalk. The results of the study can provide data support for the study of the mechanical properties of mugwort and provide a theoretical basis for the research and development of high-efficiency and low-loss mugwort harvesting machinery and the optimisation of harvesting methods.
Using UAV Images and Phenotypic Traits to Predict Potato Morphology and Yield in Peru
Authors: Ccopi Dennis , Ortega Kevin , Castañeda Italo , Rios Claudia , Enriquez Lucia , Patricio Solanch , Ore Zoila , Casanova David , Agurto Alex , Zuñiga Noemi , Urquizo Julio
Published: October 2024

Precision agriculture aims to improve crop management using advanced analytical tools. In this context, the objective of this study is to develop an innovative predictive model to estimate the yield and morphological quality, such as the circularity and length–width ratio of potato tubers, based on phenotypic characteristics of plants and data captured through spectral cameras equipped on UAVs. For this purpose, the experiment was carried out at the Santa Ana Experimental Station in the central Peruvian Andes, where advanced potato clones were planted in December 2023 under three levels of fertilization. Random Forest, XGBoost, and Support Vector Machine models were used to predict yield and quality parameters, such as circularity and the length–width ratio. The results showed that Random Forest and XGBoost achieved high accuracy in yield prediction (R2 > 0.74). In contrast, the prediction of morphological quality was less accurate, with Random Forest standing out as the most reliable model (R2 = 0.55 for circularity). Spectral data significantly improved the predictive capacity compared to agronomic data alone. We conclude that integrating spectral indices and multitemporal data into predictive models improved the accuracy in estimating yield and certain morphological traits, offering key opportunities to optimize agricultural management.
Antioxidant Activity of Zingiber officinale R. Extract Using Pressurized Liquid Extraction Method
Authors: Saldaña-Olguin Marlon , Quispe-Ciudad Bernardo Junior , Aguirre Elza
Published: October 2024

Global food demand is rising, leading to increased food waste, which contains underutilized bioactive compounds. The Pressurized Liquid Extraction (PLE) method employs high temperature and pressure to maintain the solvent in a liquid state above its boiling point, thereby minimizing extraction time and solvent usage. Ginger waste is known to contain bioactive compounds with significant antioxidant activity. We aimed to assess the effect of temperature, time, and particle size on the total phenolic content (TPC) and antioxidant activity (AA) of ginger (Zingiber officinale R.) waste aqueous extract using the PLE method. A Box–Behnken design with 16 runs was employed. Each extraction utilized 40 g of the sample and was conducted at a constant pressure of 20 bar with a solvent ratio of 27:1 mL/g. Data analysis was performed with Minitab® 19.1 (64-bit). TPC ranged from 10.42 to 14.1 mg GAE/g, and AA ranged from 72.9 to 111.9 μmol TE/g. The model explained 81.07% of AA’s total variability. Positive correlation was found between TPC and AA (Pearson’s ρ = 0.58, p < 0.05). The optimized extraction conditions were a temperature of 126 °C, an extraction time of 38 min, and a particle size between 355 and 500 μm. Temperature significantly influenced AA (p < 0.05), while time and particle size were not significant factors. To enhance future research, conducting nutritional and functional studies on the extracted compounds would provide valuable insights. Lastly, evaluating the economic feasibility of using PLE for ginger waste valorization should be considered to support its commercial application.
Cultivation Technology and Plant Density Affecting the Yield and Carotenoid Content of Beauregard Sweet Potato
Authors: Balázs Viktor , Helyes Lajos , Daood Hussein G. , Pék Zoltán , Ilahy Riadh , Neményi András , Égei Márton , Takács Sándor
Published: October 2024

Given the global importance of sweet potatoes as a nutrient-rich staple food, this research aimed to find the optimal cultivation practices to improve both yield and carotenoid content, with a particular focus on enhancing β-carotene content. In this study, the effects of different cultivation methods and plant densities on the agronomic parameters, physiological characteristics and carotenoid content of the ‘Beauregard’ variety were investigated across two consecutive growing seasons. Besides storage root yield, the key physiological parameters, including SPAD and chlorophyll fluorescence (Fv/Fm), were monitored to assess plant health and photosynthetic performance. Carotenoid content, including trans-β-carotene, cis-β-carotene, and ζ-carotene, was quantified using high-performance liquid chromatography (HPLC). Results indicated that the ridge cultivation method, particularly when combined with twin-row planting, consistently produced the highest yields, reaching the maximum of 40.87 t ha−1 in 2020. The flat cultivation method, especially in simple rows, showed the lowest yield. The analysis revealed that plant density had a more pronounced effect on yield and carotenoid content than the ridge or flat cultivation method alone. The maximum β-carotene content was achieved in the simple row (17,500 plants/ha) treatment planted on ridges with 247 µg/g. Significant correlations between both SPAD readings and Fv/Fm and yield were revealed, but no correlations with storage root carotenoid content were found. This suggests that, while these leaf physiological traits can be used to estimate the yield, they are not directly associated with the carotene content of the storage root. The study highlights the ridge cultivation and 35,000 plants/ha method as a stable and high-yielding option for ‘Beauregard’ in terms of improving and balancing the yield and carotenoid content; however, reducing the plant density resulted in elevated carotenoid content with significant yield reductions. The findings contribute to the understanding of how agronomic practices influence the nutritional and physiological traits of sweet potatoes, with implications for improving food security and nutritional outcomes in sweet potato cultivation.
Geoelectric Joint Inversion for 3D Imaging of Vineyard Ground
Authors: Lopane Nicola , Albéri Matteo , Barbagli Alessio , Chiarelli Enrico , Colonna Tommaso , Gallorini Fabio , Guastaldi Enrico , Mantovani Fabio , Petrone Dario , Pierini Silvio , Raptis Kassandra Giulia Cristina , Strati Virginia
Published: October 2024

Using a novel joint inversion approach, this study tackles the challenge of accurately characterizing subsurface electrical resistivity in vineyards, a critical and strategic aspect of precision viticulture. For the first time, we integrate 3D Galvanic Contact Resistivity with multi-2D Capacitively Coupled Resistivity data. Conducted in a prestigious Sangiovese vineyard in Montalcino (Tuscany, Italy), the data are analyzed utilizing a single algorithm capable of inverting Capacitively Coupled Resistivity, Galvanic Contact Resistivity, and joint datasets. This approach combines data sensitive to different depths and spatial resolutions, resulting in a comprehensive analysis of soil resistivity variations and moisture distribution, thus providing a detailed and coherent subsurface model. The joint inversion produced a high spatial resolution 3D resistivity model with a density of 20.21 data/m3. This model significantly enhances subsurface characterization, delineating root systems and correlating water distribution with resistivity patterns, showing relative variations sometimes greater than 50%. This method reduced data misfit more effectively than individual inversions and identified a low-resistivity volume (<20 Ω·m), extending from northeast to south, indicating the presence of subsurface water. The systematic alternation of high and low resistivity across vineyard rows highlights the impact of soil management activities on resistivity and supports targeted interventions for vineyard health.
Leaf Surface Micromorphology in Hybrids of Wheat and ×Trititrigia × Elymus farctus
Authors: Babosha Alexander V. , Loshakova Pavla O. , Pogost Alina A. , Gevorkyan Margarita M. , Alenicheva Anastasia D. , Komarova Galina I. , Wineshenker Tatyana S. , Klimenkova Irina N. , Upelniek Vladimir P.
Published: October 2024

The leaf surface micromorphology and the size of the stomatal complex of hybrids in the eighth seed generation from the crossing of ×Trititrigia cziczinii × Elymus farctus (f11814) on the wheat-like wheat-wheatgrass hybrid w107 were investigated by performing scanning electron microscopy of frozen samples (cryoSEM). The micromorphological characteristics of the paternal plants (w107) were dominant in the hybrid leaves. Costal long cells with silicified wavy walls, characteristic of w107 but absent in the mother plants f11814 and E. farctus, were observed in all hybrid samples examined. Conversely, shield-shaped prickles, a characteristic feature of E. farctus, were retained only in some hybrids. In addition, the maternal feature of Ω-shaped junctions of long epidermal cells in the intercostal zone was completely absent in hybrids. Quantitative parameters of the stomatal apparatus showed a weak correlation with micromorphological markers. Stomatal density on the adaxial side was inversely correlated with stomatal size, while variation in these parameters on the abaxial side occurred independently. The prevalence of paternal micromorphological traits in the hybrids seems to be a consequence of the elimination of genetic material from E. farctus, analogous to the loss of chromosomes from wild species observed in other distant crosses.
Antiviral Effects of Avian Interferon-Stimulated Genes
Authors: He Xingchen , Zhang Shiyuan , Zou Ziheng , Gao Pei , Yang Liangyu , Xiang Bin
Published: October 2024

Interferons (IFNs) stimulate the expression of numerous IFN-stimulating genes via the Janus kinase-signal transducers and activators of the transcription (JAK-STAT) signaling pathway, which plays an important role in the host defense against viral infections. In mammals, including humans and mice, a substantial number of IFN-stimulated genes (ISGs) have been identified, and their molecular mechanisms have been elucidated. It is important to note that avian species are phylogenetically distant from mammals, resulting in distinct IFN-induced ISGs that may have different functions. At present, only a limited number of avian ISGs have been identified. In this review, we summarized the identified avian ISGs and their antiviral activities. As gene-editing technology is widely used in avian breeding, the identification of avian ISGs and the elucidation of their molecular mechanism may provide important support for the breeding of avians for disease resistance.