bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validation of quantitative loop-mediated isothermal amplification assay using a fluorescent distance-based paper device for detection of Escherichia coli in urine
Authors: Saengsawang Natkrittaya , Ruang-areerate Panthita , Kaeothaisong Nuanlaong , Leelayoova Saovanee , Mungthin Mathirut , Juntanawiwat Piraporn , Hanyanunt Patomroek , Potisuwan Patsanun , Kesakomol Piyanate , Butsararattanagomen Pornphan , Wichaiwong Pattarawadee , Dungchai Wijitar , Ruang-areerate Toon 
Published: October 2023

AbstractUropathogenic Escherichia coli (UPEC) causes up to 90% of urinary tract infections (UTI) which is more prevalent among females than males. In urine, patients with symptomatic UTI usually have a high concentration of bacterial infection, ≥ 105 colony-forming units (CFU) per mL, in which the culture method is regularly the gold standard diagnosis. In this study, a simple and inexpensive distance-based paper device (dPAD) combined with the fluorescent closed tube LAMP assay was validated for simultaneously screening and semi-quantifying the infection level of E. coli in 440 urine samples of patients with UTI. The dPAD could measure the LAMP amplicons and semi-quantify the levels of E. coli infection in heavy (≥ 104 CFU/mL), light (≤ 103 CFU/mL) and no infection. The sensitivity and specificity had reliable performances, achieving as high as 100 and 92.7%, respectively. The one step LAMP assay could be performed within 3 h, which was 7.5 times faster than the culture method. To empower early UTI diagnosis and fast treatment, this inexpensive dPAD tool combined with the fluorescent closed tube LAMP assay is simple, reliably fast and practically portable for point-of-care settings, particularly in resource-limited areas, which can be set up in all levels of healthcare facilities.
Machine learning regression algorithms to predict short-term efficacy after anti-VEGF treatment in diabetic macular edema based on real-world data
Authors: Shi Ruijie , Leng Xiangjie , Wu Yanxia , Zhu Shiyin , Cai Xingcan , Lu Xuejing 
Published: October 2023

AbstractThe objective of this retrospective study was to predict short-term efficacy of anti-vascular endothelial growth factor (VEGF) treatment in diabetic macular edema (DME) using machine learning regression models. Real-world data from 279 DME patients who received anti-VEGF treatment at Ineye Hospital of Chengdu University of TCM between April 2017 and November 2022 were analyzed. Eight machine learning regression models were established to predict four clinical efficacy indicators. The accuracy of the models was evaluated using mean absolute error (MAE), mean square error (MSE) and coefficient of determination score (R2). Multilayer perceptron had the highestR2and lowestMAEamong all models. Regression tree and lasso regression had similarR2, with lasso having lowerMAEandMSE. Ridge regression, linear regression, support vector machines and polynomial regression had lowerR2and higherMAE. Support vector machine had the lowestMSE, while polynomial regression had the highestMSE. Stochastic gradient descent had the lowestR2and highMAEandMSE. The results indicate that machine learning regression algorithms are valuable and effective in predicting short-term efficacy in DME patients through anti-VEGF treatment, and the lasso regression is the most effective ML algorithm for developing predictive regression models.
The impact of industrial robot adoption on corporate green innovation in China
Authors: Liang Lin , Lu Liujie , Su Ling 
Published: October 2023

AbstractGreen innovation plays a crucial role in transforming economic models and achieving sustainable development in enterprises. As an important embodiment of artificial intelligence technology, how industrial robots can effectively promote the green transformation of enterprises has become an important issue. This paper examines the impact and mechanisms of industrial robot adoption on corporate green innovation, as well as its heterogeneous effects. Using data from Chinese listed companies from 2007 to 2019, we find that industrial robot adoption has a significant positive impact on corporate green innovation, enhancing both its quantity and quality. Furthermore, our mechanism study reveals that industrial robot adoption can promote corporate green innovation by improving productivity and environmental management capabilities. Additionally, we investigate the moderating effects of various factors and conclude that the positive impact of industrial robot adoption on green innovation is more pronounced among the state-owned enterprises, enterprises with the intense market competition, as well as enterprises located in regions with higher carbon emissions intensity. This paper contributes to enrich the research on industrial robots and corporate green innovation, and provides a reference to improve environmental management and achieve a low-carbon economy in emerging markets.
Cost effectiveness of quadrivalent influenza vaccines in the elderly population of Malaysia
Authors: Aljunid Syed Mohamed , Mad Tahir Nur Syazana , Ismail Aniza , Abdul Aziz Aznida Firzah , Azzeri Amirah , Zafirah S. A. , Aizuddin Azimatun Noor 
Published: October 2023

AbstractThe economic burden of influenza is a significant issue within healthcare system, related to higher medical costs particularly among the elderly. Yet, influenza vaccination rates in the elderly in Malaysia were considerably low as it is not part of Malaysia’s national immunization program, with substantial mortality and morbidity consequences. Therefore, we conducted a cost-effectiveness analysis of quadrivalent influenza vaccine (QIV) for the elderly in Malaysia compared with the current no-vaccination policy. A static cost-utility model, with a lifetime horizon based on age, was used for the analysis to assess the cost-effectiveness and health outcomes associated with QIV. Univariate and probabilistic sensitivity analyses were performed to test the effects of variations in the parameters. The use of QIV in Malaysia’s elderly population would prevent 66,326 potential influenza cases and 888 potential deaths among the elderly, leading to 10,048 potential quality-adjusted life years (QALYs) gained. The QIV would also save over USD 4.4 million currently spent on influenza-related hospitalizations and reduce productivity losses by approximately USD 21.6 million. The ICER per QALY gained from a third-party payer’s perspective would be USD 2216, which is lower than the country’s gross domestic product per capita. A QIV-based vaccination program in the elderly was found to be highly cost-effective, therefore would reduce the financial burden of managing influenza and reduce pre-mature death related to this disease.
An integrative analysis reveals the prognostic value and potential functions of MTMR2 in hepatocellular carcinoma
Authors: Yao Yuanqian , Lai Jiawen , Yang Yuwen , Wang Guangyao , Lv Jianlin 
Published: October 2023

AbstractAbnormal expression of myotubularin-related protein 2 (MTMR2) has been identified in certain types of cancer, leading to varying effects on tumor genesis and progression. However, the various biological significances of MTMR2 in hepatocellular carcinoma (HCC) have not been systematically and comprehensively studied. The aim of this study was to explore the role of MTMR2 in HCC. We obtained the raw data from Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Afterward, we analyzed the data using R and cBioPortal. We investigated the connection between MTMR2 and its expression, prognosis, clinical significance, methylation, genetic alterations, tumor microenvironment (TME), tumor mutation burden (TMB), and drug reactivity in HCC patients. MTMR2 expression levels in HCC cells were validated through western blotting and RT-qPCR. MTMR2 exhibits high levels of expression across a wide range of cancer types, including HCC. MTMR2 is diagnostically valuable in detecting HCC, with its up-regulated expression often being indicative of poor prognosis among HCC patients. The in vitro experiments confirmed elevated MTMR2 expression in HepG2, HUH-7, and MHCC-97H cells. Univariate and multivariate Cox analysis demonstrated that MTMR2 was an independent prognostic factor in HCC patients. The cg20195272 site has the highest degree of methylation in MTMR2, and it is positively correlated with MTMR2 expression. Patients with high levels of methylation at the cg20195272 site show poor prognosis. Analysis of the TME indicates that high expression of MTMR2 is associated with elevated ESTIMATE score and that MTMR2 expression correlates positively with infiltration by resting memory CD4 T cells, activated dendritic cells, as well as several immune checkpoints. There is a negative correlation between MTMR2 expression and TMB, and drug sensitivity analyses have shown that higher MTMR2 expression is associated with lower IC50 values. This study indicates that increased expression of MTMR2 may play a crucial role in the occurrence, progression, diagnosis, prognostic prediction and drug therapy of HCC.
Structural damage detection using deep learning and FE model updating techniques
Authors: Lee Yunwoo , Kim Heesoo , Min Seongi , Yoon Hyungchul 
Published: October 2023

AbstractThe structural condition can be estimated by various methods. Damage detection, as one of those methods, deals with identifying changes in specific features within structural behavior based on numerical models. Since the method is based on simulation for various damage conditions, there are limitations in applicability due to inevitable discrepancies between the analytical model and the actual structure. Finite element model updating is a technique for establishing a finite element model that can reflect the current state of a target structure based on the measured responses. It is performed based on optimization for various structural parameters, but the final output can converge differently depending on the initial model and the characteristics of the algorithm. Although the updated model may not faithfully replicate the target structure as it is, it can be considered equivalent in terms of the relationship between the structural properties and behavioral characteristics of the target. This allows for the analysis of changes in the mechanical relationships established for the target structure. The change can be related to structural damage, and artificial intelligence technology can provide an alternative solution in such complex problems where analytical approaches are challenging. Taking practical aspects from the aforementioned methods, a novel structural damage detection methodology is presented in this study for identifying the location and extent of the damage. Model updating is used to establish a reference model that reflects the structural characteristics of the target. Training data for various damage conditions based on the reference model allows the artificial intelligence networks to identify damage to the target structure.
Distortion correction using topup algorithm by single k-space (TASK) for echo planar imaging
Authors: Hwang Seon-Ha , Lee Hyun-Soo , Choi Seung Hong , Park Sung-Hong 
Published: October 2023

AbstractDistortion of echo planar imaging (EPI) can be corrected using B0field maps, which can be estimated with the topup algorithm that requires two EPI images with opposite distortions. In this study, we propose a new algorithm, termed topup algorithm by single K-space (TASK), to generate two input images from a single k-space for the topup algorithm to correct EPI distortions. The centric EPI contains the opposite phase-encoding polarities in one k-space, which can be divided into two halves with opposite distortions. Therefore, two inputs could be extracted by dividing the k-space into halves and processing them using the proposed procedure including an iterative procedure of automatic brain masking and uniformity correction. The efficiency of TASK was evaluated using 3D EPI. Quantitative evaluations showed that TASK corrected EPI distortion at a similar level to the traditional methods. The estimated field maps from the conventional topup and TASK showed a high correlation ($$r=0.80\pm 0.05$$r=0.80±0.05). An ablation study showed the validity of every suggested step. Furthermore, it was confirmed that TASK was effective for distortion correction of two-shot centric EPI as well, demonstrating its wider applicability. In conclusion, TASK can correct EPI distortions by its own single k-space information with no additional scan.
Non-operative treatment for simple acute appendicitis (NOTA) in children during the COVID-19 era: new lessons from the pandemic
Authors: Alsaggaf Ameen , Owiwi Yazeed , Shalaby Mohamed , Ghallab Alaa , Zidan Mazen , Alawi Ahmed , Bustangi Nasir , Awad Mohammed , Bana Abdulelah , Al Zeair Saad , Afandi Ahmed , Basyouni Ahmed , Al Nasser Ibrahim , Raml Enas , Raboei Enaam 
Published: October 2023

AbstractCoronavirus (COVID-19) was a pandemic disease that was affecting our medical and surgical daily practice badly. The surgical management of acute appendicitis was the gold standard, but new studies suggest the safety of antibiotic treatment alone. Non-operative treatment for simple acute appendicitis (NOTA) avoids surgery, the risks of general anesthesia, and long hospital stays. It also decreases the risk of exposure to coronavirus. We aimed to study the cost-effectiveness and outcome of NOTA during the COVID-19 pandemic and compared it to single-incision pediatric endo-surgery appendectomy (SIPESA). A prospective cohort study for NOTA of patients from 6 to 12 years old in the COVID-19 pandemic period from April 1st, 2020, to April 30th, 2021, patients were divided into two groups: Group S was managed by SIPESA, and Group N was managed by NOTA. Family education and assurance with detailed explanation were done for early detection of any complications, and we continue monitoring the patients until their complete recovery. Group S had 24 cases (40%), mean age 9.3 years. Group N had 36 cases (60%), mean age 9.1 years. Six cases (17%) in group N were converted to surgical management in the first 6 months of the study. The mean cost dropped from $2736/day to $400/day. The mean psychological stress for the children improved from 4.4 in April to 2 in September. The mean follow-up was 3.5 months. NOTA is a feasible, cost-effective approach, and we recommend it, as we have learned this lesson during the COVID-19 pandemic days.
A three-dimensional vision measurement method based on double-line combined structured light
Authors: Wang Mingze , Sun Qiucheng , Gao Changbo , Ren Zeming , Dai Weiyu 
Published: October 2023

AbstractIn this paper, a structured light vision measurement method using a scanning laser line and a positioning laser line is proposed. The novel method enables the scanning laser plane to slide along a slide rail while maintaining intersection with the positioning laser plane, eliminating the need to determine the scanning direction and moving step. During the measurement process, the laser plane equations need to be recalibrated for each new position, so a real-time calibration method is given. Initially, the geometric barycenter method is employed to detect the subpixel coordinates of the light stripe intersection point. Subsequently, these coordinates are projected into the camera coordinate system using the initial equations of the positioning laser plane. Finally, leveraging the normal information of the initial equation of the scanning laser plane and the three-dimensional coordinates of the light stripe intersection point, the real-time calibration of the scanning laser plane equations can be accomplished. The proposed method enables the three-dimensional reconstruction of objects, and its accuracy is verified through measurements on gauge blocks. Experimental results demonstrate that this method achieves precise and stable three-dimensional reconstruction of object surface shape.
Effects of slight shading in summer on the leaf senescence and endogenous hormone and polyamine contents in herbaceous peony
Authors: Xie Anqi , Lv Mengwen , Zhang Dongliang , Shi Yajie , Yang Lijin , Yang Xiao , Du Jie , Sun Limin , Sun Xia 
Published: October 2023

AbstractHerbaceous peony is a perennial root plant that likes light and is cold-resistant. During summer, high temperature and strong light intensity advance its entry into the leaf wilting stage, which limits the accumulation of nutrients and formation of strong buds and severely affects its growth and development the following year. In this study, the wild herbaceous peony species and two main cultivars, ‘Zifengyu’ and ‘Hongfengyu’, were subjected to slight shading and strong light environments in summer, and their effects on leaf senescence and endogenous hormone and polyamine contents were explored. Slight shading treatment significantly delayed withering, increased the leaf net photosynthetic rate, and increased the chlorophyll, soluble sugar, indole-3-acetic acid, zeatin, gibberellin, spermine, spermidine, putrescine, and polyamine contents. Additionally, slight shading significantly reduced the proline and abscisic acid contents. Slight shading during summer prolonged the green period and delayed leaf senescence. The tolerance of tested materials to strong light intensity in summer was ranked as follows: ‘Zifengyu’ > ‘Hongfengyu’ > wild species. In conclusion, this study revealed that summer leaf senescence is delayed in herbaceous peony through shading and growth regulators. Additional varieties should be evaluated to provide reference for high-efficiency, high-quality, and high-yield cultivation of herbaceous peony.
Combination of genomic instability score and TP53 status for prognosis prediction in lung adenocarcinoma
Authors: Feng Juan , Lan Yang , Liu Feng , Yuan Ye , Ge Jia , Wei Sen , Luo Hu , Li Jianjun , Luo Tao , Bian Xiuwu 
Published: October 2023

AbstractThe genomic instability (GI) /homologous recombination deficiency (HRD) score, calculated as the sum of the events of loss of heterozygosity (LOH), large-scale state transition (LST) and telomere allele imbalance (TAI), is used to guide the choice of treatment in several cancers, but its relationship with genomic features, clinicopathological characteristics and prognosis in lung cancer is poorly understood, which could lead to population bias in prospective studies. We retrospectively analyzed 1011 lung cancer patients whose tumor samples were successfully profiled by high-throughput sequencing panel including GI/HRD score. Alterations of many cancer suppressor genes were associated with higher GI/HRD scores, biallelic inactivation of TP53 was correlated with a high GI/HRD score. A combination of two gene alterations exhibited a higher GI/HRD scores than single gene alterations. The GI/HRD score was associated with advanced stages in lung adenocarcinoma but not in lung squamous cell carcinoma. Furthermore, patients with higher GI/HRD scores had significantly shorter overall survival and progression-free survival than patients with lower GI/HRD scores. Finally, patients with a combination of a higher GI/HRD scores and TP53 alteration exhibited an extremely poor prognosis compared with patients with a lower GI/HRD scores and wild-type TP53 (overall survival, training cohort, hazard ratio (HR) = 8.56, P < 0.001; validation cohort, HR = 6.47, P < 0.001; progression-free survival, HR = 4.76, P < 0.001). Our study revealed the prognostic value of the GI/HRD score in lung adenocarcinoma, but not for all lung cancer. Moreover, the combination of the GI/HRD score and TP53 status could be a promising strategy to predict the prognosis of patients with lung adenocarcinoma.
Ship detection based on YOLO algorithm for visible images
Authors: Huang Qian , Sun Huashan , Wang Yiming , Yuan Yang , Guo Xiaotong , Gao Qiang 
Published: October 2023

AbstractShip detection is a crucial task for waterway surveillance and channel optimization, especially in close proximity to the shore. However, detecting ship in visible image‐based detection remains a challenge due to the limited nature of visible image datasets. To address this issue, the Inland Ships Data Set (ISDS) is constructed to facilitate research on ship identification. On the other hand, most detection methods struggle to accurately identify ships that are small in size. Therefore, a visible image‐based ship detection model is proposed that employs a multi‐scale weighted feature fusion structure with the YOLOv4 detection model to improve the efficacy of small ship detection. Specifically, the YOLOv4 model is improved through fusing multi‐scale feature, redesigning priori frame, and enhancing loss function. The model, named YOLOv4‐MSW (i.e. YOLOv4 based on Multi‐Scale Weighted feature fusion), exhibits improved performance on ship detection in experiments conducted on the ISDS dataset, outperforming the original YOLOv4 model by improving the average precision (AP) by 4.87% and the recall rate by 10.03%. Meanwhile, the model achieve better detection accuracy and improve the average precision rate by at least 0.86% compared to existing learned object detection methods. The code related to this work are released at https://github.com/Sunhuashan/YOLOv4‐MSW. The whole dataset is available at https://drive.google.com/drive/folders/1fzJ2fcqiko6lFwqIEGghMceoQgv‐8jBy.
Optimal output‐constrained control of medium‐voltage DC shipboard power systems for pulsed power load accommodation
Authors: Tu Zhenghong , Peng Jiangkai , Fan Bo , Liu Liming , Liu Wenxin 
Published: October 2023

AbstractFor pulsed power load (PPL) accommodation in a medium‐voltage DC (MVDC) shipboard power system (SPS), the charging control of energy storage systems (ESSs) and the generation control of distributed generators (DGs) need to be properly coordinated. Targeting the important but not well‐studied problem, an optimal output‐constrained control algorithm for the offline PPL accommodation strategy is presented. Three control objectives including realising the generation and charging control references, maintaining the DC bus and supercapacitor voltages within the safe operating ranges, and minimising the total generation cost of DGs, are fulfilled concurrently. First, an SPS model with multiple DGs, a supercapacitor ESS, and regular loads is developed. By restricting the DC bus and supercapacitor voltages within pre‐defined constraints, both the transient‐ and steady‐state performances of the SPS are guaranteed. Furthermore, by incorporating the cost minimisation objective into designed virtual control signals, the third control objective on energy efficiency is realised. The stability of the presented algorithm is rigorously proven based on the Lyapunov method. Finally, detailed case studies are conducted to validate the performance of the designed algorithm.