bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictors of Ureteral Strictures after Retrograde Ureteroscopic Treatment of Impacted Ureteral Stones: A Systematic Literature Review
Authors: Tonyali Senol , Yilmaz Mehmet , Tzelves Lazaros , Emiliani Esteban , De Coninck Vincent De , Keller Etienne Xavier , Miernik Arkadiusz
Published: May 2023

Background: The stricture-formation rate following ureteroscopy ranges from 0.5 to 5% and might amount to 24% in patients with impacted ureteral stones. The pathogenesis of ureteral stricture formation is not yet fully understood. It is likely that the patient and stone characteristics, as well as intervention factors, play a role in this process. In this systematic review, we aimed to determine the potential factors responsible for ureteral stricture formation in patients having impacted ureteral stones. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) criteria, we conducted systematic online research through PubMed and Web of Science without a time restriction, applying the keywords “ureteral stone”, “ureteral calculus”, “impacted stone”, “ureteral stenosis”, “ureteroscopic lithotripsy”, “impacted calculus”, and “ureteral strictures” singly or in combination. Results: After eliminating non-eligible studies, we identified five articles on ureteral stricture formation following treatment of impacted ureteral stones. Ureteral perforation and/or mucosal damage appeared as key predictors of ureteral stricture following retrograde ureteroscopy (URS) for impacted ureteral stones. Besides ureteral perforation stone size, embedded stone fragments into the ureter during lithotripsy, failed URS, degree of hydronephrosis, nephrostomy tube or double-J stent (DJS)/ureter catheter insertion were also suggested factors leading to ureteral strictures. Conclusion: Ureteral perforation during surgery might be considered the main risk factor for ureteral stricture formation following retrograde ureteroscopic stone removal for impacted ureteral stones.
Laboratory Data and IBDQ—Effective Predictors for the Non-Invasive Machine-Learning-Based Prediction of Endoscopic Activity in Ulcerative Colitis
Authors: Gavrilescu Otilia , Popa Iolanda Valentina , Dranga Mihaela , Mihai Ruxandra , Cijevschi Prelipcean Cristina , Mihai Cătălina
Published: May 2023

A suitable, non-invasive biomarker for assessing endoscopic disease activity (EDA) in ulcerative colitis (UC) has yet to be identified. Our study aimed to develop a cost-effective and non-invasive machine learning (ML) method that utilizes the cost-free Inflammatory Bowel Disease Questionnaire (IBDQ) score and low-cost biological predictors to estimate EDA. Four random forest (RF) and four multilayer perceptron (MLP) classifiers were proposed. The results show that the inclusion of IBDQ in the list of predictors that were fed to the models improved accuracy and the AUC for both the RF and the MLP algorithms. Moreover, the RF technique performed noticeably better than the MLP method on unseen data (the independent patient cohort). This is the first study to propose the use of IBDQ as a predictor in an ML model to estimate UC EDA. The deployment of this ML model can furnish doctors and patients with valuable insights into EDA, a highly beneficial resource for individuals with UC who need long-term treatment.
Dual-Source Photon-Counting Computed Tomography—Part I: Clinical Overview of Cardiac CT and Coronary CT Angiography Applications
Authors: Cademartiri Filippo , Meloni Antonella , Pistoia Laura , Degiorgi Giulia , Clemente Alberto , Gori Carmelo De , Positano Vincenzo , Celi Simona , Berti Sergio , Emdin Michele , Panetta Daniele , Menichetti Luca , Punzo Bruna , Cavaliere Carlo , Bossone Eduardo , Saba Luca , Cau Riccardo , Grutta Ludovico La , Maffei Erica
Published: May 2023

The photon-counting detector (PCD) is a new computed tomography detector technology (photon-counting computed tomography, PCCT) that provides substantial benefits for cardiac and coronary artery imaging. Compared with conventional CT, PCCT has multi-energy capability, increased spatial resolution and soft tissue contrast with near-null electronic noise, reduced radiation exposure, and optimization of the use of contrast agents. This new technology promises to overcome several limitations of traditional cardiac and coronary CT angiography (CCT/CCTA) including reduction in blooming artifacts in heavy calcified coronary plaques or beam-hardening artifacts in patients with coronary stents, and a more precise assessment of the degree of stenosis and plaque characteristic thanks to its better spatial resolution. Another potential application of PCCT is the use of a double-contrast agent to characterize myocardial tissue. In this current overview of the existing PCCT literature, we describe the strengths, limitations, recent applications, and promising developments of employing PCCT technology in CCT.
The Future of Minimal-Access Myoma Surgery with In-Bag Contained Morcellation
Authors: Devassy Rajesh , Devassy Rohan Rajesh , de Wilde Maya Sophie , Krentel Harald , Adlan Aizura , Torres-de la Roche Luz Angela , De Wilde Rudy Leon
Published: May 2023

Contained electromechanical morcellation has emerged as a safety approach for laparoscopic myomatous tissue retrieval. This retrospective single-center analysis evaluated the bag deployment practicability and safety of electromechanical in-bag morcellation when used for big surgical benign specimens. The main age of patients was 39.3 years (range 21 to 71); 804 myomectomies, 242 supracervical hysterectomies, 73 total hysterectomies, and 1 retroperitoneal tumor extirpation were performed. A total of 78.7% of specimens weighed more than 250 g (n = 881) and 9% more than 1000 g. The largest specimens, weighing 2933 g, 3183 g, and 4780 g, required two bags for complete morcellation. Neither difficulties nor complications related to bag manipulation were recorded. Small bag puncture was detected in two cases, but peritoneal washing cytology was free of debris. One retroperitoneal angioleiomyomatosis and three malignancies were detected in histology (leiomyosarcoma = 2; sarcoma = 1); therefore, patients underwent radical surgery. All patients were disease-free at 3 years follow-up, but one patient presented multiple abdominal metastases of the leiomyosarcoma in the third year; she refused subsequent surgery and was lost from follow-up. This large series demonstrates that laparoscopic bag morcellation is a safe and comfortable method to remove large and giant uterine tumors. Bag manipulation takes only a few minutes, and perforations rarely occur and are easy to detect intraoperatively. This technique did not result in the spread of debris during myoma surgery, potentially avoiding the additional risk of parasitic fibroma or peritoneal sarcoma.
Eye Movements as Proxy for Visual Working Memory Usage: Increased Reliance on the External World in Korsakoff Syndrome
Authors: Böing Sanne , Ten Brink Antonia F. , Hoogerbrugge Alex J. , Oudman Erik , Postma Albert , Nijboer Tanja C. W. , Van der Stigchel Stefan
Published: May 2023

In the assessment of visual working memory, estimating the maximum capacity is currently the gold standard. However, traditional tasks disregard that information generally remains available in the external world. Only when to-be-used information is not readily accessible, memory is taxed. Otherwise, people sample information from the environment as a form of cognitive offloading. To investigate how memory deficits impact the trade-off between sampling externally or storing internally, we compared gaze behaviour of individuals with Korsakoff amnesia (n = 24, age range 47–74 years) and healthy controls (n = 27, age range 40–81 years) on a copy task that provoked different strategies by having information freely accessible (facilitating sampling) or introducing a gaze-contingent waiting time (provoking storing). Indeed, patients sampled more often and longer, compared to controls. When sampling became time-consuming, controls reduced sampling and memorised more. Patients also showed reduced and longer sampling in this condition, suggesting an attempt at memorisation. Importantly, however, patients sampled disproportionately more often than controls, whilst accuracy dropped. This finding suggests that amnesia patients sample frequently and do not fully compensate for increased sampling costs by memorising more at once. In other words, Korsakoff amnesia resulted in a heavy reliance on the world as ‘external memory’.
Nanocellulose as an Avenue for Drug Delivery Applications: A Mini-Review
Authors: Varghese Rini , Cherian Reeba , Chirayil Cintil , Antony Tijo , Kargarzadeh Hanieh , Thomas Sabu
Published: May 2023

A controlled and sustained release of an accurate dose of medications into a system can cure diseases associated with the human body. Different potential drug delivery vehicles, which are biocompatible and non-toxic, have been synthesized and developed for the controlled release of drugs targeting specific organs or areas. A delivery agent procured from sustainable sources with less or no side effects is more advantageous in terms of compatibility and toxicity. Among a few bioresources, one such material obtained is the nanocellulose-based drug delivery vehicle. They are ideal for the transport and release of drugs since they are biocompatible and possess good mechanical properties. A major characteristic feature of nanocellulose is that different surface modifications are possible due to the presence of a large number of hydroxyl groups, which can strengthen the interactions required with the therapeutic drug for delivery. Pharmaceutical drugs can strongly bind to the nanocellulose material through electrostatic interactions, and the release can occur in a sustained manner to the target within a few minutes to several days. In this mini-review, we have tried to summarize some of the most important works carried out in the field of nanocellulose-based drug delivery, different types of nanocellulose, its surface modification possibilities, and delivery of medications through three main routes, oral, transdermal, and topical, that have been reported to be effective.
The Effect of Ice Floe on the Strength, Stability, and Fatigue of Hybrid Flexible Risers in the Arctic Sea
Authors: Korotygin Dimitrii , Nammi Sathish. K. , Pancholi Ketan
Published: May 2023

Flexible risers have proven to be a popular choice for deepwater exploration due to their ability to withstand functional and environmental stress while maintaining system integrity. In the challenging arctic conditions, lightweight hybrid composite flexible risers are likely to be employed to mitigate the increase in effective tension. This study investigates the strength and stability performance of production hybrid composite flexible risers with composite pressure armour in the harsh environmental conditions of the Arctic seas. At a water depth of 340 m, the flexible riser was analysed in various global configurations to evaluate the static, dynamic, and lamina-scale performance of its carbon fibre-reinforced thermoplastic polymer composite layer. The drifting ice in the region generated additional load on the riser system, and the effects of this ice on the riser design and its dynamic and lamina-level performances were also analysed. The results indicate that the current riser design incorporating the composite layer is insufficient to ensure system integrity without mitigating the effects of ice loading. The carbon fibre direction in each lamina must be optimised for excess axial stress emanating from the combined action of hoop, axial, and bending stresses. Finally, recommendations on how to improve the life of the lightweight hybrid composite riser in arctic conditions are provided.
Muscle Strength and Hamstrings to Quadriceps Ratio in Young Soccer Players: A Cross-Sectional Study
Authors: Mandroukas Athanasios , Michailidis Yiannis , Metaxas Thomas
Published: May 2023

The aim of the present study was to examine and compare the concentric isokinetic peak torque of the knee flexors and extensors muscles, as well as their ratio, in young soccer players. Two hundred and sixty-five (n = 265) young soccer players were divided into five groups: U-12 (n = 43, mean age 11.5 ± 0.4 yrs), U-14 (n = 63, mean age 13.6 ± 0.3 yrs), U-16 (n = 64, mean age 15.4 ± 0.5 yrs), U-18 (n = 53, mean age 17.5 ± 0.4 yrs) and U-20 (n = 42, mean age 19.3 ± 0.6 yrs). Three maximal voluntary isokinetic leg extensions and flexions at angular velocities of 60, 180, and 300°·s−1, and H:Q strength ratio was determined. The largest H:Q strength ratio for all ages, with the exception of age group U-12, appears at a slow angular velocity of 60°·s−1, and the smallest H:Q ratio at a fast angular velocity of 300°·s−1. In age group U-12, at an angular velocity of 60°·s−1, the strength of the quadriceps muscle was almost twice the strength of the hamstrings. The H:Q strength ratio was smaller in age group U-12 and greater in group U-20. In age group U-12, the greatest H:Q strength ratio appeared at an angular velocity of 180°·s−1, while in the other age groups, it appeared at 60°·s−1. Strength training of hamstring muscles remains inadequate across ages. The small H:Q strength ratio in younger ages and the large H:Q ratio in older ages suggest that high-intensity training may increase the H:Q strength ratio, which, in turn, may protect the knee joint from excessive and burdensome loads.
Possibilities of Artificial Intelligence-Enabled Feedback Control System in Robotized Gas Metal Arc Welding
Authors: Penttilä Sakari , Lund Hannu , Skriko Tuomas
Published: May 2023

In recent years, welding feedback control systems and weld quality estimation systems have been developed with the use of artificial intelligence to increase the quality consistency of robotic welding solutions. This paper introduces the utilization of an intelligent welding system (IWS) for feedback controlling the welding process. In this study, the GMAW process is controlled by a backpropagation neural network (NN). The feedback control of the welding process is controlled by the input parameters; root face and root gap, measured by a laser triangulation sensor. The NN is trained to adapt NN output parameters; wire feed and arc voltage override of the weld power source, in order to achieve consistent weld quality. The NN is trained offline with the specific parameter window in varying weld conditions, and the testing of the system is performed on separate specimens to evaluate the performance of the system. The butt-weld case is explained starting from the experimental setup to the training process of the IWS, optimization and operating principle. Furthermore, the method to create IWS for the welding process is explained. The results show that the developed IWS can adapt to the welding conditions of the seam and feedback control the welding process to achieve consistent weld quality outcomes. The method of using NN as a welding process parameter optimization tool was successful. The results of this paper indicate that an increased number of sensors could be applied to measure and control the welding process with the developed IWS.
The Study of Fishing Vessel Behavior Identification Based on AIS Data: A Case Study of the East China Sea
Authors: Xing Bowen , Zhang Liang , Liu Zhenchong , Sheng Hengjiang , Bi Fujia , Xu Jingxiang
Published: May 2023

The goal of this paper is to strengthen the supervision of fishing behavior in the East China Sea and effectively ensure the sustainable development of fishery resources. Based on AIS data, this paper analyzes three types of fishing boats (purse seine operation, gill net operation and trawl operation) and uses the cubic spline interpolation algorithm to optimize the ship trajectory and construct high-dimensional features. It proposes a new coding method for fishing boat trajectory sequences. This method uses the Geohash algorithm to divide the East China Sea into grids and generate corresponding numbers. Then, the ship trajectory is mapped to the grid, the fishing boat trajectory points are associated with the divided grid, and the ship trajectory ID is extracted from the corresponding grid. The extracted complete trajectory sequence passes through the CBOW (continuous bag of words) model, and the correlation of trajectory points is fully learned. Finally, the fishing boat trajectory is converted from coordinate sequence to trajectory vector, and the processed trajectory sequence is trained by the LightGBM algorithm. In order to obtain the optimal classification effect, the optimal superparameter combination is selected. We put forward a LightGBM algorithm based on the Bayesian optimization algorithm, and obtained the classification results of three kinds of fishing boats. The final result was evaluated using the F1_score. Experimental results show that the F1_score trained with the proposed trajectory vectorization method is the highest, with a training accuracy of 0.925. Compared to XgBoost and CatBoost, the F1_score increased by 1.8% and 1.2%, respectively. The results show that this algorithm demonstrates strong applicability and effectiveness in fishery area evaluations and is significant for strengthening fishery resource management.
Joint Optimization of Inventory and Repositioning for Sea Empty Container Based on Queuing Theory
Authors: Wang Qing-Bin , Wang Zhi-Wen , Zheng Jian-Feng
Published: May 2023

Approximately 20% of global container transportation activities are used for empty container repositioning, which does not generate profit margins. For container supply ports, in addition to periodically transporting excess empty containers to container shortage ports to reduce their inventory costs and meet empty container demand of container shortage ports, they also need to maintain a certain amount of empty container inventory to meet their uncertain needs in the future. This paper considers the container supply port and container shortage port as a whole, so that the container supply port maintains a certain amount of empty container inventory to meet its own uncertain needs, and empty container repositioning is carried out based on this. Based on queuing theory, an empty container repositioning model was established with the objective function of minimizing the total cost of the empty container inventory system and the empty container repositioning system and designing genetic algorithms to solve the model. The results indicate that considering empty container inventory and repositioning as a whole resulted in a total cost reduction of approximately 7.2%. Finally, a sensitivity analysis was conducted by changing the parameters in the model, and the results of the sensitivity analysis provided support for the decision-making of shipping lines in different situations.
Array-Based Underwater Acoustic Target Classification with Spectrum Reconstruction Based on Joint Sparsity and Frequency Shift Invariant Feature
Authors: Lu Chenxiang , Zeng Xiangyang , Wang Qiang , Wang Lu , Jin Anqi
Published: May 2023

The target spectrum, which is commonly used in feature extraction for underwater acoustic target classification, can be improperly recovered via conventional beamformer (CBF) owing to its frequency-variant spatial response and lead to degraded classification performance. In this paper, we propose a target spectrum reconstruction method under a sparse Bayesian learning framework with joint sparsity priors that can not only achieve high-resolution target separation in the angular domain but also attain beamwidth constancy over a frequency range at no cost of reducing angular resolution. Experiments on real measured array data show the recovered spectrum via our proposed method can effectively suppress interference and preserve more detailed spectral structures than CBF. This indicates our method is more suitable for target classification because it has the capability of retaining more representative and discriminative characteristics. Moreover, due to target motion and the underwater channel effect, the frequency of prominent spectral line components can be shifted over time, which is harmful to classification performance. To overcome this problem, we proposed a frequency shift-invariant feature extraction method with the help of elaborately designed frequency shift-invariant filter banks. The classification experiments demonstrate that our proposed methods outperform traditional CBF and Mel-frequency features and can help improve underwater recognition performance.
A Side-Scan Sonar Image Synthesis Method Based on a Diffusion Model
Authors: Yang Zhiwei , Zhao Jianhu , Zhang Hongmei , Yu Yongcan , Huang Chao
Published: May 2023

The limited number and under-representation of side-scan sonar samples hinders the training of high-performance underwater object detection models. To address this issue, in this paper, we propose a diffusion model-based method to augment side-scan sonar image samples. First, the side-scan sonar image is transformed into Gaussian distributed random noise based on its a priori discriminant. Then, the Gaussian noise is modified step by step in the inverse process to reconstruct a new sample with the same distribution as the a priori data. To improve the sample generation speed, an accelerated encoder is introduced to reduce the model sampling time. Experiments show that our method can generate a large number of representative side-scan sonar images. The generated side-scan sonar shipwreck images are used to train an underwater shipwreck object detection model, which achieves a detection accuracy of 91.5% on a real side-scan sonar dataset. This exceeds the detection accuracy of real side-scan sonar data and validates the feasibility of the proposed method.
Theory, Method and Engineering Application of Computational Mechanics in Offshore Structures
Authors: Yan Jun , Xu Wanhai , Hu Zhiqiang , Lou Min
Published: May 2023

Oceans cover approximately 71% of the planet’s surface, and 97% of the Earth’s water is contained within the ocean [...]
Stability Analysis of Wind Turbine Blades Based on Different Structural Models
Authors: Wang Bin , Li Ying , Gao Shan , Shen Kanmin , Zhao Shengxiao , Yao Yu , Zhou Zhilu , Hu Zhenhong , Zheng Xing
Published: May 2023

In order to better simulate the actual working conditions of wind turbines more realistically, this paper adopts the two-way fluid–structure coupling method to study the NREL 5 MW wind turbine, considering the blade coupling deformation and equivalent stress and strain distribution of the blades with different internal structures under different working conditions. The results show that the maximum equivalent stress and strain distribution of the beam–structure wind turbine blade was near the leading edge of the blade. The maximum equivalent stress and strain distribution of the shell structure wind turbine blade was near the leading edge of the blade root, and the dangerous area is obvious but smaller than that of the beam-type wind turbine. The coupled deformation of a wind turbine model with a shell structure blade with a web is significantly reduced, and the equivalent stress and strain distribution of the skin is similar to that of the shell structure, but the numerical value and the maximum equivalent stress distribution area are significantly smaller. From the comparison of the three, the shell structure blade with a web is the best.
Fungal–Bacterial Co-Infections and Super-Infections among Hospitalized COVID-19 Patients: A Systematic Review
Authors: Bantun Farkad
Published: May 2023

This study systematically reviewed fungal–bacterial co-infections and super-infections among hospitalized COVID-19 patients. A PRISMA systematic search was conducted. On September 2022, Medline, PubMed, Google Scholar, PsychINFO, Wiley Online Library, NATURE, and CINAHL databases were searched for all relevant articles published in English. All articles that exclusively reported the presence of fungal–bacterial co-infections and super-infections among hospitalized COVID-19 patients were included. Seven databases produced 6937 articles as a result of the literature search. Twenty-four articles met the inclusion criteria and were included in the final analysis. The total number of samples across the studies was 10,834, with a total of 1243 (11.5%) patients admitted to the intensive care unit (ICU). Of these patients, 535 underwent mechanical ventilation (4.9%), 2386 (22.0%) were male, and 597 (5.5%) died. Furthermore, hospitalized COVID-19 patients have a somewhat high rate (23.5%) of fungal–bacterial co-infections and super-infections. Moreover, for SARS-CoV-2 patients who have a chest X-ray that suggests a bacterial infection, who require immediate ICU admission, or who have a seriously immunocompromised condition, empiric antibiotic therapy should be taken into consideration. Additionally, the prevalence of co-infections and super-infections among hospitalized COVID-19 patients may have an impact on diagnosis and treatment. It is crucial to check for fungal and bacterial co-infections and super-infections in COVID-19 patients.
Identification and Characterization of Dmct: A Cation Transporter in Yarrowia lipolytica Involved in Metal Tolerance
Authors: González-Lozano Katia Jamileth , Aréchiga-Carvajal Elva Teresa , Jiménez-Salas Zacarías , Valdez-Rodríguez Debany Marlen , León-Ramírez Claudia Geraldine , Ruiz-Herrera José , Adame-Rodríguez Juan Manuel , López-Cabanillas-Lomelí Manuel , Campos-Góngora Eduardo
Published: May 2023

Yarrowia lipolytica is a dimorphic fungus used as a model organism to investigate diverse biotechnological and biological processes, such as cell differentiation, heterologous protein production, and bioremediation strategies. However, little is known about the biological processes responsible for cation concentration homeostasis. Metals play pivotal roles in critical biochemical processes, and some are toxic at unbalanced intracellular concentrations. Membrane transport proteins control intracellular cation concentrations. Analysis of the Y. lipolytica genome revealed a characteristic functional domain of the cation efflux protein family, i.e., YALI0F19734g, which encodes YALI0F19734p (a putative Yl-Dmct protein), which is related to divalent metal cation tolerance. We report the in silico analysis of the putative Yl-Dmct protein’s characteristics and the phenotypic response to divalent cations (Ca2+, Cu2+, Fe2+, and Zn2+) in the presence of mutant strains, Δdmct and Rdmct, constructed by deletion and reinsertion of the DMCT gene, respectively. The absence of the Yl-Dmct protein induces cellular and growth rate changes, as well as dimorphism differences, when calcium, copper, iron, and zinc are added to the cultured medium. Interestingly, the parental and mutant strains were able to internalize the ions. Our results suggest that the protein encoded by the DMCT gene is involved in cell development and cation homeostasis in Y. lipolytica.
Using EfficientNet-B7 (CNN), Variational Auto Encoder (VAE) and Siamese Twins’ Networks to Evaluate Human Exercises as Super Objects in a TSSCI Images
Authors: Segal Yoram , Hadar Ofer , Lhotska Lenka
Published: May 2023

In this article, we introduce a new approach to human movement by defining the movement as a static super object represented by a single two-dimensional image. The described method is applicable in remote healthcare applications, such as physiotherapeutic exercises. It allows researchers to label and describe the entire exercise as a standalone object, isolated from the reference video. This approach allows us to perform various tasks, including detecting similar movements in a video, measuring and comparing movements, generating new similar movements, and defining choreography by controlling specific parameters in the human body skeleton. As a result of the presented approach, we can eliminate the need to label images manually, disregard the problem of finding the start and the end of an exercise, overcome synchronization issues between movements, and perform any deep learning network-based operation that processes super objects in images in general. As part of this article, we will demonstrate two application use cases: one illustrates how to verify and score a fitness exercise. In contrast, the other illustrates how to generate similar movements in the human skeleton space by addressing the challenge of supplying sufficient training data for deep learning applications (DL). A variational auto encoder (VAE) simulator and an EfficientNet-B7 classifier architecture embedded within a Siamese twin neural network are presented in this paper in order to demonstrate the two use cases. These use cases demonstrate the versatility of our innovative concept in measuring, categorizing, inferring human behavior, and generating gestures for other researchers.
Demographic and Socioeconomic Factors in Prospective Retina-Focused Clinical Trial Screening and Enrollment
Authors: Cao Jessica A. , Patel Sagar B. , Wong Calvin W. , Garcia David , Munoz Jose , Cone Cassandra , Zamora Deneva , Reagan Mary , Nguyen Tieu V. , Pearce Will , Fish Richard H. , Brown David M. , Chaudhary Varun , Wykoff Charles C. , Fan Kenneth C.
Published: May 2023

Historically marginalized populations are disproportionately affected by many diseases that commonly affect the retina, yet they have been traditionally underrepresented in prospective clinical trials. This study explores whether this disparity affects the clinical trial enrollment process in the retina field and aims to inform future trial recruitment and enrollment. Age, gender, race, ethnicity, preferred language, insurance status, social security number (SSN) status, and median household income (estimated using street address and zip code) for patients referred to at least one prospective, retina-focused clinical trial at a large, urban, retina-based practice were retrospectively extracted using electronic medical records. Data were collected for the 12-month period from 1 January 2022, through 31 December 2022. Recruitment status was categorized as Enrolled, Declined, Communication (defined as patients who were not contacted, were contacted with no response, were waiting for a follow-up, or were scheduled for screening following a clinical trial referral.), and Did Not Qualify (DNQ). Univariable and multivariable analyses were used to determine significant relationships between the Enrolled and Declined groups. Among the 1477 patients, the mean age was 68.5 years old, 647 (43.9%) were male, 900 (61.7%) were White, 139 (9.5%) were Black, and 275 (18.7%) were Hispanic. The distribution of recruitment status was: 635 (43.0%) Enrolled, 232 (15.7%) Declined, 290 (19.6%) Communication, and 320 (21.7%) DNQ. In comparing socioeconomic factors between the Enrolled and Declined groups, significant odds ratios were observed for age (p < 0.02, odds ratio (OR) = 0.98, 95% confidence interval (CI) [0.97, 1.00]), and between patients who preferred English versus Spanish (p = 0.004, OR = 0.35, 95% CI [0.17, 0.72]. Significant differences between the Enrolled and Declined groups were also observed for age (p < 0.05), ethnicity (p = 0.01), preferred language (p < 0.05), insurance status (p = 0.001), and SSN status (p < 0.001). These factors may contribute to patient participation in retina-focused clinical trials. An awareness of these demographic and socioeconomic disparities may be valuable to consider when attempting to make clinical trial enrollment an equitable process for all patients, and strategies may be useful to help address these challenges.
How Migration Behavior Affects the Contracted Land Disposal Methods of Rural Migrants in China: An Analysis Based on the Perspective of Geographical Differences
Authors: Zhou Yihu , Fang Tingting
Published: May 2023

Migration leads to the separation of rural people from their contracted land and, thus, affects the human–land relationship, agricultural production, and food security in China’s rural areas. Using spatial autocorrelation analysis, GeoDetector analysis, and geographical weighted regression, the mechanism by which the migration behavior of the rural population impacts their contracted land disposal methods was analyzed in this study, and the spatial heterogeneity of this mechanism was further revealed from the perspective of geographical differentiation. The results of this study show that: (1) Chinese rural migrants exhibit pronounced geographical differences in the disposition of contracted land. The spatial distribution patterns of family operation, subleasing, and abandonment are different. (2) Migration behavior contributes to the differences in contracted land disposal methods across regions. Educational attainment, the number of cities migrated to, and the house purchase rate significantly contribute to the geographical differences among all three contracted land disposal methods. (3) The mechanisms by which migration behavior influences rural migrants’ land disposal decisions vary. The direction and degree of the influence of each factor on family operation are relatively consistent across regions. However, regarding the subleasing and abandonment of contracted land, the mechanisms by which migration behavior influences land disposal decision-making exhibit significant regional heterogeneity. The results of this study provide a useful reference for many countries to solve the problems of the human–land relationship and rural development.
Impact of Climate Change on Agroecosystems and Potential Adaptation Strategies
Authors: Semeraro Teodoro , Scarano Aurelia , Leggieri Angelo , Calisi Antonio , De Caroli Monica
Published: May 2023

Agriculture is currently one of the leading economic sectors most impacted by climate change. Due to its great field of application and its susceptibility to meteorological variability, the effects of climate change on agriculture have significant social and economic consequences for human well-being. Moreover, the increasing need for land spaces for population growth has produced strong competition between food and urbanization, leading to a loss of the agroecosystem that supports food security. This review aims to understand the main risks generated by climate change in agricultural production and the potential strategies that can be applied to increase agriculture’s resilience. Agricultural risk can be linked to the decrease in the productivity of foods, weed overgrowth at the crops expense, increase in parasites, water availability, soil alteration, negative impact on production costs and consequent change in the adopted cultivars, reduction in the pollination process, intense fires, and alteration of product quality. Thus, climate change can impact the provisioning of ecosystem services, reducing food security in terms of quantity and quality for future generations. Finally, in this review, we report the main adaptation strategies to increase agroecosystem resilience in adverse environments generated by climate change. Mainly, we highlight new technologies, such as new breeding technologies and agrivoltaic and smart agricultural applications, which, combined with agroecosystems, can reduce the agricultural risks following climate change (for example, drought events and low availability of water). We suggest that the combination of natural capital and technologies can be defined as an “innovation-based solution” able to support and increase ecosystem service flow in agroecosystems.
Multiscale Structural Mechanics of Rotary Shaft Seals: Numerical Studies and Visual Experiments
Authors: Grün Jeremias , Gohs Marco , Bauer Frank
Published: May 2023

Although rotary shaft seals have been used successfully in many industrial applications for decades, their tribological behavior is still not completely understood. In-depth knowledge of the structural mechanics is essential for the design and optimization of such sealing systems. High complexity results from the multiscale interactions in the tribological system rotary shaft seal. Large macroscopic deformations occur due to the hyperelastic material behavior of elastomers coupled with microscopic tangential distortions of the sealing edge surface in the contact area. This paper includes both numerical and experimental studies on the tribological behavior of rotary shaft seals. A multiscale finite element model provides the simulation of the macroscopic deformations and the microscopic displacements. A test rig equipped with a hollow glass shaft enables in situ visual contact analyses, qualitative determinations of pressure distributions and quantitative measurements of elastomer surface distortions. The optical phenomenon of frustrated total internal reflection enables qualitative evaluations of the pressure distribution. Particle image velocimetry (PIV) is employed to quantify the tangential distortions. The test rig enables the measurement of the friction torque with the same configuration. The results of the numerical and experimental investigations for the radial load, friction torque and tangential distortions are compared and discussed. This serves to validate the simulation methods and the correlation of the measured parameters. This finally results in a solid and validated basis for further tribological investigations of rotary shaft seals.
Collection Auctions-Based Autonomous Intersection Management
Authors: Li Jinjian , Yin Biao , Fang Yong
Published: May 2023

The traffic management system holds immense importance due to its significant impact on human living standards. With the advent of advanced technologies such as natural language processing and autonomous vehicles, this study proposes a novel cooperative traffic management system based on collection auctions at an isolated unsignalized intersection, taking into account the users’ preferences for passing the intersection while being subject to their social credits. Once vehicles enter the vehicle-to-infrastructure communication zone, drivers provide the intersection control center with their bidding information, which reflects their urgency for right-of-way. According to the traffic and biding information, the vehicles’ passing sequence is optimized by the control center, in order to maximize the drivers’ average satisfaction. To demonstrate the effectiveness of the proposed system, a series of simulation experiments were conducted under varying traffic volumes. The simulation results were then compared with several other traffic control systems from the literature. It was shown that the proposed algorithm demonstrates superior performance in terms of computational time, traffic delay, and drivers’ personal satisfaction.
The Concept of Determining Route Signatures in Urban and Extra-Urban Driving Conditions Using Artificial Intelligence Methods
Authors: Małek Arkadiusz , Caban Jacek , Dudziak Agnieszka , Marciniak Andrzej , Vrábel Ján
Published: May 2023

The article describes the implementation of road driving tests with a vehicle in urban and extra-urban traffic conditions. Descriptions of the hardware and software needed for archiving the data obtained from the vehicle’s on-board diagnostic connector are presented. Then, the routes are analyzed using artificial intelligence methods. In this article, the reference of the route was defined as the trajectory of the driving process, represented by the engine rotational speed, the driving speed, and acceleration in the state space. The state space was separated into classes based on the results of the cluster analysis. In the experiment, five classes were clustered. The K-Means clustering algorithm was employed to determine the clusters in the variant without prior labelling of the classes using the teaching method and without participation of a teacher. In this way, the trajectories of the driving process in the five-state state space were determined. The article compares the signatures of routes created in urban and extra-urban driving conditions. Significant differences between the obtained results were indicated. Interesting methods of displaying the saved data are presented and the potential practical applications of the proposed method are indicated.
Spherical Inverted Pendulum on a Quadrotor UAV: A Flatness and Discontinuous Extended State Observer Approach
Authors: Martinez-Vasquez Adrian H. , Castro-Linares Rafael , Rodríguez-Mata Abraham Efraím , Sira-Ramírez Hebertt
Published: May 2023

This article addresses the problem of balancing an inverted spherical pendulum on a quadrotor. The full dynamic model is obtained via the Euler-Lagrange formalism, where the dynamics of the pendulum is coupled to the dynamics of the quadrotor, taking as control inputs the torques associated with the yaw, roll, and pitch dynamics, and a control input for the vertical displacement in height. A trajectory tracking control scheme is proposed by means of an active disturbance rejection control based on a discontinuous extended state observer (ADRC-DESO) that allows controlling the system in the translational dynamics of the quadrotor including the rotational dynamics and the inverted pendulum dynamics. To address this problem, the dynamic model is linearized around an equilibrium point, taking into consideration that the system operates in close vicinity of the equilibrium points, thus considerably simplifying the dynamic model. Proving that the linear model is controllable and therefore differentiable flat, flat outputs are proposed around the displacements associated with the three cartesian axes of the Euclidean space, including a dynamic associated with the yaw dynamics of the quadrotor allowing to parameterize the full linear system. Simulation results as well as a convergence analysis validate the performance of the strategy.
Research on Swing Model and Fuzzy Anti Swing Control Technology of Bridge Crane
Authors: Yu Zhen , Dong Hao-Ming , Liu Chang-Ming
Published: May 2023

A bridge crane is often used in a complex environment and is often subject to the interference of all loads. Some uncertain factors often have an inevitable impact on its swing. So the force situation of the bridge crane during a working cycle is analyzed, and a three-dimensional dynamic mathematical model of the bridge crane is built. Through the simulation analysis of the model under the action of a driving force and wind load, the change law of the swing angle of the bridge crane is studied. Then, the fuzzy control theory is used to determine the control parameter in the anti-sway control process. The position, swing angle deviation, and deviation rate of the bridge crane are taken as the input, and the parameter correction is obtained after the fuzzification by using the center of gravity method. The anti-sway fuzzy control system of the bridge crane is designed and simulated. The research results show that the swing model of the crane is reasonable and the fuzzy PID anti-sway controller can not only improve the adaptability of the control system, but also overcome the large overshoot, quickly restrain the swing, and effectively realize the anti-sway function of the bridge crane.
Friction in Adhesive Contacts: Experiment and Simulation
Authors: Lyashenko Iakov A. , Filippov Alexander E. , Popov Valentin L.
Published: May 2023

An experimental study of the process of friction between a steel spherical indenter and a soft elastic elastomer, with a strongly pronounced adhesive interaction between the surfaces of the contacting bodies, is presented. We consider sliding of the indenter at low speed (quasi-static contact) for different indentation depths. The forces, displacements and contact configuration as functions of time were recorded. The most important finding is that under conditions of uni-lateral continuous sliding, the tangential stress in the contact area remains constant and independent on the indentation depth and details of loading. We suggest a simple numerical model in which the elastic substrate is considered as a simple elastic layer (thus reminding a two-dimensional elastic foundation), although with in-plane elastic interactions. It is found that this model leads to the dynamic scenarios which qualitatively resemble the experimentally observed behavior of the considered system.
Fixed Point Results in F-Bipolar Metric Spaces with Applications
Authors: Alamri Badriah
Published: May 2023

The aim of this research article is to obtain fixed point results in the context of F-bipolar metric spaces. The obtained results extend some fixed point theorems in the existing literature. We also provide a non-trivial example to validate our claims. The existence and uniqueness of the solution of the integral equation are proved as applications of our leading results. Furthermore, the existence of the unique solution in homotopy theory is also investigated.
An FW–GA Hybrid Algorithm Combined with Clustering for UAV Forest Fire Reconnaissance Task Assignment
Authors: Liu Xinlin , Jing Tian , Hou Linyi
Published: May 2023

The assignment of tasks for unmanned aerial vehicles (UAVs) during forest fire reconnaissance is a highly complex and large-scale problem. Current task allocation methods struggle to strike a balance between solution speed and effectiveness. In this paper, a two-phase centralized UAV task assignment model based on expectation maximization (EM) clustering and the multidimensional knapsack model (MKP) is proposed for the forest fire reconnaissance task assignment. The fire situation information is acquired using the sensors carried by satellites at first. Then, the EM algorithm based on the Gaussian mixture model (GMM) is applied to get the initial position of every UAV. In the end, the MKP is applied for UAV task assignment based on the initial positions of the UAVs. An improved genetic algorithm (GA) based on the fireworks algorithm (FWA) is proposed for faster iteration speed. A simulation was carried out against the background of forest fires in Liangshan Prefecture, Sichuan Province, and the simulation’s results demonstrate that the task assignment model can quickly and effectively address task allocation problems on a large scale. In addition, the FW–GA hybrid algorithm has great advantages over the traditional GA, particularly in solving time, iteration convergence speed, and solution effectiveness. It can reduce up to 556% of the iteration time and increase objective function value by 1.7% compared to the standard GA. Furthermore, compared to the GA–SA algorithm, its solving time is up to 60 times lower. This paper provides a new idea for future large-scale UAV task assignment problems.
Splines Parameterization of Planar Domains by Physics-Informed Neural Networks
Authors: Falini Antonella , D’Inverno Giuseppe Alessio , Sampoli Maria Lucia , Mazzia Francesca
Published: May 2023

The generation of structured grids on bounded domains is a crucial issue in the development of numerical models for solving differential problems. In particular, the representation of the given computational domain through a regular parameterization allows us to define a univalent mapping, which can be computed as the solution of an elliptic problem, equipped with suitable Dirichlet boundary conditions. In recent years, Physics-Informed Neural Networks (PINNs) have been proved to be a powerful tool to compute the solution of Partial Differential Equations (PDEs) replacing standard numerical models, based on Finite Element Methods and Finite Differences, with deep neural networks; PINNs can be used for predicting the values on simulation grids of different resolutions without the need to be retrained. In this work, we exploit the PINN model in order to solve the PDE associated to the differential problem of the parameterization on both convex and non-convex planar domains, for which the describing PDE is known. The final continuous model is then provided by applying a Hermite type quasi-interpolation operator, which can guarantee the desired smoothness of the sought parameterization. Finally, some numerical examples are presented, which show that the PINNs-based approach is robust. Indeed, the produced mapping does not exhibit folding or self-intersection at the interior of the domain and, also, for highly non convex shapes, despite few faulty points near the boundaries, has better shape-measures, e.g., lower values of the Winslow functional.