bluuebunny/crossref_metadata_2025 huggingface dataset:
Corrosion Hazards on Urban Infrastructure Structures on the Example of the Al Bayt Stadium in Katar
Authors: Królikowska Agnieszka , Bonora Pier Luigi
Published: July 2023

A huge part of corrosion failures and even of catastrophes takes origin from a trivial mistake in either choice or connection of different materials, as well as from an inaccurate evaluation of the compatibility between materials an environment. The example shown in the present paper summarizes several wrong solutions due to the lack of knowledge of the basic rules of corrosion control. By chance, either the consequences of such mistakes were so precocious that it was possible to find a remedy during the construction, or they were happily so venial as to be tolerated. This paper is third in a series devoted to enhancing the need of a professional corrosion control design for infrastructures.
Optical Super‐Resonances in Mesoscale Dielectric Cenosphere: Giant Magnetic Field Generations
Authors: Minin Oleg V , Zhou Song , Minin Igor V
Published: July 2023

Resonant light scattering by mesoscale dielectric spheres has received enormous attention and found many interesting applications. The recently emerged field of Mesotronics provides novel opportunities for wavelength-scaled optics and new fundamental aspects are still being uncovered. It has recently been demonstrated that high-order Mie resonances can be excited in homogeneous low-dissipation mesoscale dielectric spheres, leading to the generation of intense magnetic fields. This Letter describes a simple and effective way to drastically enhance the superresonance effect. Proof-of-principle results for the first time show that yet one more novel phenomenon of increasing the intensity of the magnetic field without changing the resonant Mie size parameter of the sphere by introducing an air cavity. In such a dielectric cenosphere (from two Greek words “kenos” - hollow and “sphaira” - sphere), by correct choosing of the air cavity size, it is possible to increase the intensity of the electromagnetic fields at the poles of the sphere by an order of magnitude due to increasing of amplitude of resonant partial wave coefficient.
Scaled-Invariant Extended Quasi-Lindley Model: Properties, Estimation and Application
Authors: Kayid Mohamed , Abouammoh Abdulrahman , Alomani Ghadah
Published: July 2023

In many research fields, statistical probability models are often used to analyze real-world data. However, data from many fields, such as the environment, economics, and health care, do not necessarily fit traditional models. New empirical models need to be developed to improve their fit. In this paper, we explore a further extension of the quasi-Lindley model. Maximum likelihood, least square error, Anderson-Darling algorithm, and expectation-maximization algorithm are four techniques for estimating the parameters under study. All techniques provide accurate and reliable estimates of the parameters. However, the mean square error of the expectation maximization approach was lower. The usefulness of the proposed model was demonstrated by analyzing a dynamical systems data set, and the analysis shows that it outperforms the other models in all statistical models considered.
Digital Technologies Selection under Hesitant Fuzzy Information: The Case of the Automotive Sector
Authors: Gallab Maryam , Lamrani Youssef , Bouloiz Hafida , Di Nardo Mario , Tkiouat Mohamed , Jebbor Sara , Elfakir Adil
Published: July 2023

With advances in information technology, big data, mobile communications, and robotics, digital technologies are increasingly being used in factories around the world. This digital transformation is named industry 4.0. Today, industrial companies are looking at how to adopt this era and implement these technologies 4.0 while improving their performance and generating more profits.
The objective of this paper is to help companies to better choose the appropriate digital technologies according to their activities using a multi-experts-multi-criteria decision-making approach under hesitant fuzzy information. The proposed model is a generic model based on Multi-Agent Systems allowing to have an idea of the parameters necessary to apply the adopted approach.
The adopted approach allows a better representation of uncertainty and subjectivity of experts’ judgments. It would be of great interest, especially, when exact quantitative data are not available. A real case company example is exposed (automotive company) towards putting into practice the proposed approach.
Mídias Digitais e Ensino de História: reflexões a partir de um projeto do PIBID no Mato Grosso do Sul (2020-2022)
Authors: Locastre Aline Vanessa , Alves Carlos Monteiro , Dos Santos Fabiana
Published: July 2023

Nossa discussão apresenta o relato deexperiência sobre o ensino de História eas mídias digitais que ocorreu no programade PIBID em História da UniversidadeEstadual de Mato Grosso do Sul(UEMS), durante o período de EnsinoRemoto Emergencial. A partir da produçãode jogos digitais com a temáticaindígena, os bolsistas, que em sua maioriasão das etnias Kaiowá e Guarani,uniram a tecnologia disponível em soluçõesda Google para realizar a interaçãocom os estudantes da educação básicadas escolas envolvidas no projeto. Pormeio de uma análise bibliográfica e documental,nossa discussão assenta-sesobre os dados da desigualdade de acessoàs mídias digitais e à internet no Brasile posteriormente sobre a nossa experiência,que traz à tona a formação de professores e o ensino de História diantede novos desafios, tecnologias e metodologias.
A HQ Hades, o senhor dos mortos e o Ensino de História Antiga
Authors: Campos Carlos Eduardo da Costa , Bantim de Assumpção Luis Filipe
Published: July 2023

Na atualidade se nota uma ampliação dasreflexões sobre o uso de recursos tecnológicose linguagens para o Ensino deHistória Antiga. Ademais, o contexto daCovid-19, assim como as novas demandasdos discentes impactaram diretamentea forma da ensino-aprendizagemao redor do mundo. Assim, percebemosum aumento na utilização da linguagemquadrinística como forma de atrair osdiscentes, principalmente por ser inteligívelentre jovens e adultos. Nosso objetode análise, neste artigo, será a série Deusesdo Olimpo, de George O’Connor,com foco na HQ intitulada Hades: o senhordos mortos. Logo, problematizaremoso uso das histórias em quadrinhoscomo um instrumento de Ensino de História,caracterizando a sua linguagem eseu discurso, bem como demonstrando oseu potencial para o ensino básico.
Mindfulness Applications
Authors: Boden Lauren M. , Rodriguez Christian , Kelly John D. , Khalsa Amrit S. , Casper David S.
Published: July 2023

Background:

Stress and burnout are prevalent within the orthopaedic surgery community. Mindfulness techniques have been shown to improve wellness, yet traditional courses are generally time-intensive with low surgeon utilization. We sought to determine whether the introduction of a simple mindfulness-based phone application would help decrease stress, anxiety, and burnout in orthopaedic surgery residents.

Methods:

Twenty-four residents participated in this prospective, randomized controlled trial. After simple 1:1 randomization, the treatment group received access to a mindfulness-based phone application for 2 months while the control group did not receive access. All participants completed the Perceived Stress Scale, Generalized Anxiety Disorder-7, and Maslach Burnout Inventory with emotional exhaustion (EE), depersonalization (DP), and personal accomplishment subscores to measure stress, anxiety, and burnout at baseline and after 2 months. Paired t tests were used to compare baseline scores and conclusion scores for both groups.

Results:

There was no difference in baseline burnout scores between groups, but the treatment group had higher stress and anxiety scores at baseline. On average, the treatment group spent approximately 8 minutes per day, 2 days per week using the mindfulness application. After 2 months, the treatment group had significantly decreased stress (mean = −7.42, p = 0.002), anxiety (mean = −6.16, p = 0.01), EE (mean = −10.83 ± 10.72, p = 0.005), and DP (mean = −5.17 ± 5.51, p = 0.01). The control group did not have any significant differences in stress, anxiety, or burnout subscores.

Conclusions:

Use of a mindfulness-based phone app for 2 months led to significant reductions in stress, anxiety, and burnout scores in orthopaedic surgery residents. Our results support the use of a mindfulness-based app to help decrease orthopaedic resident stress, anxiety, and burnout. Benefits were seen with only modest use, suggesting that intensive mindfulness training programs may not be necessary to effect a change in well-being. The higher baseline stress and anxiety in the treatment group may suggest that mindfulness techniques are particularly effective in those who perceive residency to be more stressful.

Level of Evidence:

I
Resilience through disasters – The reinstatement and subsequent restart of the Sydney Desalination Plant
Authors: Karamihas Reece , Blaikie Matt
Published: July 2023

Large scale seawater desalination was implemented across Australia by supplying all mainland state capital cities as a result of the millennium drought (1997-2009) in order to diversify and increase the resilience of municipal water supplies. In the state of New South Wales (NSW), construction began on the Sydney Desalination Plant (the Plant) in 2007 and following its completion in 2010 it operated for two years through a process proving period. By 2012 the millennium drought had broken, and the Plant entered a care and maintenance mode (termed Water Security Mode, or WSM) from June 2012. The Plant operates under rules set by the NSW Government through its Metropolitan Water Plan which outlines the primary role as a drought response asset, with provision also to provide emergency response. At around the same time, the NSW Government entered in to a 50-year lease of the Plant to a private company, Sydney Desalination Plant Pty Limited (SDP) in June 2012, that was backed by a 50-year water supply contract with Sydney Water Corporation. The Plant has since been operated by SDP. The NSW Government approach to the resilience of water supply to the greater Sydney region has progressed in recent times, with the 2004 Metropolitan Water Plan undertaking a detailed investigation into the feasibility of not just desalination, but also groundwater and recycled water options to improve system resilience, largely in response to the Millennium Drought. This approach was further reinforced by the 2006 Metropolitan Water Plan, which detailed the progress of planning of a desalination plant in Sydney, and its importance in overall system resilience. The Plant is located in Kurnell, NSW, and has a nameplate capacity of 250 million litres/day (MLD) and the provision for expansion of up to 500 MLD with inlet/outlet seawater tunnels, delivery pipeline and land already sized accordingly.
Design strategies for reducing energy and total costs for large-scale seawater reverse osmosis plants
Authors: Chao Kenneth , Rozenbaoum Eugene , Hyung Hoon
Published: July 2023

One of the main obstacles limiting seawater reverse osmosis (SWRO) from becoming a more widespread solution to water shortages is the overall capital and operational costs, partially driven by energy consumption required for the SWRO process. Since its inception, however, the power requirement for SWRO has decreased dramatically through numerous factors, including improved RO membrane performance, the introduction of energy recovery systems, and improved design practices and efficiency. While many of these solutions relate to technological advances, membrane system design can be optimised during the design stage and maximise total cost savings of using SWRO. Improving design practice of SWRO to reduce power consumption requires a thorough analysis of all components, such as operating conditions, recovery, system flux, and membrane model selection. This paper presents essential design considerations that impact energy use and strategies for maximising total cost savings for SWRO plants.
Machine learning prediction accuracy score: The use of Feature selection techniques
Authors: Owusu-Adjei Michael , Hayfron-Acquah James Ben , Frimpong Twum , Abdul-Salaam Gaddafi
Published: July 2023

Medical facilities around the world attract and collect personal and healthcare context-based data of millions and billions of people every year. These centers have become information-rich data-centers. Advances in technology coupled with its increased use within healthcare systems with documented results showing various performance evaluation metrics such as prediction accuracy scores has heightened research interests for additional knowledge discovery on insights into patterns of change and important contributory factors. A key challenge to achieving better performance outcomes is the identification of critical constituent factors and its impact. In the healthcare industry, collected data in many instances are of higher dimensionality and unstructured in some respects making their use for effective machine learning predictions difficult resulting in poor predictive outcomes. In this regard, various selection techniques have been employed to help address dataset dimensionality challenges. This article examines the impact of three most widely used feature selection techniques on prediction accuracy score with healthcare context-based dataset in the prediction of treatment default for hypertensive patients with comorbidities. Using tree based classification models; extreme gradient boosting classifier, gradient boosting classifier and random forest classifier together with learning curves we demonstrate how model performance behavior could be explained. Results obtained show that random forest classifier generalizes well on cross validation with minimum training examples. Prediction accuracy scores achieved for the various models with feature selection techniques such as Boruta, principal component analysis and mutual information gain are; for Boruta, extreme gradient boosting classifier 97.93% and 98.23%, Gradient Boosting Classifier 98.03% and 98.13% and Random Forest 97.94% and 97.94% respectively. For principal component analysis; extreme gradient boosting 97.94%, gradient boosting 98.13% and random forest 97.47% and for mutual information gain; extreme gradient boosting 98.56%, gradient boosting 98.63% and random forest 98.31%. Further evaluation metrics to determine performance using receiver operating characteristic curve show the following scores; extreme gradientboosting classifier achieves a score of 90.90%, gradient boosting classifier 83.70% and random forest 78.40%. Additional performance evaluation with learning curves to determine model performance behavior show that even though random forest achieves the least roc_auc score, it generalizes well on unseen data, has the least root mean square error score and shows no need for additional features to achieve optimum performance. These scores as recorded show the impact of applying feature selection techniques on prediction accuracy scores and explains model performance behavior in the prediction of treatment default for patients suffering from hypertension with comorbidities.
The effects of anesthetic drug choice on heart rate variability and echocardiography parameters in cats
Authors: Panprom Chattida , Pattanapon Nakrob , Petchdee Soontaree
Published: July 2023

Heart rate variability is one of the assessments for cardiovascular risk during general anesthesia. The aims of this study were to assess the effects of an anesthetic drug on heart rate and heart rate variability (HRV) in cats and to provide the information for clinical applications. Twenty-four healthy client-owned cats of various breeds, 12 females and 12 males scheduled for elective surgery, were enrolled in this study. The cats were premedicated and induced with 4 protocols: protocol 1, diazepam (0.3 mg/kg) and propofol (3 mg/kg); protocol 2, diazepam (0.3 mg/kg) and alfaxalone (3 mg/kg); protocol 3, diazepam (0.3 mg/kg) and ketamine (5 mg/kg); and protocol 4, xylazine (1 mg/kg) and tiletamine/zolazepam (Zoletil) (5 mg/kg). The heart rate and heart rate variability of the 24 cats were collected before and at least 1 hour after administering the anesthetic drugs. Echocardiography was performed to evaluate heart function. Doppler was used to obtain the mean blood pressure. After anesthetic drug administration, higher heart rates were found in cats premedicated and induced with alfaxalone (p = 0.045) than in the other protocols, and the lowest heart rate (HR) values were found in cats in protocol 4 using xylazine and Zoletil. The HRV low frequency (LF) and high frequency (HF) power ratios increase in all protocols except for cats premedicated and intubation with propofol. The standard deviation of the normal sinus beats (SDNN) was higher in cats premedicated and induced with ketamine than in other anesthetic protocols (p = 0.015). An increase in sympathetic activity and reduced heart rate variability is associated with high blood pressure and left atrial dimension. The percentage of fractional shortening (FS) decreased in cats premedicated with ketamine. This study demonstrated that an anesthetic protocol using diazepam and propofol preserved cardiovascular function and was safe to use for surgeries in cats.
Spatially resolved metabolomics and isotope tracing reveal dynamic metabolic responses of dentate granule neurons with acute stimulation
Authors: Miller Anne , York Elisa , Stopka Sylwia , Martínez-François Juan , Hossain Md Amin , Baquer Gerard , Regan Michael , Agar Nathalie , Yellen Gary
Published: July 2023

Neuronal activity creates an intense energy demand that must be met by rapid metabolic responses. To investigate metabolic adaptations in the neuron-enriched dentate granule cell (DGC) layer within its native tissue environment, we employed murine acute hippocampal brain slices coupled with fast metabolite preservation, followed by mass spectrometry imaging (MALDI-MSI) to generate spatially resolved metabolomics and isotope tracing data. Here we show that membrane depolarization induces broad metabolic changes, including increased glycolytic activity in DGCs. Increased glucose metabolism in response to stimulation is accompanied by mobilization of endogenous inosine into pentose phosphates, via the action of purine nucleotide phosphorylase (PNP). The PNP reaction is an integral part of the neuronal response to stimulation, as inhibiting PNP leaves DGCs energetically impaired during recovery from strong activation. Performing MSI on brain slices bridges the gap between live cell physiology and the deep chemical analysis enabled by mass spectrometry.
Research on the impact of AI application on capital chain resilience
Authors: Li Rensi
Published: July 2023

Unfavorable external factors such as COVID-19 and economy recession have affected the abilities of enterprises to continue operating. Among them, capital chain resilience has become a key issue for enterprises. In the new era, artificial intelligence (AI) technology can provide new solutions for avoiding the breakage of the capital chain. Using data from listed companies in China, we find that AI technology can improve capital chain resilience. The main impact mechanism is to reduce the level of corporate financial constraints and improve internal control efficiency, and when corporate governance efficiency and resource acquisition capability are lower, such as poor levels of executive supervision and incentive, governance, executive resource acquisition ability, financial statement tone, business and financing environment, the effect of AI technology on improving capital chain resilience is more obvious. We enrich the research on AI and capital chain resilience, provide references for enterprises to use AI technology to help enterprises obtain more funds, warn of risks, and make correct decisions quickly in a crisis to help enterprises survive the crisis smoothly.
Route Optimization for Energy Efficiency in IoT and Software Defined RPL Heterogeneous Networks
Authors: Gasouma Amir , Yusof Kamaludin , Bouallegue Belgacem , Ahmed Abdelmoty , Khattab Mahmoud
Published: July 2023

The Internet of Things (IoT) technology is one of the most important emerging technologies in today's world, and it is one of the most important and hot topics in information technology research. The Internet of Things (IoT) refers to the concept of connecting smart things to monitor, control, or exchange data over the Internet. These smart things could be tiny devices, with limited battery capacity and power supplies. These devices' high energy consumption shortens their lifespan, affecting the entire IoT network. The Internet Engineering Task Force (IETF) developed the main routing protocols used in the IoT, such as the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL), and standardized it in RFC6550, as one of the IoT's core routing protocols, and it is the only standard protocol that assists the routing process in Low Power and Lossy Networks (LLNs) of IoT applications. An approach that addresses the challenges of IoT networks and exploits new flexible network architectures, such as Software-Defined RPL networks, there is a considerable gap in adapting objective functions (OFs) for routing and controlling control messages for RPL operations, which enhance the energy efficiency of the IoT networks. This paper proposes a unique software-defined RPL system with optimized RPL operations for heterogeneous IoT environments to enhance energy efficiency. The proposed work performed adaptive OF selection and routing, for that purpose the proposed work formulated three categories of objective functions (OF1, OF2, OF3) namely TriOF. The optimal OF is selected based on the status of the network using the Killer Whale Optimization (KWO) algorithm. It improved the performance of adaptive OF selection and enhanced the network energy efficiency. We evaluate the outcomes through a series of simulated experiments using the Network Simulator (NS3). The proposed model approach results in a reduced number of control messages, control overhead, packet delivery ratio, and packet loss rate. Compared to the contrast works, energy consumption is reduced by 40% and 60%, respectively.
A Many-Objective Optimization Evolutionary Algorithm Based on Double Surrogate-Assisted Adaptive Guiding Evolutionary Direction
Authors: Dali Jiao , Yifei Yao , Du Cheng , Qingliang Li , Fanhua Yu
Published: July 2023

In expensive Many-objective Optimization Problems, Surrogate-Assisted Evolutionary Algorithms (SAEAs) are often used to reduce the number of original Function Evaluations (FE). However, traditional SAEAs may suffer from long running times due to the complex computational demands of the surrogate models themselves. In this paper, we propose a novel algorithm called " A Many-Objective Optimization Evolutionary Algorithm Based on Double Surrogate-Assisted Adaptive Guiding Evolutionary Direction (DSAG)", aimed at further reducing the running time of SAEAs. The proposed algorithm employs two surrogate models: one for predicting the diversity of solutions and another for predicting the convergence value of solutions, and then sorts the solutions based on the prediction results. Afterwards, the algorithm adaptively adjusts the type and number of candidate solutions according to the "Convergence-Related Average Move Distance (CAMD)" proposed in this paper. This algorithm can adaptively bias towards either the convergence exploration stage or the diversity exploration stage. Compared with other classical surrogate-assisted evolutionary algorithms, the proposed algorithm first categorizes the decision variables and uses the categorized data to train two surrogate models, which makes the overall complexity and running time of the algorithm superior to others. Finally, we compared the performance of this algorithm on different problems using benchmark test functions to verify its ability to explore diversity and improve convergence. Then, we compared the running time of the algorithm with changes in the target dimension, decision variable dimension, and number of Original FE on the same test problems, and demonstrated the superior performance of the algorithm.
Prevalence and Imaging-Based Classification of Pituitary Adenomas with Hard Consistency: A Systematic Review and Meta-Analysis
Authors: Gaia Felipe , Pokorny Gabriel , Cortez Gustavo M , Zymberg Samuel Tau , Cruz Oswaldo Laércio Mendonça
Published: July 2023

OBJECTIVE
Transsphenoidal resection of pituitary adenomas may be difficult in patients with hard tumors. To determine the genuine incidence and performance of radiological features in diagnosing pituitary adenomas with hard consistency, we conducted a comprehensive review and meta-analysis of the literature.
METHODS
A literature search was conducted and publications comparing intraoperative pituitary tumor consistency and preoperative magnetic resonance imaging (MRI) were included. The authors assessed the prevalence of hard pituitary tumors using a random-effects meta-analysis and univariate analysis.
RESULTS
Of 916 studies, 888 were excluded. Finally, 28 trials with 1116 patients with pituitary tumors were considered. Hard-consistency tumors were adjudicated intraoperatively in 219 patients (weighted incidence, 16.82%; 95% CI, 12.35-22.48%, I2 = 65.1%). With a weighted proportion of 15%, 17 studies (60%) demonstrated a link between radiological results and intraoperative tumor consistency in at least one MRI sequence (95% CI, 10,31% - 22,70%). In 31% and 53% of the trials, apparent diffusion correlation (ADC) and T2-weighted sequences were linked to tumor consistency. Nonetheless, inconsistent signal intensities across trials make it impossible for conventional MRI sequences to correctly estimate pituitary tumor consistency.
CONCLUSION
In the current study population, the weighted incidence of pituitary tumors classified as having a hard consistency was 16%.
An Artificial Intelligence Video-Based Assessment of Upper-limb Bradykinesia in Parkinson’s Disease
Authors: Guarin Diego , Wong Joshua , Ramirez-Zamora Adolfo
Published: July 2023

As there is a lack of an objective biomarker for Parkinson’s disease (PD), the clinical practice relies on serial neurologic assessments to track and characterize disease progression. These clinical scales lack the resolution to detect subtle changes, classify the movements into broad categories, require significant expertise for proper application, and are not sensible enough for early diagnosis; imaging markers are objective and sensible for early diagnosis but are costly and not commonly available. The video-based movement measures estimated using AI algorithms for motion tracking represent a novel alternative for diagnosing and assessing PD. Video-based measures are objective, sensitive to small changes, inexpensive, and easily accessible. This paper explores the correlation between objective kinematics measures derived from videos of the Finger Tapping Test using AI-based algorithms for markerless motion tracking with well-established clinical and imaging markers of disease progression in PD. The results demonstrate that AI-based algorithms for markerless motion tracking accurately track hand movements during the Finger Tapping Test. Different movement aspects, such as speed, duration, amplitude, and rhythm alterations, can be quantified from the videos. Our analysis showed that these video-based measures were significantly correlated with clinical rating scales, including the Movement Disorder Society – Parkinson’s Disease Rating Scale Part III and its Finger Tapping subscore. Additionally, some measures significantly correlated with imaging markers, such as Free Water in the posterior Substantia Nigra. Furthermore, video-based measures could detect the presence of PD from the Finger Tapping Test videos with high accuracy. The best classification model achieved an average accuracy of 95% and an area under the receiver operating characteristic curve of 0.87. Finally, we introduce The Hand Tracking Tool, an easy-to-use interface for analyzing Finger Tapping Test videos using AI-based algorithms for markerless motion tracking and obtaining objective movement measures.
m5C RNA modiﬁcation upregulates E2F1 expression dependently on YBX1 phase separation and promotes tumor progression in ovarian cancer
Authors: Yi Ping , Liu Xiaoyi , Wei Qinglv , Yang Chenyue , Zhao Hongyan , Mobet Youchaou , Luo Qingya , Yan Dan , Zuo Xinzhao , Chen Ningxuan , Yang Yu , Li Li , Wang Wei , Yu Jianhua , Jing Xu , Liu Tao
Published: July 2023

5-methylcytosine (m5C) is a common RNA modification that modulates gene expression at the post-transcriptional level, but the cross-talk between m5C RNA modification and biomolecule condensation as well as transcription factor-mediated transcriptional regulation in ovarian cancer remains poorly understood. In this study, we uncover that the RNA methytransferase NSUN2 facilitates m5C modification of mRNA and forms a positive feedback regulatory loop with the transcription factor E2F1 in ovarian cancer. Specifically, NSUN2 promotes m5C modification of E2F1 mRNA and enhances its stability, and E2F1 binds to NSUN2 promoter followed by the activated transcription reciprocally. The RNA binding protein YBX1 acts as the m5C reader and is involved in NSUN2-mediated E2F1 regulation. m5C modification promotes YBX1 phase separation that upregulates E2F1 expression. In ovarian cancer, NSUN2 and YBX1 are amplified and upregulated, and higher expressions of NSUN2 and YBX1 predict a worse prognosis for ovarian cancer patients. Moreover, E2F1 transcriptionally regulates the expression of oncogenes MYBL2 and RAD54L, driving ovarian cancer progression. Thus, our study delineates a NSUN2-E2F1-NSUN2 circuitry regulated by m5C modification dependently on YBX1 phase separation, and the identified previously unknown pathway can be a promising target for ovarian cancer treatment.
Preclinical Training of Future Ocular Surgeons: a French Opinion-Based Study
Authors: KITIC Nicolas , BOURGES Jean-Louis
Published: July 2023

Purpose : To assess ophthalmology residents satisfaction regarding surgical training during residency in France.
Methods : A questionnaire consisting of 28 questions was designed and sent to residents of ophthalmology across the 27 French regions.
Results : A total of 30.3% of ophthalmology residents in France completed our questionnaire. All French regions participated. They rated 5,27/10 ± 2.42 the global surgical training during residency. They had performed at least one step of any type of ocular surgery for 93.4% of them, while 80.7% had completed at least one full cataract surgery, by the second half of the 3rd semester on average (Paris : 2.59 semesters ± 1.36 ; regions : 4.05 semesters ± 1.96, p < 0.0001). Only 48.9% identified a surgical mentor during their residency, but 82.2% did not clearly identify surgical goals & objectives during their training.
Simulation was available for any type of ocular surgery to all residents in the Paris (Île-de-France) region and to 78.1% in other regions (p < 0.005). Residents who accessed drylabs and wetlabs gave a satisfaction score of 7.31/10±1.89 and 6.39/10±2.15 to it respectively.
Simulation was a mandatory part of the curriculum for 35.2% of the resident. They commented on on reduced access to subspecialized surgery. They were willing for more access to simulation and surgery on real patients, as well for closer mentoring and clearly defined surgical goals within the curriculum.
Conclusion : Ophthalmology residents seemed globally satisfied with their surgical training nationwide, although we observed disparities across region. They largely acknowledged a lack of standard procedures nationwide. They acclaimed simulation during the initial phase of residency, progressively switching towards surgery on real patients. An “operating license” during residency could be a viable way for the resident to demonstrate that they have acquired enough surgical abilities to perform surgery on real patients.
Can the Regional 3D Stress Field according to the Wallace-Bott Hypothesis predict fault slip directions of future large earthquakes?
Authors: Ishibe Takeo , Terakawa Toshiko , Hashima Akinori , Mochizuki Masashi , Matsu'ura Ritsuko S.
Published: July 2023

When evaluating strong ground motion and tsunamis from specified source faults, it is required that the input parameters, such as fault geometry, rake angle, and slip amount, do not deviate from those of a real earthquake. Recently, a regional three-dimensional (3D) tectonic stress field was used to estimate rake angles for mapped submarine faults with the Wallace-Bott hypothesis (WB), the direction of fault slip was parallel to the resolved stress vector on a preexisting fault, and strong ground motion and tsunamis were simulated. However, this modeling technique has not been adequately validated. Additionally, it is necessary to examine how the stress field estimated from seismological data for a limited period (~10 years) can be used as a proxy for long-term tectonic stress fields. In this study, to provide such validation, we utilized two catalogs of focal mechanism solutions for earthquakes and compared the observed rake angles with those calculated from the regional 3D tectonic stress field with WB by fixing the fault strike and dip angles according to those from the focal mechanism data. The resulting misfit angles between the observed and calculated rake angles are generally small (ranging between -30° and 30°), excluding several regions (e.g., the source and surrounding regions of the 2011 off the Pacific coast of Tohoku earthquake and swarm-like activities activated after the 2011 quake). We also confirmed that the calculated rake angles and classified fault types are consistent with geomorphologically and geologically evaluated types of faulting for major Quaternary active faults in the Kyushu district of southwest Japan. These results support the validity and effectiveness of estimating rake angles for a specific fault with known geometry from the above method and data, while also showing that close attention is required to apply this method to, for example, seismically inactive regions where the inverted stress fields include significant uncertainties and/or near sites of recent and large earthquakes, where the stress fields have been perturbed.
Sliding mode control of the hydraulic swing joint based on nonlinear disturbance observers
Authors: Yang Mingxing , Zhang Xing , Lu Yaxing , Xie Nenggang , Wang Lu , Xi Ruru
Published: July 2023

Due to the nonlinearity of the hydraulic position servo system and its model uncertainty, which makes it more difficult to establish an accurate mathematical model, while a single control algorithm can no longer meet the control accuracy and demand of the hydraulic servo system. In order to better study the position control method of hydraulic swing joint and improve the control accuracy, this paper attempts to address the position servo control problem of hydraulic swing joint by proposing a sliding mode control approach in which, based on nonlinear disturbance observers and the effectiveness of the algorithm is verified by AMESim-Matlab/Simulink co-simulation. Firstly, this paper briefly describes the three-dimensional model of hydraulic swing joint and analyzes the working principle of the position servo system of hydraulic swing joint. Secondly, the mathematical model of the hydraulic swing joint position servo system was established, the control algorithm was designed, and the stability of the control algorithm was proved using Lyapunov theory. Thirdly, combining the rich component model library of AMEsim platform and the powerful numerical computing capability of Matlab platform, the co-simulation of the two platforms is realized by creating S-Function interface in Matlab platform. Finally, the validity of the proposed sliding mode control strategy based on the nonlinear disturbance observers (NDOB-SMC) strategy is verified through experimental analysis of co-simulation, and compared with the traditional PID as well as the traditional sliding mode control (SMC) algorithm, which is found to possess superior control accuracy and practical application capability.
Retrospective significance of total bilirubin as a predictor of acute appendicitis
Authors: Saad Hassan A , El-Taher Ahmed K , Abo-Alella Heba Alhussein , Riad Mohamed , Elsayed Ashraf
Published: July 2023

Objective
The present research aimed to examine the clinical importance of preoperative total bilirubinemia in patients with acute appendicitis and determine whether it has any practical application for predicting severe appendicitis.
Methods
A retrospective analysis of appendicectomies was done in one hospital (N = 636 cases of acute appendicitis presented to the emergency department between December 2019 and January 2023). Using multivariate analysis, we looked at predictive data for complex (perforated or gangrenous) appendicitis, including demographics, gender, white blood cell count, degree of C-reactive protein (CRP) elevation, high-temperature peritoneal signs and indicators, and total bilirubin level.
Results
Those with total bilirubin (>1.1 mg/dL), high CRP levels (>0.5 mg/dL), positive peritoneal irritated symptoms, and a temperature (>37.3 C) had considerably higher rates of acute appendicitis. Age (>64 years), hyperbilirubinemia, high CRP level, and fever (odds ratios of 3.36, 1.75, 7.61, and 2.43, respectively) were identified by multivariate analysis as associated risks for complex appendicitis. High temperatures, raised CRP levels, and hyperbilirubinemia were also found to be risks for complex appendicitis in all individuals, especially those under 65 years old (odds ratios: 1.99, 5.90, and 2.72, respectively).
Conclusions
High temperatures, elevated CRP, and high total bilirubin were good predictor factors of acute appendicitis, especially useful among cases younger than 65 years, but total bilirubin was a more precise indicator.
Detection rate of brain MR and MR angiography for neuroimaging abnormality in patients with newly diagnosed left-sided infective endocarditis
Authors: Kim Seongken , Suh Chong Hyun , Kim Tae Oh , Heo Hwon , Shim Woo Hyun , Kim Sang Joon , Lee Seung-Ah
Published: July 2023

We aimed to investigate the detection rate of brain MR and MR angiography for neuroimaging abnormality in newly diagnosed left-sided infective endocarditis patients with/without neurological symptoms. This retrospective study included consecutive patients with definite or possible left-sided infective endocarditis according to the modified Duke criteria who underwent brain MRI and MR angiography between March 2015 and October 2020. The detection rate for neuroimaging abnormality on MRI was defined as the number of patients with positive brain MRI findings divided by the number of patients with left-sided infective endocarditis. Positive imaging findings included acute ischemic lesions, cerebral microbleeds, hemorrhagic lesions, and mycotic aneurysms. In addition, aneurysm rupture rate and median period to aneurysm rupture were evaluated on follow-up studies. A total 115 patients (mean age: 55 years ± 19; 65 men) were included. The detection rate for neuroimaging abnormality was 77% (89/115). The detection rate in patients without neurological symptoms was 70% (56/80). Acute ischemic lesions, cerebral microbleeds, and hemorrhagic lesions were detected on MRI in 56% (64/115), 57% (66/115), and 20% (23/115) of patients, respectively. In particular, mycotic aneurysms were detected on MR angiography in 3% of patients (4/115), but MR angiography in 5 patients (4.3%) was insignificant for mycotic aneurysm. Among the 9 mycotic aneurysm patients, aneurysm rupture occurred in 4 (44%), with a median period of aneurysm rupture of 5 days. The detection rate of brain MRI for neuroimaging abnormality in newly diagnosed left-sided infective endocarditis patients was high, even without neurological symptoms.
FCWWO: Fuzzy Chaotic Whale Wolf Optimization for Enhancing Network Lifetime and Minimizing Energy Consumption
Authors: P Vijitha Devi. , Kavitha K. , Usha D. , Kumar T. Ganesh
Published: July 2023

The Wireless Sensor Networks (WSN) include several sensors which collect data from their surroundings and transmit it to the destination node. In WSN, sensor nodes operate individually and build the ad-hoc network infrastructure. The observing data perceives the sensor nodes and the data have been sent to the Base Station (BS) with the utilization of gateway and Cluster Head (CH). The WSNs have limited battery power which diminishes the lifetime of the network. The clustering algorithm is one of the efficient solutions that help in improving the WSNs network. Many algorithms were applied in the clustering process in rectifying the issue of NP-hard optimization. But, these algorithms lead to disadvantages namely delay, slow conveyance rate and weak exploitation stage. Therefore, in this paper, a novel Fuzzy Chaotic Whale Wolf (FCWW) optimization is proposed for selecting the optimal CH. The primary goal of our article is to lessen computational complexity with increased network lifetime. The main operation of the CH is gathering information from the sensor nodes and directly communicating with the BS. As compared to other techniques, the proposed FCWW algorithm provides 712 kbps of throughput, 98.8% of packet delivery ratio, network lifetime of 1652 seconds, 35% of energy consumption and 82 ms of end-to-end latency respectively.
Enhancing Supercapacitor Performance through Design Optimization of Laser-Induced Graphene and MWCNT Coatings for Flexible and Portable Energy Storage
Authors: Tariq Hassan , Awan Saif Ullah , Hussain Danish , Rizwan Syed , Shah Saqlain A. , Zainab Sana , Riaz M. Bilal
Published: July 2023

The field of supercapacitors consistently focuses on research and challenges to improve energy efficiency, capacitance, flexibility, and stability. Low-cost laser-induced graphene (LIG) offers a promising alternative to commercially available graphene for next-generation wearable and portable devices, thanks to its remarkable specific surface area, excellent mechanical flexibility, and exceptional electrical properties. We report on the development of LIG-based flexible supercapacitors with optimized geometries, which demonstrate high capacitance and energy density while maintaining flexibility and stability. Three-dimensional porous graphene films were synthesized, and devices with optimized parameters were fabricated and tested. One type of device utilized LIG, while two other types were fabricated on LIG by coating multi-walled carbon nanotubes (MWCNT) at varying concentrations. Characterization techniques, including scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray diffraction (XRD), Raman spectroscopy, and voltammetry, were employed to analyze the fabricated devices. AFM analysis revealed a surface roughness of 2.03 µm for LIG due to laser treatment. SEM images displayed compact, dense, and porous surface morphology. XRD analysis confirmed the presence of graphene and graphene oxide, which was further supported by energy-dispersive X-ray spectroscopy (EDX) data. Raman spectroscopy indicated that the fabricated samples exhibited distinct D and G bands at 1362 cm–1 and 1579 cm–1, respectively. Cyclic voltammetry (CV) results showed that LIG's capacitance, power density, and energy density were 6.09 mF cm–2, 0.199 mW cm–2, and 3.38 µWh cm–2, respectively, at a current density of 0.2 mA cm–2. The LIG-MWCNT coated electrode exhibited a higher energy density of 6.05 µWh cm–2 and an areal-specific capacitance of 51.975 mF cm–2 compared to the LIG-based devices. The fabricated device has potential applications in smart electronics, nanorobotics, microelectromechanical systems (MEMS), and wearable and portable electronics.
Comparison of Delayed Bleeding to Immediate Bleeding Following Thyroidectomy
Authors: Lee Jun Sung , Lee Jin Seok , Yun Hyeok Jun , Chang Hojin , Kim Seok-Mo , Lee Yong Sang , Chang Hang-Seok
Published: July 2023

Background
It is important to identify risk factors for post-thyroidectomy bleeding requiring airway intervention or reoperation. Therefore, we aimed to compare the characteristics of patients with postoperative bleeding after thyroid surgery according to the period until reoperation.
Method
We conducted a retrospective study analyzing data between April 2009 and July 2022 and included 126 patients who had postoperative bleeding. The patients were grouped according to the period between thyroidectomy and reoperation due to bleeding (0 day, 1–7 days, > 7 days). We performed among-group comparisons of patient characteristics and surgical aspects, including the extent of surgery.
Results
The ratios of male-female and lateral neck dissection were higher in the post-operative bleeding group than in the group without bleeding. In the analysis of patients with postoperative bleeding, grouped according to period between thyroidectomy and reoperation, there was a significant among-group difference in the male-female ratio. The male sex was positively correlated with the reoperation period. Further, the reoperation period was also positively correlated with total thyroidectomy and lateral neck dissection and the operation time showed a significant among-group difference.
Conclusions
Our results indicate that the male sex and lateral neck dissection are risk factors for postoperative bleeding after thyroidectomy. Furthermore, male sex, total thyroidectomy, and lateral neck dissection are risk factors for delayed bleeding. Therefore, clinicians should consider these factors for interventions against immediate or delayed bleeding after thyroidectomy.
Improving assessment quality of soil natural attenuation capacity at the point and regional scales
Authors: Guang Xu , Qu Mingkai , Liu Maosheng , Chen Jian , Zhao Yongcun , Huang Biao
Published: July 2023

Soil natural attenuation capacity (NAC) is an important ecosystem service that maintains a clean environment for organisms in the soil, which in turn supports other services. However, spatially varying indicator weights were rarely considered in the traditionally-used soil NAC assessment model (e.g., ecosystem-service performance model) at the point scale. Moreover, in the spatial simulation of soil NAC, the traditionally-used geostatistical models were usually susceptible to spatial outliers and ignore valuable auxiliary information (e.g., land-use types). This study first proposed a novel soil NAC assessment method based on the ecosystem-service performance model and moving window-entropy weight method (MW-EW) (NACMW−EW). Next, NACMW−EW was used to assess soil NAC in the study area in Guixi City, China, and further compared with the traditionally-used NAC and NACEW. Then, robust sequential Gaussian simulation with land-use types (RSGS-LU) was established for the spatial simulation of NACMW−EW and compared with the traditionally-used SGS, SGS-LU, and RSGS. Last, soil NAC’s spatial uncertainty was evaluated based on the 1000 simulations generated by RSGS-LU. The results showed that: (i) MW-EW effectively revealed the spatially varying indicator weights but EW couldn’t; (ii) NACMW−EW obtained more reasonable results than NAC and NACEW; (iii) RSGS-LU (RMSE = 0.118, MAE = 0.089) generated higher spatial simulation accuracy than SGS-LU (RMSE = 0.123, MAE = 0.092), RSGS (RMSE = 0.132, MAE = 0.096), and SGS (RMSE = 0.135, MAE = 0.099); (iv) the relatively high (P[NACMW−EW(u) > 0.57] ≥ 0.95) and low (P[NACMW−EW(u) > 0.57] ≤ 0.05) threshold-exceeding probability areas were mainly located in the south and east part of the study area, respectively. It is concluded that the proposed methods were effective tools for soil NAC assessment at the point and regional scales, and the results provided accurate spatial decision support for soil ecosystem service management.