bluuebunny/crossref_metadata_2025 huggingface dataset:
One-Step Ethanol Conversion for 1,3-Butadiene Synthesis over Two-Dimensional VMT-SiO2 Nanomesh Loaded with Magnesium and Copper Oxide
Authors: Qin Yaqi , Fang Kegong , Li Wenbin , Jiu Hongfang
Published: May 2024

A two-dimensional porous silica nanomesh (VMT-SiO2) was used as a carrier to prepare MgO-CuO-based catalysts and tested for one-step ethanol conversion to 1,3-butadiene. The effects of catalyst composition and different calcination temperatures on the reaction performances of the catalysts were mainly investigated. Combining various characterization techniques, such as HRTEM, XRD, FT-IR, and TPD, it was found that the dispersion state of MgO and CuO on the catalyst surface was related to the calcination temperature, which further induced changes in the acid–base properties. A small number of acidic centers and a proper proportion of medium–strong alkaline centers maintained a subtle balance, affecting catalytic performance. A lower total acid/base ratio is more conducive to ethanol conversion and 1,3-butadiene formation. At the same time, the synergistic effect of CuO and MgO promotes the transformation of the intermediate acetaldehyde product, which is the key to ensuring the subsequent aldol condensation and then 1,3-butadiene formation. Among the investigated samples, the CuO/MgO-VMT-SiO2 catalyst calcined at 500 °C exhibited the best catalytic performance, with an impressive ethanol conversion of 47.8% and 1,3-butadiene formation (42.6% selectivity and a space-time yield of 182.0 gC4H6·kgcat−1·h−1).
Torque Calculation and Dynamical Response in Halbach Array Coaxial Magnetic Gears through a Novel Analytical 2D Model
Authors: Tzouganakis Panteleimon , Gakos Vasilios , Kalligeros Christos , Papalexis Christos , Tsolakis Antonios , Spitas Vasilios
Published: May 2024

Coaxial magnetic gears have piqued the interest of researchers due to their numerous benefits over mechanical gears. These include reduced noise and vibration, enhanced efficiency, lower maintenance costs, and improved backdrivability. However, their adoption in industry has been limited by drawbacks like lower torque density and slippage at high torque levels. This work presents an analytical 2D model to compute the magnetic potential in Halbach array coaxial magnetic gears for every rotational angle, geometry configuration, and magnet specifications. This model calculates the induced torques and torque ripple in both rotors using the Maxwell Stress Tensor. The results were confirmed through Finite Element Analysis (FEA). Unlike FEA, this analytical model directly produces harmonics values, leading to faster computational times as it avoids torque calculations at each time step. In a case study, a standard coaxial magnetic gear was compared to one with a Halbach array, revealing a 14.3% improvement in torque density and a minor reduction in harmonics that cause torque ripple. Additionally, a case study was conducted to examine slippage in both standard and Halbach array gears during transient operations. The Halbach array coaxial magnetic gear demonstrated a 13.5% lower transmission error than its standard counterpart.
Analysis of a Novel Method for Generating 3D Mesh at Contact Points in Packed Beds
Authors: Szambien Daniel F. , Ziegler Maximilian R. , Ulrich Christoph , Scharf Roland
Published: May 2024

This study comprehensively analyzes the impact of the novel HybridBridge method, developed by the authors, for generating a 3D mesh at contact points within packed beds within the effective thermal conductivity. It compares HybridBridge with alternative methodologies, highlights its superiority and outlines potential applications. The HybridBridge employs two independent geometry parameters to facilitate optimal flow mapping while maintaining physically accurate effective thermal conductivity and ensuring high mesh quality. A method is proposed to estimate the HybridBridge radius for a defined packed bed and cap height, enabling a presimulative determination of a suitable radius. Numerical analysis of a body-centered-cubic unit cell with varied HybridBridges is conducted alongside previous simulations involving a simple-cubic unit cell. Additionally, a physically based resistance model is introduced, delineating effective thermal conductivity as a function of the HybridBridge geometry and porosity. An equation for the HybridBridge radius, tailored to simulation parameters, is derived. Comparison with the unit cells and a randomly packed bed reveals an acceptable average deviation between the calculated and utilized radii, thereby streamlining and refining the implementation of the HybridBridge methodology.
Selection of Appropriate Criteria for Optimization of Ventilation Element for Protective Clothing Using a Numerical Approach
Authors: Vejanand Sanjay Rajni , Janushevskis Alexander , Vaicis Ivo
Published: May 2024

While there are multiple methods to ventilate protective clothing, there is still room for improvement. In our research, we are using ventilation elements that are positioned at the ventilation holes in the air space between the body and clothing. These ventilation elements allow air to flow freely while preventing sun radiation, rain drops, and insects from directly accessing the body. Therefore, the shape of the ventilation element is crucial. This led us to study the shape optimization of ventilation elements through the utilization of metamodels and numerical approaches. In order to accomplish the objective, it is crucial to thoroughly evaluate and choose suitable criteria for the optimization process. We know from prior research that the toroidal cut-out shape element provides better results. In a previous study, we optimized the shape of this element based on the minimum pressure difference as a criterion. In this study, we are using different criteria for the shape optimization of ventilation elements to determine which are most effective. This study involves a metamodeling strategy that utilizes local and global approximations with different order polynomials, as well as Kriging approximations, for the purpose of optimizing the geometry of ventilation elements. The goal was achieved by a sequential process. (1) Planning the position of control points of Non-Uniform Rational B-Splines (NURBS) in order to generate elements with a smooth shape. (2) Constructing geometric CAD models based on the design of experiments. (3) Compute detailed model solutions using SolidWorks Flow Simulation. (4) Developing metamodels for responses using computer experiments. (5) Optimization of element shape using metamodels. The procedure is repeated for six criteria, and subsequently, the results are compared to determine the most efficient criteria for optimizing the design of the ventilation element.
Fine Chemicals from Natural Sources with Potential Application in the Cosmetic/Pharmaceutical Industry
Authors: Feliczak-Guzik Agnieszka
Published: May 2024

There is no doubt that chemistry has provided countless products that have improved people’s lives in almost every aspect [...]
Stimulated Microcontroller Dataset for New IoT Device Identification Schemes through On-Chip Sensor Monitoring
Authors: Ramos Alberto , Martín Honorio , Cámara Carmen , Peris-Lopez Pedro
Published: May 2024

Legitimate identification of devices is crucial to ensure the security of present and future IoT ecosystems. In this regard, AI-based systems that exploit intrinsic hardware variations have gained notable relevance. Within this context, on-chip sensors included for monitoring purposes in a wide range of SoCs remain almost unexplored, despite their potential as a valuable source of both information and variability. In this work, we introduce and release a dataset comprising data collected from the on-chip temperature and voltage sensors of 20 microcontroller-based boards from the STM32L family. These boards were stimulated with five different algorithms, as workloads to elicit diverse responses. The dataset consists of five acquisitions (1.3 billion readouts) that are spaced over time and were obtained under different configurations using an automated platform. The raw dataset is publicly available, along with metadata and scripts developed to generate pre-processed T–V sequence sets. Finally, a proof of concept consisting of training a simple model is presented to demonstrate the feasibility of the identification system based on these data.
Three-Dimensional Assessment of Upper Airway Volume and Morphology in Patients with Different Sagittal Skeletal Patterns
Authors: Pop Silvia Izabella , Procopciuc Ana , Arsintescu Bianca , Mițariu Mihai , Mițariu Loredana , Pop Radu Vasile , Cerghizan Diana , Jánosi Kinga Mária
Published: May 2024

Background: The relationship between respiratory function and craniofacial morphology has garnered significant attention due to its implications for upper airway and stomatognathic development. Nasal breathing plays a key role in craniofacial growth and dental positioning. This study investigated upper airway morphology and volume differences among individuals with class I, II, and III skeletal anomalies. Methods: Ninety orthodontic patients’ CBCT scans were analyzed to assess the oropharynx and hypopharynx volumes. Skeletal diagnosis was established based on the cephalometric analysis. Results: A significant volume change in the oropharynx and pharynx was demonstrated when comparing class II with class III anomalies (p = 0.0414, p = 0.0313). The total volume of the pharynx was increased in class III anomalies. The area of the narrowest part of the pharynx (MIN-CSA) significantly decreased in classes I and II compared to class III (p = 0.0289, p = 0.0003). Patients with Angle class III anomalies exhibited higher values in the narrowest pharyngeal segment. Gender differences were significant in pharyngeal volumes and morphologies across malocclusion classes. Conclusions: The narrowest segment of the pharynx had the highest values in patients with Angle class III. The volume of the oropharynx was found to be greater in patients with Angle class III versus patients with Angle class II.
Advancing Evidence Generation for Circulating Tumor DNA: Lessons Learned from A Multi-Assay Study of Baseline Circulating Tumor DNA Levels across Cancer Types and Stages
Authors: McKelvey Brittany A. , Andrews Hillary S. , Baehner Frederick L. , Chen James , Espenschied Carin R. , Fabrizio David , Gorton Vanessa , Gould Claire , Guinney Justin , Jones Greg , Lv Xiangyang , Nahorski Michael S. , Palomares Melanie R. , Pestano Gary A. , Sausen Mark , Silk Alain , Zhang Nicole , Zhang Zhihong , Stewart Mark D. , Allen Jeff D.
Published: May 2024

Circulating tumor DNA (ctDNA) holds promise as a biomarker for predicting clinical responses to therapy in solid tumors, and multiple ctDNA assays are in development. However, the heterogeneity in ctDNA levels prior to treatment (baseline) across different cancer types and stages and across ctDNA assays has not been widely studied. Friends of Cancer Research formed a collaboration across multiple commercial ctDNA assay developers to assess baseline ctDNA levels across five cancer types in early- and late-stage disease. This retrospective study included eight commercial ctDNA assay developers providing summary-level de-identified data for patients with non-small cell lung cancer (NSCLC), bladder, breast, prostate, and head and neck squamous cell carcinoma following a common analysis protocol. Baseline ctDNA levels across late-stage cancer types were similarly detected, highlighting the potential use of ctDNA as a biomarker in these cancer types. Variability was observed in ctDNA levels across assays in early-stage NSCLC, indicative of the contribution of assay analytical performance and methodology on variability. We identified key data elements, including assay characteristics and clinicopathological metadata, that need to be standardized for future meta-analyses across multiple assays. This work facilitates evidence generation opportunities to support the use of ctDNA as a biomarker for clinical response.
Quantitative 3D Analysis of Levator Ani Muscle Subdivisions in Nulliparous Women: MRI Feasibility Study
Authors: Moser Nathalie , Skawran Stephan , Steigmiller Klaus , Röhrnbauer Barbara , Winklehner Thomas , Reiner Cäcilia S. , Betschart Cornelia
Published: May 2024

Background: The levator ani muscle (LAM) is crucial for pelvic floor stability, yet its quantitative MRI assessment is only a recent focus. Our study aims to standardize the quantitative analysis of the LAM morphology within the 3D Pelvic Inclination Correction System (3D-PICS). Methods: We analyzed 35 static MR datasets from nulliparous women examining the pubovisceral (PVM), iliococcygeal (ICM), coccygeal (COC), and puborectal muscle (PRM). The PVM consists of three origin-insertion pairs, namely the puboanal (PAM), puboperineal (PPM) and pubovaginal muscle (PVaM). The analysis included a quantitative examination of the morphology of LAM, focusing on the median location (x/y/z) (x: anterior–posterior, y: superior–inferior, z: left–right) of the origin and insertion points (a), angles (b) and lengths (c) of LAM. Inter-rater reliability was calculated. Results: Interindividual variations in 3D coordinates among muscle subdivisions were shown. In all, 93% of all origin and insertion points were found within an SD of <8 mm. Angles to the xz-plane range between −15.4° (right PRM) and 40.7° (left PAM). The PRM is the largest pelvic muscle in static MRI. The ICC indicated moderate-to-good agreement between raters. Conclusions: The accurate morphometry of the LAM and its subdivisions, along with reliable inter-rater agreement, was demonstrated, enhancing the understanding of normal pelvic anatomy in young nulliparous women.
A Multi-Stage Approach for Cardiovascular Risk Assessment from Retinal Images Using an Amalgamation of Deep Learning and Computer Vision Techniques
Authors: Prasad Deepthi K. , Manjunath Madhura Prakash , Kulkarni Meghna S. , Kullambettu Spoorthi , Srinivasan Venkatakrishnan , Chakravarthi Madhulika , Ramesh Anusha
Published: May 2024

Cardiovascular diseases (CVDs) are a leading cause of mortality worldwide. Early detection and effective risk assessment are crucial for implementing preventive measures and improving patient outcomes for CVDs. This work presents a novel approach to CVD risk assessment using fundus images, leveraging the inherent connection between retinal microvascular changes and systemic vascular health. This study aims to develop a predictive model for the early detection of CVDs by evaluating retinal vascular parameters. This methodology integrates both handcrafted features derived through mathematical computation and retinal vascular patterns extracted by artificial intelligence (AI) models. By combining these approaches, we seek to enhance the accuracy and reliability of CVD risk prediction in individuals. The methodology integrates state-of-the-art computer vision algorithms and AI techniques in a multi-stage architecture to extract relevant features from retinal fundus images. These features encompass a range of vascular parameters, including vessel caliber, tortuosity, and branching patterns. Additionally, a deep learning (DL)-based binary classification model is incorporated to enhance predictive accuracy. A dataset comprising fundus images and comprehensive metadata from the clinical trials conducted is utilized for training and validation. The proposed approach demonstrates promising results in the early prediction of CVD risk factors. The interpretability of the approach is enhanced through visualization techniques that highlight the regions of interest within the fundus images that are contributing to the risk predictions. Furthermore, the validation conducted in the clinical trials and the performance analysis of the proposed approach shows the potential to provide early and accurate predictions. The proposed system not only aids in risk stratification but also serves as a valuable tool for identifying vascular abnormalities that may precede overt cardiovascular events. The approach has achieved an accuracy of 85% and the findings of this study underscore the feasibility and efficacy of leveraging fundus images for cardiovascular risk assessment. As a non-invasive and cost-effective modality, fundus image analysis presents a scalable solution for population-wide screening programs. This research contributes to the evolving landscape of precision medicine by providing an innovative tool for proactive cardiovascular health management. Future work will focus on refining the solution’s robustness, exploring additional risk factors, and validating its performance in additional and diverse clinical settings.
Individualizing Surveillance after Endovascular Aortic Repair Using a Modular Imaging Algorithm
Authors: Hofmann Amun Georg , Mlekusch Irene , Wickenhauser Georg , Walter Corinna , Taher Fadi , Assadian Afshin
Published: May 2024

Objectives: Surveillance after endovascular aortic repair (EVAR) and fenestrated EVAR (FEVAR) is mainly directed by one-size-fits-all approaches instead of personalized decision making, even though treatment strategies and often endografts themselves are tailor-made to adjust for individual patients. We propose a modular imaging algorithm that escalates surveillance imaging based on invasiveness and need. Materials and Methods: In this retrospective observational study of single-center data, results of a modular imaging algorithm were analyzed. The algorithm is characterized by initiating the examination with standard B-mode then transitioning to Duplex ultrasound, B-Flow, and CEUS. Additional CT(A) studies are conducted where required. The study population included both patients receiving EVAR or FEVAR. A comparative analysis was conducted regarding endoleak detection. Results: The study population included 28 patients receiving EVAR and 40 patients receiving FEVAR. They accounted for 101 follow-up visits, which led to 431 distinct imaging studies. CEUS has the highest endoleak detection rate, followed by CTA and B-Flow. Duplex ultrasound and B-Flow resulted in 0 and 1 false positive cases, respectively, considering CEUS the reference standard. In a select group of six patients, CEUS was omitted after endoleaks were displayed by Duplex ultrasound or B-Flow, leading to a successful type II coiling and no aneurysm-related adverse events. Conclusions: The proposed modular algorithm showed great potential to incorporate principles of personalized medicine in surveillance after endovascular aortic treatment. Since Duplex ultrasound and B-Flow rarely cause false positive endoleaks, more resource-intensive and invasive imaging studies such as CEUS and CTA can be omitted after positive identification.
Influence of Achalasia on the Spirometry Flow–Volume Curve and Peak Expiratory Flow
Authors: Jankovic Jelena , Milenkovic Branislava , Simic Aleksandar , Skrobic Ognjan , Valipour Arschang , Ivanovic Nenad , Buha Ivana , Milin-Lazovic Jelena , Djurdjevic Natasa , Jandric Aleksandar , Colic Nikola , Stojkovic Stefan , Stjepanovic Mihailo
Published: May 2024

Background: Achalasia is an esophageal motor disorder characterized by aperistalsis and the failure of the relaxation of the lower esophageal sphincter. We want to find out whether external compression or recurrent micro-aspiration of undigested food has a functional effect on the airway. Methods: The aim of this research was to analyze the influence of achalasia on the peak expiratory flow and flow–volume curve. All of the 110 patients performed spirometry. Results: The mean diameter of the esophagus was 5.4 ± 2.1 cm, and nine of the patients had mega-esophagus. Seven patients had a plateau in the inspiratory part of the flow–volume curve, which coincides with the patients who had mega-esophagus. The rest of the patients had a plateau in the expiration part of the curve. The existence of a plateau in the diameter of the esophagus of more than 5 cm was significant (p 0.003). Statistical significance between the existence of a plateau and a lowered PEF (PEF < 80) has been proven (p 0.001). Also, a statistical significance between the subtype and diameter of more than 4 cm has been proved. There was no significant improvement in the PEF values after operation. In total, 20.9% of patients had a spirometry abnormality finding. The frequency of the improvement in the spirometry values after surgery did not differ significantly by achalasia subtype. The improvement in FEV1 was statistically significant compared to the FVC values. Conclusions: Awareness of the influence of achalasia on the pulmonary parameters is important because low values of PEF with a plateau on the spirometry loop can lead to misdiagnosis. The recognition of various patterns of the spirometry loop may help in identifying airway obstruction caused by another non-pulmonary disease such as achalasia.
Radiomic Features of Acute Cerebral Hemorrhage on Non-Contrast CT Associated with Patient Survival
Authors: Zaman Saif , Dierksen Fiona , Knapp Avery , Haider Stefan P. , Abou Karam Gaby , Qureshi Adnan I. , Falcone Guido J. , Sheth Kevin N. , Payabvash Seyedmehdi
Published: May 2024

The mortality rate of acute intracerebral hemorrhage (ICH) can reach up to 40%. Although the radiomics of ICH have been linked to hematoma expansion and outcomes, no research to date has explored their correlation with mortality. In this study, we determined the admission non-contrast head CT radiomic correlates of survival in supratentorial ICH, using the Antihypertensive Treatment of Acute Cerebral Hemorrhage II (ATACH-II) trial dataset. We extracted 107 original radiomic features from n = 871 admission non-contrast head CT scans. The Cox Proportional Hazards model, Kaplan–Meier Analysis, and logistic regression were used to analyze survival. In our analysis, the “first-order energy” radiomics feature, a metric that quantifies the sum of squared voxel intensities within a region of interest in medical images, emerged as an independent predictor of higher mortality risk (Hazard Ratio of 1.64, p < 0.0001), alongside age, National Institutes of Health Stroke Scale (NIHSS), and baseline International Normalized Ratio (INR). Using a Receiver Operating Characteristic (ROC) analysis, “the first-order energy” was a predictor of mortality at 1-week, 1-month, and 3-month post-ICH (all p < 0.0001), with Area Under the Curves (AUC) of >0.67. Our findings highlight the potential role of admission CT radiomics in predicting ICH survival, specifically, a higher “first-order energy” or very bright hematomas are associated with worse survival outcomes.
Vascular Endothelial Damage in COPD: Where Are We Now, Where Will We Go?
Authors: Screm Gianluca , Mondini Lucrezia , Salton Francesco , Confalonieri Paola , Trotta Liliana , Barbieri Mariangela , Romallo Antonio , Galantino Alessandra , Hughes Michael , Lerda Selene , Confalonieri Marco , Ruaro Barbara
Published: May 2024

Background: Chronic obstructive pulmonary disease (COPD) has higher rates among the general population, so early identification and prevention is the goal. The mechanisms of COPD development have not been completely established, although it has been demonstrated that endothelial dysfunction plays an important role. However, to date, the measurement of endothelial dysfunction is still invasive or not fully established. Nailfold video capillaroscopy (NVC) is a safe, non-invasive diagnostic tool that can be used to easily evaluate the microcirculation and can show any possible endothelial dysfunctions early on. The aim of this review is to evaluate if nailfold microcirculation abnormalities can reflect altered pulmonary vasculature and can predict the risk of cardiovascular comorbidities in COPD patients. Methods: A systematic literature search concerning COPD was performed in electronic databases (PUBMED, UpToDate, Google Scholar, ResearchGate), supplemented with manual research. We searched in these databases for articles published until March 2024. The following search words were searched in the databases in all possible combinations: chronic obstructive pulmonary disease (COPD), endothelial damage, vascular impairment, functional evaluation, capillaroscopy, video capillaroscopy, nailfold video capillaroscopy. Only manuscripts written in English were considered for this review. Papers were included only if they were able to define a relationship between COPD and endothelium dysfunction. Results: The search selected 10 articles, and among these, only three previous reviews were available. Retinal vessel imaging, flow-mediated dilation (FMD), and skin autofluorescence (AF) are reported as the most valuable methods for assessing endothelial dysfunction in COPD patients. Conclusions: It has been assumed that decreased nitric oxide (NO) levels leads to microvascular damage in COPD patients. This finding allows us to assume NVC’s potential effectiveness in COPD patients. However, this potential link is based on assumption; further investigations are needed to confirm this hypothesis.
Pancreatic Iodine Density and Fat Fraction on Dual-Energy Computed Tomography in Acute Pancreatitis
Authors: Matana Kaštelan Zrinka , Brumini Ivan , Poropat Goran , Tkalčić Lovro , Grubešić Tiana , Miletić Damir
Published: May 2024

The aim of our study was to investigate iodine density (ID) and fat fraction (FF) on dual-energy computed tomography (DECT) in patients with acute pancreatitis (AP). This retrospective study included 72 patients with clinically confirmed AP and 62 control subjects with DECT of the abdomen. Two radiologists assessed necrosis and measured attenuation values, ID, and FF in three pancreatic segments. We used receiver operating characteristic (ROC) analysis to determine the optimal threshold for ID for the differentiation between AP groups. The ID was significantly higher in interstitial edematous AP compared to necrotizing AP and the control group (both p < 0.05). The ROC curve analysis revealed the thresholds of ID for detecting pancreatic necrosis ≤ 2.2, ≤2.3, and ≤2.4 mg/mL (AUC between 0.880 and 0.893, p > 0.05) for the head, body, and tail, respectively. The FF was significantly higher for pancreatitis groups when compared with the control group in the head and body segments (both p < 0.001). In the tail, the difference was significant in necrotizing AP (p = 0.028). The ID values were independent of attenuation values correlated with the FF values in pancreatic tissue. Iodine density values allow for differentiation between morphologic types of AP.
Abnormal Static Sagittal Cervical Curvatures following Motor Vehicle Collisions: A Retrospective Case Series of 41 Patients before and after a Crash Exposure
Authors: Haas Jason W. , Oakley Paul A. , Ferrantelli Joseph R. , Katz Evan A. , Moustafa Ibrahim M. , Harrison Deed E.
Published: May 2024

Previous investigations have found a correlation between abnormal curvatures and a variety of patient complaints such as cervical pain and disability. However, no study has shown that loss of the cervical curve is a direct result of exposure to a motor vehicle collision (MVC). This investigation presents a retrospective consecutive case series of patients with both a pre-injury cervical lateral radiograph (CLR) and a post-injury CLR after exposure to an MVC. Computer analysis of digitized vertebral body corners on CLRs was performed to investigate the possible alterations in the geometric alignment of the sagittal cervical curve. Methods: Three spine clinic records were reviewed over a 2-year period, looking for patients where both an initial lateral cervical X-ray and an examination were performed prior to the patient being exposed to a MVC; afterwards, an additional exam and radiographic analysis were obtained. A total of 41 patients met the inclusion criteria. Examination records of pain intensity on numerical pain rating scores (NPRS) and neck disability index (NDI), if available, were analyzed. The CLRs were digitized and modeled in the sagittal plane using curve fitting and the least squares error approach. Radiographic variables included total cervical curve (ARA C2–C7), Chamberlain’s line to horizontal (skull flexion), horizontal translation of C2 relative to C7, segmental translations (retrolisthesis and anterolisthesis), and circular modelling radii. Results: There were 15 males and 26 females with an age range of 8–65 years. Most participants were drivers (28) involved in rear-end impacts (30). The pre-injury NPRS was 2.7 while the post injury was 5.0; p < 0.001. The NDI was available on 24/41 (58.5%) patients and increased after the MVC from 15.7% to 32.8%, p < 0.001. An altered cervical curvature was identified following exposure to MVC, characterized by an increase in the mean radius of curvature (265.5 vs. 555.5, p < 0.001) and an approximate 8° reduction of lordosis from C2–C7; p < 0.001. The mid-cervical spine (C3–C5) showed the greatest curve reduction with an averaged localized mild kyphosis at these levels. Four participants (10%) developed segmental translations that were just below the threshold of instability, segmental translations < 3.5 mm. Conclusions: The post-exposure MVC cervical curvature was characterized by an increase in radius of curvature, an approximate 8° reduction in C2–C7 lordosis, a mild kyphosis of the mid-cervical spine, and a slight increase in anterior translation of C2–C7 sagittal balance. The modelling result indicates that the post-MVC cervical sagittal alignment approximates a second-order buckling alignment, indicating a significant alteration in curve geometry. Future biomechanics experiments and clinical investigations are needed to confirm these findings.
Pathological and Molecular Diagnosis of Uveal Melanoma
Authors: Păsărică Mihai Adrian , Curcă Paul Filip , Dragosloveanu Christiana Diana Maria , Grigorescu Alexandru Călin , Nisipașu Cosmin Ionuț
Published: May 2024

(1) Background: Uveal melanoma (UM) is a common malignant intraocular tumor that presents with significant genetic differences to cutaneous melanoma and has a high genetic burden in terms of prognosis. (2) Methods: A systematic literature search of several repositories on uveal melanoma diagnosis, prognosis, molecular analysis, and treatment was conducted. (3) Results: Recent genetic understanding of oncogene-initiation mutations in GNAQ, GNA11, PLCB4, and CYSLTR2 and secondary progression drivers of BAP1 inactivation and SF3B1 and EIF1AX mutations offers an appealing explanation to the high prognostic impact of adding genetic profiling to clinical UM classification. Genetic information could help better explain peculiarities in uveal melanoma, such as the low long-term survival despite effective primary tumor treatment, the overwhelming propensity to metastasize to the liver, and possibly therapeutic behaviors. (4) Conclusions: Understanding of uveal melanoma has improved step-by-step from histopathology to clinical classification to more recent genetic understanding of oncogenic initiation and progression.
A Benchmarking Study of Irrigation Advisory Platforms
Authors: Boujdi Soukaina , Ezzahri Abdelkhalek , Bouziani Mourad , Yaagoubi Reda , Kenny Lahcen
Published: May 2024

In the contemporary agricultural landscape, agriculture faces four pressing demands: competitiveness, ensuring food security for a growing population, environmental sustainability, and providing farmers with acceptable living conditions. To meet this global challenge, digital technologies represent a major avenue for innovation and development towards modernized digital agriculture. In this context, irrigation advisory platforms have proven to be transformational tools for both farmers and policymakers, offering insights into the appropriate crop water requirements. This article presents a benchmarking analysis of around 20 professional irrigation advisory platforms. The methodology involves selecting 20 platforms based on accessibility ensuring geographical characteristic diversity. Our findings highlight key criteria shaping the ecosystem of such platforms, including the services offered and their objectives, the types of covered crops, the target users, the form, as well as the source, the availability of the platform, and the variety of data utilized. Lastly, we discuss the main conclusions drawn from our analysis and provide insights into the challenges and future perspectives of irrigation advisory platforms in enhancing agricultural practices and sustainability.
Tax Complexity and Firm Tax Evasion: A Cross-Country Investigation
Authors: Saptono Prianto Budi , Mahmud Gustofan , Salleh Fauzilah , Pratiwi Intan , Purwanto Dwi , Khozen Ismail
Published: May 2024

This paper endeavours to investigate whether a complex tax system influences firms’ propensity toward tax evasion across countries. To achieve the objectives of this study, we utilised the World Bank Enterprise Survey and the World Bank’s Doing Business databases covering more than 46,000 companies from 83 countries. Our study revealed that the increased time required to pay taxes and higher total tax payments were associated with a greater extent and incidence of tax evasion among firms. The consistency of these benchmark regression results was proven through endogeneity analysis and several robustness tests. Furthermore, our heterogeneity analyses showed that the effect of tax complexity on firm tax evasion was more prominent in low- and lower-middle-income countries and also in the primary industry. These findings offer promising evidence for policymakers, particularly in low- and lower-middle-income countries where the majority of companies operate in the primary industry. Addressing the complexity of the tax system could potentially mitigate the adverse impact on tax evasion levels in these countries. Furthermore, our spatial analysis provides valuable insights, emphasising the potential impact of tax complexity in neighbouring countries and underscoring the necessity for policymakers in the home countries to strategise on harmonising and streamlining their tax systems.
Mathematics in Art and History Museums: An Informal Mathematics Education Case for Teachers’ In-Service Training
Authors: Casi Raffaele , Sabena Cristina
Published: May 2024

Recognizing the omnipresence of mathematics across various contexts, this paper addresses the untapped potential of museums as rich venues for informal mathematics learning beyond traditional educational settings like classrooms. This paper presents the InformalMath program, designed for the professional development of primary and middle school teachers using integrating mathematics education within art and history museums through designing mathematics visit workshops. Specifically, the focus is placed on Phase 1 of the program, in which teachers participated in two informal mathematics education workshops at two museums in Turin, Italy, and were asked to reflect on their participation through a written essay. The analysis of the essays reveals significant engagement, appreciation of mathematics as a cultural artifact, and the emergence of creativity and inclusion among participating teachers. These findings highlight the benefits of such interdisciplinary approaches in enhancing mathematical understanding and pedagogical strategies. Conclusions emphasize the program’s success in not only enriching teachers’ instructional repertoire but also in promoting a more holistic, engaging, and contextualized approach to mathematics education, suggesting a promising avenue for future educational practices and research in informal learning environments.
Self-Esteem and Coping Strategies in Adolescent Cancer Patients during the Period of Illness and Follow-Up
Authors: Sáez Rodríguez Diego José , Ortigosa Quiles Juan Manuel , Marin Antonio Riquelme , Martínez Raquel Suriá
Published: May 2024

The importance of self-esteem during the course of oncological illness has been well-documented by some previous studies. However, data assessing its association with various coping strategies, especially considering the period of illness, are still scarce. The objective of this study is to analyze the differences in coping strategies among oncological adolescents, taking into account their self-esteem, illness period, age, and sex. A total of 201 oncological patients between the ages of 12 and 17 from three different Spanish cities were included in this study. All of them were asked to answer a tailored questionnaire, encompassing information about age, sex, and illness period. Additionally, the coping strategies were measured using the ACS scale, while self-esteem was evaluated using the SENA questionnaire. The results demonstrated that male adolescents and older individuals exhibited higher levels of self-esteem. The main coping strategies associated with higher self-esteem were “ignore the problem”, “focus on positive”, “physical recreation”, and “wishful thinking” both during the treatment and the follow-up phases. We conclude that higher self-esteem is associated with some of the coping strategies such as “focus on positive”, “ignore the problem”, and “wishful thinking”. Sociodemographic variables influence the relationship between self-esteem and coping strategies, but no differences were found regarding the period of illness.
Edge HPC Architectures for AI-Based Video Surveillance Applications
Authors: Rossi Federico , Saponara Sergio
Published: May 2024

The introduction of artificial intelligence (AI) in video surveillance systems has significantly transformed security practices, allowing for autonomous monitoring and real-time detection of threats. However, the effectiveness and efficiency of AI-powered surveillance rely heavily on the hardware infrastructure, specifically high-performance computing (HPC) architectures. This article examines the impact of different platforms for HPC edge servers, including x86 and ARM CPU-based systems and Graphics Processing Units (GPUs), on the speed and accuracy of video processing tasks. By using advanced deep learning frameworks, a video surveillance system based on YOLO object detection and DeepSort tracking algorithms is developed and evaluated. This study thoroughly assesses the strengths, limitations, and suitability of different hardware architectures for various AI-based surveillance scenarios.
Exploring the Odd–Even Effect, Current Stabilization, and Negative Differential Resistance in Carbon-Chain-Based Molecular Devices
Authors: Wang Lijun , Zhou Liping , Wang Xuefeng , You Wenlong
Published: May 2024

The transport properties of molecular devices based on carbon chains are systematically investigated using a combination of non-equilibrium Green’s function (NEGF) and density functional theory (DFT) first-principle methods. In single-carbon-chain molecular devices, a distinct even–odd behavior of the current emerges, primarily influenced by the density of states (DOS) within the chain channel. Additionally, linear, monotonic currents exhibit Ohmic contact characteristics. In ladder-shaped carbon-chain molecular devices, a notable current stabilization behavior is observed, suggesting their potential utility as current stabilizers within circuits. We provide a comprehensive analysis of the transport properties of molecular devices featuring ladder-shaped carbon chains connecting benzene-ring molecules. The occurrence of negative differential resistance (NDR) in the low-bias voltage region is noted, with the possibility of manipulation by adjusting the position of the benzene-ring molecule. These findings offer a novel perspective on the potential applications of atom chains.
Enhancing the Safety of Autonomous Vehicles in Adverse Weather by Deep Learning-Based Object Detection
Authors: Zhang Biwei , Simsek Murat , Kulhandjian Michel , Kantarci Burak
Published: May 2024

Recognizing and categorizing items in weather-adverse environments poses significant challenges for autonomous vehicles. To improve the robustness of object-detection systems, this paper introduces an innovative approach for detecting objects at different levels by leveraging sensors and deep learning-based solutions within a traffic circle. The suggested approach improves the effectiveness of single-stage object detectors, aiming to advance the performance in perceiving autonomous racing environments and minimizing instances of false detection and low recognition rates. The improved framework is based on the one-stage object-detection model, incorporating multiple lightweight backbones. Additionally, attention mechanisms are integrated to refine the object-detection process further. Our proposed model demonstrates superior performance compared to the state-of-the-art method on the DAWN dataset, achieving a mean average precision (mAP) of 99.1%, surpassing the previous result of 84.7%.
Prediction of Icing on Wind Turbines Based on SCADA Data via Temporal Convolutional Network
Authors: Zhang Yujie , Kehtarnavaz Nasser , Rotea Mario , Dasari Teja
Published: May 2024

Icing on the blades of wind turbines during winter seasons causes a reduction in power and revenue losses. The prediction of icing before it occurs has the potential to enable mitigating actions to reduce ice accumulation. This paper presents a framework for the prediction of icing on wind turbines based on Supervisory Control and Data Acquisition (SCADA) data without requiring the installation of any additional icing sensors on the turbines. A Temporal Convolutional Network is considered as the model to predict icing from the SCADA data time series. All aspects of the icing prediction framework are described, including the necessary data preprocessing, the labeling of SCADA data for icing conditions, the selection of informative icing features or variables in SCADA data, and the design of a Temporal Convolutional Network as the prediction model. Two performance metrics to evaluate the prediction outcome are presented. Using SCADA data from an actual wind turbine, the model achieves an average prediction accuracy of 77.6% for future times of up to 48 h.
Li4SiO4-Based Heat Carrier Derived from Different Silica Sources for Thermochemical Energy Storage
Authors: Wang Xicheng , Xia Wentao , Xu Wenlong , Chen Zengqiao , Ren Xiaohan , Yang Yuandong
Published: May 2024

Thermochemical energy storage (TCES) is one of the key technologies facilitating the integration of renewable energy sources and mitigating the climate crisis. Recently, Li4SiO4 has been reported to be a promising heat carrier material for TCES applications, owing to its moderate operation temperature and stability. During the synthetic processes, the properties of the Si source used directly influence the performance of derived Li4SiO4 materials; however, the internal relations and effects are not yet clear. Hence, in this work, six kinds of SiO2 sources with different phases, morphology, particle size, and surface area were selected to synthesize a Li4SiO4-based TCES heat carrier. The physicochemical properties of the SiO2 and the corresponding derived Li4SiO4 were characterized, and the comprehensive performance (e.g., heat storage/releasing capacity, rate, and cyclic stability) of the Li4SiO4 samples was systematically tested. It was found that the silica microspheres (SPs), which possess an amorphous phase, uniform micro-scale structure, and small particle size, could generate Li4SiO4 TCES materials with a highest initial capacity of 777.7 kJ/kg at 720 °C/900 °C under pure CO2. As a result, the SP-L showed an excellent cumulative heat storage amount of 5.84 MJ/kg within 10 heat-releasing/storage cycles, which was nearly 1.5 times greater than the value of Li4SiO4 derived from commonly used silicon dioxide. Furthermore, the effects of the utilized Si source on the performance of as-prepared Li4SiO4 and corresponding mechanisms were discussed, which offers guidance for the future selection of Si sources to produce high-performance Li4SiO4-based TCES heat carriers.
Choosing the Most Suitable Working Fluid for a CTEC
Authors: Achkienasi Aliet , Silva Rodolfo , Mendoza Edgar , Luna Luis D.
Published: May 2024

This study aims to explore additional fluids beneficial for coastal thermal energy converter (CTEC) operation. Ammonia’s thermodynamic properties, characterized by higher condensation temperatures and pressures, demand significantly elevated operating pressures, resulting in a substantial energy load for efficient operation. Thus, exploring alternatives such as R134a becomes crucial, particularly considering its potential as a better working fluid for power generation in a Rankine cycle. The research methodology involves employing computational fluid dynamics (CFD) simulations alongside experimental investigations to examine the performance of an axial turbine concept under different working fluids. The results obtained indicate that R134a is the most appropriate working fluid for an axial turbine within a CTEC, outperforming ammonia, thereby implying significantly better operational efficiency.
Forecasting the Power Generation Mix in Italy Based on Grey Markov Models
Authors: D’Amico Guglielmo , Karagrigoriou Alex , Vigna Veronica
Published: May 2024

This study considers an application of the first-order Grey Markov Model to foresee the values of Italian power generation in relation to the available energy sources. The model is used to fit data from the Italian energy system from 2000 to 2022. The integration of Markovian error introduces a random element to the model, which is able now to capture inherent uncertainties and misalignments between the Grey Model predictions and the real data. This application provides valuable insights for strategic planning in the energy sector and future developments. The results show good accuracy of the predictions, which could provide powerful information for the effective implementation of energy policies concerning the evolution of energy demand in the country. Results show an improvement in the performance of more than 50% in terms of Root Mean Squared Error (RMSE) when the Markov chain is integrated in the analysis. Despite advancements, Italy’s 2032 energy mix will still significantly rely on fossil fuels, emphasizing the need for sustained efforts beyond 2032 to enhance sustainability.
The Role of Flexibility in the Integrated Operation of Low-Carbon Gas and Electricity Systems: A Review
Authors: Amiri Mohammad Mehdi , Ameli Mohammad Taghi , Strbac Goran , Pudjianto Danny , Ameli Hossein
Published: May 2024

The integration of gas and electricity networks has emerged as a promising approach to enhance the overall flexibility of energy systems. As the transition toward sustainable and decarbonized energy sources accelerates, the seamless coordination between electricity and gas infrastructure becomes increasingly crucial. This paper presents a comprehensive review of the state-of-the-art research and developments concerning the flexibility in the operation of low-carbon integrated gas and electricity networks (IGENs) as part of the whole system approach. Methods and solutions to provide and improve flexibility in the mentioned systems are studied and categorized. Flexibility is the system’s ability to deal with changes and uncertainties in the network while maintaining an acceptable level of reliability. The presented review underscores the significance of this convergence in facilitating demand-side management, renewable energy integration, and overall system resilience. By highlighting the technical, economic, and regulatory aspects of such integration, this paper aims to guide researchers, policymakers, and industry stakeholders toward effective decision-making and the formulation of comprehensive strategies that align with the decarbonization of energy systems.