bluuebunny/crossref_metadata_2025 huggingface dataset:
Online Action Detection Incorporating an Additional Action Classifier
Authors: Hsu Min-Hang , Hsu Chen-Chien , Wang Yin-Tien , Huang Shao-Kang , Chien Yi-Hsing
Published: October 2024

Most online action detection methods focus on solving a (K + 1) classification problem, where the additional category represents the ‘background’ class. However, training on the ‘background’ class and managing data imbalance are common challenges in online action detection. To address these issues, we propose a framework for online action detection by incorporating an additional pathway between the feature extractor and online action detection model. Specifically, we present one configuration that retains feature distinctions for fusion with the final decision from the Long Short-Term Transformer (LSTR), enhancing its performance in the (K + 1) classification. Experimental results show that the proposed method achieves an accuracy of 71.2% in mean Average Precision (mAP) on the Thumos14 dataset, outperforming the 69.5% achieved by the original LSTR method.
A Stock Prediction Method Based on Multidimensional and Multilevel Feature Dynamic Fusion
Authors: Dong Yuxin , Hao Yongtao
Published: October 2024

Stock price prediction has long been a topic of interest in academia and the financial industry. Numerous factors influence stock prices, such as a company’s performance, industry development, national policies, and other macroeconomic factors. These factors are challenging to quantify, making predicting stock price movements difficult. This paper presents a novel deep neural network framework that leverages the dynamic fusion of multi-dimensional and multi-level features for stock price prediction, which means we utilize fundamental trading data and technical indicators as multi-dimensional data and local and global multi-level information. Firstly, the model dynamically assigns weights to multi-dimensional features of stocks to capture the impact of each feature on stock prices. Next, it applies the Fourier transform to the global features to capture the long-term trends of the global environment and dynamically fuses these with local and global features of the stocks to capture the overall market environment’s impact on individual stocks. Finally, temporal features are captured using an attention layer and an RNN-based model, which incorporates historical price data to forecast future prices. Experiments on stocks from various industries within the Chinese CSI 300 index reveal that the proposed model outperforms traditional methods and other deep learning approaches in terms of stock price prediction. This paper proposes a method that facilitates the dynamic integration of multi-dimensional and multi-level features in an efficient manner and experimental results show that it improves the accuracy of stock price predictions.
Investigating the Quantification Capabilities of a Nanopore-Based Sequencing Platform for Food Safety Application via External Standards of Lambda DNA and Lambda Spiked Beef
Authors: Harper Sky , Counihan Katrina L. , Kanrar Siddhartha , Paoli George C. , Tilman Shannon , Gehring Andrew G.
Published: October 2024

Six hundred million cases of disease and roughly 420,000 deaths occur globally each year due to foodborne pathogens. Current methods to screen and identify pathogens in swine, poultry, and cattle products include immuno-based techniques (e.g., immunoassay integrated biosensors), molecular methods (e.g., DNA hybridization and PCR assays), and traditional culturing. These methods are often used in tandem to screen, quantify, and characterize samples, prolonging real-time comprehensive analysis. Next-generation sequencing (NGS) is a relatively new technology that combines DNA-sequencing chemistry and bioinformatics to generate and analyze large amounts of short- or long-read DNA sequences and whole genomes. The goal of this project was to evaluate the quantitative capabilities of the real-time NGS Oxford Nanopore Technologies’ MinION sequencer through a shotgun-based sequencing approach. This investigation explored the correlation between known amounts of the analyte (lambda DNA as a pathogenic bacterial surrogate) with data output, in both the presence and absence of a background matrix (Bos taurus DNA). A positive linear correlation was observed between the concentration of analyte and the amount of data produced, number of bases sequenced, and number of reads generated in both the presence and absence of a background matrix. In the presence of bovine DNA, the sequenced data were successfully mapped to the NCBI lambda reference genome. Furthermore, the workflow from pre-extracted DNA to target identification took less than 3 h, demonstrating the potential of long-read sequencing in food safety as a rapid method for screening, identification, and quantification.
Shear-Thinning Extrudable Hydrogels Based on Star Polypeptides with Antimicrobial Properties
Authors: Skoulas Dimitrios , Fallon Muireann , Genoud Katelyn J. , O’Brien Fergal J. , Hughes Deirdre Fitzgerald , Heise Andreas
Published: October 2024

Hydrogels with low toxicity, antimicrobial potency and shear-thinning behavior are promising materials to combat the modern challenges of increased infections. Here, we report on 8-arm star block copolypeptides based on poly(L-lysine), poly(L-tyrosine) and poly(S-benzyl-L-cysteine) blocks. Three star block copolypeptides were synthesized with poly(S-benzyl-L-cysteine) always forming the outer block. The inner block comprised either two individual blocks of poly(L-lysine) and poly(L-tyrosine) or a statistical block copolypeptide from both amino acids. The star block copolypeptides were synthesized by the Ring Opening Polymerization (ROP) of the protected amino acid N-carboxyanhydrides (NCAs), keeping the overall ratio of monomers constant. All star block copolypeptides formed hydrogels and Scanning Electron Microscopy (SEM) confirmed a porous morphology. The investigation of their viscoelastic characteristics, water uptake and syringe extrudability revealed superior properties of the star polypeptide with a statistical inner block of L-lysine and L-tyrosine. Further testing of this sample confirmed no cytotoxicity and demonstrated antimicrobial activity of 1.5-log and 2.6-log reduction in colony-forming units, CFU/mL, against colony-forming reference laboratory strains of Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus, respectively. The results underline the importance of controlling structural arrangements in polypeptides to optimize their physical and biological properties.
The Revolution of Genetic Diagnosis: An Example from Rare Disorders
Authors: Zampatti Stefania
Published: October 2024

Since the advent of DNA sequencing, genetic analyses have been increasingly incorporated into clinical practice to support the diagnosis of rare disorders [...]
Cost Analysis of End-Stage Renal Disease in Pediatric Patients in Greece
Authors: Ntais Christos , Loizou Konstantina , Panagiotakis Costas , Kontodimopoulos Nikolaos , Fanourgiakis John
Published: October 2024

Background/Objectives: The cost resulting from peritoneal dialysis (PD), conventional hemodialysis (HD) and online hemodiafiltration (OL-HDF) in pediatric patients with end-stage renal disease (ESRD) has not been estimated to date in Greece. The present single-center retrospective study aimed to estimate the mean annual cost of the above methods, as well as the individual components of this cost. Methods: Twenty pediatric patients undergoing the three different methods of renal replacement therapy were included in this study. Their mean total annual cost was estimated by the method of micro-costing and the bottom-up approach. Results: The mean total annual cost for PD patients (n = 7) was estimated at EUR 56,676.04; for conventional HD patients (n = 9), it was EUR 39,786.86; and for OL-HDF patients (n = 4), it was EUR 43,894.73. The PD method was found to be more expensive than the other two methods (p < 0.001 vs. conventional HD and p = 0.024 vs. OL-HDF). PD consumables used for daily application had the greatest contribution to the total annual cost. The total mean annual cost in the groups of patients undergoing HD and OL-HDF did not differ significantly (p = 0.175). The total operating cost of the renal dialysis unit had the greatest contribution to the total mean annual costs of both the conventional HD and OL-HDF techniques. Conclusions: This cost analysis provides useful information to healthcare policymakers who make decisions about the treatment of children with ESRD.
Pain Management in Knee Osteoarthritis: Insights from an Exploratory Online Survey of Italian Patients and Physicians
Authors: Iolascon Giovanni , Migliore Alberto , Beretta Giovanna , Bernetti Andrea , Bortolotti Roberto , Celano Antonella , Giarratano Antonino , Marinangeli Franco , Momoli Alberto , Sebastiani Gian Domenico , Tomasini Andrea , Tonolo Silvia , Madotto Fabiana , Di Martino Alberto , Natoli Silvia
Published: October 2024

Background: In Italy, knee osteoarthritis (KOA) accounts for over 5 million prevalent cases and requires long-term multidisciplinary management. The most frequent KOA symptom is pain. The aim of the survey is to provide a national overview of the current management of moderate-to-severe pain associated with KOA from both clinicians’ and patients’ perspectives. Methods: An exploratory qualitative survey was conducted in Italy between July and October 2023. The survey participants were members of four national scientific societies and two patient associations who were invited to participate via email and given an online questionnaire. Questions included a mix of single and multiple responses and scalar items. Results: In total, 1473 clinicians and 150 patients with KOA completed the questionnaire. Patients rated knee pain as both the most burdensome symptom and the most frequent reason for treatment dissatisfaction and seeking consultation. One in two patients declared that they were unsatisfied/little satisfied with the current prescribed analgesic treatments. The clinicians surveyed preferentially prescribed intra-articular hyaluronic acid, oral non-steroidal anti-inflammatory drugs/paracetamol, non-pharmacological intervention, and intra-articular corticosteroids. The clinicians’ selection of analgesic therapy often failed to adequately meet patients’ expectations for pain relief. Conclusions: Our findings highlight the current unmet needs of patients with KOA in Italy and call for new approaches to effectively optimize the management of KOA-associated pain.
Assessing the Association of Pain Intensity Scales on Quality of Life in Elderly Patients with Chronic Pain: A Nursing Approach
Authors: Alodhialah Abdulaziz M. , Almutairi Ashwaq A. , Almutairi Mohammed
Published: October 2024

Background: Chronic pain is prevalent among the elderly and significantly affects their quality of life (QoL). Pain intensity scales are crucial tools in evaluating the severity of pain and tailoring management strategies. This study investigates the relationship between various pain intensity scales and QoL among elderly patients with chronic pain, highlighting the implications for nursing practice. Methods: A cross-sectional study was conducted with 150 elderly patients (aged 65 and above) in Riyadh, Saudi Arabia. Participants were assessed using the Numeric Rating Scale (NRS), Visual Analog Scale (VAS), and McGill Pain Questionnaire (MPQ) alongside the 36-Item Short-Form Health Survey (SF-36) to evaluate QoL. Data analysis involved Pearson correlation and multiple regression to explore the association of pain intensity on QoL. Results: All pain scales showed significant negative correlations with QoL. The MPQ exhibited a significant association, suggesting its comprehensive nature captures the multidimensional association of pain more effectively. Regression analysis identified pain intensity, age, and duration of chronic pain as significant predictors of reduced QoL. Conclusions: The findings emphasize the importance of selecting appropriate pain assessment tools that reflect the complex nature of pain in elderly patients. Implementing comprehensive pain assessments like the MPQ can enhance individualized care strategies and potentially improve the QoL in this population. This study underscores the role of nurses in optimizing pain management approaches tailored to the elderly.
Correction: Dolina et al. Trigger Point Therapy Techniques as an Effective Unconventional Method of Treating Tension Headaches: A Systematic Review. Healthcare 2024, 12, 1868
Authors: Dolina Aleksandra , Baszczowski Michał , Wilkowicz Wiktor , Zieliński Grzegorz , Szkutnik Jacek , Gawda Piotr
Published: October 2024

In the original publication [...]
The Empathetic Involvement of Nurses in the Context of Neuroscience: A Mixed-Methods Study
Authors: Bonacaro Antonio , Cortese Federico , Taffurelli Chiara , Sollami Alfonso , Merlini Cinzia , Artioli Giovanna
Published: October 2024

Background/Objectives: Empathy and emotional regulation (susceptibility and resistance) play an important role in a nurse’s well-being and the provision of high-quality care. This phenomenon has not yet been studied in the context of nurses working in neuroscience. This study aimed to explore the perceptions related to empathy among nurses working in neuroscience contexts. Methods: Employing a mixed-methods approach, we conducted an online quantitative survey with 211 nurses working in various neuroscience settings using the Balanced Emotional Empathy Scale (BEES) and 15 online semistructured qualitative interviews to delve deeper into empathetic experiences. The mean and measures of dispersion, such as standard deviation, were used to analyze the quantitative data. Thematic analysis investigated qualitative data, and data triangulation was performed. Results: The quantitative findings revealed no significant differences in empathy or emotional regulation across the different neuroscience settings but highlighted an increase in susceptibility related to young age (under 29) and years of service (first 5 years). The interviews brought to light the challenges nurses face in highly emotional situations and the strategies they employ to manage empathy and maintain professional detachment, such as self-care strategies, awareness development, and team support. One hindering factor is managers. Conclusions: The findings of this study underscore the essential role of empathetic capability in nursing care in neuroscience. The experience of younger nurses and the first 5 years of employment are elements to be considered by managers for burnout risk. Nurses demonstrate susceptibility and resistance and maintain a balance in dealing with high-emotional-stress situations. The implications of these findings are significant and should guide future research and practice in the field of neuroscience nursing.
Conventional and Nano-Zinc Foliar Spray Strategies to Improve the Physico-Chemical Properties and Nutritional and Antioxidant Compounds of Timor Mango Fruits under Abiotic Stress
Authors: Abdel-Sattar Mahmoud , Makhasha Essa , Al-Obeed Rashid S.
Published: October 2024

Zinc deficiency is common under heat stress, and further research is needed to determine how to enhance the fruit quality of mango trees through the use of three forms of zinc, namely Zn-NPs, zinc sulfate (ZnSO4), and chelated zinc (Zn-chelated), as a foliar spray. This research was carried out using ten treatments to investigate the effect of zinc forms on the fruit quality of Timor mango trees. With a few notable exceptions, every fruit quality measurement (physical characteristics, chemical properties, mineral contents, and antioxidant compounds) responded to every treatment looked into; however, the extent of the reaction differed depending on the fruiting measurement. Furthermore, the Zn-NPs created a larger difference in the fruiting measurements than the ZnSO4 and Zn-chelated forms. ZnO NPs at 100 ppm ranked first, followed by ZnO NPs in the first spray and zinc EDTA in the second spray, followed by ZnO NPs in the first spray and ZnSO4 in the second, for all mineral content and antioxidant compound measurements and most of the fruit physico-chemical characteristics. In contrast, the lowest levels of minerals and antioxidant compounds and most of the fruit physico-chemical characteristics were found in the controls. The outcomes of the other treatments after the three treatments lay somewhere between these two extremes, and this pattern was detected throughout two seasons. Spraying Timor mango trees with nano, chelated, and sulfate zinc can be considered a safe and environmentally friendly natural method for improving fruit quality in abiotic stress regions.
Effect of Fertilization in Companion Cropping Systems of Andean Fruit Trees in the Municipality of Ipiales
Authors: Moran-Chamorro Ovidio Javier , Andrade-Díaz Danita , Chirivi-Salomon Juan Sebastian , Velasquez-Vasconez Pedro Alexander
Published: October 2024

Companion cropping offers a potential solution to the challenges of sustainable agriculture, such as optimizing resource use and reducing reliance on chemical inputs. The problem of achieving higher yields while maintaining environmental health remains critical. This practice enhances natural resource conservation, improves fertilization, and optimizes nutrient cycling through the balanced use of chemical and organic sources. Studies, such as those involving tree tomato and Hass avocado, have demonstrated a significant yield increase compared to monocultures, underscoring the viability of this practice. In addition to their environmental benefits, companion crops provide economic advantages by allowing producers to harvest multiple products simultaneously, thereby strengthening food security and the rural economy. This study evaluated three levels of fertilization and interactions between fruit trees at different altitudes, observing differential behavior in the variables evaluated. The combination of cape gooseberry and blackberry showed significantly positive results, with more leaves and fewer pests, demonstrating the benefits of companion plants. A trend towards the combined use of chemical and organic fertilizers was observed, a potential strategy to reduce costs and improve crop growth. The results indicated that the UF system (P. peruviana and P. vulgaris) had the highest plant height, while TF (tree tomato and bean) showed the best stem perimeter development. The incidence of pests was also significant, with Trialeurodes vaporarioum being most prevalent in the P. peruviana companion. These findings support companion cropping as a viable and promising strategy for more efficient and sustainable agriculture, offering both environmental and economic benefits.
A Graphic Review of Studies on Ocean and Mediterranean Sea Environment Quality
Authors: Briciu Andrei-Emil
Published: October 2024

With so many studies today on the water quality of the sea, one can hardly comprehend the multitude of topics that arise all over the world. This study provides a few graphic syntheses related to the most frequent words (including their clustering and links), trend topics, the spatial distribution of the researched areas, and the thematic evolution of the research directions over the decades. The most frequent authors’ keywords have a 50% similitude between the ocean studies and the studies related to the Mediterranean Sea; these keywords are part of a causal chain that dominates the marine studies on water quality: nutrients → eutrophication → phytoplankton → chlorophyll → seagrass. The most frequent words in the titles and abstracts of the selected papers from the Web of Science are “concentration” and “species”; in the Mediterranean studies, “chlorophyll” and “temperature” are the most frequent. In close connection with water quality, Zostera marina (eelgrass) and Crassotrea virginica (eastern oyster) prevail at the global scale, while Posidonia oceanica (Neptune grass) is relevant in the Mediterranean space. Some of the most studied water bodies are the South China Sea, San Francisco Bay, Chesapeake Bay, and, in the Mediterranean Sea, the Adriatic, Ionian, Aegean, and Marmara seas. “Climate change” and “remote sensing” are trend topics that shape the current studies on water quality; the increasing sea surface temperature enhances algal blooms—these need to be monitored using satellite imagery for the sustainable evolution of human activities, including aquaculture.
Reply to Bektaş, S. Comment on “Ioannidou, S.; Pantazis, G. Helmert Transformation Problem. From Euler Angles Method to Quaternion Algebra. ISPRS Int. J. Geo-Inf. 2020, 9, 494”
Authors: Pantazis George , Ioannidou Stefania
Published: October 2024

The comment disputes some of the inferences in the paper “Helmert Transformation Problem. From Euler Angles Method to Quaternion Algebra”, published in this journal. The key points in the dissent are the following: (1) The number of unknown parameters in the reverse transformation problem using dual quaternions. (2) The reliability of both data and the results. (3) There should be no differences between Euler angles and quaternion methods. Our response is summarized as follows: (1) The problem can be solved using either eight or nine unknown parameters. (2) All the data and results are real. (3) There should be differences between methods because of different calculations.
Enhancing Brain Tumor Detection Through Custom Convolutional Neural Networks and Interpretability-Driven Analysis
Authors: Dewage Kavinda Ashan Kulasinghe Wasalamuni , Hasan Raza , Rehman Bacha , Mahmood Salman
Published: October 2024

Brain tumor detection is crucial for effective treatment planning and improved patient outcomes. However, existing methods often face challenges, such as limited interpretability and class imbalance in medical-imaging data. This study presents a novel, custom Convolutional Neural Network (CNN) architecture, specifically designed to address these issues by incorporating interpretability techniques and strategies to mitigate class imbalance. We trained and evaluated four CNN models (proposed CNN, ResNetV2, DenseNet201, and VGG16) using a brain tumor MRI dataset, with oversampling techniques and class weighting employed during training. Our proposed CNN achieved an accuracy of 94.51%, outperforming other models in regard to precision, recall, and F1-Score. Furthermore, interpretability was enhanced through gradient-based attribution methods and saliency maps, providing valuable insights into the model’s decision-making process and fostering collaboration between AI systems and clinicians. This approach contributes a highly accurate and interpretable framework for brain tumor detection, with the potential to significantly enhance diagnostic accuracy and personalized treatment planning in neuro-oncology.
Estimation of Pavement Condition Based on Data from Connected and Autonomous Vehicles
Authors: Llopis-Castelló David , Camacho-Torregrosa Francisco Javier , Romeral-Pérez Fabio , Tomás-Martínez Pedro
Published: October 2024

Proper road network maintenance is essential for ensuring safety, reducing transportation costs, and improving fuel efficiency. Traditional pavement condition assessments rely on specialized equipment, limiting the frequency and scope of inspections due to technical and financial constraints. In response, crowdsourcing data from connected and autonomous vehicles (CAVs) offers an innovative alternative. CAVs, equipped with sensors and accelerometers by Original Equipment Manufacturers (OEMs), continuously gather real-time data on road conditions. This study evaluates the feasibility of using CAV data to assess pavement condition through the International Roughness Index (IRI). By comparing CAV-derived data with traditional pavement auscultation results, various thresholds were established to quantitatively and qualitatively define pavement conditions. The results indicate a moderate positive correlation between the two datasets, particularly in segments with good-to-satisfactory surface conditions (IRI 1 to 2.5 dm/km). Although the IRI values from CAVs tended to be slightly lower than those from auscultation surveys, this difference can be attributed to driving behavior. Nonetheless, our analysis shows that CAV data can be used to reliably identify pavement conditions, offering a scalable, non-destructive, and continuous monitoring solution. This approach could enhance the efficiency and effectiveness of traditional road inspection campaigns.
Device-Assisted Left Atrial Appendage Exclusion: From Basic Sciences to Clinical Applications
Authors: Karpierz Julia Izabela , Piotrowski Michał , Bartuś Krzysztof , Chmiel Radosław , Wijatkowska Katarzyna , Słomka Artur
Published: October 2024

Device-assisted left atrial appendage exclusion plays a crucial role in the prevention of fatal ischemic complications in patients with atrial fibrillation and contraindications to anticoagulation treatment. Various devices with different safety profiles and device-related complications are available in daily practice to perform this procedure. In this review, the anatomy, physiology, and functions of the left atrial appendage were detailed, and all available devices used for epicardial and endocardial exclusion of the left atrial appendage and their clinical outcomes were discussed. Future research should aim to further investigate the long-term effects of left atrial appendage exclusion on body homeostasis, blood coagulation, and cardiac function.
Secondary Bacterial Infections in Critically Ill COVID-19 Patients Admitted in the Intensive Care Unit of a Tertiary Hospital in Romania
Authors: Pintea-Simon Ionela-Anca , Bancu Ligia , Mare Anca Delia , Ciurea Cristina Nicoleta , Toma Felicia , Brukner Mădălina Cristina , Văsieșiu Anca-Meda , Man Adrian
Published: October 2024

Background: The outbreak of the COVID-19 pandemic caught healthcare systems in many countries unprepared. Shortages of personnel, medicines, disinfectants, and intensive care unit (ICU) capacities, combined with inadvertent use of antibiotics and emergence of drug-resistant secondary infections, led to a surge in COVID-19-related mortality. Objective: We aimed to evaluate the prevalence of secondary bacterial infections and the associated antibiotic resistance in a temporary established ICU dedicated to COVID-19 patients. We also assessed the utility of clinical and routine laboratory data as predictors of secondary infections and mortality in these patients. Methods: We examined the medical records of 243 patients admitted to the COVID-19 Medical Support Unit of Târgu Mures, Romania, between 1 August 2020 and 31 January 2021. Results: Among the 243 patients admitted to the COVID-19 Medical Support Unit of Târgu Mures between 1 August 2020 and 31 January 2021, 59 (24.3%) presented secondary infections. Acinetobacter baumannii and Klebsiella pneumoniae were the most frequent isolates (31.1% and 18.9%, respectively), most of them multidrug resistant. Chronic obstructive pulmonary disease had a higher prevalence in patients who developed secondary infections (p = 0.012). Secondary infections were associated with longer stay in the ICU and with higher mortality (p = 0.006 and p = 0.038, respectively). Conclusions: Early identification of secondary infections and proper use of antibiotics are necessary to limit the spread of multidrug-resistant microorganisms in COVID-19 patients admitted in the ICU.
Extent of Endoscopic Sinus Surgery for Odontogenic Sinusitis of Endodontic Origin with Ethmoid and Frontal Sinus Involvement
Authors: Kwiatkowska Marta Aleksandra , Szczygielski Kornel , Jurkiewicz Dariusz , Rot Piotr
Published: October 2024

Background/Objectives: Odontogenic sinusitis (ODS) is the most common cause of unilateral maxillary sinus opacification. Initial treatment consists of intranasal steroids and antimicrobial therapy. In case of persistence of the disease, endoscopic sinus surgery (ESS) is advised. It is still not clear what extension of ESS is required and whether frontal sinusotomy or ethmoidectomy is justified in ODS with frontal sinus involvement. Methods: Adult patients presented with uncomplicated recalcitrant bacterial ODS due to endodontic-related dental pathology were evaluated by an otolaryngologist and a dentist and scheduled for ESS. Sinus CT scan demonstrated opacification of maxillary sinus and partial or complete opacification of extramaxillary sinuses ipsilateral to the side of ODS. Patients were undergoing either maxillary antrostomy, antroethmoidectomy, or antroethmofrontostomy. Preoperative and postoperative evaluations were done with nasal endoscopy, dental examination, subjective and radiological symptoms. Results: The study group consisted of 30 patients. Statistically significant decreases in values after surgery were found for SNOT-22, OHIP-14, Lund–Mackay, Lund–Kennedy, and Zinreich scale. Tooth pain was present in 40% cases during the first visit and in 10% during the follow-up visit. Foul smell was initially reported by 73.3% and by one patient during follow-up visit (3.3%). Significantly longer total recovery time and more crusting was marked for antroethmofrontostomy when compared to maxillary antrostomy. Conclusions: ESS resolved ODS with ethmoid and frontal involvement in almost every case. Minimal surgery led to improved overall clinical success in the same way as antroethmofrontostomy without risking the frontal recess scarring and stenosis.
Mechanical Mapping of the Common Carotid Artery in Healthy Individuals Aged 2 to 40 Years
Authors: Maurice Roch Listz , Dahdah Nagib
Published: October 2024

(1) Background: In 2022, the World Stroke Organization said there were more than 12.2 million new cases of stroke each year, between all ages and sexes. Six and a half million people die each year from stroke. Ischemic stroke accounts for 7.6 million (62%) cases, with 3.3 million (51%) deaths. Stroke is mainly linked to the atherosclerosis of a large artery. (2) Objective: Since the carotid artery directly supplies the brain, we used age-dependent mechanical mapping on the healthy common carotid artery (CCA) with the aim of being able to predict and thus potentially prevent ischemic stroke. (3) Methods: We assessed the CCA stiffness of 95 healthy control (CTL) females (2.23–39.46 years) and 107 healthy CTL males (2.85–40 years). Cine-loops of B-mode CCA data were digitally recorded with conventional medical ultrasound devices. Arterial wall elastic moduli were estimated offline using a proprietary non-invasive imaging-based biomarker algorithm (ImBioMark). Statistical analyzes were carried out with Excel software. (4) Results: Females showed a linear regression profile of CCA elastic moduli ranging from 41 ± 2 kPa to 54 ± 17 kPa (R2 = 0.88), while males showed one ranging from 38 ± 5 kPa to 63 ± 22 kPa (R2 = 0.83). For qualitative and quantitative illustrations, the elastic modulus data of CTLs were compared with those of subjects with Kawasaki disease and subjects born prematurely, respectively. (5) Conclusions: This study introduced some fundamental features of the mechanical evolution of the CCA as a function of age (2–40 years). Since atherosclerotic arteriopathy starts early in life, this gives the ability to predict risks of stroke and other cardiovascular diseases with the possibility of applying a more comprehensive range of potential preventive measures early in life. This is consistent with preventive medicine objectives which aim to be more predictive to implement pre-emptive measures as opposed to diagnostic and curative approaches.
The Relationship Between the Burpee Movement Program and Strength and Endurance Performance Measures in Active Young Adults: A Cross-Sectional Analysis
Authors: Šiska Ľuboslav , Balint Gheorghe , Židek Daniel , Sedlacek Jaromir , Tkacik Štefan , Balint Nela Tatiana
Published: October 2024

Objectives: This paper aimed to assess the motor performance in the Burpee Movement Program through the acceleration recorded by the Phyphox mobile app and define its relationship to strength and endurance parameters. Methods: Altogether, 15 students in physical education teaching completed the 3 × 3 min Burpee Movement Program, consisting of the repeated execution of a single burpee with maximum effort at regular intervals triggered by a sound signal. During the load phase, the intensity of the burpee and the fatigue index expressed in percentages were evaluated by means of the acceleration recorded through a mobile phone. In the second part of testing, we evaluated the performance parameters during a bench press and squat where the intensity was measured using a linear displacement transducer (Tendo Power Analyzer) and aerobic endurance was assessed with a 20 m shuttle run test (20 mSR). Results: The average intensity of the burpee ranged from 3.12 to 11.12 ms−2. The fatigue index ranged from −21.95% (which represented an increase in performance) to 33.63% (which represented a decrease in performance). The performances in the bench presses ranged from 58 to 480 W and from 175 to 696 W during the squats. The distance in the 20 m shuttle run test (20 mSR) ranged from 540 to 2000 m. The intensity of the burpee showed a significant correlation to the performances achieved in the bench presses and squats r = 0.82 and 0.79. The fatigue index showed a significant correlation to the 20 m shuttle run test (20 mSR) r = −0.67. Conclusions: These findings indicate that in, our case, the results from the Burpee Movement Program are significantly associated with the participants’ strength and endurance abilities. We recommend using BMP for the development of strength–endurance abilities, but further exploration is needed regarding the potential use of BMP as a diagnostic test.
Differentiation of Benign and Malignant Neck Neoplastic Lesions Using Diffusion-Weighted Magnetic Resonance Imaging
Authors: Gamaleldin Omneya , Iannella Giannicola , Cavalcanti Luca , Desouky Salaheldin , Shama Sherif , Gamaleldin Amel , Elwany Yasmine , Magliulo Giuseppe , Greco Antonio , Pace Annalisa , Virgilio Armando De , Maniaci Antonino , Lavalle Salvatore , Messineo Daniela , Bahgat Ahmed
Published: October 2024

The most difficult diagnostic challenge in neck imaging is the differentiation between benign and malignant neoplasms. The purpose of this work was to study the role of the ADC (apparent diffusion coefficient) value in discriminating benign from malignant neck neoplastic lesions. The study was conducted on 53 patients with different neck pathologies (35 malignant and 18 benign/inflammatory). In all of the subjects, conventional MRI (magnetic resonance imaging) sequences were performed apart from DWI (diffusion-weighted imaging). The mean ADC values in the benign and malignant groups were compared using the Mann–Whitney test. The ADCs of malignant lesions (mean 0.86 ± 0.28) were significantly lower than the benign lesions (mean 1.43 ± 0.57), and the mean ADC values of the inflammatory lesions (1.19 ± 0.75) were significantly lower than those of the benign lesions. The cutoff value of 1.1 mm2/s effectively differentiated benign and malignant lesions with a 97.14% sensitivity, a 77.78% specificity, and an 86.2% accuracy. There were also statistically significant differences between the ADC values of different malignant tumors of the neck (p, 0.001). NHL (0.59 ± 0.09) revealed significantly lower ADC values than SCC (0.93 ± 0.15). An ADC cutoff point of 0.7 mm2/s was the best for differentiating NHL (non-Hodgkin lymphoma) from SCC (squamous cell carcinoma); it provided a diagnostic ability of 100.0% sensitivity and 89.47% specificity. ADC mapping may be an effective MRI tool for the differentiation of benign and inflammatory lesions from malignant tumors in the neck.
Investigating the Sim-to-Real Generalizability of Deep Learning Object Detection Models
Authors: Rüter Joachim , Durak Umut , Dauer Johann C.
Published: October 2024

State-of-the-art object detection models need large and diverse datasets for training. As these are hard to acquire for many practical applications, training images from simulation environments gain more and more attention. A problem arises as deep learning models trained on simulation images usually have problems generalizing to real-world images shown by a sharp performance drop. Definite reasons and influences for this performance drop are not yet found. While previous work mostly investigated the influence of the data as well as the use of domain adaptation, this work provides a novel perspective by investigating the influence of the object detection model itself. Against this background, first, a corresponding measure called sim-to-real generalizability is defined, comprising the capability of an object detection model to generalize from simulation training images to real-world evaluation images. Second, 12 different deep learning-based object detection models are trained and their sim-to-real generalizability is evaluated. The models are trained with a variation of hyperparameters resulting in a total of 144 trained and evaluated versions. The results show a clear influence of the feature extractor and offer further insights and correlations. They open up future research on investigating influences on the sim-to-real generalizability of deep learning-based object detection models as well as on developing feature extractors that have better sim-to-real generalizability capabilities.
Quantitative Comparison of Color-Coded Parametric Imaging Technologies Based on Digital Subtraction and Digital Variance Angiography: A Retrospective Observational Study
Authors: Góg István , Sótonyi Péter , Nemes Balázs , Kiss János P. , Szigeti Krisztián , Osváth Szabolcs , Gyánó Marcell
Published: October 2024

The evaluation of hemodynamic conditions in critical limb-threatening ischemia (CLTI) patients is inevitable in endovascular interventions. In this study, the performance of color-coded digital subtraction angiography (ccDSA) and the recently developed color-coded digital variance angiography (ccDVA) was compared in the assessment of key time parameters in lower extremity interventions. The observational study included 19 CLTI patients who underwent peripheral vascular intervention at our institution in 2020. Pre- and post-dilatational images were retrospectively processed and analyzed by a commercially available ccDSA software (Kinepict Medical Imaging Tool 6.0.3; Kinepict Health Ltd., Budapest, Hungary) and by the recently developed ccDVA technology. Two protocols were applied using both a 4 and 7.5 frames per second acquisition rate. Time-to-peak (TTP) parameters were determined in four pre- and poststenotic regions of interest (ROI), and ccDVA values were compared to ccDSA read-outs. The ccDVA technology provided practically the same TTP values as ccDSA (r = 0.99, R2 = 0.98, p < 0.0001). The correlation was extremely high independently of the applied protocol or the position of ROI; the r value was 0.99 (R2 = 0.98, p < 0.0001) in all groups. A similar correlation was observed in the change in passage time (r = 0.98, R2 = 0.96, p < 0.0001). The color-coded DVA technology can reproduce the same hemodynamic data as a commercially available DSA-based software; therefore, it has the potential to be an alternative decision-supporting tool in catheter labs.
Influence of Printing Parameters on the Morphological Characteristics of Plasma Directed Energy-Deposited Stainless Steel
Authors: Segovia-Guerrero Luis , Gil-Mena Antonio José , Baladés Nuria , Sales David L. , Fonollá Carlota , de la Mata María , de Nicolás-Morillas María
Published: October 2024

This study investigated the influence of printing parameters and strategies on the morphological characteristics of austenitic stainless steel beads deposited on carbon steel substrates, using plasma directed energy deposition (DED). The experimental setup varied the welding current, wire feed speed, and torch travel speed, and we analyzed three printing strategies: simple-linear, overlapping, and oscillating. Moreover, advanced 3D scanning and computational analysis were used to assess the key morphological features, including bead width and height. The results showed that the computational model developed by using parabolic assumptions accurately predicted the geometric outcomes of the overlapping beads. The oscillating printing strategy was the one that showed improved morphological uniformity and bead substrate wettability, so these features were used for multi-layer component manufacturing. The use of equivalent wavelength–amplitude values resulted in maximum combinations of bead height and width. Moreover, cost-effective carbon steel substrates were feasibly used in microstructural and elemental analyses, with the latter ones confirming the alignment of the bead composition with the wire-fed material. Overall, this study provides practical insights for optimizing plasma DED processes, thus enhancing the efficiency and quality of metal component manufacturing.
UUV-Assisted Icebreaking Application in Polar Environments Using GA-SPSO
Authors: Pan Wei , Wang Yang , Song Fei , Peng Likun , Zhang Xiaofeng
Published: October 2024

This paper addresses the challenges faced by icebreakers in polar environments, particularly the difficulty in sensing underwater ice formations when navigating through thick ice layers, which often results in suboptimal icebreaking effectiveness. To overcome these challenges, this paper introduces a novel underwater robot equipped with both sensing and icebreaking capabilities. We propose a path-planning method for icebreaking that leverages the synergistic capabilities of the genetic algorithm and safe particle swarm optimization (GA-SPSO). The GA-SPSO algorithm integrates the global search prowess of the particle swarm optimization with the local optimization strength of the genetic algorithm, enabling efficient and adaptive path planning in complex ice environments. The unmanned underwater vehicles (UUV)-assisted icebreaking approach developed here utilizes the UUV’s flexibility and high-precision environmental sensing to provide real-time optimization suggestions for icebreaker navigation paths. Simulation results demonstrate that the GA-SPSO algorithm not only effectively circumvents hazardous areas but also significantly reduces the energy consumption and operational time of icebreakers, thereby enhancing the safety and stability of navigation. When compared to the conventional safe particle swarm optimization (SPSO), our approach shows marked improvements in path length, convergence speed, and obstacle avoidance capabilities, significantly enhancing the success and efficiency of polar navigation missions.
Optimizing Ship Draft Observation with Wave Energy Attenuation and PaddlePaddle-OCR in an Anti-Fluctuation Device
Authors: Wei Yaoming , Du Huan , Hu Qinyou , Wang Hu
Published: October 2024

With the development and application of artificial intelligence (AI) in the shipping industry, using AI to replace traditional draft survey methods in bulk carriers can significantly reduce manpower, lower the risks associated with visual observations, improve measurement accuracy, and minimize the impact of human subjective factors. Ultimately, the integration of software and hardware technologies will replace human visual observations with automated draft measurement calculations. A similar anti-fluctuation device described in this article has been used in ship draft observation based on AI-assisted proving, which can ease the fluctuation of the wave inside the pipe. Observers can directly read the water surface inside the pipe and compare it to the ship’s draft mark to obtain the final draft, effectively improving draft observation accuracy. However, some surveyors refuse to accept the readings obtained from this device, citing a lack of theoretical basis or the absence of accreditation from relevant technical authorities, leading to the rejection of results. To address these issues, this paper integrates wave energy attenuation theory with PaddlePaddle-OCR recognition to further validate the anti-fluctuation device for accurate ship draft observation. The experimental results are as follows: first, the pipe effectively suppresses the amplitude of external water surface fluctuations by 75%, explaining the fundamental theory that wave heights within the anti-fluctuation device are consistent with external swell heights. When taking a draft measurement, the system dynamically adjusts the position of the main tube in response to the ship’s movements, maintaining the stability of the measurement section and significantly reducing the difficulty of observations. Due to the reduction in fluctuation amplitude, there is a noticeable improvement in observation accuracy.
Study on the Prediction of Motion Response of Offshore Platforms Based on ResCNN-LSTM
Authors: Diao Feng , Liu Tianyu , Likeufack Mdemaya Franck Aurel , Xu Gang
Published: October 2024

In the random sea environment, offshore platforms are influenced by factors such as wind, waves, and currents, as well as their interactions, leading to complex motion phenomena that affect the safety of offshore platform operations. Consequently, accurately predicting the motion response of offshore platforms has long been a key focus in the fields of naval architecture and ocean engineering. This paper utilizes STAR-CCM+ to simulate time-history data of offshore platform motion responses under both regular and irregular waves. Furthermore, a predictive model combining residual convolutional neural networks and long short-term memory neural networks using neural network technology is also studied. This model utilizes an autoregressive approach to predict the motion responses of offshore platforms, with its predictive accuracy validated through comprehensive evaluations. Under regular wave conditions, the coefficient of determination (R2) for the platform’s heave and pitch responses consistently exceeds 0.99. Meanwhile, under irregular wave conditions, the R2 values remain generally above 0.4. Additionally, the model exhibits commendable performance in terms of Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) metrics. The aim of this study is to present a novel approach to predicting offshore platform motion responses, while providing a more scientific basis for decision-making in offshore platform operations.
Morphology and Effect of Load on Bridge Piers Impacted by Continuous Sea Ice
Authors: Gong Li , Cui Yue , Du Yunfei , Qin Long , Zhao Xinyuan
Published: October 2024

In order to study the collision of sea ice on bridge piers of a sea-crossing bridge, this study establishes a finite element model of the impact of sea ice on bridge piers in aqueous media based on explicit dynamics analysis software and programming software using the arbitrary Lagrangian Eulerian (ALE) method. The results show that, when the sea-ice spacing is larger than the sea-ice edge length, the increase in sea-ice spacing leads to a decrease in the collision force and a significant increase in the probability of climbing and overturning. The increase in sea-ice mass significantly increases the impact force on the bridge abutment, and the peak value increases linearly with the increase in mass, and the sea-ice climbing and overturning phenomena are obvious. Different shapes of sea ice are obtained by cutting the sea-ice field with the two-dimensional Voronoi method, and the maximum impact force increases significantly with the increase in the average area. Irregularly shaped sea ice leads to a larger impact force and triggers the accumulation climbing phenomenon, which is verified by experiments, and the experimental values are in good agreement with the simulated values. In conclusion, this study reveals the significant effects of the spacing, mass, and shape of sea ice on the impact force of bridge piers, which provides an important reference for the design of bridge structures.