bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and Experimental Validation of a Sense and Avoid System for a Mini-UAV
Authors: Fiorio Marco , Galatolo Roberto , Di Rito Gianpietro
Published: December 2024

This paper provides an integrated overview of the three-year effort to design and implement a prototypical SAA system based on a multisensory architecture leveraging data fusion between optical and radar sensors. The work was carried out within the context of the Italian research project named TERSA (Electrical and radar technologies for remotely piloted aircraft systems) undertaken by the University of Pisa in collaboration with its industrial partners, aimed at the design and development of a series of innovative technologies for remotely piloted aircraft systems of small scale (MTOW < 25 Kgf). The approach leverages advanced computer vision algorithms and an Extended Kalman Filter to enhance obstacle detection and tracking capabilities. The “Sense” module processes environmental data through a radar and an electro-optical sensor, while the “Avoid” module utilizes efficient geometric algorithms for collision prediction and evasive manoeuvre computation. Initially, this integrated system has been rigorously tested by means of a sophisticated simulation environment that replicates real-world conditions, including the generation of realistic artificial scenery to evaluate the closed loop interaction between sense and avoid modules in a Hardware-in-the-Loop (HIL) setup. Preliminary results demonstrate the system’s effectiveness in real-time detection and avoidance of non-cooperative obstacles, providing high computational efficiency and responsiveness while ensuring compliance of UAV aero mechanical constraints and safety constraints in terms of minimum distance requirements. At a later stage of the project, the effectiveness of the integrated system was evaluated by means of a preliminary flight test campaign conducted at the Lucca-Tassignano airport in Italy. The findings underscore the potential for deploying such advanced SAA systems in tactical UAV operations, contributing significantly to the safety of flight in non-segregated airspaces.
The Space Phasors Theory and the Conditions for the Correct Decoupling of Multiphase Machines
Authors: Serrano-Iribarnegaray L. , Bonet-Jara J.
Published: December 2024

This paper analyzes first the general statements accepted in the technical literature concerning the complete dynamic decoupling of constant air-gap multiphase machines with space harmonics (usually resorting to the instantaneous symmetrical components, ISC) and shows that they are not correct, since they only hold (and only with good approximation) for the particular case of converter-controlled machines. It then deduces in a rigorous theoretical way the correct conditions in all cases for both a precise and an approximate decoupling of multiphase machines and thereupon verifies them through numerous simulations. To do that, the Space Phasors Theory (SPhTh) is applied, whose true core, often unknown or misunderstood, is clearly explained. Preceding this point, the concept of dynamic phasor of g sequence, which is widely used in the SPhTh, is introduced and the necessary historical and critical review of the ISC is undertaken.
Multimodal AI Framework for Lung Cancer Diagnosis: Integrating CNN and ANN Models for Imaging and Clinical Data Analysis
Authors: Oncu Emir
Published: December 2024

Lung cancer remains a leading cause of cancer-related mortality worldwide, underscoring the critical need for early and accurate diagnostic tools. This study presents a novel multimodal artificial intelligence (AI) framework integrating convolutional neural networks (CNNs) and artificial neural networks (ANNs) to enhance lung cancer detection and classification. The CNN model was trained on a dataset of 900 CT images, meticulously preprocessed and categorized into four classes: adenocarcinoma, large cell carcinoma, squamous cell carcinoma, and normal tissue. Using advanced techniques such as Grad-CAM (Gradient-weighted Class Activation Mapping), the CNN provided interpretable predictions with a weighted average accuracy of 91%, achieving near-perfect AUC values for most classes. Simultaneously, an ANN was developed using clinical data from 999 patients, incorporating 24 features that captured demographic, symptomatic, lifestyle, and genetic factors. The ANN exhibited an exceptional classification performance, attaining an overall accuracy of 99% with minimal misclassifications. Together, these models form a robust diagnostic system that leverages the complementary strengths of imaging and clinical data analysis to improve diagnostic accuracy and clinical decision-making. The proposed framework not only delivers precise classification but also emphasizes interpretability, scalability, and clinical applicability. While the CNN excels in imaging-based diagnosis, the ANN offers reliable predictions grounded in patient-specific clinical data. Future work will focus on expanding datasets, incorporating additional diagnostic modalities, and optimizing the models for real-world clinical deployment. This study highlights the transformative potential of multimodal AI in advancing the early detection and management of lung cancer.
Early Detection of the Pathogenetic Variants of HRR Genes in Prostate Cancer: Critical Analysis and Experimental Design
Authors: Bottillo Irene , Sciarra Alessandro , Bevilacqua Giulio , Gentilucci Alessandro , Sciarra Beatrice , Santarelli Valerio , Salciccia Stefano , Bacigalupo Francesca , Pastacaldi Francesco , Ciccone Maria Pia , De Marchis Laura , Santini Daniele , Magliocca Fabio Massimo , Merenda Elisabetta , Forte Flavio , Grammatico Paola
Published: December 2024

It has been shown that the pathogenic variants (PVs) of the DDR genes, whether of a germinal or somatic nature, represent a predictive biomarker of high sensitivity to treatment with inhibitors of the enzyme PARP, in patients with hormone-resistant metastatic prostate cancer (HRPCa).
Moreover, the detection of PVs of the HRR genes in PCa patients can help to define the patient’s prognosis and the choice of the therapeutic procedure. Among men with metastatic PCa, the frequency of PVs in HRR genes ranges from 11% to 33%, a significantly higher rate compared to non-metastatic PCa, where the incidence is between 5% and 10%. Next Generation Sequencing (NGS) results were more commonly obtained from newly acquired somatic samples compared to archived samples (prostate biopsy or prostatectomy). We developed an experimental multidisciplinary prospective study in patients with new diagnosis of high-risk PCa at biopsy. Aim is to evaluate the the presence of PVs of different HRR genes in patients with the first diagnosis of PCa in relation to a metastatic or non-metastatic stage, tumor aggressiveness and early risk of progression. Among 43 initial tumor samples from 22 patients, 25 samples, from 12 patients, were selected for library preparation based on DNA concentration and quality. After the NGS, 14 different DNA variants were prioritized.
Oncogenetic and likely oncogenetic variants were found in ATM, BRCA1, PTEN, KMT2D and CDH1 genes. Moreover, variants of uncertain significance were found in ATM, DDR2, FANCA, FOXA1, PLCB4, PTCH1 and RB1.
Field Assessment of Arsenic Uptake in Durum Wheat (Triticum durum Desf.) as Influenced by Soil Tillage Practices and Fertilization Source in Mediterranean Environment
Authors: Bravo Ilenia , Atait Mariam , Colamatteo Ilenia , Mancinelli Roberto , Allam Mohamed , Papetti Patrizia , Radicetti Emanuele
Published: December 2024

Nowadays, Arsenic accumulation in agricultural soils and its transfer in crop yields is representing a growing concern that threat to food safety and security in Mediterranean environment. Soil tillage and fertilization may increase the accumulation of Arsenic in plant tissues, therefore, there is the need to develop sustainable agronomical practices able to support crop yield while mitigate As accumulation. The current study carried out in a 7-year long-term experiment with the aim to evaluate As uptake by different plant parts of durum wheat. The experimental treatments are: (i) three soil tillage practices (plowing, subsoiling and spading) and (ii) two fertilization methods (mineral and organic). A factorial randomized complete block design with three replications was adopted. The experimental period refers to the 2018/2019, 2019/2020 and 2020/2021 growing seasons. The results suggested that the maximum level of Arsenic was found in plant roots and minimum was found in wheat kernels. The chemical fertilization as 2020×Mineral (1.522 mg As kg-1 d.m) and 2020×Plowing (1.855 mg As kg-1 d.m) had the maximum Arsenic content in roots. Conversely, the level of Arsenic content was minimum in wheat kernels for organic fertilization as 2021×Organic (0.012 mg As kg-1 d.m) and subsoiling tillage as 2021×Subsoiling (0.008 mg As kg-1 d.m.). Moreover, the application of organic fertilization source, as a tool for enhancing the soil organic matter content also significantly decreased the Arsenic level. The results suggests that reduced tillage practices and adoption of organic amendment could be identified as sustainable agronomic practices in agri-food systems able to improve the quality and assure a safe consumption of wheat kernels. Further studies will be required to evaluate the effectiveness of these agronomical practices also in other crops.
Underwater Gas Leak Quantification by Convolutional Neural Network using Images
Authors: Caldas Gustavo Luís Rodrigues , de Souza Jr. Maurício B. , Moreira Roger Matsumoto
Published: December 2024

Exploration and production activities in deep-water oil and gas reservoirs can directly impact the surrounding ecosystems. Thus, a tool capable of measuring oil and gas leaks based on surveillance images, especially in pre-mature stages, is of great importance for risk assessment. In the present work, a convolutional neural network (U-Net) is applied to leak images using transfer learning and hyperparameter optimization, aiming to predict bubble diameter and flow rate. The data was extracted from a reduced model leak experiment, with a total of 77,676 frames processed, indicating a Big Data context. The results agreed with the data obtained in the laboratory: for the flow rate prediction, coefficients of determination by transfer learning and hyperparameter optimization were, respectively, 0.938 and 0.941. Therefore, the novel methodology has potential applications in the Oil & Gas Industry, in which leaks captured by remotely operated vehicles can be measured by an artificial intelligence agent.
Statistical and Block Copolymers of n-Dodecyl and Allyl Isocyanate via Coordination Polymerization. A Route to Polyisocyanates with Improved Thermal Stability
Authors: Iatrou Maria , Katara Aikaterini , Klonos Panagiotis A. , Kyritsis Apostolos , Pitsikalis Marinos
Published: December 2024

Well-defined amorphous/semi-crystalline statistical copolymers of n-dodecyl isocyanate, DDIC, and allyl isocyanate, ALIC, were synthesized via coordination polymerization, using the chiral half-titanocene complex CpTiCl2(O-(S)-2-Bu) as initiator. In the frame of the terminal model the monomer reactivity ratios of the statistical copolymers were calculated using both well-known linear graphical methods and the computer program COPOINT. The molecular and structural characteristics of the copolymers were also calculated. The thermal properties of these samples were studied by Differential Scanning Calorimetry, DSC, measurements. The kinetics of the thermal decomposition of the statistical copolymers was studied by Thermogravimetric Analysis, TGA, and Differential Thermogravimetry, DTG, and the activation energy of this process was calculated employing several theoretical models. Moreover, block copolymers with the structure P[DDIC-b-(DDIC-co-ALIC)] were synthesized by sequential addition of monomers and coordination polymerization methodologies. The samples were characterized by nuclear magnetic resonance, NMR, spectroscopy, size exclusion chromatography, SEC, and DSC. The thermal stability of the blocks was also studied by TGA and DTG and compared to the corresponding statistical copolymers, showing that the macromolecular architecture greatly affects the properties of the copolymers. Thiol-ene click post-polymerization reaction was performed to introduce aromatic groups along the polyisocyanate chain in order to improve the thermal stability of the parent polymers.
A Review of Polysaccharide-Protein Interactions in Food Systems: Mechanisms, Stability, and Applications
Authors: Yiasmin Mst Nushrat Mst , Al Azad Salauddin , Easdani Md , Islam Md. Serajul , Hussain Mudassar , Cao Weichao , Chen Nuo , Uriho Angelo , Asaduzzaman Md. , Xiao Hua
Published: December 2024

Dietary soft matter components' compatibility and assembly structures are fundamental to advancing food science and industry. This analysis underscores the critical importance of com-patibility and structural stability among these components, particularly emphasizing natural polymers such as polysaccharides and proteins. These polymers can form persistent co-soluble interactions or undergo phase separation, contingent upon their intermolecular assembly con-figurations. The interplay between polysaccharides and proteins is instrumental in shaping the microstructure of food matrices. The intricate balance between attractive and repulsive forces significantly influences the efficacy of self-assembly processes, while weak interactions facilitate necessary structural adaptations. Conversely, excessive forces or insufficient fluctuations can precipitate systemic instability. The article further examines various physical and chemical methodologies that elucidate the principles governing the compatibility and associations of soft matter components. An assessment of soft-material suitability and assembly characteristics is conducted through techniques such as phase modelling, turbidity analysis, microscopy, thermal analysis, rheology, and spectroscopy. Thus, the discourse highlights the imperative of compre-hending soft matter interactions to inform the development of functional food products and their diverse applications, limitations, and future prospective.
Diastolic Function Evaluation in the Personalized Exercise Prescription Program for Solid Organs Transplanted Subjects: Is Atrial Strain Useful?
Authors: Orlandi Melissa , Corsi Marco , Bini Vittorio , Palazzo Roberto , Gitto Stefano , Fiorillo Claudia , Becatti Matteo , Maglione Marco , Stefani Laura
Published: December 2024

Introduction: solid organs transplanted recipients (OTR) have been recently involved in exercise prescription programs in order to reduce the high prevalence of cardiovascular diseases. The normal systolic and diastolic cardiac function is fundamental to personalize the prescription. Diastolic dysfunction can be associated to an higher risk of cardiovascular events and left atrial (LA) strain is an emerging parameter in the evaluation of diastolic compromising, especially in subjects with preserved ejection fraction. Left atrial (LA) strain has never been explored in this category. The study aimed to evaluate the contribution of the LA strain in the assessment of diastolic function of OTR and its potential contribution in the exercise program. Materials and Methods: 54 solid OTR (liver and kidney transplanted) regularly trained for at least 12 months in an home based partially supervised model at moderate intensity estimated by cardiopulmonary exercise test, underwent a complete echocardiographic analysis. Measured variables included left ventricle systolic function (ejection fraction: EF), diastolic function (E/A and E/E’), LA indexed volumes, LA peak atrial longitudinal strain (PALS) and LA peak atrial contraction strain (PACS). The data were compared to 44 healthy subjects (HS). Results: OTR showed an overweight condition (BMI: 25.79 ±2.92 vs 22.25±2.95). Both groups showed a preserved systolic function (EF: OTR 63.1±3.5% vs HS 66.9±6.1; p<0,001) while diastolic standard parameters were significantly different (E/A: 1.01±0.4 vs 1.960.74; p<0.001; E/E’: 9.2±2.7 vs 6.91.3; p<0.001, in OTR and HS respectively) despite normal. LA strain was significantly lower in OTR vs HS (4C PALS: 33.7±9.7 vs 45.4; p<0.001 and 4C PACS: 15.9±6.7 vs 11.67.5; p=0.006; 2C PALS: 35.3±11.1 vs 47.614.9; p<0.001; 2C PALS: 17.4±4.9 vs 13.2; p=0.001, in OTR and HS respectively). A specific correlation of 2 and 4 chamber PACs and PALs with BMI has been observed (R for 4C PALS -0.406** and 2C PALS -0.276*). Conclusions: These findings suggest that the coexistence of increased body weight in asymptomatic OTR patients can exacerbate the impairment of LA strains. LA strain detection could be useful in the personalized exercise program for OTR especially if asymptomatic subjects and with elevated cardiovascular risk profile, to potentially manage the exercise program in the long term. Larger studies will confirm the role in an eventual structured clinical score index.
Research on the Variation Laws of Fire Flooding in Heavy Oil Reservoirs with Different Oil Saturations
Authors: Zhao Fajun , Zhu Shun , Zhang Changjiang , Yang Zian , Sun Mingze , Zhang Hong
Published: December 2024

This study investigates the behavior of heavy oil reservoirs under varying oil saturation conditions through laboratory-scale in-situ combustion (ISC) physical simulation experiments. The research focuses on the propagation stability of the combustion front and key parameters influencing the fire flooding process, with a systematic examination of crude oil composition changes and upgrading mechanisms during ISC. By employing gas chromatography (GC) and infrared spectroscopy (IR) analyses, the study evaluates the transformation of saturated hydrocarbons, aromatic hydrocarbons, resins, and asphaltenes in the produced oil before and after ISC.The results demonstrate that oil saturation plays a critical role in determining combustion efficiency, cracking dynamics, and upgrading performance. At high oil saturation (65%), combustion reactions are vigorous, yielding enhanced cracking efficiency, a significant increase in light hydrocarbon content, and effective conversion of heavy components, achieving optimal upgrading outcomes. Conversely, at low oil saturation (30%), cracking efficiency is reduced, light hydrocarbons are lost, and heavy components, including asphaltenes and polycyclic aromatic hydrocarbons, accumulate, resulting in less effective upgrading. Nonetheless, ignition and stable combustion are achievable even at low oil saturation levels.This study offers strategies to optimize ISC operations tailored to different oil saturation conditions, providing valuable insights for improving combustion efficiency and enhancing the quality of produced oil in heavy oil reservoirs.
In-Situ Fixation and Intertrochanteric Osteotomy for Severe Slipped Capital Femoral Epiphysis Following Femoral Neck Fracture: A Case Report with Application of Virtual Surgical Planning and 3D-Printed Patient-Specific Instruments
Authors: Trisolino Giovanni , Menozzi Grazia Chiara , Ramella Marco , Depaoli Alessandro , Schmidt Olaf Stefan , Cosentino Andrea , Viotto Marianna , Todisco Marco , Alessandri Giulia , Caravelli Silvio , Mosca Massimiliano , Rocca Gino
Published: December 2024

(1) Background: femoral neck fractures are rare but serious injuries in children and adolescents, often resulting from high-energy trauma and prone to complications like avascular necrosis (AVN) and nonunion. Even rarer is the development of slipped capital femoral epiphysis (SCFE) following femoral neck fracture, which presents unique diagnostic and treatment challenges. SCFE can destabilize the femoral head, with severe cases requiring complex surgical interventions; (2) Methods: this report details a case of a 15-year-old male with autism spectrum disorder (ASD) who developed severe SCFE one month after treatment for a Delbet type III femoral neck fracture. The condition was managed with an Imhäuser intertrochanteric osteotomy (ITO), in-situ fixation (ISF), and osteochondroplasty (OChP), supported by virtual surgical planning (VSP) and 3D-printed patient-specific instruments (PSIs) for precise correction and fixation; (3) Results: the surgery was completed without complications. At six months postoperatively, the patient exhibited a pain-free, mobile hip with radiographic evidence of fracture healing and no signs of AVN. Functional outcomes were favorable despite rehabilitation challenges due to ASD; (4) Conclusions: the Imhäuser ITO, combined with ISF and OChP, effectively addressed severe SCFE after femoral neck fracture, minimizing AVN risk. VSP and PSIs enhanced surgical accuracy and efficiency, demonstrating their value in treating rare and complex pediatric orthopedic conditions.
Design of Theophylline Binding Guide RNA for Allosteric Regulation of CRISPR/Cas9 System
Authors: Dolzhikova Olga , Meschaninova Mariya , Endutkin Anton , Golyshev Victor , Vorobyeva Mariya , Novopashina Darya
Published: December 2024

The possibility of CRISPR/Cas gene editing system regulation is an important point for creation of effective molecular biological instrument. Allosteric regulation at the level of guide RNAs is one of possible approach to regulate gene editing system. In this work, we designed chimeric guide RNAs (sgRNA, crRNA, and tracrRNA) containing an aptamer to theophylline in their structure in order to create gene editing systems whose activity can be regulated (increased or decreased) allosterically. Two approaches were used to design the guide RNAs. In the first variant, aptamer sequence was a part of the main elements of guide RNAs. In the second variant, the aptamer sequence was added to the 3'- or 5'-end of the guide RNAs. Changes in Cas9 nuclease activity in the presence of constructed chimeric guide RNAs and the effect of theophylline on the efficiency of model DNA cleavage were studied. Several promising candidates for the role of components of the theophylline-activated and deactivated CRISPR/Cas9 system have been discovered.
Real-Time Models for Manufacturing Processes: How to Build Predictive Reduced Models
Authors: Horr Amir M. , Drexler Hugo
Published: December 2024

New data science and real-time modelling techniques facilitate better monitoring and control of manufacturing processes. By using real-time data models, industries can improve their processes and identify areas where resources are being wasted. This leads to more optimized processes that reduce trial and error loops and the overall environmental footprint. Implementing real-time data analytics allows industries to make quicker, informed decisions and immediate corrections to material processes. This ensures that manufacturing sustainability targets are regularly met, and product quality is maintained. Digital twin and shadow concepts have also been proposed to bridge the gap between physical manufacturing processes and their virtual prototypes. This paper demonstrates the predictive power of real-time reduced models within the digital twin framework to optimize process parameters using data-driven and hybrid techniques. Various reduced and real-time model building techniques are investigated, with brief descriptions of their mathematical and analytical foundations. The role of machine learning (ML) and ML-assisted data schemes in enhancing predictions and corrections is also explored. Real-world applications of these reduced techniques for extrusion and additive manufacturing (AM) processes are presented as case studies.
Evaluating the Role of Visual Fidelity in Digital Vtubers on Mandarin Chinese Character Learning
Authors: Cao Xiaoxiao , Tong Wei , Ono Kenta , Watanebe Makoto
Published: December 2024

Despite the growing presence of digital Vtubers in educational settings, there is limited empirical evidence on their effectiveness in language acquisition. In this investigation, we delved into the realm of digital education to assess how the visual fidelity of digital Vtuber avatars affects the acquisition of Mandarin Chinese characters by beginners. Through incorporating a diverse array of digital Vtubers, ranging from simple two-dimensional figures to complex three-dimensional models, we explored the relationship between digital Vtuber design and learner engagement and efficacy. This study employed a randomized tutorial distribution, immediate post-tutorial quizzing, and a realism scoring rubric, with statistical analysis conducted through Pearson correlation. The analysis involving 608 participants, illuminated a clear positive correlation: digital Vtubers with higher levels of realism significantly enhanced learning outcomes, underscoring the importance of visual fidelity in educational content. This research substantiates the educational utility of digital Vtubers and underscores their potential in creating more immersive and effective digital learning environments. The findings advocate for leveraging sophisticated digital Vtubers to foster deeper learner engagement, improve educational achievement, and promote sustainable educational practices, offering insights for the future development of digital learning strategies.
The Effect of Virtual Reality Feedback Training Using Smart Insoles on Spasticity, Balance, and Gait in Chron-Ic Stroke Patients
Authors: Kim Sunmin , Kim Kyunghun
Published: December 2024

BACKGROUND: This study aimed to investigate the effects of a smart insole-based virtual reality program on balance and gait in patients with chronic stroke. The intention was to provide baseline data for an intervention program designed to improve balance and gait in chronic stroke patients within clinical practice.
OBJECTIVE: Thirty-five chronic stroke patients were randomly divided into two groups: the experimental group, which received a smart insole-based virtual reality training program, and the control group, which received general physical therapy.
METHODS: Prior to the initiation of this study, patients' balance ability was assessed using the Timed Up and Go (TUG) test, and Biorescue (Romberg OE, Romberg CE) was used for further evaluation. Affected step length, stride length, total double support, and cadence were measured to assess gait ability.
RESULT: After the intervention, the experimental group showed a significant increase in TUG and Romberg test (OE, CE) values compared to the control group. Regarding gait ability, the experimental group showed significant increases in velocity, step length, and cadence post-intervention compared to pre-intervention scores, with differences significantly higher than those of the control group.
CONCULSION: The conclusion of this study is that a virtual reality training program based on a smart insole is an effective intervention for chronic stroke patients and can serve as foundational data for clinical practice. It is also significant as an intervention method for chronic stroke patients who require long-term treatment.
Does Hypertension Mediate the Association of the Serum Uric Acid-to-Albumin Ratio with Mortality in U.S. Adults? A Prospective Cohort Study
Authors: Ye Yongzhi , Chen Meiqiong , Ji Fada , Mi Suicai
Published: December 2024

(1) Background: The uric acid-to-albumin ratio (UAR) has emerged as a potential inflammation and oxidative stress biomarker for cardiovascular health; however, its association with mortality risk in the general population and the mediating role of hypertension remain understudied. (2) Methods: The data set comprised 52,534 participants aged 18 years and older from the National Health and Nutrition Examination Survey (NHANES) database, collected between 1999 and 2018. UAR was calculated as the ratio of uric acid (mg/dL) to albumin (g/dL). Covariates included demographic factors, lifestyle variables, and health conditions. The primary outcome was all-cause mortality, with specific-cause mortality as a secondary outcome. Cox proportional hazard models and restricted cubic spline regression (RCS) were used to assess the correlation between UAR levels and risk of death, and mediation analysis was performed to evaluate the role of hypertension in the UAR-mortality relationship.(3) Results: Higher UAR levels were significantly associated with an increased risk of all-cause mortality (hazard ratio [HR], 1.91; 95% confidence interval [CI], 1.77-2.05) and specific cause-related mortalities, particularly heart disease and nephropathy. A strong association was observed between hypertension and mortality (HR, 1.44; 95% CI, 1.36-1.53). The results of the mediation analysis indicated that hypertension played a role in mediating the relationship between UAR and mortality. The mediation effect estimate was -14.34 (95% CI: -18.02, -10.67), p<0.0001, and the proportion mediated by hypertension was 6.09%. This suggests that UAR has a direct impact on mortality, independent of its effect on hypertension. (4) Conclusions: The results of our study indicate a significant correlation between UAR, hypertension, and mortality. This suggests that UAR may serve as a potential biomarker for early risk identification and an antioxidant target for further clinical interventions.
Efficacy and Clinical Application of Najuta Fenestrated Stent Grafts in Aortic Arch Aneurysm Repair
Authors: Onitsuka Seiji , Tanaka Atsuhisa , Otsuka Hiroyuki , Shintani Yusuke , Kanamoto Ryo , Negoto Shinya , Tayama Eiki
Published: December 2024

Endovascular stent graft repair was developed to minimize the invasiveness of open surgery for thoracic and abdominal aortic diseases. This approach involves covering the diseased segment with a stented artificial graft. However, in thoracic endovascular aortic repair (TEVAR) for aortic arch diseases, special consideration is needed to preserve the aortic arch vessels. Traditional stent grafts often require additional procedures, such as bypass surgery, to reconstruct the arch vessels. The semi-custom-made Najuta fenestrated stent graft was developed to address this issue. It is a three-dimensional patient-specific stent graft with fenestrations that allow for the preservation of the arch vessels. This study discusses the unique features of the Najuta stent graft and the techniques for its deployment and provides an analysis of treatment outcomes based on the current literature.
Three-Dimensional Dynamic Positioning Using a Novel Lyapunov-Based Model Predictive Control for Small Autonomous Surface/Underwater Vehicles
Authors: Ji Daxiong , Ogbonnaya Somadina Godwin , Hussain Sheharyar , Hussain Ahmad Faraz , Ye Zhanying , Li Huiping , Tang Yuangui , Li Shuo
Published: December 2024

Small Autonomous Surface/Underwater Vehicles (S-ASUV) are gradually attracting attention from related fields due to their small size, low energy consumption, and flexible motion. Existing dynamic positioning(DP) control approaches suffer from chronic restrictions that hinder adaptability to varying practical conditions, rendering performance poor. A new three-dimensional (3D) dynamic positioning control method for S-ASUV is proposed to tackle this issue. Firstly, the dynamic model for the DP control problem considering the thrust allocation is established by deriving from the dynamic models of S-ASUV. A novel Lyapunov-based model predictive control (LBMPC) method is then designed. Unlike the conventional LMPC, this study uses multi-variable PID as the secondary control law, improving the accuracy and rapidity of the control performance significantly. Both the feasibility and stability are proved rigorously. A series of digital experiments using S-ASUV’s model under diverse conditions demonstrate the proposed method's advantages over existing controllers, affirming satisfactory performances for 3D dynamic positioning in complex environments.
The Effect of Rhizophagus irregularis Inoculation and Phosphorus Treatment on Root Metabolome of Medicago lupulina During Development at the Stage of the First Leaf to the Mature Fruit
Authors: Yurkov Andrey P. , Puzanskiy Roman K. , Kryukov Alexey A. , Kudriashova Tatyana R. , Kovalchuk Anastasia I. , Gorenkova Anastasia I. , Bogdanova Ekaterina M. , Laktionov Yuri V. , Romanyuk Daria A. , Yemelyanov Vladislav V. , Shavarda Alexey L. , Shishova Maria F.
Published: December 2024

An actual biological problem is to identify the effect of mycorrhization by fungi of arbuscular mycorrhiza (АМ) on the metabolic profiles of plant roots at the key stages of host plant development. The aim of the study was to evaluate the effect of Rhizophagus irre-gularis inoculation and/or phosphorus treatment on the root metabolome of Medicago lupulina at the stages from the first leaf to the mature fruit. The assessment of metabolic profiles was performed using GC-MS. 327 metabolites were identified: 26 amino acids, 20 carboxylic acids, 14 fatty acids, 58 sugars, sterols, phenolic compounds, etc. The efficient AM is characterized with upregulation of the metabolism of proteins, carbohydrates and lipids, as well as an increase in the content of phosphates. The level of acids of tricar-boxylic acid cycle were generally lower during mycorrhization. For the first time, the lateral branching initiation stage was shown to have a key importance for the development of efficient AM symbiosis. 14 metabolic markers of the efficient AM symbiosis development were identified. The conclusion is that AM significantly improve plant adaptation to low Pi conditions through metabolic alterations.
“No One Is Safe”: Agricultural Burnings, Wildfires and Risk Perception in Two Agropastoral Communities in the Puna of Cusco, Peru
Authors: Taboada-Hermoza Rossi , Martínez Alejandra G.
Published: December 2024

By designing a conceptual framework that intertwines the use of fire in agricultural activities, the occurrence of wildfires, and the perception of wildfire risk, this article analyses the relationship between these three elements in both wet and dry Puna grasslands. It focuses on two peasant and agropastoral communities, Vilcabamba and Apachaco, both located in Cusco, the region with the highest number of wildfires in Peru. This study highlights the sociocultural significance and persistence of agricultural burnings in Puna agropastoral communities; the necessity of considering changes in agricultural activity, mutual aid systems, and communal institutions—especially concerning land ownership—to explain the occurrence of wildfires; and the widespread perception of wildfire risk among community members, who are aware of the likelihood and severity of wildfire events, while government policies to address this hazard focus primarily on raising awareness and prohibiting burnings.
Advances in Composite Materials for Space Applications: A Comprehensive Literature Review
Authors: Tserpes Konstantinos
Published: December 2024

Space structures are perhaps the most complicated man-made structures due to their extremely harsh and complex operational environments. For these structures, materials serve as crucial technology drivers. Composite materials are increasingly used in space structures due to their specific mechanical properties, customizability, and ability to easily acquire multifunctional and smart characteristics. This review critically examines the state-of-the-art in composite materials application and the computational models used to design and analyze composite space structures.
Research on Teaching Evaluation of Landscape Bridge Aesthetics Creation Ability Based on Sustainable Development Concept
Authors: Li Jinping , Dong Fenghui
Published: December 2024

Keywords: Bridge aesthetics; Landscape design; Capability evaluation; Output oriented; Interval reliability
Study of Magnetron-Deposited Ta-Cu and Nb-Cu Coatings: Their Structure, Mechanical Properties, and Antimicrobial Behavior
Authors: Pogrebnjak Alexander , Borisov Alexander , Tekebayeva Zhanar , Maratuly Bauyrzhan , Jes Alexey , Azamatov Bagdat , Bondar Oleksandr , Mukhamedova Amina
Published: December 2024

This article investigated Ta-Cu and Nb-Cu coatings deposited via magnetron sputtering from metal targets with varying copper content. Scanning electron microscopy (SEM) combined with energy dispersive spectroscopy (EDS) revealed that the coatings had an average thickness of 2.5 μm, with a Cu composition of approximately 10 wt.% and Ta exceeding 86%, with the remaining percentages attributed to carbon and oxygen from the residual vacuum chamber atmosphere. It was observed that increasing the coating thickness from 2.5 μm to 8.5 μm did not result in a significant change in nanohardness (3.29 GPa) in Nb-Cu coatings, although the elastic modulus increased by 15% (from 81 to 95 GPa). Ta-Cu coatings demonstrated superior antibacterial properties compared to Nb-Cu coatings. Consequently, Ta-Cu coatings exhibit considerable potential for further applications due to their favorable structural properties and enhanced antibacterial efficacy.
Explainable Machine Learning dalam Analisis Risiko Akademis Mahasiswa Fakultas Vokasi Institut Teknologi Sepuluh Nopember
Authors: Ananda Lovinki Fitra , Dewi Mukti Ratna , Habibi Mochammad Reza
Published: December 2024

Abstrak:

Mahasiswa dengan performa akademis yang buruk dan tingkat  drop out yang relatif tinggi dapat memengaruhi akreditasi dan citra institusi pendidikan tinggi. Hal tersebut dapat diantisipasi dengan cara mengevaluasi kondisi akademik mahasiswa, khususnya pada mahasiswa yang menunjukkan penurunan performa akademis. Penelitian ini bertujuan memberikan informasi mengenai faktor-faktor yang memengaruhi risiko akademis mahasiswa menggunakan explainable machine learning. Persentase mahasiswa yang berisiko akademis hanya sebesar 7,3% sehingga kasus imbalance ini perlu ditangani menggunakan SMOTE untuk mengoptimalkan kinerja model klasifikasi. Model random forest pada data yang telah seimbang memiliki kemampuan prediksi dengan tingkat akurasi 96,4%, specificity mencapai 95%, dan nilai recall atau sensitivity sebesar 98%. Selanjutnya, SHAP diimplementasikan untuk mengetahui kontribusi masing-masing faktor terhadap potensi risiko akademik. Hasil dari SHAP menunjukkan bahwa skor TPKA kuantitatif, diikuti oleh jenis kelamin dan jalur masuk memiliki kontribusi paling tinggi terhadap risiko akademis mahasiswa

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Abstract:

Students with poor academic performance and relatively high dropout rates can affect the accreditation and image of higher education institutions. This can be anticipated by evaluating the academic conditions of students, especially those who show a decline in academic performance. This study uses explainable machine learning to provide information on the factors that influence students’ academic risk. The percentage of students at academic risk is only 7.3%, so this imbalance case needs to be handled using SMOTE to optimize the performance of the classification model. The random forest model on balanced data has a predictive ability with an accuracy level of 96.4%, specificity reaching 95%, and a recall or sensitivity value of 98%. Furthermore, SHAP is implemented to determine the contribution of each factor to the potential academic risk. The results of SHAP show that the three most significant contributing factors to students’ academic risk are the quantitative TPKA score, followed by gender and type of student admission.
A Hybrid Model to Enhance The Performance of Classifier in Financial Distress Prediction
Authors: Dewi Mukti Ratna , Susilaningrum Destri
Published: December 2024

Accurately predicting financial distress is a critical issue in financial decision-making. Financial distress must be detected as early as possible as an important determining factor in decision-making for internal companies and financial institutions related to financing or loan decisions. Various studies on financial distress prediction in Indonesia have been carried out, ranging from traditional statistical approaches to machine learning. However, the performance of the two methods is still not optimal. Therefore, this study tries to develop machine learning techniques by combining cluster analysis and classification in a hybrid model to improve the prediction model’s performance. The case study adopted in this study is the prediction of financial distress in non-financial companies listed on the IDX from 2018-2021 by combining k-means clustering and Support Vector Machine. The analysis results show that the hybrid classifier has an accuracy value of 92.7%, which is higher than the accuracy of the single classifier, which is 88.6%.
Russian extreme hypertriglyceridemia registy (REGGI): a call to action
Authors: Chubykina U. V. , Ezhov M. V. , Sokolov A. A. , Vasiluev P. A. , Ivanova O. N. , Zakharova E. Y.
Published: December 2024

Hypertriglyceridemia (HTG) is associated with an increased risk of atherosclerotic cardiovascular disease, pancreatitis developing, and all-cause mortality. The risk escalates with rising triglyceride levels and is most significant in extreme HTG (triglycerides above 10 mmol/L). According to epidemiological studies in the Russian Federation, the extreme HTG prevalence varies between 0.1-0.2% (affecting 146,000 to 292,000 Russians). Extreme HTG can be monogenic or polygenic (multifactorial), this determines the clinical course of the disease. Registries are among the most effective models for studying disease development, as they can compile information on clinical, laboratory, instrumental, and molecular data from patients with specific pathologies, and enable analysis of this data and the subsequent development and integration of improved diagnostic and treatment models into clinical practice. The establishment of a registry for extreme HTG will deepen our understanding of the hyperlipidemia nature, regional characteristics of its prevalence, and the phenotypic manifestation of the disease in our country. It will also facilitate the organized and standardized collection of patient information. Data obtained through registry monitoring will enhance diagnostic and monitoring approaches for patients with extreme HTG in practical healthcare settings. The purpose is to present current information on the diagnosis, monitoring, and treatment of patients with extreme HTG, and to announce the creation of the Russian Extreme hypertriGlyceridemia reGIstry (REGGI).
Prospects for the use of anti-inflammatory therapy in patients with coronary artery disease
Authors: Abduzhamalova N. M. , Mamedov M. N.
Published: December 2024

Coronary atherosclerosis is the primary cause of coronary artery disease, one of the world’s greatest causes of death. Inflammation plays a major role in atherosclerosis formation and progression. Cardiovascular disease risk factors such as dyslipidemia, hyperglycemia, smoking, hypertension and others contribute to endothelial injury. This sets off a cascade of inflammatory reactions accompanied by the release of cytokines and other inflammatory mediators, ultimately leading to rupture or erosion of the atherosclerotic plaque and atherothrombosis. Large studies such as CANTOS (Canakinumab Anti-Inflammatory Thrombosis Outcomes Study); COLCOT (Colchicine Cardiovascular Outcomes Trial) and LoDoCo2 (Low Dose Colchicine 2) demonstrated that the use of anti-inflammatory drugs improves the prognosis of patients with coronary atherosclerosis. At present, the most convincing evidence of the effectiveness of anti-inflammatory therapy was obtained only for colchicine and canakinumab. However, despite these promising results, there are still many issues to be addressed. Firstly, more research is needed to determine the optimal dosage and duration of these drugs. Secondly, the safety of their prolonged use should be carefully assessed, especially in the context of possible side effects. For example, anti-inflammatory drugs can potentially pose infectious risks that require special monitoring and follow-up. The review presents current views on the possibilities immunomodulatory drugs using in the complex treatment of atherosclerosis.
Postmyocardial syndrome after myocardial infarction and percutaneous coronary intervention
Authors: Klimenko A. A. , Demidova N. A. , Veselkin V. V. , Kirdyashkina T. A. , Chinova A. A. , Shandanovina Yu. A.
Published: December 2024

Postmyocardial syndrome (Dressler syndrome) is a form of secondary pericarditis with or without pericardial effusion resulting from myocardial damage. Dressler syndrome is not a common disease, but it should be suspected in patients with pathognomonic symptoms after a myocardial infarction (MI). The article presents a clinical case of a 65-year-old man, a smoker who is overweight, with a history of hypertension, MI with ST segment elevation, stenting of the envelope branch of the left coronary artery, thrombospiration. According to coronary angiography, the patient revealed a multivessel lesion of the coronary arteries. Two weeks after stenting, the patient’s condition worsened: shortness of breath, pain in the left half of the chest, fever appeared. During the examination at the outpatient stage, bilateral hydrothorax and hydropericardium were revealed. He was hospitalized, was treated with ibuprofen 600 mg 3 times a day for 7 days, with a positive effect. Ten days after discharge, the patient noted an increase in shortness of breath, an increase in body temperature, a recurrence of dull chest pain. He was hospitalized at the Vorokhobov City Clinical Hospital No. 67, where bilateral hydrothorax, hydropericardium, pneumonitis were detected during the examination. the diagnosis "Postmyocardial syndrome, recurrent course" was established. Hospital treatment was carried out with colchicine, methylprednisolone, acetylsalicylic acid, ticagrelor, losartan, bisoprolol, amlodipine, spironolactone. Against the background of the therapy, the condition improved, the patient began to notice an increase in exercise tolerance, a gradual regression of dull chest pain on the left, body temperature decrease to subfebrile figures. Positive dynamics of laboratory parameters was noted.