bluuebunny/crossref_metadata_2025 huggingface dataset:
The Prevalence, Etiology and Treatment of Gastroduodenal Ulcers and Perforation: A Systematic Review
Authors: Amalia Rizki , Vidyani Amie , I’tishom Reny , Efendi Wiwin Is , Danardono Edwin , Wibowo Bogi Pratomo , Parewangi Muhammad Lutfi , Miftahussurur Muhammad , Malaty Hoda M.
Published: February 2024

(1) Background: Gastroduodenal perforation (GDP) is a life-threatening condition caused by a spontaneous or traumatic event. Treatment should be based on the mechanism of damage, timing, location, extent of the injury, and the patient’s clinical condition. We aimed to examine several etiologic factors associated with gastroduodenal perforation and to search for the best method(s) for its prevention and treatment. (2) Methods: We conducted extensive literature reviews by searching numerous studies obtained from PubMed, Science Direct, and Cochrane for the following keywords: gastroduodenal perforation, Helicobacter pylori, NSAIDs’ use, side effects of GDP, laparoscopy, and surgery. The primary outcome was the reported occurrence of GDP. (3) Results: Using keywords, 883 articles were identified. After applying the inclusion and exclusion criteria, 53 studies were eligible for the current analyses, with a total number of 34,692 gastroduodenal perforation cases. Even though the risk factors of gastroduodenal perforation are various, the prevalence of H. pylori among patients with perforation is considerably high. As technology develops, the treatment for gastric perforation will also improve, with laparoscopic surgery having a lower mortality and complication rate compared to open surgery for GDP treatment. (4) Conclusions: H. pylori infection plays the most significant role in GDP, more than NSAIDs, surgery, chemotherapy, or transplantation. Treatment of H. pylori infection is essential to decrease the prevalence of GDP and speed up its recovery. However, urgent cases require immediate intervention, such as laparoscopic or open surgery.
Usefulness Assessment of Automated Strabismus Angle Measurements Using Innovative Strabiscan Device
Authors: Grudzińska Ewa , Durajczyk Magdalena , Grudziński Marek , Marchewka Łukasz , Modrzejewska Monika
Published: February 2024

Background: The variability of the obtained results of manual tests assessing the angle of strabismus depends on the experience, skills, and training of the examiner. The authors hope that this new measuring device will provide a more sensitive and repeatable method for detecting small strabismus angles compared to the gold standard—PCT. The purpose of this article is to present an innovative strabismus angle demonstration device, called Strabiscan, to provide automated measurements of eye deviation and to compare the obtained results of these measurements to the traditional manual method. Methods: For patients with manifest strabismic disease (n = 30) and a group of healthy subjects (n = 30), a detailed history was taken and routine ophthalmologic examinations were performed, including best-corrected distance visual acuity, assessment of refractive error using an autorefractometer after cycloplegia, biomicroscopic evaluation of the anterior segment of the eye and evaluation of the eye fundus by indirect ophthalmoscopy. Subsequently, each patient and healthy subject was subjected to a prismatic cover–uncover test using a manual method, after which the presence of strabismus was detected and its angle assessed using a Strabiscan demonstration device. Results: In the control group using the Strabiscan demonstration device, small-angle latent strabismus ≤ 3DP was diagnosed in 83% of patients, while >3DP was found in 13%. In contrast, using the prismatic cover–uncover test, latent strabismus ≤ 3DP was diagnosed in only 13% of patients, and latent strabismus with an angle > 3DP was found in 13% of patients. No statistically significant differences were noted in the measurements of strabismus angles made by the different methods. Conclusions: The Strabiscan demonstration device allows quick and accurate assessment of the strabismus angle. Compared to the prismatic cover–uncover test, it has a higher sensitivity for detecting low-angle latent strabismus. Measurements with the Strabiscan do not require the presence of additional assistants for the test.
Long-Term Follow-Up after Iliosacral Screw Fixation of Unstable Pelvic Ring Fractures
Authors: Stolberg-Stolberg Josef , Lodde Moritz F. , Seiß Dominik , Köppe Jeanette , Hartensuer René , Raschke Michael J. , Riesenbeck Oliver
Published: February 2024

(1) Background: High-energy injuries of the pelvic ring are rare. The wide application of iliosacral screw fixation of the posterior pelvic ring is relatively new. The aim of the present study was to evaluate the long-term quality of life. (2) Methods: All patients treated with an iliosacral screw for a posterior pelvic ring stabilization after high-energy trauma at a level 1 trauma center between 2005 and 2015 were included. Pelvic ring injuries were classified according to the Tile classification adapted by AO/ASIF. The clinical evaluation included the patient-oriented questionnaires surveys of the Majeed Score, Iowa Pelvic Score (IPS), Work Ability Index (WAI), SF-36, EQ5D-5L. (3) Results: A total of 84 patients were included with a median follow-up of 130.1 months (IQR 95.0–162.0 months). The median ISS was 22.5 (IQR 16.0–29.0), mean Majeed Score 83.32 (SD ± 19.26), IPS 77.88 (SD ± 13.96), WAI 32.71 (SD ± 11.31), SF-36 PF 71.25 (SD ± 29.61) and EQ5D-5L 0.83 (SD ± 0.21). There was a notably difference between uni- and bilateral pelvic fractures (p = 0.033) as well as a correlation with the ISS (p = 0.043) with inferior functional outcome measured by IPS. (4) Conclusions: Long-term follow-up of iliosacral screw fixation of unstable pelvic ring fractures showed a good quality of life and functional outcome with equal EQ5D-5L results and inferior SF-36 physical functioning compared to the German population.
Alpha-1 Antitrypsin PI M Heterozygotes with Rare Variants: Do They Need a Clinical and Functional Follow-Up?
Authors: Annunziata Anna , Fiorentino Giuseppe , Balestrino Marco , Rega Roberto , Spinelli Sara , Atripaldi Lidia , Sola Alessio , Massaro Federica , Calabrese Cecilia
Published: February 2024

(1) Background: Few data are available on the risk of airway dysfunction in protease inhibitor (PI*) M heterozygotes carrying rare null or deficient allelic variants of the gene SERPINA-1 (PI*MR). (2) Methods: In this observational study, in a cohort of PI*MR heterozygotes, we evaluated respiratory functional parameters at baseline and at one-year follow-up. Moreover, we compared such parameters with those of the PI*MZ and PI*MS patients. (3) Results: A total of 60 patients were recruited; 35 PI*MR, 11 PI*MZ and 14 PI*MS. At the annual follow-up, the PI*MR and PI*MZ patients demonstrated a significantly higher FEV1 decline than the PI*MS group (p = 0.04 and p = 0.018, respectively). The PI*MR patients showed a significant increase in DLCO annual decline in comparison with the PI*MS group (p = 0.02). At baseline, the PI*MR smoking patients, compared with nonsmokers, showed statistically significant lower values of FEV1, FEV1/FVC and DLCO (p = 0.0004, p < 0.0001, p = 0.007, respectively) and, at the one-year follow-up, they displayed a significantly higher FEV1 and DLCO decline (p = 0.0022, p = 0.011, respectively). PI*MR heterozygotes with COPD showed a significantly higher FEV1, FEV1/FVC and DLCO annual decline in comparison with healthy PI*MR (p = 0.0083, p = 0.043, p = 0.041). (4) Conclusions: These results suggest that PI*MR heterozygotes, particularly smokers with COPD, have a greater annual decline in respiratory functional parameters and need to be monitored.
A Mobile App for Detecting Potato Crop Diseases
Authors: Pineda Medina Dunia , Miranda Cabrera Ileana , de la Cruz Rolisbel Alfonso , Guerra Arzuaga Lizandra , Cuello Portal Sandra , Bianchini Monica
Published: February 2024

Artificial intelligence techniques are now widely used in various agricultural applications, including the detection of devastating diseases such as late blight (Phytophthora infestans) and early blight (Alternaria solani) affecting potato (Solanum tuberorsum L.) crops. In this paper, we present a mobile application for detecting potato crop diseases based on deep neural networks. The images were taken from the PlantVillage dataset with a batch of 1000 images for each of the three identified classes (healthy, early blight-diseased, late blight-diseased). An exploratory analysis of the architectures used for early and late blight diagnosis in potatoes was performed, achieving an accuracy of 98.7%, with MobileNetv2. Based on the results obtained, an offline mobile application was developed, supported on devices with Android 4.1 or later, also featuring an information section on the 27 diseases affecting potato crops and a gallery of symptoms. For future work, segmentation techniques will be used to highlight the damaged region in the potato leaf by evaluating its extent and possibly identifying different types of diseases affecting the same plant.
Effect of Liquid Miscibility Gap on Defects in Inconel 625–GRCop42 Joints through Analysis of Gradient Composition Microstructure
Authors: Preis Jakub , Xu Donghua , Paul Brian K. , Eschbach Peter A. , Pasebani Somayeh
Published: February 2024

Joining of Cu-based dispersion-strengthened alloys to Ni-based superalloys has garnered increased attention for liquid rocket engine applications due to the high thermal conductivity of Cu-based alloys and high temperature tensile strength of Ni-based superalloys. However, such joints can suffer from cracking when joined via liquid state processes, leading to part failure. In this work, compositions of 15–95 wt.% GRCop42 are alloyed with Inconel 625 and characterized to better understand the root cause of cracking. Results indicate a lack of miscibility between Cu-deprived and Cu-rich liquids in compositions corresponding to 30–95 wt.% GRCop42. Two distinct morphologies are observed and explained by use of CALPHAD; Cu-deprived dendrites with Cu-rich interdendritic zones at 30–50 wt.% GRCop42 and Cu-deprived spheres surrounded by a Cu-rich matrix at 60–95 wt.% GRCop42. Phase analysis reveals brittle intermetallic phases precipitate in the 60–95 wt.% GRCop42 Cu-deprived region. Three cracking mechanisms are proposed herein that provide guidance on the avoidance of defects Ni-based superalloy to Cu-based dispersion strengthened alloy joints.
Methodology for Predicting Maritime Traffic Ship Emissions Using Automatic Identification System Data
Authors: Ribeiro da Silva João N. , Santos Tiago A. , Teixeira Angelo P.
Published: February 2024

This paper develops a methodology to estimate ship emissions using Automatic Identification System data (AIS). The methodology includes methods for AIS message decoding and ship emission estimation based on the ship’s technical and operational characteristics. A novel approach for ship type identification based on the visited port terminal is described. The methodology is implemented in a computational tool, SEA (Ship Emission Assessment). First, the accuracy of the method for ship type identification is assessed and then the methodology is validated by comparing its predictions with those of two other methodologies. The tool is applied to three case studies using AIS data of maritime traffic along the Portuguese coast and in the port of Lisbon for one month. The first case study compares the estimated emissions of a ferry and a cruise ship, with the ferry emitting much less than the cruise ship. The second case study estimates the geographical distribution of emissions in the port of Lisbon, with terminals corresponding to areas with a heavier concentration of exhaust emissions. The third case study focuses on the emissions from a container ship sailing along the continental coast of Portugal, differing considerably from port traffic since it operates exclusively in cruising mode.
Navigating Safety and Compliance in High-Voltage Shore Connection Systems: A Comprehensive Exploration of IEC/IEEE 80005-1 Standards and the Guidelines of Ship Classification Societies
Authors: Hsu Shih-Hsien , Tzu Fu-Ming , Chen Yi-Dong , Huang Chun-Wei
Published: February 2024

This paper addresses the growing concern over air pollutant emissions (NOx, SOx, PM, CO2) from ocean-going vessels in harbor areas and the role of Onshore Power Supply (OPS) systems in mitigating these emissions during vessel berthing. However, the slow progress in global shore power facilities is attributed to safety- and specification-related concerns. Our study conducts a comprehensive analysis, comparing international shore power regulations, with a specific focus on the IEC/IEEE 80005-1 standard and guidelines from various ship classification societies. We introduce checklists, scoring tables, and spider diagrams to evaluate the regulatory content, highlighting the strengths and weaknesses of each approach. Furthermore, this paper emphasizes the significance of a well-defined operational process for high-voltage shore connection (HVSC) to ensure the safety of OPS operations. We present process diagrams for key operational stages, based on IEC/IEEE 80005-1 specifications and evaluation criteria. The ultimate goal of this research is to drive the global adoption of shore power and foster the establishment of shore power facilities worldwide. This aligns with the broader environmental protection objectives of achieving cleaner ports and reducing emissions for a sustainable future.
Navigating the Future: Developing Smart Fairways for Enhanced Maritime Safety and Efficiency
Authors: Heikkilä Marikka , Himmanen Heidi , Soininen Olli , Sonninen Sanna , Heikkilä Jukka
Published: February 2024

The maritime industry is rapidly evolving with digital technologies, aiming to enhance efficiency, safety, and sustainability. Recent interest has focused on autonomous vessels and the digitalization of ports, yet fairway development has lagged behind. To effectively support the growing digital and autonomous marine traffic, it is essential that fairways are also upgraded and modernized. Addressing this need, this study examines key elements of Smart Fairways, with a particular focus on Finland’s maritime infrastructure. This research contributes to the development of the Smart Fairways concept by identifying five foundational and ten advanced Smart Fairway service elements. The main finding highlights the foundational role of communication systems in the development of more advanced Smart Fairway services such as Enhanced Vessel Traffic Service, Port just-in-time Service, Remote Pilotage, and Digital Twin of the Physical Fairway.
Methodological Aspects of Assessing the Thermal Load on Diesel Engine Parts for Operation on Alternative Fuel
Authors: Lebedevas Sergejus , Milašius Edmonas
Published: February 2024

The decarbonization of maritime transport has become a crucial strategy for the adoption of renewable low-carbon fuels (LCFs) (MARPOL 73/78 (Annex VI) and COM (2021) 562-final 2021/0210 (COD)). In 2018, 98% of operated marine diesel engines ran on fossil fuels. The application of LCFs, according to expert assessments (DNV GL), is considered the most effective solution to the decarbonization challenge in the maritime sector. This publication presents methodological proposals related to assessing the reliability of operational diesel engines when transitioning to low- carbon fuels. The proposed methodology implements an interconnected assessment of the combustion cycle parameters and the limiting reliability factors of the thermal load on the most critical components of the cylinder–piston group. The optimization of the combustion cycle parameters for the indicators of energy and the environmental efficiency of low-carbon fuel applications was combined with the evaluation and assurance of permissible values of the thermal load factors on the components to determine the overall reliability of the engine. Thus, the possibility of overload and engine failures was already eliminated at the retrofitting design stage. The algorithm for the parametric analysis was grounded in the practical application of established α-formulae for the heat exchange intensity, such as those of the Central Diesel Engine Research Institute and G. Woschni. This approach was combined with modeling the combustion cycle parameters by employing statistical or single-zone mathematical models such as IMPULS and AVL BOOST. The α-formulae for low carbon fuels were verified based on the thermal balance data. The structure of the solutions for the effectiveness of the practical implementation of this methodology was comprehensively oriented towards diesel “families”, as exemplified by the models 15/15 (pmi = 1.2, 1.4, and 1.6 MPa). The long-term goal of the obtained results in the structure of comprehensive decarbonization research was to assess the factors of the reliable operation of characteristic groups of medium-speed (350–1000 rpm) and high-speed (1000–2100 rpm) marine engines for reliable operation in the medium term on ammonia.
Efficacy of Filter Trocar for Clear Visualization during Laparoscopic Cholecystectomy: A Prospective Randomized Controlled Trial
Authors: Chae Ho-Chang , Kim Beom-Jin , Choi Yoo Shin , Suh Suk-Won , Lee Seung Eun
Published: February 2024

Filter trocar designed to eliminate harmful smoke is also regarded as effective for improving surgical visualization. The aim of this study is to evaluate the efficacy of filter trocar in maintaining clear operative view. From 2019 to 2020, 100 patients underwent laparoscopic cholecystectomy and they were randomized to either the control or filter group. The primary end point was a laparoscopic operative view score (1, clear; 2, slightly blurry; 3, completely blurry) during gallbladder dissection from the liver bed when dissection was started (LV1), when dissection was half completed (LV2) and when dissection was completed (LV3). Between the control and filter groups, there were no significant differences in mean LV1 (1.44 vs. 1.40, p = 0.234) and LV3 (1.86 vs. 2.01, p = 0.880). There was no significant difference in the mean duration of suction after dissection (3.82 s vs. 3.67 s, p = 0.097) and the mean number of laparoscope removals from inside to outside the body to clean during gallbladder dissection from the liver bed (0.55 vs. 0.22, p = 0.963) or the mean amount of time required to dissect the gallbladder from the liver bed (221.58 s vs. 177.09 s, p = 0.253). The study demonstrated that filter trocar is not as effective as expected in the maintenance of clear operative view. Further study is needed to develop devices to improve clear surgical visualization.
The Impact of the Mechanism for Aligning Horizontal Fiscal Imbalances on the Stability of the Financial System
Authors: Yaroshevych Nataliia , Kondrat Iryna , Kalaitan Tetyana
Published: February 2024

The growth of state transfers to offset disparities in regional development affects the stability of the country’s financial system. This article delves into this outcome, empirically analyzing whether the transfer system for horizontal fiscal alignment leads to decreased financial system stability through increased borrowing at municipal and national levels. To test this hypothesis, we employ a quasi-experimental analysis strategy, examining potential scenarios of configuring transfers to Ukrainian municipalities for addressing horizontal fiscal imbalance. Across various transfer calculation scenarios involving changes in the calculation period, the number of budgets in consideration, and the alignment subject, we find that a suboptimal system of horizontal fiscal alignment, transferring funds from financially secure municipalities to insecure ones, leads to a rise in the public finance debt, subsequently decreasing financial system stability. Additionally, we discover that the current mechanism in Ukraine for horizontal fiscal alignment, designed to mitigate inequalities in socio-economic development among communities and regions, paradoxically exacerbates these disparities, artificially inflates indicators of decentralization reform success, and undermines public finance stability.
Morphology and Distribution of Primary Carbides in Forged Cr-Ni-Mo-V/Nb Steel
Authors: Li Yang , Xu Tingting , Cao Xin , Wu Zhipeng , Fan Jianwen , Hu Chundong , Dong Han
Published: February 2024

This study aims to investigate in situ the three-dimensional (3D) morphology and distribution of primary carbides (PCs) in electro-slag remelting (ESR) forged 30Cr3Ni3Mo2V steel. A facile non-aqueous electrolytic etching method was applied to prepare 3D PCs on the matrix. The morphology, composition, and element concentrations of PCs were characterized using a combination of optical microscopy (OM), scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS), and electron back-scattered diffusion (EBSD). The precipitation, type, and composition of PCs in the same steel were also simulated using Thermo-Calc software Version 2015a. The results indicate that PC is rich in Nb, which is a potential heterogeneous nucleating agent. Both the size and number of PCs increase from the edge to the center of the ingot. The large-sized PCs present three dominant types of morphology, which vary in different regions, i.e., a bulky type dominates in the edge region, a lamellar type dominates in the middle region, and a stripy type dominates in the core region. The results of EBSD analysis show that the orientation of PCs with different morphologies is different and that more nanosized V-rich type carbides are precipitated on the matrix. The thermodynamic calculations show that MC precipitates from the liquid phase when the solid phase fraction is greater than 0.985 and that the MC-type carbides are rich in Nb, which agrees well with the experimental results.
Mo-Doped LSCF as a Novel Coke-Resistant Anode for Biofuel-Fed SOFC
Authors: Javan Kimia Y. , Lo Faro Massimiliano , Vecino-Mantilla Sebastian , Sglavo Vincenzo M.
Published: February 2024

Climate change and damage to the environment, as well as the limitations of fossil fuels, have pushed governments to explore infinite renewable energy options such as biofuels. Solid Oxide Fuel Cell (SOFC) is a sustainable energy device that transforms biofuels into power and heat. It is now being researched to function at intermediate temperatures (600–700 °C) in order to prevent material deterioration and improve system life span. However, one of the major disadvantages of reducing the temperature is that carbon deposition impairs the electrochemical performance of the cell with a Ni-YSZ traditional anode. Here, molybdenum was doped into La0.6Sr0.4Co0.2Fe0.8O3−δ (LSCFMo) as an innovative anode material with higher coke resistance and better phase stability under reducing conditions. X-ray diffraction (XRD) analysis showed increasing phase stability by increasing the Mo dopant. Electrochemical measurements proved that the LSCFMo anode is an active catalyst towards the methanol oxidation even at low temperatures as 600 °C, with an open circuit voltage (OCV) of 0.55 V, while GDC10 (Ga0.9Ce0.1O1.95) is used as the electrolyte. As an insightful result, no trace of any carbon deposition was found on the anode side after the tests. The combination of phase composition, morphological, and electrochemical studies demonstrate that LSCFMo is a suitable anode material for SOFCs fed by biofuels.
Investigating the Behavior of Thin-Film Formation over Time as a Function of Precursor Concentration and Gas Residence Time in Nitrogen Dielectric Barrier Discharge
Authors: Fotouhiardakani Faegheh , Destrieux Alex , Profili Jacopo , Laurent Morgane , Ravichandran Sethumadhavan , Dorairaju Gowri , Laroche Gaetan
Published: February 2024

This study aims to establish a correlation between the fragmentation process and the growth mechanisms of a coating deposited on a fluoropolymer. Deposition was carried out using dielectric barrier discharge at atmospheric pressure, employing an oxygen-containing organic precursor in a nitrogen environment. The findings reveal that the impact of precursor concentration on the formation of specific functionalities is more significant than the influence of treatment time. The X-ray photoelectron spectroscopy (XPS) results obtained indicate a reduction in the N/O ratio on the coating’s surface as the precursor concentration in the discharge increases. Fourier transform infrared spectroscopy (FTIR) analysis, conducted in the spectral range of 1500 cm−1 to 1800 cm−1, confirmed the connection between the chemical properties of plasma-deposited thin films and the concentration of organic precursors in the discharge. Furthermore, the emergence of nitrile moieties (C≡N) in the FTIR spectrum at 2160 cm−1 was noted under specific experimental conditions.
Microstructures and Corrosion Properties of Wire Arc Additive Manufactured Copper–Nickel Alloys
Authors: Song Jie , Jimenez Xavier A. , To Albert C. , Fu Yao
Published: February 2024

The 70/30 copper–nickel alloy is used mainly in critical parts with more demanding conditions in marine settings. There is a need for innovative methods that offer fast production and cost-effectiveness in order to supplement current copper–nickel alloy manufacturing processes. In this study, we employ wire arc additive manufacturing (WAAM) to fabricate the 70/30 copper–nickel alloy. The as-built microstructure is characterized by columnar grains with prominent dendrites and chemical segregation in the inter-dendritic area. The aspect ratio of the columnar grain increases with increasing travel speed (TS) at the same wire feed speed (WFS). This is in contrast with the equiaxed grain structure, with a more random orientation, of the conventional sample. The sample built with a WFS of 8 m/min, TS of 1000 mm/min, and a track distance of 3.85 mm exhibits superior corrosion properties in the 3.5 wt% NaCl solution when compared with the conventional sample, as evidenced by a higher film resistance and breakdown potential, along with a lower passive current density of the WAAM sample. The corrosion morphology reveals the critical roles played by the nickel element that is unevenly distributed between the dendrite core and inter-dendritic area.
Structural Stability and Disorder Level of Moderately Reduced Paper-like Graphene Oxide Investigated with Micro-Raman Analysis
Authors: Janulewicz Karol Adam , Fok Tomasz , Bartosewicz Bartosz , Bartnik Andrzej , Fiedorowicz Henryk , Wachulak Przemysław
Published: February 2024

This paper discusses the results of the micro-Raman analysis performed on paper-like graphene oxide (GO) samples consisting of many functionalised graphene layers and annealed at moderate temperatures (≤500 °C) under vacuum conditions (p ≃ 10−4 mbar). The analysis of the standalone samples revealed that the obtained material is characterised by a noticeable disorder level but still stays below the commonly accepted threshold of high or total disorder. GO formed in a simple way showed two spectral bands above 1650 cm−1 recorded very rarely or not at all and their origin has been discussed in detail. The results also confirmed the metastable character of multilayer GO after the annealing process at moderate temperatures as the C/O ratio was kept between 2 and 3 and the spectral features were stable within the annealing temperature range.
bmp-2 Gene-Transferred Skeletal Muscles with Needle-Type Electrodes as Efficient and Reliable Biomaterials for Bone Regeneration
Authors: Kawai Mariko Yamamoto , Yoshida Takeshi , Kato Tomoki , Watanabe Takuma , Kashiwagi Marina , Yamanaka Shigeki , Yamamoto Hiromitsu , Nagahiro Shigeki , Iwamoto Tsutomu , Masud Khan , Aoki Kazuhiro , Ohura Kiyoshi , Nakao Kazumasa
Published: February 2024

Background: Bone morphogenetic protein-2 (bmp-2) has a high potential to induce bone tissue formation in skeletal muscles. We developed a bone induction system in skeletal muscles using the bmp-2 gene through in vivo electroporation. Natural bone tissues with skeletal muscles can be considered potential candidates for biomaterials. However, our previous system using plate-type electrodes did not achieve a 100% success rate in inducing bone tissues in skeletal muscles. In this study, we aimed to enhance the efficiency of bone tissue formation in skeletal muscles by using a non-viral bmp-2 gene expression plasmid vector (pCAGGS-bmp-2) and needle-type electrodes. Methods: We injected the bmp-2 gene with pCAGGS-bmp-2 into the skeletal muscles of rats’ legs and immediately placed needle-type electrodes there. Skeletal tissues were then observed on the 21st day after gene transfer using soft X-ray and histological analyses. Results: The use of needle-type electrodes resulted in a 100% success rate in inducing bone tissues in skeletal muscles. In contrast, the plate-type electrodes only exhibited a 33% success rate. Thus, needle-type electrodes can be more efficient and reliable for transferring the bmp-2 gene to skeletal muscles, making them potential biomaterials for repairing bone defects.
Production of Mn-Ga Magnets
Authors: Saito Tetsuji , Tanaka Masahiro , Nishio-Hamane Daisuke
Published: February 2024

Mn-based magnets are known to be a candidate for use as rare-earth-free magnets. In this study, Mn-Ga bulk magnets were successfully produced by hot pressing using the spark plasma sintering method on Mn-Ga powder prepared from rapidly solidified Mn-Ga melt-spun ribbons. When consolidated at 773 K and 873 K, the Mn-Ga bulk magnets had fine grains and exhibited high coercivity values. The origin of the high coercivity of the Mn-Ga bulk magnets was the existence of the D022 phase. The Mn-Ga bulk magnet consolidated at 873 K exhibited the highest coercivity of 6.40 kOe.
Facile Synthesis of Nitrogen-Doped Graphene Quantum Dots/MnCO3/ZnMn2O4 on Ni Foam Composites for High-Performance Supercapacitor Electrodes
Authors: Liu Di , Kim Soeun , Choi Won Mook
Published: February 2024

This study reports the facile synthesis of rationally designed composite materials consisting of nitrogen-doped graphene quantum dots (N-GQDs) and MnCO3/ZnMn2O4 (N/MC/ZM) on Ni foam using a simple hydrothermal method to produce high-performance supercapacitor applications. The N/MC/ZM composite was uniformly synthesized on a Ni foam surface with the hierarchical structure of microparticles and nanosheets, and the uniform deposition of N-GQDs on a MC/ZM surface was observed. The incorporation of N-GQDs with MC/ZM provides good conductivity, charge transfer, and electrolyte diffusion for a better electrochemical performance. The N/MC/ZM composite electrode delivered a high specific capacitance of 960.6 F·g−1 at 1 A·g−1, low internal resistance, and remarkable cycling stability over 10,000 charge–discharge cycles. Additionally, an all-flexible solid-state asymmetric supercapacitor (ASC) device was fabricated using the N/MC/ZM composite electrode. The fabricated ASC device produced a maximum energy density of 58.4 Wh·kg−1 at a power density of 800 W·kg−1 and showed a stable capacitive performance while being bent, with good mechanical stability. These results provide a promising and effective strategy for developing supercapacitor electrodes with a high areal capacitance and high energy density.
Weight Minimization of Type 2 Composite Pressure Vessel for Fuel Cell Electric Vehicles Considering Mechanical Safety with Kriging Metamodel
Authors: An Jaewook , Lee Hamin , Kim Chang-Wan
Published: February 2024

In recent years, increased sales of fuel cell electric vehicles (FCEVs) have required composite overwrapped pressure vessel (COPV) designs to be lightweight and allow safe high-pressure hydrogen storage. In this study, we propose the weight minimization of Type 2 COPVs for FCEVs considering mechanical safety. Steel liner thickness, ply thickness, ply orientation, and the number of plies were set as design variables, and weight minimization was performed. For the constraints of optimization, the Tsai–Wu failure index of the composite layer and von Mises stress of the steel liner are considered. The design of experiments (DoE) was conducted to generate kriging model and perform sensitivity analysis. The optimized design of Type 2 COPVs was determined by satisfying all constraints, with significant weight reduction and preserved mechanical safety of the structure.
An Exergoeconomic Evaluation of an Innovative Polygeneration System Using a Solar-Driven Rankine Cycle Integrated with the Al-Qayyara Gas Turbine Power Plant and the Absorption Refrigeration Cycle
Authors: Talal Wadah , Akroot Abdulrazzak
Published: February 2024

This study aims to develop, evaluate, and improve a polygeneration system that combines solar and Brayton cycle technologies and focuses on the sequential integration of heat. In this configuration, the exhaust gases from the Al-Qayyarah gas turbine power plant and the parabolic trough collector (PTC) array generate steam through a high recovery steam generation process. An absorption refrigeration system also supplies the Brayton circuit with low-temperature air. This process is evaluated from a 3E perspective, which includes exergy, energy, and exergoeconomic analyses for two different configurations. These configurations are integrated solar combined cycle (ISCC) with and without absorption systems (ISCC and ISCC-ARC). In addition, a comprehensive analysis was carried out to assess the impact of critical factors on the output generated, the unit cost of the products, and the exergy and energy efficiency for each configuration. The results revealed that the power produced by the ISCC-ARC and ISCC systems is 580.6 MW and 547.4 MW, respectively. Accordingly, the total energy and exergy efficiencies for the ISCC-ARC are 51.15% and 49.4%, respectively, while for the ISCC system, they are 50.89% and 49.14%, respectively. According to the results, the total specific costs for the ISCC-ARC system increased from 69.09 $/MWh in June to 79.05 $/MWh in December. ISCC’s total specific costs also fluctuate throughout the year, from 72.56 $/MWh in June to 78.73 $/MWh in December.
Arc Detection of Photovoltaic DC Faults Based on Mathematical Morphology
Authors: Song Lei , Lu Chunguang , Li Chen , Xu Yongjin , Zhang Jiangming , Liu Lin , Liu Wei , Wang Xianbo
Published: February 2024

With the rapid growth of the photovoltaic industry, fire incidents in photovoltaic systems are becoming increasingly concerning as they pose a serious threat to their normal operation. Research findings indicate that direct current (DC) fault arcs are the primary cause of these fires. DC arcs are characterized by high temperature, intense heat, and short duration, and they lack zero crossing or periodicity features. Detecting DC fault arcs in intricate photovoltaic systems is challenging. Hence, researching DC fault arcs in photovoltaic systems is of crucial significance. This paper discusses the application of mathematical morphology for detecting DC fault arcs. The system utilizes a multi-stage mathematical morphology filter, and experimental results have shown its effective extraction of fault arc features. Subsequently, we propose a method for detecting DC fault arcs in photovoltaic systems using a cyclic neural network, which is well-suited for time series processing tasks. By combining multiple features extracted from experiments, we trained the neural network and achieved high accuracy. This experiment demonstrates that our recurrent neural network (RNN) based scheme for DC fault arc recognition has significant reference value and implications for future research. The ROC curve on the test set approaches 1 from the initial state, and the accuracy on the test set remains at 98.24%, indicating the strong robustness of the proposed model.
Design and Development of a Brake Test Bench for Formula SAE Race Cars
Authors: Vecchiato Luca , Negri Matteo , Picci Giulio , Viale Luca , Zaltron Giulio , Giacometti Stefano , Meneghetti Giovanni
Published: February 2024

The optimization of the brake systems is crucial for vehicle performance and safety of Formula SAE (FSAE) race cars. This study introduces a specialized brake test bench designed to enhance the understanding and testing of these systems. The bench integrates a rotating mechanical system mounting a brake disc-caliper group, which is driven by an electric motor, a pneumatic brake pedal assembly to simulate real braking conditions, and a comprehensive array of sensors that facilitate the measurement of critical parameters, such as rotation speed, braking torque, oil pressure, and disc temperature. Its structure, sensor integration, and control electronics are fully described, demonstrating the capability to replicate on-track scenarios in a controlled environment. The results underscore the utility of the bench in providing precise and consistent testing conditions essential for analyzing the efficiency, durability, and safety of the braking systems of FSAE race cars.
Designing an Industrial Product Service System for Robot-Driven Sanding Processing Line: A Reinforcement Learning Based Approach
Authors: Yang Yuqian , Chen Xin , Yang Maolin , Guo Wei , Jiang Pingyu
Published: February 2024

The Industrial Product Service System (IPS2) is considered a sustainable and efficient business model, which has been gradually popularized in manufacturing fields since it can reduce costs and satisfy customization. However, a comprehensive design method for IPS2 is absent, particularly in terms of requirement perception, resource allocation, and service activity arrangement of specific industrial fields. Meanwhile, the planning and scheduling of multiple parallel service activities throughout the delivery of IPS2 are also in urgent need of resolution. This paper proposes a method containing service order design, service resource configuration, and service flow modeling to establish an IPS2 for robot-driven sanding processing lines. In addition, we adopt the modified Deep Q-network (DQN) to realize a scheduling scheme aimed at minimizing the total tardiness of multiple parallel service flows. Finally, our industrial case study validates the effectiveness of our methods for IPS2 design, demonstrating that the modified deep reinforcement learning algorithm reliably generates robust scheduling schemes.
Machine Learning Predictive Analysis of Liquefaction Resistance for Sandy Soils Enhanced by Chemical Injection
Authors: Cong Yuxin , Motohashi Toshiyuki , Nakao Koki , Inazumi Shinya
Published: February 2024

The objective of this study was to investigate the liquefaction resistance of chemically improved sandy soils in a straightforward and accurate manner. Using only the existing experimental databases and artificial intelligence, the goal was to predict the experimental results as supporting information before performing the physical experiments. Emphasis was placed on the significance of data from 20 loading cycles of cyclic undrained triaxial tests to determine the liquefaction resistance and the contribution of each explanatory variable. Different combinations of explanatory variables were considered. Regarding the predictive model, it was observed that a case with the liquefaction resistance ratio as the dependent variable and other parameters as explanatory variables yielded favorable results. In terms of exploring combinations of explanatory variables, it was found advantageous to include all the variables, as doing so consistently resulted in a high coefficient of determination. The inclusion of the liquefaction resistance ratio in the training data was found to improve the predictive accuracy. In addition, the results obtained when using a linear model for the prediction suggested the potential to accurately predict the liquefaction resistance using historical data.
On K-Banhatti, Revan Indices and Entropy Measures of MgO(111) Nanosheets via Linear Regression
Authors: Almalki Norah , Tabassum Hafsah
Published: February 2024

The structure and topology of chemical compounds can be determined using chemical graph theory. Using topological indices, we may uncover much about connectivity, complexity, and other important aspects of molecules. Numerous research investigations have been conducted on the K-Banhatti indices and entropy measurements in various fields, including the study of natural polymers, nanotubes, and catalysts. At the same time, the Shannon entropy of a graph is widely used in network science. It is employed in evaluating several networks, including social networks, neural networks, and transportation systems. The Shannon entropy enables the analysis of a network’s topology and structure, facilitating the identification of significant nodes or structures that substantially impact network operation and stability. In the past decade, there has been a considerable focus on investigating a range of nanostructures, such as nanosheets and nanoparticles, in both experimental and theoretical domains. As a very effective catalyst and inert substrate, the MgO nanostructure has received a lot of interest. The primary objective of this research is to study different indices and employ them to look at entropy measures of magnesium oxide(111) nanosheets over a wide range of p values, including p=1,2,3,…,j. Additionally, we conducted a linear regression analysis to establish the correlation between indices and entropies.
Advancing Semantic Classification: A Comprehensive Examination of Machine Learning Techniques in Analyzing Russian-Language Patient Reviews
Authors: Kalabikhina Irina , Moshkin Vadim , Kolotusha Anton , Kashin Maksim , Klimenko German , Kazbekova Zarina
Published: February 2024

Currently, direct surveys are used less and less to assess satisfaction with the quality of user services. One of the most effective methods to solve this problem is to extract user attitudes from social media texts using natural language text mining. This approach helps to obtain more objective results by increasing the representativeness and independence of the sample of service consumers being studied. The purpose of this article is to improve existing methods and test a method for classifying Russian-language text reviews of patients about the work of medical institutions and doctors, extracted from social media resources. The authors developed a hybrid method for classifying text reviews about the work of medical institutions and tested machine learning methods using various neural network architectures (GRU, LSTM, CNN) to achieve this goal. More than 60,000 reviews posted by patients on the two most popular doctor review sites in Russia were analysed. Main results: (1) the developed classification algorithm is highly efficient—the best result was shown by the GRU-based architecture (val_accuracy = 0.9271); (2) the application of the method of searching for named entities to text messages after their division made it possible to increase the classification efficiency for each of the classifiers based on the use of artificial neural networks. This study has scientific novelty and practical significance in the field of social and demographic research. To improve the quality of classification, in the future, it is planned to expand the semantic division of the review by object of appeal and sentiment and take into account the resulting fragments separately from each other.
Leveraging Chain-of-Thought to Enhance Stance Detection with Prompt-Tuning
Authors: Ding Daijun , Fu Xianghua , Peng Xiaojiang , Fan Xiaomao , Huang Hu , Zhang Bowen
Published: February 2024

Investigating public attitudes towards social media is crucial for opinion mining systems to gain valuable insights. Stance detection, which aims to discern the attitude expressed in an opinionated text towards a specific target, is a fundamental task in opinion mining. Conventional approaches mainly focus on sentence-level classification techniques. Recent research has shown that the integration of background knowledge can significantly improve stance detection performance. Despite the significant improvement achieved by knowledge-enhanced methods, applying these techniques in real-world scenarios remains challenging for several reasons. Firstly, existing methods often require the use of complex attention mechanisms to filter out noise and extract relevant background knowledge, which involves significant annotation efforts. Secondly, knowledge fusion mechanisms typically rely on fine-tuning, which can introduce a gap between the pre-training phase of pre-trained language models (PLMs) and the downstream stance detection tasks, leading to the poor prediction accuracy of the PLMs. To address these limitations, we propose a novel prompt-based stance detection method that leverages the knowledge acquired using the chain-of-thought method, which we refer to as PSDCOT. The proposed approach consists of two stages. The first stage is knowledge extraction, where instruction questions are constructed to elicit background knowledge from a VLPLM. The second stage is the multi-prompt learning network (M-PLN) for knowledge fusion, which learns model performance based on the background knowledge and the prompt learning framework. We evaluated the performance of PSDCOT on publicly available benchmark datasets to assess its effectiveness in improving stance detection performance. The results demonstrate that the proposed method achieves state-of-the-art results in in-domain, cross-target, and zero-shot learning settings.
Evolution Equations with Liouville Derivative on R without Initial Conditions
Authors: Fedorov Vladimir E. , Skripka Nadezhda M.
Published: February 2024

New classes of evolution differential equations with the Liouville derivative in Banach spaces are studied. Equations are considered on the whole real line and are not endowed by the initial conditions. Using the methods of the Fourier transform theory, we prove the unique solvability in the sense of classical solutions for the equation solved with respect to the Liouville fractional derivative with a bounded operator at the unknown function. This allows us to obtain the analogous result for the equation with a linear degenerate operator at the fractional derivative and with a spectrally bounded pair of operators. Abstract results are applied to obtain new results on the unique solvability of systems of ordinary differential equations, boundary problems to partial differential equations, and systems of equations.
Mathematical Modelling of Traction Equipment Parameters of Electric Cargo Trucks
Authors: Malozyomov Boris V. , Martyushev Nikita V. , Sorokova Svetlana N. , Efremenkov Egor A. , Valuev Denis V. , Qi Mengxu
Published: February 2024

Electric vehicles are one of the most innovative and promising areas of the automotive industry. The efficiency of traction equipment is an important factor in the operation of an electric vehicle. In electric vehicles, the energy stored in the battery is converted into mechanical energy to drive the vehicle. The higher the efficiency of the battery, the less energy is lost in the conversion process, which improves the overall energy efficiency of the electric vehicle. Determining the performance characteristics of the traction battery of an electric vehicle plays an important role in the selection of the vehicle and its future operation. Using mathematical modelling, it is shown that battery capacity, charging rate, durability and efficiency are essential to ensure the comfortable and efficient operation of an electric vehicle throughout its lifetime. A mathematical model of an electric truck including a traction battery has been developed. It is shown that, with the help of the developed mathematical model, it is possible to calculate the load parameters of the battery in standardised driving cycles. The data verification is carried out by comparing the data obtained during standardised driving with the results of mathematical modelling.