bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Heat Treatment Temperature on the Microstructure and Properties of Titanium-Clad Steel Plate Prepared by Vacuum Hot Rolling
Authors: Pu Juan , Chen Tingmu , Sun Yubo , Long Weimin , Sun Huawei , Chen Yunxia
Published: August 2024

Titanium-clad steel plates are widely used in chemical equipment and nuclear power equipment due to their excellent corrosion resistance and high strength. However, the Ti-C and Fe-Ti compounds generated easily at the titanium/steel interface deteriorate the bonding strength of titanium and steel, especially in high-temperature service environments. In this study, pure Fe DT4 was chosen as an intermediate layer to control the formation of interfacial compounds. The plates of titanium/DT4/steel were manufactured by hot rolling technology with a small hole vacuuming. Then, titanium-clad steel plates were annealed at temperatures of 450 °C, 550 °C, and 650 °C to modify microstructure and properties. The interfacial microstructure composition, mechanical properties of titanium-clad steel plates, and the corrosion resistance property of titanium plates were studied in the as-rolled state and under different annealing temperatures. The results showed that compounds of TiC, FeTi, and Fe2Ti were generated at the interface of titanium-clad steel plates in the as-rolled state. After the annealing treatment, the types and quantities of the interfacial compounds were reduced, and these compounds were mainly TiC and FeTi at an annealing temperature of 450 °C. The interfacial compound was only TiC at an annealing temperature of 550 °C. However, the compounds of TiC and FeTi appeared at the interface at an annealing temperature of 650 °C. The variation of interfacial compounds determined the hardness and the shear strength of the titanium-clad steel plates. The more the interfacial compounds, the higher the hardness and the lower the shear strength. Therefore, when the annealing temperature was 550 °C, the interfacial hardness was lowest and the shear strength was highest. Meanwhile, the corrosion resistance of the titanium-clad plates showed significant improvement, indicating that this temperature provides favorable conditions for enhancing the corrosion performance of the plate.
Influence of Process Parameters on Properties of Non-Reactive RF Magnetron-Sputtered Indium Tin Oxide Thin Films Used as Electrodes for Organic Light-Emitting Diodes
Authors: Diletto Claudia , Nunziata Fiorita , Aprano Salvatore , Migliaccio Ludovico , Maglione Maria Grazia , Rubino Alfredo , Tassini Paolo
Published: August 2024

Indium tin oxide (ITO) is a transparent conductive oxide (TCO) commonly used in the realization of optoelectronic devices needing at least a transparent electrode. In this work, ITO thin films were deposited on glass substrates by non-reactive RF magnetron sputtering, investigating the effects of power density, sputtering pressure, and substrate temperature on the electrical, optical, and structural properties of the as-grown films. High-quality films, in terms of crystallinity, transparency, and conductivity were obtained. The 120 nm thick ITO films grown at 225 °C under an argon pressure of 6.9 mbar and a sputtering power density of 2.19 W/cm2 without post-annealing treatments in an oxidizing environment showed an optical transmittance near 90% at 550 nm and a resistivity of 2.10×10−4 Ω cm. This material was applied as the electrode of simple-structure organic light-emitting diodes (OLEDs).
Ovarian Mesonephric-like Adenocarcinoma: Its Prevalence in a Japanese High-Volume Cancer Center and a Literature Review on Therapeutic Targets
Authors: Ogawa Ayako , Yoshida Hiroshi , Kawano Saria , Kikkawa Nao , Kobayashi-Kato Mayumi , Tanase Yasuhito , Uno Masaya , Ishikawa Mitsuya
Published: August 2024

Background: Ovarian mesonephric-like adenocarcinoma (MLA) is a newly described histological type known for its aggressive behavior. This study aims to determine the frequency of ovarian MLA, review the existing literature, and elucidate its clinicopathological characteristics, including the potential therapeutic targets. Methods: We retrospectively reviewed the pathological diagnoses of 501 primary ovarian cancer surgical cases at our institution from 2010 to 2023. MLAs exhibiting typical morphological and immunohistochemical features were included. The frequency and clinicopathological characteristics of these cases were summarized. Additionally, we conducted a literature search using PubMed to collect and summarize previously reported cases of ovarian MLAs. Results: Among the 501 primary ovarian cancer cases, we identified 3 cases (0.6%) of MLA. The patients were 52–76 years old, and the initial FIGO stages were IC1 (two cases) and IIIB (one case). All the cases exhibited HRP, pMMR, PD-L1 negativity (CPS < 1), and low HER2 expression. Two cases experienced metastatic recurrence. A literature review identified 97 cases of MLA. The MLAs frequently exhibited KRAS mutations (90%, 38/42), with a recurrence rate of 39% (26/67). Conclusion: MLAs accounted for 0.6% of malignant ovarian tumors at our institution, all of which were advanced or recurrent cases. These cases showed HRP, pMMR, and PD-L1 negativity, indicating a lack of current therapeutic targets. The literature also reported a high incidence of advanced and recurrent cases, highlighting the need for accurate diagnosis and the development of new treatments. The frequent KRAS mutations suggest a potential therapeutic target for recurrent or metastatic MLA.
Prospective Comparison of Nine Different Handheld Ultrasound (HHUS) Devices by Ultrasound Experts with Regard to B-Scan Quality, Device Handling and Software in Abdominal Sonography
Authors: Merkel Daniel , Lueders Christian , Schneider Christoph , Yousefzada Masuod , Ruppert Johannes , Weimer Andreas , Herzog Moritz , Lorenz Liv Annebritt , Vieth Thomas , Buggenhagen Holger , Weinmann-Menke Julia , Weimer Johannes Matthias
Published: August 2024

Background: The HHUS market is very complex due to a multitude of equipment variants and several different device manufacturers. Only a few studies have compared different HHUS devices under clinical conditions. We conducted a comprehensive prospective observer study with a direct comparison of nine different HHUS devices in terms of B-scan quality, device handling, and software features under abdominal imaging conditions. Methods: Nine different HHUS devices (Butterfly iQ+, Clarius C3HD3, D5CL Microvue, Philips Lumify, SonoEye Chison, SonoSite iViz, Mindray TE Air, GE Vscan Air, and Youkey Q7) were used in a prospective setting by a total of 12 experienced examiners on the same subjects in each case and then assessed using a detailed questionnaire regarding B-scan quality, handling, and usability of the software. The evaluation was carried out using a point scale (5 points: very good; 1 point: insufficient). Results: In the overall evaluation, Vscan Air and SonoEye Chison achieved the best ratings. They achieved nominal ratings between “good” (4 points) and “very good” (5 points). Both devices differed significantly (p < 0.01) from the other seven devices tested. Among the HHUS devices, Clarius C3HD3 and Vscan Air achieved the best results for B-mode quality, D5CL Microvue achieved the best results for device handling, and SonoEye Chison and Vscan Air achieved the best results for software. Conclusions: This is the first comprehensive study to directly compare different HHUS devices in a head-to-head manner. While the majority of the tested devices demonstrated satisfactory performance, notable discrepancies were observed between them. In particular, the B-scan quality exhibited considerable variation, which may have implications for the clinical application of HHUS. The findings of this study can assist in the selection of an appropriate HHUS device for specific applications, considering the clinical objectives and acknowledging the inherent limitations.
Profile Photograph Classification Performance of Deep Learning Algorithms Trained Using Cephalometric Measurements: A Preliminary Study
Authors: Kocakaya Duygu Nur Cesur , Özel Mehmet Birol , Kartbak Sultan Büşra Ay , Çakmak Muhammet , Sinanoğlu Enver Alper
Published: August 2024

Extraoral profile photographs are crucial for orthodontic diagnosis, documentation, and treatment planning. The purpose of this study was to evaluate classifications made on extraoral patient photographs by deep learning algorithms trained using grouped patient pictures based on cephalometric measurements. Cephalometric radiographs and profile photographs of 990 patients from the archives of Kocaeli University Faculty of Dentistry Department of Orthodontics were used for the study. FH-NA, FH-NPog, FMA and N-A-Pog measurements on patient cephalometric radiographs were carried out utilizing Webceph. 3 groups for every parameter were formed according to cephalometric values. Deep learning algorithms were trained using extraoral photographs of the patients which were grouped according to respective cephalometric measurements. 14 deep learning models were trained and tested for accuracy of prediction in classifying patient images. Accuracy rates of up to 96.67% for FH-NA groups, 97.33% for FH-NPog groups, 97.67% for FMA groups and 97.00% for N-A-Pog groups were obtained. This is a pioneering study where an attempt was made to classify clinical photographs using artificial intelligence architectures that were trained according to actual cephalometric values, thus eliminating or reducing the need for cephalometric X-rays in future applications for orthodontic diagnosis.
Application of Artificial Intelligence in Cone-Beam Computed Tomography for Airway Analysis: A Narrative Review
Authors: Ismail Izzati Nabilah , Subramaniam Pram Kumar , Chi Adam Khairul Bariah , Ghazali Ahmad Badruddin
Published: August 2024

Cone-beam computed tomography (CBCT) has emerged as a promising tool for the analysis of the upper airway, leveraging on its ability to provide three-dimensional information, minimal radiation exposure, affordability, and widespread accessibility. The integration of artificial intelligence (AI) in CBCT for airway analysis has shown improvements in the accuracy and efficiency of diagnosing and managing airway-related conditions. This review aims to explore the current applications of AI in CBCT for airway analysis, highlighting its components and processes, applications, benefits, challenges, and potential future directions. A comprehensive literature review was conducted, focusing on studies published in the last decade that discuss AI applications in CBCT airway analysis. Many studies reported the significant improvement in segmentation and measurement of airway volumes from CBCT using AI, thereby facilitating accurate diagnosis of airway-related conditions. In addition, these AI models demonstrated high accuracy and consistency in their application for airway analysis through automated segmentation tasks, volume measurement, and 3D reconstruction, which enhanced the diagnostic accuracy and allowed predictive treatment outcomes. Despite these advancements, challenges remain in the integration of AI into clinical workflows. Furthermore, variability in AI performance across different populations and imaging settings necessitates further validation studies. Continued research and development are essential to overcome current challenges and fully realize the potential of AI in airway analysis.
Machine Learning Models for Predicting Mortality in Patients with Cirrhosis and Acute Upper Gastrointestinal Bleeding at an Emergency Department: A Retrospective Cohort Study
Authors: Tsai Shih-Chien , Lin Ching-Heng , Chu Cheng-C. J. , Lo Hsiang-Yun , Ng Chip-Jin , Hsu Chun-Chuan , Chen Shou-Yen
Published: August 2024

Background: Cirrhosis is a major global cause of mortality, and upper gastrointestinal (GI) bleeding significantly increases the mortality risk in these patients. Although scoring systems such as the Child–Pugh score and the Model for End-stage Liver Disease evaluate the severity of cirrhosis, none of these systems specifically target the risk of mortality in patients with upper GI bleeding. In this study, we constructed machine learning (ML) models for predicting mortality in patients with cirrhosis and upper GI bleeding, particularly in emergency settings, to achieve early intervention and improve outcomes. Methods: In this retrospective study, we analyzed the electronic health records of adult patients with cirrhosis who presented at an emergency department (ED) with GI bleeding between 2001 and 2019. Data were divided into training and testing sets at a ratio of 90:10. The ability of three ML models—a linear regression model, an XGBoost (XGB) model, and a three-layer neural network model—to predict mortality in the patients was evaluated. Results: A total of 16,025 patients with cirrhosis and 32,826 ED visits for upper GI bleeding were included in the study. The in-hospital and ED mortality rates were 11.2% and 2.2%, respectively. The XGB model exhibited the highest performance in predicting both in-hospital and ED mortality (area under the receiver operating characteristic curve: 0.866 and 0.861, respectively). International normalized ratio, renal function, red blood cell distribution width, age, and white blood cell count were the strongest predictors in all the ML models. The median ED length of stay for the ED mortality group was 17.54 h (7.16–40.01 h). Conclusions: ML models can be used to predict mortality in patients with cirrhosis and upper GI bleeding. Of the three models, the XGB model exhibits the highest performance. Further research is required to determine the actual efficacy of our ML models in clinical settings.
Robust Nonlinear Control with Estimation of Disturbances and Parameter Uncertainties for UAVs and Integrated Brushless DC Motors
Authors: Vera Vaca Claudia Verónica , Di Gennaro Stefano , Vaca García Claudia Carolina , Acosta Lúa Cuauhtémoc
Published: August 2024

Unmanned Aerial Vehicles (UAVs) have become increasingly prevalent in various applications, ranging from surveillance to package delivery. Achieving precise control of UAV position while enhancing robustness against uncertainties and disturbances remains a critical challenge. In this study, we propose a robust nonlinear control system for a UAV and its actuators, focusing on accurately controlling the position reference vector and improving robustness against parameter uncertainties and external disturbances. The control strategy employs two control loops: an outer loop for the UAV frame and an inner loop for the UAV actuators. The outer loop generates the required angular velocities for the actuators to follow the reference position vector using the UAV’s output and the inner loop ensures that the actuators track these angular velocity references. Both control loops utilize PI-like controllers for simplicity. The proposed system incorporates nonlinear control techniques and estimation strategies for disturbances and parameter variations, enabling dynamic adaptation to changing environmental conditions. Numerical simulations were performed using both Simulink® and the simulated PX4 Autopilot environment, showing the effectiveness of the proposed control system in achieving precise position control and robust performance for both the UAV and its actuators in the presence of uncertainties and disturbances. These results underscore the potential applicability of the control system in other UAV operational scenarios.
Research on Active Disturbance Rejection Control with Parameter Tuning for Permanent Magnet Synchronous Motor Based on Improved PSO Algorithm
Authors: Zhou Ziyang , Wang Liming , Wang Yang , Zhou Xinlei , Tong Yipin
Published: August 2024

Addressing the issue of significant speed fluctuations in permanent magnet synchronous motors (PMSM) under load, this paper proposes an active disturbance rejection control strategy based on an improved particle swarm optimization (PSO) algorithm. Initially, the speed of the PMSM is considered as the comprehensive optimization objective, and an active disturbance rejection control (ADRC) model for the PMSM is established by integrating the ADRC with vector control. Subsequently, an adaptive PSO algorithm incorporating genetic algorithms is proposed. This algorithm uses chaotic initialization for uniform particle distribution, introduces adaptive inertia weight and dynamic cognitive factors to enhance search efficiency, and integrates the crossover and mutation modules from genetic algorithms, optimizing mutations using a Gaussian probability function. Simulation results demonstrated that: (1) under identical external load conditions, the proposed ADRC strategy ensured smaller speed fluctuations and a smoother waveform for the PMSM, and (2) compared to the traditional PSO algorithm, the proposed method reduced the speed fluctuation after external load by approximately 26%.
A Novel Method for Damping State Switching Based on Machine Learning of a Strapdown Inertial Navigation System
Authors: Lyu Xu , Zhu Jiupeng , Wang Jungang , Dong Ruiqi , Qian Shiyi , Hu Baiqing
Published: August 2024

The integrated navigation system based on the Global Navigation Satellite System (GNSS) in conjunction with the strapdown inertial navigation system (SINS) and the Doppler Velocity Logger (DVL) is essential for accurate and long-distance navigation in maritime environments. However, the error of the integrated navigation system gradually diverges due to the inevitable velocity measurement error of DVL when GNSS outages occur. To ensure the high navigational accuracy and stability of SINS, it is necessary to dynamically adjust the damping state of SINS provided externally. In this paper, we have developed a novel method for damping state switching based on machine learning with SINS. We construct a model of the change in reference velocity error and use sliding window technology to obtain the reference velocity error for model training. Before training, the digital compass loop is designed to process and highlight the change in reference velocity change errors. In order to reduce the impact of the damping switching, a variable damping system is used to transform the traditional one-time switching of the damping coefficient into a gradual switching, effectively reducing the impact of a sudden change in the damping coefficient on the system. Simulation experiments and tests on ships show that the proposed method effectively reduces the overshoot error integrated underwater during state switching. This research is of great importance for the optimal design of integrated underwater navigation systems.
Design and Development of Shadow: A Cost-Effective Mobile Social Robot for Human-Following Applications
Authors: Torrejón Alejandro , Zapata Noé , Bonilla Lucas , Bustos Pablo , Núñez Pedro
Published: August 2024

This study explores the development and implementation of Shadow, an advanced mobile social robot designed to meet specific functional requirements. Shadow is intended to serve both as a versatile tool and a human companion, assisting in various tasks across different environments. The construction emphasizes cost efficiency and high agility, utilizing 3D printing technology exclusively. The robot features omnidirectional kinematics and a flexible power electronics system, accommodating diverse energy needs with lithium batteries that ensure at least seven hours of autonomous operation. An integrated sensor array continuously monitors the power system, tracks tilt and acceleration, and facilitates self-diagnostic functions. Rapid prototyping allows for swift iteration, testing, and refinement to align with project goals. This paper provides a comprehensive blueprint for designing cost-effective, highly agile robots using advanced manufacturing techniques. Extensive testing, including stability and sensory skills evaluations, demonstrates Shadow’s adherence to its design objectives. Shadow has advanced from technology readiness level (TRL) 2 to TRL 7 within a year and is currently undergoing trials with advanced functionalities, offering significant insights into overcoming practical design challenges and optimizing robot functionality.
Frequency Characteristic Analysis of the VSC-HVDC DC Oscillating Power under AC Sub-Synchronous Disturbances
Authors: Bin Zijun , Feng Xuan , Miao Zilong , Kong Xiangping , Li Peng , Shao Bingbing
Published: August 2024

The DC-side response characteristics of the VSC-HVDC transmission system under AC-side sub-synchronous disturbances may lead to the propagation of AC/DC oscillations, and then there may be non-fundamental frequency oscillation on the DC-side. To clarify the interactive influence mechanism and propagation evolution law of the AC and DC side sub-synchronous oscillations in the VSC-HVDC transmission system, the frequency characteristics of the DC-side oscillation power are investigated by considering the effect of converter control links. First, the AC-side voltage and current frequency responses under single/multiple SSO components are analyzed. Secondly, the frequency characteristics of the DC-side power after the injection of single/multiple SSO components are investigated. Meanwhile, the effect of system control parameters on the sub-synchronous responses of the DC-side power is investigated. Finally, the theoretical analysis is verified with PSCAD/EMTDC simulations. The results show that under the influence of the AC-side SSO components, the DC-side of VSC-HVDC faces the risk of multi-frequency oscillations; when there are multiple SSO components on the AC-side, there is a coupling between the components, and the system control parameters affect the amplitude of the DC-side oscillation power.
The Change in Maintenance Strategy on the Efficiency and Quality of the Production System
Authors: Rakyta Miroslav , Bubenik Peter , Binasova Vladimira , Gabajova Gabriela , Staffenova Katarina
Published: August 2024

The presented contribution deals with the research of the maintenance strategy and procedures for improving maintenance processes in order to increase the efficiency and quality of the production system. It is based on a thorough analysis of the research of the available literary sources published in foreign and domestic scientific journals. The subsequent proposal includes defining new goals and maintenance performance indicators relevant to today’s production systems to track improvements in the sustainable development of the production system. There are also basic principles of the maintenance strategy with links to the production system and the choice of strategy for the organization. This paper emphasizes the audit of maintenance management and the implementation of quality in maintenance. Next, a new procedure for changing the maintenance strategy is described. This process includes reviewing the criticality of machines and equipment and their structural units, then resource and capacity planning and inputs for maintenance management, and the impact of maintenance on the operating costs of the production system. This was based on which partial projects in companies were verified—automotive industry (spare parts, preventive maintenance, planned maintenance, RCFA, TPM), rubber industry (quality, production efficiency), pharmaceutical industry (preventive and predictive maintenance), engineering industry (TPM, LOTO, RCM). The overall verification of the creation of the maintenance strategy and the proposed methodology was carried out on the basis of the outputs of the sub-projects and overall projects in the following companies with positive results—glass industry, chemical industry, and operational research (research and development of equipment for non-reactor parts of nuclear power plants). Ten steps of the audit of the current state of the management of maintenance processes were proposed, to ensure economic improvements in the costs of maintenance processes and operating costs, ensuring competitiveness. A methodology for changing the maintenance strategy focused on the efficiency, quality, and costs of the production system was proposed. The average benefits from the implementation of strategy changes in organizations reached at least the following: (1) increase in production efficiency—OEE (7%), (2) improvement in production quality (20%), (3) improvement in performance (15%), and (4) reduction in maintenance process costs (10%) in implemented projects.
Deep Siamese Neural Network-Driven Model for Robotic Multiple Peg-in-Hole Assembly System
Authors: Chen Jinlong , Tang Wei , Yang Minghao
Published: August 2024

Robots are now widely used in assembly tasks. However, when robots perform the automatic assembly of Multi-Pin Circular Connectors (MPCCs), the small diameter of the pins and the narrow gaps between them present significant challenges. During the assembly process, the robot’s end effector can obstruct the view, and the contact between the pins and the corresponding holes is completely blocked, making this task more precise and challenging than the common peg-in-hole assembly. Therefore, this paper proposes a robotic assembly strategy for MPCCs that includes two main aspects: (1) we employ a vision-based Deep Siamese Neural Network (DSNN) model to address the most challenging peg-in-hole alignment problem in MPCC assembly. This method avoids the difficulties of modeling in traditional control strategies, the high training costs, and the low sample efficiency in reinforcement learning. (2) This paper constructs a complete practical assembly system for MPCCs, covering everything from gripping to final screwing. The experimental results consistently demonstrate that the assembly system integrated with the DSNN can effectively accomplish the MPCC assembly task.
One Health Ecological Approach to Sustainable Wireless Energy Transfer Aboard Electric Vehicles for Smart Cities
Authors: Razek Adel
Published: August 2024

This investigation is part of a topical situation where wireless equipment is gradually being used for energy transfer, particularly for autonomous systems and the use of decarbonized energies. A characteristic example of decarbonized autonomous use is linked to the substitution of thermal engine vehicles for electric vehicles (EVs) equipped with energy storage batteries. This response was considered in an ecological context of reducing air pollution and defending planetary biodiversity, which are currently vital. These EVs ultimately operate thanks to the wireless charging of their batteries when stationary or running. By changing long-established means of transport that have become a threat to biodiversity, it is necessary to ensure that innovative replacement solutions protect this biodiversity. In addition, the construction of wireless power transfer (WPT) battery chargers for these EVs must offer an optimal ecology of clean energy saving. In such a context, the two concepts of One Health (OH) and Responsible Attitude (RA) will find their place in the design and control of WPT tools in EVs. This contribution aims to illustrate and analyze the roles of the green and non-wasteful OH and RA approaches in the design and control of WPT embedded in EVs for the smart city (SC) environment. In the paper, WPT tools are first introduced. The design and control of EV battery charging tools are then examined. The biological effects on living tissues due to the electromagnetic field (EMF) radiation of WPT are analyzed. The phenomena and equations governing the design of WPT and the effects of EMF radiation are then exposed. The OH and RA approaches in the SC context are afterward analyzed. The protection against the unsafe effects of WPT tools in the SC environment is consequently explored. The analyses followed in the paper are supported by examples from the literature. The explorations proposed in this contribution have made it possible to highlight certain notions, allowing a more in-depth understanding of the use of EVs with WPT rechargeable batteries for SCs. Thus, the analysis and fusion of these topics are at the heart of this contribution.
A Comprehensive Review on Molecular Dynamics Simulations of Forced Convective Heat Transfer in Nanochannels
Authors: Fallahzadeh Rasoul , Bozzoli Fabio , Cattani Luca , Naeimabadi Niloofar
Published: August 2024

As the demand for miniaturization of thermal management systems for electronic devices rises, numerous researchers are dedicating their efforts to the study of single-phase forced convective heat transfer (FCHT) within nanoscale channels. However, investigating FCHT in nanochannels (FCHT-NC) using experimental and theoretical methods is challenging. Alternately, molecular dynamics (MD) simulations have emerged as a unique and powerful technique in recent years. This paper presents a comprehensive review of the application of the MD simulation method in the study of FCHT-NC. Firstly, the current paper reviews various simulation techniques and models, along with their associated primary parameters employed in FCHT-NC, through a detailed and systematic literature survey and critical analysis. Evaluating the current methods and discussing their limitations provide helpful guidelines for future studies. Furthermore, based on the existing literature in the MD simulation, this review outlines all influencing parameters on the performance of FCHT-NC, covering their effects and discussing underlying mechanisms. Finally, key challenges and future research directions are summarized in this review, thereby providing essential support for researchers seeking to apply the MD simulation method to investigate FCHT-NC.
The Impact of Changes in Green Space Structures on Thermal Mitigation and Costs under a Constant Green Volume
Authors: Li Zilong , Qi Zhiyong , Zheng Bohong , Luo Xi
Published: August 2024

Green space improves outdoor thermal comfort and promotes the residents’ physical and mental health. Currently, many cities are using green volume indicators to evaluate the quality of residential green space and to help form the latest evaluation standards. However, from the perspective of plant green volume, the impact of green space structures on thermal mitigation has not been emphasized. Furthermore, the cost of green space will change with the green space structures. Therefore, we evaluate the impact of changes in green space structures on thermal mitigation and costs from the perspective of plant green volume and aim to find suitable allocations of plant green volume, which balance thermal mitigation with cost savings. This study analyzed the regional climate and residential green space structures. Then, we discussed the relationship between thermal mitigation and the costs of different structures. The analytical results indicated that thermal comfort improves as the green volume of trees increases, with costs also increasing. Where the green volume exceeds 70%, no “extreme heat stress” moments occur for the whole day. When the green volume of trees increases from 20% to 60%, the thermal mitigation is 3.62 °C. However, the mitigation is only 1.74 °C when the green volume increases from 60% to 100%, which is less than half of the former, numerically. This study suggests that the green volume of trees in residential green spaces should be controlled at 60%–70% and the corresponding green volume of shrubs should be 30%–40%. This study rationally balances the thermal mitigation and costs of residential green space, which will directly guide residential green space planning in real situations.
Which Factors Affect the Visual Preference and User Experience: A Case Study of the Mulan River Greenway in Putian City, China
Authors: Zheng Junming , Chen Yashan , Guan Lei
Published: August 2024

Greenways are an important component of urban green infrastructure. User experiences and visual preferences are highly related to human well-being. The influencing factors of user experience and the relationship between environmental attributes with visual preference were explored by using the analytic hierarchy process method and questionnaire experiments. In this study, the analytic hierarchy process was conducted to construct the users’ experience evaluation system, and three methods were used to reveal the influencing factors of the users’ experience in the Mulan River greenway, China. The connection between visual perception and environmental attributes was also identified. The results show that the site leveling, plant landscape aesthetics, and air quality are the main factors affecting user experience. The most significant factor influencing visual preference is the green view index. The green view index can promote visual preference within 60%. Various environmental features contribute to visual preference, providing quantitative support for enhancing landscape quality. This research reveals the factors of visual preference that contribute to forming scientific recommendations for the management and quality improvement of the Mulan River greenway.
Yeast for the Production of Biochemicals and Biofuels
Authors: Paul Debarati
Published: August 2024

Demands for bioenergy resources, nutraceuticals, biofertilizers, and other industrially important chemicals have escalated globally due to rapid urbanization, industrialization, and a growing awareness about bio-based, environment-friendly products [...]
Functional Properties of Foods and Beverages
Authors: Abbasi Arshad Mehmood , Guo Xinbo , Chen Yongsheng
Published: August 2024

The conception “Let food be thy medicine and medicine be thy food” introduced by the father of medicine “Hippocrates” highlights the significance of bioactive substances in human health [...]
Green Ultrasound-Assisted Extraction of Bioactive Compounds from Cumari-Do-Pará Peppers (Capsicum chinense Jacq.) Employing Vegetable Oils as Solvents
Authors: Cardoso Raiane Vieira , da Silva Davi Vieira Teixeira , Santos-Sodré Samíria de Jesus Lopes , Pereira Patricia Ribeiro , Freitas Cyntia Silva , Moterle Diego , Kanis Luiz Alberto , Silva Luiza Helena Meller da , Rodrigues Antonio Manoel da Cruz , Paschoalin Vania Margaret Flosi
Published: August 2024

Capsaicin, carotenoids, and phenolic compounds from cumari-do-Pará peppers (Capsicum chinense Jacq.) harvested from two different locations in Pará, Brazil, and at different ripening stages were extracted by employing green methodologies as an alternative to organic solvents. Edible vegetable oils from soybeans (Glycine max), Brazilian nuts (Bertholettia excelsa H.B.), and palm olein were used in combination with ultrasonic-assisted extraction (UAE). The proximate composition of the pepper extracts and vitamin C were determined through AOAC methods, total phenolics and carotenoids were assessed by UV/Vis spectrophotometry, and capsaicin by high-performance liquid chromatography. Antioxidant cumari-do-Pará extract activities were evaluated by the ABTS radical scavenging and β-carotene/linoleic acid assays. The vegetable oils were suitable for extracting and preserving bioactive pepper compounds, especially mature ones harvested from Igarapé-Açu. Bioactive compound content and antioxidant activity varied with harvesting location and ripening stage. Soybean oil was the most effective in extracting bioactive pepper compounds, particularly carotenoids, with 69% recovery. Soybean oil extracts enriched in capsaicin, carotenoids, and phenolics obtained from cumari-do-Pará can be used as spices in foodstuffs and/or as additives in pharmaceutical and nutraceutical formulations. Edible vegetable oils combined with UAE are promising for bioactive compound extraction, representing an environmentally friendly, safe, low-cost, versatile, and fast alternative.
Validation of an Optical Technology for the Determination of pH in Milk during Yogurt Manufacture
Authors: Liu Siqi , Contreras Fanny , Alemán Ricardo S. , Fuentes Jhunior Marcía , Arango Oscar , Castillo Manuel
Published: August 2024

Current systems that allow inline pH control in the fermented dairy industry have drawbacks, such as protein adhesion on the non-glass pH probes, measurement distortion, frequent recalibration needs, and sensitivity to extreme pH conditions encountered during clean-in-place operations. Therefore, the objective of this study was to validate the feasibility of estimating the pH of milk during the yogurt making process by using a NIR light backscatter sensor measuring under different fermentation temperatures and milk protein concentrations using a mathematical model that correlates the light scatter signal with pH. Three replications of the experiment with two protein concentrations (3.5 and 4.0%) and two fermentation temperatures (43 and 46 °C) were used to validate this inline pH prediction model. Continuous and discontinuous measurements of pH were collected as a reference during fermentation, simultaneously with the light backscatter data acquisition. Also, the effect of adjusting the initial voltage gain of the light scatter device on the accuracy of the pH prediction model was evaluated. Temperature and initial voltage were the main factors affecting the fitting accuracy of the model. The adjustment of the initial voltage gain improved the pH prediction model fit. The model has been successfully validated for both continuous and discontinuous measurements of pH, with SEP values < 0.09 pH units and CV < 1.78%. The proposed optical inline and non-destructive method was feasible for inline pH monitoring of milk fermentation, avoiding traditional manual pH measurement.
Recent Advances in Physical Processing Techniques to Enhance the Resistant Starch Content in Foods: A Review
Authors: Farooq Muhammad Adil , Yu Jianmei
Published: August 2024

The physical modification of starch to produce resistant starch (RS) is a viable strategy for the glycemic index (GI) lowering of foods and functionality improvement in starchy food products. RS cannot be digested in the small intestine but can be fermented in the colon to produce short-chain fatty acids rather than being broken down by human digestive enzymes into glucose. This provides major health advantages, like better blood sugar regulation, weight control, and a lower chance of chronic illnesses. This article provides a concise review of the recent developments in physical starch modification techniques, including annealing, extrusion, high-pressure processing, radiation, and heat–moisture treatment. Specifically, the focus of this paper is on the alteration of the crystalline structure of starch caused by the heat–moisture treatment and annealing and its impact on the resistance of starch to enzymatic hydrolysis, as well as the granular structure and molecular arrangement of starch caused by extrusion and high-pressure processing, and the depolymerization and crosslinking that results from radiation. The impacts of these alterations on starch’s textural qualities, stability, and shelf life are also examined. This review demonstrates how physically modified resistant starch can be used as a flexible food ingredient with both functional and health benefits. These methods are economically and ecologically sustainable since they successfully raise the RS content and improve its functional characteristics without the need for chemical reagents. The thorough analysis of these methods and how they affect the structural characteristics and health advantages of RS emphasizes the material’s potential as an essential component in the creation of functional foods that satisfy contemporary dietary and health requirements.
Optimization of the Preparation Process and Ameliorative Efficacy in Osteoporotic Rats of Peptide–Calcium Chelates from Skipjack Tuna (Katsuwonus pelamis) Meat
Authors: Yan Wan-Zhen , Wang Jiao , Wang Yu-Mei , Zeng Yu-Hui , Chi Chang-Feng , Wang Bin
Published: August 2024

This study aimed to establish the preparation process of peptide–calcium chelates (TMP-Ca) using skipjack tuna meat and investigate the function and mechanism of TMP-Ca in an osteoporosis model of rats. The results indicated that trypsin is more suitable for preparing the Ca-chelating hydrolysates of tuna meat, and the optimal hydrolysis conditions were derived as follows: digestion time 4 h, material–liquid ratio 1:10, and enzyme dose 3%. The conditions for chelating Ca with tuna meat hydrolysate were optimized to be chelation time 50 min, temperature 50 °C, pH 8.0, and a peptide–Ca ratio 1:10. The prepared hydrolysate was subjected to ultrafiltration, and the fraction (TMP) (MW <1 kDa) showed the highest Ca chelation rate (51.27 ± 1.42%) and was made into the peptide–Ca chelates (TMP-Ca). In osteoporotic rats, TMP-Ca significantly improved the decrease in ovarian indexes caused by retinoic acid. It also elevated serum Ca, phosphorus, and bone turnover indexes, increased the number of bone trabeculae, and improved bone microstructure. In addition, we confirmed that TMP-Ca could regulate the OPG/TRAF6 pathway to reduce osteoclast differentiation, inhibit bone resorption, and promote bone formation. Therefore, TMP-Ca could significantly ameliorate osteoporosis, and this study provides a functional component for the preparation of healthcare products using skipjack tuna meat to treat osteoporosis.
Forecasting Container Throughput of Singapore Port Considering Various Exogenous Variables Based on SARIMAX Models
Authors: Lee Geun-Cheol , Bang June-Young
Published: August 2024

In this study, we propose a model to forecast container throughput for the Singapore port, one of the busiest ports globally. Accurate forecasting of container throughput is critical for efficient port operations, strategic planning, and maintaining a competitive advantage. Using monthly container throughput data of the Singapore port from 2010 to 2021, we develop a Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) model. For the exogenous variables included in the SARIMAX model, we consider the West Texas Intermediate (WTI) crude oil price and China’s export volume, alongside the impact of the COVID-19 pandemic measured through global confirmed cases. The predictive performance of the SARIMAX model was evaluated against a diverse set of benchmark methods, including the Holt–Winters method, linear regression, LASSO regression, Ridge regression, ECM (Error Correction Mechanism), Support Vector Regressor (SVR), Random Forest, XGBoost, LightGBM, Long Short-Term Memory (LSTM) networks, and Prophet. This comparative analysis was conducted by forecasting container throughput for the year 2022. Results indicated that the SARIMAX model, particularly when incorporating WTI prices and China’s export volume, outperformed other models in terms of forecasting accuracy, such as Mean Absolute Percentage Error (MAPE).
Analysis of the(3+1)-Dimensional Fractional Kadomtsev–Petviashvili–Boussinesq Equation: Solitary, Bright, Singular, and Dark Solitons
Authors: Seadway Aly R. , Ali Asghar , Bekir Ahmet , Cevikel Adem C.
Published: August 2024

We looked at the (3+1)-dimensional fractional Kadomtsev–Petviashvili–Boussinesq (KP-B) equation, which comes up in fluid dynamics, plasma physics, physics, and superfluids, as well as when connecting the optical model and hydrodynamic domains. Furthermore, unlike the Kadomtsev–Petviashvili equation (KPE), which permits the modeling of waves traveling in both directions, the zero-mass assumption, which is required for many scientific applications, is not required by the KP-B equation. In several applications in engineering and physics, taking these features into account allows researchers to acquire more precise conclusions, particularly in studies pertaining to the dynamics of water waves. The foremost purpose of this manuscript is to establish diverse solutions in the form of exponential, trigonometric, hyperbolic, and rational functions of the (3+1)-dimensional fractional (KP-B) via the application of four analytical methods. This KP-B model has fruitful applications in fluid dynamics and plasma physics. Additionally, in order to better explain the potential and physical behavior of the equation, the relevant models of the findings are visually indicated, and 2-dimensional (2D) and 3-dimensional (3D) graphics are drawn.
Interaction Solutions for the Fractional KdVSKR Equations in (1+1)-Dimension and (2+1)-Dimension
Authors: Zhang Lihua , Zheng Zitong , Shen Bo , Wang Gangwei , Wang Zhenli
Published: August 2024

We extend two KdVSKR models to fractional KdVSKR models with the Caputo derivative. The KdVSKR equation in (2+1)-dimension, which is a recent extension of the KdVSKR equation in (1+1)-dimension, can model the soliton resonances in shallow water. Applying the Hirota bilinear method, finite symmetry group method, and consistent Riccati expansion method, many new interaction solutions have been derived. Soliton and elliptical function interplaying solution for the fractional KdVSKR model in (1+1)-dimension has been derived for the first time. For the fractional KdVSKR model in (2+1)-dimension, two-wave interaction solutions and three-wave interaction solutions, including dark-soliton-sine interaction solution, bright-soliton-elliptic interaction solution, and lump-hyperbolic-sine interaction solution, have been derived. The effect of the order γ on the dynamical behaviors of the solutions has been illustrated by figures. The three-wave interaction solution has not been studied in the current references. The novelty of this paper is that the finite symmetry group method is adopted to construct interaction solutions of fractional nonlinear systems. This research idea can be applied to other fractional differential equations.
Phenotypic Variability of LGMD 2C/R5 in a Genetically Homogenous Group of Bulgarian Muslim Roma
Authors: Taneva Ani , Gresham David , Guergueltcheva Velina , Chamova Teodora , Bojinova Veneta , Gospodinova Mariana , Katzarova Maria , Petkov Radoslav , Voit Thomas , Aneva Lidia , Asenov Ognyan , Georgieva Bilyana , Mihaylova Violeta , Bichev Stoyan , Todorov Tihomir , Todorova Albena , Kalaydjieva Luba , Tournev Ivailo
Published: August 2024

Sarcoglycanopathies are among the most frequent and severe forms of autosomal recessive forms of limb-girdle muscular dystrophies (LGMDs) with childhood onset. Four subtypes are known: LGMDR3, LGMDR4, LGMDR5 and LGMDR6, which are caused, respectively, by mutations in the SGCA, SGCB, SGCG and SGCD genes. We present the clinical variability of LGMD 2C/R5 among a genetically homogeneous group of 57 patients, belonging to 35 pedigrees. Molecular genetic analysis showed that all 57 patients were homozygous for the C283Y variant. The muscles of the pelvic girdle and the trunk were affected early and were more severely affected, followed by the shoulder girdle. Macroglossia, hypertrophy of the calves, scapular winging and lumbar hyperlordosis were common in the ambulatory phase. A great intra and interfamilial variability in the clinical presentation of LGMD 2C/R5 was observed, despite having the same underlying molecular defect. Females demonstrated a relatively milder clinical course compared to males. Mean creatine phosphokinase (CK) CK levels were 20 times above normal values. Muscle computer tomography (CT) CT or MRIs showed earlier and more severe involvement of the flexor proximal limb muscles in comparison to extensor muscles.