bluuebunny/crossref_metadata_2025 huggingface dataset:
Variations and Claims in International Construction Projects in the MENA Region from the Last Decade
Authors: Abdelalim Ahmed Mohammed , Al-Sabah Ruqaya , Salem Mohamed , Said Salah Omar , Tantawy Mohamed , Ezz Al-Regal Mohamed Ramadan
Published: August 2024

This study delves into the dynamics of ‘Variations’ and ‘Claims’ in construction projects. This study aims to identify, categorize, and devise mitigation strategies for critical types of variations and claims that are aligned with the contract’s FIDIC conditions. The research draws on input from construction industry professionals, including contract administrators and project managers, and focuses on the MENA region. The region’s extensive adoption of FIDIC standards and the rapidly growing construction sector drive this choice. Data collection encompassed a questionnaire distributed to 80 industry experts, predominantly through interviews focused on countries such as Saudi Arabia, the UAE, Kuwait, and Egypt. Utilizing SPSS-V.25 for statistical analysis, this study uncovers the most prevalent and impactful causes of variations and claims, highlighting the critical need for managerial intervention. A key feature is the integration of scientometric analysis into a quantitative finding. Implementing a k-means clustering analysis is a significant addition to the methodology. The survey had high internal consistency with a Cronbach’s alpha of 0.97, and the respondents reported frequent and significant claims such as delayed drawings, ambiguous documents, and client changes. The results showed that effective claims management requires clear communication and balanced contracts, while poor design and contract documentation cause variations and claims. The correlation analysis showed strong positive correlations between claim types and causes. To reduce claims and address these factors, most respondents said the survey could predict and reduce claims.
A GPT-Powered Assistant for Real-Time Interaction with Building Information Models
Authors: Fernandes David , Garg Sahej , Nikkel Matthew , Guven Gursans
Published: August 2024

This study introduces DAVE (Digital Assistant for Virtual Engineering), a Generative Pre-trained Transformer (GPT)-powered digital assistant prototype, designed to enable real-time, multimodal interactions within Building Information Modeling (BIM) environments for updating and querying BIM models using text or voice commands. DAVE integrates directly with Autodesk Revit through Python scripts, the Revit API, and the OpenAI API and utilizes Natural Language Processing (NLP). This study presents (1) the development of a practical AI chatbot application that leverages conversational AI and BIM for dynamic actions within BIM models (e.g., updates and queries) at any stage of a construction project and (2) the demonstration of real-time, multimodal BIM model management through voice or text, which aims to reduce the complexity and technical barriers typically associated with BIM processes. The details of DAVE’s development and system architecture are outlined in this paper. Additionally, the comprehensive process of prototype testing and evaluation including the response time analysis and error analysis, which investigated the issues encountered during system validation, are detailed. The prototype demonstrated 94% success in accurately processing and executing single-function user queries. By enabling conversational interactions with BIM models, DAVE represents a significant contribution to the current body of knowledge.
Can Smart City Construction Promote Urban Green and High-Quality Development?—Validation Analysis from 156 Cities in China
Authors: Li Shilong , Wang Rui
Published: August 2024

The in-depth participation and application of new-generation information and communication technologies, such as big data, Internet of Things, artificial intelligence, etc., in the field of smart cities have promoted their abilities in urban fine governance, public services, ecological livability, scientific and technological innovation, etc. Smart cities are gradually becoming recognized as the best solution to “urban problems”. Smart city construction drives urban innovative development, accumulates kinetic energy for economic growth, strengthens social support functions, enhances the effectiveness of the ecological environment, and promotes the convergence and integration of urban green development and high-quality development. This paper constructs a difference-in-differences model based on propensity score matching. Additionally, fiscal science and technology investment is introduced as mediating variables to further explain the mechanism through which smart city pilot policy impacts urban green and high-quality development. This research uses panel data from 156 prefecture-level cities in China from 2006 to 2019 to empirically test that the construction of smart cities has a significant positive effect on urban green and high-quality development. The mediation effect model shows that an increase in the level of local government’s fiscal science and technology investment enhances the positive effect of smart city construction on urban green and high-quality development. This research concludes with policy recommendations: the government should seize the development opportunity presented by smart city pilot policy, providing necessary policy support and financial incentive for the construction of smart cities. This will optimize the local economic structure, transform the driving forces of urban development, and assist cities in achieving green and high-quality development.
Seismic Performance of Embedded Connections for Precast Hybrid Coupled Wall Systems: Experimental Study and Theoretical Analysis
Authors: Lu Hailu , Su Mingzhou , Wang Yadong , Zhou Yubo , Shen Shihao
Published: August 2024

The novel precast hybrid coupled wall structure system considers convenience requirements for the production and construction of prefabricated components. In this study, to determine the ultimate shear strength of embedded beam-to-wall connections, four full-scale specimens were meticulously designed using the “weak connections and strong components” methodology. Under low-cycle loading on a coupling steel beam, the experimental results indicated that the shear strength of the specimen was approximately twice that predicted by the Mattock–Gaafar mechanical model employed in Seismic Provisions for Structural Steel Buildings (ANSI/AISC 341-16). Therefore, a mechanical model was established to analyze the force transfer between the steel beam and concrete wall. Finally, design formulas for the shear strength were proposed, in addition to corresponding suggestions for construction reinforcement in the embedded area and adjacent zones.
Special Issue Catalysis for Bitumen/Heavy Oil Upgrading and Petroleum Refining
Authors: Mukhamatdinov Irek I. , Sviridenko Nikita N.
Published: August 2024

Currently, fossil fuels continue to play a crucial role in daily life [...]
Microstructure and First Hydrogenation Properties of Individual Phases in TiFe + 12 wt.% ZrV2 Alloy
Authors: Bellon Monsalve Daniela , Ulate-Kolitsky Elena , Cubero-Sesin Jorge M. , Martínez-Amariz Alejandro-David , Huot Jacques
Published: August 2024

This study investigates the microstructure and first hydrogenation properties of Fe52Ti40Zr3V5 and Fe37Ti44Zr9V10 alloys, which are individual phases present in the as-cast TiFe + 12 wt.% ZrV2 alloy (parent alloy). The parent alloy exhibited fast first hydrogenation kinetics due to the interplay of these two phases. Our objective is to study the hydrogen storage behavior of these individual phases. The samples were synthesized by arc melting and characterized by X-ray diffraction, scanning electron microscopy, and energy-dispersive spectroscopy. The results show that when these alloys are melted separately, they do not exhibit the same phase composition as in the parent alloy, indicating a metastable state under our synthesis conditions, which significantly impacts their hydrogen storage behavior. Hydrogenation capacity was measured using a homemade Sieverts apparatus. Both alloys demonstrated excellent first hydrogenation kinetics, with an absorption capacity of 0.9 wt.% for the Fe52Ti40Zr3V5 alloy and 2.3 wt.% for Fe37Ti44Zr9V10 alloy. Our key finding is that the final crystal structure of multi-element alloys is highly dependent on the synthesis method.
An Iron Oxide and Polyaniline Composite-Based Triboelectric Nanogenerator for Intrusion Detection Sensor
Authors: Kim Inkyum , Park Jihyeon , Chun Seungwoo , Yun Jonghyeon , Lee Minwoo , Goh Tae Sik , Park Wook , Choi Hyuk Jin , Kim Daewon
Published: August 2024

An increase in the number of small electronics is anticipated, requiring the preparation of an adequate powering method. A triboelectric nanogenerator, capable of scavenging ambient mechanical energy, is proposed as an efficient means to reduce power consumption for self-sustainable sensors, although its electrical output needs enhancement to broaden its technological applicability. In this work, a magnetic composite comprising iron oxide and polyaniline was synthesized to augment triboelectricity through the modulation of magnetic field intensity using physical chemistry. The crystallinity of the composite, chemical bonding, and structure of the surface are analyzed. The surface potential of the composite, embedded into polydimethylsiloxane, is quantitatively evaluated by using Kelvin probe force microscopy. By amalgamating magnetic flux density and triboelectric outputs, the optimization of the triboelectric layer is achieved, yielding output values of 93.86 V, 6.9 µA, and 127.5 µW. Following a reduction in surface adhesion after the powder coating process, a wind-based triboelectric nanogenerator is fabricated. Its excellent sensitivity to wind and exceptional long-term endurance are assessed, confirming its suitability as a sensor. The practicality of employing this device in intrusion detection, leveraging a wireless door-opening sensor, is demonstrated using synthesized composite materials.
Conservation and Protection Treatments for Cultural Heritage: Insights and Trends from a Bibliometric Analysis
Authors: Pérez-Gandarillas Lucía , Manteca Carmen , Yedra Ángel , Casas Abraham
Published: August 2024

Cultural heritage is a fundamental part of the society’s identity, and its conservation is of great relevance as it transcends time and memory. To minimize its deterioration, cultural heritage has traditionally undergone diverse preservation and maintenance treatments, and the attention of researchers to developing new and innovative methods for state diagnosis and protection treatments has been increasing in the recent decades. Despite extensive efforts in preservation, there remains a need for comprehensive and systematic mapping of scientific research to identify emerging trends and innovations in the field. To address this gap, in this study, a literature review using a bibliometric analysis and LDA methodology was conducted to systematically map scientific research outputs on cultural heritage conservation and protection. Data were retrieved from the Scopus database, and the annual publications, countries, most-cited publications, authors, institutions, and keywords have been comprehensively analyzed, leading to the detection of research trends and contributing to the existing knowledge in the field. The findings show an increasing number of studies in this field in the last decades, particularly since 2010. Italy, home to the largest number of UNESCO heritage sites, is the most prolific country. Most of the studies are related to metal, paper, and stone as substrates to be protected. Significant progress has been made in understanding the deterioration processes through precise diagnosis and the development of innovative treatments for protection. In this sense, the latest trends have been detected, such as the use of non-invasive techniques for diagnosis and the use of nanotechnology and nature-based treatments for conservation treatments.
Bioactive Triple-Helical Recombinant Collagen Gels for Improved Healing of Sunburned Skin
Authors: Yang Yi , Tian Bei , Xie Yi , Liu Peng , Yao Linyan , Xiao Jianxi
Published: August 2024

Excessive ultraviolet (UV) exposure can lead to sunburn, characterized by skin barrier damage, inflammation, pain, and an increased risk of skin cancer. Recombinant collagens have gradually attracted attention due to their high purity, low immunogenicity, batch-to-batch consistency, and excellent solubility. Additionally, the type of dressing significantly affects wound repair. Gels are ideal for sunburn treatment because they maintain a moist environment, adhere firmly, and do not need to be removed. Herein, we have created bioactive triple-helical recombinant collagen (THRC) gels for improved healing of sunburned skin. The THRC gels remained stable after a three-month stability test, displaying a rheological behavior characteristic of non-Newtonian pseudoplastic fluids. In vivo skin irritation tests conducted on New Zealand rabbits demonstrated that THRC gels were safe for use. A sunburned mice model was established to study the biological effects of THRC gels. Non-invasive combo evaluations indicated that THRC gels exhibited an exceptional capability of recovering dermis density, erythema index (EI), hydration, and transepidermal water loss (TEWL) of sunburned skin to a healthy state. Histological observations revealed that THRC gels significantly enhanced the repair of damaged skin by accelerating the recovery process, promoting collagen deposition and regeneration. Molecular biological characterizations further demonstrated their remarkable antioxidant properties, including the inhibition of lipoperoxidation and the enhancement in superoxide dismutase (SOD) and glutathione (GSH) activities. These safe and bioactive recombinant collagen gels provide a novel approach for sunburn repair and show potential for long-term cosmetic benefits.
Ferroelectric and Structural Properties of Cobalt-Doped Lead Ferrite Thin Films Formed by Reactive Magnetron Sputtering
Authors: Beklešovas Benas , Stankus Vytautas , Iljinas Aleksandras , Marcinauskas Liutauras
Published: August 2024

Cobalt-doped lead ferrite (Pb2Fe2O5) thin films were deposited by reactive magnetron sputtering. The influence of the cobalt concentration and synthesis temperature on the structure, phase composition and ferroelectric properties of Pb2Fe2O5 thin films was investigated. It was determined that the increase in deposition temperature increased the grain size and density of the Co-doped PFO thin films. The XRD data demonstrated that the Co-doped Pb2Fe2O5 thin films consisted of Pb2Fe2O5 and PbO phases with a low amount of CoO and Co3O4 phases. The increase in the cobalt concentration in the Pb2Fe2O5 films slightly enhanced the cobalt oxide phase content. Polarization dependence on electric field measurement demonstrated that the highest ferroelectric properties of the Co-doped Pb2Fe2O5 films were obtained when the synthesis was performed at 550 °C temperatures. The increase in the cobalt concentration in the films enhanced the remnant polarization and coercive field values. It was found that the Co-doped Pb2Fe2O5 film deposited at 550 °C temperature and containing 10% cobalt had the highest remnant polarization (72 µC/cm2) and coercive electric field (105 kV/cm).
Machine Learning on Ultrasound Texture Analysis Data for Characterizing of Salivary Glandular Tumors: A Feasibility Study
Authors: Liao Li-Jen , Cheng Ping-Chia , Chan Feng-Tsan
Published: August 2024

Background: Objective quantitative texture characteristics may be helpful in salivary glandular tumor differential diagnosis. This study uses machine learning (ML) to explore and validate the performance of ultrasound (US) texture features in diagnosing salivary glandular tumors. Material and methods: 122 patients with salivary glandular tumors, including 71 benign and 51 malignant tumors, are enrolled. Representative brightness mode US pictures are selected for further Gray Level Co-occurrence Matrix (GLCM) texture analysis. We use a t-test to test the significance and use the receiver operating characteristic curve method to find the optimal cut-point for these significant features. After splitting 80% of the data into a training set and 20% data into a testing set, we use five machine learning models, k-nearest Neighbors (kNN), Naïve Bayes, Logistic regression, Artificial Neural Networks (ANNs) and supportive vector machine (SVM), to explore and validate the performance of US GLCM texture features in diagnosing salivary glandular tumors. Results: This study includes 49 female and 73 male patients, with a mean age of 53 years old, ranging from 21 to 93. We find that six GLCM texture features (contrast, inverse difference movement, entropy, dissimilarity, inverse difference and difference entropy) are significantly different between benign and malignant tumors (p < 0.05). In ML, the overall accuracy rates are 74.3% (95%CI: 59.8–88.8%), 94.3% (86.6–100%), 72% (54–89%), 84% (69.5–97.3%) and 73.5% (58.7–88.4%) for kNN, Naïve Bayes, Logistic regression, a one-node ANN and SVM, respectively. Conclusions: US texture analysis with ML has potential as an objective and valuable tool to make a differential diagnosis between benign and malignant salivary gland tumors.
Novel Twist Morphing Aileron and Winglet Design for UAS Control and Performance
Authors: Negahban Mir Hossein , Bashir Musavir , Priolet Clovis , Botez Ruxandra Mihaela
Published: August 2024

This study introduces a novel “twist morphing aileron and winglet” design for the Unmanned Aircraft System UAS-S45. Improving rolling efficiency through twist morphing ailerons and reducing induced drag through twist morphing winglets are the two main objectives of this study. A novel wing design is introduced, and a high-fidelity gradient-based aerodynamic shape optimization is performed for twist morphing ailerons and twist morphing winglets, separately, with specified objective functions. The twist morphing aileron is then compared to the conventional hinged aileron configuration in terms of rolling efficiency and other aerodynamic properties, in particular aircraft maneuverability. The results for twist morphing ailerons show that the novel morphing design increases the aileron efficiency by 34% compared to the conventional design and reduces induced drag by 61%. Next, twist morphing winglets are studied regarding the induced drag in cruise and climb flight conditions. The results for twist morphing winglets indicate that the novel design reduces induced drag by 25.7% in cruise flight and up to 16.51% in climb; it also decreases the total drag by up to 7.5% and increases aerodynamic efficiency by up to 9%.
Wandering Drunkards Walk after Fibonacci Rabbits: How the Presence of Shared Market Opinions Modifies the Outcome of Uncertainty
Authors: Maloumian Nicolas
Published: August 2024

Shared market opinions and beliefs by market participants generate a set of constraints that mediate information through a not-so-unstable system of expected target prices. Price trajectories, within these sets of constraints, confirm or disprove the likelihood of participant expectations and cannot, de facto, be considered permutable, as literature has shown, since their inner structure is dynamically affected by their own progress, suggesting per se the presence of both heat and cycles. This study described and discussed how trajectories are built using different alphabets and suggests that prices follow an ergodic course within structurally similar tessellation classes. It is reported that the courses of price moves are self-similar due to their a priori structure, and they do not need to be complete in order to create the conditions, in resembling conditions, for the appearance of the well-known and commonly used Fibonacci ratios between price trajectories. To date, financial models and engineering are mostly based on the mathematics of randomness. If these theoretical findings need empirical validation, such a potential infrastructure of ratios would suggest the possibility for a superstructure to exist, in other words, the emergence of exploitable patterns.
A Multi-Local Search-Based SHADE for Wind Farm Layout Optimization
Authors: Yang Yifei , Tao Sichen , Li Haotian , Yang Haichuan , Tang Zheng
Published: August 2024

Wind farm layout optimization (WFLO) is focused on utilizing algorithms to devise a more rational turbine layout, ultimately maximizing power generation efficiency. Traditionally, genetic algorithms have been frequently employed in WFLO due to the inherently discrete nature of the problem. However, in recent years, researchers have shifted towards enhancing continuous optimization algorithms and incorporating constraints to address WFLO challenges. This approach has shown remarkable promise, outperforming traditional genetic algorithms and gaining traction among researchers. To further elevate the performance of continuous optimization algorithms in the context of WFLO, we introduce a multi-local search-based SHADE, termed MS-SHADE. MS-SHADE is designed to fine-tune the trade-off between convergence speed and algorithmic diversity, reducing the likelihood of convergence stagnation in WFLO scenarios. To assess the effectiveness of MS-SHADE, we employed a more extensive and intricate wind condition model in our experiments. In a set of 16 problems, MS-SHADE’s average utilization efficiency improved by 0.14% compared to the best algorithm, while the optimal utilization efficiency increased by 0.3%. The results unequivocally demonstrate that MS-SHADE surpasses state-of-the-art WFLO algorithms by a significant margin.
Learning Abstract Chemistry Concepts with Virtual Reality: An Experimental Study Using a VR Chemistry Lab and Molecule Simulation
Authors: Hu-Au Elliot
Published: August 2024

In this 2 × 2 between-subject experimental study, a virtual reality (VR) laboratory simulation is paired with a VR molecular world intervention to teach chemistry concepts. The independent variables are the implementation timing of the molecular world intervention (Pre-lab vs. Integrated) and the level of embodiment (Traditional vs. VR). Eighty students (N = 80), ages 11–18 years old, from a community center in New York City participated, completing a pretest, a laboratory simulation, a molecular intervention, and a post-test. The pre- and post-test measures included multiple-choice, free-response, and drawing questions. A key finding was that integrating the intervention within the lab simulation, no matter which level of embodiment, led to significantly higher gains in learning. The combination of using physical manipulatives and integrating them within the lab exercise (Integrated Traditional condition) demonstrated the greatest gains overall. On drawing measures, the Integrated VR condition showed significant improvement in three out of the four drawing categories (i.e., molecule shape, atom quantity, and relative sizes). The implications are that even though using a VR molecular world intervention can lead to significant learning of abstract chemistry content, the use of physical manipulatives is still a more effective tool.
A Review of Multifunctional Antenna Designs for Internet of Things
Authors: Arnaoutoglou Dimitrios G. , Empliouk Tzichat M. , Kaifas Theodoros N. F. , Chryssomallis Michael T. , Kyriacou George
Published: August 2024

The Internet of Things (IoT) envisions the interconnection of all electronic devices, ushering in a new technological era. IoT and 5G technology are linked, complementing each other in a manner that significantly enhances their impact. As sensors become increasingly embedded in our daily lives, they transform everyday objects into “smart” devices. This synergy between IoT sensor networks and 5G creates a dynamic ecosystem where the infrastructure provided by 5G’s high-speed, low-latency communication enables IoT devices to function more efficiently and effectively, paving the way for innovative applications and services that enhance our awareness and interactions with the world. Moreover, application-oriented and multifunctional antennas need to be developed to meet these high demands. In this review, a comprehensive analysis of IoT antennas is conducted based on their application characteristics. It is important to note that, to the best of our knowledge, this is the first time that this categorization has been performed in the literature. Indeed, comparing IoT antennas across different applications without considering their specific operational contexts is not practical. This review focuses on four primary operational fields: smart homes, smart cities, and biomedical and implantable devices.
A Novel Switch Architecture for Multi-Die Optimization with Efficient Connections
Authors: Luo Jifeng , Yu Feng , Li Weijun , Xing Qianjian
Published: August 2024

Switches play a critical role as core components in data center networks. The advent of multi-die chiplet packaging as a prevailing trend in complex chip development presents challenges in designing the multi-die packaging of switch chips. With limited inter-die connections in mind, we propose a scalable, unified switch architecture optimized for efficient connectivity. This architecture includes the strategic mapping of data queues, meticulous planning of data paths, and the integration of a unified interface, all aiming to facilitate efficient switch operations within constrained connectivity environments. Our optimization efforts encompass various areas, including refining arbitration strategies, managing mixed unicast and multicast transmissions, and mitigating network congestion to alleviate bottlenecks in data flow. These enhancements contribute to heightened levels of performance and robustness in the switching process. During the validation phase, the structure we propose reduced interconnection usage between dies by 25%, while supporting functions such as unicast and multicast transmissions.
Optimizing Unmanned Aerial Vehicle Electronics: Advanced Charging Systems and Data Transmission Solutions
Authors: Barrile Vincenzo , La Foresta Fabio , Genovese Emanuela
Published: August 2024

Interest in Unmanned Aerial Vehicles (UAVs) has been increasingly growing in recent years, especially for purposes other than those for which they were initially used (civil and military purposes). Currently, in fact, they are used for advanced monitoring and control purposes, for 3D reconstructions of the territory and cultural heritage, and for freight transport. The problem in using these systems consists of the limited flight autonomy. In fact, commercially used drones, today, are sold with a set of batteries of limited duration which do not allow flights over large areas and, therefore, detailed surveys. The present work seeks to overcome these limitations by proposing an intelligent automatic charging system (Intelligent Charging Network) created using PC Engines Alix and an experimental drone prototype using a Raspberry Pi 3 and a Navio 2 module. At the same time, an efficient Intelligent Charging Network–drone communication system and a data transmission system are proposed, which allow images acquired by the drone to be transferred directly to the server used for data storage for their subsequent processing as well as the transmission of the flight plan from the QGroundControl application to the drone. The proposed system represents technological innovation in the field of drones with potential future developments linked to the implementation of sustainable drones.
A Bibliometric Review of Intrusion Detection Research in IoT: Evolution, Collaboration, and Emerging Trends
Authors: Goranin Nikolaj , Hora Simran Kaur , Čenys Habil Antanas
Published: August 2024

As the IoT market continues to rapidly expand, ensuring the security of IoT systems becomes increasingly critical. This paper aims to identify emerging trends and technologies in IoT intrusion detection. A bibliometric analysis of research trends in IoT intrusion detection, leveraging data from the Web of Science (WoS) repository, is conducted to understand the landscape of publications in this field. The analysis reveals a significant increase in publications on intrusion detection in IoT, indicating growing research interest. Research articles are the leading category of publications, and the analysis also highlights the collaborative linkages among authors, institutions, and nations. Co-occurrence analysis and citation analysis provide insights into the relationships among keywords and the impact of publications. The study also identifies keyword and publication citation burst detection, with recommendations for future research focusing on advanced machine learning techniques to enhance intrusion/anomaly detection. This comprehensive analysis offers valuable guidance for diverse and extensive applications in IoT intrusion detection.
Investigation and Analysis of the Power Quality in an Academic Institution’s Electrical Distribution System
Authors: Alawasa Khaled M. , Al-Badi Abdullah H.
Published: August 2024

The presence of non-linear, time-variant loads in power networks introduces harmonics and other power quality issues in voltage and current waveforms. With the growing prevalence of power electronics, managing harmonic distortion has become a significant challenge in modern power distribution systems. This study aims to assess and analyze power quality at various locations within an academic institution (Sultan Qaboos University). The study encompasses the outputs of PV converters, uninterruptible power supplies (UPS), chillers with variable-speed motors, 11 kV/415 V transformers at both the College of Engineering and the Center of Information Systems, as well as two main substations supplying power to the university (33 kV/11 kV). Data collected—such as harmonic content in current and voltage waveforms and Total Harmonic Distortion (THD)—were meticulously analyzed to identify the factors affecting waveform quality. Measurements were conducted using advanced power quality instruments (Fluke 435-II), and the data were analyzed using MATLAB software. The study reveals that most results adhered to both the Oman grid code and international standards. The findings and methodology presented in this paper provide a critical benchmark for guiding standards compliance as Sultan Qaboos University, and other academic institution, undertakes the modernization of aging equipment and the expansion of new high-tech facilities.
Correction: Kurian et al. Estimation of Carbon Footprint of Residential Building in Warm Humid Climate of India through BIM. Energies 2021, 14, 4237
Authors: Kurian Rosaliya , Kulkarni Kishor Sitaram , Ramani Prasanna Venkatesan , Meena Chandan Swaroop , Kumar Ashok , Cozzolino Raffaello
Published: August 2024

There was an error in the original publication [...]
The Role of Solar Concentrators in Photocatalytic Wastewater Treatment
Authors: Roy Joy Sankar , Messaddeq Younès
Published: August 2024

The global challenge of sustainable and affordable wastewater treatment technology looms large as water pollution escalates steadily with the rapid pace of industrialization and population growth. The photocatalytic wastewater treatment is a cutting-edge and environmentally friendly technology that uses photons from light source to degrade and remove organic and inorganic contaminants from water. Thus, utilizing solar energy for photocatalytic wastewater treatment holds great promise as a renewable solution to alleviate pressures on the global water crisis. Employing solar concentrators to intensify sunlight for photocatalysis represents a promising avenue for future applications of a low-cost and rapid sustainable wastewater purification process. This groundbreaking approach will unveil fresh technological avenues for a cost-effective, sustainable, and swift wastewater purification process utilizing sunlight. This review article explores diverse solar concentrating systems and their potential applications in the wastewater treatment process.
A Techno-Economic Assessment of DC Fast-Charging Stations with Storage, Renewable Resources and Low-Power Grid Connection
Authors: Singh Gurpreet , D’Arpino Matilde , Goveas Terence
Published: August 2024

The growing demand for high-power DC fast-charging (DCFC) stations for electric vehicles (EVs) is expected to lead to increased peak power demand and a reduction in grid power quality. To maximize the economic benefits and station utilization under practical constraints set by regulatory authorities, utilities and DCFC station operators, this study explores and provides methods for connecting DCFC stations to the grid, employing low-power interconnection rules and distributed energy resources (DERs). The system uses automotive second-life batteries (SLBs) and photovoltaic (PV) systems as energy buffer and local energy resources to support EV charging and improve the station techno-economic feasibility through load shifting and charge sustaining. The optimal sizing of the DERs and the selection of the grid interconnection topology is achieved by means of a design space exploration (DSE) and exhaustive search approach to maximize the economic benefits of the charging station and to mitigate high-power demand to the grid. Without losing generality, this study considers a 150 kW DCFC station with a range of DER sizes, grid interconnection specifications and related electricity tariffs of American Electric Power (AEP) Ohio and the Public Utility Commission of Ohio (PUCO). Various realistic scenarios and strategies are defined to account for the interconnection requirements of the grid to the DCFC with DERs. The system’s techno-economic performance over a ten-year period for different scenarios is analyzed and compared using a multitude of metrics. The results of the analysis show that the the integration of DERs in DCFC stations has a positive impact on the economic value of the investment when compared to traditional installations.
Inhibition of Soil Wind-Erosion and Dust by Shelterbelts in the Hilly Area of Loess Plateau and Its Influencing Factors
Authors: Yan Bing , Cui Yue , Fan Mingyuan , Li Zhixue , Sun Libo , Chang Xiaomin
Published: August 2024

The Loess Plateau is an important source of particulate matter pollution in North China. In order to establish and repair shelterbelts and improve their function of inhibiting wind erosion and dust, four typical shelterbelts (Populus simonii, Pinus tabulaeformis Carr., Pinus tabulaeformis Carr. × Populus simonii and Caragana korshinskii Kom.) were selected to investigate the inhibition rate of soil wind-erosion and the reduction rates of PM1, PM2.5 and PM10 by stand type, stand structure and soil properties. A sample plot survey and semi-fixed observation method were used to measure wind speed and particulate matter concentration and to calculate wind protection effect, sand transport rate, vertical flux of particulate matter, wind-erosion inhibition rate and particulate matter reduction rate. The results showed that the Pinus tabulaeformis Carr. forest and Caragana korshinskii Kom. forest had the best windproofing effect, at 2 m (82.9% ± 23.8%) and 0.5 m (54.4% ± 21.5%), respectively. The distribution curve of the sediment flux of shelterbelts is a logarithmic function. The wind-erosion inhibition rate and PM1 reduction rate of the Pinus tabulaeformis Carr. forest were significantly greater than those of other stand types (p < 0.05). The generalized linear mixed model (GLMM) shows that the DBH variation coefficient (CV) can effectively explain the reduction rate of PM1. It is suggested that policies be enacted to add or replace Pinus tabulaeformis Carr. forest in polluted areas to prevent wind erosion and dust.
Simulation of LUCC Scenarios and Analysis of the Driving Force of Carbon Stock Supply Changes in the North China Plain in the Context of Urbanization
Authors: Ma Dongling , Huang Qingji , Wang Qian , Lin Zhenxin , Xu Hailong
Published: August 2024

The North China Plain is the core region of China’s economic development, and exploring the impacts of its land use and cover change (LUCC) and different urbanization regional drivers on carbon stocks is conducive to promoting sustainable development and carbon balance within the region. In the study, the North China Plain was selected as the study area, and the Patch-Generating Land Use Simulation (PLUS) model and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model were comprehensively applied to set up three land use policies, predict land use changes in 2030, and calculate carbon stock changes. Meanwhile, the Extreme Gradient Boosting (XGBoost) algorithm was used to analyze the degree of influence of different drivers on the supply of carbon stocks in different urbanization regions. Studies show that if the North China Plain prioritizes economic development, the area of farmland and forests will significantly decrease, leading to a substantial decline in carbon stocks. If ecological protection is the development focus, the reduction in farmland and forests will be less, and carbon stocks will remain relatively stable. If farmland protection is the development focus, the reduction in farmland will be minimal, but there will still be some impact on carbon stocks. The driving forces of carbon stock supply vary significantly across different regions. In underdeveloped regions, population density and vegetation cover have a greater impact on carbon stocks. In developing and urban–rural combined regions, vegetation cover and population migration have a greater impact on carbon stocks. In developed regions, the area of artificial land and gross domestic product (GDP) have a greater impact on carbon stocks. The study results provide scientific evidence for regional land use planning and policy formulation.
Does Fire Influence the Greenness Index of Trees? Twelve Months to Decode the Answer in a Rarámuri Mixed Forest
Authors: Pompa-García Marín , Rodríguez-Flores Felipa de Jesús , Sigala José A. , Rodríguez-Trejo Dante Arturo
Published: August 2024

Fire is one of the most significant agents of disturbance in forest ecosystems, with implications for their structure and composition. An understanding of its dynamics is essential for the delineation of forest management policies in the context of predicted climate scenarios. Based on the monthly monitoring of greenness index (NDVI) values recorded over one year at the individual crown level, this study aimed to analyze the dynamics of NDVI values for four different genera, growing in a Mexican mixed forest and subjected to a prescribed burn, relative to those of a control (unburned) treatment. The results demonstrated the general effect of burning over time on NDVI values among the genera, with Pinus showing the most significant effect, while the effect on Quercus was not significant. Tree height was related to NDVI values for Pinus and Juniperus in the burned area, where low-growing individuals responded negatively in terms of greenness index values. Further studies are still required, but we can conclude that fire plays a differential role in the dynamics of canopy activity and that tree size is an important variable. The results also contribute to our understanding of forest responses to fire disturbance, providing indicators with which to assess ecosystem stability under the threat of extreme climatic variations.
Study on the Influence Mechanism of the Key Active Structure of Coal Molecules on Spontaneous Combustion Characteristics Based on Extraction Technology
Authors: Guo Jun , Wu Yunfei , Liu Yin , Cai Guobin , Li Dailin , Jin Yan
Published: August 2024

The molecular structure of coal is complex, and the existing research methods are limited, so it is difficult to clarify its influence mechanism on the spontaneous-combustion characteristics of coal. In this paper, the previous extraction, FTIR, TPR, TG-DSC and other experimental results are combined to analyze the extraction weakening effect and the correlation analysis of the spontaneous-combustion characteristic parameters of raffinate coal. The results show that extraction can destroy the connection bond of coal molecules, change the content of dominant active groups in the coal spontaneous-combustion reaction, increase the lower limit of the key temperature nodes of coal spontaneous-combustion or extend the temperature range, resulting in an increase in the ignition-point temperature of coal and a decrease in coal quality. This paper will provide a theoretical basis for the study of the microscopic mechanism of coal spontaneous-combustion and then provide new ideas for the development of an active prevention and control technology for coal spontaneous-combustion.
First Insights into the Migration Route and Spatial Distribution of the Endangered Chinese Sturgeon (Acipenser sinensis) in the Yangtze River Estuary
Authors: Zhu Jiazhi , Guo Wentao , Li Zhiyuan , Jiang Wei
Published: August 2024

Chinese sturgeon (Acipenser sinensis) is an endangered species, and the Yangtze River Estuary is an important migration channel for this species. With the scale of Chinese sturgeon restocking along the Yangtze River gradually increasing, an increasing number of artificially bred Chinese sturgeon will come to the estuary. It is urgent to make the first insights about the distribution characteristics and migration strategy of the endangered Chinese sturgeon in the Yangtze River Estuary available. So, to balance the need for information about this endangered species and its conservation, a total of 14 Chinese sturgeons were released in the waters near Chongming Island on 9 April 2021 and 20 October 2022, and 50% of them have been successfully recovered. The data demonstrated that Chinese sturgeon had a good migration ability in the Yangtze River Estuary and its adjacent waters. One sturgeon returned to the freshwater area of the estuary after spending approximately 46 days in the sea at a maximum depth of 54.5 m, and two sturgeons returned to the Yangtze River mainstream within 3.5 days after release. We propose that the Northern Channel of the estuary may be the main passway for Chinese sturgeon to undertake the river–sea migration. The bycatch data of Chinese sturgeon showed that this species may prefer the southern area of the estuary. We hypothesize that the food resources and salinity regime are the main factors that promote Chinese sturgeon to enter the shoals around the coast of Chongming Island. The ocean currents, river runoff, salinity, and food resource may affect the distribution of Chinese sturgeon along the Chinese coast. Future work on the conservation of Chinese sturgeon should focus on the marine life history and continuously enrich the research data to improve conservation strategies.
Variation in the Aroma Composition of Jasmine Tea with Storage Duration
Authors: Qi Zihao , Huang Wenjing , Liu Qiuyan , Ning Jingming
Published: August 2024

This study investigated the changes in the aroma of jasmine tea during storage. Solid-phase micro-extraction (SPME)–gas chromatography (GC)-mass spectrometry (MS) and stir bar sorptive extraction (SBSE)-GC-MS were combined to detect all volatile compounds. GC-olfactometry (GC-O), odor activity value (OAV), and p-value were employed to analyze and identify the key aroma compounds in six jasmine tea samples stored for different durations. Nine key aroma compounds were discovered, namely (Z)-3-hexen-1-yl acetate, methyl anthranilate, methyl salicylate, trans-β-ionone, linalool, geraniol, (Z)-4-heptenal, benzoic acid methyl ester, and benzoic acid ethyl ester. The importance of these compounds was confirmed through the aroma addition experiment. Correlation analysis showed that (Z)-4-heptenal might be the main reason for the increase in the stale aroma of jasmine tea. Through sensory evaluation and specific experimental analysis, it can be concluded that jasmine tea had the best aroma after 3 years of storage, and too long a storage time may cause the overall aroma of the tea to weaken and produce an undesirable odor. The findings can provide a reference for the change in aroma during the storage of jasmine tea and provide the best storage time (3 years) in terms of jasmine tea aroma.
On New Generalized Hermite–Hadamard–Mercer-Type Inequalities for Raina Functions
Authors: Çiftci Zeynep , Coşkun Merve , Yildiz Çetin , Cotîrlă Luminiţa-Ioana , Breaz Daniel
Published: August 2024

In this research, we demonstrate novel Hermite–Hadamard–Mercer fractional integral inequalities using a wide class of fractional integral operators (the Raina fractional operator). Moreover, a new lemma of this type is proved, and new identities are obtained using the definition of convex function. In addition to a detailed derivation of a few special situations, certain known findings are summarized. We also point out that some results in this study, in some special cases, such as setting α=0=φ,γ=1, and w=0,σ(0)=1,λ=1, are more reasonable than those obtained. Finally, it is believed that the technique presented in this paper will encourage additional study in this field.
Advanced Observation-Based Bipartite Containment Control of Fractional-Order Multi-Agent Systems Considering Hostile Environments, Nonlinear Delayed Dynamics, and Disturbance Compensation
Authors: Khan Asad , Javeed Muhammad Awais , Rehman Saadia , Niazi Azmat Ullah Khan , Zhong Yubin
Published: August 2024

This paper introduces an advanced observer-based control strategy designed for fractional multi-agent systems operating in hostile environments. We take into account the dynamic nature of the agents with nonlinear delayed dynamics and consider external disturbances affecting the system. The manuscript presents an improved observation-based control approach tailored for fractional-order multi-agent systems functioning in challenging conditions. We also establish various applicable conditions governing the creation of observers and disturbance compensation controllers using the fractional Razmikhin technique, signed graph theory, and matrix transformation. Furthermore, our investigation includes observation-based control on switching networks by employing a typical Lyapunov function approach. Finally, the effectiveness of the proposed strategy is demonstrated through the analysis of two simulation examples.
Blackcurrant Pomace Extract as a Natural Antioxidant in Vienna Sausages Reformulated by Replacement of Pork Backfat with Emulsion Gels Based on High Oleic Sunflower and Flaxseed Oils
Authors: Cîrstea (Lazăr) Nicoleta , Nour Violeta , Corbu Alexandru Radu , Codină Georgiana Gabriela
Published: August 2024

The incorporation of a blackcurrant pomace extract (BPE) at 2.5%, 5.0% and 10.0% into an emulsion gel based on high oleic sunflower and linseed oils was examined in order to obtain a functional ingredient to be used as a pork backfat replacer in Vienna sausages. The replacement of the pork backfat with the control emulsion gel reduced the cooking loss but negatively affected the color by decreasing L* and a* values as compared with the traditional product. A decrease in the n-6/n-3 ratio from 10.99 to around 1.54 (by 7 times) was achieved through reformulation, while the PUFA/SFA ratio increased from 0.49 to 1.09. The incorporation of BPE did not have a major impact on the fatty acid profile and improved color by increasing redness, but negatively affected the texture by increasing hardness, gumminess and share force as compared with the sausages reformulated without extract. BPE reduced the pH and the thermal stability of the emulsion gels, increased cooking loss and decreased moisture retention in sausages. BPE increased the oxidative stability of Vienna sausages enriched in polyunsaturated fatty acids; however, the incorporation of BPE into the emulsion gels above 5% affected the sensory scores for appearance, texture and general acceptability of the reformulated sausages.