bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Influence of Compression and Offset of Cushion Blocks on the Axial Strength of Transformers
Authors: Sun Lu , Gao Shuguo , Li Tianran , Yao Jiaxin , Wang Ping , Zhu Jianhao
Published: December 2023

The instability of the winding-cushion structure is one of the primary causes of transformer failures. Insulation cushion compression and offset are the predominant forms leading to structural instability. Therefore, this paper, using the SFSZ7-31500/110 transformer as an example, first derives the theoretical formula for mechanical stress calculation. It clarifies the key influencing parameters of the winding-cushion block structure on the axial bending stress of the winding. Subsequently, an electromagnetic force finite element calculation model is established to obtain the axial force distribution in the winding and the distribution of unbalanced displacement during short-circuit processes. Based on the force and offset distribution, a specific cushion block compression and offset test platform is constructed. By setting different cushion block variables, the effects of cushion block unbalanced height and cushion block offset on the winding’s bending elastic modulus are determined. Finally, a simulation model for stress calculation of the winding-cushion block structure is established, revealing the influence pattern of cushion block compression and offset instability on the axial strength of the winding. The results of this study indicate that the greater the uneven cushion block height, the lower the axial strength of the winding. Under the same cushion block offset angle, winding structures with non-uniform cushion block offsets exhibit the worst axial stability. When the offset angles are 30°, 45°, and 60°, the maximum axial bending stress of the winding increases by 1.73%, 3.46%, and 7.82%, respectively. Increasing the offset angle exacerbates the decrease in the axial strength of the winding up to a certain extent. The findings in this study have significant implications for enhancing a transformer’s short-circuit resistance.
Fusion of SoftLexicon and RoBERTa for Purpose-Driven Electronic Medical Record Named Entity Recognition
Authors: Cui Xiaohui , Yang Yu , Li Dongmei , Qu Xiaolong , Yao Lei , Luo Sisi , Song Chao
Published: December 2023

Recently, researchers have extensively explored various methods for electronic medical record named entity recognition, including character-based, word-based, and hybrid methods. Nonetheless, these methods frequently disregard the semantic context of entities within electronic medical records, leading to the creation of subpar-quality clinical knowledge bases and obstructing the discovery of clinical knowledge. In response to these challenges, we propose a novel purpose-driven SoftLexicon-RoBERTa-BiLSTM-CRF (SLRBC) model for electronic medical records named entity recognition. SLRBC leverages the fusion of SoftLexicon and RoBERTa to incorporate the word lexicon information from electronic medical records into the character representations, enhancing the model’s semantic embedding representations. This purpose-driven approach helps achieve a more comprehensive representation and avoid common segmentation errors, consequently boosting the accuracy of entity recognition. Furthermore, we employ the classical BiLSTM-CRF framework to capture contextual information of entities more effectively. In order to assess the performance of SLRBC, a series of experiments on the public datasets of CCKS2018 and CCKS2019 were conducted. The experimental results demonstrate that SLRBC can efficiently extract entities from Chinese electronic medical records. The model attains F1 scores of 94.97% and 85.40% on CCKS2018 and CCKS2019, respectively, exhibiting outstanding performance in the extraction and utilization efficiency of clinical information.
Research on Hail Mechanism Features Based on Dual-Polarization Radar Data
Authors: Li Na , Zhang Jun , Wang Di , Wang Ping
Published: December 2023

Hail is a type of severe convective weather disaster characterized by abundant water vapor and strong updrafts, resulting in intense and high reflectivity echoes in hail clouds, often accompanied by an overhanging form. Although hail research has made great progress, it is still challenging to achieve accurate identification of hail. Compared with traditional radar, dual-polarization radar can output a variety of polarization parameters and provide information about the shape and phase of precipitation particles, which is conducive to the identification of hail particles. In this study, dual-polarization radar data are used to explore more hail features from various perspectives, starting with the morphological characteristics of hail clouds and using common feature extraction methods in the field of image processing. A comprehensive approach to high-dimensional features is developed. Using machine learning methods, hail identification models are constructed in both the traditional mechanism feature space and the new feature space constructed in this study. Experimental results strongly confirm the significant effectiveness of the five-dimensional new mechanism features developed in this paper for hail identification.
Coefficient Inequalities for q-Convex Functions with Respect to q-Analogue of the Exponential Function
Authors: Khan Majid , Khan Nazar , Tawfiq Ferdous M. O. , Ro Jong-Suk
Published: December 2023

In mathematical analysis, the q-analogue of a function refers to a modified version of the function that is derived from q-series expansions. This paper is focused on the q-analogue of the exponential function and investigates a class of convex functions associated with it. The main objective is to derive precise inequalities that bound the coefficients of these convex functions. In this research, the initial coefficient bounds, Fekete–Szegő problem, second and third Hankel determinant have been determined. These coefficient bounds provide valuable information about the behavior and properties of the functions within the considered class.
Multiagent-Based Control for Plug-and-Play Batteries in DC Microgrids with Infrastructure Compensation
Authors: Al-Saadi Mudhafar , Short Michael
Published: December 2023

The influence of the DC infrastructure on the control of power-storage flow in micro- and smart grids has gained attention recently, particularly in dynamic vehicle-to-grid charging applications. Principal effects include the potential loss of the charge–discharge synchronization and the subsequent impact on the control stabilization, the increased degradation in batteries’ health/life, and resultant power- and energy-efficiency losses. This paper proposes and tests a candidate solution to compensate for the infrastructure effects in a DC microgrid with a varying number of heterogeneous battery storage systems in the context of a multiagent neighbor-to-neighbor control scheme. Specifically, the scheme regulates the balance of the batteries’ load-demand participation, with adaptive compensation for unknown and/or time-varying DC infrastructure influences. Simulation and hardware-in-the-loop studies in realistic conditions demonstrate the improved precision of the charge–discharge synchronization and the enhanced balance of the output voltage under 24 h excessively continuous variations in the load demand. In addition, immediate real-time compensation for the DC infrastructure influence can be attained with no need for initial estimates of key unknown parameters. The results provide both the validation and verification of the proposals under real operational conditions and expectations, including the dynamic switching of the heterogeneous batteries’ connection (plug-and-play) and the variable infrastructure influences of different dynamically switched branches. Key observed metrics include an average reduced convergence time (0.66–13.366%), enhanced output-voltage balance (2.637–3.24%), power-consumption reduction (3.569–4.93%), and power-flow-balance enhancement (2.755–6.468%), which can be achieved for the proposed scheme over a baseline for the experiments in question.
Risk for Seasonal Affective Disorder (SAD) Linked to Circadian Clock Gene Variants
Authors: Dang Thanh , Russel William A. , Saad Tazmilur , Dhawka Luvna , Ay Ahmet , Ingram Krista K.
Published: December 2023

Molecular pathways affecting mood are associated with circadian clock gene variants and are influenced, in part, by the circadian clock, but the molecular mechanisms underlying this link are poorly understood. We use machine learning and statistical analyses to determine the circadian gene variants and clinical features most highly associated with symptoms of seasonality and seasonal affective disorder (SAD) in a deeply phenotyped population sample. We report sex-specific clock gene effects on seasonality and SAD symptoms; genotypic combinations of CLOCK3111/ZBTB20 and PER2/PER3B were significant genetic risk factors for males, and CRY2/PER3C and CRY2/PER3-VNTR were significant risk factors for females. Anxiety, eveningness, and increasing age were significant clinical risk factors for seasonality and SAD for females. Protective factors for SAD symptoms (in females only) included single gene variants: CRY1-GG and PER3-VNTR-4,5. Clock gene effects were partially or fully mediated by diurnal preference or chronotype, suggesting multiple indirect effects of clock genes on seasonality symptoms. Interestingly, protective effects of CRY1-GG, PER3-VNTR-4,5, and ZBTB20 genotypes on seasonality and depression were not mediated by chronotype, suggesting some clock variants have direct effects on depressive symptoms related to SAD. Our results support previous links between CRY2, PER2, and ZBTB20 genes and identify novel links for CLOCK and PER3 with symptoms of seasonality and SAD. Our findings reinforce the sex-specific nature of circadian clock influences on seasonality and SAD and underscore the multiple pathways by which clock variants affect downstream mood pathways via direct and indirect mechanisms.
Irisin Enhances Mitochondrial Function in Osteoclast Progenitors during Differentiation
Authors: Estell Eben , Ichikawa Tsunagu , Giffault Paige , Bonewald Lynda , Spiegelman Bruce , Rosen Clifford
Published: December 2023

Irisin is a myokine released from muscle during exercise with distinct signaling effects on tissues throughout the body, including an influence on skeletal remodeling. Our previous work has shown that irisin stimulates resorption, a key first step in bone remodeling, by enhancing osteoclastogenesis. The present study further investigates the action of irisin on the metabolic function of osteoclast progenitors during differentiation. Fluorescent imaging showed increased mitochondrial content and reactive oxygen species production with irisin treatment in osteoclast progenitors after 48 h of osteoclastogenic culture. Mitochondrial stress testing demonstrated a significant increase in maximal oxygen consumption rate and spare capacity after 48 h of preconditioning with irisin treatment. Together, these findings further elucidate the stimulatory action of irisin on osteoclastogenesis, demonstrating an enhancement of metabolism through mitochondrial respiration in the progenitor to support the energy demands of their differentiation into mature osteoclasts.
Altered Red Blood Cell Fatty Acid and Serum Adipokine Profiles in Subjects with Obesity
Authors: Léniz Asier , Fernández-Quintela Alfredo , Arranz Sara , Portune Kevin , Tueros Itziar , Arana Eunate , Castaño Luis , Velasco Olaia , Portillo María P.
Published: December 2023

Background: Adipokines, as well as the fatty acid profile of red blood cell (RBC) membranes, are known to play important roles in the development and progression of metabolic complications induced by obesity. Thus, the objective of this study is to compare the serum adipokine profile and the RBC membrane fatty acid profile of normal-weight and obese adults, and to analyze their relationship with serum biochemical parameters. Methods: An observational case–control study was performed in 75 normal-weight and obese adult subjects. Biochemical serum parameters, eight serum adipokines and the RBC membrane fatty acid profiles were measured. Associations between parameters were established using regression analysis. Results: Subjects with obesity showed increased levels of leptin, fibroblast growth factor 21 (FGF21) and overexpressed nephroblastoma (NOV/CCN3), decreased adiponectin, and similar levels of vaspin and chemerin compared to normal-weight subjects. Significant positive and negative correlations were found with triglycerides and high-density lipoprotein-cholesterol (HDL-c), respectively. An increase in the total ω-6 fatty acids in the RBC membrane fatty acid profiles in subjects with obesity was observed, because of higher levels of both dihomo-γ-linolenic acid (DGLA) and arachidonic acid (AA), and decreased total ω-3 fatty acids, mainly due to lower levels of docosahexaenoic acid (DHA). The ω-6/ω-3 ratio in the RBCs was significantly higher, suggesting an inflammatory status, as was also suggested by a reduced adiponectin level. A negative association between DGLA and adiponectin, and a positive association between DHA and serum triglycerides, was observed. Conclusions: Important alterations in serum adipokine and RBC fatty acid profiles are found in subjects with obesity.
Kepler Algorithm for Large-Scale Systems of Economic Dispatch with Heat Optimization
Authors: Hakmi Sultan Hassan , Shaheen Abdullah M. , Alnami Hashim , Moustafa Ghareeb , Ginidi Ahmed
Published: December 2023

Combined Heat and Power Units Economic Dispatch (CHPUED) is a challenging non-convex optimization challenge in the power system that aims at decreasing the production cost by scheduling the heat and power generation outputs to dedicated units. In this article, a Kepler optimization algorithm (KOA) is designed and employed to handle the CHPUED issue under valve points impacts in large-scale systems. The proposed KOA is used to forecast the position and motion of planets at any given time based on Kepler’s principles of planetary motion. The large 48-unit, 96-unit, and 192-unit systems are considered in this study to manifest the superiority of the developed KOA, which reduces the fuel costs to 116,650.0870 USD/h, 234,285.2584 USD/h, and 487,145.2000 USD/h, respectively. Moreover, the dwarf mongoose optimization algorithm (DMOA), the energy valley optimizer (EVO), gray wolf optimization (GWO), and particle swarm optimization (PSO) are studied in this article in a comparative manner with the KOA when considering the 192-unit test system. For this large-scale system, the presented KOA successfully achieves improvements of 19.43%, 17.49%, 39.19%, and 62.83% compared to the DMOA, the EVO, GWO, and PSO, respectively. Furthermore, a feasibility study is conducted for the 192-unit test system, which demonstrates the superiority and robustness of the proposed KOA in obtaining all operating points between the boundaries without any violations.
Living Lab-Based Service Interaction Design for a Companion Robot for Seniors in South Korea
Authors: Kwon Ju Yeong , Ju Da Young
Published: December 2023

A living lab is a valuable method for designing tangible and intangible service elements, ensuring a comprehensive user experience. Developing a digital companion service, which users may be unfamiliar with, requires observing user behavior in real-world environments and analyzing living and behavioral patterns. A living lab starts with understanding user characteristics and behaviors. Living lab methods have an impact on the accuracy and precision of service design. The number of seniors in South Korea is rapidly increasing, leading to a rise in social issues like solitary deaths and suicide. Addressing these problems has led to a growing demand for companion robots. To design effective companion services, understanding seniors’ living environments and their cognitive and behavioral traits is essential. This opinion piece, based on a national R&D project, presents the development of a digital companion for seniors. It offers insights, providing a comprehensive overview of living lab-based service interaction design and proposing methodologies about living lab environment construction and experimentation and considerations when designing robot interaction functions and appearance. The living lab environment includes real living spaces, laboratories, virtual reality settings, and senior welfare centers. Using the research findings, we created service scenarios, analyzed senior language characteristics, and developed the concept and facial expressions of the digital companion. To successfully introduce a novel service, it is crucial to analyze users’ real-life behavior and adjust the service accordingly.
Deep CNN-Based Static Modeling of Soft Robots Utilizing Absolute Nodal Coordinate Formulation
Authors: El-Hussieny Haitham , Hameed Ibrahim A. , Nada Ayman A.
Published: December 2023

Soft continuum robots, inspired by the adaptability and agility of natural soft-bodied organisms like octopuses and elephant trunks, present a frontier in robotics research. However, exploiting their full potential necessitates precise modeling and control for specific motion and manipulation tasks. This study introduces an innovative approach using Deep Convolutional Neural Networks (CNN) for the inverse quasi-static modeling of these robots within the Absolute Nodal Coordinate Formulation (ANCF) framework. The ANCF effectively represents the complex non-linear behavior of soft continuum robots, while the CNN-based models are optimized for computational efficiency and precision. This combination is crucial for addressing the complex inverse statics problems associated with ANCF-modeled robots. Extensive numerical experiments were conducted to assess the performance of these Deep CNN-based models, demonstrating their suitability for real-time simulation and control in statics modeling. Additionally, this study includes a detailed cross-validation experiment to identify the most effective model architecture, taking into account factors such as the number of layers, activation functions, and unit configurations. The results highlight the significant benefits of integrating Deep CNN with ANCF models, paving the way for advanced statics modeling in soft continuum robotics.
Advanced Applications of Silk-Based Hydrogels for Tissue Engineering: A Short Review
Authors: Akdag Zekiye , Ulag Songul , Kalaskar Deepak M. , Duta Liviu , Gunduz Oguzhan
Published: December 2023

Silk has been consistently popular throughout human history due to its enigmatic properties. Today, it continues to be widely utilized as a polymer, having first been introduced to the textile industry. Furthermore, the health sector has also integrated silk. The Bombyx mori silk fibroin (SF) holds the record for being the most sustainable, functional, biocompatible, and easily produced type among all available SF sources. SF is a biopolymer approved by the FDA due to its high biocompatibility. It is versatile and can be used in various fields, as it is non-toxic and has no allergenic effects. Additionally, it enhances cell adhesion, adaptation, and proliferation. The use of SF has increased due to the rapid advancement in tissue engineering. This review comprises an introduction to SF and an assessment of the relevant literature using various methods and techniques to enhance the tissue engineering of SF-based hydrogels. Consequently, the function of SF in skin tissue engineering, wound repair, bone tissue engineering, cartilage tissue engineering, and drug delivery systems is therefore analysed. The potential future applications of this functional biopolymer for biomedical engineering are also explored.
MLBRSA: Multi-Learning-Based Reptile Search Algorithm for Global Optimization and Software Requirement Prioritization Problems
Authors: Kailasam Jeyaganesh Kumar , Nalliah Rajkumar , Nallagoundanpalayam Muthusamy Saravanakumar , Manoharan Premkumar
Published: December 2023

In the realm of computational problem-solving, the search for efficient algorithms tailored for real-world engineering challenges and software requirement prioritization is relentless. This paper introduces the Multi-Learning-Based Reptile Search Algorithm (MLBRSA), a novel approach that synergistically integrates Q-learning, competitive learning, and adaptive learning techniques. The essence of multi-learning lies in harnessing the strengths of these individual learning paradigms to foster a more robust and versatile search mechanism. Q-learning brings the advantage of reinforcement learning, enabling the algorithm to make informed decisions based on past experiences. On the other hand, competitive learning introduces an element of competition, ensuring that the best solutions are continually evolving and adapting. Lastly, adaptive learning ensures the algorithm remains flexible, adjusting the traditional Reptile Search Algorithm (RSA) parameters. The application of the MLBRSA to numerical benchmarks and a few real-world engineering problems demonstrates its ability to find optimal solutions in complex problem spaces. Furthermore, when applied to the complicated task of software requirement prioritization, MLBRSA showcases its capability to rank requirements effectively, ensuring that critical software functionalities are addressed promptly. Based on the results obtained, the MLBRSA stands as evidence of the potential of multi-learning, offering a promising solution to engineering and software-centric challenges. Its adaptability, competitiveness, and experience-driven approach make it a valuable tool for researchers and practitioners.
Antibody Profiling: Kinetics with Native Biomarkers for Diagnostic Assay and Drug Developments
Authors: Jucknischke Ute , Friebe Sebastian , Rehle Markus , Quast Laura , Schmidt Sven H.
Published: December 2023

Despite remarkable progress in applied Surface Plasmon Resonance (SPR)-based methods, concise monitoring of kinetic properties for native biomarkers from patient samples is still lacking. Not only are low concentrations of native targets in patient samples, often in the pM range, a limiting and challenging factor, but body fluids as complex matrices furthermore complicate measurements. The here-described method enables the determination of kinetic constants and resulting affinities for native antigens from patients’ cerebrospinal fluid (CSF) and sera binding to antibodies. Using a significantly extended target-enrichment step, we modified a common sandwich-assay protocol, based on a primary and secondary antibody. We successfully analyze antibody kinetics of native targets from a variety of origins, with consistent results, independent of their source. Moreover, native neurofilament light chain (NFL) was investigated as an exemplary biomarker. Obtained data reveal antibodies recognizing recombinant NFL with high affinities, while showing no, or only significantly weakened binding to native NFL. The indicated differences for recombinant vs. native material demonstrate another beneficial application. Our assay is highly suitable for gaining valuable insights into characteristics of native biomarkers, thus impacting on the binder development of diagnostic reagents or pharmaceutical drugs.
The Green Mirror: Reflecting on Sustainability Reporting Practices of Indian and Australian Real Estate Stakeholders
Authors: Tirumala Raghu Dharmapuri , Upadhyay Kruti
Published: December 2023

Within the real estate sector, the concept of sustainability has traditionally been associated with green building initiatives. This study broadens the scope by examining environmental disclosure practices across a spectrum of stakeholders, including developers, financiers, suppliers, and advisors, within the real estate sectors of Australia and India. Utilizing the Global Reporting Initiative (GRI) standards to evaluate environmental reporting, this research scrutinizes publicly disclosed company data to assess the sector’s engagement with sustainability. The findings reveal a pronounced focus on emissions and energy, with less attention to other critical factors like biodiversity, materials, and supplier environmental assessment. This selective disclosure suggests a need for a more holistic approach to sustainability reporting. This study also investigates the influence of regional nuances and the integration of international reporting standards, shedding light on the varied practices of sustainability reporting within the industry. Furthermore, this paper examines the relationship between environmental disclosures and financial performance, measured by the economic value added (EVA). It was observed that environmental disclosures do not show a significant correlation with EVA for companies in either country, indicating that current reporting practices do not directly impact financial outcomes as captured by this metric. These findings offer actionable insights for enhancing reporting practices, encouraging a collective approach to address the environmental impacts of real estate, and contributing to the discourse on responsible environmental stewardship.
An Explainable Evaluation Model for Building Thermal Comfort in China
Authors: Liu Haiyang , Ma Enlin
Published: December 2023

The concentration of atmospheric greenhouse gases is being amplified by human activity. Building energy consumption, particularly for heating and cooling purposes, constitutes a significant proportion of overall energy demand. This research aims to establish a smart evaluation model to understand the thermal requirements of building occupants based on an open-access dataset. This model is beneficial for making reasonable adjustments to building thermal management, based on factors such as different regions and building user characteristics. Employing Bayesian-optimized LightGBM and SHAP (SHapley Additive exPlanations) methods, an explainable machine learning model was developed to evaluate the thermal comfort design of buildings in different areas and with different purpose. Our developed LightGBM model exhibited superior evaluation performance on the test set, outperforming other machine learning models, such as XGBoost and SVR (Support Vector Regression). The SHAP method further helps us to understand the interior evaluation mechanism of the model and the interactive effect among input features. An accurate thermal comfort design for buildings based on the evaluation model can benefit the carbon-neutral strategy.
Wind Effects on Re-Entrant Wing Faces of Plus Plan-Shaped Building
Authors: Kumar Arun , Meena Rahul Kumar , Raj Ritu , Khan Mohammad Iqbal , Khatib Jamal M.
Published: December 2023

The wind flow patterns and pressure distribution around a plus-shaped building are significantly influenced by re-entrant corner dimensions and building height. The present study aims to find the wind effects and study the pressure distribution with different flow patterns. The building has a plan area of approximately 300 square meters and a height of 50 m, maintaining equal lengths for the re-entrant corners. The research study is performed using the ANSYS CFX academic version. The study employs diverse visualizations, featuring the pressure coefficient (CPe), vertical and specific surface streamlines, and pressure contours. Wind incidence angles for the study are varied from 0° to 90° at an interval of 15°. Building dimensions are scaled down as per the ASCE wind tunnel test manual, and the length scale is kept at 1:100 for CFD investigation. This approach yields crucial insights into the circulation of wind patterns and the distribution of pressure across a wide range of wind incidence angles. The influence of streamlines in the bottom portion of the building model is relatively minimal. In contrast to the upper portion, the bottom exhibits robust vortices, particularly for the wind angles varying from 0° to 30°. Positive pressure is observed on the windward face, and the leeward face and side face exhibit negative pressure. This study furnishes valuable insights into flow patterns and pressure distribution across a wide range of wind incidence angles from 0° to 90° at an interval of 15°. These findings contribute significantly to a thorough comprehension of the wind flow patterns and pressure distribution around the plus-shaped building model.
Service Life Design of Concrete Structures Made of High-Volume Limestone Powder Concrete—Case of the Carbonation-Induced Corrosion
Authors: Carević Vedran , Marinković Snežana , Plavšić Jasna , Radović Andrija
Published: December 2023

One of the paths to CO2 emissions reduction in the concrete industry is to use low-clinker cements, providing at the same time the performance of concrete that is adequate for application in concrete structures. This paper explores the impact of the clinker replacement with high amounts of limestone powder (21–70% in the powder phase) on concrete carbonation resistance. To quantify this impact, the empirical relationship between the carbonation resistance and the compressive strength of the high-volume limestone powder concrete (HVLPC) was established. For that purpose, the regression analysis was applied on the experimental results collected from the published research. The service life analysis based on the full probabilistic approach was performed using the fib Model Code 2010 prediction model and proposed empirical relationship. The first-order reliability method (FORM) was applied to solve the limit state function of reinforcement depassivation with a reliability index equal to 1.3. The obtained minimum concrete cover depths were 40–110% higher compared to those prescribed in the current European standard EN 1992-1-1:2004 for indicative strength classes. Based on the full probabilistic analysis, recommended cover depths are given for all carbonation exposure classes, commonly applied concrete strength classes, and service lives of 50 and 100 years.
Simulation of Carbon Emission Reduction in Power Construction Projects Using System Dynamics: A Chinese Empirical Study
Authors: Li Lihong , Shi Jing , Liu Hao , Zhang Ruyu , Guo Chunbing
Published: December 2023

Power construction projects (PCPs) consume a large amount of energy and contribute significantly to carbon emissions. There is relatively little research on carbon emission reduction in PCPs, especially in predicting carbon emission reduction from a dynamic perspective. After identifying the influencing factors that promote the carbon emission reduction effect of PCPs, this study adopted a dynamic analysis method to elucidate the relationship between the variables. A quantitative carbon emission reduction system for PCPs with 51 variables was established using the system dynamics model, and the system simulation was performed using Vensim PLE software. Finally, a sensitivity analysis was conducted on four key factors: R&D investment, the prefabricated construction level, the scale of using energy-saving material, and the energy efficiency of transmission equipment. The results show that: (1) The reduction in carbon emissions from PCPs continues to increase. (2) R&D investment is the most significant factor for improving the carbon emission reduction in PCPs. (3) The value of the above four influencing factors should be increased within a reasonable range so that the four factors can work better to promote the carbon emission reduction effect of PCPs. This paper creatively proposes a dynamic prediction model for carbon emission reduction in the PCP, and the research results provide the scientific basis for government supervision and enterprise decision-making.
Evaluation of Properties of Asphalt Concrete Mixture Using Basalt Aggregate from Jeju Island
Authors: Han Soohyun , Baek Cheolmin
Published: December 2023

In this study, the engineering properties of basalt aggregate used for asphalt road pavement on Jeju Island were evaluated, and the characteristics of the asphalt mixtures used were evaluated to assess the suitability of Jeju Island basalt as road construction material. Chemical composition and surface morphology analysis of the basalt and granite aggregate, engineering characteristics analysis, and filler property evaluation were performed. Mix design was performed, and the basic properties of three asphalt mixtures for the surface, intermediate, and base layers were evaluated. Permanent deformation resistance was evaluated through a wheel tracking test, and moisture resistance was evaluated through a dynamic immersion test and a tensile strength ratio test. The optimum asphalt contents of the asphalt mixture using low-porosity basalt aggregate and high-porosity basalt aggregate were determined to be 5.7% and 5.9% in the surface layer, 5.3% and 5.4% in the intermediate layer, and 4.7% and 5.1% in the base layer, respectively. It was found that the basic properties of the asphalt mixtures satisfied Korean quality standards. The dynamic immersion test results of low-porosity basalt aggregate and high-porosity basalt aggregate were 20% and 10%, respectively, which fall far below the quality standard of 50%. The tensile strength ratios of the basalt asphalt mixtures for the intermediate layer were 0.69 and 0.40, and they were found to increase significantly to 0.87 and 0.80 after the application of a suitable anti-stripping agent. Therefore, it was concluded that in order to apply Jeju Island basalt to asphalt pavement, an appropriate anti-stripping material must be applied.
A Method to Compute Shadow Geometry in Open Building Information Modeling Authoring Tools: Automation of Solar Regulation Checking
Authors: Voivret Charles , Bigot Dimitri , Rivière Garry
Published: December 2023

Building solar protection regulations is essential to save energy in hot climates. The protection performance is assessed using a shading factor computation that models the sky irradiance and the geometry of shadow obstructing the surface of interest. While Building Information Modeling is nowadays a standard approach for practitioners, computing shadow geometry in BIM authoring tools is natively impossible. Methods to compute shadow geometry exist but are out of reach for the usual BIM authoring tool user because of algorithm complexity and non-friendly BIM implementation platform. This study presents a novel approach, dubbed solid clipping, to calculate shadow geometry accurately in a BIM authoring tool. The aim is to enhance project delivery by enabling solar control verification. This method is based on typical Computer Aided Design (CAD) in BIM authoring tools. The method is generic enough to be implemented using any BIM authoring tool’s visual and textual API. This work demonstrates that a thermal regulation, here the French overseas one, can be checked concerning solar protection, thanks to a BIM model. Beyond automation, this paper shows that, by directly leveraging the BIM model, designs presently not feasible by the usual process can be studied and checked.
Source Location Identification in an Ideal Urban Street Canyon with Time-Varying Wind Conditions under a Coupled Indoor and Outdoor Environment
Authors: Dai Yuwei , Hou Minzhang , Wang Haidong , Tu Wanli
Published: December 2023

Source location identification methods are typically applied to steady-state conditions under pure indoor or outdoor environments, but under time-varying wind conditions and coupled indoor and outdoor environments, the applicability is not clear. In this study, we proposed an improved adjoint probability method to identify the pollutant source location with time-varying inflows in street canyons and used scaled outdoor experiment data to verify the accuracy. The change in inflow velocity will affect the airflow structure inside the street canyons. Outdoor wind with a lower temperature will exchange heat with the air with a higher temperature inside the street canyon, taking away part of the heat and reducing the heat of the air inside the street canyons. Moreover, the room opening will produce some air disturbance, which is conducive to the heat exchange between the air near the opening and the outdoor wind. Furthermore, the fluctuations of the upper wind will influence the diffusion of the tracer gas. We conducted three cases to verify the accuracy of the source identification method. The results showed that the conditioned adjoint location probability (CALP) of each case was 0.06, 0.32, and 0.28. It implies that with limited pollutant information, the improved adjoint probability method can successfully identify the source location in the dynamic wind environments under coupled indoor and outdoor conditions.
Evaluation of Ecological Parameters of a Compression Ignition Engine Fueled by Diesel Oil with an Eco Fuel Shot Liquid Catalyst
Authors: Osipowicz Tomasz , Koniuszy Adam , Taustyka Viktar , Abramek Karol Franciszek , Mozga Łukasz
Published: December 2023

This article discusses the potential applications of the Fuel Shot liquid catalyst in compression ignition (CI) engines for reducing toxic substances in exhaust gases. Incorporating catalysts into fuel can optimize the combustion process, consequently reducing the emission of toxic substances into the atmosphere. Toxic compounds, such as nitrogen oxides, particulate matter, and hydrocarbons, adversely affect flora and fauna. Various methods are known for reducing their concentration in engine exhaust gases, one of which is the Fuel Shot liquid catalyst. The authors conducted experiments on a Fiat 1.3 JTD engine with a Common Rail system. The results indicate that the application of the liquid catalyst reduces the content of nitrogen oxides and hydrocarbons in the exhaust gases and slightly decreases fuel consumption. Additionally, investigations were carried out on the engine’s injection apparatus, which was fueled with modified fuel. The findings demonstrate that the fuel additive does not affect the wear of precision parts of fuel injectors and high-pressure pumps.
Novel In Vitro Multienzyme Cascade for Efficient Synthesis of d-Tagatose from Sucrose
Authors: Liu Shuangyu , Tu Wenyu , Ni Ye , Guo Yuanyi , Han Ruizhi
Published: December 2023

d-Tagatose is a rare sugar with low calories, and is extensively used in food, beverage, and drug additives. In this study, an in vitro multienzyme cascade route for d-tagatose synthesis from sucrose (MCTS) was designed, which contains five enzymes (sucrose phosphorylase, fructokinase, d-fructose 6-phosphate 4-epimerase, d-tagatose 6-phosphate phosphatase, and polyphosphate kinase). The whole MCTS route comprised a sucrose phosphorylation reaction, and a phosphorylation–dephosphorylation reaction coupled with an ATP regeneration system. After optimization, the conversion of d-tagatose from 10 mM sucrose reached 82.3%. At an elevated sucrose concentration of 50 mM, 72.4% of d-tagatose conversion and 0.27 g·L–1·h−1 of space–time yield were obtained. Furthermore, ADP consumption decreased to 1% of the sucrose concentration after introducing the ATP regeneration system. The MCTS strategy is an efficient and cost-effective approach for d-tagatose production.
Separable Roles for Neur and Ubiquitin in Delta Signalling in the Drosophila CNS Lineages
Authors: Kalodimou Konstantina , Stapountzi Margarita , Vüllings Nicole , Seib Ekaterina , Klein Thomas , Delidakis Christos
Published: December 2023

The execution of a Notch signal at the plasma membrane relies on the mechanical force exerted onto Notch by its ligand. It has been appreciated that the DSL ligands need to collaborate with a ubiquitin (Ub) ligase, either Neuralized or Mindbomb1, in order to exert this pulling force, but the role of ubiquitylation per se is uncertain. Regarding the Delta–Neur pair, it is documented that neither the Neur catalytic domain nor the Delta intracellular lysines (putative Ub acceptors) are needed for activity. Here, we present a dissection of the Delta activity using the Delta–Notch-dependent expression of Hey in newborn Drosophila neurons as a sensitive in vivo assay. We show that the Delta–Neur interaction per se, rather than ubiquitylation, is needed for activity, pointing to the existence of a Delta–Neur signaling complex. The Neur catalytic domain, although not strictly needed, greatly improves Delta–Neur complex functionality when the Delta lysines are mutated, suggesting that the ubiquitylation of some component of the complex, other than Delta, can enhance signaling. Since Hey expression is sensitive to the perturbation of endocytosis, we propose that the Delta–Neur complex triggers a force-generating endocytosis event that activates Notch in the adjacent cell.
The Sleep Quality- and Myopia-Linked PDE11A-Y727C Variant Impacts Neural Physiology by Reducing Catalytic Activity and Altering Subcellular Compartmentalization of the Enzyme
Authors: Sbornova Irina , van der Sande Emilie , Milosavljevic Snezana , Amurrio Elvis , Burbano Steven D. , Das Prosun K. , Do Helen H. , Fisher Janet L. , Kargbo Porschderek , Patel Janvi , Porcher Latarsha , De Zeeuw Chris I. , Meester-Smoor Magda A. , Winkelman Beerend H. J. , Klaver Caroline C. W. , Pocivavsek Ana , Kelly Michy P.
Published: December 2023

Recently, a Y727C variant in the dual-specific 3′,5′-cyclic nucleotide phosphodiesterase 11A (PDE11A-Y727C) was linked to increased sleep quality and reduced myopia risk in humans. Given the well-established role that the PDE11 substrates cAMP and cGMP play in eye physiology and sleep, we determined if (1) PDE11A protein is expressed in the retina or other eye segments in mice, (2) PDE11A-Y7272C affects catalytic activity and/or subcellular compartmentalization more so than the nearby suicide-associated PDE11A-M878V variant, and (3) Pde11a deletion alters eye growth or sleep quality in male and female mice. Western blots show distinct protein expression of PDE11A4, but not PDE11A1-3, in eyes of Pde11a WT, but not KO mice, that vary by eye segment and age. In HT22 and COS-1 cells, PDE11A4-Y727C reduces PDE11A4 catalytic activity far more than PDE11A4-M878V, with both variants reducing PDE11A4-cAMP more so than PDE11A4-cGMP activity. Despite this, Pde11a deletion does not alter age-related changes in retinal or lens thickness or axial length, nor vitreous or anterior chamber depth. Further, Pde11a deletion only minimally changes refractive error and sleep quality. That said, both variants also dramatically alter the subcellular compartmentalization of human and mouse PDE11A4, an effect occurring independently of dephosphorylating PDE11A4-S117/S124 or phosphorylating PDE11A4-S162. Rather, re-compartmentalization of PDE11A4-Y727C is due to the loss of the tyrosine changing how PDE11A4 is packaged/repackaged via the trans-Golgi network. Therefore, the protective impact of the Y727C variant may reflect a gain-of-function (e.g., PDE11A4 displacing another PDE) that warrants further investigation in the context of reversing/preventing sleep disturbances or myopia.
Regulatory TR3-56 Cells in the Complex Panorama of Immune Activation and Regulation
Authors: Carriero Flavia , Rubino Valentina , Leone Stefania , Montanaro Rosangela , Brancaleone Vincenzo , Ruggiero Giuseppina , Terrazzano Giuseppe
Published: December 2023

The interplay between immune activation and immune regulation is a fundamental aspect of the functional harmony of the immune system. This delicate balance is essential to triggering correct and effective immune responses against pathogens while preventing excessive inflammation and the immunopathogenic mechanisms of autoimmunity. The knowledge of all the mechanisms involved in immune regulation is not yet definitive, and, probably, the overall picture is much broader than what has been described in the scientific literature so far. Given the plasticity of the immune system and the diversity of organisms, it is highly probable that numerous other cells and molecules are still to be ascribed to the immune regulation process. Here, we report a general overview of how immune activation and regulation interact, based on the involvement of molecules and cells specifically dedicated to these processes. In addition, we discuss the role of TR3-56 lymphocytes as a new cellular candidate in the immune regulation landscape.
Coagulation Factor Xa Has No Effects on the Expression of PAR1, PAR2, and PAR4 and No Proinflammatory Effects on HL-1 Cells
Authors: Ruf Lukas , Bukowska Alicja , Gardemann Andreas , Goette Andreas
Published: December 2023

Atrial fibrillation (AF), characterised by irregular high-frequency contractions of the atria of the heart, is of increasing clinical importance. The reasons are the increasing prevalence and thromboembolic complications caused by AF. So-called atrial remodelling is characterised, among other things, by atrial dilatation and fibrotic remodelling. As a result, AF is self-sustaining and forms a procoagulant state. But hypercoagulation not only appears to be the consequence of AF. Coagulation factors can exert influence on cells via protease-activated receptors (PAR) and thereby the procoagulation state could contribute to the development and maintenance of AF. In this work, the influence of FXa on Heart Like-1 (HL-1) cells, which are murine adult atrial cardiomyocytes (immortalized), was investigated. PAR1, PAR2, and PAR4 expression was detected. After incubations with FXa (5–50 nM; 4–24 h) or PAR1- and PAR2-agonists (20 µM; 4–24 h), no changes occurred in PAR expression or in the inflammatory signalling cascade. There were no time- or concentration-dependent changes in the phosphorylation of the MAP kinases ERK1/2 or the p65 subunit of NF-κB. In addition, there was no change in the mRNA expression of the cell adhesion molecules (ICAM-1, VCAM-1, fibronectin). Thus, FXa has no direct PAR-dependent effects on HL-1 cells. Future studies should investigate the influence of FXa on human cardiomyocytes or on other cardiac cell types like fibroblasts.
Cardiovascular Risk Assessment of Elevated Blood Pressure for Screening and Early Detection in Children 6 to 9 Years of Age in the Valencian Community: ANIVA Study
Authors: Morales-Suarez-Varela Maria , Peraita-Costa Isabel , Llopis-Morales Agustin , Navarro Perez Jorge
Published: December 2023

Elevated blood pressure (EBP), hypertension (HT), and prehypertension (PHT), along with the rising prevalence of overweight/obesity in children, correlate with a heightened risk of cardiovascular complications. This study focuses on assessing the prevalence of overweight/obesity and EBP and identifying potential indicators for effective early screening and detection of EBP in children aged 6 to 9 years old. This cross-sectional study was conducted with 1142 students from different schools across the Valencian Community in Spain. Data collection involved administering a questionnaire alongside direct anthropometric measurements of each student. The collected data underwent comprehensive statistical analysis, including frequencies, percentages, means, and chi-square automatic interaction detector (CHAID) analysis. In the sample, 7.5% of the children had HT and 6.8% had PHT, meaning 14.3% presented with EBP. Additionally, 17.0% of the children were classified as overweight and 3.9% as obese. Body mass index >23.1, body fat percentage >20.79%, and Kidmed scores <8 were identified as potential markers for early detection of EBP. The study reveals a significant incidence of EBP and overweight/obesity. Implementing screening protocols for early detection of EBP is imperative to forestall future cardiovascular events. Moreover, lifestyle modifications emerge as the most crucial approach for managing these risk factors.