bluuebunny/crossref_metadata_2025 huggingface dataset:
Inverse Regulation of Cartilage Neogenesis at Physiologically Relevant Calcium Conditions by Human Articular Chondrocytes and Mesenchymal Stromal Cells
Authors: Hammersen Tim , Buchert Justyna , Zietzschmann Severin , Diederichs Solvig , Richter Wiltrud
Published: June 2023

Elaborate bioreactor cultivation or expensive growth factor supplementation can enhance extracellular matrix production in engineered neocartilage to provide sufficient mechanical resistance. We here investigated whether raising extracellular calcium levels in chondrogenic cultures to physiologically relevant levels would provide a simple and inexpensive alternative to enhance cartilage neogenesis from human articular chondrocytes (AC) or bone marrow-derived mesenchymal stromal cells (BMSC). Interestingly, AC and BMSC-derived chondrocytes showed an opposite response to a calcium increase from 1.8 mM to 8 mM by which glycosaminoglycan (GAG) and collagen type II production were elevated during BMSC chondrogenesis but depressed in AC, leading to two-fold higher GAG/DNA values in BMSC-based neocartilage compared to the AC group. According to control treatments with Mg2+ or sucrose, these effects were specific for CaCl2 rather than divalent cations or osmolarity. Importantly, undesired pro-hypertrophic traits were not stimulated by calcium treatment. Specific induction of PTHrP mRNA and protein by 8.0mM calcium only in AC, along with negative effects of recombinant PTHrP1-34 on cartilage matrix production, suggested that the PTHrP pathway contributed to the detrimental effects in AC-based neocartilage. Altogether, raising extracellular calcium levels was discovered as a novel, simple and inexpensive stimulator for BMSC-based cartilage neogenesis without the need for special bioreactors, whereas such conditions should be avoided for AC.
Progress in the Graphene Oxide-Based Composite Coatings for Anticorrosion of Metal Materials
Authors: Tang Shuo , Lei Bing , Feng Zhiyuan , Guo Honglei , Zhang Ping , Meng Guozhe
Published: June 2023

Graphene oxide (GO), derived from the two-dimensional nanosheet graphene, has received unprecedented attention in the field of metal corrosion protection owing to its excellent barrier performance and various active functional groups. In this review, the protection mechanism “labyrinth effect” of composite coatings against metal corrosion was demonstrated systematically. The origination, structure and properties of GO were also analyzed. Their poor dispersion in polymer and tendency to aggregate as nanofillers in composite coatings are the main limitations during application of the coating fillers. In addition, a comprehensive overview on the perspectives of the surface modification of GO and the multi-functionalization of the composite coatings based on GO were given in particular. Green modification methods, reasonable arrangement of GO sheets in composites and development of multi-functional coatings remain challenges in current studies and should be a focus in the future development of GO-based anticorrosive coatings. This review is of value to researchers interested in the design and application of GO in corrosion protection coatings.
Nano–Bio Interface of Molybdenum Disulfide for Biological Applications
Authors: Wu Rongrong , Dong Mingdong , Liu Lei
Published: June 2023

The unique nano–bio interfacial phenomena play a crucial role in the biosafety and bioapplications of nanomaterials. As a representative two-dimensional (2D) nanomaterial, molybdenum disulfide (MoS2) has shown great potential in biological applications due to its low toxicity and fascinating physicochemical properties. This review aims to highlight the nano–bio interface of MoS2 nanomaterials with the major biomolecules and the implications of their biosafety and novel bioapplications. First, the nano–bio interactions of MoS2 with amino acids, peptides, proteins, lipid membranes, and nucleic acids, as well as the associated applications in protein detection, DNA sequencing, antimicrobial activities, and wound-healing are introduced. Furthermore, to facilitate broader biomedical applications, we extensively evaluated the toxicity of MoS2 and discussed the strategies for functionalization through interactions among MoS2 and the variety of macromolecules to enhance the biocompatibility. Overall, understanding the nano–bio interface interaction of two-dimensional nanomaterials is significant for understanding their biocompatibility and biosafety, and further provide guidance for better biological applications in the future.
Optimizing Water Distribution through Explainable AI and Rule-Based Control
Authors: Ferrari Enrico , Verda Damiano , Pinna Nicolò , Muselli Marco
Published: June 2023

Optimizing water distribution both from an energy-saving perspective and from a quality of service perspective is a challenging task since it involves a complex system with many nodes, many hidden variables and many operational constraints. For this reason, water distribution systems need to handle a delicate trade-off between the effectiveness and computational time of the solution. In this paper, we propose a new computationally efficient method, named rule-based control, to optimize water distribution networks without the need for a rigorous formulation of the optimization problem. As a matter of fact, since it is based on a machine learning approach, the proposed method employs only a set of historical data, where the configuration can be labeled according to a quality criterion. Since it is a data-driven approach, it could be applied to any complex network where historical labeled data are available. In particular, rule-based control exploits a rule-based classification method that allows us to retrieve the rules leading to good or bad performances of the system, even without any information about its physical laws. The evaluation of the results on some simulated scenarios shows that the proposed approach is able to reduce energy consumption while ensuring a good quality of the service. The proposed approach is currently used in the water distribution system of the Milan (Italy) water main.
Exploring Clustering Techniques for Analyzing User Engagement Patterns in Twitter Data
Authors: Kanavos Andreas , Karamitsos Ioannis , Mohasseb Alaa
Published: June 2023

Social media platforms have revolutionized information exchange and socialization in today’s world. Twitter, as one of the prominent platforms, enables users to connect with others and express their opinions. This study focuses on analyzing user engagement levels on Twitter using graph mining and clustering techniques. We measure user engagement based on various tweet attributes, including retweets, replies, and more. Specifically, we explore the strength of user connections in Twitter networks by examining the diversity of edges. Our approach incorporates graph mining models that assign different weights to evaluate the significance of each connection. Additionally, clustering techniques are employed to group users based on their engagement patterns and behaviors. Statistical analysis was conducted to assess the similarity between user profiles, as well as attributes, such as friendship, followings, and interactions within the Twitter social network. The findings highlight the discovery of closely linked user groups and the identification of distinct clusters based on engagement levels. This research emphasizes the importance of understanding both individual and group behaviors in comprehending user engagement dynamics on Twitter.
Current Landscape of Immune Checkpoint Inhibitor Therapy for Hepatocellular Carcinoma
Authors: Ruff Samantha M. , Manne Ashish , Cloyd Jordan M. , Dillhoff Mary , Ejaz Aslam , Pawlik Timothy M.
Published: June 2023

The liver maintains a balance between immune tolerance and activation in its role as a filtration system. Chronic inflammation disrupts this immune microenvironment, thereby allowing for the rise and progression of cancer. Hepatocellular carcinoma (HCC) is a liver tumor generally diagnosed in the setting of chronic liver disease. When diagnosed early, the primary treatment is surgical resection, liver transplantation, or liver directed therapies. Unfortunately, patients with HCC often present at an advanced stage or with poor liver function, thereby limiting options. To further complicate matters, most systemic therapies are relatively limited and ineffective among patients with advanced disease. Recently, the IMbrave150 trial demonstrated that the combination of atezolizumab and bevacizumab was associated with better survival compared to sorafenib among patients with advanced HCC. As such, atezolizumab and bevacizumab is now recommended first-line therapy for these patients. Tumor cells work to create an immunotolerant environment by preventing the activation of stimulatory immunoreceptors and upregulating expression of proteins that bind inhibitory immunoreceptors. ICIs work to block these interactions and bolster the anti-tumor function of the immune system. We herein provide an overview of the use of ICIs in the treatment of HCC.
Host Range Expansion of Nest-Parasitic Moths Pyralis regalis and Hypsopygia mauritialis in Social Wasp Nests: New Findings and Implications for Biological Control
Authors: Shin Young-Min , Lee Heung Sik , Kim Il-Kwon , Kim Chang-Jun , Choi Moon Bo
Published: June 2023

Parasitic moths are common in social wasp (Hymenoptera) nests, attacking many species of Polistinae and a few species of Vespinae. In the Republic of Korea, two moth species are known to parasitize the brood of Polistes rothneyi koreanus: Pyralis regalis (Pyralidae) and Anatrachyntis japonica (Cosmopterigidae). Although previously reported elsewhere, a novel case of parasitization was recently documented in the Republic of Korea, in which Hypsopygia mauritialis (Pyralidae) was identified in the nests of social wasps. Pyralis regalis is the most common parasitic moth in the Republic of Korea, feeding on the nests of 11 species of social wasps, mostly the Korean Vespa species. To that list of hosts, we add a species of Dolichovespula and two species of Polistes. Parasitism of Vespa velutina nigrithorax, an invasive alien hornet, by both P. regalis and H. mauritialis, was observed for the first time. However, their potential to control invasive alien hornets is expected to be low. This study provides new insights into the diversity of nest-parasitic moths in social wasp nests and their hosts in the Republic of Korea, and highlights the potential for these moths to impact pest populations.
Black Cumin Seed (Nigella sativa) in Inflammatory Disorders: Therapeutic Potential and Promising Molecular Mechanisms
Authors: Rashwan Hager K. , Mahgoub Shahenda , Abuelezz Nermeen Z. , Amin Hatem K.
Published: June 2023

Inflammation is an essential defense mechanism against harmful stimuli. However, uncontrolled inflammatory mechanisms culminate in disturbed responses that contribute to multiple serious diseases. Besides common synthetic drugs, there is a growing interest in optimizing the use of natural products as therapeutic or protective supplements against inflammatory disorders. Black cumin seed (BCS), or Nigella sativa (Family Ranunculaceae), is widely used as a health-supportive herb in the Middle East, Far East and West Asia. BCS is a rich source of phytochemicals, and studies have reported its promising effects against a variety of metabolic, proliferative, respiratory, and neurological disorders associated with disrupted inflammatory pathways. This review presents an updated comprehensive assessment of BCS’s effects against various inflammatory disorders and highlights the role of BCS’s bioactive constituents in inflammation and oxidative stress pathways. Moreover, it outlines the future possibilities for enhancing therapeutic activity through efficient pharmaceutical formulations. Thorough analysis of international research studies published between the years 1998 and 2023 reveals the promising anti-inflammatory potential of BCS’s bioactive constituents through modulating inflammation and crucial oxidative stress players in inflammatory disorders. Thus, the bioactive constituents of BCS can be further boosted by updated technologies such as nano-incorporation for the improved management of inflammatory diseases.
A Special Relativistic Exploitation of the Second Law of Thermodynamics and Its Non-Relativistic Limit
Authors: Papenfuss Christina
Published: June 2023

A thermodynamic process is a solution of the balance equations fulfilling the second law of thermodynamics. This implies restrictions on the constitutive relations. The most general way to exploit these restrictions is the method introduced by Liu. This method is applied here, in contrast to most of the literature on relativistic thermodynamic constitutive theory, which goes back to a relativistic extension of the Thermodynamics of Irreversible Processes. In the present work, the balance equations and the entropy inequality are formulated in the special relativistic four-dimensional form for an observer with four-velocity parallel to the particle current. The restrictions on constitutive functions are exploited in the relativistic formulation. The domain of the constitutive functions, the state space, is chosen to include the particle number density, the internal energy density, the space derivatives of these quantities, and the space derivative of the material velocity for a chosen observer. The resulting restrictions on constitutive functions, as well as the resulting entropy production are investigated in the non-relativistic limit, and relativistic correction terms of the lowest order are derived. The restrictions on constitutive functions and the entropy production in the low energy limit are compared to the results of an exploitation of the non-relativistic balance equations and entropy inequality. In the next order of approximation our results are compared to the Thermodynamics of Irreversible Processes.
Uniform Treatment of Integral Majorization Inequalities with Applications to Hermite-Hadamard-Fejér-Type Inequalities and f-Divergences
Authors: Horváth László
Published: June 2023

In this paper, we present a general framework that provides a comprehensive and uniform treatment of integral majorization inequalities for convex functions and finite signed measures. Along with new results, we present unified and simple proofs of classical statements. To apply our results, we deal with Hermite-Hadamard-Fejér-type inequalities and their refinements. We present a general method to refine both sides of Hermite-Hadamard-Fejér-type inequalities. The results of many papers on the refinement of the Hermite-Hadamard inequality, whose proofs are based on different ideas, can be treated in a uniform way by this method. Finally, we establish a necessary and sufficient condition for when a fundamental inequality of f-divergences can be refined by another f-divergence.
Embedding-Based Deep Neural Network and Convolutional Neural Network Graph Classifiers
Authors: Elnaggar Sarah G. , Elsemman Ibrahim E. , Soliman Taysir Hassan A.
Published: June 2023

One of the most significant graph data analysis tasks is graph classification, as graphs are complex data structures used for illustrating relationships between entity pairs. Graphs are essential in many domains, such as the description of chemical molecules, biological networks, social relationships, etc. Real-world graphs are complicated and large. As a result, there is a need to find a way to represent or encode a graph’s structure so that it can be easily utilized by machine learning models. Therefore, graph embedding is considered one of the most powerful solutions for graph representation. Inspired by the Doc2Vec model in Natural Language Processing (NLP), this paper first investigates different ways of (sub)graph embedding to represent each graph or subgraph as a fixed-length feature vector, which is then used as input to any classifier. Thus, two supervised classifiers—a deep neural network (DNN) and a convolutional neural network (CNN)—are proposed to enhance graph classification. Experimental results on five benchmark datasets indicate that the proposed models obtain competitive results and are superior to some traditional classification methods and deep-learning-based approaches on three out of five benchmark datasets, with an impressive accuracy rate of 94% on the NCI1 dataset.
A Laser Data Compensation Algorithm Based on Indoor Depth Map Enhancement
Authors: Chi Xiaoni , Meng Qinyuan , Wu Qiuxuan , Tian Yangyang , Liu Hao , Zeng Pingliang , Zhang Botao , Zhong Chaoliang
Published: June 2023

The field of mobile robotics has seen significant growth regarding the use of indoor laser mapping technology, but most two-dimensional Light Detection and Ranging (2D LiDAR) can only scan a plane of fixed height, and it is difficult to obtain the information of objects below the fixed height, so inaccurate environmental mapping and navigation mis-collision problems easily occur. Although three-dimensional (3D) LiDAR is also gradually applied, it is less used in indoor mapping because it is more expensive and requires a large amount of memory and computation. Therefore, a laser data compensation algorithm based on indoor depth map enhancement is proposed in this paper. Firstly, the depth map acquired by the depth camera is removed and smoothed by bilateral filters to achieve the enhancement of depth map data, and the multi-layer projection transformation is performed to reduce the dimension to compress it into pseudo-laser data. Secondly, the pseudo-laser data are used to remap the laser data according to the positional relationship between the two sensors and the obstacle. Finally, the fused laser data are added to the simultaneous localization and mapping (SLAM) front-end matching to achieve multi-level data fusion. The performance of the multi-sensor fusion before and after is compared with that of the existing fusion scheme via simulation and in kind. The experimental results show that the fusion algorithm can achieve a more comprehensive perception of environmental information and effectively improve the accuracy of map building.
A Fault Diagnosis Method for Power Battery Based on Multiple Model Fusion
Authors: Zhou Juan , Wu Zonghuan , Zhang Shun , Wang Peng
Published: June 2023

The widespread adoption and utilization of electric vehicles has been constrained by power battery performance. We proposed a fault diagnosis method for power batteries based on multiple-model fusion. The method effectively fused the advantages of various classification models and avoided the bias of a single model towards certain fault types. Firstly, we collected and sorted parameter information of the power battery during operation. Three common neural networks: back propagation (BP) neural network, convolution neural network (CNN), and long short-term memory (LSTM) neural network, were applied to battery fault diagnosis to output the fault types. Secondly, the fusion algorithm proposed in this paper determined the accurate fault type. Based on the improved voting method, the proposed fusion algorithm, named the multi-level decision algorithm, calculated the voting factors of the diagnostic results of each classification model. According to the set decision thresholds, multi-level decision voting was conducted to avoid neglecting effective classification information from minority models, which can occur with traditional voting methods. Finally, the accuracy and effectiveness of the proposed method were verified by comparing the accuracy of each classification model with the multiple model fusion algorithm.
A Comprehensive Review of Degradation Prediction Methods for an Automotive Proton Exchange Membrane Fuel Cell
Authors: Nguyen Huu-Linh , Lee Sang-Min , Yu Sangseok
Published: June 2023

Proton exchange membrane fuel cells (PEMFCs) are an alternative power source for automobiles that are capable of being cleaner and emission-free. As of yet, long-term durability is a core issue to be resolved for the mass production of hydrogen fuel cell vehicles that requires varied research in the range from sustainable materials to the optimal operating strategy. The capacity to accurately estimate performance degradation is critical for developing reliable and durable PEMFCs. This review investigates various PEMFC performance degradation modeling techniques, such as model-based, data-driven, and hybrid models. The pros and cons of each approach are explored, as well as the challenges in adequately predicting performance degradation. Physics-based models are capable of simulating the physical and electrochemical processes which occur in fuel cell components. However, these models tend to be computationally demanding and can vary in terms of parameters between different studies. On the other hand, data-driven models provide rapid and accurate predictions based on historical data, but they may struggle to generalize effectively to new operating conditions or scenarios. Hybrid prediction approaches combine the strengths of both types of models, offering improved accuracy but also introducing increased computational complexity to the calculations. The review closes with recommendations for future research in this area, highlighting the need for more extensive and accurate prediction models to increase the reliability and durability of PEMFCs for fuel cell electric vehicles.
Deep Neural Networks in Power Systems: A Review
Authors: Khodayar Mahdi , Regan Jacob
Published: June 2023

Identifying statistical trends for a wide range of practical power system applications, including sustainable energy forecasting, demand response, energy decomposition, and state estimation, is regarded as a significant task given the rapid expansion of power system measurements in terms of scale and complexity. In the last decade, deep learning has arisen as a new kind of artificial intelligence technique that expresses power grid datasets via an extensive hypothesis space, resulting in an outstanding performance in comparison with the majority of recent algorithms. This paper investigates the theoretical benefits of deep data representation in the study of power networks. We examine deep learning techniques described and deployed in a variety of supervised, unsupervised, and reinforcement learning scenarios. We explore different scenarios in which discriminative deep frameworks, such as Stacked Autoencoder networks and Convolution Networks, and generative deep architectures, including Deep Belief Networks and Variational Autoencoders, solve problems. This study’s empirical and theoretical evaluation of deep learning encourages long-term studies on improving this modern category of methods to accomplish substantial advancements in the future of electrical systems.
On the Use of Ultrasonic Flowmeters for Cooling Energy Metering and Sub-Metering in Direct Expansion Systems
Authors: Aprea Ciro , Canale Laura , Dell’Isola Marco , Ficco Giorgio , Frattolillo Andrea , Maiorino Angelo , Petruzziello Fabio
Published: June 2023

The Energy Efficiency Directive (EED, Directive 2012/27/EU) has made mandatory the installation of individual metering systems in the case of buildings with centralized heating/cooling and hot water sources (multi-apartment and multi-purpose buildings), provided it is economically and technically feasible. Individual metering of heating/cooling systems is mainly based on thermal energy meters (TEM), which are widely used for direct metering in heating applications. On the other hand, direct metering of energy consumption in cooling systems still represents a challenge, given the different types of cooling units and the lack of regulations from the technical and legal points of view. In this context, this paper briefly overviews the available centralized cooling systems and the possible solutions for metering and sub-metering, which depend on the specific application. Vapour Compression Refrigeration (VCR) systems are spreading worldwide for air conditioning applications. Particular attention has been paid to the direct metering of cooling energy and specifically to refrigerant flow rate measurement, which represents a critical issue because of the small-diameter pipes and the different thermodynamic properties of the fluid used. Thus, an experimental campaign has been developed and carried out in order to compare a clamp-on ultrasonic flowmeter with a more accurate Coriolis one in a direct expansion (DE) system. The experimental tests have been performed at two different temperature conditions, showing a relative error in the mass flow rate measurements within ±10%.
Integrated Control of Motion Actuators for Enhancing Path Following and Yaw Stability of Over-Actuated Autonomous Vehicles
Authors: Zhang Wenliang , Drugge Lars , Nybacka Mikael , Jerrelind Jenny
Published: June 2023

Advanced active safety systems play a crucial role in ensuring the safe driving of vehicles in critical conditions such as an obstacle avoidance manoeuvre. However, conventional techniques relying mainly on braking interventions may not result in the desired vehicle response in such situations. Over-actuation through the control of individual motion actuators could potentially improve the safety performance of vehicles. This study evaluates various configurations of motion actuators for path following and yaw stability control of vehicles in critical driving scenarios. The configurations include active front steering (S), active front steering + torque vectoring (ST), active front steering + active camber (SC) and active front steering + torque vectoring + active camber (STC). The evaluation is achieved based on a nonlinear model predictive control formulation, which considers yaw stability and the physical limits of motion actuators. This problem formulation uses a double-track vehicle model, combined with the Dugoff tyre model and its variant with the camber effect, to model the vehicle dynamics. The actuator configurations are evaluated regarding the passing velocity, tracking accuracy, safety distance and robustness to reference trajectory variation. The results indicate that the integrated control of STC performs the best among all the four configurations while S performs the worst. Furthermore, SC is generally superior to ST.
Experimental Investigation and Modelling of Sediments Effect on the Performance of Cadmium Telluride Photovoltaic Panels
Authors: Gonçalves Bernardo , Fernandes João F. P. , Torres João Paulo N. , Marques Lameirinhas Ricardo A.
Published: June 2023

Of the different renewable sources of energy, photovoltaic energy has one of the highest potentials. In recent decades, several technological and research advances have contributed to the consolidation of its potential. One current photovoltaic energy research topic is the analysis of the impact of sediments on the panels’ performance. The development of models to predict the performance of panels in the presence of sediments may allow for better decision-making when considering maintenance operations. This work contributed to the investigation of the influence of sand on the production of photovoltaic energy in cadmium telluride (CdTe) panels. Six panels of this type with different colors and transparencies were experimentally tested with and without the presence of sand. The impact of the sand on the cells’ performance was evaluated by analyzing the change in the 1M5P model’s parameters and in the power, efficiency, and fill factors. The experimental results show different negative impacts on the output power of the CdTe panels, from −14% in the orange panel to −36% in the green panel. Based on this study, the development of a model capable of predicting the effect of the sand on these panels was introduced. The developed model was validated experimentally, with a maximum deviation of 4.6%. These results can provide support for the decision-making around maintenance activities and for the development of new techniques to avoid sediment deposition on CdTe panels.
Overview of Photovoltaic and Wind Electrical Power Hybrid Systems
Authors: Chrifi-Alaoui Larbi , Drid Saïd , Ouriagli Mohammed , Mehdi Driss
Published: June 2023

The overexploitation of non-renewable fossil resources has led to dangerous warming of our planet due to greenhouse gas emissions. The main reason for this problem is the increase in global energy demand. The rising prices of oil and gas have pushed governments around the world to turn to renewable energy, especially solar and wind power. For this reason, the present paper aimed to focus on photovoltaic and wind energy systems. However, exploitation of these two sources individually is not always easy because of their intermittent and irregular characters. Therefore, the obvious solution is the hybridisation of these two sources, which, when used alongside other systems such as batteries, increases the reliability, availability, and efficiency of these renewable sources. The main objective of this paper is to give an overview of different configurations of hybrid solar and wind energy conversion systems. First, the behaviour of each system, as well as their mathematical models, characteristics, and existing topologies, is presented. Then, the control strategies, optimal configurations, and sizing techniques, as well as different energy management strategies, of these hybrid PV–wind systems are presented.
The Effect of a Magnetic Field on Solid–Liquid Contact Electrification for Streaming Flow Energy Harvesting
Authors: Nguyen Thanh Ha , Ahn Kyoung Kwan
Published: June 2023

In recent years, the triboelectric nanogenerator (TENG) has been recognized as a promising method for energy harvesting and self-powered devices. However, in order to improve the output efficiency of the TENG, it is necessary to change the types of dielectric materials, which requires advanced technology and a high cost to implement. To address this issue, we developed a parallel electrode magnetic-TENG (Mag-TENG) based on contact electrification of a liquid–solid interface under the effect of the magnetic field, which enhances the output performance of the TENG without having to develop the dielectric material. Our experimental results achieved a higher output of the TENG under the influence of a magnetic field when an increase of the magnetic field strength went from 0 to 360 mT, and the flow rate of unsteady seawater was variable from 390 to 690 mL/min. Specifically, compared to the without-magnetic field case, the output current increased by approximately 6.5 times and the output voltage by 2.7 times. These findings suggested that using a magnetic field to enhance the TENG’s efficiency has significant potential for energy harvesting from seawater and self-powered flow sensors.
The Influence of Storage Tank Volume on the Nighttime Heat Dissipation and Freezing Process of All-Glass Vacuum Tube Solar Water Heaters
Authors: Wang Shidong , Wang Xing , Mao Mingqiang , Wang Yongtao , Liu Shiping , Luo Baoming , Li Tao
Published: June 2023

The issue of freezing often occurs when using all-glass vacuum tube solar water heaters during cold winter seasons, leading to problems such as pipe ruptures and tank leakage. In order to further study the nocturnal heat dissipation and freezing characteristics of these heaters, a three-dimensional transient numerical model of their nocturnal heat dissipation was established. The model simulated the nocturnal heat dissipation process, and experimental validations were conducted through nocturnal temperature drops of the collector and temperature drops of individual tubes without a storage tank. Experimental and simulation results revealed that in clear weather conditions during cold winters in Luoyang, the all-glass vacuum tube solar water heaters experienced freezing issues during the night, with freezing predominantly starting from the bottom surface of the vacuum tubes. The frozen length along the tube wall and the thickness of ice at the bottom section reached up to 1180 mm and 5 mm, respectively. In the absence of a storage tank, the freezing situation was severe, with approximately 4/5 of the individual tubes completely frozen. Under specified operating conditions, different storage tank volumes exhibited varying degrees of freezing in the all-glass vacuum tube solar water heaters. When the volume was increased to 15 L, the temperature drop in the storage tank and the vacuum tubes decreased by 12.1% and 7.6%, respectively. Larger storage tank volumes resulted in reduced freezing risks in all-glass vacuum tube solar collectors. This study provides valuable guidance for the design and application of solar collectors and serves as a reference for the development and application of solar energy utilization technologies.
Examination of the Emission of Gas-Phase Components, Including Some Not-Conventional Ones from a Parking Heater, While Increasing the Bioethanol Content of the Fuel
Authors: Nagy Péter , Zsoldos Ibolya , Szabados György
Published: June 2023

The air pollutant emissions of a motor vehicle do not only mean the emissions from the engine used for propelling the vehicle. Another possible source is the passenger compartment heater. In the focus of our research, we investigated the effect of mixing gasoline-powered cabin air and ethanol (E10, E30, E100 on a volumetric basis) on the emissions of the equipment. Among the pollutant components examined, there were conventional components and so called not-conventional components. The chosen length of the test was 1800 s, while the intake air parameters temperature (tin) and relative humidity (h) have been kept constant (tin = 15 °C, h = 30%). Bioethanol mixing has a significant reducing effect on NOx (oxides of nitrogen) and CO2 (carbon dioxide). As for the components CO (carbon monoxide), THC (total hydrocarbons), CH4 (methane) and N2O (nitrous oxide), the values of the components reach usable values only in the start-up and burnout phases, while in the stable-operation phase, their values are outside the limit of detectability. A small part of THC is only CH4; a more significant part is NMHC (non-methane hydrocarbons). The results of the developed vehicle fleet model for calculating the GHG (greenhouse gas) emissions of a vehicle fleet equipped with such a device showed that the fleet’s GHG emissions are less than 1% of the annual emissions from the combustion of transport fuel.
Implementation of Digital Twin for Increasing Efficiency of Renewable Energy Sources
Authors: Belik Milan , Rubanenko Olena
Published: June 2023

This paper presents an analysis of the instability of the electricity generation of renewable energy sources (RESs), specifically Digital Twins of RESs. The first part deals with the analysis of RES electricity generation around the world and Ukraine. The following chapter describes features of functioning power grids in modern conditions in Ukraine and ways to ensure the balance reliability in the power system for conditions of high-grade RES integration. The rapid increase in electricity generation RESs causes control problems of distributed power supply in the power grid. A mathematical model of the parameter controls in normal mode electric power systems for conditions with high integration of RESs is proposed in the second part. The study investigates components of the optimality criterion at the control of normal mode parameters of the electric power system with RESs. In general, digital transformation helps decarbonize the energy supply, decrease dependency on fossil fuels, and integrate renewables into power systems. A model Digital Twin (DT) of a photovoltaic system, or an exact 3D visualization, analyzing the accumulator system depending on load and generation, are presented. The problems of Digital Twin are very widely discussed, but many papers and studies are general without any practical implementations. The main part of this paper focuses on research and deals with daily electricity generation from different kinds of RESs, namely mini-hydropower stations, photovoltaic power stations, and wind power stations. Measured data of electricity generation from photovoltaic power plants, wind power plants, and mini-hydropower plants and obtained meteorological factors were used for the calculation of Spearman’s, Kendall’s, and Pearson’s correlation rank coefficients. The main contribution of this research is to determine the main metrological factors for each kind of studied RES. In the future, it will help to decide the task of forecasting power generation more presciently. Additionally, the presented model of DT RESs allows the installation and operation of grids with higher efficiency, because it can help to predict all influences, from shading up to the optimization of the battery storage system.
Numerical Investigation of the Influence of Roof-Cutting Parameters on the Stability of Top Coal Gob-Side Entry Retaining by Roof Pre-Fracturing in Ultra-Thick Coal Seam
Authors: Yang Yongkang , Gao Peipeng , Zhang Chao , Wang Chenlong
Published: June 2023

Gob-side entry retaining by roof cutting, a pillarless mining technique, plays a critical role in maintaining continuous production, rapid connection, and enhancing the coal recovery rate in fully mechanized top coal caving working faces. This technique stands as a sustainable development method in coal mining. The present research, set against the backdrop of the Yitang Coal Mine 100602 top coal gob-side entry retaining by roof cutting, investigates the influence of roof-cutting borehole depth, borehole dip angle, mining height, and coal seam thickness on stability in an ultra-thick coal seam under 12 distinct mining conditions. A typical model of overburden structure post-roof pre-splitting was established to study the failure mechanism of the top coal roof. The results reveal that the dip angle and depth of the roof pre-fracturing borehole significantly impact the movement characteristics of the overlying strata. Optimal conditions are found when the dip angle and depth of the roof pre-fracturing borehole, the mining height, and the top coal thickness are 10°, 16 m, 4 m, and 4 m, respectively. Under these circumstances, the load transfer from the goaf to the gob-side entry can be effectively intercepted, mitigating the influence of roof fracture activities on the top coal gob-side entry. Field measurements confirm that suitable anchor-net support can stabilize the roof’s rock structure. This research underpins the significance of roof pre-fracturing for the promotion and application of top coal gob-side entry retaining by roof cutting in ultra-thick coal seams.
Greenhouse Gas Emissions from Incineration of Municipal Solid Waste in Seoul, South Korea
Authors: Kwon Youngsun , Choi Kyunghoon , Jang Yong-Chul
Published: June 2023

Greenhouse gas (GHG) emissions from the incineration of municipal solid waste (MSW) have become a concern in the solid waste community from the perspective of climate change mitigation and response. In this study, we aimed to estimate the GHG emissions from the incineration of MSW in Seoul, with a population of about 10 million, by using the IPCC (Intergovernmental Panel on Climate Change) 2006 guideline and scenario analysis for 2030 and 2040. In 2021, Seoul generated 2899 kt of MSW/yr. Approximately 40% (1163 kt/yr) of Seoul’s MSW was disposable (or non-recyclable) waste. Out of the disposable waste, about 741 kt/yr of combustible waste was treated by incineration, resulting in 545 kt CO2 eq emissions, which was about 7.5 times higher than the 74 kt CO2 eq in 2000. The dominant contributor to the GHG emissions was plastic waste, accounting for the largest fraction of 92% (501 kt CO2 eq/yr in 2021). Scenario analysis showed that if the current situation (BAU scenario) is considered, with the assumption of no reduction in MSW generation, the capacity of Seoul’s four incineration facilities will be exceeded in 2029. All other scenarios (S1, S2, and S3) showed reduced amounts of MSW incineration and GHG emissions compared to the BAU scenario. Especially, S3 (waste reduction and increased recycling rate) revealed a 53% reduction when compared to the BAU scenario. Based on the results of our scenario analysis, it is expected that in 2040, the GHG emissions from incineration will be in a range of from about 389 kt CO2 eq to 832 kt CO2 eq, depending on the waste minimization policy and recycling efforts in the future. Strengthened regulations on and efforts towards plastic waste reduction and the recycling of MSW will be crucial with the perspectives of GHG emissions by incineration and resource recovery.
Development of Interior and Exterior Automotive Plastics Parts Using Kenaf Fiber Reinforced Polymer Composite
Authors: Uzoma Akubueze Emmanuel , Nwaeche Chiemerie Famous , Al-Amin Md. , Muniru Oluwa Segun , Olatunji Ololade , Nzeh Sixtus Onyedika
Published: June 2023

The integration of sustainable components in automotive parts is in growing demand. This study involves the entire process, from the extraction of kenaf cellulosic fibers to the fabrication of automotive parts by applying injection molding (sample only) and Resin Transfer Molding (RTM) techniques. Fibers were pretreated, followed by moisture content analysis before composite fabrication. The composite was fabricated by integrating the fibers with polypropylene, maleic anhydride polypropylene (MAPP), unsaturated polyester, and epoxy resin. Mechanical tests were done following ASTM D5083, ASTM D256, and ASTM D5229 standards. The RTM technique was applied for the fabrication of parts with reinforced kenaf long bast fibers. RTM indicated a higher tensile strength of 55 MPa at an optimal fiber content of 40%. Fiber content from 10% to 40% was found to be compatible with or better than the control sample in mechanical tests. Scanning Electron Microscope (SEM) images showed both fiber-epoxy-PE bonding along with normal irregularities in the matrix. The finite element simulations for the theoretical analysis of the mechanical performance characteristics showed higher stiffness and strength in the direction parallel to the fiber orientation. This study justifies the competitiveness of sustainable textile fibers as a reinforcement for plastics to use in composite materials for automotive industries.
A New Species of Ampelovirus Detected in Persea lingue (Ruiz & Pav.) Nees ex Kopp, a Common Tree of the Threatened Chilean Sclerophyll Forest
Authors: Zamorano Alan , Gamboa Camila , Camilla Colombina , Beltrán Francisca , Magni Carlos , Vaswani Suraj , Martínez-Herrera Eduardo , Fiore Nicola
Published: June 2023

Biotic and abiotic stress seriously affects the development of plants, leading to the death of a significant number of plants in natural landscapes. Over the last twelve years, the central zone of Chile has been under an intensive drought, affecting the species inhabiting the Chilean Mediterranean forest, which is classified as a biological hotspot. In this context, our group started a small survey to monitor the presence of intracellular pathogens that may be infecting the plants, increasing the damage caused by the water deprivation. Several plants of one species, Persea lingue, showed symptoms of interveinal yellowing and leaf curling. RNA-seq analyses of one of these samples showed the presence of a long contig with high coverage only in symptomatic plants. Phylogenetic analysis and the molecular features indicated that it was a new species of the Ampelovirus genus. RT-PCR analyses determined the presence of the virus only in symptomatic plants of the same natural preserve.
Identification of ApbHLH1 as a Partner Interacting with ApMYB1 to Promote Anthocyanin Biosynthesis during Autumnal Leaf Coloration in Acer palmatum
Authors: Chen Long , Sun Sujing , Qiu Gengcheng , Yang Jiading
Published: June 2023

Anthocyanin biosynthesis determines the leaf color of Acer palmatum as a widely-planted landscape tree. Previously, ApMYB1 has been characterized as a positive regulator of anthocyanin biosynthesis. To further elucidate the mechanism of leaf coloration, the present study identified a basic helix-loop-helix (bHLH) transcription factor (ApbHLH1) through the phylogenetic analysis of 156 putative bHLH proteins in Acer palmatum and eight reference bHLHs which were known to be involved in the anthocyanin biosynthesis of selected plants. Protein structure comparison showed that ApbHLH1 has a conserved bHLH domain, and its N-terminal contains an MYB-interacting region. The expression of ApbHLH1 in leaves was found to not be correlated with anthocyanin contents either in green, semi-red leaves or during leaf autumnal senescence when anthocyanin content increased. ApbHLH1 expression in detached leaves was induced by exogenous senescence-promoting chemicals, including H2O2, SA, MeJA, ACC and ABA, with certain durations. In particular, either high light or low temperature induced ApbHLH1 expression significantly, and combination of high light and low temperatures seemed more effective in inducing ApbHLH1 expression. Luciferase complementation imaging assays confirmed the physical interaction between ApbHLH1 and ApMYB1, which could be abolished by either the truncating MYB-interacting region of ApbHLH1 or the deleting bHLH interacting domain of ApMYB1. The transient expression of ApbHLH1 could not induce anthocyanin production, while the co-expression of ApbHLH1 and ApMYB1 resulted in a higher accumulation of anthocyanins compared to the expression of ApMYB1 alone in tobacco leaves. Collectively, our results revealed that ApbHLH1 participated in leaf coloration through binding with ApMYB1 and enhancing the ApMYB1 function of promoting anthocyanin biosynthesis during leaf autumnal reddening in Acer palmatum. ApbHLH1 could have the potential for breeding color-leafed plants through co-transformation with ApMYB1.
Morphological Crown Attributes Contributing to Differential Height and Diameter Growth among Families in a Coastal Douglas-Fir Progeny Test: Crown Structural Evidence for Crop Ideotypes
Authors: Joo Sukhyun , Maguire Douglas A. , St. Clair J. Bradley , Ye Terrance Z. , Jayawickrama Keith J. S.
Published: June 2023

Theoretical tree crop ideotypes have long and narrow live crowns with a high total leaf area. This crown form allows more efficient exploitation of site resources, in part by physically occupying less growing space per unit leaf area and by packing a greater number of trees into a given area. Genetic selection for crop ideotypes has been proposed as a strategy for maximizing productivity per unit area in stands managed under intensive silviculture. The primary objective of this study was to test the relationship between the relative growth performance of different families in a Douglas-fir (Pseudotsuga menziesii var. menziesii [Mirb.] Franco) progeny test and morphological crown attributes that conform to a theoretical crop ideotype. The overarching goal was to identify attributes conferring superior height and diameter growth on families and to facilitate the incorporation of these attributes and associated growth mechanisms into hybrid growth models for intensively managed plantations. Crown structural attributes were measured on destructively sampled trees and averaged for the entire crown and each third of live crown length among families. Multivariate analysis revealed that crown attributes averaged over the entire crown performed best for identifying families with different height and diameter growth, followed successively by the bottom, middle, and top crown third. Trees with relatively short branch lengths and steep branch angles tended to have higher total leaf area per unit crown length (TLACL), and this structural attribute showed a strong positive correlation with cumulative diameter growth. The ratio of crown width to crown length (CWL) was moderately and negatively correlated with cumulative height growth. The families displaying the most rapid diameter growth in this progeny test conformed to a theoretical crop ideotype, while those with the most rapid height growth displayed crown attributes with a less obvious relationship to the crop ideotype concept. TLACL implied one possible mechanism driving genetic gain in Douglas-fir families, given its high heritability and strongly positive correlation with growth performance. Incorporating TLACL as an explanatory variable in diameter growth models could at least partly represent different genetic levels. TLACL is less strongly correlated with height growth rate, so incorporating CWL may better represent genetic effects on height growth models.