bluuebunny/crossref_metadata_2025 huggingface dataset:
Reviewing Federated Learning Aggregation Algorithms; Strategies, Contributions, Limitations and Future Perspectives
Authors: Moshawrab Mohammad , Adda Mehdi , Bouzouane Abdenour , Ibrahim Hussein , Raad Ali
Published: May 2023

The success of machine learning (ML) techniques in the formerly difficult areas of data analysis and pattern extraction has led to their widespread incorporation into various aspects of human life. This success is due in part to the increasing computational power of computers and in part to the improved ability of ML algorithms to process large amounts of data in various forms. Despite these improvements, certain issues, such as privacy, continue to hinder the development of this field. In this context, a privacy-preserving, distributed, and collaborative machine learning technique called federated learning (FL) has emerged. The core idea of this technique is that, unlike traditional machine learning, user data is not collected on a central server. Nevertheless, models are sent to clients to be trained locally, and then only the models themselves, without associated data, are sent back to the server to combine the different locally trained models into a single global model. In this respect, the aggregation algorithms play a crucial role in the federated learning process, as they are responsible for integrating the knowledge of the participating clients, by integrating the locally trained models to train a global one. To this end, this paper explores and investigates several federated learning aggregation strategies and algorithms. At the beginning, a brief summary of federated learning is given so that the context of an aggregation algorithm within a FL system can be understood. This is followed by an explanation of aggregation strategies and a discussion of current aggregation algorithms implementations, highlighting the unique value that each brings to the knowledge. Finally, limitations and possible future directions are described to help future researchers determine the best place to begin their own investigations.
Review of Deep Reinforcement Learning and Its Application in Modern Renewable Power System Control
Authors: Li Qingyan , Lin Tao , Yu Qianyi , Du Hui , Li Jun , Fu Xiyue
Published: May 2023

With the ongoing transformation of electricity generation from large thermal power plants to smaller renewable energy sources (RESs), such as wind and solar, modern renewable power systems need to address the new challenge of the increasing uncertainty and complexity caused by the deployment of electricity generation from RESs and the integration of flexible loads and new technologies. At present, a high volume of available data is provided by smart grid technologies, energy management systems (EMSs), and wide-area measurement systems (WAMSs), bringing more opportunities for data-driven methods. Deep reinforcement learning (DRL), as one of the state-of-the-art data-driven methods, is applied to learn optimal or near-optimal control policy by formulating the power system as a Markov decision process (MDP). This paper reviews the recent DRL algorithms and the existing work of operational control or emergency control based on DRL algorithms for modern renewable power systems and control-related problems for small signal stability. The fundamentals of DRL and several commonly used DRL algorithms are briefly introduced. Current issues and expected future directions are discussed.
Coastal Depositional Responses to Relative Sea-Level Rise: Insights from a Superimposed Sandstone–Shale–Coal Reservoir in the Linxing Gas Field, China
Authors: Liu Jincheng , Zhang Yan , Tan Jingqiang
Published: May 2023

The Ximing Sandstone-to-No. 9 Coal succession of the Taiyuan Formation in the Linxing gas field records a complex internal architecture of a transgressive succession developed in the western coast of the late Pennsylvanian North China epeiric sea. Facies and sequence stratigraphic analyses reveal its depositional evolution from fluvial channels through fluvial-dominated and tide-influenced inner estuaries to tide-dominated estuaries and finally to wave-dominated barrier lagoons. The evolution from fluvial- to tide-dominated deposition has been ascribed to the funnel-shaped valley coupled with an increased tidal prism induced by the upstepping and backstepping shoreline. The evolution from tide- to wave-dominated deposition has been ascribed to the wide North China epeiric seaway lacking local coastline irregularities after the incised-valley fill that provided sufficient fetch for the occurrence of large storm waves. Grain-size analysis reveals the relative importance of traction, saltation, dispersed suspension, and flocculated suspension in the development of the transgressive estuarine to lagoonal deposits. This study not only contributes to a proper understanding of coastal depositional response to the relative sea-level rise but also provides a context within which to interpret the symbiotic relationship of the superimposed sandstone–shale–coal reservoirs and predict the distribution of favorable unconventional gas production formation.
Experimental Analysis of the Long-Term Stability of Thermoelectric Generators under Thermal Cycling in Air and Argon Atmosphere
Authors: Schwab Julian , Fritscher Christopher , Filatov Michael , Kober Martin , Rinderknecht Frank , Siefkes Tjark
Published: May 2023

It is estimated that 72% of the worldwide primary energy consumption is lost as waste heat. Thermoelectric Generators (TEGs) are a possible solution to convert a part of this energy into electricity and heat for space heating. However, for their deployment a proven long-term operation is required. Therefore, this research investigates the long-term stability of TEGs on system level in air and argon atmosphere under thermal cycling up to 543 K. The layout of the examined test objects resembles a TEG in stack design. The results show that the maximal output power of the test object in air reaches a plateau at 57% of the initial power after 50 cycles caused by an increased electrical resistance of the system. Whereas the test object in argon atmosphere shows no significant degradation of electrical power or resistance. The findings represent a step towards the understanding of the long-term stability of TEGs and can be used as a guideline for design decisions.
Electricity, Transportation, and Water Provision of 100% Renewable Energy for Remote Areas
Authors: Torabi Roham , Gomes Álvaro , Morgado-Dias Fernando
Published: May 2023

The integration of variable renewable energy sources in islands has become crucial in reducing their dependency on imported fossil fuels. This study aimed to assess the energy transition of an island towards a 100% renewable energy system for power generation, inland transport, and potable water provision. Linking various fossil-fuel-consuming sectors, such as transport and potable water supply systems, may strongly assist in reducing the possible mismatch between renewable energy source production and demand and contribute to fulfilling other system requirements. The use of energy storage technologies is vital and unlike traditional power systems; as the number of components in the system increases, their proper capacity needs to be accurately determined. This work employs a multi-objective optimization assessment using a modified NSGA-II algorithm to depict the energy transition for Porto Santo Island. To evaluate the solutions, we considered the main criteria of energy cost, avoided environmental impacts (CO2-equivalent emissions) of the proposed system, and loss of power supply. The Pareto front contains various solutions under different system configurations. Results indicate that full inland transport electrification (introducing 3000 EVs) can account for 18% of the avoided CO2 emissions of the island while sharing 28–40% of the up-front cost of the system, depending on the proposed system’s components. The EV’s costs incorporate subsidies and their battery replacement. Another interesting finding from the optimization process is that the solution with the highest avoided CO2 emissions involves keeping a diesel generator for supplying 4% of the island’s total demand and using an underwater compressed air energy storage with a capacity of 280 MWh. This suggests that adding more installed wind turbines or PV panels may not necessarily contribute to reducing the emissions of the entire system.
Optimal Capacity and Operational Planning for Renewable Energy-Based Microgrid Considering Different Demand-Side Management Strategies
Authors: Kiptoo Mark Kipngetich , Adewuyi Oludamilare Bode , Howlader Harun Or Rashid , Nakadomari Akito , Senjyu Tomonobu
Published: May 2023

A bi-objective joint optimization planning approach that combines component sizing and short-term operational planning into a single model with demand response strategies to realize a techno-economically feasible renewable energy-based microgrid is discussed in this paper. The system model includes a photovoltaic system, wind turbine, and battery. An enhanced demand response program with dynamic pricing devised based on instantaneous imbalances between surplus, deficit, and the battery’s power capacity is developed. A quantitative metric for assessing energy storage performance is also proposed and utilized. Emergency, critical peak pricing, and power capacity-based dynamic pricing (PCDP) demand response programs (DRPs) are comparatively analyzed to determine the most cost-effective planning approach. Four simulation scenarios to determine the most techno-economic planning approach are formulated and solved using a mixed-integer linear programming algorithm optimization solver with the epsilon constraint method in Matlab. The objective function is to minimize the total annualized costs (TACs) while satisfying the reliability criterion regarding the loss of power supply probability and energy storage dependency. The results show that including the DRP resulted in a significant reduction in TACs and system component capacities. The cost-benefit of incorporating PCDP DRP strategies in the planning model increases the overall system flexibility.
Experimental and Numerical Optimization Study on Performance of Phase-Change Thermal Energy Storage System
Authors: Tang Yuqing , Zhu Neng , Li Siqi , Hou Yingzhen
Published: May 2023

Promoting the use of solar energy resources has always involved the challenges of instability and supply–demand mismatch. The key to solving these issues is to efficiently store and utilize solar energy resources using high-performance heat storage devices. This study designed a high-performance shell-and-tube phase-change thermal storage device and established a numerical model using ANSYS software to summarize the device’s dynamic melting law. To verify the accuracy of the numerical simulation, a performance testing platform for the phase-change thermal storage device was built to investigate the impact of various factors, such as the inlet water temperature, inlet water flow rate, type of heat storage, and initial temperature of the device, and to reveal the change law of the device’s performance. The results show that the inlet water temperature has the most significant impact on the device’s heat storage and release performance. When the device’s heat storage or release is used for heating, changing the inlet water flow rate has a weak and limited effect on the device’s performance. However, when the device’s heat release is used to provide domestic hot water, increasing the make-up water temperature and reducing the inlet water flow rate can significantly improve the device’s effective heat release. Furthermore, based on the experimental validation of the model’s correctness, this study further simulated and studied the impact of different factors on the device’s heat storage process to optimize its structural design and provide technical references for the device’s actual operation and installation. The results show that the placement of fins has a negligible effect on the performance of the heat storage device while reducing the fin spacing and increasing the fin thickness can significantly improve the melting efficiency of the phase-change material (PCM). Additionally, the heat storage characteristics of the device are significantly better in the vertical installation mode than in the horizontal installation mode. This study provides theoretical guidance and technical references for the design and use of phase-change thermal storage devices.
Improving the Electrochemical Performance of Core–Shell LiNi0.8Co0.1Mn0.1O2 Cathode Materials Using Environmentally Friendly Phase Structure Control Process
Authors: Xu Lipeng , Tian Chongwang , Bao Chunjiang , Zhao Jinsheng , Leng Xuning
Published: May 2023

The phase structure of the precursor is crucial for the microstructure evolution and stability of Ni-rich cathode materials. Using sodium lactate as a green complexing agent, cathode electrode materials with different phase structures and unique core–shell structures were prepared by the co-precipitation method in this study. The influence of the phase structure of the nickel-rich precursor on the cathode electrode materials was studied in depth. It was found that α-NCM811 had large interlayer spacing, which was beneficial for the diffusion of lithium ions. In contrast, β-NCM811 had smaller interlayer spacing, a good layered structure, and lower ion mixing, resulting in better cycling performance. The core–shell-αβ-NCM811 with α-NCM811 as the core and β-NCM811 as the shell was prepared by combining the advantages of the two different phases. The core–shell-αβ-NCM811 showed the highest discharge capacity of 158.7 mAh/g at 5 C and delivered excellent rate performance. In addition, the β-NCM811 shell structure with smaller layer spacing could prevent corrosion of the α-NCM811 core by the electrolyte. Thus, the capacity retention rate of the core–shell-αβ-NCM811 was still as high as 86.16% after 100 cycles.
Review of Compressed Air Receiver Tanks for Improved Energy Efficiency of Various Pneumatic Systems
Authors: Dindorf Ryszard , Takosoglu Jakub , Wos Piotr
Published: May 2023

This review examines compressed air receiver tanks (CARTs) for the improved energy efficiency of various pneumatic systems such as compressed air systems (CAS), compressed air energy storage systems (CAESs), pneumatic propulsion systems (PPSs), pneumatic drive systems (PDSs), pneumatic servo drives (PSDs), pneumatic brake systems (PBSs), and compressed air vehicles (CAVs). The basic formulas and energy efficiency indicators used in a CART calculation and selection are included. New scientific research by the authors on measurements based on tank methods, numerical solutions in the process of charging and discharging, the valve-to-tank-to-valve system and pneumatic propulsion system was presented. The numerical model of the valve-tank-valve system takes into account CART polytropic charging and discharging processes, the mass flow balance equation, and the sound (choked) and subsonic mass flow rate in the inlet and outlet valves. Future research directions to improve the energy efficiency of a CART charging and discharge are highlighted. The effective density of energy storage in CART was compared to that of other renewable energy sources and other fuels. Economic and environmental issues were also considered by adopting various energy performance indicators. The discussion also focused on the design concept and computational model of the hybrid tricycle bike (HTB) pneumatic propulsion system.
Capacity Optimal Allocation Method and Frequency Division Energy Management for Hybrid Energy Storage System Considering Grid-Connected Requirements in Photovoltaic System
Authors: Li Wei , Jin Ruixin , Ma Xiaoyong , Zhang Guozun
Published: May 2023

The coordination between a hybrid energy storage system (HESS) and photovoltaic (PV) power station can significantly reduce grid-connected PV power fluctuations. This study proposes a HESS capacity optimal allocation method considering the grid-connected PV requirements. Firstly, based on the power fluctuation requirements in the PV power station grid-connected regulations, the maximum power point tracking working point switching control is performed for the PV power station, from which the grid-connected PV power and HESS power are obtained. Then, a capacity optimal allocation method and frequency division energy management strategy (EMS) for HESS is proposed to find the energy response and power response of each energy storage source. Furthermore, a multi-objective optimization function with HESS cutoff frequency as the independent variable is constructed, and the input cost of HESS and the life loss of the lithium battery are optimized. Finally, the overall strategy is compared and analyzed under the scenarios of three typical PV power fluctuations. Simulation results show that the control strategy has a good smoothing effect on PV power fluctuations. From the perspective of the annual comprehensive input cost, HESS realizes the optimal capacity allocation when the cutoff frequency is 0.0066 Hz.
A Novel Dual Receiver–Storage Design for Concentrating Solar Thermal Plants Using Beam-Down Optics
Authors: Saldivia David , Taylor Robert A.
Published: May 2023

Advanced power cycles—such as the supercritical carbon dioxide (sCO2) cycle—have the potential to reduce the levelized cost of energy (LCOE) of concentrated solar thermal power (CST) plants by significantly boosting their overall solar-to-electric efficiency. To successfully integrate these cycles into CST plants, the industry may need to transition away from liquid working fluids (e.g., synthetic oils and molten salts) to solid and/or gaseous heat transfer media, which are more stable at high temperatures. To address this challenge, this study investigates a novel rotating receiver–storage unit that could enable high-temperature CST plants. A validated numerical model is presented for the charging and discharging processes of the proposed design. It was found that with cast steel as the storage medium in the proposed design, it is possible to achieve >70% receiver efficiency for operation temperatures of 850–1000 K. The overall plant model shows this design is best for relatively small CST systems as modularized units of 10 m diameter (reaching an energy density around 80 kWh/m3), which can be used to drive a 5 MWe sCO2 CST plant. These findings suggest that such a design would have up to 9 h of storage and could be effectively employed as an efficient peaking plant.
Prediction of TOC Content in Organic-Rich Shale Using Machine Learning Algorithms: Comparative Study of Random Forest, Support Vector Machine, and XGBoost
Authors: Sun Jiangtao , Dang Wei , Wang Fengqin , Nie Haikuan , Wei Xiaoliang , Li Pei , Zhang Shaohua , Feng Yubo , Li Fei
Published: May 2023

The total organic carbon (TOC) content of organic-rich shale is a key parameter in screening for potential source rocks and sweet spots of shale oil/gas. Traditional methods of determining the TOC content, such as the geochemical experiments and the empirical mathematical regression method, are either high cost and low-efficiency, or universally non-applicable and low-accuracy. In this study, we propose three machine learning models of random forest (RF), support vector regression (SVR), and XGBoost to predict the TOC content using well logs, and the performance of each model are compared with the traditional empirical methods. First, the decision tree algorithm is used to identify the optimal set of well logs from a total of 15. Then, 816 data points of well logs and the TOC content data collected from five different shale formations are used to train and test these three models. Finally, the accuracy of three models is validated by predicting the unknown TOC content data from a shale oil well. The results show that the RF model provides the best prediction for the TOC content, with R2 = 0.915, MSE = 0.108, and MAE = 0.252, followed by the XGBoost, while the SVR gives the lowest predictive accuracy. Nevertheless, all three machine learning models outperform the traditional empirical methods such as Schmoker gamma-ray log method, multiple linear regression method and ΔlgR method. Overall, the proposed machine learning models are powerful tools for predicting the TOC content of shale and improving the oil/gas exploration efficiency in a different formation or a different basin.
Constrained Least-Squares Parameter Estimation for a Double Layer Capacitor
Authors: Jannif Nayzel I. , Kumar Rahul R. , Mohammadi Ali , Cirrincione Giansalvo , Cirrincione Maurizio
Published: May 2023

This paper presents an estimation of the parameters for a Double Layer Super Capacitor (DLC) that is modelled with a two-branch circuit. The estimation is achieved using a constrained minimization technique, which is developed off-line and uses a single constraint to write the matrix equation. The model is algebraically manipulated to obtain a matrix equation, and a signal processing system is developed to prepare the signals for the identification algorithms. The proposed method builds on the results obtained using an unconstrained ordinary least-squares (OLS) technique. The method is tested both in simulation and experimentally, using a specially-designed experimental rig. A current ramp input is used to generate the corresponding output voltage and its derivatives. The results obtained from the constrained off-line minimization algorithm are compared with those obtained using a traditional off-line estimation method. The discussion of the results shows that the proposed method outperforms the traditional estimation technique. In summary, this paper contributes to the field of DLC parameter estimation by introducing a new off-line constrained minimization technique. The results obtained from the simulations and experimental rig demonstrate the effectiveness of the proposed method with two of three parameters showing relative errors less than 5%.
Geographical Modeling of Charging Infrastructure Requirements for Heavy-Duty Electric Autonomous Truck Operations
Authors: Adegbohun Feyijimi , von Jouanne Annette , Agamloh Emmanuel , Yokochi Alex
Published: May 2023

This study presents an analysis of the charging infrastructure requirements for autonomous electric trucks (AETs) in a specified geographical region, focusing on the state of Texas as a case study. A discrete-time, agent-based model is used to simulate the AET fleet and consider various model parameters such as trip distance/duration, the number of trips, and charging speeds. The framework incorporates unique properties of the Texas road network to assess the sensitivity of charging infrastructure needs. By synergizing electrification and automation, AETs offer benefits such as reduced carbon emissions, enhanced transportation safety, decreased congestion, and improved operational costs for fleets. By simulating daily trips and energy consumption patterns, an analysis of the charging infrastructure needs for cities along the Texas highway triangle formed by I-35, I-45 and I-10 revealed that the total charging energy and average charging power for these major cities ranges between 443~533 MWh/day and 18.5~22 MW, with costs in the range of USD $7.74~$15.93 million for each city, depending on charging infrastructure design and exclusive of any enhancements to the distribution grid infrastructure needed to support the charging infrastructure. This data-driven approach may be replicated for other regions by adapting the simulation parameters to allow policymakers and stakeholders to assess the charging infrastructure requirements and related investments needed to support the transition to electric and autonomous heavy-duty trucking.
Coupled Hydromechanical Modeling and Assessment of Induced Seismicity at FWU: Utilizing Time-Lapse VSP and Microseismic Data
Authors: Acheampong Samuel Appiah , Ampomah William , Lee Don , Eastwood-Anaba Angus
Published: May 2023

The objective of this work is to utilize integrated geomechanics, field vertical seismic profile (VSP) and microseismic data to characterize the complex subsurface stress conditions at the Farnsworth Unit (FWU). The model is based on a five-spot sector model extracted from a primary geomechanical model. The five-spot well injection pattern is characterized by extensive reservoir characterization data, such well logs, extracted cores and borehole geophone data, to facilitate the detailed examination of stress changes and microseismic event occurrences. The study utilizes field vertical seismic volumes acquired from the injection well 13-10A. The seismic volumes successfully provided snapshots of the behavior of the reservoir at distinct times. The use of VSP and microseismic data provided direct and indirect estimates of the dynamic stress changes occurring in the overburden, reservoir and underburden rock formations. In order to illuminate the stress regions and identify rocks that have undergone inelastic failure, microseismic event occurrences were utilized. Microseismic activity has been detected at the FWU; further study of its locations, timing, and magnitude was needed to deduce the nature of the changing stress state. The results of the study revealed that microseismic events were successfully modeled within the Morrow B formation. Moment magnitudes of seismic events were within the same magnitudes for events in the reservoir, suggesting the suitability of the model. The results of the study showed that the computed moment magnitudes for seismic events were insignificant to warrant safety concerns. The study findings showed the usefulness of coupled hydromechanical models in predicting the subsurface stress changes associated with CO2 injection. The knowledge gained from this study will serve as a guideline for industries planning to undertake underground CO2 storage, and characterize the subsurface stress changes.
A Review on Active Heat Transfer Enhancement Techniques within Latent Heat Thermal Energy Storage Systems
Authors: Shank Kyle , Tiari Saeed
Published: May 2023

Renewable energy resources require energy storage techniques to curb problems with intermittency. One potential solution is the use of phase change materials (PCMs) in latent heat thermal energy storage (LHTES) systems. Despite the high energy storage density of PCMs, their thermal response rate is restricted by low thermal conductivity. The topic of heat transfer enhancement techniques for increasing thermal performance of LHTES systems has mainly focused on passive heat transfer enhancement techniques with less attention towards active methods. Active heat transfer enhancement techniques require external power supplied to the system. In this paper, recent advances in active heat transfer enhancement techniques within LHTES systems are reviewed, including mechanical aids, vibration, jet impingement, injection, and external fields. The pertinent findings related to the field are summarized in relation to the charging and discharging processes of PCMs. Suggestions for future research are proposed, and the importance of additional energy input for storage is discussed.
Supercapacitor Constant-Current and Constant-Power Charging and Discharging Comparison under Equal Boundary Conditions for DC Microgrid Application
Authors: Staņa Ģirts , Voitkāns Jānis , Kroičs Kaspars
Published: May 2023

This work analyzes and compares the differences in efficiency between supercapacitor constant-current and constant-power charging under the same boundary conditions, i.e., charging from the same initial voltage to the same final voltage in equal charging times in both variants. Similarly, supercapacitor constant-current and constant-power discharging are compared under the same boundary conditions, i.e., discharging from the same initial voltage to the same final voltage in equal discharging times for both variants. The study included calculations and virtual simulations based on the most frequently used equivalent RC model of supercapacitors. As a result, theoretical calculations and simulations with the RC model confirmed that constant-current charging/discharging is more efficient than constant-power charging/discharging. The results show that this difference is usually not higher than 1%. Practical experiments confirm an almost equal efficiency of both strategies, but it was difficult to validate exactly such small, theoretically calculated differences. Overall, from a practical point of view, the two charging/discharging methods can be considered as close, and nearly equal in terms of efficiency.
Changes in the Pattern of Weekdays Electricity Real Consumption during the COVID-19 Crisis
Authors: Jula Nicolae-Marius , Jula Diana-Mihaela , Oancea Bogdan , Papuc Răzvan-Mihail , Jula Dorin
Published: May 2023

In this paper, using data from Romania, we analysed the changes in electricity consumption generated during the COVID-19 crisis, and the measures taken against the spread of the coronavirus to limit the effects of the pandemic. Using a seasonal autoregressive econometric model, we found that, beyond seasonal (weekly, monthly, quarterly, yearly) effects, the average daily electricity real consumption in Romania, during the state of the emergency period (16 March 16 to 14 May 2020) decreased by −194.8 MW (about −2.9%), compared to the historical data (2006–March 2022), and this decrease is not due to the action of some random factors, and it is not a manifestation of domain-specific seasonality. The literature discusses the hypothesis that during the pandemic time, the profile of daily electricity consumption on weekdays was close to the typical Sunday profile. We tested a similar hypothesis for Romania. As a methodology, we tried to go beyond the simple interpretation of statistics and graphics (as found in most papers) and we calculated some measures of distances (the Mahalanobis distance, Manhattan distance) and similarity (coefficient of correlation, cosines coefficient) between the vectors of daily electricity real consumptions, by hourly intervals. As the time interval, we have analysed, for Romania, the electricity real consumption over the period January 2006–March 2022, by day of the week and within the day, by hourly intervals (5911 observations). We found (not very strong) evidence supporting a hypothesis that, in the pandemic crisis, the profile of electricity consumption approaches the weekend pattern only for the state of the emergency period, and we could not find the same evidence for the state of the alert period (June 2020–March 2022). The strongest closeness is to the hourly consumption pattern of Saturday. That is, for Romania, in terms of electricity consumption, “under lockdown, every day is a Sunday” (Staffell) it is rather “under lockdown, every day is (almost) a Saturday”! During the state of the alert period, consumption returned to the pre-crisis profile. Since certain behaviours generated by the pandemic have been maintained in the medium and long term (distance learning, working from home, online sales, etc.), such studies can have policy implications, especially for setting energy policy measures (e.g., in balancing load peaks).
Onset of Viscous Dissipation Instability in Plane Couette Flow with Temperature-Dependent Viscosity
Authors: Sene Alioune , Ben Sadek Sara , Hirata Silvia C. , Ouarzazi Mohamed Najib
Published: May 2023

The conditions for the onset of dissipation thermal instability with temperature-dependent viscosity in the plane Couette flow of a Newtonian fluid are analyzed. The studied system consists of a horizontal fluid layer confined between an adiabatic (fixed) lower wall and an isothermal (moving) upper wall. Both the exponential and the linear fluidity models are considered in order to account for the thermodependency of the fluid’s viscosity. The linear stability analysis of the base solution with respect to arbitrarily oriented normal modes is carried out numerically by employing a shooting method. The most unstable disturbances are proven to be stationary longitudinal rolls, and their stability is governed by three dimensionless parameters: the viscous dissipation Rayleigh number, Prandtl number and a parameter that represents the variability of the viscosity with temperature. It is shown that the effect of the variation of the viscosity is to promote the stability of the base flow. As expected, the two viscosity models’ results diverge as the variability of the viscosity increases, and the exponential model is found to be more stable than the linear fluidity one. By considering the thermophysical properties of real fluids, it is shown that viscous dissipation thermal instability precedes hydrodynamic instability. An energy budget analysis is proposed to better understand both the stabilization effect of the thermal variability of the viscosity and differences with viscous dissipation hydrodynamic instability.
Economic and Ecological Optimization of Thermal Insulation Depending on the Pre-Set Temperature in a Dwelling
Authors: Dylewski Robert , Adamczyk Janusz
Published: May 2023

Improvement of the energy efficiency of buildings contributes to energy savings. It is obvious that thermal modernization of a building reduces the demand for energy needed to heat it. The energy demand itself also depends significantly on the temperature maintained inside the building. The article proposes a methodology for determining the economic and ecological benefits of thermal insulation of a building and the optimal thickness of thermal insulation depending on the pre-set temperature. The analysis includes various types of heat sources and materials used for thermal insulation. A range of pre-set air temperature values in residential premises from 17 °C to 26 °C was analysed. Determining the optimal thickness of the external walls, in accordance with the preferences of building users, even at the level of designing the thermal insulation of the building, is of significant importance for economic and ecological benefits. The optimum thickness of thermal insulation in the case of the ecological assessment was much higher in each variant than in the case of the economic assessment.
Development of Alkali-Activated 3D Printable Concrete: A Review
Authors: Mujeeb Syed , Samudrala Manideep , Lanjewar Bhagyashri A. , Chippagiri Ravijanya , Kamath Muralidhar , Ralegaonkar Rahul V.
Published: May 2023

The construction world has changed day by day and is becoming more digitalized by introducing new technologies. Three-dimensional concrete printing (3DCP) is one such technology that has automated building process along with several benefits such as reduced material waste, reduced human hazard, and time savings. Traditionally, this technique utilizes cement to construct numerous structures, resulting in a significant carbon footprint and negative environmental impact. There is a need to find alternate solutions to reduce cement consumption. Alkali activation technology has replaced cement completely. The scope of development of alkali-activated 3D printable concrete utilizing agro-industrial byproducts is presented in this study. A review of the fresh and hardened properties of alkali-activated 3D printable concrete was the primary objective. The change in properties of 3D concrete mixes with the variation of additives that influence the ultimate strength parameters is presented. This study explores the curing conditions and in-depth behavior of uses of 3DCP in the construction industry. The environmental benefits over conventional concreting technology are presented. As per previous studies, the optimum mix composition per cubic meter concrete is 600–700 kg/m3 of binder content, 450 kg/m3 of alkali activator solution, and 600–800 kg/m3 of fine aggregate content. This study contributes to the making of 3D printable alkali-activated concrete.
Chytrids in Soil Environments: Unique Adaptations and Distributions
Authors: Hanrahan-Tan Deirdre G. , Lilje Osu , Henderson Linda
Published: May 2023

Chytridiomycota (zoosporic true fungi) have a consistent presence in soils and have been frequently identified within many diverse terrestrial environments. However, Chytridiomycota and other early-diverging fungi have low representation in whole-genome sequencing databases compared to Dikarya. New molecular techniques have provided insights into the diversity and abundance of chytrids in soils and the changes in their populations both spatially and temporally. Chytrids complete their life cycle within rapidly changing soil environments where they may be more common within micropores due to protection from predation, desiccation, and extreme temperatures. Reproductive and morphological changes occur in response to environmental changes including pH, fluctuating nutrient concentrations, and metals at levels above toxic thresholds. Rhizoids share some features of hyphae, including the spatial regulation of branching and the ability to attach, adapt to, and proliferate in different substrates, albeit on a microscale. Soil chytrids provide a pool of novel enzymes and proteins which enable a range of lifestyles as saprotrophs or parasites, but also can be utilised as alternative tools with some biotechnological applications. Thus, 3D live-cell imaging and micromodels such as MicroCT may provide insight into zoospore functions and rhizoid plasticity, respectively, in response to various conditions. A combination of classical techniques of soil chytrid baiting with simultaneous molecular and ecological data will provide insights into temporal population changes in response to environmental change. The authors emphasise the need to review and improve DNA-based methodologies for identifying and quantifying chytrids within the soil microbiome to expand our knowledge of their taxonomy, abundance, diversity, and functionality within soil environments.
How the Presence of CO2 Absorption Promoters and Composition of the Choline Chloride/Amine/Molecular Solvent Mixtures Influence Its Thermophysical Properties and Ability to Absorb Carbon Dioxide
Authors: Kazarina Olga V. , Golovacheva Anna A. , Markin Zakhar A. , Petukhov Anton N. , Kazarin Alexander S. , Atlaskin Artem A. , Sazanova Tatyana S. , Markov Artyom N. , Kapinos Alexander A. , Barysheva Alexandra V. , Suvorov Sergey S. , Dokin Egor S. , Vorotyntsev Ilya V. , Vorotyntsev Andrey V.
Published: May 2023

The present research provides data on the density (ρ), viscosity (η) and ability to absorb carbon dioxide of systems containing amine, molecular solvent (MS) and choline chloride (ChCl), with the investigation of the physical properties of both neat amine/MS/ChCl mixtures and their samples after complete CO2 saturation. The effect of the mixture composition was studied by varying amine from primary (monoethanolamine, MEA) to secondary (diethanolamine, DEA) and tertiary (triethanolamine, TEA) amine, and the degree of its substitution from a mono- (MEA, DEA and TEA) to a doubly-substituted (ethylenediamine, EDA) compound. The role of an MS was investigated via the exchange of ethylene glycol (EG) with water and dimethylsulfoxide (DMSO). In addition, the influence of the CO2 absorption promoters present in the ternary MEA/EG/ChCl mixture at an amount of 5 wt. % was also investigated. We show that an increase in ρ and η in the amine/EG/ChCl mixture affects the properties of neat amines. This suggests that in the studied ternary mixtures, the nature of the interspecies interactions is very similar to those in the previously studied MEA/EG/ChCl system. When EG was exchanged for H2O or DMSO, a decrease in ρ and an increase in η were observed. A comparison of the data with the corresponding properties of the systems composed of each pair of the mixture components indicates that the intensity and/or number of interspecies interactions in the present ternary mixtures were stronger than those in pure H2O, DMSO and MEA. While in the presence of promoters no significant changes in the studied properties were found, for the corresponding CO2-saturated samples, the ρ and η increased proportionally to the amount of absorbed gas. This was also the case for all the systems studied in the present research. The overall CO2 absorption of the EG-based mixtures decreased when going from primary to secondary and tertiary amines; it was 21% higher for the MEA/H2O/ChCl system compared to the mixtures containing EG and DMSO, which, in turn, showed similar absorption capacities. When the promoters were added to the MEA/EG/ChCl mixture, the highest capacity was found for the piperazine-containing system.
Histone Demethylase Modulation: Epigenetic Strategy to Combat Cancer Progression
Authors: Srivastava Rashmi , Singh Rubi , Jauhari Shaurya , Lodhi Niraj , Srivastava Rakesh
Published: May 2023

Epigenetic modifications are heritable, reversible changes in histones or the DNA that control gene functions, being exogenous to the genomic sequence itself. Human diseases, particularly cancer, are frequently connected to epigenetic dysregulations. One of them is histone methylation, which is a dynamically reversible and synchronously regulated process that orchestrates the three-dimensional epigenome, nuclear processes of transcription, DNA repair, cell cycle, and epigenetic functions, by adding or removing methylation groups to histones. Over the past few years, reversible histone methylation has become recognized as a crucial regulatory mechanism for the epigenome. With the development of numerous medications that target epigenetic regulators, epigenome-targeted therapy has been used in the treatment of malignancies and has shown meaningful therapeutic potential in preclinical and clinical trials. The present review focuses on the recent advances in our knowledge on the role of histone demethylases in tumor development and modulation, in emphasizing molecular mechanisms that control cancer cell progression. Finally, we emphasize current developments in the advent of new molecular inhibitors that target histone demethylases to regulate cancer progression.
Spatial Optimization with Morphological Spatial Pattern Analysis for Green Space Conservation Planning
Authors: Lin Jinyao , Zeng Yijuan , He Yuqi
Published: May 2023

Conservation areas are essential for preserving green spaces and biological diversity. Although previous studies have demonstrated that spatial optimization techniques are effective for balancing the relationship between ecological importance and spatial pattern during conservation practices, the design of ecological corridors still requires an efficient, intelligent, and flexible workflow. In addition, functional connectivity information is usually unavailable or very difficult to obtain. To alleviate these problems, this paper has developed a new spatial optimization-based model that combines morphological spatial pattern analysis (MSPA) with ecological importance assessment. The consideration of MSPA can guarantee enough ecological corridors in the conservation plan, while the regions with higher ecological importance can be discovered through an ecological importance assessment. This method has been applied to the planning of conservation areas in a highly developed city. Several experiments have indicated that our proposed model could achieve much better performance than conventional models in terms of spatial pattern. Therefore, this new model is expected to assist decision processes during the planning and regulation of green spaces in fragmented urban ecosystems. Furthermore, it can be applied to ecological management and planning in many other aspects because the above-mentioned research gaps are not unique to only Asian or less-developed countries.
Sustainable Behaviors Conceptualization for Forest Adventures Tours: The Case of Cloud Ocean Sites in Hyrcanian Forests Listed as UNESCO’s World Heritage Property
Authors: Ghorbani Amir , Zhu Kai , Mousazadeh Hossein , Almani Farahnaz Akbarzadeh , Zangiabadi Ali , Pireh Mahin , Dávid Lóránt Dénes
Published: May 2023

The Cloud Ocean phenomenon in the Hyrcanian Forests, listed in the UNESCO World Heritage List, is one of the most stunning yet lesser-known ecotourism destinations that has recently attracted the attention of adventure tours. However, the increasing number of ecotourists visiting these sites is expected to threaten the sensitive ecosystem of the Cloud Ocean sites. Therefore, this study aims to conceptualize sustainable behaviors for off-road forest tours in the Cloud Ocean sites of the Hyrcanian Forests. A combined qualitative-quantitative approach was adopted to achieve this aim, using the meta-synthesis method to cover the qualitative part and Smart PLS software for the quantitative data analysis. The qualitative assessment involved 19 participants, while the quantitative study included 240 experts who helped monitor and evaluate the indicators as components of the model. Previous literature has given little attention to the Cloud Ocean sites. Therefore, the conceptualization of sustainable behavior for forest adventure tours in these sites is considered the most significant contribution of this study. Paying attention to the dimensions of the proposed model can significantly reduce damage to these sites.
Identification, Classification and Expression Analysis of the CesA Gene Family from Pinus massoniana
Authors: Hou Yanqing , Wang Dengbao , Agassin Romaric Hippolyte , Zhang Chi , Lou Xuan , Zhu Peihuang , Zhang Mengyang , Huang Zichen , Ji Kongshu
Published: May 2023

Cellulose synthase (CESA) is a key enzyme in the synthesis of cellulose, which plays an important role in cell wall construction and plant growth and development. In this study, seven CesA genes of P. massoniana were identified by searching the transcriptome data. Bioinformatics analysis showed that the putative CESA proteins were composed of 984–1101 amino acids, each containing the typical motifs of CESA proteins. Phylogenetic analysis showed that Transcript4609, Tran-script2643 and Transcript1263 were clustered into three groups with proteins related to regulating secondary wall synthesis, while Transcript691, Transcript1283, Transcript418 and Transcript556 were categorized into three clades with those associated with the formation of the primary cell walls. RT-qPCR analysis showed that the CesA genes were differentially expressed in different tissues, and most of the genes were induced by different abiotic stress and hormones. Transcript4609, Tran-script2643 and Transcript1263 were mainly expressed in the xylem and could respond to drought and salt stress induced by ABA, MeJA, ETH and SA hormones, indicating that these three CesA genes may play an important role in the response to abiotic stress in P. massoniana. This study revealed the possible biochemical and physiological functions of the CesA gene in P. massoniana, which can provide a basis for further exploration of the function of the CesA gene in cell wall formation and the response to external stress.
Trees Adjust the Shape of Branch Unions to Increase Their Load-Bearing Capacity
Authors: Rust Steffen
Published: May 2023

The likelihood of branch union failure often needs to be assessed in tree risk assessment. Most of the guidance used in practice is based on the shape of these forks, specifically the shape (“U” or “V”), the angle between the branches, the presence of lateral bulges, and the aspect ratio of the branches. This study extends previous studies with a novel approach to the biomechanical analysis of fork shape and contributes results from destructive tests on two important European tree species, using comparatively large trees. Surprisingly, many samples deviated from the expected pattern of constant or decreasing cross-sectional area from the trunk beyond the fork. The results show three mechanisms that counteract the potential weakening at a bifurcation, two of which have not been documented before: an increase in section modulus from the stem base to where the stems part, an increase in section modulus caused by lateral bulging, and an increase in section modulus in the branches caused by an adjusted shape. Neither the shape of the forks nor the amount of included bark had a significant impact on their strength. Like several previous studies, the results of this study caution against the use of simple rules to assess the likelihood of branch union failure. The increasing availability of “digital twins” of urban trees may help us to use these results to assess the shape of branch unions in a quantitative way.