bluuebunny/crossref_metadata_2025 huggingface dataset:
Robust Control of SEDCM by Fuzzy-PSO
Authors: Singh Nagendra , Sharma Akhilesh Kumar , Tiwari Manish , Jasiński Michał , Leonowicz Zbigniew , Rusek Stanislav , Gono Radomir
Published: January 2023

Industries have many rotational operations that are used for design, transport, lift, drilling, rolling, robotics, and many other applications. These rotating applications require a proper controller for accurate control of the operation. Separately excited DC motors (SEDCMs) are versatile and have various industrial operations because of their specific speed control characteristics. So, for smooth and accurate operation of an SEDC motor, controllers should be used. PI and PID controllers are used in many cases, but they are ineffective for nonlinear load operation. A fuzzy controller is a heuristic controller and can provide automatic control of the operation. Its operation depends on the selection of the correct membership values. This work proposes a novel particle swarm optimization (PSO) technique that would provide the optimum value of the membership for fuzzy controllers for optimum control of the industrial processes. To obtain SEDC results, MATLAB simulation was performed, and the fuzzy controller with novel PSO was implemented. A fuzzy PSO controller used for motor speed control operation obtains a rise time of 0.00026 s, settling time of 0.000214 s, maximum overshoot of zero, and delay time of 0.016 s, which are the best values when compared to PID and PID-Fuzzy controllers. It is observed that the results obtained from the separately excited DC motor using a fuzzy PSO controller improve the dynamic behavior of the motor that so it smoothly tracks the required speed without any more overshoot or oscillation than the PID controller. Such dynamic, stable operation of the motor makes it perfect for industrial as well as household operations.
Progress of Placement Optimization for Accelerating VLSI Physical Design
Authors: Qiu Yihang , Xing Yan , Zheng Xin , Gao Peng , Cai Shuting , Xiong Xiaoming
Published: January 2023

Placement is essential in very large-scale integration (VLSI) physical design, as it directly affects the design cycle. Despite extensive prior research on placement, achieving fast and efficient placement remains challenging because of the increasing design complexity. In this paper, we comprehensively review the progress of placement optimization from the perspective of accelerating VLSI physical design. It can help researchers systematically understand the VLSI placement problem and the corresponding optimization means, thereby advancing modern placement optimization research. We highlight emerging trends in modern placement-centric VLSI physical design flows, including placement optimizers and learning-based predictors. We first define the placement problem and review the classical placement algorithms, then discuss the application bottleneck of the classical placement algorithms in advanced technology nodes and give corresponding solutions. After that, we introduce the development of placement optimizers, including algorithm improvements and computational acceleration, pointing out that these two aspects will jointly promote accelerating VLSI physical design. We also present research working on learning-based predictors from various angles. Finally, we discuss the common and individual challenges encountered by placement optimizers and learning-based predictors.
Text Network-Based Method for Measuring Hand Functions in Degenerative Brain Disease Patients
Authors: Kang Cholzi , Kim Jaehoon , Moon Hosang , Chung Sungtaek
Published: January 2023

In this study, we collected various past study results on tools and analytical methods for measuring hand functions of patients with degenerative brain diseases, such as Parkinson’s disease and stroke, and selected and proposed appropriate hand function measurement tools, methods, and analysis software based on text network analysis. We searched the literatures using keywords related to degenerative brain disease and stroke patients for participant types, use of devices and sensors for the intervention types, and hand function assessment for measurement types. Among the 2484 literatures collected, 19 were eventually selected based on certain inclusion and exclusion criteria. As a result of text network analysis, the degree-centrality and the betweenness centrality were the highest in the keyword of Parkinson’s disease for the participant type, force sensor for the intervention type, and finger tapping for the measurement type. Based on these results, pinch gloves comprising an FSR sensor were manufactured, and software and contents were implemented to measure and analyze various quantitative parameter values during finger tapping. The software can evaluate endurance and agility by measuring the finger-tapping intensity and operation time using the index finger and thumb. The contents can evaluate the stability of hand functions by analyzing the coefficient of variation of the tapping interval, the average contact time, and the accuracy of hand functions by analyzing the reaction rate to the presented visual stimulus. As a result of comparing hand functions through 10 types of analysis parameters with a sample of 12 ordinary subjects (8 men and 4 women) using the manufactured pinch gloves, there was a difference between the two genders in the items evaluating muscle strength and agility, and a significant difference in the analysis parameters evaluating stability and accuracy. The results indicate that using the text network analysis-based hand function measurement tool and the method proposed in this study should help derive the objective research results as well as a quantitative comparison of research results of various researchers.
Fast Heterogeneous Clutter Suppression Method Based on Improved Sparse Bayesian Learning
Authors: Wang Qiang , Zhang Yani , Li Zhihui , Zhao Weihu
Published: January 2023

In order to deal with the problem space-time adaptive processing (STAP) performance degradation of an airborne phased array system caused by the serious shortage of independent and identical distributed (IID) training samples in the nonhomogeneous clutter environment, an improved direct data domain method based on sparse Bayesian learning is proposed in this paper, which only uses a single snapshot data of a cell under test (CUT) to suppress the clutter and has fast computational speed. Firstly, three hyper-parameters required to obtain the sparse solution are derived. Secondly, the comparative analysis of their iterative formulas is made, and the piecewise iteration of hyper-parameter that has an obvious influence on the computational complexity of obtaining sparse solution is presented. Lastly, with the approximate prior information of the target, the clutter sparse solution is given and its covariance matrix is effectively estimated to calculate the adaptive filter weight and realize the clutter suppression. Simulation results verify that the proposal can dramatically decrease the computational burden while keeping the superior heterogeneous clutter suppression performance.
Effect of Alkaline Pretreatment on the Fuel Properties of Torrefied Biomass from Rice Husk
Authors: Tsai Chi-Hung , Shen Yun-Hwei , Tsai Wen-Tien
Published: January 2023

Lignocellulosic biomass from rice husk (RH) is a renewable resource for fuel production, but it could pose ash-related challenges. This work focused on investigating the effects of pretreatment at different sodium hydroxide (NaOH) concentrations (i.e., 0.0, 0.25, 0.50, 0.75 and 1.00 M) on the calorific values and ash contents of treated RH products, and also finding the optimal torrefaction conditions. The results showed that alkaline pretreatment by sodium hydroxide (NaOH) reduced the ash content in the RH samples by over 85 wt%. Due to its relatively excellent calorific values and low ash content, the RH sample with 0.25 M NaOH pretreatment (i.e., RH-25) was chosen as a starting feedstock in the subsequent torrefaction experiments as a function of 240–360 °C for holding time of 0–90 min. In addition, the surface properties by scanning electron microscopy—energy dispersive X-ray spectroscopy (SEM-EDS) and Fourier-transform infrared spectroscopy (FTIR) were also used to observe the elemental compositions preliminarily. Based on the fuel properties of the torrefied RH products, the optimal torrefaction conditions can be found at around 280 °C for holding 30 min. As compared to the calorific value of the RH-25 (i.e., 18.74 MJ/kg) and its mass yield (i.e., 0.588), the calorific value, enhancement factor and energy yield of the optimal product were 28.97 MJ/kg, 1.55 and 0.91, respectively. Although the resulting product has a high calorific value like coal, it could have slight potential for slagging and fouling tendency and particulate matter emissions due to the relatively high contents of silicon (Si) and sodium (Na), based on the results of EDS and FTIR.
Modelling and Energy Management of an Off-Grid Distributed Energy System: A Typical Community Scenario in South Africa
Authors: Obaro Adewale Zakariyahu , Munda Josiah Lange , YUSUFF Adedayo Adedamola
Published: January 2023

Conventional power systems have been heavily dependent on fossil fuel to meet the increasing energy demand due to exponential population growth and diverse technological advancements. This paper presents an optimal energy model and power management of an off-grid distributed energy system (DES) capable of providing sustainable and economic power supply to electrical loads. The paper models and co-optimizes multi-energy generations as a central objective for reliable and economic power supply to electrical loads while simultaneously satisfying a set of system and operational parameters. In addition, mixed integer nonlinear programing (MINLP) optimization technique is exploited to maximize power system generation between interconnected energy sources and dynamic electrical load with highest reliability and minimum operational and emission costs. Due to frequent battery cycling operation in the DES, rainflow algorithm is applied to the optimization result to estimate the depth of discharge (DOD) and subsequently count the number of cycles. The validity and performance of the power management strategy is evaluated with an aggregate load demand scenario of sixty households as a benchmark in a MATLAB program. The simulation results indicate the capability and effectiveness of optimal DES model through an enhanced MINLP optimization program in terms of significant operational costs and emission reduction of the diesel generator (DG). Specifically, the deployment of DES minimizes the daily operational cost by 71.53%. The results further indicate a drastic reduction in CO2 emissions, with 22.76% reduction for the residential community load scenario in contrast to the exclusive DG system. This study provides a framework on the economic feasibility and effective planning of green energy systems (GESs) with efficient optimization techniques with capability for further development.
Construction Work and Utilities in Historic Centers: Strategies for a Transition towards Fuel-Free Construction Sites
Authors: Simeone Davide , Rotilio Marianna , Cucchiella Federica
Published: January 2023

In historic centers, construction works consist of complex activities that must balance the operative requirements and lower the impacts on a delicate and sensible environment. In this urban system, especially regarding relevant reconstruction processes such as post-natural disaster scenarios, construction operations are performed through the traditional construction processes, using fuel-based generators and vehicles with limited efficiency and with relevant impacts in terms of the consumed energy, noise and vibrations. In the global transition of the construction sectors towards a zero-emission and fuel-free future, construction sites in historic centers represent a particular opportunity where the application of fuel-free strategies is particularly feasible and can provide additional value in terms of the environmental impact, productivity and health and safety. This work addresses the need for a framework to provide the basis for the application of fuel-free principles in construction within historic city centers dealing with two major concepts: the adaptive construction site as a way to reduce the energy demand and the potential adoption of fuel-free machines. The former is derived from the analysis of a real project in the historic city of L’Aquila, while the latter is defined through the identification and categorization of the applicable electric machines, equipment and vehicles and the discussion of the limits, opportunities and added value of the fuel-free strategies.
Consideration on Proper Management and Final Disposal of Residues from SRF Manufacturing Facilities in South Korea
Authors: Lee Suyoung , Kim Kyuyeon , Kim Dongyoon , Kang Jungu , Jeon Taewan
Published: January 2023

Solid Refuse Fuel (SRF) manufacturing facilities process 4.72 million tons of waste annually. The residues generated after manufacturing SRF products account for 35–40% of the input waste, and most of them are finally disposed of in landfills. The process flow and management status of SRF manufacturing facilities were investigated, and the residues generated from SRF manufacturing facilities using municipaland industrial waste, respectively, were separated by particle size. The appropriate separation conditions for the residues according to the characteristics of the input raw materials were presented through the analysis of loss on ignition (LOI), organic foreign substance content, heating value, and carbon content. Based on this, the appropriate management criteria (draft) for the subsequent treatment of final residues were derived to improve recyclability. Residues generated in the SRF manufacturing process need to be additionally separated into combustibles and incombustibles through cylindrical rotary separating devices before subsequent the final disposal process.
A Brief Survey on the Development of Intelligent Dispatcher Training Simulators
Authors: Dong Ao , Lai Xinyi , Lin Chunlong , Lin Changnian , Jin Wei , Wen Fushuan
Published: January 2023

The well-known dispatcher training simulator (DTS), as a good tool to train power system dispatchers, has been widely used for over 40 years. However, with the high-speed development of the smart grid, the traditional DTSs have struggled to meet the power industry’s expectations. To enhance the effectiveness of dispatcher training, technical innovations in DTSs are becoming more and more demanding. Meanwhile, the ever-advancing artificial intelligence (AI) technology provides the basis for the design of intelligent DTSs. This paper systematically reviews the traditional DTS in terms of its origin, structure, and functions, as well as limitations in the context of the smart grid. Then, this paper summarizes the AI techniques commonly used in the field of power systems, such as expert systems, artificial neural networks, and the fuzzy set theory, and employs them to develop intelligent DTSs. Regarding a less studied aspect of DTSs, i.e., intelligent training control, we introduce the Adaptive Learning System (ALS) to develop a personalized training program, which will also be an important aspect of future research.
Review of Key Technologies for Offshore Floating Wind Power Generation
Authors: Zhou Bowen , Zhang Zhibo , Li Guangdi , Yang Dongsheng , Santos Matilde
Published: January 2023

In recent years, due to the global energy crisis, increasingly more countries have recognized the importance of developing clean energy. Offshore wind energy, as a basic form of clean energy, has become one of the current research priorities. In the future, offshore wind farms will be developed in deep and distant sea areas. In these areas, there is a new trend of floating offshore wind platforms replacing fixed wind power platforms, due to their low cost, ease of installation, and independence from the water depth. However, the stability of offshore floating platforms is poor and their power fluctuations are significant; furthermore, they are more prone to failure because of sea wind, waves, and currents. This paper summarizes and analyzes the current research progress and critical technical issues of offshore floating wind power generation, such as stability control technology, integrated wind storage technology, wind power energy management, and long-distance transmission of electricity for floating wind power generation at sea. Finally, future research directions for key offshore wind power technologies are presented.
Influence of Roller Blinds Shading Strategy on West and South Facing Buildings
Authors: Hu Tzu-Yang , Chen Chun-Kuei , Lin Feng-Yi , Lin Ta-Hui
Published: January 2023

This study investigates the impact of roller blinds as an energy-saving strategy in a subtropical climate. Lighting control experiments were performed on west-facing and south-facing windows in the Subtropical Performance-Testbed for Innovative eNergy Research in Buildings Laboratory (SPINLab). This study accepts sunlight below 8000 lux and requires the indoor lighting of at least a reading of 500 lux. For the west-facing window experiment, the curtain energy-saving strategy implemented in this study resulted in 10% less energy consumption for air-conditioning and saved 90% of the lighting power consumption of the west facing window building. For the south-facing window experiment, we found that sunlight can fully supplement the lighting without adjusting the roller blinds because the window opening is different from the sunlight direction. In addition, the significant heat flux difference between the west-facing and south-facing windows experiments is also reflected in the energy consumption of the air conditioners.
Analysis of Net-Metering and Cross-Subsidy Effects in South Korea: Economic Impact across Residential Customer Groups by Electricity Consumption Level
Authors: Kim Junhyung , Baek Keon , Lee Eunjung , Kim Jinho
Published: January 2023

Recently, thanks to various support mechanisms, residential photovoltaics (PVs) for self-consumption are proliferating at a rapid pace. The net-metering scheme, one of the prevailing support mechanisms for self-consumption PVs, contributes to the proliferation of residential PVs by enhancing the economic benefits of PV adopters, but it suffers from certain disadvantages, such as missing network revenue of utilities and spread of cross-subsidies between the customers. This paper analyzes the cross-subsidy effect of residential PV proliferation across customer groups segmented according to their PV adoption and electricity consumption level under the net-metering scheme in the Korean electricity market. The results show that missing network revenue of utilities increase by about 0.83% for every 1% increase of residential PV penetration, and customers in the lowest usage tier provide more cross-subsidies toward customers in the higher usage tiers as with higher proliferation of residential PVs. In addition, this paper suggests that the cross-subsidy effect between customers can be reduced by introducing a new network charge design that is more consistent with the cost-causality principle as well as targeted deployment policies for self-consumption PVs.
MPPT Solution for Commercial Small Wind Generation Systems with Grid Connection
Authors: Ramos-Paja Carlos Andres , Henao-Bravo Elkin Edilberto , Saavedra-Montes Andres Julian
Published: January 2023

Power generation using small wind turbines connected to AC grids has been gaining attention and contributions in recent years. As small wind turbines are connected to remote areas as support energy systems, there are not extensive contributions connecting those small turbines to AC grids. This paper presents the integration of a small wind generation system which is AC-grid-connected. The system is composed of a 160 W commercial small wind turbine with a permanent magnet synchronous generator and a 140 W Texas Instruments (Dallas, TX, USA) development kit devoted to connecting photovoltaic panels to AC grids. Several experimental tests were developed to characterize the devices, e.g., to obtain the power–current curves of the synchronous generator. Moreover, a mathematical model of the flyback converter is developed in detail in order to design a new converter controller. All the control capacity of the development kit is used to extract the maximum power of the synchronous generator, to reject the oscillation produced by the inverter and to connect the system to the AC grid. Experimental results show that is possible to integrate these devices to provide energy to power systems with some achievable adaptations.
A New Approach to the Use of Energy from Renewable Sources in Low-Voltage Power Distribution Networks
Authors: Mazur Łukasz , Kłosowski Zbigniew
Published: January 2023

Currently, in rural networks with a large amount of distributed generation, PV installations are often disconnected due to the excessively high voltage in the network, which often exceeds the limit value, in accordance with the PN-EN 50160 standard. Disconnecting such an installation extends the return on investment costs by preventing the generation of electricity for the owner’s needs and results in the consumption of this energy from the grid. In such a case, the recipient has to bear the costs related to the purchase of this energy. In order to solve the problem of excessively high voltage in a low-voltage distribution network with a large amount of distributed generation, the authors of this article proposed a new approach to the use of electricity from these sources. In order to present the benefits of the proposed solution, a computer simulation was used. In order to carry it out, a mathematical model of a low-voltage power grid with distributed generation was developed using the electric multipole method and Newton’s method, which is discussed in the paper. To determine the advantages of the proposed solution, nine variants of the operation of an exemplary low-voltage power grid over one day were analyzed. The main conclusion based on the analysis of the results is that the proposed approach improves the operation of the power system by maintaining the voltage values within the standard range for the entire tested part of the network. In addition, the proposed approach does not increase the power or electricity when generating electricity from a PV installation. The proposed solution can also serve as a very attractive stimulus for the creation of energy cooperatives.
Study on Slagging Characteristics of Co-Combustion of Meager Coal and Spent Cathode Carbon Block
Authors: Zhang Jigang , Liu Zijun , Li Xian , Wang Bin , Teng Zhaocai , Han Kuihua
Published: January 2023

The harmless disposal of spent cathode carbon blocks (SCCBs) has become an urgent issue in the primary aluminum industry, and the disposal of SCCBs by co-combustion in pulverized coal boilers is expected to be the most effective treatment method. A muffle furnace at 815 °C was used in this study to perform a co-combustion experiment of meager coal and SCCBs. The ash fusion characteristics (AFTs), microscopic morphology, and minerals composition of co-combustion ash were characterized. The interaction mechanism of different mineral components and the change in AFTs and viscosity-temperature characteristics were investigated using FactSage software. Results show that the change in the ash deformation temperature (DT) is correlated linearly with the SCCB addition ratio, whereas other characteristic temperatures exhibit a nonlinear relationship. The contents of SiO2, Al2O3, and Na2O collectively determine the DT in the ash, and the influence degree from high to low is in the order of SiO2, Na2O, and Al2O3. The phase diagram of Na2O–Al2O3–SiO2 is used to accurately predict the changing trend of the melting point of co-combustion ash. The ratio changes between refractory and fusible minerals in the ash, as well as the degree of low-temperature eutectic reaction between sodium- and calcium-containing minerals, are the main factors affecting the melting point of ash. When the blending amount of SCCBs is 5%, mostly complete combustion is achieved, and slagging does not occur easily. The optimal blending ratio of SCCBs is obtained using the co-combustion method from the aspect of AFTs and viscosity-temperature characteristics. This work lays a theoretical foundation for industrial application.
Working with Different Building Energy Performance Tools: From Input Data to Energy and Indoor Temperature Predictions
Authors: d’Ambrosio Alfano Francesca Romana , Olesen Bjarne Wilkens , Pepe Daniela , Palella Boris Igor
Published: January 2023

Energy consumption calculations and thermal comfort conditions assessment are crucial issues in building simulations when using Building Energy Performance Simulation (BEPS) tools. The available software has been separately validated under different boundaries and operating conditions. Consequently, the predicted output of the same building simulated with two separate software can disagree. This issue is relevant not only for research purposes but also for professionals who need to compare the energy performance of the same building with different simulation engines. This work aims at contributing to the field in two ways. Above all, it clarifies the preparation of the building model and the correct definition of input data and boundary conditions when different software are used (IDA ICE and Design Builder/Energy Plus). In addition, it compares the output (energy and indoor temperatures) of two BEPS for the same building (in different configurations) exposed to the same weather conditions. The study shows that the two most significant differences are represented by the temperature values, while the energy predictions agree.
Artificial Intelligence and Machine Learning for Energy Consumption and Production in Emerging Markets: A Review
Authors: Mhlanga David
Published: January 2023

An increase in consumption and inefficiency, fluctuating trends in demand and supply, and a lack of critical analytics for successful management are just some of the problems that the energy business throughout the world is currently facing. This study set out to assess the potential contributions that AI and ML technologies could make to the expansion of energy production in developing countries, where these issues are more pronounced because of the prevalence of numerous unauthorized connections to the electricity grid, where a large amount of energy is not being measured or paid for. This study primarily aims to address issues that arise due to frequent power outages and widespread lack of access to energy in a wide range of developing countries. Findings suggest that AI and ML have the potential to make major contributions to the fields of predictive turbine maintenance, energy consumption optimization, grid management, energy price prediction, and residential building energy demand and efficiency assessment. A discussion of what has to be done so that developing nations may reap the benefits of artificial intelligence and machine learning in the energy sector concluded the paper.
A Fuzzy Logic Control for Maximum Power Point Tracking Algorithm Validated in a Commercial PV System
Authors: Derbeli Mohamed , Napole Cristian , Barambones Oscar
Published: January 2023

Photovoltaic (PV) panels are devices capable of transforming solar energy into electricity without emissions. They are still a trending technology in the market not only because of the renewable features but also due to the avoidance of movable parts, which makes them an option with low maintenance. If the output voltage is insufficient or needs to be regulated, a boost converter is commonly connected to a PV panel. In this article, a commercial PV with a boost converter is controlled through a dSPACE platform for a maximum power point tracking (MPPT) task. Due to previous related experience, a fuzzy logic technique is designed and tested in real-time. The results are compared with an incremental conductance (IncCond) algorithm because it is a feasible and reliable tool for MPPT purposes. The outcomes show enhancement (in comparison with IncCond) in the steady-state oscillation, response time and overshoot values, which are 73.2%, 81.5% and 52.9%, respectively.
Numerical Analysis of Two-Stage Turbine System for Multicylinder Engine under Pulse Flow Conditions with High Pressure-Ratio Turbine Rotor
Authors: Kozak Dariusz , Mazuro Paweł
Published: January 2023

Internal combustion engine (ICE) exhaust gases provide a high amount of energy which is partially lost to the environment. Such energy can be recovered with a turbocharger turbine or other after-treatment device. As the engine exhaust flow varies not only with the engine load but also with the opening and closing of the exhaust valves, a proper matching between the engine and the turbine should be established to maximize the recovery of waste energy. That is why a twin-scroll or dual turbocharging system is implemented, especially in multi-cylinder engines. Such systems require a very complex pipeline to eliminate the interference of the exhaust pulses between the adjacent cylinder ignitions. In this study, the two-stage, multi-channel turbine system was investigated for two different rotor geometries: the old, high-performance rotor A and the smaller but more modern rotor B, which was scaled to match rotor A. Both geometries were compared at three different turbine speeds and variable turbine geometry (VTG) vane positions. It was found that the two-stage turbine system with rotor B geometry provided an 8% higher total efficiency than rotor A due to the lower flow losses within the rotor passage.
Hydrogen Production Methods Based on Solar and Wind Energy: A Review
Authors: Benghanem Mohamed , Mellit Adel , Almohamadi Hamad , Haddad Sofiane , Chettibi Nedjwa , Alanazi Abdulaziz M. , Dasalla Drigos , Alzahrani Ahmed
Published: January 2023

Several research works have investigated the direct supply of renewable electricity to electrolysis, particularly from photovoltaic (PV) and wind generator (WG) systems. Hydrogen (H2) production based on solar energy is considered to be the newest solution for sustainable energy. Different technologies based on solar energy which allow hydrogen production are presented to study their benefits and inconveniences. The technology of water decomposition based on renewable energy sources, to produce hydrogen, can be achieved by different processes (photochemical systems; photocatalysis systems, photo-electrolysis systems, bio-photolysis systems, thermolysis systems, thermochemical cycles, steam electrolysis, hybrid processes, and concentrated solar energy systems). A comparison of the different methods for hydrogen production based on PV and WG systems was given in this study. A comparative study of different types of electrolyzers was also presented and discussed. Finally, an economic assessment of green hydrogen production is given. The hydrogen production cost depends on several factors, such as renewable energy sources, electrolysis type, weather conditions, installation cost, and the productivity of hydrogen per day. PV/H2 and wind/H2 systems are both suitable in remote and arid areas. Minimum maintenance is required, and a power cycle is not needed to produce electricity. The concentrated CSP/H2 system needs a power cycle. The hydrogen production cost is higher if using wind/H2 rather than PV/H2. The green energy sources are useful for multiple applications, such as hydrogen production, cooling systems, heating, and water desalination.
How Does the Digital Economy Affect Carbon Emission Efficiency? Evidence from Energy Consumption and Industrial Value Chain
Authors: Lyu Kangni , Yang Shuwang , Zheng Kun , Zhang Yao
Published: January 2023

China is confronted with the dual constraints of economic transformation and carbon emission reduction. As the digital economy is a key force in promoting economic transformation and optimizing industrial structure, it is crucial to analyze the digital economy’s impact on carbon emission reduction from the perspective of energy consumption and industrial value chain implications. We selected data from 251 prefecture-level cities and above in China from 2011 to 2019 as research samples, measured the development level of the digital economy using the entropy value method, and constructed relevant regression models based on two-way fixed effects, intermediary analysis, and moderation analysis. The research reveals that: (1) The digital economy has a significant contribution to carbon emission efficiency, and there are significant regional heterogeneity and city size differences; (2) The digital economy can improve carbon emission efficiency by reducing energy consumption. (3) From a value chain perspective, industrial structure rationalization weakens the carbon emission efficiency improvement effect of the digital economy to a certain extent, whereas industrial structure upgrading obviously enhances the carbon efficiency improvement effect of the digital economy. The above findings enrich the research in the field of digital economy and environmental governance, contribute to a more comprehensive understanding of the mechanisms by which the digital economy affects the carbon emission efficiency, as well as provide policy implications for enhancing the use of the digital economy in the regional energy consumption and industrial value chain.
Glycerol Dehydration to Acrolein Catalyzed by Silicotungstic Acid: Effect of Mesoporous Support
Authors: Liu Lu , Yu Fei , Wang Siqun , Ye Xiaofei Philip
Published: January 2023

To facilitate value-added chemical production from renewable glycerol, gas-phase glycerol dehydration to acrolein was conducted using supported silicotungstic acid as solid acid catalysts, focusing on the effects of mesoporous catalyst supports on the catalytic performance. One alumina (Al) support with average mesopore size of 30 nm and two silica supports (Si1254 and Si1252) with mesopore size of 6 nm and 11 nm, respectively, were comparatively evaluated in this study. It was found that the Si1254 silica support with the smallest pore size (6 nm) deactivated the fastest, decreasing both the glycerol conversion and acrolein selectivity along the time-on-stream. The other silica support Si1252 with 11 nm pore size provided an acrolein yield comparable to the Al support over the tested 7.5 h time-on-stream (73.9 mol% for Si1252 vs. 74.1 mol% for Al). However, the mechanisms for achieving the comparable yield are different. Si1252 showed higher acrolein selectivity than Al, but it also deactivated faster than Al due to its quicker coking. On the other hand, Al showed more stable performance in terms of glycerol conversion rate and less coking, but it had lower acrolein selectivity and a higher selectivity to byproducts, especially the undesired byproducts of acetaldehyde and propionaldehyde, which posed difficulties in downstream separation.
Neural-Network-Inspired Correlation (N2IC) Model for Estimating Biodiesel Conversion in Algal Biodiesel Units
Authors: Mahfouz Abdullah Bin , Ali Abulhassan , Crocker Mark , Ahmed Anas , Nasir Rizwan , Show Pau Loke
Published: January 2023

Algal biodiesel is of growing interest in reducing carbon emissions to the atmosphere. The production of biodiesel is affected by many process parameters. Although many research works have been conducted, the influence of each parameter on biodiesel production is not well understood when considering a complete system. Therefore, the experimental data from literature sources related to types of algae, methanol-to-algal-oil ratio, temperature, and time on the biodiesel production rate were reviewed and introduced into a neural-network-inspired correlation (N2IC) model to study the rate of transesterification. The developed N2IC model optimized for biodiesel production is based on the studied variables, specifically reaction time, temperature, methanol-to-algal-oil ratio, and type of algae. It was found from ANN analysis that the reaction time is the most significant parameter with 87% importance, followed by temperature (85%), alcohol-to-oil-molar ratio (75%), and type of algae (62%). Using error analysis, the results from the proposed N2IC model show excellent agreement with the experimentally obtained values with an overall 5% error. The results show that the N2IC model can be utilized effectively to solve the problem of industrial biodiesel production when various operating data are readily available.
Insight into the Substrate Specificity of Lactobacillus paracasei Aspartate Ammonia-Lyase
Authors: Huang Yi-Hao , You Weir-Chiang , Chen Yung-Ju , Ciou Jhih-Ying , Hsieh Lu-Sheng
Published: January 2023

Aspartate ammonia-lyase (AAL) catalyzes the reversible conversion reactions of aspartate to fumaric acid and ammonia. In this work, Lactobacillus paracasei LpAAL gene was heterologously expressed in Escherichia coli. As well as a recombinant His-tagged LpAAL protein, a maltose-binding protein (MBP) fused LpAAL protein was used to enhance its protein solubility and expression level. Both recombinant proteins showed broad substrate specificity, catalyzing aspartic acid, fumaric acid, phenylalanine, and tyrosine to produce fumaric acid, aspartic acid, trans-cinnamic acid, and p-coumaric acid, respectively. The optimum reaction pH and temperature of LpAAL protein for four substrates were measured at 8.0 and 40 °C, respectively. The Km values of LpAAL protein for aspartic acid, fumaric acid, phenylalanine, and tyrosine as substrates were 5.7, 8.5, 4.4, and 1.2 mM, respectively. The kcat values of LpAAL protein for aspartic acid, fumaric acid, phenylalanine, and tyrosine as substrates were 6.7, 0.45, 4.96, and 0.02 s−1, respectively. Therefore, aspartic acid, fumaric acid, phenylalanine, and tyrosine are bona fide substrates for LpAAL enzyme.
Deciphering Microbial Diversity and Functional Codes of Traditional Fermented Whole Grain Tianpei from Typical Regions of China
Authors: Ren Fei , Liu Ming , Liu Yanxiang , Tian Xiaohong , Jiang Ping , Tan Bin
Published: January 2023

Whole grains are a crucial part of healthy and sustainable diets, attracting great attention. Tianpei is a popular traditional fermented whole grain food and beverage from China. It is suitable for all ages with lots of health benefits. However, its microflora and their functions, relations between microbial taxa and functions with Tianpei properties, were still little informed, limiting the fermentation optimization and quality improvement. In this study, the characteristics and distribution of the microbial flora taxa and their functions of the fermented whole grain Tianpei from typical regions of China were mainly deciphered through metagenomic methods. Phyla Mucoromycota, Firmicutes, Ascomycota, and Proteobacteria were the most abundant. Rhizopus, Limosilactobacillus, and Lactobacillus were the most abundant genera. Microbial COG functions carbohydrate transport and metabolism (mainly including fructose, galactose, glucose, L-arabinose, and mannose) and amino acid transport and metabolism (mainly including arginine, asparagine, glutamine, and glycine) kept a high abundance. PCA (Principal Component Analysis) illustrated that the microbial community and their functions of every Tianpei sample clustered individually based on the analysis, related with the factors of raw material and sources. The microbial taxa, microbial functions, and the Tianpei properties were significantly correlated. Rhizopus, Limosilactobacillus, and Lactobacillus contributed most COG functions in Tianpei samples. Analysis of quorum sensing, pfam, secretion protein, probio, and cytochromes P450 were also annotated and found among Tianpei microbial communities. A sum of 105 probiotics were classified, mainly belonging to Lactobacillus, Leuconostoc, Acetobacter, Bacillus, Bifidobacterium, Pediococcus, etc. Tianpei samples made in the library with the most abundant and functional microbial key taxa strains—Rhizophus oryzae, Lactobacillus plantarum, and Limosilactobacillus fermentum—showed rich nutrient chemicals. The results indicate that microbial taxa and their functions could determine Tianpei properties. Thus, the quality, nutrients, flavor, and industrial production of Tianpei could be further investigated, promoted, and improved in the future based on the characteristics of these microbial taxa and their functions, such as the regulations of the main carbohydrate and AA. The study will also lay a foundation for the fermentative characteristics and condition technology of fermented whole grain food.
Role of Attention and Design Cues for Influencing Cyber-Sextortion Using Social Engineering and Phishing Attacks
Authors: Pethers Brent , Bello Abubakar
Published: January 2023

Cyber sextortion attacks are security and privacy threats delivered to victims online, to distribute sexual material in order to force the victim to act against their will. This continues to be an under-addressed concern in society. This study investigated social engineering and phishing email design and influence techniques in susceptibility to cyber sextortion attacks. Using a quantitative methodology, a survey measured susceptibility to cyber sextortion with a focus on four different email design cues. One-way repeated measures ANOVA, post hoc comparison tests, Friedman nonparametric test, and Spearman correlation tests were conducted with results indicating that attention to email source and title/subject line significantly increased individuals’ susceptibility, while attention to grammar and spelling, and urgency cues, had lesser influence. As such, the influence of these message-related factors should be considered when implementing effective security controls to mitigate the risks and vulnerabilities to cyber sextortion attacks.
Impact of Fire History on the Structure of a Temperate Forest in Northern Mexico
Authors: Zúñiga-Vásquez José M. , Villanueva-Díaz José , Cerano-Paredes Julián , Quiñonez-Barraza Gerónimo
Published: January 2023

Understanding the ecological role of fire in forests is essential for proper management and conservation programs. The objectives of this study were: (1) to reconstruct the history of fires in a temperate forest in Sierra Madre Occidental; and (2) to interpret the impacts of fire and climate on forest structure. Sixty tree cross-sections with fire scars were analyzed, and descriptive statistics of fire history were generated. Additionally, growth cores were analyzed, and the ages of trees of different diameter categories were calculated. The synchrony between fire history and tree establishment was determined, and precipitation and Palmer Drought Severity Index (PDSI) values were correlated with the number of trees established per year. The presence of 137 fire scars was determined, which allowed the reconstruction of 41 fire events over the period 1855–2019; however, only the period 1940–2015 was used to compare tree recruitment, as tree establishment was detected in this period. The mean fire interval (MFI) was 2.28 years in general, and 12.17 years for extensive fires. As regards vegetation, a continuous recruitment pattern was observed, typical of a frequent low-intensity fire regime, although peak regeneration occurred after extensive fires. The correlation analysis showed that the number of trees established per year was influenced by the wet conditions that occurred in December of the previous year and the dry conditions in September and October of the previous year. This finding demonstrates the historical influence of fire and climate on the structure of the current stand in the study area. Therefore, the present study highlights the importance of including fire in forest management programs, considering the natural fire regime to which the species in this ecosystem are already adapted.
Round Goby Detection in Lakes Huron and Michigan—An Evaluation of eDNA and Fish Catches
Authors: Przybyla-Kelly Kasia J. , Spoljaric Ashley M. , Nevers Meredith B.
Published: January 2023

Aquatic surveys for fish in large water bodies (e.g., Laurentian Great Lakes of North America) often require a flexible approach using multiple methods, surveying different depths, and sampling across seasons, especially when the target species is elusive in its natural habitat. The round goby (Neogobius melanostomus) is an invasive, bottom-dwelling fish inhabiting rocky areas of all five Great Lakes. While trawl surveys are typically used for abundance assessments, angling has been demonstrated as a means of supplementing surveys with additional data. Yet, round goby abundance and distribution is still not well described. Recently, with considerable success, scientists have explored sampling environmental DNA (eDNA) to complement traditional monitoring techniques for population abundance estimates, early detection of invasive species, and spawning or migration events. Therefore, we collected eDNA from water samples alongside bottom trawls and hook and line angling in Lakes Huron and Michigan to detect round goby. eDNA samples were analyzed by both droplet digital PCR (ddPCR) and quantitative PCR (qPCR) to maximize the likelihood of detection. Overall, round goby was captured in 23% of the trawls, but the eDNA based methods detected round goby in 74% and 66% of samples by ddPCR and qPCR, respectively, mostly in samples collected at <30 m depths, and mostly in the fall. More studies comparing eDNA based methods to traditional monitoring, especially trawls in large open waters, may contribute to a better understanding of using eDNA in population assessments.
Localization of Acetylcholine, Alpha 7-NAChR and the Antimicrobial Peptide Piscidin 1 in the Macrophages of Fish Gut: Evidence for a Cholinergic System, Diverse Macrophage Populations and Polarization of Immune Responses
Authors: Zaccone Giacomo , Alesci Alessio , Mokhtar Doaa , Aragona Marialuisa , Guerrera Maria , Capillo Gioele , Albano Marco , de Oliveira Fernandes Jorge , Kiron Viswanath , Sayed Ramy , Hussein Marwa , Lo Cascio Patrizia , Kuciel Michal , Zuwala Krystyna , Germanà Antonino , Icardo Jose , Lauriano Eugenia
Published: January 2023

The recognition and elimination of invading pathogens are vital for host survival. Macrophages play a central role in host protection and cells functionally reminiscent of vertebrate macrophages are present in all multicellular organisms. A pattern responsible for bacterial recognition found on the surface of macrophages is CD14. These cells possess a repertoire of antimicrobial molecules stored in their granules and lysosomes. Polarization states observed in mammalian macrophages termed M1 and M2 also likely exist in fish macrophages. Markers for macrophage subtypes are slowly but definitively emerging in fish species. In the present study cell markers such as CD14, acetylcholine, alpha 7 acetylcholine nicotinic receptor (nAChR) subtype, the inducible nitric oxidase synthase (iNOS), and the antimicrobial peptide piscidin 1 are reported for the first time in the intestinal macrophages of both catfish Heteropneustes fossilis (Bloch, 1794) and the African bonytongue Heterotis niloticus (Cuvier, 1829) along the anterior and the posterior axis and the concentric muscle layers. Many antimicrobial effector responses of vertebrate macrophages including respiratory burst and NO induction are similar across the diverse animal taxa. Antibodies against calbindin coupled with ones to VAChT and tubulin revealed the localization of myenteric and submucosal plexuses, which are made up of enteric neurons, glial cells, and nerves near macrophages. Current studies allow for the elucidation of multiple roles of macrophages in disease models providing an insight into their in vivo function in fish.