bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comprehensive Simulation Study of Physicochemical and Geochemical Interactions on Immiscible CO2-LSWAG Injection in Carbonates
Authors: Bastos Ladislane dos Santos , Lins Igor Emanuel da Silva , Costa Gloria Meyberg Nunes , Vieira de Melo Silvio Alexandre Beisl
Published: January 2023

Low-salinity water-alternating-CO2 (CO2-LSWAG) injection has been widely studied and employed due to its capability to promote enhanced oil recovery (EOR). However, there is no consensus on the dominant mechanisms for oil recovery in carbonates due to the extreme complexity of the oil–brine–rock interactions. This work proposes a comparative investigation of the physicochemical and geochemical effects of continuous CO2 and CO2-LSWAG immiscible injections on oil recovery in a carbonate core. Simulations were carried out using oil PVT properties and relative permeability experimental data from the literature. A comparison of SO42− and Mg2+ as interpolant ions, oil, water and gas production, pressure, and rock and fluid properties along the core and in the effluent was made. The results show a high recovery factor for CO2 (62%) and CO2-LSWAG (85%), even in immiscible conditions. The mineral dissolution and porosity variations were more pronounced for CO2-LSWAG than CO2. The simulation results showed that Mg2+ as an interpolant improves oil recovery more than SO42− because Mg2+ concentration in the aqueous phase after LSW injection leads to relative permeability values, which are more favorable.
Study on Intermittent Microwave Convective Drying Characteristics and Flow Field of Porous Media Food
Authors: Man Yu , Tong Junjie , Wang Tingyu , Wang Shuxiang , Xu Hu
Published: January 2023

Numerical simulations were carried out for moist, porous media, intermittent microwave convective drying (IMCD) using a multiphase flow model in porous media subdomains coupled with a forced-convection heat-transfer model in an external hot air subdomain. The models were solved by using COMSOL Multiphysics was applied at the pulse ratio (PR) of 3. Based on drying characteristics of porous media and the distribution of the evaporation interface, IMCD was compared with convection drying (CD). Drying uniformity K, velocity difference, temperature difference, and humidity difference were introduced to evaluate the performance of three models with different inlets and outlet wall curvature. The numerical results show that as the moisture content of slices was reduced to 3 kg/kg, the drying rate in IMCD was 0.0166–0.02 m/s higher than that in CD, and the total drying time of the former was 81.35% shorter than that of the latter. In the late drying stage of IMCD, the core of the sample still had a high vapor concentration and temperature, which led to the evaporation interface remaining on the surface. The vapor evaporated from the slices can diffuse rapidly to the outside, which is why IMCD is superior to traditional convection drying. Through the comprehensive analysis of the models with different inlet and outlet wall curvatures, the drying uniformity K of the type III was the highest, reaching 89.28%. Optimizing flow-field distribution can improve uniform of airflow distribution.
Analyses of Interpolant Ion Effects on Smart Water Core Flooding in Carbonate
Authors: Bastos Ladislane dos Santos , Lins Igor Emanuel da Silva , Costa Gloria Meyberg Nunes , Vieira de Melo Silvio Alexandre Beisl
Published: January 2023

Smart water flooding (SWF) is a promising enhanced oil recovery (EOR) technique due to its economic advantages. For this process, wettability alteration is the most accepted controlling effect that leads to increased recovery factors (RFs). The main objective of this work is to investigate how the relative permeability curves’ interpolant affects the SWF mechanisms’ assessment. Wettability alteration is described by shifting these curves in simulations. Numerical simulations of core flooding tests are applied to carbonate at 114.4 °C. A comparison of oil recovery factor (RF), pH and effluent composition is performed for different injection approaches. Mg2+ and SO42− are the interpolant ions and the salinity levels range from 30 to 1 kppm. A simulation of 24 scenarios, 12 for each type of interpolant, is presented. Results show that RF changes significantly, due to salinity and composition, for each interpolant. This has a relevant influence on the interpolant. The greater the dilution, the smaller the effect of the interpolant and brine composition on the recovery estimates. When considering SO42− as an interpolant, the trend is that divalent rich brine (DV) has a higher recovery factor. In contrast, when Mg2+ is the interpolant, DV tends to have a lower recovery. The analysis of ionic exchange and pH variation corroborate the wettability alteration behavior. A pH increase was observed in all scenarios, regardless of the salinity, ion composition or interpolant variation. Also, monitoring the CH3COO-X reduction and SO4-X2 increase equivalent fractions indicated the ion exchange mechanism as being well represented in all simulations. In addition, the results emphasize that even at very low concentrations, SO42− plays a fundamental role in initiating the ion exchange process that culminates in the wettability alteration as a consequence of smart water injection.
A Novel Distributed Consensus-Based Approach to Solve the Economic Dispatch Problem Incorporating the Valve-Point Effect and Solar Energy Sources
Authors: Moin Muhammad , Ahmed Waqas , Rehan Muhammad , Iqbal Muhammad , Ullah Nasim , Zeb Kamran , Uddin Waqar
Published: January 2023

This research focused on the design of a distributed approach using consensus theory to find an optimal solution of the economic dispatch problem (EDP) by considering the quadratic cost function along with the valve-point effect of generators and renewable energy systems (RESs). A distributed consensus approach is presented for the optimal economic dispatch under a complex valve-point effect by accounting for solar energy in addition to conventional power plants. By employing the beta distribution function and communication topology between generators, a new optimality condition for the dispatch problem was formulated. A novel distributed updation law for generation by considering the communication between generators was provided to deal with the valve-point effect. The convergence of the proposed updation law was proved analytically using Lyapunov stability and graph theory. An algorithm for ensuring a distributed economic dispatch via conventional power plants, integrated with solar energy, was addressed. To the best of the authors’ knowledge, a distributed nonlinear EDP approach for dealing with the valve-point loading issue via nonlinear incremental costs has been addressed for the first time. The designed approach was simulated for benchmark systems with and without a generation capacity constraint, and the results were compared with the existing centralized and distributed strategies.
Nurturing Green Consumer Values and Renewable Energy Reliance through Societal Education in Uttar Pradesh for Inclusive Capacity Building
Authors: Singh Uma Shankar , Nermend Malgorzata , Singh Swapnil
Published: January 2023

The main focus of this research has been on examining the renewable energy sources (RESs) consumption with respect to green consumer values (GCVs). These GCVs have primarily been examined with regard to different products and services. The most significant strategy for strengthening everyone is social education. While GCVs are assumed to be nurtured through education, specific understanding about the long-term benefits of renewable energy for a sustainable life is measured with the belief that the greater the training and development the better shaped the society can be, which boosts morale and increases their energy reliance with RES, assessed by the respondents of Uttar Pradesh (UP), as the outcome of the research. The implications for the stakeholders are the long-term advantages of renewable energy for a sustainable existence, since a society may be better formed and its reliance on RESs for energy rises the more training and development it receives. The advantages are visible, though we may not be able to completely transition soon, but it is crucial that we think for the future. The quantitative research method applies statistical analyses, such as ANOVA, spectral analysis, and multilayer perceptron analysis, justifying the requirement of education. The results justify that the solution to this problem—that green consumer values are being learned—can be nurtured by societal education. Learning about green consumer values can make society understand the renewable energy benefits, which can better shape society and lead to capacity building.
Combined Effect of Coal Fly Ash (CFA) and Nanosilica (nS) on the Strength Parameters and Microstructural Properties of Eco-Friendly Concrete
Authors: Golewski Grzegorz Ludwik
Published: January 2023

Disposal of the coal fly ash (CFA) generated from thermal power plants in huge quantities is one of the major concerns for the industry, as well as the natural environment. On the other hand, CFA can be used within a certain percentage range in the cement concrete mix as a replacement for cement. Nanomaterials can also be used to improve the properties of concrete. Therefore, this study investigated the effects of nanosilica (nS) on the mechanical parameters and microstructure of CFA cement concretes. This study utilized an nS content of 5%, along with three CFA contents, i.e., of 0, 15, and 25% by volume. Mechanical property tests and a thorough overview of changes in the structure of modified concrete were carried out to study the effect of the CFA content on the analyzed parameters of concrete containing nS. This study had the goal of elucidating the reinforcing mechanisms of CFA concrete by nS and providing design guidance for the practical engineering applications of CFA-nS composites. Based on the conducted studies, it was found that the combined usage of nS and CFA has synergistic and positive effects on improving mechanical parameters and microstructure in such concretes. The combined strengthening of a cement matrix by nS and CFA can fill the pores and microcracks in concrete composites and effectively improve the mechanical properties and microstructure of such materials. In this study, the optimal improvement was achieved when the concentration of additions was 5% nS and 15% CFA. The 28-day compressive strength and splitting tensile strength were increased by 37.68 and 36.21%, respectively, in comparison to control concrete. Tailored blended cements composed of nS and CFA content (up to 30% replacement level) can significantly improve the parameters of concrete composites, as well as reduce the carbon footprint of cement-based materials—constituting a step toward the production of eco-friendly concretes.
Control of a Three-Phase Grid-Connected Voltage-Sourced Converter Using Long Short-Term Memory Networks
Authors: Ghidewon-Abay Sengal , Mehrizi-Sani Ali
Published: January 2023

With the rise of inverter-based resources (IBRs) within the power system, the control of grid-connected converters (GCCs) has become pertinent due to the fact they interface IBRs to the grid. The conventional method of control for a GCC such as the voltage-sourced converter (VSC) is through a decoupled control loop in the synchronous reference frame. However, this model-based control method is sensitive to parameter changes causing deterioration in controller performance. Data-driven approaches such as machine learning can be utilized to design controllers that are capable of operating GCCs in various system conditions. This work explores a deep learning-based control method for a three-phase grid-connected VSC, specifically utilizing a long short-term memory (LSTM) network for robust control. Simulations of a conventional controlled VSC are conducted using Simulink to collect data for training the LSTM-based controller. The LSTM model is built and trained using the Keras and TensorFlow libraries in Python and tested in Simulink. The performance of the LSTM-based controller is evaluated under different case studies and compared to the conventional method of control. Simulation results demonstrate the effectiveness of this approach by outperforming the conventional controller and maintaining stability under different system parameter changes.
Green Marketing and Customers’ Purchasing Behavior: A Systematic Literature Review for Future Research Agenda
Authors: Skackauskiene Ilona , Vilkaite-Vaitone Neringa
Published: January 2023

With the rising concern for environmental issues, there is an ever-increasing demand for sustainable actions to minimize the damage to ecosystems. Seeking to meet such a demand, energy companies worldwide embrace green marketing solutions. This article aims to provide a comprehensive and systematic overview of green marketing and its impact on customers’ purchasing behavior to develop a research agenda that helps to identify promising areas for future research. We conducted a systematic literature review to fill in the lack of conceptual clarity on the relationship between green marketing solutions and customers’ purchasing behavior. After compiling a candidate pool of 2604 papers and applying a set of inclusion and exclusion criteria, the final sample comprised 166 articles published between 1995 and 2022. The results demonstrate that scholars frequently chose the energy sector to research green marketing’s impact on purchasing behavior. The review indicates that the theory of planned behavior with its progenitor theory of reasoned action seems to be highly featured. The literature emphasizes green marketing at the tactical level as impacting customer behavior measures at the purchase and post-purchase stages. Our study helps marketers to identify the best practices in the area to influence customers’ behavior effectively.
Cooling Optimization Strategy for a 6s4p Lithium-Ion Battery Pack Based on Triple-Step Nonlinear Method
Authors: Zhang Hongya , Chen Hao , Fang Haisheng
Published: January 2023

In a battery cooling system, by adopting a cooling optimization control strategy, the battery temperature under different external environments and load currents can be adjusted to ensure performance and safety. In this study, two modes of the thermal management system are established for the 6s4p (six serial and four parallel batteries in a stage) battery pack. A single particle model, considering battery aging, is adopted for the battery. Furthermore, a cooling optimization control strategy for the battery is proposed based on the triple-step nonlinear method, and then the optimization effect is validated under two C-rate charge–discharge cycles, NEDC cycles, and US06 cycles. Moreover, an extended PID control strategy is constructed and compared with the triple-step nonlinear method. A comparison of pump power, thermal behavior, and aging performance indicate parallel cooling is more advantageous. This verifies the validity of the triple-step nonlinear method and shows its advantages over the extended PID method. The present study provides a method to investigate the thermal behavior and aging performance of a battery pack in a BTM system, and fills in the research gaps in the cooling optimization control strategy for battery packs.
Multi-Criterial Assessment of Electric Vehicle Integration into the Commercial Sector—A Case Study
Authors: Pietracho Robert , Wenge Christoph , Komarnicki Przemyslaw , Kasprzyk Leszek
Published: January 2023

Transforming the transport sector to zero emission is an integral part of changes to the energy sector worldwide. This effects not only the electrification of the private sector but also the commercial sector. The aim of this study is to develop methodologies, algorithms and associated requirements for the integration of electric vehicles into a logistics application with a possible reduction in operating costs. The most favorable solution for a company was evaluated using the analytic hierarchy process algorithm considering three main aspects: economic, environmental and technical. An analysis of the environmental impact of the vehicle fleet in terms of atmospheric emissions was also conducted, based on the data available for combustion and electric vehicles, considering the well-to-tank approach. The costs associated with operating an electric vehicle were identified and compared to the current costs associated with operating a standard diesel-based fleet. Incorporating the identified costs of electrifying the vehicle fleet, an algorithm was implemented to reduce the number of vehicles in the company and, thereby, significantly reducing the costs associated with fleet maintenance.
Production and Assessment of New Biofuels from Waste Cooking Oils as Sustainable Bioenergy Sources
Authors: Caliskan Hakan , Yildiz Ibrahim , Mori Kazutoshi
Published: January 2023

In this study, renewable and sustainable biofuel production from waste cooking oil and its blends with diesel fuel are investigated in terms of specific fuel properties. The fuel blends are named “Renewable Biofuel (RBF) 20” (20% biofuel–80% diesel), “Renewable Biofuel 50” (50% biofuel–50% diesel), and “Renewable Biofuel 100” (100% biofuel). The acid number, flash point, viscosity, cloud point, density, and pour point fuel properties of the new Renewable Biofuels are experimentally obtained and compared with diesel fuel. The viscosities of the biofuels are found to be 2.774 mm2/s for Renewable Biofuel 20, 3.091 mm2/s for Renewable Biofuel 50, and 4.540 mm2/s for Renewable Biofuel 100. Renewable Biofuel 20 has the minimum density value among biofuels. The density of Renewable Biofuel 20, Renewable Biofuel 50, and Renewable Biofuel 100 are obtained as 835 kg/m3, 846 kg/m3, and 884 kg/m3, respectively. More energy can be released with the use of Renewable Biofuel 100 in terms of heating value. The new fuel specification of biofuels can contribute to the fuel industry and help the studies on fuels for diesel engines.
Optimal Parameter Identification of Perovskite Solar Cells Using Modified Bald Eagle Search Optimization Algorithm
Authors: Olabi Abdul , Rezk Hegazy , Abdelkareem Mohammad , Awotwe Tabbi , Maghrabie Hussein , Selim Fatahallah , Rahman Shek , Shah Sheikh , Zaky Alaa
Published: January 2023

In this paper, a modified bald eagle search optimization algorithm was applied for the first time to determine the parameters of the triple diode model (TDM) of perovskite solar cells (PSCs). Two experimental datasets are considered; the first is measured I–V points for a PSC at standard conditions. The second consists of the measured I–V points for a modified PSC. In contrast, the cost function to be minimized is the root mean square error (RMSE) between the experimental dataset and the calculated one. To prove the superiority of modified bald eagle search optimization (mBES), a comparison with the original bald eagle search optimization (BES), particle swarm optimizer (PSO), Hunger games search (HGS), and recent Coronavirus Disease Optimization Algorithm (COVIDOA) was implemented. Furthermore, statistical analysis of ANOVA and Tukey tests was performed. The results demonstrate the lead of the recommended mBES in identifying the parameters of the TDM for PSCs, where the RMSE achieved the least value among the used optimization algorithms in this study.
New Advances in Oil, Gas, and Geothermal Reservoirs
Authors: Zhu Daoyi
Published: January 2023

The most significant geo-energy sources in the world today continue to be oil, gas, and geothermal reservoirs. To increase oil and gas reserves and production, new theories are constantly being developed in the laboratory and new technologies are being applied in the oilfield. This Special Issue compiles recent research focusing on cutting-edge ideas and technology in oil, gas, and geothermal reservoirs, covering the fields of well drilling, cementing, hydraulic fracturing, improved oil recovery, conformance control, and geothermal energy development.
One-Step Construction of Co2P Nanoparticles Encapsulated into N-Doped Porous Carbon Sheets for Efficient Oxygen Evolution Reaction
Authors: Wang Ke , Zhang Ruimin , Guo Yun , Liu Yunjie , Tian Yu , Wang Xiaojun , Wang Peng , Liu Zhiming
Published: January 2023

It is critical and challenging to develop high performance transition metal phosphides (TMPs) electrocatalysts for oxygen evolution reaction (OER) to address fossil energy shortages. Herein, we report the synthesis of Co2P embedded in N-doped porous carbon (Co2P@N-C) via a facile one-step strategy. The obtained catalyst exhibits a lower overpotential of 352 mV for OER at a current density of 10 mA cm−2 and a small Tafel slope of 84.6 mV dec−1, with long-time reliable stability. The excellent electrocatalytic performance of Co2P@N-C can be mainly owed to the synergistic effect between the Co2P and highly conductive N-C substrate, which not only affords rich exposed active sites but also promotes faster charge transfer, thus significantly promoting OER process. This work presents a promising and industrially applicable synthetic strategy for the rational design of high performance nonnoble metal electrocatalysts with enhanced OER performance.
The Influence of the Intramolecular 2D Interactions on the Physicochemical Properties of Hexasubstituted Benzene Derivatives
Authors: Szlapa-Kula Agata , Kula Sławomir , Filipek Patrycja , Krompiec Stanisław , Filapek Michał
Published: January 2023

This paper contains a comprehensive study regarding the synthesis and physicochemical properties of new hexasubstitued benzene derivatives. In this work, three compounds of this type (including two electropolymerisable monomers) were synthesized in a one-step reaction with good yields ranging from 34% to 56%. A thermal investigation shows that this type of compound is stable up to 360 °C (10% weight loss temperature). The influence of the substituents in the first and second position of the central benzene on the stability, luminescence, and (spectro)electrochemical behavior was thoroughly studied with the aid of theoretical calculations. In each case, strong blue shifting of the π-π* transition (according to 1,4-disubstitued analogs) was observed, proving this moieties’ orthogonal orientation. In the case of derivatives with a Bt-core-Bt formula (where Bt = 2,2′-bithiophene-5-yl), an electrochemical oxidation process transformed them into conducting polymers. The polymer presents extraordinary stability during multiple p-doping; thus, spectroelectrochemical measurements of polymeric films were also performed.
Review on the Microgrid Concept, Structures, Components, Communication Systems, and Control Methods
Authors: Abbasi Maysam , Abbasi Ehsan , Li Li , Aguilera Ricardo P. , Lu Dylan , Wang Fei
Published: January 2023

This paper provides a comprehensive overview of the microgrid (MG) concept, including its definitions, challenges, advantages, components, structures, communication systems, and control methods, focusing on low-bandwidth (LB), wireless (WL), and wired control approaches. Generally, an MG is a small-scale power grid comprising local/common loads, energy storage devices, and distributed energy resources (DERs), operating in both islanded and grid-tied modes. MGs are instrumental to current and future electricity network development, such as a smart grid, as they can offer numerous benefits, such as enhanced network stability and reliability, increased efficiency, an increased integration of clean and renewable energies into the system, enhanced power quality, and so forth, to the increasingly growing and complicated power systems. By considering several objectives in both islanded and grid-tied modes, the development of efficient control systems for different kinds of MGs has been investigated in recent years. Among these control methods, LB communication (LBcom)-based control methods have attracted much attention due to their low expenses, recent developments, and high stability. This paper aims to shed some light on different aspects, a literature review, and research gaps of MGs, especially in the field of their control layers, concentrating on LBcom-based control methods.
Public Policies for Renewable Energy: A Review of the Perspectives for a Circular Economy
Authors: Nunes Anna , Coelho Junior Luiz , Abrahão Raphael , Santos Júnior Edvaldo , Simioni Flávio , Rotella Junior Paulo , Rocha Luiz
Published: January 2023

The development and implementation of public policies towards renewable energies are crucial in order to address the contemporary challenges faced by humanity. The 3Rs (reduce, reuse, and recycle), as a circular economic practice, are often cited as one of the best solutions for sustainable development. Therefore, this study analyzed public policies for renewable energy from the perspective of the circular economy. Accordingly, a systematic review of the literature was carried out with respect to the beneficiaries and convergences of circularities, with a focus on public policies for renewable energies. The sample had public policies classified into three types (distributive, redistributive, and regulatory policies). The results showed that the first studies began in 1999, with a significant increase in publications during the 2010s, in which Germany was the country with the greatest contribution. The analyses associated with space showed the countries committed to the use of renewable energies and the 3Rs of the circular economy to reduce greenhouse gas emissions. The economic analyses revealed that the circular economy for the generation of renewable energy has a positive economic return in terms of social well-being and the mitigation of environmental degradation. There is a barrier to the circular economy’s development posed by the cost of its implementation in the private sector and the resistance to raising awareness in society, requiring strong public sector engagement in decision making and the constant evaluation of public policies. It is concluded that the circular economy facilitates more efficient, productive structures and public policies, promoting alternatives for energy security and sustainability for the world energy matrix.
Equivalent Consumption Minimization Strategy Based on Belt Drive System Characteristic Maps for P0 Hybrid Electric Vehicles
Authors: Hegde Shailesh , Bonfitto Angelo , Galluzzi Renato , Molina Luis M. Castellanos , Amati Nicola , Tonoli Andrea
Published: January 2023

A P0 system is used in hybrid automobiles to improve engine economy and performance. An essential element of the P0 system for effectively transmitting power to the drive train is the belt drive system (BDS). The features of electric machine (EM) and internal combustion engines (ICE) are taken into account by standard energy management systems, such as the equivalent consumption minimization strategy (ECMS). In order to maximize the effectiveness of the P0 system, this work provides a novel formulation of the ECMS, which considers the power loss map of the BDS in addition to the characteristic maps of EM and ICE. A test bench is built up to characterize the BDS, and it is verified using an open-loop Hardware in the Loop (HIL) in the WLTP driving cycle. To find the most appropriate equivalence factors for the ECMS, which would ordinarily be tuned through trial and error, a genetic algorithm (GA) is used. With regard to the standard ECMS, the proposed methodology intends to reduce fuel usage and CO2 emissions. Two belts in BDS were tested in the WLTP to achieve CO2 savings of 1.1 and 0.9 [g/km], indicating the enhancement of system performance by using the BDS power loss maps in ECMS.
Time-Series Well Performance Prediction Based on Convolutional and Long Short-Term Memory Neural Network Model
Authors: Wang Junqiang , Qiang Xiaolong , Ren Zhengcheng , Wang Hongbo , Wang Yongbo , Wang Shuoliang
Published: January 2023

In the past, reservoir engineers used numerical simulation or reservoir engineering methods to predict oil production, and the accuracy of prediction depended more on the engineers’ own experience. With the development of data science, a new trend has arisen to use deep learning to predict oil production from the perspective of data. In this study, a hybrid forecasting model (CNN-LSTM) based on a convolutional neural network (CNN) and a Long Short-Term Memory (LSTM) neural network is proposed and used to predict the production of fractured horizontal wells in volcanic reservoirs. The model solves the limitation of traditional methods that rely on personal experience. First, the production constraints and production data are used to form a feature space, and the abstract semantics of the feature time series are extracted through convolutional neural network, then the LSTM neural network is used to predict the time series. The certain hyperparameters of the whole model are optimized by Particle Swarm Optimization algorithm (PSO). In order to estimate the model, some production dynamics from the Xinjiang oilfield of China are used for comparative analysis. The experimental results show that the CNN-LSTM model is superior to traditional neural networks and conventional decline curves.
The Environmental Impact of Changes in the Structure of Electricity Sources in Europe
Authors: Bukowski Marcin , Majewski Janusz , Sobolewska Agnieszka
Published: January 2023

The limited use of non-renewable energy sources facilitates a reduction in the negative environmental impact of electricity production. The policies of European countries aim to change the structure of electricity sources, focusing particularly on non-renewable sources. The aim of this study was to assess changes in the structure of electricity generation depending on the energy sources used in 34 European countries in the years 1990–2020 in terms of their environmental impact. This study was conducted using cluster analysis: a method applied in multivariate comparative analyses. Such an approach provided a new, broader outlook on changes in the structure of electric energy production in Europe. A total of nine homogeneous groups of countries were distinguished in terms of energy transformation. The ecological scarcity method 2013 was applied to assess the environmental impact of electricity production in the analyzed countries. In the investigated period, the negative environmental impact of electricity production in European countries decreased. The median of the volume of this impact, determined based on the structure of production in 1990, for the analyzed countries was 464 UBP/1 kWh. In the following years, the value of the median dropped to 413 UBP/1 kWh (2000), 322 UBP/1 kWh (2010), and 204 UBP/1 kWh (2020), respectively. The diversification of the countries in this respect also decreased, which resulted in a reduction in the number of clusters from eight in 1990 to two in 2020.
Using ARIMA to Predict the Growth in the Subscriber Data Usage
Authors: Nkongolo Mike
Published: January 2023

Telecommunication companies collect a deluge of subscriber data without retrieving substantial information. Exploratory analysis of this type of data will facilitate the prediction of varied information that can be geographical, demographic, financial, or any other. Prediction can therefore be an asset in the decision-making process of telecommunications companies, but only if the information retrieved follows a plan with strategic actions. The exploratory analysis of subscriber data was implemented in this research to predict subscriber usage trends based on historical time-stamped data. The predictive outcome was unknown but approximated using the data at hand. We have used 730 data points selected from the Insights Data Storage (IDS). These data points were collected from the hourly statistic traffic table and subjected to exploratory data analysis to predict the growth in subscriber data usage. The Auto-Regressive Integrated Moving Average (ARIMA) model was used to forecast. In addition, we used the normal Q-Q, correlogram, and standardized residual metrics to evaluate the model. This model showed a p-value of 0.007. This result supports our hypothesis predicting an increase in subscriber data growth. The ARIMA model predicted a growth of 3 Mbps with a maximum data usage growth of 14 Gbps. In the experimentation, ARIMA was compared to the Convolutional Neural Network (CNN) and achieved the best results with the UGRansome data. The ARIMA model performed better with execution speed by a factor of 43 for more than 80,000 rows. On average, it takes 0.0016 s for the ARIMA model to execute one row, and 0.069 s for the CNN to execute the same row, thus making the ARIMA 43× (0.0690.0016) faster than the CNN model. These results provide a road map for predicting subscriber data usage so that telecommunication companies can be more productive in improving their Quality of Experience (QoE). This study provides a better understanding of the seasonality and stationarity involved in subscriber data usage’s growth, exposing new network concerns and facilitating the development of novel predictive models.
The Effects of Tree Canopy Structure and Tree Coverage Ratios on Urban Air Temperature Based on ENVI-Met
Authors: Wang Haihua , Cai Yue , Deng Weifen , Li Chong , Dong Ya , Zhou Lv , Sun Jingyi , Li Chen , Song Bingzheng , Zhang Fangfang , Zhou Guomo
Published: January 2023

Vegetation configuration in residential districts improves human comfort by effectively moderating the thermal environment. Herein, the reliability of ENVI-met is verified by comparing the field measured with simulated data, including air temperature and relative humidity. The cooling effect of trees gradually increased with increasing tree coverage. Under the same coverage, trees with a tree crown diameter (TCD) of 3 m have the strongest cooling capacity, followed by trees with a TCD of 7 m, and trees with a TCD of 5 m have the weakest cooling capacity. The cooling capacity of a TCD of 3 m is considerably higher than that a TCD of 5 m and a TCD of 7 m. When the tree coverage ratio is 50%, the difference among the three TCDs is the largest. When the tree coverage is 50% or 70%, the cooling effect of TCD at 7 m is considerably higher than that at 5 m. For different canopy sizes and shapes under the same degree of tree coverage, only when the tree coverage is more than 50% and TCD is 3 m, the cooling capacity of a cylindrical shape is 0.2 to 0.3 °C higher than that of conical and ellipsoidal shapes. However, the difference between conical and ellipsoidal shapes when TCD is 5 or 7 m is not significant (∆Ta < 0.1 °C). Our results suggest that small canopy trees have a better cooling effect than large canopy trees for the same level of coverage.
A Systematic Review of Logging Impacts in the Amazon Biome
Authors: DeArmond Daniel , Emmert Fabiano , Pinto Alberto C. M. , Lima Adriano J. N. , Higuchi Niro
Published: January 2023

Every year, logging in the world’s largest tropical forest, located within the Amazon biome, continues unabated. Although it is a preferred alternative to deforestation, the residual stand and site are impacted by logging. The objective of this review was to determine and assess the current state of research throughout Amazonia on the subject of logging impacts. To achieve this goal, a systematic approach was utilized to gather, assess and categorize research articles conducted in the Amazon biome over the last decade. Eligibility for inclusion of articles required demonstration of a direct impact from logging operations. A total of 121 articles were determined to meet the eligibility requirements and were included in this review. Articles were subdivided into three environmental categories: forest (n = 85), wildlife (n = 24) and streams (n = 12). The results of this review demonstrated that impacts from logging activities to the forest site were a direct result of the logging cycle (e.g., how often logging occurs) or logging intensity (e.g., how many trees are felled). The impacts to wildlife varied dependent on species, whereas impacts to streams were affected more by the logging system. Overall, research suggested that to attain sustainability and diminish the impacts from logging, a lower logging intensity of 10–15 m3 ha−1 and a longer logging cycle of 40–60 years would be essential for the long-term viability of forest management in Amazonia.
Robust Control Based on Modeling Error Compensation of Microalgae Anaerobic Digestion
Authors: Rodríguez-Jara Mariana , Velasco-Pérez Alejandra , Vian Jose , Vigueras-Carmona Sergio E. , Puebla Héctor
Published: January 2023

Microalgae are used to produce renewable biofuels (biodiesel, bioethanol, biogas, and biohydrogen) and high-value-added products, as well as in bioremediation and CO2 sequestration tasks. In the case of anaerobic digestion of microalgae, biogas can be produced from mainly proteins and carbohydrates. Anaerobic digestion is a complex process that involves several stages and is susceptible to operational instability due to various factors. Robust controllers with simple structure and design are necessary for practical implementation purposes and to achieve a proper process operation despite process variabilities, uncertainties, and complex interactions. This paper presents the application of a control design based on the modeling error compensation technique for the anaerobic digestion of microalgae. The control design departs from a low-order input–output model by enhancement with uncertainty estimation. The results show that achieving desired organic pollution levels and methanogenic biomass concentrations as well as minimizing the effect of external perturbations on a benchmark case study of the anaerobic digestion of microalgae is possible with the proposed control design.
Optimization of Solvent Extraction of Lipids from Yarrowia lipolytica towards Industrial Applications
Authors: Tsirigka Asimina , Ntoula Maria , Kontogiannopoulos Konstantinos N. , Karabelas Anastasios J. , Patsios Sotiris I.
Published: January 2023

Extraction of intracellular lipids of the oleaginous yeast Yarrowia lipolytica has been systematically studied aiming towards a sustainable extraction process for lipid recovery. Selection of suitable industrial (bulk) solvents and extraction parameters that lead to maximization of lipid recovery are significant issues to be addressed, with industrial applications motivating this study. Biomass from fermentation of Yarrowia lipolytica (MUCL 28849) was used in small laboratory tests to assess different solvent mixtures (i.e., methanol/hexane, isopropanol/hexane, and methanol/ethyl acetate), implementing a systematic design of experiments methodology to identify near-optimum values of key extraction variables (i.e., polar/non-polar ratio, vortex time, dry biomass/solvent ratio) in regard to lipid yield (g lipids/g dry biomass). The methanol/hexane mixture exhibited the highest extraction yield in a wide range of experimental conditions, resulting in the following optimum parameters: polar/non-polar ratio 3/5, vortex time 0.75 h, and dry biomass/solvent ratio 40. Extraction tests on a fifty-times-larger scale (in a Soxhlet apparatus employing the optimal extraction parameters) confirmed the optimization outcome by obtaining up to 27.6% lipids per dry biomass (L/DB), compared to 12.1% L/DB with the reference lipid extraction method employing chloroform/methanol. Assessment of lipid composition showed that unsaturated fatty acid recovery was favored by the methanol/hexane solvent. Fatty acid composition was not affected by the increase in Soxhlet reflux cycles, whilst the lipid yield was notably favored.
Louvered Fin-and-Flat Tube Compact Heat Exchanger under Ultrasonic Excitation
Authors: Amiri Delouei Amin , Sajjadi Hasan , Atashafrooz Meysam , Hesari Mohammad , Ben Hamida Mohamed Bechir , Arabkoohsar Ahmad
Published: January 2023

Utilizing ultrasonic excitation as an active method for studying the rate of heat transfer has gained considerable attention recently. The present study investigated the effects of ultrasonic excitation on the heat transfer rate in a fin-and-flat tube heat exchanger experimentally. The performance of the heat exchanger was investigated with and without the presence of ultrasonic excitation. A comprehensive parameter study was attempted, so several parameters, including ambient temperature, flow rate, air passing velocity, Reynolds number, and Nusselt number, were studied in a relatively wide range. An adequate uncertainty test, as well as a validation assessment, is provided to certify the credibility of the obtained results and the hired facility. The results revealed that reducing the flow rate, ambient temperature, and air passing velocity on the heat exchanger increased the ultrasonic excitation’s effects. The highest heat transfer enhancement in the present experiment was 70.11%, measured at the lowest air passing velocity and ambient temperature with a Reynolds number 2166. The data presented in this paper will be useful for the optimal design of ultrasonic vibrating fin-and-tube heat exchangers.
Relative Condition Parameters for Fishes of Montana, USA
Authors: Eckelbecker Robert W. , Heili Nathaniel M. , Guy Christopher S. , Schmetterling David A.
Published: January 2023

Body condition indices are commonly used in the management of fish populations and are a surrogate to physiological attributes such as tissue-energy reserves. Relative condition factor (Kn) describes the condition of species relative to populations in a geographic area. We developed models to allow for the calculation of Kn in Montana, USA by using the weight–length data collected by Montana Fish, Wildlife & Parks. We generated log10weight–log10length relationships to obtain Montana specific parameter estimates for relative condition equations (W′) for 51 species and three subspecies. We developed separate models by water type (e.g., lotic and lentic) and sex for five species due to varying growth based on sexual dimorphism and varying ecosystem types. Relative condition offers the advantage of describing body condition relative to species in Montana, provides a condition index for species that do not have standard-weight models developed for relative weight (Wr), and affords more information for the global database on weight–length relationships of fishes.
Evaluating the Use of a Similarity Index (SI) Combined with near Infrared (NIR) Spectroscopy as Method in Meat Species Authenticity
Authors: Cozzolino Daniel , Bureš Daniel , Hoffman Louwrens C.
Published: January 2023

A hand-held near infrared (NIR) spectrophotometer combined with a similarity index (SI) method was evaluated to identify meat samples sourced from exotic and traditional meat species. Fresh meat cuts of lamb (Ovis aries), emu (Dromaius novaehollandiae), camel (Camelus dromedarius), and beef (Bos taurus) sourced from a commercial abattoir were used and analyzed using a hand-held NIR spectrophotometer. The NIR spectra of the commercial and exotic meat samples were analyzed using principal component analysis (PCA), linear discriminant analysis (LDA), and a similarity index (SI). The overall accuracy of the LDA models was 87.8%. Generally, the results of this study indicated that SI combined with NIR spectroscopy can distinguish meat samples sourced from different animal species. In future, we can expect that methods such as SI will improve the implementation of NIR spectroscopy in the meat and food industries as this method can be rapid, handy, affordable, and easy to understand for users and customers.
Isolation of a Novel Anti-Diabetic α-Glucosidase Oligo-Peptide Inhibitor from Fermented Rice Bran
Authors: Hu Jingfei , Lai Xiaohua , Wu Xudong , Wang Huanyu , Weng Nanhai , Lu Jing , Lyu Mingsheng , Wang Shujun
Published: January 2023

At present, the incidence rate of diabetes is increasing gradually, and inhibiting α-glucosidase is one of the effective methods used to control blood sugar. This study identified new peptides from rice bran fermentation broth and evaluated their inhibitory activity and mechanism against α-glucosidase. Rice bran was fermented with Bacillus subtilis MK15 and the polypeptides of <3 kDa were isolated by ultrafiltration and chromatographic column, and were then subjected to LC-MS/MS mass spectrometry analysis. The results revealed that the oligopeptide GLLGY showed the greatest inhibitory activity in vitro. Docking studies with GLLGY on human α-glucosidase (PDB ID 5NN8) suggested a binding energy of −7.1 kcal/mol. GLLGY acts as a non-competitive inhibitor and forms five hydrogen bonds with Asp282, Ser523, Asp616, and His674 of α-glucosidase. Moreover, it retained its inhibitory activity even in a simulated digestion environment in vitro. The oligopeptide GLLGY could be developed into a potential anti-diabetic agent.
Non-Destructive Measurement of Egg’s Haugh Unit by Vis-NIR with iPLS-Lasso Selection
Authors: Yuan Leiming , Fu Xueping , Yang Xiaofeng , Chen Xiaojing , Huang Guangzao , Chen Xi , Shi Wen , Li Limin
Published: January 2023

Egg freshness is of great importance to daily nutrition and food consumption. In this work, visible near-infrared (vis-NIR) spectroscopy combined with the sparsity of interval partial least square regression (iPLS) were carried out to measure the egg’s freshness by semi-transmittance spectral acquisition. A fiber spectrometer with a spectral range of 550-985 nm was embedded in the developed spectral scanner, which was designed with rich light irradiation mode from another two reflective surfaces. The semi-transmittance spectra were collected from the waist of eggs and monitored every two days. Haugh unit (HU) is a key indicator of egg’s freshness, and ranged 56–91 in 14 days after delivery. The profile of spectra was analyzed the relation to the changes of egg’s freshness. A series of iPLS models were constructed on the basis of spectral intervals at different divisions of the spectral region to predict the egg’s HU, and then the least absolute shrinkage and selection operator (Lasso) was used to sparse the number of iPLS member models acting as a role of model selection and fusion regression. By optimization of the number of spectral intervals in the range of 1 to 40, the 26th fusion model obtained the best performance with the minimum root mean of squared error of prediction (RMSEP) of 5.161, and performed the best among the general PLS model and other intervals-combined PLS models. This study provided a new, rapid, and reliable method for the non-destructive and in-site determination of egg’s freshness.