bluuebunny/crossref_metadata_2025 huggingface dataset:
Replica Field Theory for a Generalized Franz–Parisi Potential of Inhomogeneous Glassy Systems: New Closure and the Associated Self-Consistent Equation
Authors: Frusawa Hiroshi
Published: March 2024

On approaching the dynamical transition temperature, supercooled liquids show heterogeneity over space and time. Static replica theory investigates the dynamical crossover in terms of the free energy landscape (FEL). Two kinds of static approaches have provided a self-consistent equation for determining this crossover, similar to the mode coupling theory for glassy dynamics. One uses the Morita–Hiroike formalism of the liquid state theory, whereas the other relies on the density functional theory (DFT). Each of the two approaches has advantages in terms of perturbative field theory. Here, we develop a replica field theory that has the benefits from both formulations. We introduce the generalized Franz–Parisi potential to formulate a correlation functional. Considering fluctuations around an inhomogeneous density determined by the Ramakrishnan–Yussouf DFT, we find a new closure as the stability condition of the correlation functional. The closure leads to the self-consistent equation involving the triplet direct correlation function. The present field theory further helps us study the FEL beyond the mean-field approximation.
Bank-Specific and Macroeconomic Determinants of Profitability of Islamic Shariah-Based Banks: Evidence from New Economic Horizon Using Panel Data
Authors: Gazi Md. Abu Issa , Karim Rejaul , Senathirajah Abdul Rahman bin S , Ullah A. K. M Mahfuj , Afrin Kaniz Habiba , Nahiduzzaman Md.
Published: March 2024

The purpose of this study is to analyze significant variables that permit us to ascertain the profitability of Bangladeshi Shariah-based banks. In doing so, two profitability measurements, namely, return on asset (ROA) and return on equity (ROE), have been used as dependent variables, while capital adequacy, asset management quality, operational efficiency, credit risk, liquidity, and the size of the bank have been considered as bank-specific independent variables. In addition, the rate of interest, inflation, and GDP growth rate have also been taken as macroeconomic independent variables. This study examined panel data of eight Shariah-based Islamic banks over a thirteen-year period spanning from 2010 to 2022, applying different kinds of linear regression models, including pooled ordinary least squares (OLS), fixed effects, and random effects. Subsequently, the generalized method of moments (GMM) approach is also applied to assess the robustness of the findings. The results revealed that the profitability of Bangladeshi Shariah-based Islamic banks is positively associated with asset management quality, liquidity, and credit risk. In contrast, capital adequacy, operational efficiency, and bank size are negatively correlated with the bank’s profitability. Concerning the macroeconomic factors, the findings indicated a notable positive correlation between the profitability of Shariah-based banks in Bangladesh and both the inflation rate and the interest rate spread. However, this study has also found that the profitability of the sample banks of Bangladesh is not significantly influenced by GDP growth. By providing fresh empirical data, the current research aimed to close a significant vacuum in the body of knowledge on banks and provide important insights for policymakers, managers, and other stakeholders by focusing on particular bank-specific and macroeconomic aspects that influence the profitability of Shariah-based Islamic banks in Bangladesh.
Celebrating and Leveraging Classroom Geographic and Cultural Diversity to Enhance Student Learning
Authors: Forbes Marissa H. , Lord Susan M. , Díaz-Montiel Paulina
Published: March 2024

In the fall of 2022, we offered a pedagogically redesigned sociotechnical environmental engineering elective for junior and senior undergraduates that applied place-based and culturally sustaining pedagogies. The course featured a project designed to facilitate the celebration and leveraging of classroom geographic and cultural diversity to enhance student learning about water sustainability. We analyzed the students’ written project reflections using an inductive thematic analysis to explore whether and how the project and pedagogical model augmented student learning. The primary themes that emerged included: (1) deepened knowledge of home and culture; (2) global conceptualizations; (3) re-evaluation of perceptions and beliefs (in terms of water sustainability and personal relationships with water); and (4) future-facing viewpoints. We consider each of these ‘enhancements’ to the student learning because they extend beyond the course objectives and explore the sociotechnical aspect of engineering. The purpose of this paper is to share the course and project model, our findings from its implementation, and suggestions on how this pedagogical framework could be adapted and scaled to expand the learning of a range of topics at different learner levels.
Teaching Summary Writing as a Transferable Academic Skill in Ukrainian University Context
Authors: Kvasova Olga
Published: March 2024

Teaching and assessing summary writing remains in the focus of research into academic literacy, the issue revisited by every new generation of researchers in the light of the emerging affordances and plurilingual reality. In higher Ukrainian education, where teaching academic skills has gained momentum only in the past 15–20 years, summary writing pertains mostly to teaching Ukrainian to international students, teaching English for professional communication and training post-graduates. A 15-year practice of teaching academic English to students of linguistics has provided the author with extensive empirical data which, upon analysis conducted within action research, have enabled maximized effect on teaching summary writing. Along with the teaching methodology, the assessment technique was also optimized, based on rating scales with the criteria accepted by the students and detailed feedback provided to them via the Google Classroom platform. The comparison of pre-and post-tests of writing summaries of Ukrainian research articles verifies the hypothesis about the transferability of summarization skills built in English to academic L1. The author formulates the limitations of the action research project, implications and prospects of further research.
The Effects of Nature Exposure Therapies on Stress, Depression, and Anxiety Levels: A Systematic Review
Authors: Paredes-Céspedes Diana Marcela , Vélez Norida , Parada-López Alejandra , Toloza-Pérez Yesith Guillermo , Téllez Eliana M. , Portilla Claudia , González Carolina , Blandón Leany , Santacruz Juan Carlos , Malagón-Rojas Jeadran
Published: March 2024

Background: Mental well-being plays a pivotal role within the broader spectrum of health and illness, encompassing factors such as stress, depression, and anxiety. Nature-based therapeutic interventions have emerged as a promising approach to addressing these mental health challenges. This study seeks to assess the impact of these interventions on stress, depression, and anxiety levels. Methods: We conducted an extensive search for randomized clinical trials that examined stress, anxiety, and depression levels. The selected studies underwent a rigorous risk-of-bias assessment following the guidelines outlined in the Cochrane Handbook for Systematic Reviews. Results: Our review encompassed findings from eight publications. Among them, two studies measuring cortisol levels revealed significant differences between the pre-test and post-test measurements within the intervention groups. In two studies that employed the Stress Response Inventory, a significant decrease in stress levels was observed within the intervention groups in contrast to the control groups. However, no significant differences were noted in studies that utilized the Restorative Outcome Scale. In the assessment of anxiety and depression levels, three studies employed the Positive and Negative Affect Schedule, while four studies utilized The Profile of Mood States scale; none of these studies demonstrated significant differences. Conclusions: The current body of evidence offers limited support for advocating nature-based therapeutic interventions as a primary approach to reducing stress, depression, and anxiety.
Assessing the Reliability of Machine Learning Models Applied to the Mental Health Domain Using Explainable AI
Authors: Pendyala Vishnu , Kim Hyungkyun
Published: March 2024

Machine learning is increasingly and ubiquitously being used in the medical domain. Evaluation metrics like accuracy, precision, and recall may indicate the performance of the models but not necessarily the reliability of their outcomes. This paper assesses the effectiveness of a number of machine learning algorithms applied to an important dataset in the medical domain, specifically, mental health, by employing explainability methodologies. Using multiple machine learning algorithms and model explainability techniques, this work provides insights into the models’ workings to help determine the reliability of the machine learning algorithm predictions. The results are not intuitive. It was found that the models were focusing significantly on less relevant features and, at times, unsound ranking of the features to make the predictions. This paper therefore argues that it is important for research in applied machine learning to provide insights into the explainability of models in addition to other performance metrics like accuracy. This is particularly important for applications in critical domains such as healthcare.
Investigation of a Hybridized Cascade Trigeneration Cycle Combined with a District Heating and Air Conditioning System Using Vapour Absorption Refrigeration Cooling: Energy and Exergy Assessments
Authors: Agberegha Larry , Aigba Peter , Nwigbo Solomon , Onoroh Francis , Samuel Olusegun , Bako Tanko , Der Oguzhan , Ercetin Ali , Sener Ramazan
Published: March 2024

The insufficiency of energy supply and availability remains a significant global energy challenge. This work proposes a novel approach to addressing global energy challenges by testing the supercritical property and conversion of low-temperature thermal heat into useful energy. It introduces a combined-cascade steam-to-steam trigeneration cycle integrated with vapour absorption refrigeration (VAR) and district heating systems. Energetic and exergetic techniques were applied to assess irreversibility and exergetic destruction. At a gas turbine power of 26.1 MW, energy and exergy efficiencies of 76.68% and 37.71% were achieved, respectively, while producing 17.98 MW of electricity from the steam-to-steam driven cascaded topping and bottoming plants. The cascaded plant attained an energetic efficiency of 38.45% and an exergy efficiency of 56.19%. The overall cycle efficiencies were 85.05% (energy) and 77.99% (exergy). More than 50% of the plant’s lost energy came from the combustion chamber of the gas turbine. The trigeneration system incorporated a binary NH3–H2O VAR system, emphasizing its significance in low-temperature energy systems. The VAR system achieved a cycle exergetic efficiency of 92.25% at a cooling capacity of 2.07 MW, utilizing recovered waste heat at 88 °C for district hot water. The recovered heat minimizes overall exergy destruction, enhancing thermal plant performance.
Uncertainty Analysis of the Storage Efficiency Factor for CO2 Saline Resource Estimation
Authors: Wang Zan , Qi Shengwen , Zheng Bowen
Published: March 2024

Carbon capture and sequestration (CCS) is a promising technology for reducing CO2 emissions to the atmosphere. It is critical to estimate the CO2 storage resource before deploying the CCS projects. The CO2 storage resource is limited by both the formation pore volume available to store CO2 and the maximum allowable pressure buildup for safe injection. In this study, we present a workflow for estimating the volume- and pressure-limited storage efficiency factor and quantifying the uncertainty in the estimates. Thirteen independent uncertain physical parameters characterizing the storage formation are considered in the Monte Carlo uncertainty analysis. The uncertain inputs contributing most to the overall uncertainty in the storage efficiency factor are identified. The estimation and uncertainty quantification workflow is demonstrated using a publicly available dataset developed for a prospective CO2 storage site. The statistical distributions of the storage efficiency factor for the primary storage formation and the secondary storage formation located in deeper depth are derived using the proposed workflow. The effective-to-total porosity contributes most to the overall uncertainty in the estimated storage efficiency factor at the study site, followed by the maximum allowable pressure buildup, the net-to-gross thickness ratio, the irreducible water saturation, and the permeability. While the significant uncertain input variables identified are tailored to the characteristics of the study site, the statistical methodology proposed can be generalized and applied to other storage sites. The influential uncertain inputs identified from the workflow can provide guidance on future data collection needs for uncertainty reduction, improving the confidence in the CO2 saline storage resource estimates.
Investigation of the Behavior of Hydrocarbons during Crude Oil Fouling by High-Resolution Electrospray Ionization Mass Spectrometry
Authors: Kondyli Aikaterini , Schrader Wolfgang
Published: March 2024

Crude oil is probably the most complex natural chemical mixture processed in various ways to make fuel and fine chemicals among a wide range of products in industrial processing. The conditions of those industrial processes often include high temperatures, which often cause undesired chemical reactions. One of those reaction sequences is crude oil fouling, which finally results in the formation of undesired solid deposits of carbon material, a calamity that costs millions of dollars worldwide each year and produces toxic waste. However, the compounds involved in fouling, let alone the underlying reaction mechanisms, are not understood to date. Here, in order to investigate chemical fouling, the process was simulated under laboratory conditions, focusing on hydrocarbons as the main constituents of crude oil. The results demonstrate large differences within the hydrocarbon class of compounds before and after thermal treatment, even for a very light crude oil fraction, which initially does not contain any bigger or heavier compounds. Here, the fouling reaction is simulated and studied on the molecular level using high-resolution mass spectrometry. After thermal treatment, new, higher molecular weight hydrocarbon compounds with high aromaticity were detected. Results indicate that a radical reaction leads to the formation of larger and more aromatic compounds. The findings were verified by the use of a model hydrocarbon compound to study the mechanism.
Prediction of ORF for Optimized CO2 Flooding in Fractured Tight Oil Reservoirs via Machine Learning
Authors: Yue Ming , Dai Quanqi , Liao Haiying , Liu Yunfeng , Fan Lin , Song Tianru
Published: March 2024

Tight reservoirs characterized by complex physical properties pose significant challenges for extraction. CO2 flooding, as an EOR technique, offers both economic and environmental advantages. Accurate prediction of recovery rate plays a crucial role in the development of tight oil and gas reservoirs. But the recovery rate is influenced by a complex array of factors. Traditional methods are time-consuming and costly and cannot predict the recovery rate quickly and accurately, necessitating advanced multi-factor analysis-based prediction models. This study uses machine learning models to rapidly predict the recovery of CO2 flooding for tight oil reservoir development, establishes a numerical model for CO2 flooding for low-permeability tight reservoir development based on actual blocks, studies the effects of reservoir parameters, horizontal well parameters, and injection-production parameters on CO2 flooding recovery rate, and constructs a prediction model based on machine learning for the recovery. Using simulated datasets, three models, random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM), were trained and tested for accuracy evaluation. Different levels of noise were added to the dataset and denoised, and the effects of data noise and denoising techniques on oil recovery factor prediction were studied. The results showed that the LightGBM model was superior to other models, with R2 values of 0.995, 0.961, 0.921, and 0.877 for predicting EOR for the original dataset, 5% noise dataset, 10% noise dataset, and 15% noise dataset, respectively. Finally, based on the optimized model, the key control factors for CO2 flooding for tight oil reservoirs to enhance oil recovery were analyzed. The novelty of this study is the development of a machine-learning-based method that can provide accurate and cost-effective ORF predictions for CO2 flooding for tight oil reservoir development, optimize the development process in a timely manner, significantly reduce the required costs, and make it a more feasible carbon utilization and EOR strategy.
Numerical Simulation Study on the Gas–Solid Flow Characteristics of a Large-Scale Dual Fluidized Bed Reactor: Verification and Extension
Authors: Lin Yubin , Wang Qinhui , Xie Guilin , Fang Mengxiang , Luo Zhongyang
Published: March 2024

Dual fluidized bed (DFB) reactor systems are widely used in gas–solid two-phase flow applications, whose gas–solid flow characteristics have a significant effect on the performance of many kinds of technologies. A numerical simulation model was established on the basis of a large-scale DFB reactor with a maximum height of 21.6 m, and numerical simulations focused on gas–solid flow characteristics were carried out. The effects of the superficial gas velocity of both beds and the static bed height and particle size on the distribution of the pressure and solid suspension density and the solid circulation rate were studied. The simulation results were in good agreement with the experimental data. With the strong support of the experimental data, the gas–solid flow characteristics of large-scale DFB reactors were innovatively evaluated in this numerical simulation study, which effectively makes up for the shortcomings of the current research. The results showed that the superficial gas velocity of both beds and the static bed height have different degrees of influence on the gas–solid flow characteristics. Specifically, for 282 μm particles, when the superficial gas velocity of both beds and the static bed height were 4.5 m/s, 2.5 m/s, and 0.65 m, respectively, under typical working conditions, the bottom pressure of the two furnaces was 3412.42 Pa and 2812.86 Pa, respectively, and the solid suspension density was 409.44 kg/m3 and 427.89 kg/m3, respectively. Based on the simulation results, the empirical formulas of the solid circulation rate were fitted according to different particle sizes. Under similar conditions, the solid circulation rates of particles with a particle size of 100 μm, 282 μm, 641 μm, and 1000 μm were 2.84–13.28, 0.73–4.91, 0.024–0.216, and 0.0026–0.0095 kg/(m2s), respectively. It can be found that the influence of the particle size on the solid circulation rate is the most significant among all parameters.
Unlocking the Thermal Efficiency of Irregular Open-Cell Metal Foams: A Computational Exploration of Flow Dynamics and Heat Transfer Phenomena
Authors: Xu Qian , Wu Yunbing , Chen Ye , Nie Zhengwei
Published: March 2024

An open-cell metal foam has excellent characteristics such as low density, high porosity, high specific surface area, high thermal conductivity, and low mass due to its unique internal three-dimensional network structure. It has gradually become a new material for enhanced heat transfer in industrial equipment, new compact heat exchangers, microelectronic device cooling, etc. This research established a comprehensive three-dimensional structural model of open-cell metal foams utilizing Laguerre–Voronoi tessellations and employed computational fluid dynamics to investigate its flow dynamics and coupled heat transfer performance. By exploring the impact of foam microstructure on flow resistance and heat transfer characteristics, the study provided insights into the overall convective heat transfer performance across a range of foam configurations with varying pore densities and porosities. The findings revealed a direct correlation between convective heat transfer coefficient (h) and pressure drop (ΔP) with increasing Reynolds number (Re), accompanied by notable changes in fluid turbulence kinetic energy (e) and temperature (T), ultimately influencing heat transfer efficiency. Furthermore, the analysis demonstrated that alterations in porosity (ε) and pore density significantly affected unit pressure drop (ΔP/L) and convective heat transfer coefficient (h). This study identified an optimal configuration, highlighting a metal foam with a pore density of 20 PPI and a porosity of 95% as exhibiting superior overall convective heat transfer performance.
Electricity Cost Savings in Energy-Intensive Companies: Optimization Framework and Case Study
Authors: Benalcazar Pablo , Malec Marcin , Kaszyński Przemysław , Kamiński Jacek , Saługa Piotr W.
Published: March 2024

In recent years, there has been an increasing urgency among energy-intensive companies to find innovative ways of mitigating the negative financial impacts of rising fuel and electricity prices. Consequently, companies are exploring new technological solutions to lower electricity costs, such as investing in their own power generation sources or storage systems. In this context, this article presents a data-driven optimization-based framework to manage and optimize the operation of a hybrid energy system within industries characterized by substantial power requirements. The framework encompasses several key aspects: electricity generation, self-consumption, storage, and electric grid interaction. The case of an energy-intensive company specializing in wood processing and office furniture production is evaluated. This study explored two system configurations of hybrid energy systems within an energy-intensive company. The result of the analyzed case shows that the system’s flexibility is enhanced by its ability to store energy, resulting in electricity cost savings of nearly 72% and total operating cost savings of 20%.
BLDC Motor Speed Control with Digital Adaptive PID-Fuzzy Controller and Reduced Harmonic Content
Authors: Kroičs Kaspars , Būmanis Arvīds
Published: March 2024

Low power brushless direct current (BLDC) motors are used in many consumer appliances. These motors have a relatively high winding resistance and therefore current control loop can be avoided in some cases, but fast and accurate speed regulation can be still needed. To minimize harmonics and generated sound noise, improved sinusoidal pulse width modulation (PWM) has been tested in the paper. As the most suitable commutation type, the sine wave with the third harmonic component has been selected. This type of communication reduced the torque ripple of the motor. This paper analyses the possibility to improve traditional proportional-integral-derivative (PID) speed regulator with Fuzzy logic block. A simulation model of BLDC motor, inverter, speed detection circuit and controller have been created. Simulation results showed that by applying the Fuzzy-based PID controller, the transient time can be reduced from 0.2 s to 0.05 s and overshoot can be avoided in comparison with traditional PID controller. Experimental results show a significant improvement in the motor dynamics—the overshoot and transient time were reduced twice. The difference with simulation results and experimental ones can be explained by delays introduced by the microcontroller.
Film Cooling Modeling in a Turbine Working under the Unsteady Exhaust Flow of Pulsed Detonation Combustion
Authors: Varatharajulu Purgunan Gokkul Raj , Asli Majid , Nacci Teodosio , Misul Daniela Anna , Salvadori Simone , Stathopoulos Panagiotis
Published: March 2024

Pressure gain combustors (PGCs) have demonstrated significant advantages over conventional combustors in gas turbine engines by increasing the thermal efficiency and reducing the pollution emission level. PGCs use shock waves to transfer energy which contributes to the increase in outlet total pressure. One of the major obstacles in the actual implementation of PGCs in the gas turbine cycle is the exploitation of the highly unsteady flow of the combustor outlet with the downstream turbine. Because of the higher outlet temperature from the PGCs, the turbine blade cooling becomes essential. Due to the highly fluctuating unsteady flow of PGCs, 3D CFD simulation of turbines becomes very expensive. In this work, an alternative approach of using a 1D unsteady Euler model for the turbine is proposed. One of the novel aspects of this paper is to implement the turbine blade cooling in the unsteady 1D Euler model. The main parameters required for the turbine blade cooling are the cooling air mass flow rate, temperature, and pressure. Due to the introduction of coolant flow, the blades are no longer adiabatic and the mass flow rate across the turbine is not constant. Comparing the 1D Euler results against zero-dimensional calculation and 3D CFD approach showed a very good match for both steady and unsteady simulations confirming the applicability of the 1D method.
An Experimental Study on the Effect of Nanofluids on the Thermal Conductivity and Rheological Properties of a Coolant for Liquids
Authors: Sun Le , Geng Jiafeng , Dong Kaijun , Sun Qin
Published: March 2024

Thermal conductivity and viscosity are important properties for nanofluids as they significantly affect the flow and heat transfer process. To date, the rheological properties of water-based nanofluids have been well studied, while the results are scarce for non-aqueous nanofluids. In this study, the thermal conductivity and rheological properties of two different kinds of oxide nanofluids (CuO and Al2O3) in a typical commercial data center focusing on liquid coolants were systematically investigated at different mass fractions and temperatures. The results showed that the addition of nanoparticles can significantly improve the heat conduction capacity of mineral oil coolants. There is an average increase in thermal conductivity of up to 20–25%. The shear rate–shear stress and shear rate–viscosity curves all showed that mineral oil coolant-based oxide nanofluids behaved as Newtonian fluids and that nanoparticles did not cause the increment in viscosity. The effect of temperature on rheological properties was also studied, and the result showed that high temperatures resulted in low viscosity and shear stress. Finally, the effect of particle type was investigated, and it was found that no matter what kind of nanoparticles were added, their effects on the rheological behaviors were the same.
An Effective Biomonitor of Potentially Toxic Elements in Marine Ecosystems: The Brown Alga Dictyota spiralis
Authors: Nitopi Maria Antonietta , Baldantoni Daniela , Baldi Vincenzo , Di Stefano Floriana , Bellino Alessandro
Published: March 2024

Coastal marine areas are threatened by different forms of pollution, among which potentially toxic elements (PTEs) represent a primary hazard. In this study, 16 Mediterranean macroalgae colonizing the upper eulittoral and infralittoral zones were studied for their PTE accumulation capabilities in order to identify possible biomonitors that could replace the use of Posidonia oceanica, a protected species. To achieve this objective, macronutrients (Ca, K, Mg, P, S), micronutrients (Cr, Cu, Fe, Mn, Na, Ni, Si, V, Zn) and non-essential elements (Cd, Pb) were analyzed in the thalli of different algal species, the leaves of P. oceanica and in sediments collected from six sampling sites along the Cilento coast (Campania, Italy), all characterized by different anthropogenic pressures. For sediments, a sequential extraction of PTEs to evaluate their bioavailability profile was also carried out together with the analysis of mineralogical composition, particle size distribution, pH and organic matter content. Macrophytes, belonging to different divisions (six Rhodophyta, four Chlorophyta, six Heterokontophyta, one Embryophyta), are characterized by different PTE concentrations, with a few ones being characterized by an even accumulation response toward the different PTEs. One of these, the brown alga Dictyota spiralis, is able to accumulate PTEs in concentrations similar to P. oceanica and provides more accurate concentration gradients, highlighting clear pollution scenarios that were overlooked using P. oceanica only. Therefore, D. spiralis is a useful PTE biomonitor of coastal marine ecosystems and a suitable replacement for P. oceanica, also featuring the possibility of being employed in active biomonitoring applications.
Economic Profitability of Carbon Sequestration of Fine-Aroma Cacao Agroforestry Systems in Amazonas, Peru
Authors: Goñas Malluri , Rojas-Briceño Nilton B. , Gómez Fernández Darwin , Iliquín Trigoso Daniel , Atalaya Marin Nilton , Bravo Verónica Cajas , Díaz-Valderrama Jorge R. , Maicelo-Quintana Jorge L. , Oliva-Cruz Manuel
Published: March 2024

Currently, the economic profitability of cocoa is being affected by the increasing incidence of pests, low selling prices, high production costs, and the presence of cadmium in cocoa farms, posing a potential risk of crop abandonment. Therefore, the objective of the present research was to evaluate the economic profitability of carbon sequestration of fine-aroma cacao agroforestry systems in Amazonas, Peru, using the economic indicators of NPV, EIRR, and the benefit–cost ratio. For this purpose, 53 small cocoa producers of the APROCAM cooperative were involved, from which data were obtained on the general characteristics of the production system, production and maintenance costs, indirect costs, and administrative costs; in addition, the costs of implementation and maintenance of an environmental services project were calculated to finally make a cash flow projected over 5 years. As part of the results, the economic analysis was carried out on 104.25 hectares of cocoa belonging to the total number of farmers evaluated, who reported an average yield of 957.32 kg of dry cocoa per he. In addition, it was found that the production cost is PEN 3.91/kg of dry cocoa, and the average selling price is PEN 7.38/kg of dry cocoa. After the economic analysis, it was found that the implementation of an environmental services project is profitable (NPV = PEN 1,454,547.8; EIRR = 44% and B/C = 1.86). These results open up an opportunity for cocoa farmers to diversify and increase their income by contributing to climate change mitigation.
To Achieve a Win–Win Situation: Reorganizing and Enhancing Agroforestry Ecosystem Assets and Productivity to Inform Karst Desertification Control
Authors: Huang Yunting , Xiong Kangning , Xiao Jie
Published: March 2024

The ongoing degradation of fragile ecosystems increasingly diminishes the availability of natural resources. Consequently, the conservation and utilization of ecosystem assets have emerged as a focal point of global research. This study focuses on integrating agroforestry ecosystem assets (AEA) with their capacity to provide ecosystem services, aiming to explore their interconnections and enhance their optimization. We employed a comprehensive literature review method, utilizing the Scopus database to select, analyze, and include 61 pertinent studies on AEA globally. The systematic literature review results show the following: (1) The overall number of published papers is showing an upward trend, indicating that research in this field is gradually expanding. The geographical focus of the literature is primarily in Europe and Asia, with academic institutions being the main contributors to this research. (2) Landmark research findings are mainly concentrated in the areas of identification, quantitative assessment, and decision management. Among these, quantitative assessment is the main focus, while the research on identification, decision management, and influencing factors is relatively limited and explores the relevant key scientific questions. (3) The above information highlights the key areas for improvement in the karst desertification control agroforestry ecosystem, focusing on two aspects: fragile habitats and human–land relationships. Furthermore, this review furnishes essential recommendations for agroforestry practitioners and policymakers across various regions, emphasizing the critical need to thoroughly evaluate and leverage the connections between the quantity and quality of ecosystem assets. Such an approach is pivotal for facilitating the strategic restructuring and optimization of agroforestry ecosystems. This, in turn, aims to elevate the sustainability of AEA utilization and enhance their ability to provide ecosystem services (ES).
Can Ensemble Techniques and Large-Scale Fire Datasets Improve Predictions of Forest Fire Probability Due to Climate Change?—A Case Study from the Republic of Korea
Authors: Ahn Hyeon Kwon , Jung Huicheul , Lim Chul-Hee
Published: March 2024

The frequency of forest fires worldwide has increased recently due to climate change, leading to severe and widespread damage. In this study, we investigate potential changes in the fire susceptibility of areas in South Korea arising from climate change. We constructed a dataset of large-scale forest fires from the past decade and employed it in machine learning models that integrate climatic, socioeconomic, and environmental variables to assess the risk of forest fires. According to the results of these models, the eastern region is identified as highly vulnerable to forest fires during the baseline period, while the western region is classified as relatively safe. However, in the future, certain areas along the western coast are predicted to become more susceptible to forest fires. Consequently, as climate change continues, the risk of domestic forest fires is expected to increase, leading to the need for proactive prevention measures and careful management. This study contributes to the understanding of forest fire occurrences under diverse climate scenarios.
Study on the Process Optimization of Peanut Coat Pigment Staining of Poplar Wood
Authors: Qi Yiqing , Zhang Ziqiang , Sun Yue , Shen Liming , Han Jianlin
Published: March 2024

Wood staining is a crucial technique for enhancing the decorative effect of wood. Different mordants and mordant processes can influence the staining effect of wood. In this study, three types of mordants and mordant methods were selected to improve the color difference and colorfastness to the washing of poplar veneer, using green peanut pigment as the dye. An orthogonal test was conducted to investigate the effects of mordant temperature, mordant time, and mordant concentration on color difference and colorfastness to washing. Range and variance analysis were employed to determine these properties’ main factors. A fuzzy comprehensive evaluation method was used to evaluate and optimize the color difference value and colorfastness of washing. The results revealed that all three factors had significant impacts on both color difference and colorfastness to washing during the process of mordant staining. The optimal process conditions (temperature, concentration, time) for achieving desirable staining effects on poplar veneer were determined as 50 °C, 0.8%, and 2 h, respectively. Furthermore, Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray diffraction (XRD) analyses demonstrated that the dye formed complexes with poplar wood, enabling it to adhere to wood grain apertures and tube walls effectively. Mordant treatment increased the crystallinity of stained wood significantly while improving its overall staining performance considerably. This study provides substantial data support for future optimization processes involving natural pigment coal staining in wood.
Dynamic Changes in Vegetation Ecological Quality in the Tarim Basin and Its Response to Extreme Climate during 2000–2022
Authors: Zhang Yuanmei , Lu Yan , Sun Guili , Li Li , Zhang Zhihao , Zhou Xiaoguo
Published: March 2024

The Tarim Basin is located in an arid inland area; the ecological environment is fragile, and it is extremely sensitive to climate change. For the purpose of studying dynamic changes in the vegetation response of vegetation in the Tarim Basin to extreme climate, this study used the Vegetation Ecological Quality Index (EQI) as a vegetation indicator and calculated 12 extreme climate indices using Rclimdex. Pearson correlation analysis was used to explore the relationship between EQI values and various extreme climate indices at both inter-annual and intra-annual scales. Additionally, geographic detector analysis was employed to examine the single and interactive effects of extreme climate on the EQI for different vegetation types. The following was found: (1) During 2000–2022, the EQI showed an upward trend in the Tarim Basin, and the increase in agricultural vegetation was the fastest. (2) Since 2000, the extreme warm temperature indices have risen, whereas the extreme cold temperature indices have declined. The warming rate of nighttime temperatures exceeds that of daytime, and the extreme precipitation rises intensively. Simultaneously, continuous dry days have also increased. (3) On an inter-annual scale, the EQI is primarily negatively correlated with the most extreme warm temperature indices, while it is positively correlated with extreme cold temperatures and extreme precipitation indices. On an intra-annual scale, there is an obvious regional concentration in the correlation between the EQI and extreme climate indices. The diurnal temperature range (DTR) and cold daytimes (TX10P) have inhibitory and promoting effects on areas with high and low EQI, respectively. The extremum indices, temperature warm indices, and precipitation intensity indices have a promoting effect on areas with a high EQI and an inhibiting effect on areas with a low EQI. The interaction between extreme climate indices has a greater impact on the EQI than the effect of a single extreme climate index, especially with a significant impact on forests and shrubs. This study provides a reference for the early warning of meteorological disasters, ecosystem protection, and sustainable management in the Tarim Basin.
Assessing Forest-Change-Induced Carbon Storage Dynamics by Integrating GF-1 Image and Localized Allometric Growth Equations in Jiangning District, Nanjing, Eastern China (2017–2020)
Authors: Liu Jiawei , Yang Boxiang , Li Mingshi , Xu Da
Published: March 2024

Forest and its dynamics are of great significance for accurately estimating regional carbon sequestration, emissions and carbon sink capacity. In this work, an efficient framework that integrates remote sensing, deep learning and statistical modeling was proposed to extract forest change information and then derive forest carbon storage dynamics during the period 2017 to 2020 in Jiangning District, Nanjing, Eastern China. Firstly, the panchromatic band and multi-spectral bands of GF-1 images were fused by using four different methods; Secondly, an improved Mask-RCNN integrated with Swin Transformer was devised to extract forest distribution information in 2020. Finally, by using the substitution strategy of space for time in the 2017 Forest Management and Planning Inventory (FMPI) data, local carbon density allometric growth equations were fitted by coniferous forest and broad-leaved forest types and compared, and the optimal fitting was accordingly determined, followed by the measurements of forest-change-induced carbon storage dynamics. The results indicated that the improved Mask-RCNN synergizing with the Swin Transformer gained an overall accuracy of 93.9% when mapping the local forest types. The carbon storage of forest standing woods was calculated at 1,449,400 tons in 2020, increased by 14.59% relative to that of 2017. This analysis provides a technical reference for monitoring forest change and lays a data foundation for local agencies to formulate forest management policies in the process of achieving dual-carbon goals.
Qualitative Anatomical Characteristics and Fiber Quality of Tapped Styrax sumatrana Wood Grown in North Sumatra, Indonesia
Authors: Darwis Atmawi , Purusatama Byantara Darsan , Iswanto Apri Heri , Kim Nam-Hun , Hartono Rudi , Susilowati Arida
Published: March 2024

This study investigated the qualitative anatomical characteristics and fiber quality of tapped Styrax sumatrana wood to facilitate its further utilization. The transverse surface of the tapped S. sumatrana was light or greyish brown in the sapwood and reddish brown in the heartwood. The resin canals of the tapped wood were formed along the growth rings at the boundaries between the heartwood and sapwood. Furthermore, microscopic analyses revealed an irregular outline and rounded epithelial cells at the edges of the intercellular traumatic canal (TC). Approximately 8–16 epithelial cells surrounded the resin canals. The fibers in the tapped S. sumatrana were generally thin-walled, whereas those near the TC were thick-walled. Moreover, S. sumatrana were diffuse-porous and exhibited intermediately distinct or indistinct growth ring boundaries. The vessels were mainly radial multiples and clusters of 3–5. In addition, they showed a diagonal-to-radial pattern arrangement and a few tangential bands. Deposits were observed in some vessels in the tapped part but were absent in the untapped part. The fiber length of the tapped S. sumatrana wood was classified as moderate to extensive and categorized as second-grade pulp quality. Finally, the cell walls were classified as thin to moderate.
Implementing Internet of Things Service Platforms with Network Function Virtualization Serverless Technologies
Authors: Femminella Mauro , Reali Gianluca
Published: March 2024

The need for adaptivity and scalability in telecommunication systems has led to the introduction of a software-based approach to networking, in which network functions are virtualized and implemented in software modules, based on network function virtualization (NFV) technologies. The growing demand for low latency, efficiency, flexibility and security has placed some limitations on the adoption of these technologies, due to some problems of traditional virtualization solutions. However, the introduction of lightweight virtualization approaches is paving the way for new and better infrastructures for implementing network functions. This article discusses these new virtualization solutions and shows a proposal, based on serverless computing, that uses them to implement container-based virtualized network functions for the delivery of advanced Internet of Things (IoT) services. It includes open source software components to implement both the virtualization layer, implemented through Firecracker, and the runtime environment, based on Kata containers. A set of experiments shows that the proposed approach is fast, in order to boost new network functions, and more efficient than some baseline solutions, with minimal resource footprint. Therefore, it is an excellent candidate to implement NFV functions in the edge deployment of serverless services for the IoT.
User Experience, Functionality and Aesthetics Evaluation in an Academic Multi-Site Web Ecosystem
Authors: Giannakoulopoulos Andreas , Pergantis Minas , Lamprogeorgos Aristeidis
Published: March 2024

The present study focuses on using qualitative and quantitative data to evaluate the functionality, user experience (UX), and aesthetic approach offered by an academic multi-site Web ecosystem consisting of multiple interconnected websites. Large entities in various industry fields often have the need for an elaborate Web presence. In an effort to address the challenges posed by this need specifically in the field of academia, the authors developed, over a period of many years, a multi-site ecosystem within the Ionian University, which focuses on interconnectivity and a collaborative approach to academic content management. This system, known as “Publish@Ionio”, uses a singular content management infrastructure to allow for the creation of content for different websites that share both information and resources while at the same time allowing for individual variations in both functionality and aesthetics. The ecosystem was evaluated through quantitative data from its operation and qualitative feedback from a focus-group interview with experts, including website editors and administrative staff. The collected data were used to assess the strengths and weaknesses of the multi-site approach based on the actions and needs of the individuals in charge of generating content. The study led to conclusions on the advantages that interoperability offers in terms of digital and human resource management, the benefits of a unified aesthetic approach that allows for variability, and the necessity of collaborative content management tools that are tailored to the content’s nature.
IMBA: IoT-Mist Bat-Inspired Algorithm for Optimising Resource Allocation in IoT Networks
Authors: Almudayni Ziyad , Soh Ben , Li Alice
Published: March 2024

The advent of the Internet of Things (IoT) has revolutionised our interaction with the environment, facilitating seamless connections among sensors, actuators, and humans. Efficient task scheduling stands as a cornerstone in maximising resource utilisation and ensuring timely task execution in IoT systems. The implementation of efficient task scheduling methodologies can yield substantial enhancements in productivity and cost-effectiveness for IoT infrastructures. To that end, this paper presents the IoT-mist bat-inspired algorithm (IMBA), designed specifically to optimise resource allocation in IoT environments. IMBA’s efficacy lies in its ability to elevate user service quality through enhancements in task completion rates, load distribution, network utilisation, processing time, and power efficiency. Through comparative analysis, IMBA demonstrates superiority over traditional methods, such as fuzzy logic and round-robin algorithms, across all performance metrics.
Impact of Technological Processes on the Formation of Furosine, Acrylamide and Furan in Traditional Venezuelan Cocoa
Authors: Moreno-Trujillo Thayra Rocio , Perez Elevina , Verardo Vito , García-Villanova Belén , Guerra-Hernández Eduardo Jesús
Published: March 2024

The present study was conducted to determine and analyse the content of furosine, acrylamide and furan in fermented cocoa beans from the Chuao (“criollo variety”) and Barlovento (“trinitario variety”) regions of Venezuela, after roasting (in the shell at 110–180 °C for 15–60 min) and alkalisation (with sodium bicarbonate or potassium carbonate, at concentrations of 10–25 g/kg in order to evaluate the impact of these operations. The highest furosine contents (up to 249 mg/100 g of protein) were found in fermented, sun-dried samples, and were higher in the nibs than in the shells. The acrylamide content increased in line with the temperature, to 160 °C in the shells, and to 180 °C in the nibs. At temperatures of up to 140 °C, the acrylamide content was higher in the shells than in the nibs. The furan content increased in line with the temperature and in this case too, was greater in the shells. The content of both furosine and furan decreased with alkalisation, while the presence of acrylamide was irregular and determined by the roasting temperature and the alkalising agent employed. Although the furosine, acrylamide and furan contents varied between the beans from the two regions and the varieties considered (Chuao and Barlovento), these three compounds were correlated to a statistically significant degree.