bluuebunny/crossref_metadata_2025 huggingface dataset:
Origin of Temperature Coefficient of Resonance Frequency in Rutile Ti1−xZrxO2 Microwave Ceramics
Authors: Khan Izaz , Khan Aneela , Muhammad Raz , Mao Minmin , Han Dandan , Song Kaixin , Lei Wen , Wang Dawei
Published: May 2024

In this study, we report the effect of Zr4+ doping on the optical energy gap and microwave dielectric properties of rutile TiO2. Rietveld analysis explicitly confirmed that Zr4+ occupies the octahedral site, forming a single-phase tetragonal structure below the solubility limit (x < 0.10). Notably, at x = 0.025, a significant enhancement in Q × fo was observed. This enhancement was attributed to the reduction in dielectric loss, associated with a decrease in oxygen vacancies and a lower concentration of Ti3+ paramagnetic centers. This conclusion was supported by Raman and electron paramagnetic resonance spectroscopy, respectively. The origin of high τf in rutile Ti1−xZrxO2 is explained on the basis of the octahedral distortion/tetragonality ratio, covalency, and bond strength.
Study of Optical Performance and Structure of Yb/Al (1.5 wt.% Si) and Yb/Al (Pure) Multilayers Designed for the 73.6 nm Range
Authors: Lai Bo , Qi Runze , Zhang Zengbo , Wang Zhanshan
Published: May 2024

Yb/Al multilayer films exhibit excellent theoretical reflectivity in the 54–90 nm wavelength range. This study attempted to incorporate 1.5% wt.% of Si impurities into Al to suppress the crystallization of Al, reduce interfacial roughness, and enhance the actual reflectivity of the prepared Yb/Al multilayer films. Internal microstructure changes in the film layers before and after Si impurity doping were investigated using GIXRR, AFM, and XRD techniques. The reflectivity of two types of multilayer films, Yb/Al (1.5 wt.% Si) and Yb/Al (pure), was tested to evaluate the effect of Si impurity on film performance. The reflectivity of Yb/Al (1.5 wt.% Si) multilayers compared to Yb/Al (pure) multilayers increased by approximately 4%.
Machine Learning Decision System on the Empirical Analysis of the Actual Usage of Interactive Entertainment: A Perspective of Sustainable Innovative Technology
Authors: Guste Rex Revian A. , Ong Ardvin Kester S.
Published: May 2024

This study focused on the impact of Netflix’s interactive entertainment on Filipino consumers, seamlessly combining vantage points from consumer behavior and employing data analytics. This underlines the revolutionary aspect of interactive entertainment in the quickly expanding digital media ecosystem, particularly as Netflix pioneers fresh content distribution techniques. The main objective of this study was to find the factors impacting the real usage of Netflix’s interactive entertainment among Filipino viewers, filling a critical gap in the existing literature. The major goal of using advanced data analytics techniques in this study was to understand the subtle dynamics affecting customer behavior in this setting. Specifically, the random forest classifier with hard and soft classifiers was assessed. The random forest compared to LightGBM was also employed, alongside the different algorithms of the artificial neural network. Purposive sampling was used to obtain responses from 258 people who had experienced Netflix’s interactive entertainment, resulting in a comprehensive dataset. The findings emphasized the importance of hedonic motivation, underlining the requirement for highly engaging and rewarding interactive material. Customer service and device compatibility, for example, have a significant impact on user uptake. Furthermore, behavioral intention and habit emerged as key drivers, revealing interactive entertainment’s long-term influence on user engagement. Practically, the research recommends strategic platform suggestions that emphasize continuous innovation, user-friendly interfaces, and user-centric methods. This study was able to fill in the gap in the literature on interactive entertainment, which contributes to a better understanding of consumer consumption and lays the groundwork for future research in the dynamic field of digital media. Moreover, this study offers essential insights into the intricate interaction of consumer preferences, technology breakthroughs, and societal influences in the ever-expanding environment of digital entertainment. Lastly, the comparative approach to the use of machine learning algorithms provides insights for future works to adopt and employ among human factors and consumer behavior-related studies.
Exploiting Anytime Algorithms for Collaborative Service Execution in Edge Computing
Authors: Nogueira Luís , Coelho Jorge , Pereira David
Published: May 2024

The diversity and scarcity of resources across devices in heterogeneous computing environments can impact their ability to meet users’ quality-of-service (QoS) requirements, especially in open real-time environments where computational loads are unpredictable. Despite this uncertainty, timely responses to events remain essential to ensure desired performance levels. To address this challenge, this paper introduces collaborative service execution, enabling resource-constrained IoT devices to collaboratively execute services with more powerful neighbors at the edge, thus meeting non-functional requirements that might be unattainable through individual execution. Nodes dynamically form clusters, allocating resources to each service and establishing initial configurations that maximize QoS satisfaction while minimizing global QoS impact. However, the complexity of open real-time environments may hinder the computation of optimal local and global resource allocations within reasonable timeframes. Thus, we reformulate the QoS optimization problem as a heuristic-based anytime optimization problem, capable of interrupting and quickly adapting to environmental changes. Extensive simulations demonstrate that our anytime algorithms rapidly yield satisfactory initial service solutions and effectively optimize the solution quality over iterations, with negligible overhead compared to the benefits gained.
Computational Discovery of Novel Imidazole Derivatives as Inhibitors of SARS-CoV-2 Main Protease: An Integrated Approach Combining Molecular Dynamics and Binding Affinity Analysis
Authors: Babalola Benjamin Ayodipupo , Adegboyega Abayomi Emmanuel
Published: May 2024

One of the most pressing challenges associated with SARS treatment is the emergence of new variants that may be transmissible, causing more severe disease or being resistant to the current standard of treatment. This study aimed to identify potential drug candidates from novel imidazole derivatives against SARS-CoV-2 main protease (Mpro), a crucial drug target for treating viral infection, using a computational approach that integrated molecular docking and dynamics simulation. In this study, we utilized AutoDock Vina within the PyRx workspace for molecular docking analysis to explore the inhibitory effects of the compounds on the Mpro, a drug target for SARS-CoV-2. The ADMET properties of these compounds, including absorption, distribution, metabolism, excretion, and toxicity, were evaluated using the SwissADME and ADMETLab servers. Each of the 18 compounds that were tested demonstrated strong binding affinities towards Mpro, with imidazolyl–methanone C10 showing the most significant binding affinity. Moreover, pyridyl–imidazole C5, thiophenyl–imidazole C1, and quinoline–imidazole C14 displayed binding affinities of −8.3, −8.2, and −7.7 Kcal/mol, respectively. These compounds interacted with specific amino acid residues (HIS A:41—CYS A:145) within the Mpro protein. To assess the stability of the ligand with the best binding affinity, molecular dynamics (MD) simulations were conducted using Schrodinger software, which revealed its stability over the simulation period. The study provides valuable insights into the potential of imidazole derivatives as SARS-CoV-2 Mpro inhibitors. All compounds including C10 display promising characteristics and hold potential as drug candidates for SARS-CoV-2. However, further optimization and experimental validation of these compounds are necessary to advance their development as effective therapeutics against viral infections.
Investigating Genetic Diversity and Population Structure in Rice Breeding from Association Mapping of 116 Accessions Using 64 Polymorphic SSR Markers
Authors: Singh Alok , Kumar Devendra , Gemmati Donato , Ellur Ranjith , Singh Ashutosh , Tisato Veronica , Dwivedi Devendra , Singh Sanjay , Kumar Kishor , Khan Nawaz , Singh Ajay
Published: May 2024

Genetic variability in rice breeding programs plays a very crucial role. It provides an outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For a greater understanding of population structure, the genetic relationship among different rice lines is indispensable prior to the setting of a correlation among dynamic alleles and traits. In the present investigation, the genetic diversity and population structure of 116 rice accessions were studied to understand genetic relatedness and diversity among them using 64 polymorphic SSR markers. A genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model- and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% was likely due to differences within groups. This study suggested that population structure and genetic relatedness should be considered to establish marker–trait associations for association mapping when working with the core collection of germplasm lines.
Survival, Nest Site Affiliation and Post-Fledging Movements of Danish White-Tailed Eagles (Haliaeetus albicilla)
Authors: Eskildsen Daniel Palm , Ali Nina Yasmin , Larsen Jonas Colling , Thorup Kasper , Skelmose Kim , Tøttrup Anders P.
Published: May 2024

The early life movement patterns of long-lived, large raptors, such as the white-tailed eagle (Haliaeetus albicilla), remain largely unexplored. In this study, we have tracked 22 individuals of white-tailed eagles hatched in Denmark to investigate key parameters, including survival rates, causes of death, nest site fidelity, geographical distribution, and dispersal behaviors. Our analyses are based on approximately 340,000 GPS/GSM telemetry positions from the 22 individuals. We found that survival rates were lower in the first year of life, especially among females, but increased in subsequent years. The primary causes of death were wind turbine collisions and avian influenza. Movement analyses revealed that juvenile eagles frequented nest sites in August and September, with females showing earlier exploratory flights and dispersal. Both males and females spent most of their first calendar year near their nest sites. In the second calendar year, a significant proportion of their time was spent at well-known white-tailed eagle resting areas in Denmark, as well as visiting neighboring countries. Notably, one individual set a new distance record for a Danish GPS-tagged white-tailed eagle, venturing at least 1750 km away from its nest site to visit Sweden, Finland, Russia, and Norway. Our results, indicating that juvenile white-tailed eagles continue to utilize nest sites into September, suggest an extension of the recommended time period for nest protection zones provided by BirdLife Denmark (DOF).
Efficacy and Safety of Botulinum Toxin in the Management of Temporomandibular Symptoms Associated with Sleep Bruxism: A Systematic Review
Authors: Buzatu Roxana , Luca Magda Mihaela , Castiglione Luca , Sinescu Cosmin
Published: May 2024

Sleep bruxism, characterized by involuntary grinding or clenching of teeth during sleep, poses significant challenges in management due to its potential to induce temporomandibular joint disorders (TMDs) and other related symptoms. The use of Botulinum toxin Type A (BoNT-A), also known as Botox®, has been proposed as a therapeutic intervention. This systematic review aims to evaluate the efficacy and safety of BoNT-A in the management of sleep bruxism, focusing on pain reduction, improvement in jaw function, reduction in bruxism episodes, and the incidence of adverse effects. An exhaustive search was conducted across PubMed, Scopus, and Embase databases up to January 2024, adhering to the PRISMA guidelines. Nine randomized clinical trials (RCTs) involving 137 participants were analyzed for efficacy and safety outcomes. The studies demonstrated a significant reduction in mean pain scores (from 7.1 to 0.2 at 6 months and 1 year post-treatment in one study) and a notable decrease in the number of bruxism events (from 4.97/h to 1.70/h in the BoNT-A group in another study). Additionally, improvements were observed in jaw stiffness and total sleep time. Adverse effects varied but were generally mild and transient, including injection site pain in 20% of participants in one study and cosmetic changes in smile in 15.4% of patients in another. These findings suggest that BoNT-A injections may provide some benefits for treating nocturnal bruxism, potentially reducing TMD symptoms like pain and improving jaw function. However, these findings are preliminary due to variability in study designs and the absence of detailed statistical analysis.
Fluctuation Theorems for Heat Exchanges between Passive and Active Baths
Authors: Semeraro Massimiliano , Suma Antonio , Negro Giuseppe
Published: May 2024

In addition to providing general constraints on probability distributions, fluctuation theorems allow us to infer essential information on the role played by temperature in heat exchange phenomena. In this numerical study, we measure the temperature of an out-of-equilibrium active bath using a fluctuation theorem that relates the fluctuations in the heat exchanged between two baths to their temperatures. Our setup consists of a single particle moving between two wells of a quartic potential accommodating two different baths. The heat exchanged between the two baths is monitored according to two definitions: as the kinetic energy carried by the particle whenever it jumps from one well to the other and as the work performed by the particle on one of the two baths when immersed in it. First, we consider two equilibrium baths at two different temperatures and verify that a fluctuation theorem featuring the baths temperatures holds for both heat definitions. Then, we introduce an additional Gaussian coloured noise in one of the baths, so as to make it effectively an active (out-of-equilibrium) bath. We find that a fluctuation theorem is still satisfied with both heat definitions. Interestingly, in this case the temperature obtained through the fluctuation theorem for the active bath corresponds to the kinetic temperature when considering the first heat definition, while it is larger with the second one. We interpret these results by looking at the particle jump phenomenology.
Public Health Expenditure and Sustainable Health Outcomes in 45 Sub-Saharan African Countries: Does Government Effectiveness Matter?
Authors: Arize Augustine , Kalu Ebere Ume , Lubiani Greg , Udemezue Ndubuisi N.
Published: May 2024

This paper examines the interaction between health expenditure and health outcomes with due consideration for government effectiveness across developing African economies. The rich data for this study draw from forty-five Sub-Saharan African (SSA) countries covering the period 1960 to 2022. The analysis follows a country-specific comparative manner using the Autoregressive Distributed Lag (ARDL) model as the major estimation technique. The results indicate that poor health outcomes are not due to inadequate budgetary allocations alone. Specifically, this study found a cointegrating relationship and strong adjustment of health outcomes deriving from the shocks and dynamics of not just health expenditures, but also government effectiveness. It is therefore recommended that strong institutions and safety nets be created to guard against corruption and leakages that derail the beneficial impact of public health spending. Also, government expenditures should be focused more on cottage and primary health dimensions to better mitigate adverse health conditions in SSA countries.
The Use of Research in Schools: Principals’ Capacity and Contributions
Authors: Farley-Ripple Elizabeth N.
Published: May 2024

Policy expectations for the role of research evidence in educational decision-making have grown exponentially in the U.S. and globally, yet there has been limited attention to school capacity to engage in evidence-informed improvement. In this paper, I address this gap by first conceptualizing principal leadership for evidence use and, second, use this conceptual lens to examine large-scale survey data about school evidence use practices and capacity. Drawing on data from a national survey of more than 4000 educators in 134 schools in the US, I explore school practices and capacity to use research and surface opportunities and needs for principal leadership in evidence-informed improvement. Findings suggest that there is an opportunity to improve the role of research in school improvement decision-making, and that principals may contribute to school capacity in specific ways that relate to developing human capital, influencing culture, leveraging resources, and shaping decision-making. Data reveal moderate evidence of research use in agenda setting and of organizational routines that support research use, but lack of uptake of those routines for research use as well as limited investment in resources (e.g., time). Further, decision-making was distributed across a wide range of improvement initiatives, with evidence of a lack of clarity about goals. Although principals report confidence and experience with using research, overall school staff also reported limited experience with prior research, including coursework or participation in research, and low confidence in critically consuming research. Implications point to the need to strengthen principals’ own evidence use capacity as well as focus on dimensions school capacity as part of evidence use initiatives. Recommendations suggest strategies for developing principals’ knowledge and skills around leadership for evidence-informed improvement.
Associations of Eating Habits with Self-Rated Health and Life Satisfaction in Adolescents: A 42-Country Cross-Sectional Study
Authors: Chen Sitong , López-Gil José Francisco , Memon Aamir Raoof , Bao Ran , Yang Xingyi
Published: May 2024

Objective: The aim of this study was to explore the associations of eating habits with self-rated health and life satisfaction in adolescents using a multiple-country sample. Methods: Cross-sectional data from the Health Behavior in School-Aged Children (HBSC) 2013/2014 wave was used in this study. A self-reported questionnaire was used to collect data on independent variables including breakfast on weekdays, breakfast at weekends, and consumption of fruits, vegetables, sweets, and soft dirks. Outcomes included self-rated health and life satisfaction. Regression models were used to assess the associations between the independent variables and the two outcomes, separately, after controlling for covariates. Results were presented using odds ratios (ORs) and 95% confidence intervals (CIs). Results: Of all the study participants (aged 11–15 years), 50.8% were girls. Compared with no consumption of breakfast on weekdays, eating breakfast for five days had 1.22 times greater likelihood for improved self-rated health (OR = 1.22, 95% CI: 1.19–1.25, p < 0.001). Participants who ate breakfast for both days (OR = 1.41, 95% CI: 1.36–1.46, p < 0.001) and one day (OR = 1.12, 95% CI = 1.08–1.17, p < 0.001) were more likely to experience improved self-rated health compared to never eating breakfast at weekends. Five or more days for fruit and vegetable consumption resulted in better self-rated health (all p < 0.001). Similar results were found in terms of the associations of breakfast, fruit, and vegetable consumption with life satisfaction. For example, a higher frequency of fruit intake was associated with enhanced self-rated health (e.g., OR for more than once daily = 1.42, 95% CI: 1.34–1.51, p < 0.001) compared to no fruit consumption. Similarly, a higher-frequency vegetable intake, such as more than once daily (OR = 1.33, 95% CI: 1.26–1.39, p < 0.001), was associated with improved self-rated health. Conclusions: Healthy eating habits, especially regular breakfast and a higher consumption of vegetables and fruit, are associated with better self-rated health and life satisfaction in school-aged children. Of note, the consumption of fruit would have the greatest impact on health and wellbeing outcomes. This study offers evidence that healthy eating habits can play a vital role in school-aged children’s health and wellbeing, highlighting the practical significance of educating adolescents to develop healthy eating habits.
AUV Obstacle Avoidance Framework Based on Event-Triggered Reinforcement Learning
Authors: Liu Shoufu , Ma Chao , Juan Rongshun
Published: May 2024

Autonomous Underwater Vehicles (AUVs), as a member of the unmanned intelligent ocean vehicle group, can replace human beings to complete dangerous tasks in the ocean. It is of great significance to apply reinforcement learning (RL) to AUVs to realize intelligent control. This paper proposes an AUV obstacle avoidance framework based on event-triggered reinforcement learning. Firstly, an environment perception model is designed to judge the relative position relationship between the AUV and all unknown obstacles and known targets. Secondly, considering that the detection range of AUVs is limited, and the proposed method needs to deal with unknown static obstacles and unknown dynamic obstacles at the same time, two different event-triggered mechanisms are designed. Soft actor–critic (SAC) with a non-policy sampling method is used. Then, improved reinforcement learning and the event-triggered mechanism are combined in this paper. Finally, a simulation experiment of the obstacle avoidance task is carried out on the Gazebo simulation platform. Results show that the proposed method can obtain higher rewards and complete tasks successfully. At the same time, the trajectory and the distance between each obstacle confirm that the AUV can reach the target well while maintaining a safe distance from static and dynamic obstacles.
Context Awareness Assisted Integration System for Land Vehicles
Authors: Li Xiaoyu , Guo Xiye , Liu Kai , Meng Zhijun , Chen Guokai , Tang Yuqiu , Yang Jun
Published: May 2024

Accurate context awareness of land vehicles can assist integrated navigation systems. Motion behavior recognition is one context awareness of vehicles, based on which constraint information helps reduce the impact of short-term blockage of navigation signals on radio-frequency-based positioning systems. To improve the reliability of behavior recognition, we proposed a machine learning-based vehicle motion behavior recognition and constraint method (MLMRC). The machine learning-based recognition process is directly driven by raw data from low-cost MEMS-IMU, while the traditional threshold-based method relies on previous experience. Four categories of constraint information—sensor error calibration, velocity constraint, angle constraint, and position constraint—were constructed from the recognition results. Both the simulated vehicle experiment and real vehicle experiment demonstrate the performance of the MLMRC method. When there is a short-term blockage, the MLMRC method can reduce the positioning error from 17.2% to 38.3% compared with the traditional method, which effectively improves positioning accuracy and provides support for autonomous vehicles in complex urban environments.
Video Summarization Generation Network Based on Dynamic Graph Contrastive Learning and Feature Fusion
Authors: Zhang Jing , Wu Guangli , Bi Xinlong , Cui Yulong
Published: May 2024

Video summarization aims to analyze the structure and content of videos and extract key segments to construct summarization that can accurately summarize the main content, allowing users to quickly access the core information without browsing the full video. However, existing methods have difficulties in capturing long-term dependencies when dealing with long videos. On the other hand, there is a large amount of noise in graph structures, which may lead to the influence of redundant information and is not conducive to the effective learning of video features. To solve the above problems, we propose a video summarization generation network based on dynamic graph contrastive learning and feature fusion, which mainly consists of three modules: feature extraction, video encoder, and feature fusion. Firstly, we compute the shot features and construct a dynamic graph by using the shot features as nodes of the graph and the similarity between the shot features as the weights of the edges. In the video encoder, we extract the temporal and structural features in the video using stacked L-G Blocks, where the L-G Block consists of a bidirectional long short-term memory network and a graph convolutional network. Then, the shallow-level features are obtained after processing by L-G Blocks. In order to remove the redundant information in the graph, graph contrastive learning is used to obtain the optimized deep-level features. Finally, to fully exploit the feature information of the video, a feature fusion gate using the gating mechanism is designed to fully fuse the shallow-level features with the deep-level features. Extensive experiments are conducted on two benchmark datasets, TVSum and SumMe, and the experimental results show that our proposed method outperforms most of the current state-of-the-art video summarization methods.
Using the Buckingham π Theorem for Multi-System Transfer Learning: A Case-Study with 3 Vehicles Sharing a Database
Authors: Therrien William , Lecompte Olivier , Girard Alexandre
Published: May 2024

Many advanced driver assistance schemes or autonomous vehicle controllers are based on a motion model of the vehicle behavior, i.e., a function predicting how the vehicle will react to a given control input. Data-driven models, based on experimental or simulated data, are very useful, especially for vehicles difficult to model analytically, for instance, ground vehicles for which the ground-tire interaction is hard to model from first principles. However, learning schemes are limited by the difficulty of collecting large amounts of experimental data or having to rely on high-fidelity simulations. This paper explores the potential of an approach that uses dimensionless numbers based on Buckingham’s π theorem to improve the efficiency of data for learning models, with the goal of facilitating knowledge sharing between similar systems. A case study using car-like vehicles compares traditional and dimensionless models on simulated and experimental data to validate the benefits of the new dimensionless learning approach. Preliminary results from the case study presented show that this new dimensionless approach could accelerate the learning rate and improve the accuracy of the model prediction when transferring the learned model between various similar vehicles. Prediction accuracy improvements with the dimensionless scheme when using a shared database, that is, predicting the motion of a vehicle based on data from various different vehicles was found to be 480% more accurate for predicting a simple no-slip maneuver based on simulated data and 11% more accurate to predict a highly dynamic braking maneuver based on experimental data. A modified physics-informed learning scheme with hand-crafted dimensionless features was also shown to increase the improvement to precision gains of 917% and 28% respectively. A comparative study also shows that using Buckingham’s π theorem is a much more effective preprocessing step for this task than principal component analysis (PCA) or simply normalizing the data. These results show that the use of dimensionless variables is a promising tool to help in the task of learning a more generalizable motion model for vehicles, and hence potentially taking advantage of the data generated by fleets of vehicles on the road even though they are not identical.
Jerusalem Artichoke: Energy Balance in Annual and Perennial Cropping Systems—A Case Study in North-Eastern Poland
Authors: Jankowski Krzysztof Józef , Bogucka Bożena
Published: May 2024

This article presents the results of a three-year experiment (2018–2020) conducted at the Agricultural Experiment Station in Bałcyny (north-eastern Poland) with the aim of determining Jerusalem artichoke (JA) yields and the energy balance of biomass production in (i) a perennial cropping system (only aerial biomass was harvested each year) and (ii) an annual cropping system (both aerial biomass and tubers were harvested each year). When JA was grown as a perennial crop, the demand for energy reached 25.2 GJ ha−1 in the year of plantation establishment and 12.3–13.4 GJ ha−1 in the second and third year of production. The energy inputs associated with the annual cropping system were determined in the range of 31.4–37.1 GJ ha−1. Biomass yields were twice as high in the annual than in the perennial cropping system (20.98 vs. 10.30 Mg DM ha−1). Tuber yield accounted for 46% of the total yield. The energy output of JA biomass was 1.8 times higher in the annual than in the perennial cropping system (275.4 vs. 157.3 GJ ha−1). The average energy gain in JA cultivation ranged from 140 (perennial crop) to 241 GJ ha−1 (annual crop). The energy efficiency ratio of JA biomass production reached 7.7–13.3 in the perennial cropping system, and it was 20% lower in the annual cropping system. These results imply that when JA was grown as an annual crop, an increase in energy inputs associated with plantation establishment (tillage and planting) and the harvest and transport of tubers was not fully compensated by the energy output of tubers.
Analyzing Potential Failures and Effects in a Pilot-Scale Biomass Preprocessing Facility for Improved Reliability
Authors: Emerson Rachel M. , Saha Nepu , Burli Pralhad H. , Klinger Jordan L. , Bhattacharjee Tiasha , Vega-Montoto Lorenzo
Published: May 2024

This study demonstrates a failure identification methodology applied to a preprocessing facility generating conversion-ready feedstocks from biomass meeting conversion process critical quality attribute (CQA) specifications. Failure Modes and Effects Analysis (FMEA) was used as an industrially relevant risk analysis approach to evaluate a logging residue preprocessing system to prepare feedstock for pyrolysis conversion. Risk evaluations considered both system-level and operation unit-level assessments considering process efficiency, product quality, cost, sustainability, and safety. Key outputs included estimations of semi-quantitative risk scores for each failure, identification of the failure impacts, identification of failure causes associated with material attributes and process parameters, ranking success rates of failure detection methods, and speculation of potential mitigation strategies for decreasing failure risk scores. Results showed that deviations from moisture specifications had cascading consequences for other CQAs along with process safety implications. Failures linked to fixed carbon specifications carried the highest risk scores for product quality and process efficiency impacts. As increased throughput can be inversely related to meeting product quality specifications; achieving throughput and other material-based CQAs simultaneously will likely require system optimization or prioritization based on system economics. Ultimately, this work successfully demonstrates FMEA as a risk analysis approach for other bioenergy process systems.
Analysis of Power System Electromagnetic Transients Using the Finite Element Technique
Authors: Jurić-Grgić Ivica , Lovrić Dino , Krolo Ivan
Published: May 2024

In this paper, a numerical model for the analysis of electromagnetic transients in a power system, based on the finite element technique, was developed. The simplicity of the finite element technique is manifested in the fact that the problem of solving any mathematically described phenomena in an area is reduced to solving those same phenomena in a small part of that area, i.e., finite elements. Based on appropriate mathematical models, numerical models of the synchronous generator and other parts of the power system have been developed. System of differential equations of each power system element have been included in the numerical model in such a way that we employ numerical integration of the differential equations using the generalized trapezoidal rule (ϑ-method) and reduce it to a system of algebraic equations in each time step. In a practical sense, this method enables a very simple solution to the problem of a real power system, i.e., a system with many generators, transformers, transmission lines and other elements. The accuracy of the developed numerical model for the analysis of electromagnetic transients in a power system has been confirmed by comparing the calculated results with the results obtained using the EMTP software (version 3.3) package.
A Route for Bioenergy in the Sahara Region: Date Palm Waste Valorization through Updraft Gasification
Authors: Djaafri Mohammed , Salem Fethya , Kalloum Slimane , Desideri Umberto , Bartocci Pietro , Khelafi Mostefa , Atabani Abdulaziz E. , Baldinelli Arianna
Published: May 2024

The Adrar region (Algeria) has a total of 397,800 date palm trees (Phoenix dactylifera L.). Due to annual palm cleaning, large quantities of lignocellulosic biomass are produced. Depending on the variety, an average of 65 kg of biowaste is obtained per palm tree. Since the value of this biowaste is underrated, most of the palms are burned outdoors, causing air and visual pollution. This work explores the gasification potential of lignocellulosic waste from date palms (Phoenix dactylifera L. Takarbouche variety) into useful energy. The technology investigated is air updraft fixed-bed gasification, thanks to an originally designed and built reactor, with the capability to process 1 kg of feedstock. Four types of palm waste—namely, palms, petioles, bunch, and bunch peduncles—are first characterized (bulk density, proximate analysis, fixed carbon, elemental composition, and calorific value) and then used as feedstock for two gasification tests each. The syngas produced for the four date palm wastes is combustible, with an outlet temperature between 200 and 400 °C. The operating temperature inside the gasifier varies according to the feature of the biomass cuts (from 174 °C for the peduncles to 557 °C for palms). The experimental setup is also equipped with a cyclone, allowing for the recovery of some of the tar produced during the tests. Finally, the results show that the residence time has a positive effect on the conversion rate of date palm waste, which can significantly increase it to values of around 95%.
Analysis of the Combined Effect of Major Influencing Parameters for Designing High-Performance Single (sBHE) and Double (dBHE) U-Tube Borehole Heat Exchangers
Authors: Kerme Esa Dube , Fung Alan S. , Leong Wey H.
Published: May 2024

In this paper, a comprehensive analysis of the combined effect of major influencing parameters on heat transfer in a single U-tube BHE (sBHE) and a double U-tube BHE (dBHE) with two independent circuits was performed by using a validated numerical heat transfer model. Geometrical parameters, such as shank spacing (with maximum, average, and minimum values), borehole diameter (large, medium, and small borehole sizes), and borehole depth (shallow, average, and deep borehole depths) as well as the thermal conductivity of soil and grout, which ranges from minimum to high values, were considered. The combined impact of these parameters was included under the following four major cases: (1) the combined effect of borehole depth, borehole size, and shank spacing; (2) the combined effect of borehole depth and soil and grout thermal conductivity; (3) the combined effect of soil and grout thermal conductivity and borehole size; and (4) the combined effect of soil thermal conductivity, borehole size, and shank spacing. Each of these major cases has nine different design options for both sBHEs and dBHEs. A series of results of heat transfer per unit borehole depth were generated for all the considered various cases. With the given parameters, the BHE case that provides the highest heat transfer among the various cases of sBHEs and dBHEs were obtained.
Estimation of Rubber Plantation Biomass Based on Variable Optimization from Sentinel-2 Remote Sensing Imagery
Authors: Fu Yanglimin , Tan Hongjian , Kou Weili , Xu Weiheng , Wang Huan , Lu Ning
Published: May 2024

The rapid, accurate, and non-destructive estimation of rubber plantation aboveground biomass (AGB) is essential for producers to forecast rubber yield and carbon storage. To enhance the estimation accuracy, an increasing number of remote sensing variables are incorporated into the development of multi-parameter models, which makes its practical application and the potential impact on predictive precision challenging due to the inclusion of non-essential or redundant variables. Therefore, this study systematically evaluated the performance of different parameter combinations derived from Sentinel-2 imagery, using variable optimization approaches with four machine learning algorithms (Random Forest Regression, RF; XGBoost Regression, XGBR; K Nearest Neighbor Regression, KNNR; and Support Vector Regression, SVR) for the estimation of the AGB of rubber plantations. The results indicate that RF achieved the best estimation accuracy (R2 = 0.86, RMSE = 15.77 Mg/ha) for predicting rubber plantation AGB when combined with Boruta-selected variables, outperforming other combinations (variable combinations obtained based on importance ranking, univariate combinations, and multivariate combinations). Our research findings suggest that the consideration of parameter-optimized remote sensing variables is advantageous for improving the estimation accuracy of forest biophysical parameters, when utilizing a large number of parameters for estimation.
Dynamics of Water Use Efficiency of Coniferous and Broad-Leaved Mixed Forest in East China
Authors: Du Shanfeng , Xie Deyu , Liu Shenglong , Liu Lingjuan , Jiang Jiang
Published: May 2024

The aim of our study is to understand the patterns of variation in water use efficiency (WUE) in coniferous and broad-leaved mixed forest ecosystems across multiple scales and to identify its main controlling factors. We employ the eddy covariance method to gather data from 2017, 2018, and 2020, which we use to calculate the gross primary productivity and evapotranspiration of these forests in East China and to determine WUE at the ecosystem level. The mean daily variation in WUE ranges from 4.84 to 7.88 gC kg−1 H2O, with a mean value of 6.12 gC kg−1 H2O. We use ridge regression analysis to ascertain the independent effect of environmental factors on WUE variation. We find that WUE responds differently to environmental factors at different time scales. In mixed conifer ecosystems, temperature and relative humidity emerge as the most significant environmental factors influencing WUE variability. Especially at the seasonal scale, temperature and relative humidity can explain more than 51% of the WUE variation. Our results underscore the varied effects of environmental factors on WUE variation across different time scales and aid in predicting the response of WUE to climate change in coniferous and broad-leaved mixed forest ecosystems.
Impacts of the Integrated Management of Invasive Weeds and Litter on Slope Hydrology in Eucalyptus Plantations in Central Yunnan, Southwest China
Authors: Yu Fuke , Yan Shilin , Huang Xinhui , Jin Zhiwei , Yan Yi , Li Ziguang , Yang Weixiong , Yin Jianhua , Zhang Guosheng , Chen Qibo
Published: May 2024

Background: The hydrological effects of invasive plant control in forestland have not been well studied in the past, and numerous scientific mysteries remain unsolved. The long-term suspension of the unsolved issues will unavoidably influence the sound growth and sustainable management of forest ecosystems. This study investigates the hydrological effects of controlling invasive weeds in forestland. The research aims to understand the impact of invasive weed control on soil and water loss. Methods: Conducted in Eucalyptus benthamii Maiden & Cambage plantations in Central Yunnan, SW China, which are invaded by alien weed Ageratina adenophora (Spreng.) R. M. King & H. Rob., four surface cover treatments were applied to study runoff and sediment yielding properties. The four surface cover treatments were weed harvesting and litter elimination (WH&LE), weed harvesting and litter retention (WH&LR), litter burning and weed renewal (LB&WR), and weed retention and litter retention (WR&LR). Essentially, WH&LE and LB&WR served as integrated management approaches for invasive weeds and litter, WH&LR was an independent weed control measure, and WR&LR served as a research control. Results: Runoff was significantly higher in the LB&WR plots (3.03 mm) compared to the WR&LR plots (1.48 mm) (p < 0.05). The WH&LE plots had higher runoff (2.39 mm) than the WR&LR plots (not statistically significant), while the WH&LR plots had less runoff (1.08 mm) than the WR&LR plots (not significant). Sediment yield was lower in the WH&LR plots (0.50 t/km2) than in the WR&LR plots (0.52 t/km2) (not significant), but significantly higher in the WH&LE plots (2.10 t/km2) and LB&WR plots (1.57 t/km2) than in the WR&LR plots (p < 0.05). Conclusions: Managing invasive weeds independently reduces the risk of soil and water loss, but combined management with litter can exacerbate the issue. Invasive weed control and litter management should be performed separately in slope plantations. This study provides a scientific basis for soil and water conservation, restoration and rehabilitation of plantation ecosystems.
Estimating Fire Radiative Energy Density with Repeat-Pass Aerial Thermal-Infrared Imaging of Actively Progressing Wildfires
Authors: McFadden Alexander J. , Stow Douglas A. , Riggan Philip J. , Tissell Robert , O’Leary John , Scharf Henry
Published: May 2024

Studies on estimating cumulative fire intensity from spreading wildland fires based on fire radiative energy density (FRED) have primarily been conducted through controlled experiments. The objective of this study was to assess the potential for estimating FRED for freely-burning wildfires at landscape scales. Airborne thermal infrared image sequences collected 8 and 9 December 2017 during the Thomas Fire were used for surface temperature derivation and FRED estimation. Sensitivity of varying ambient temperatures, and a newly developed method that adjusts for ash radiances on fire radiative flux density (FRFD) and FRED estimates were tested. Pixel-level image classification was run to identify FRFD time sequences that were complete or incomplete because of cloud obscuration and provided the basis for an obscuration gap filling technique. Variations in estimated ambient temperature used to estimate FRFD had little impact on FRED estimates, while our ash adjustment led to notable differences. An exponential decay model characterized FRFD time sequences well, providing a basis for gap filling irregular sequences caused by atmospheric obscuration. FRED estimates were regressed on rate of spread (ROS) magnitudes and found to be positively and significantly correlated. FRED magnitudes were higher on 9 December when the Thomas Fire burned under higher wind speeds and lower relative humidity levels (Santa Ana weather conditions) than on 8 December.
Ready-to-Use Supplementary-Food Biscuit Production with Low-Cost Ingredients for Malnourished Children in Sub-Saharan Africa
Authors: Reggi Davide , Alessio Gaia , Ndereyimana Andrè , Minuti Andrea , Spigno Giorgia , Bertoni Giuseppe
Published: May 2024

In Africa, the number of children under 5 years old who suffer from stunting and wasting are, respectively, 61.4 and 12.1 million, and to manage situations like these, emergency food products like RUTF and RUSF (ready-to-use therapeutic/supplementary food) are very useful. The aim of this study was to develop an RUSF biscuit using the low-cost food resources usually present in Sub-Saharan Africa (Burundi and the DRCongo in our case study); we conducted chemical characterization, nutritional evaluation, and a stability trial simulating the usual storage conditions in a rural context to demonstrate that RUSF can be functional also using low-cost ingredients and a simple method of production. The obtained recipes showed good potential in supplying protein integration—17.81% (BUR) and 16.77% (CON) (% as food) were the protein contents—and the protein digestibility values were very high (BUR: 91.72%; CON: 92.01%). Moreover, 30% of the daily requirement was achieved with less than 50 g of both recipes in all the considered ages. Finally, a good shelf-life was demonstrated during the 35-day testing period at 30 °C, considering moisture, texture, and lipid oxidation evolution. Recipes like these, with appropriate changes, could be very useful in all contexts where child malnutrition is a serious problem.
Impact of Lactic Acid Bacteria Fermentation Based on Biotransformation of Phenolic Compounds and Antioxidant Capacity of Mushrooms
Authors: Ayar-Sümer Eda Nur , Verheust Yannick , Özçelik Beraat , Raes Katleen
Published: May 2024

Mushrooms contain phenolic compounds that possess health-promoting properties, including antioxidant effects. However, the low solubility and form of phenolic compounds affect their bioactivity and bioaccessibility. To overcome this limitation, our study investigates the fermentation of mushrooms to increase their free phenolic content and enhance their bioactivity. Our research focused on the impact of fermentation on both free and bound phenolic fractions (FPs and BPs, respectively) in Lentinula edodes and Lactarius deliciosus, which were successively fermented with Lactiplantibacillus plantarum LMG 17673 for 72 h. We examined the total phenolic content (TPC), phenolic profile, and antioxidant activity of both FPs and BPs. Our results showed that the TPC of BPs was higher than that of FPs in both mushrooms, with strong antioxidant capabilities. Fermentation significantly increased the TPC of FPs in both mushrooms, particularly after 24 h of fermentation. The TPC of BPs in mushrooms decreased during fermentation, indicating their release from the matrix. Additionally, we identified 30 bioactive compounds using UPLC-Q-TOF-MS/MS. Our study demonstrates for the first time that lactic acid bacteria fermentation of mushrooms with high phenolic content leads to the liberation of bound phenolics, enhancing their bioactivity and bioaccessibility.