bluuebunny/crossref_metadata_2025 huggingface dataset:
The Oxidative Stability of Champagne Base Wines Aged on Lees in Barrels: A 2-Year Study
Authors: Maxe Charlotte , Romanet Rémy , Parisot Michel , Gougeon Régis D. , Nikolantonaki Maria
Published: March 2024

In contrast with the elaboration of still wines, the impact of barrel aging before the “prise de mousse” on the aging potential of Champagne base wines has not been studied so far. In the present study, the oxidative stability and related molecular fingerprints of Chardonnay Champagne base wines were reported after 1 year of on lees ageing in new oak barrels for two consecutive vintages. Regardless of the vintage, on lees ageing in new oak barrels improved the wines’ oxidative stability estimated by DPPH assay at 1 year, while UHPLC-Q-ToF-MS molecular profiling showed clear chemical modifications according to the ageing period. Oak wood molecular ellagitannins followed a linear extraction during barrel ageing for both vintages. However, the wines’ antioxidant metabolome composed by antiradical and nucleophilic compounds clearly appeared vintage- and barrel-aging dependent. These results enrich the understanding of white wines antioxidant metabolome and improve the knowledge of the ageing potential of Chardonnay Champagne base wines by integrating vintage- and barrel-ageing effects.
Dietary Chitosan Oligosaccharide Supplementation Improves Meat Quality by Improving Antioxidant Capacity and Fiber Characteristics in the Thigh Muscle of Broilers
Authors: Lan Ruixia , Wang Yuchen , Wang Haoxuan , Zhang Jia
Published: March 2024

This study investigated the effects of dietary chitosan oligosaccharide (COS) supplementation on meat quality, antioxidant capacity, and muscle fiber characteristics in the thigh muscle of broilers. The results showed that dietary COS supplementation decreased shear force and increased crude protein content and nutritional value in the thigh muscle, while decreasing the content of C16:0, C18:0, and total saturated fatty acids. Dietary COS supplementation increased free radical scavenging activity, antioxidant enzyme activity, and antioxidant enzyme-related gene expression. Additionally, COS promoted MyHCI while decreasing MyHCIIb mRNA expression levels. The myofiber transformation was associated with upregulated gene expression of CaN, NFATc1, MyoD, and SIRT1. Together, the results of this study demonstrate that dietary COS supplementation improves meat quality, nutritional value, antioxidant capacity, and myofiber transformation to more oxidative muscle fibers in the thigh muscle of broilers when its supplemental level is 400 mg/kg.
Dynamic Flow and Heat Transfer Characteristics of Uncracked Hydrocarbon Fuel under Super-Critical Pressure in the Cooling Channel of a Regeneratively Cooled Scramjet
Authors: Xu Qing , Lin Guowei , Li Haowei , Feng Yaoxun
Published: March 2024

Regeneratively cooled scramjets are successfully used as propulsion devices in hypersonic vehicles. During operation, scramjets experience acceleration. This special process causes a dynamic flow process, and heat transfer in the cooling channel commonly occurs, which may cause hazards and control difficulties for scramjets. A dynamic numerical model with a modified heat transfer coefficient calculation method was established to study the transient flow and heat transfer processes in a cooling channel. The dynamic characteristics of the flow and heat transfer under different conditions were calculated and are discussed, including the changes in the inlet fuel mass flow, heat flux, and pressure working conditions. The results indicate that the stable time of the cooling channel outlet fuel temperature is related to the rate of change in the inlet mass flow and heat flux. The stable time of the outlet fuel temperature under decreasing heat flux working conditions was approximately 12.5 s. These results summarize the dynamic flow and heat transfer characteristics, which are significant for designing cooling channels in scramjets.
Y-Rank: A Multi-Feature-Based Keyphrase Extraction Method for Short Text
Authors: Liu Qiang , Hui Yan , Liu Shangdong , Ji Yimu
Published: March 2024

Keyphrase extraction is a critical task in text information retrieval, which traditionally employs both supervised and unsupervised approaches. Supervised methods generally rely on large corpora, which introduce the problems of availability, while unsupervised methods are independent of out-sources but also lead to defects like imperfect statistical features or low accuracy. Particularly in short-text scenarios, limited text features often result in low-quality candidate ranking. To address this issue, this paper proposes Y-Rank, a lightweight unsupervised keyphrase extraction method that extracts the average information content of candidate sentences as the key statistical features from a single document, and follows a graph construction approach based on similarity to obtain the semantic features of keyphrase with high-quality and ranking accuracy. Finally, the top-ranked keyphrases are acquired by the fusion of these features. The experimental results on five datasets illustrate that Y-Rank outperforms the other nine unsupervised methods, achieves enhancements on six accuracy metrics, including Precision, Recall, F-Measure, MRR, MAP, and Bpref, and performs the highest improvement in short text scenarios.
An Experimental Study and Numerical Simulation Analysis of Thermal Oxidation Characteristics Based on Kinetic Parameters in Heavy Oil Reservoirs
Authors: Fang Chang , Wang Chao , Zheng Haoran , Liu Peng , Guo Wen , Chen Yajing , He Houfeng , Liu Pengcheng
Published: March 2024

In situ combustion (ISC), an efficient and economical method for enhancing heavy oil recovery in high-pressure, high-viscosity, and thermally challenged reservoirs, relies on the kinetics of crude oil oxidation. Despite an increased focus on kinetic models, there is a gap in understanding how oxidation kinetic parameters impact ISC effectiveness in heavy oil reservoirs. This study addresses this by selecting heavy oil samples from the G Block in the Liaohe oilfield and the M Block in the Huabei oilfield and conducting ramped temperature oxidation (RTO), pressure differential scanning calorimetry (PDSC), and thermogravimetric analysis (TGA) experiments. RTO detailed the thermal conversion process, categorizing oxidation into low-temperature oxidation (LTO), fuel deposition (FD), and high-temperature oxidation (HTO) stages. PDSC and TGA provided thermal characteristics and kinetic parameters. The feasibility of fire flooding was evaluated. Using CMG-STARS, an ISC model was established to analyze the impact of kinetic parameter changes. Activation energy significantly affected coke combustion, while the pre-exponential factor had a notable impact on cracking reactions. The recommended values for activation energy and the pre-exponential factor are provided. This study not only guides fire flooding experiments but also supports field engineering practices, particularly for in situ combustion in heavy oil reservoirs.
Peak Acceleration Distribution on the Surface of Reef Islands under the Action of Vertical Ground Motion
Authors: Jin Liguo , Du Liting , Zhou Zhenghua , Bao Xin
Published: March 2024

This paper adopts the fluid–structure coupling algorithm based on the acoustic fluid element, the fluid dynamic artificial boundary, and the consistent viscoelastic artificial boundary of solid media to establish a finite element model of the dynamic interaction of the reef-island–seawater system. Then, a numerical simulation of the seismic response of the reef-island site is carried out to study the seismic ground motion distribution patterns of the reef–seawater site and the reef-island–lagoon site. The innovation of this article is that the influence of reef–island topography and fluid–structure coupling is considered in the analysis when vertical ground motion is input. The results show that the slope angle of the bottom layer has a significant influence on the peak ground acceleration distribution and peak size on the island slope surface and the reef platform. For high-frequency input motion, a smaller reef platform width will induce a larger peak acceleration response on the reef platform. Seawater has a significant suppressive effect on vertical ground acceleration. The more high-frequency components of the input bedrock motion, the more obvious this suppression effect will be. The existence of the lagoon will amplify the maximum peak acceleration on the reef platform. According to the calculation results, lagoon terrain can amplify the maximum horizontal and vertical peak accelerations on the reef platform by about 19 and 6 times relative to the free-field results, respectively.
Use of Total Least Squares Adjustment in Geodetic Applications
Authors: Marjetič Aleš , Ambrožič Tomaž , Savšek Simona
Published: March 2024

This article discusses the method of computing the values of the unknowns under the condition of the minimum sum of the squares of the residuals of the observations, also known as the least squares method, with the additional condition of taking into account the errors in the unknowns. The problem has already been treated by many authors, especially in the field of regression analysis and the computation of transformation parameters. We give an overview of the theoretical foundations of the least squares method and extensions of this method by considering the errors in the unknowns in the model matrix. So, the total least squares method is presented in this paper, fitting the regression line to a set of points and computing transformation parameters for the transition between the old and the new Slovenian national coordinate systems. Furthermore, for the first time, the method is also presented and tested in the S-transformation between different geodetic datum-dependent solutions. Also, for the first time, we systematically compare the results of the approach with conventional approaches in all three considered tasks. With the results based on relevant statistics, we confirm the suitability of the described method for dealing with the considered computational tasks.
Insights into the Chemistry and Functional Properties of Edible Mushrooms Cropped in the Northeastern Highlands of Puebla, Mexico
Authors: Pacheco-Hernández Yesenia , Lozoya-Gloria Edmundo , Mosso-González Clemente , Varela-Caselis Jenaro Leocadio , Villa-Ruano Nemesio
Published: March 2024

Herein, we present an integrative investigation of the nutritional and nutraceutical potential of Lactarius indigo, Clitocybe nuda, Clitocybe subclavipes, Russula delica, Russula brevipes, Clitocybe squamulosa, and Amanita jacksonii, which are edible mushrooms consumed in the northeastern highlands of Puebla, Mexico. The content of protein oscillated from 4.8 to 10.9 g 100 g−1 fresh weight (FW) whereas that of fiber ranged from 8.8 to 19.7 g 100 g−1 FW. The edible species presented low amounts of fat (1.5–3.4 g 100 g−1 FW) and reducing sugars (0.8–2.9 g 100 g−1 FW), whereas the content of vitamin C oscillated from 6.5 to 84.8 mg 100 g−1 dry weight (DW). In addition, four vitamins of B complex (thiamine, riboflavin, vitamin B6, and folate) were determined in different concentrations. A high abundance of potassium (92.3–294.3 mg 100 g−1 DW), calcium (139.1–446.9 mg 100 g−1 DW), and magnesium (81.3–339.1 mg 100 g−1 DW) was determined in most of the edible mushrooms, as well as detectable levels of p-hydroxybenzoic acid (2.2–48.7 mg 100 g−1 DW), protocatechuic acid (0.5–50.8 mg 100 g−1 DW), oleic acid (14.2–98.3 mg 100 g−1 DW), linoleic acid (748–1549.6 mg 100 g−1 DW), and linolenic acid (from 9.1 to 83.6 mg 100 g−1 DW). The total phenol content and antioxidant capacity significantly (p < 0.05) varied among the studied species, and their capacity to inhibit enzymes involved in glucose, lipid, and polyamine metabolism. Nevertheless, the hydroalcoholic extracts from A. jacksonii and L. indigo efficiently inhibited alpha-glucosidase and ornithine decarboxylase (IC50 < 50 µg mL−1), respectively. The evaluation of the same extracts on microorganisms associated with the gastrointestinal tract showed negligible toxicity on probiotics (MIC > 500 µg mL−1) and moderate toxicity against pathogenic bacteria (MIC < 400 µg mL−1). Based on the studied parameters, principal component analysis and orthogonal partial least squares discriminant analysis clustered these edible mushrooms into two main groups with similar biological or chemical properties.
Predicting Student Performance in Online Learning: A Multidimensional Time-Series Data Analysis Approach
Authors: Shou Zhaoyu , Xie Mingquan , Mo Jianwen , Zhang Huibing
Published: March 2024

As an emerging teaching method, online learning is becoming increasingly popular among learners. However, one of the major drawbacks of this learning style is the lack of effective communication and feedback, which can lead to a higher risk of students failing or dropping out. In response to this challenge, this paper proposes a student performance prediction model based on multidimensional time-series data analysis by considering multidimensional data such as students’ learning behaviors, assessment scores, and demographic information, which is able to extract the characteristics of students’ learning behaviors and capture the connection between multiple characteristics to better explore the impact of multiple factors on students’ performance. The model proposed in this paper helps teachers to individualize education for students at different levels of proficiency and identifies at-risk students as early as possible to help teachers intervene in a timely manner. In experiments on the Open University Learning Analytics Dataset (OULAD), the model achieved 74% accuracy and 73% F1 scores in a four-category prediction task and was able to achieve 99.08% accuracy and 99.08% F1 scores in an early risk prediction task. Compared with the benchmark model, both the multi-classification prediction ability and the early prediction ability, the model in this paper has a better performance.
Stable Heteroclinic Channel-Based Movement Primitives: Tuning Trajectories Using Saddle Parameters
Authors: Rouse Natasha , Daltorio Kathryn
Published: March 2024

Dynamic systems which underlie controlled systems are expected to increase in complexity as robots, devices, and connected networks become more intelligent. While classical stable systems converge to a stable point (a sink), another type of stability is to consider a stable path rather than a single point. Such stable paths can be made of saddle points that draw in trajectories from certain regions, and then push the trajectory toward the next saddle point. These chains of saddles are called stable heteroclinic channels (SHCs) and can be used in robotic control to represent time sequences. While we have previously shown that each saddle is visualizable as a trajectory waypoint in phase space, how to increase the fidelity of the trajectory was unclear. In this paper, we hypothesized that the waypoints can be individually modified to locally vary fidelity. Specifically, we expected that increasing the saddle value (ratio of saddle eigenvalues) causes the trajectory to slow to more closely approach a particular saddle. Combined with other parameters that control speed and magnitude, a system expressed with an SHC can be modified locally, point by point, without disrupting the rest of the path, supporting their use in motion primitives. While some combinations can enable a trajectory to better reach into corners, other combinations can rotate, distort, and round the trajectory surrounding the modified saddle. Of the system parameters, the saddle value provides the most predictable tunability across 3 orders of magnitude.
High-Sensitivity Polarization Sensitive Optical Coherence Tomography Based on Numerical Correction for Perfect Circularly Polarized Light
Authors: Li Sifan , Hu Lantian , Cao Jing
Published: March 2024

Polarization sensitive optical coherence tomography (PSOCT) makes use of the birefringence information of the sample to compensate for the lack of internal tissue-specific contrast in conventional optical coherence tomography (OCT). Circularly polarized light is always used as an incident beam in PSOCT, but it is difficult to have perfect in practice. The manual calibration method of circularly polarized light suffers from the problems of complicated calibration operation and lack of stability. This study proposes a simple method to enhance the imaging of PSOCT without altering the system. A numerical calibration of circularly polarized light can be implemented using the original system setup, ensuring that the system’s complexity remains unchanged. Enhancements in imaging quality can be achieved through an algorithmic analysis of the captured interference fringe data. This calibration is applied in the field map of interference data before being quadrature-assembled. Notably, the proposed approach achieves high sensitivity in PSOCT. The birefringence image shows a more obvious layered structure. Improvements in the signal-to-noise ratio (SNR) were demonstrated for chicken breast, pork, and beef imaging at about 20 dB.
Design and Numerical Study of Induction-Heating Graphitization Furnace Based on Graphene Coils
Authors: Li Rui , Zhang Yuanyuan , Chu Xiaodong , Gan Lin , Li Jia , Li Baohua , Du Hongda
Published: March 2024

Induction-heating graphitization furnaces are widely used to produce high-purity graphite products due to their high heating rate, high-limit temperatures, safety, cleanliness, and precise control. However, the existing induction-heating systems based on copper coils have limited energy efficiency. This paper proposes a new induction-heating graphitization furnace based on graphene coils. Due to the excellent high-temperature resistance of the macroscopic graphene material, the coil can be placed closer to the graphite heater, which improves the electromagnetic efficiency; the coil itself does not need to pass cooling water, which reduces the heat loss of the furnace and ultimately results in a higher energy efficiency of the induction furnace. In this paper, a numerical model of the induction-heating process is established and verified, the temperature-field and electromagnetic-field distributions of the heating process are analyzed by using the model, and the energy balance calculations are performed for the original furnace and the new furnace. Through a comparison, it was found that the new furnace possesses an electromagnetic efficiency of 84.87% and a thermal efficiency of 20.82%, and it can reduce the energy consumption by 33.34%, compared with the original furnace. In addition, the influence of the coil parameters on the performance of the induction furnace is discussed. By changing the coil conductivity, the induction furnace can achieve an energy efficiency of 17.76%–18.11%. This study provides new ideas for the application of macroscopic graphene materials in high-temperature induction heating.
The Influence of Copper Oxide Particle Size on the Properties of Epoxy Resin
Authors: Bazan Patrycja , Gajda Michał , Nosal Przemysław , Bąk Agnieszka , Setlak Kinga , Łach Michał
Published: March 2024

This study examines the relationship between the size of copper particles and the properties of epoxy resin. Epoxy resin is a type of thermosetting resin commonly used as a matrix in polymer matrix composite materials reinforced with glass or carbon fibers. As part of this study, three microscale and two nanoscale composite samples modified with copper oxide particles of varying sizes were produced. This study included mechanical property tests such as static tensile tests, static bending tests, and impact tests. The results of the strength tests were compared to modeling results. Additionally, an accelerated thermal aging process was conducted to determine the impact of external conditions on the behavior of the produced composites. This study concluded with an analysis of thermal conductivity. The test results revealed that the size of the copper particles significantly impacted the tested properties. The composites with copper oxide particles on the nanoscale demonstrated the best results. These composites have promising applications in the automotive and aviation industries due to their strength, resistance to external factors, and increased thermal conductivity, suggesting their potential for producing materials that effectively dissipate heat.
Study on Water Inrush Characteristics of Hard Rock Tunnel Crossing Heterogeneous Faults
Authors: Xin Guoxu , Wang Bo , Zheng Haozhang , Zeng Linfeng , Yang Xinxin
Published: March 2024

Fault water inflow is one of the most severe disasters that can occur during the construction of hard and brittle rock tunnels. These tunnels traverse brittle fault breccia zones comprising two key components: a damage zone dominated by low-strain fractures and an internally nested high-strain zone known as the fault core. Structural heterogeneity influences the mechanical and hydraulic properties within fault breccia zones, thereby affecting the evolving characteristics of water inflow in hard rock faulting. Based on the hydraulic characteristics within hard rock fault zones, this paper presents a generalized dual-porosity fluid-solid coupling water inflow model. The model is utilized to investigate the spatiotemporal evolution patterns of water pressure, inflow velocity, and water volume during tunneling through heterogeneous fault zones in hard rock. Research findings indicate that when tunnels pass through the damage zones, water inrush velocity is high, yet the water volume is low, and both decrease rapidly over time. Conversely, within the core regions of faults, water inflow velocity is low, yet the water volume is high, and both remain relatively stable over time. Simulation results closely align with the water inflow data from China’s largest cross-section tunnel, the Tiantai Mountain Tunnel, thus validating the accuracy of the evolutionary model proposed in this paper. These findings offer a new perspective for devising effective prevention strategies for water inflow from heterogeneous faults.
Experimental Investigation on the Effect of Water Cooling on a Dry Twin-Screw Air Compressor for Proton Exchange Membrane Fuel Cells
Authors: Liu Mingkun , Wang Chuang , Li Yanpeng , Li Yuchen , Liu Lixin , Xing Ziwen
Published: March 2024

Due to the lack of oil injection cooling, it is usually necessary for dry twin-screw compressors to design cooling jackets to carry away the heat generated during operation. In order to investigate to what extent a cooling jacket can improve the performance of screw compressors, this study set up an experimental platform for a dry twin-screw compressor applied in fuel cell vehicles and used water as the working liquid in the cooling jacket. Then, the performance parameters of the screw compressor under different rotating speeds, discharge pressures, and cooling water flow rates were measured. It can be considered that the existence of a water cooling jacket is of great significance for improving the performance of dry screw compressors and improving extreme operating conditions. The research results may provide a reference for the development and improvement of dry twin-screw compressors in the future.
Analysis of the Influence of Antenna Arrangement Parameters on the Aerodynamic Performance of Telecommunication Towers
Authors: Jia Yaya , Huang Jiachen , Liu Qingkuan , Zhao Zonghan , Dong Menghui
Published: March 2024

With the widespread adoption of 5G telecommunication networks, to reduce construction costs, it has become necessary to add new equipment or antennas to existing 4G and 3G telecommunication towers. This significantly changes the original aerodynamic shape of the towers, leading to a substantial increase in the wind load, which may exceed the original structure’s bearing capacity and pose a threat to the structure’s safety. This study employed three-dimensional numerical simulation methods to systematically investigate the impact of various antenna arrangement parameters, such as the arrangement number, arrangement form, and arrangement layers, on the wind load characteristics of telecommunication towers. The findings revealed that the antenna arrangement form significantly affects the sensitivity of the telecommunication tower’s wind load to the wind direction, with more uniform antenna arrangements resulting in less sensitivity. Compared to the drag coefficient and the windward base overturning moment coefficient, the tower’s lateral force coefficient and the crosswind base overturning moment coefficient are more sensitive to changes in the wind direction. The change patterns in the tower’s overturning force coefficient and overturning moment coefficient with the antenna arrangement number are essentially the same. However, as the antenna arrangement number increases, the growth rate of the tower’s overturning moment coefficient is about twice that of the overturning force coefficient. The tower’s overturning force coefficient increases approximately linearly with the increase in antenna arrangement layers, while the tower’s overturning moment coefficient exhibits a nonlinear increase with the increase in antenna arrangement layers. The rate of increase in the wind load with the antenna arrangement layers is significantly greater than that with the antenna arrangement number. Thus, to reduce wind load, it is advisable in practical engineering applications to increase the antenna arrangement number per layer, thereby reducing the antenna arrangement layers. The study also summarized a calculation method for the structural wind load of telecommunication towers, taking into account the influence of antenna arrangement parameters, providing a reliable basis for the structural design and safety assessment of telecommunication towers in practical engineering.
Automated Generation and Internal Force Visualization for Box Culvert Based on Building Information Modeling
Authors: Wang Dejiang , Huang Jiangming
Published: March 2024

Box culverts, as a commonly employed structural form for culverts, play a critical role in traversing topographic barriers, ensuring the safety and smooth operation of transportation means such as roads and railways. However, traditional design methodologies are often time-consuming and prone to inaccuracies, failing to achieve the efficiency and precision required by modern engineering construction. To address these challenges, using the Revit 2021 and Midas Civil 2021 software platforms, we developed a Building Information Modeling (BIM) parametric modeling method for box culverts using Dynamo’s visual programming capabilities. This method enables the rapid and accurate automated generation of box culvert BIM models. Furthermore, this study proposes an effective strategy for conversion between box culvert BIM models and Midas Civil finite element models, as well as internal force visualization within a BIM project. A case study involving a box culvert underpass beneath an expressway in an urban setting was modeled parametrically and structurally validated, demonstrating that the approach not only significantly enhances modeling efficiency but also strengthens computational capabilities through bidirectional data exchange between BIM and Finite Element Analysis (FEA) software. This research has effectively advanced the application and practical implementation of BIM technology in box culvert engineering.
Additive Manufacturing for Surgical Planning and Education: A Review
Authors: Kantaros Antreas , Petrescu Florian , Abdoli Hamed , Diegel Olaf , Chan Simon , Iliescu Mihaiela , Ganetsos Theodore , Munteanu Iulian , Ungureanu Liviu
Published: March 2024

Additive manufacturing has been widely used in various industries, including the healthcare sector. Over the last few decades, AM has been playing an important role in the medical field in different areas, including surgical planning, implants, and educational activities. For surgical applications, AM can help surgeons practice and plan an operation until they are confident with the process. This can help to reduce operational risk and time. In addition, it can help to demonstrate the problem to other colleagues. AM has also been used to produce 3D models to teach students and doctors about human anatomy. This paper aims to comprehensively review the diverse applications of additive manufacturing within the domains of surgical planning and medical education. By focusing on the multifaceted roles played by AM in these critical areas, a contribution to the growing body of knowledge that underscores the transformative potential of this technology in shaping the future of healthcare practices is sought to be made.
Predicting Road Traffic Collisions Using a Two-Layer Ensemble Machine Learning Algorithm
Authors: Oyoo James Oduor , Wekesa Jael Sanyanda , Ogada Kennedy Odhiambo
Published: March 2024

Road traffic collisions are among the world’s critical issues, causing many casualties, deaths, and economic losses, with a disproportionate burden falling on developing countries. Existing research has been conducted to analyze this situation using different approaches and techniques at different stretches and intersections. In this paper, we propose a two-layer ensemble machine learning (ML) technique to assess and predict road traffic collisions using data from a driving simulator. The first (base) layer integrates supervised learning techniques, namely k- Nearest Neighbors (k-NN), AdaBoost, Naive Bayes (NB), and Decision Trees (DT). The second layer predicts road collisions by combining the base layer outputs by employing the stacking ensemble method, using logistic regression as a meta-classifier. In addition, the synthetic minority oversampling technique (SMOTE) was performed to handle the data imbalance before training the model. To simplify the model, the particle swarm optimization (PSO) algorithm was used to select the most important features in our dataset. The proposed two-layer ensemble model had the best outcomes with an accuracy of 88%, an F1 score of 83%, and an AUC of 86% as compared with k-NN, DT, NB, and AdaBoost. The proposed two-layer ensemble model can be used in the future for theoretical as well as practical applications, such as road safety management for improving existing conditions of the road network and formulating traffic safety policies based on evidence.
Investigating Nonlinear Dynamics in Atmospheric Aerosols during the Transition from Laminar to Turbulent Flow
Authors: Cazacu Marius Mihai , Roșu Alin Iulian , Ababei Razvan Vasile , Roșu Adrian , Vasincu Decebal , Nica Dragoș Constantin , Rusu Oana , Bruma Andreea Bianca , Agop Maricel
Published: March 2024

This paper investigates the nonlinear dynamics of atmospheric aerosols during the transition from laminar to turbulent flows using the framework of Scale Relativity Theory. It is proposed that the transition from multifractal to non-multifractal scales (in the dynamics of the atmospheric aerosols) can be assimilated to the transition between laminar and turbulent states. These transitions are determined by the multifractal diffusion and deposition processes. The methodology used involves the application of the principle of scale covariance, which states that the laws of atmospheric physics remain invariant with respect to spatial and temporal transformations as well as scale transformations. Based on this principle, several conservation laws are constructed. In such context, the conservation law of the density of states associated with the multifractal-non-multifractal scale transition in a one-dimensional case is then considered. The model describes the non-linear behaviour of atmospheric aerosols undergoing diffusion and deposition processes. The theoretical approach was correlated using experimental data from a ceilometer and radar reflectivity factor data.
The Variation in Atmospheric Turbidity over a Tropical Site in Nigeria and Its Relation to Climate Drivers
Authors: SoneyeArogundade Olanrewaju Olukemi , Rappenglück Bernhard
Published: March 2024

Atmospheric turbidity exhibits substantial spatial–temporal variability due to factors such as aerosol emissions, seasonal changes, meteorology, and air mass transport. Investigating atmospheric turbidity is crucial for climatology, meteorology, and atmospheric pollution. This study investigates the variation in atmospheric turbidity over a tropical location in Nigeria, utilizing the Ångström exponent (α), the turbidity coefficient (β), the Linke turbidity factor (TL), the Ångström turbidity coefficient (βEST), the Unsworth–Monteith turbidity coefficient (KAUM), and the Schüepp turbidity coefficient (SCH). These parameters were estimated from a six-month uninterrupted aerosol optical depth dataset (January–June 2016) and a one-year dataset (January–December 2016) of solar radiation and meteorological data. An inverse correlation (R = −0.77) was obtained between α and β, which indicates different turbidity regimes based on particle size. TL and βEST exhibit pronounced seasonality, with higher turbidity during the dry season (TL = 9.62 and βEST = 0.60) compared to the rainy season (TL = 0.48 and βEST = 0.20) from May to October. Backward trajectories and wind patterns reveal that high-turbidity months align with north-easterly air flows from the Sahara Desert, transporting dust aerosols, while low-turbidity months coincide with humid maritime air masses originating from the Gulf of Guinea. Meteorological drivers like relative humidity and water vapor pressure are linked to turbidity levels, with an inverse exponential relationship observed between normalized turbidity coefficients and normalized water vapor pressure. This analysis provides insights into how air mass origin, wind patterns, and local climate factors impact atmospheric haze, particle characteristics, and solar attenuation variability in a tropical location across seasons. The findings can contribute to environmental studies and assist in modelling interactions between climate, weather, and atmospheric optical properties in the region.
Chance-Constrained Optimization for a Green Multimodal Routing Problem with Soft Time Window under Twofold Uncertainty
Authors: Li Xinya , Sun Yan , Qi Jinfeng , Wang Danzhu
Published: March 2024

This study investigates a green multimodal routing problem with soft time window. The objective of routing is to minimize the total costs of accomplishing the multimodal transportation of a batch of goods. To improve the feasibility of optimization, this study formulates the routing problem in an uncertain environment where the capacities and carbon emission factors of the travel process and the transfer process in the multimodal network are considered fuzzy. Taking triangular fuzzy numbers to describe the uncertainty, this study proposes a fuzzy nonlinear programming model to deal with the specific routing problem. To make the problem solvable, this study adopts the fuzzy chance-constrained programming approach based on the possibility measure to remove the fuzziness of the proposed model. Furthermore, we use linear inequality constraints to reformulate the nonlinear equality constraints represented by the continuous piecewise linear functions and realize the linearization of the nonlinear programming model to improve the computational efficiency of problem solving. After model processing, we can utilize mathematical programming software to run exact solution algorithms to solve the specific routing problem. A numerical experiment is given to show the feasibility of the proposed model. The sensitivity analysis of the numerical experiment further clarifies how improving the confidence level of the chance constraints to enhance the possibility that the multimodal route planned in advance satisfies the real-time capacity constraint in the actual transportation, i.e., the reliability of the routing, increases both the total costs and carbon emissions of the route. The numerical experiment also finds that charging carbon emissions is not absolutely effective in emission reduction. In this condition, bi-objective analysis indicates the conflicting relationship between lowering transportation activity costs and reducing carbon emissions in routing optimization. The sensitivity of the Pareto solutions concerning the confidence level reveals that reliability, economy, and environmental sustainability are in conflict with each other. Based on the findings of this study, the customer and the multimodal transport operator can organize efficient multimodal transportation, balancing the above objectives using the proposed model.
Design and Development of Flow Fields with Multiple Inlets or Outlets in Vanadium Redox Flow Batteries
Authors: Cecchetti Marco , Messaggi Mirko , Casalegno Andrea , Zago Matteo
Published: March 2024

In vanadium redox flow batteries, the flow field geometry plays a dramatic role on the distribution of the electrolyte and its design results from the trade-off between high battery performance and low pressure drops. In the literature, it was demonstrated that electrolyte permeation through the porous electrode is mainly regulated by pressure difference between adjacent channels, leading to the presence of under-the-rib fluxes. With the support of a 3D computational fluid dynamic model, this work presents two novel flow field geometries that are designed to tune the direction of the pressure gradients between channels in order to promote the under-the-rib fluxes mechanism. The first geometry is named Two Outlets and exploits the splitting of the electrolyte flow into two adjacent interdigitated layouts with the aim to give to the pressure gradient a more transverse direction with respect to the channels, raising the intensity of under-the-rib fluxes and making their distribution more uniform throughout the electrode area. The second geometry is named Four Inlets and presents four inlets located at the corners of the distributor, with an interdigitated-like layout radially oriented from each inlet to one single central outlet, with the concept of reducing the heterogeneity of the flow velocity within the electrode. Subsequently, flow fields performance is verified experimentally adopting a segmented hardware in symmetric cell configuration with positive electrolyte, which permits the measurement of local current distribution and local electrochemical impedance spectroscopy. Compared to a conventional interdigitated geometry, both the developed configurations permit a significant decrease in the pressure drops without any reduction in battery performance. In the Four Inlets flow field the pressure drop reduction is more evident (up to 50%) due to the lower electrolyte velocities in the feeding channels, while the Two Outlets configuration guarantees a more homogeneous current density distribution.
A Review of 3D Printing Batteries
Authors: Mottaghi Maryam , Pearce Joshua M.
Published: March 2024

To stabilize the Earth’s climate, large-scale transition is needed to non-carbon-emitting renewable energy technologies like wind and solar energy. Although these renewable energy sources are now lower-cost than fossil fuels, their inherent intermittency makes them unable to supply a constant load without storage. To address these challenges, rechargeable electric batteries are currently the most promising option; however, their high capital costs limit current deployment velocities. To both reduce the cost as well as improve performance, 3D printing technology has emerged as a promising solution. This literature review provides state-of-the-art enhancements of battery properties with 3D printing, including efficiency, mechanical stability, energy and power density, customizability and sizing, production process efficiency, material conservation, and environmental sustainability as well as the progress in solid-state batteries. The principles, advantages, limitations, and recent advancements associated with the most common types of 3D printing are reviewed focusing on their contributions to the battery field. 3D printing battery components as well as full batteries offer design flexibility, geometric freedom, and material flexibility, reduce pack weight, minimize material waste, increase the range of applications, and have the potential to reduce costs. As 3D printing technologies become more accessible, the prospect of cost-effective production for customized batteries is extremely promising.
Advances in Biological Wastewater Treatment Processes: Focus on Low-Carbon Energy and Resource Recovery in Biorefinery Context
Authors: Sravan J. Shanthi , Matsakas Leonidas , Sarkar Omprakash
Published: March 2024

Advancements in biological wastewater treatment with sustainable and circularity approaches have a wide scope of application. Biological wastewater treatment is widely used to remove/recover organic pollutants and nutrients from a diverse wastewater spectrum. However, conventional biological processes face challenges, such as low efficiency, high energy consumption, and the generation of excess sludge. To overcome these limitations, integrated strategies that combine biological treatment with other physical, chemical, or biological methods have been developed and applied in recent years. This review emphasizes the recent advances in integrated strategies for biological wastewater treatment, focusing on their mechanisms, benefits, challenges, and prospects. The review also discusses the potential applications of integrated strategies for diverse wastewater treatment towards green energy and resource recovery, along with low-carbon fuel production. Biological treatment methods, viz., bioremediation, electro-coagulation, electro-flocculation, electro-Fenton, advanced oxidation, electro-oxidation, bioelectrochemical systems, and photo-remediation, are summarized with respect to non-genetically modified metabolic reactions. Different conducting materials (CMs) play a significant role in mass/charge transfer metabolic processes and aid in enhancing fermentation rates. Carbon, metal, and nano-based CMs hybridization in different processes provide favorable conditions to the fermentative biocatalyst and trigger their activity towards overcoming the limitations of the conventional process. The emerging field of nanotechnology provides novel additional opportunities to surmount the constraints of conventional process for enhanced waste remediation and resource valorization. Holistically, integrated strategies are promising alternatives for improving the efficiency and effectiveness of biological wastewater treatment while also contributing to the circular economy and environmental protection.
Biohydrogen Production from Waste Black Cumin (Nigella Sativa) Extract Liquid
Authors: Dursun Nesrin , Gülşen Hakki
Published: March 2024

Hydrogen creates water during combustion. Therefore, it is expected to be the most promising environmentally friendly energy alternative in the coming years. This study used extract liquid obtained from the waste nigella sativa generated by the black cumin oil industry. The performance of biological hydrogen manufacturing via dark fermentation was investigated in the fluidized bed reactor (FBR) and completely stirred tank reactor (CSTR) under the operation conditions of pH 5.0, 4.0, and 6.0 and a hydraulic retention time (HRT) of 36 and 24 h. The performance of hydrogen manufacturing was determined to be good under an organic loading ratio (OLR) of 6.66 g.nigella sativa extract/L and pH 4.0. According to these conditions, the maximum amount of hydrogen in CSTR and FBR was found to be 20.8 and 7.6 mL H2/day, respectively. The operating process of the reactors displayed that a reduction in HRT augmented biohydrogen manufacturing. The work that used mixed culture found that the dominant microbial population at pH 4.0 involved Hydrogenimonas thermophila, Sulfurospirillum carboxydovorans, Sulfurospirillum cavolei, Sulfurospirillum alkalitolerans, and Thiofractor thiocaminus. No research on waste black cumin extract was found in biohydrogen studies, and it was determined that this substrate source is applicable for biological hydrogen manufacturing.
Comparison of Immediate Neuromodulatory Effects between Focal Vibratory and Electrical Sensory Stimulations after Stroke
Authors: Lin Legeng , Qing Wanyi , Huang Yanhuan , Ye Fuqiang , Rong Wei , Li Waiming , Jiao Jiao , Hu Xiaoling
Published: March 2024

Focal vibratory stimulation (FVS) and neuromuscular electrical stimulation (NMES) are promising technologies for sensory rehabilitation after stroke. However, the differences between these techniques in immediate neuromodulatory effects on the poststroke cortex are not yet fully understood. In this research, cortical responses in persons with chronic stroke (n = 15) and unimpaired controls (n = 15) were measured by whole-brain electroencephalography (EEG) when FVS and NMES at different intensities were applied transcutaneously to the forearm muscles. Both FVS and sensory-level NMES induced alpha and beta oscillations in the sensorimotor cortex after stroke, significantly exceeding baseline levels (p < 0.05). These oscillations exhibited bilateral sensory deficiency, early adaptation, and contralesional compensation compared to the control group. FVS resulted in a significantly faster P300 response (p < 0.05) and higher theta oscillation (p < 0.05) compared to NMES. The beta desynchronization over the contralesional frontal–parietal area remained during NMES (p > 0.05), but it was significantly weakened during FVS (p < 0.05) after stroke. The results indicated that both FVS and NMES effectively activated the sensorimotor cortex after stroke. However, FVS was particularly effective in eliciting transient involuntary attention, while NMES primarily fostered the cortical responses of the targeted muscles in the contralesional motor cortex.
Immunologic Aspects in Fibrodysplasia Ossificans Progressiva
Authors: Diolintzi Anastasia , Pervin Mst Shaela , Hsiao Edward C.
Published: March 2024

Background: Inflammation is a major driver of heterotopic ossification (HO), a condition of abnormal bone growth in a site that is not normally mineralized. Purpose of review: This review will examine recent findings on the roles of inflammation and the immune system in fibrodysplasia ossificans progressiva (FOP). FOP is a genetic condition of aggressive and progressive HO formation. We also examine how inflammation may be a valuable target for the treatment of HO. Rationale/Recent findings: Multiple lines of evidence indicate a key role for the immune system in driving FOP pathogenesis. Critical cell types include macrophages, mast cells, and adaptive immune cells, working through hypoxia signaling pathways, stem cell differentiation signaling pathways, vascular regulatory pathways, and inflammatory cytokines. In addition, recent clinical reports suggest a potential role for immune modulators in the management of FOP. Future perspectives: The central role of inflammatory mediators in HO suggests that the immune system may be a common target for blocking HO in both FOP and non-genetic forms of HO. Future research focusing on the identification of novel inflammatory targets will help support the testing of potential therapies for FOP and other related conditions.