bluuebunny/crossref_metadata_2025 huggingface dataset:
Embedded Graphite and Carbon Nanofibers in a Polyurethane Matrix Used as Anodes in Microbial Fuel Cells for Wastewater Treatment
Authors: Pérez-Rodríguez Pedro , Covarrubias-Gordillo Carlos A. , Rodríguez-De la Garza José A. , Barrera-Martínez Cynthia L. , Martínez-Amador Silvia Y.
Published: October 2023

Composites of polyurethane and graphite and polyurethane and carbon nanofibers (PU/Graphite 0.5% and PU/CNF 1%) were synthesized and used as anodes in dual-compartment microbial fuel cells (MFCs) for municipal wastewater treatment; electrical energy generation and organic matter removal were assessed. The maximum power density, coulombic efficiency and chemical oxygen demand (COD) removal efficiency in the MFCs packed with the PU/Graphite 0.5% and PU/CNF 1% composites were 232.32 mW/m3 and 90.78 mW/m3, 5.87 and 4.41%, and 51.38 and 68.62%, respectively. In addition, the internal resistance of the MFCs with the best bioelectrochemical performance (PU/Graphite 0.5%) was 1051.11 Ω. The results obtained in this study demonstrate the feasibility of using these types of materials in dual-compartment MFCs for wastewater treatment with electric power generation.
Damage Evolution of Polypropylene–Basalt Hybrid Fiber Ceramsite Concrete under Chloride Erosion and Dry–Wet Cycle
Authors: Zhu Hongbing , Wen Siyu , Li Xiu , Li Yahan , Fu Zhenghao
Published: October 2023

To investigate the influence of polypropylene–basalt hybrid fibers (PBHFCC) on the durability of ceramsite concrete, this study determined the appearance change, mass loss rate, relative dynamic elastic modulus, compressive strength and splitting tensile strength of ceramsite concrete with four kinds of hybrid fibers volume admixture under chloride erosion and dry–wet cycles. The results reveal that under this effect, the apparent damage of each group of specimens increased with the growth of the erosion time. The quality, compressive strength and splitting tensile strength of the specimens all increased gradually during the erosion age period of the first 72 d and gradually decreased after 72 d. The relative dynamic elastic modulus was similarly mutated in 48 d. When the hybrid fiber content of the specimens is 0.15 vol %, the enhancement effect of ceramsite concrete is better than that of the other three amounts. The relative dynamic elastic modulus value is used as a damage variable to establish the damage equation, and the damage evolution equation of PBHFCC considering the volume of hybrid fiber under chloride erosion and dry–wet cycle is derived. The conclusions can be used as a reference for the durability design and construction of PBHFCC.
Characterization of Artificial Stone Produced with Blast Furnace Dust Waste Incorporated into a Mixture of Epoxy Resin and Cashew Nut Shell Oil
Authors: Perim Tatiane Brito , Carvalho Elaine , Barreto Gabriela , da Cruz Silva Thaís Leal , Monteiro Sérgio Neves , Azevedo Afonso Rangel Garcez de , Vieira Carlos Maurício Fontes
Published: October 2023

The demand for materials with improved properties and less negative impact on the environment is growing. Artificial stones are examples of these materials produced with up to 90% of particulate material joined by a binder. This article evaluates the physical and mechanical properties of two artificial stones produced with processing steel residue (blast furnace dust waste) and quartz powder. Two binders were used: pure epoxy resin, denoted as ASPB100, or a mixture of 70 wt% epoxy resin with 30 wt% cashew nut shell oil, denoted as ASPB7030. The process took place under vibration, compression (3 MPa/20 min and 90 °C) and vacuum (80 Pa). ASPB100 showed water absorption of 0.07%, while for ASPB7030, it was 0.54%. They were classified as having high mechanical strength associated with bending stress values equal to 32 and 25 MPa, respectively. Stain resistance indicated that both artificial stones had their stains removed with the tested cleaning agents. In this way, the novel artificial stones produced are sustainable alternatives for the application of blast furnace waste and cashew nut shell oil, reducing their negative impacts on the environment.
Study of Damage Prediction of Carbon Fiber Tows Using Eddy Current Measurement
Authors: Roh Jeong U , Kwon Hyein , Lee Sangjin , Ha Jae Chung , Yang Seong Baek , Lee Haeseong , Kwon Dong-Jun
Published: October 2023

When manufacturing fiber-reinforced composites, it is possible to improve the quality of fiber steel fire and reduce the number of cracks in the finished product if it is possible to quickly identify the defects of the fiber tow. Therefore, in this study, we developed a method to identify the condition of carbon fiber tow using eddy current test (ECT), which is used to improve the quality of composite materials. Using the eddy current detection sensor, we checked the impedance results according to the condition of the CF tow. We found that the materials of the workbench used in the experiment greatly affected the ECT results, so it is necessary to use a material with a non-conductive and smooth surface. We evaluated the impedance results of the carbon fiber at 2 mm intervals using the ECT sensor and summarized the impedance results according to the fiber width direction, presenting the condition of the section as a constant of variation (CV). If the condition of the carbon fiber tow was unstable, the deviation of the CV per section was large. In particular, the deviation of the CV per section was more than 0.15 when the arrangement of the fibers was changed, foreign substances were formed on the surface of the fibers, and damage occurred in the direction of the fiber width of more than 4 mm, so it was easy to evaluate the quality on CF tow.
Eco-Friendly Natural Rubber–Jute Composites for the Footwear Industry
Authors: Torres Giovanni Barrera , Hiranobe Carlos T. , da Silva Erivaldo Antonio , Cardim Guilherme P. , Cardim Henrique P. , Cabrera Flavio C. , Lozada Elizabeth R. , Gutierrez-Aguilar Carlos M. , Sánchez Juan C. , Carvalho Jaime A. Jaramillo , Job Aldo E. , Santos Renivaldo J.
Published: October 2023

Nowadays, biocomposites represent a new generation of materials that are environmentally friendly, cost-effective, low-density, and not derived from petroleum. They have been widely used to protect the environment and generate new alternatives in the polymer industry. In this study, we incorporated untreated jute fibers (UJFs) and alkaline-treated jute fibers (TJFs) at 1–5 and 10 phr into TSR 10 natural rubber as reinforcement fillers. These composites were produced to be used in countersole shoes manufacturing. Untreated fibers were compared to those treated with 10% sodium hydroxide. The alkali treatment allowed the incorporation of fibers without compromising their mechanical properties. The TJF samples exhibited 8% less hardness, 70% more tensile strength, and the same flexibility compared to their pure rubber counterparts. Thanks to their properties and ergonomic appearance, the composites obtained here can be useful in many applications: construction materials (sound insulating boards, and flooring materials), the automotive industry (interior moldings), the footwear industry (shoe soles), and anti-static moldings. These new compounds can be employed in innovative processes to reduce their carbon footprint and negative impact on our planet. Using the Lorenz–Park equation, the loaded composites examined in this study exhibited values above 0.7, which means a competitive load–rubber interaction. Scanning electron microscopy (SEM) was used to investigate the morphology of the composites in detail.
Kinetic Modeling of Cornstalk Cellulose Hydrolysis in Supercritical Water: A Comparative Study of the Effects of Temperature and Residence Time on Derivative Production
Authors: Ashfaq Muhammad Muzamal , Zholobko Oksana , Wu Xiang-Fa
Published: October 2023

Kinetic modeling is essential in understanding and controlling the process of cellulose hydrolysis for producing value-added cellulose derivatives. This study aims to adopt a set of dominate kinetic ordinary differential equations of cornstalk cellulose hydrolysis in supercritical water for mechanism-based prediction of the production of cellulose, glucose, fructose, glyceraldehyde, erythrose, 5-hydroxymethyl furfural, glycolaldehyde, threose, aldose, and other cellulose derivatives from cornstalks under processing conditions with a pressure of 89 MPa and a temperature of 378 °C, as considered in a recent experimental study in the literature. The yield rates of several cellulose derivatives, e.g., glucose, fructose, 5-HMF, and erythrose as predicted by the present model, are close to those of experimental measurements. The model is further used to predict the yield rates of a few new cellulose derivatives, e.g., glycolaldehyde, threose, and aldose, that are potentially generated in cornstalk cellulose hydrolysis in supercritical water. The present model and computational simulations can be utilized as a rational tool to predict, control, and optimize the derivative yields in cellulose hydrolysis in supercritical water via tuning the process parameters, and, therefore, are useful for the optimal production of targeted bio-based fuels and chemicals from cornstalks and other agricultural and municipal wastes.
Production Waste Management: Qualitative and Quantitative Characteristics and the Calculation of the Hazard Class of Phosphogypsum
Authors: Seraya Natalya , Litvinov Vadim , Daumova Gulzhan , Zhusipov Nursultan , Idrisheva Zhanat , Aubakirova Roza
Published: October 2023

Phosphogypsum (PG: CaSO4·2H2O) is a waste product (or by-product) from the production of phosphoric acid, the main component in the production of concentrated simple and complex fertilizers. The world production of phosphogypsum exceeds 200 million tons per year. PG discharged into water bodies (seas, rivers) or disposed of in land dumps may contain elements (including heavy metals and radionuclides) in forms and concentrations that are toxic to ecosystems and human health, which raises concerns about its impact on the environment. The concentrations of these elements vary depending on the region where the raw material is mined and the process used to produce phosphoric acid. Given the significant volumes of phosphogypsum formed, an urgent problem is not only the development of methods for its disposal, but also a special, specific control over its composition after the release of PG and during its use for removal, transportation, and storage in dumps and sludge storages. This article presents the results of comprehensive studies on the determination of the chemical and mineralogical composition of by-products from an experimental plant for the processing of phosphate raw materials of the designed chemical complex of the EuroChem-Karatau company (Republic of Kazakhstan). Based on the conducted studies, it was established that, in terms of the total toxicity index, the studied wastes belong to the fourth hazard class (low-hazardous) with the possibility of processing for the purpose of their further use.
Spatio-Temporal Variation in Soil Salinity and Its Influencing Factors in Desert Natural Protected Forest Areas
Authors: Zhao Xinyue , Xi Haiyang , Yu Tengfei , Cheng Wenju , Chen Yuqing
Published: October 2023

Soil salinity is a crucial parameter affecting soil health. Excessive surface salt accumulation degrades soil structure, inhibits vegetation growth, and diminishes plant diversity. Such increases in salinity can accelerate desertification, leading to soil resource loss, hampering agricultural progress, and compromising ecological security. However, the vastness of arid regions and data acquisition challenges often hinder efficient SSC monitoring and modeling. In this study, we leveraged remote sensing data coupled with machine learning techniques to investigate the spatio-temporal dynamics of SSC in a representative desert natural forest area, the Alxa National Public Welfare Forest. Utilizing the geodetector model, we also delved into the factors influencing SSC. Our results underscored the effectiveness of the Convolutional Neural Networks (CNN) model in predicting SSC, achieving an accuracy of 0.745. Based on this model, we mapped the spatial distribution of SSC, revealing hydrothermal conditions as pivotal determinants of salt accumulation. From 2016 to 2021, soils impacted by salinity in the research area exhibited a rising trend, attributed to the prevailing dry climate and low precipitation. Such intensified salinity accumulation poses threats to the healthy growth of protective forest vegetation. This study can provide a theoretical reference for salinization management and ecological protection in desert natural forest areas.
GFCNet: Contrastive Learning Network with Geography Feature Space Joint Negative Sample Correction for Land Cover Classification
Authors: Zhang Zhaoyang , Jing Wenxuan , Li Haifeng , Tao Chao , Zhang Yunsheng
Published: October 2023

With the continuous improvement in the volume and spatial resolution of remote sensing images, the self-supervised contrastive learning paradigm driven by a large amount of unlabeled data is expected to be a promising solution for large-scale land cover classification with limited labeled data. However, due to the richness and scale diversity of ground objects contained in remote sensing images, self-supervised contrastive learning encounters two challenges when performing large-scale land cover classification: (1) Self-supervised contrastive learning models treat random spatial–spectral transformations of different images as negative samples, even though they may contain the same ground objects, which leads to serious class confusion in land cover classification. (2) The existing self-supervised contrastive learning models simply use the single-scale features extracted by the feature extractor for land cover classification, which limits the ability of the model to capture different scales of ground objects in remote sensing images. In this study, we propose a contrastive learning network with Geography Feature space joint negative sample Correction (GFCNet) for land cover classification. To address class confusion, we propose a Geography Feature space joint negative sample Correction Strategy (GFCS), which integrates the geography space and feature space relationships of different images to construct negative samples, reducing the risk of negative samples containing the same ground object. In order to improve the ability of the model to capture the features of different scale ground objects, we adopt a Multi-scale Feature joint Fine-tuning Strategy (MFFS) to integrate different scale features obtained by the self-supervised contrastive learning network for land cover classification tasks. We evaluate the proposed GFCNet on three public land cover classification datasets and achieve the best results compared to seven baselines of self-supervised contrastive learning methods. Specifically, on the LoveDA Rural dataset, the proposed GFCNet improves 3.87% in Kappa and 1.54% in mIoU compared with the best baseline.
Identifying Major Diurnal Patterns and Drivers of Surface Urban Heat Island Intensities across Local Climate Zones
Authors: Guan Yongjuan , Quan Jinling , Ma Ting , Cao Shisong , Xu Chengdong , Guo Jiali
Published: October 2023

Deepening the understanding of diurnal characteristics and driving mechanisms of surface urban heat islands (SUHIs) across different local climate zones (LCZs) and time scales is of great significance for guiding urban surface heat mitigation. However, a comprehensive investigation of SUHIs from the diurnal, local, multi-seasonal, and interactive perspectives remains a large gap. Here, we generalized major diurnal patterns of LCZ-based SUHI intensities (SUHIIs) throughout 2020 over the urban area of Beijing, China, based on diurnal temperature cycle modeling, block-level LCZ mapping, and hierarchical clustering. A geographical detector was then employed to explore the individual and interactive impacts of 10 morphological, socioeconomic, and meteorological factors on the multi-temporal spatial differentiations of SUHIIs. Results indicate six prevalent diurnal SUHII patterns with distinct features among built LCZ types. LCZs 4 and 5 (open high- and mid-rise buildings) predominantly display patterns one, two, and five, characterized by an afternoon increase and persistently higher values during the night. Conversely, LCZs 6, 8, and 9 (open, large, and sparsely built low-rise buildings) mainly exhibit patterns three, four, and six, with a decrease in SUHII during the afternoon and lower intensities at night. The maximum/minimum SUHIIs occur in the afternoon–evening/morning for patterns 1–3 but in the morning/afternoon for patterns 5–6. In all four seasons, the enhanced vegetation index (EVI) and gross domestic product (GDP) have the top two individual effects for daytime spatial differentiations of SUHIIs, while the air temperature (TEM) has the largest explanatory power for nighttime differentiations of SUHIIs. All factor interactions are categorized as two-factor or nonlinear enhancements, where nighttime interactions exhibit notably greater explanatory powers than daytime ones. The strongest interactions are EVI ∩ GDP (q = 0.80) during the day and TEM ∩ EVI (q = 0.86) at night. The findings of this study contribute to an improved interpretation of the diurnal continuous dynamics of local SUHIIs in response to various environmental conditions.
Polar Sea Ice Detection Using a Rotating Fan Beam Scatterometer
Authors: Liu Liling , Dong Xiaolong , Lin Wenming , Lang Shuyan
Published: October 2023

Scatterometers are dedicated to monitoring sea surface wind vectors, but they also provide valuable data for polar applications. As a new type of scatterometer, the rotating fan beam scatterometer delivers a higher diversity of incidence angles and more azimuth sampling. The paper takes the first rotating fan beam scatterometer, the China France Oceanography Satellite scatterometer (CSCAT), as an example to explore the effectiveness of this new type of scatterometer in polar sea ice detection. In this paper, a Bayesian method with consideration of geometric characteristics of CSCAT is developed for sea ice detection. The implementation of this method includes the definition of CSCAT backscatter space, an estimation of the sea ice Physical Model Function (GMF), a calculation of the sea ice backscatter distance to the sea ice GMF, a probability distribution function (PDF) estimation of the square distance to the GMF (sea ice GMF and wind GMF), and a calculation of the sea ice Bayesian posterior probability. This algorithm was used to generate a daily CSCAT polar sea ice mask during the CSCAT mission period (2019–2022) (by setting a 55% threshold on the Bayesian posterior probability). The sea ice masks were validated against passive microwaves by quantitatively comparing the sea ice edges and extents. The validation suggests that the CSCAT sea ice edge and extent show good agreement with the sea ice concentration distribution (i.e., sea ice concentration ≥ 15%) of the Advanced Microwave Scanning Radiometer 2 (AMSR2). The average Euclidean distance of the sea ice edges was basically less than 12.5 km, and the deviation of the sea ice extents was less than 0.3 × 106 km2.
A Real-Time Flame Detection Method Using Deformable Object Detection and Time Sequence Analysis
Authors: Zhang Jingyuan , Shi Bo , Chen Bin , Chen Heping , Xu Wangming
Published: October 2023

Timely and accurate flame detection is a very important and practical technology for preventing the occurrence of fire accidents effectively. However, the current methods of flame detection are still faced with many challenges in video surveillance scenarios due to issues such as varying flame shapes, imbalanced samples, and interference from flame-like objects. In this work, a real-time flame detection method based on deformable object detection and time sequence analysis is proposed to address these issues. Firstly, based on the existing single-stage object detection network YOLOv5s, the network structure is improved by introducing deformable convolution to enhance the feature extraction ability for irregularly shaped flames. Secondly, the loss function is improved by using Focal Loss as the classification loss function to solve the problems of the imbalance of positive (flames) and negative (background) samples, as well as the imbalance of easy and hard samples, and by using EIOU Loss as the regression loss function to solve the problems of a slow convergence speed and inaccurate regression position in network training. Finally, a time sequence analysis strategy is adopted to comprehensively analyze the flame detection results of the current frame and historical frames in the surveillance video, alleviating false alarms caused by flame shape changes, flame occlusion, and flame-like interference. The experimental results indicate that the average precision (AP) and the F-Measure index of flame detection using the proposed method reach 93.0% and 89.6%, respectively, both of which are superior to the compared methods, and the detection speed is 24–26 FPS, meeting the real-time requirements of video flame detection.
Diffusion Model for DAS-VSP Data Denoising
Authors: Zhu Donglin , Fu Lei , Kazei Vladimir , Li Weichang
Published: October 2023

Distributed acoustic sensing (DAS) has emerged as a transformational technology for seismic data acquisition. However, noise remains a major impediment, necessitating advanced denoising techniques. This study pioneers the application of diffusion models, a type of generative model, for DAS vertical seismic profile (VSP) data denoising. The diffusion network is trained on a new generated synthetic dataset that accommodates variations in the acquisition parameters. The trained model is applied to suppress noise in synthetic and field DAS-VSP data. The results demonstrate the model’s effectiveness in removing various noise types with minimal signal leakage, outperforming conventional methods. This research signifies diffusion models’ potential for DAS processing.
Accelerometric Classification of Resting and Postural Tremor Amplitude
Authors: van der Linden Christina , Berger Thea , Brandt Gregor A. , Strelow Joshua N. , Jergas Hannah , Baldermann Juan Carlos , Visser-Vandewalle Veerle , Fink Gereon R. , Barbe Michael T. , Petry-Schmelzer Jan Niklas , Dembek Till A.
Published: October 2023

Clinical rating scales for tremors have significant limitations due to low resolution, high rater dependency, and lack of applicability in outpatient settings. Reliable, quantitative approaches for assessing tremor severity are warranted, especially evaluating treatment effects, e.g., of deep brain stimulation (DBS). We aimed to investigate how different accelerometry metrics can objectively classify tremor amplitude of Essential Tremor (ET) and tremor in Parkinson’s Disease (PD). We assessed 860 resting and postural tremor trials in 16 patients with ET and 25 patients with PD under different DBS settings. Clinical ratings were compared to different metrics, based on either spectral components in the tremorband or pure acceleration, derived from simultaneous triaxial accelerometry captured at the index finger and wrist. Nonlinear regression was applied to a training dataset to determine the relationship between accelerometry and clinical ratings, which was then evaluated in a holdout dataset. All of the investigated accelerometry metrics could predict clinical tremor ratings with a high concordance (>70%) and substantial interrater reliability (Cohen’s weighted Kappa > 0.7) in out-of-sample data. Finger-worn accelerometry performed slightly better than wrist-worn accelerometry. We conclude that triaxial accelerometry reliably quantifies resting and postural tremor amplitude in ET and PD patients. A full release of our dataset and software allows for implementation, development, training, and validation of novel methods.
Soil Carbon Stock and Indices in Sandy Soil Affected by Eucalyptus Harvest Residue Management in the South of Brazil
Authors: de São José Jackson Freitas Brilhante , Vargas Luciano Kayser , Lisboa Bruno Britto , Vieira Frederico Costa Beber , Zanatta Josiléia Acordi , Araujo Elias Frank , Bayer Cimelio
Published: October 2023

There has been limited research on the effect of eucalyptus harvest residue management on soil organic carbon (SOC) in subtropical environments. This research evaluated the effect on soil C indices of the following eucalyptus harvest residue managements: AR, with all forest remnants left on the soil; NB, where bark was removed; NBr, in which branches were removed; NR, which removed all residues; and NRs, which is same as NR but also used a shade net to prevent the litter from the new plantation from reaching the soil surface. C stocks within the soil depths of 0–20 cm and 0–100 cm increased linearly with the C input from eucalyptus harvest residues. In the layer of 0–20 cm, the lowest soil C retention rate was 0.23 Mg ha−1 year−1, in the NR treatment, while in the AR treatment, the retention rate was 0.68 Mg ha−1 year−1. In the 0–100 cm layer, the highest C retention rate was obtained in the AR (1.47 Mg ha−1 year−1). The residues showed a high humification coefficient (k1 = 0.23) and a high soil organic matter decomposition rate (k2 = 0.10). The carbon management index showed a close relationship with the C input and tree diameter at breast height.
The Semi-Hyperbolic Distribution and Its Applications
Authors: Ivanov Roman V.
Published: October 2023

This paper studies a subclass of the class of generalized hyperbolic distribution called the semi-hyperbolic distribution. We obtain analytical expressions for the cumulative distribution function and, specifically, their first and second lower partial moments. Using the received formulas, we compute the value at risk, the expected shortfall, and the semivariance in the semi-hyperbolic model of the financial market. The formulas depend on the values of generalized hypergeometric functions and modified Bessel functions of the second kind. The research illustrates the possibility of analysis of generalized hyperbolic models using the same methodology as is employed for the well-established variance-gamma model.
The Role of Tourism in Promoting the Urbanization of Ethnic Border Areas: A Case Study of Xishuangbanna
Authors: Yu Jiao , Yang Jianxin , Li Jiangfeng , Lin Ling , Ren Yingjian
Published: October 2023

Taking Xishuangbanna Dai Autonomous Prefecture, a typical ethnic border area with rapid tourism development, as an example, this study uses a coupling coordination degree model to quantitatively analyze tourism and urbanization, two subsystems in Xishuangbanna, and measure the level of coordinated development between tourism and urbanization in Xishuangbanna. This study provides a theoretical basis for building famous tourist cities and for improving the urbanization efficiency and level in areas such as Xishuangbanna with abundant tourism resources but insufficient urbanization. The following results were obtained: (1) Xishuangbanna’s tourism plays a strong role in promoting urbanization, and its tourism urbanization response coefficient, tourism industry location entropy, and tourism urbanization level indicator all show clear upward trends; tourism has become a local advantage industry and has a significant positive correlation with urbanization. (2) In the evaluation system for tourism urbanization quality, the weights are ranked in the order of social indicators > economic indicators > population indicators > spatial indicators > eco-environmental indicators; over time, social indicators and economic indicators show clear fluctuating upward trends, population indicators fluctuate greatly, and spatial indicators and eco-environmental indicators fluctuate little. (3) The top five indicators influencing tourism urbanization are the number of the incoming individuals, the number of travel agencies, the number of corporate enterprises in the catering industry, the forest coverage rate, and the number of ethnic minority villages. (4) In the evaluation of the coupling coordination degree, the comprehensive evaluation indicator is low, resulting in an overall low coupling coordination degree of tourism urbanization quality in Xishuangbanna, and three types of coupling coordinated development (i.e., severe, moderate, and mild imbalances) are observed.
Transitioning to an IFRS-Based Accounting System: Longitudinal Insights from Practitioners in Portugal
Authors: Silva Ana Paula , Fontes Alexandra , Menezes Carlos , Montenegro Tânia Menezes
Published: October 2023

This paper explores the extent to which International Financial Reporting Standards (IFRS)-wide support (regardless of the institutional context) is warranted. Drawing from an institutional theory framework, it investigates the extent to which practitioners in a code-law-rooted country perceive the materialization of claimed benefits of IFRS and the institutional forces that may hinder the IFRS’s institutionalization process. An interpretative approach based on qualitative research was adopted. Longitudinal evidence was gathered from 34 in-depth semi-structured in-person interviews with Portuguese preparers conducted in 2009 (just before an IFRS-based accounting system was adopted) and 2017 (at a post-implementation mature stage). Qualitative data analysis was carried out using a thematic coding scheme derived from the adopted theoretical framework: legitimacy and economic (operational and financial) benefits and institutional contradictions (IFRS’s in-country adequacy). The main results highlight that, while legitimacy benefits have been broadly recognized, economic benefits were scantly perceived due to the enduring code-law institutional logic embedded in the Portuguese context. Consistently, a high possibility of decoupling and manipulating accounts was acknowledged, which in turn casts reservations not only about the material consequences of the international convergence process to IFRS but also about its contribution towards sustainable development. Given that a major academic debate persists on whether accounting harmonization is beneficial, this research’s findings fill this gap and provide valuable insights for future research, practice, and regulation. Particularly, our findings enhance the urgency of developing institutional adjustments, such as changing national culture, on behalf of the Anglo-Saxon-based institutional approach of IFRS.
An Optimized Decision Model for Electric Vehicle Aggregator Participation in the Electricity Market Based on the Stackelberg Game
Authors: Xu Xiangchu , Zhan Zewei , Mi Zengqiang , Ji Ling
Published: October 2023

With the growing popularity of charging pile infrastructure and the development of smart electronic devices and 5G communication technologies, the electric vehicle aggregator (EVA) as a bidding entity can aggregate numerous electric vehicle (EV) resources to participate in the electricity market. Moreover, as the number of grid-connected EVs increases, EVA will have an impact on the nodal marginal prices of electricity market clearing. Aiming at the bidding and offering problem of EVA participation in the day-ahead and intra-day electricity markets, based on the Stackelberg game theory, this paper establishes a bilevel optimization model for EVA participation in the two-stage electricity market as a price-maker. In the proposed bilevel model, the upper-level and lower-level models are constructed as an operational problem for EVA and a market-clearing problem for independent system operator (ISO), respectively. In the day-ahead stage, EVA is optimized to maximize its own expected benefits, and ISO aims to improve the social benefits. In the intra-day stage, EVA is optimized to maximize its self-interest, and the ISO aims to make it possible to minimize the cost of expenditures to maintain the system’s supply–demand balance. Karush–Kuhn–Tucker (KKT) conditions and dual theory are used to transform the nonlinear bilevel programming model into a mixed-integer single-level linear programming model. In order to verify the validity of the proposed bilevel model as well as to comparatively analyze the impact of EVA’s participation in the electricity market on the market clearing results. Two scenarios are set up where EVA is seen as the price-taker in Scenario 1 and EVA is seen as the price-maker in Scenario 2. ISO’s revenue under Scenario 2 increased by USD 2262.66 compared to Scenario 1. In addition, the EVA acts as an energy consumer in Scenario 1 with a charging cost of USD 26,432.95, whereas in Scenario 2, the EVA can profit by participating in the electricity market with a revenue of USD 26,432.95, at which point the EVA acts like a virtual power plant. The simulation examples verify that the proposed bilevel optimization model can improve the benefits of ISO and EVA at the same time, achieving mutual benefits for both parties. In addition, the simulation analyzes the impact of abandonment penalty price on ISO and EVA intra-day revenues. Comparing the scenarios where the abandonment penalty price is 0 with USD 10/MW, the ISO’s revenue in the intra-day market decreases by USD 197.5. Correspondingly, EVA’s reserve capacity is dispatched to consume wind power in the intra-day market, and its revenue increases by USD 197.5. The proposed two-stage bilevel optimization model can provide a reference for EVA to develop scheduling strategies in the day-ahead and intra-day electricity markets.
Disaggregating Asian Identities through Case Studies of High School Students in Electronic Textiles Classrooms
Authors: Jayathirtha Gayithri , Castro Francisco Enrique Vicente
Published: October 2023

While most of the identity-related work within STEAM education has examined learners from different marginalized groups, Asians and Asian Americans are some of the least studied identities despite the underrepresentation of several Asian sub-groups within STEAM fields. Educational research has embraced the “model minority” myth, adopted a White-colonial gaze, aggregated Asians into a single “racial group”, and treated it as a dominant group within STEM fields. By resisting the White-centered, colonial simplifications and also conducting ways of engaging with learners that identify with Asian communities, we present four case studies of “Asian” high school students in two STEAM classrooms (which were both implementing an electronic textiles unit) in an attempt to disaggregate and to highlight the diversity and complications in the the otherwise simplified “Asian” identity. We answer the question of how electronic textiles projects support students’ “Asian” identity expression, negotiation, and development. We share how our cases accentuated the role of materiality and pedagogical context in opening possibilities for students to narrate stories of historical, cultural, and familial significance while navigating their complicated “Asian” (or not) identities. We discuss the implications of our findings for the research, design, and practice within STEAM activities to better support the highly diverse and invisibly marginalized Asian-origin students.
Identifying D Mesons from Radiative W Decays at the Large Hadron Collider
Authors: Bakos Evelin , de Groot Nicolo , Vranjes Nenad
Published: October 2023

In this paper, we present two machine learning algorithms to identify D mesons produced in a colour singlet state from radiative W boson decays at the LHC. The combined network algorithm is able to identify D mesons via its hadronic decays with an efficiency of 47% while suppressing a background of quark and gluon jets by a factor of 100. Using the developed algorithm, we perform a prospective study for the measurement of B(W→Dsγ).
Role of Differential Susceptibility and Infectiousness on the Dynamics of an SIRS Model for Malaria Transmission
Authors: Safan Muntaser , Bichara Derdei , Yong Kamuela E. , Alharthi Amira , Castillo-Chavez Carlos
Published: October 2023

A deterministic model for the transmission dynamics of SIRS-type malaria in hosts and SI in mosquito populations is proposed. The host population is differentiated between naive, primary, and secondary susceptible individuals. Primary and secondary infected individuals (and also recovered) are differentiated from each other according to their degree of infectiousness. The impact of changing the relative susceptibilities of primary and secondary (with respect to naive) susceptible individuals on the dynamics is investigated. Also, the impact of changing the relative infectiousness of secondary infected, primary, and secondary recovered individuals (with respect to primary infected) on the transmission dynamics of malaria is studied.
Bibliometric Performance and Future Relevance of Virtual Manufacturing Technology in the Fourth Industrial Revolution
Authors: Kobara Yawo Mamoua , Akpan Ikpe Justice
Published: October 2023

Virtual manufacturing (VM) technology emerged in the 1980s as a revolutionary strategy to optimize and streamline the entire product/service manufacturing lifecycle. However, over the years, its popularity appears to have waned. Further, the advent of the fourth industrial revolution (4IR) or Industry 4.0 brings with it other integrated digital technologies, including the Internet of Things (IoT), Blockchain, and digital twin (DT), among others. DT offers functions like VM plus other benefits, including intelligent manufacturing, to revolutionize future manufacturing operations activities and predictive capability using real-time data. This paper employs bibliographic metadata from publications indexed on SCOPUS to evaluate the recent trends in VM research and develop predictive models to forecast VM’s future trajectory and relevance in 4IR. The results of the bibliometric evaluation of VM-related scientific literature publications show a rapidly declining research productivity and highlight an exponential decline from the mid-2000s. This period of VM publication decline coincides with the advent of 4IR and DT technology, which are trending. The results of the predictive analytics using the quadratic regression model created in this study to forecast the future relevance of VM in the 4IR era suggest that VM publications show a similar conclusion. VM research output increased until 2009 and then started decreasing exponentially. The quadratic model implies an exponential decrease in yearly VM publications. Future works can evaluate DT and VM research trends from the last two decades.
Transiting Circumbinary Planets in the Era of Space-Based Photometric Surveys
Authors: Kostov Veselin B.
Published: October 2023

Planets orbiting binary stars—circumbinary planets—play a paramount role in our understanding of planetary and stellar formation and evolution, dynamical interactions in many-body systems, and the potential for habitable environments beyond the Solar System. Each new discovery holds immense value and inherent fascination both for the astronomical community and for the general public. This is perhaps best demonstrated by the 1500+ citations of the discovery papers for the 14 known transiting circumbinary planets and the dozens of related press-releases in major news outlets. This article reviews the observational and theoretical aspects related to the detection and confirmation of transiting circumbinary planets around main-sequence binaries from space-based surveys, discusses the associated challenges, and highlights some of the recent results.
Advances of Reverse Vaccinology for mRNA Vaccine Design against SARS-CoV-2: A Review of Methods and Tools
Authors: da Silva Maria Karolaynne , Campos Daniel Melo de Oliveira , Akash Shopnil , Akter Shahina , Yee Leow Chiuan , Fulco Umberto Laino , Oliveira Jonas Ivan Nobre
Published: October 2023

mRNA vaccines are a new class of vaccine that can induce potent and specific immune responses against various pathogens. However, the design of mRNA vaccines requires the identification and optimization of suitable antigens, which can be challenging and time consuming. Reverse vaccinology is a computational approach that can accelerate the discovery and development of mRNA vaccines by using genomic and proteomic data of the target pathogen. In this article, we review the advances of reverse vaccinology for mRNA vaccine design against SARS-CoV-2, the causative agent of COVID-19. We describe the steps of reverse vaccinology and compare the in silico tools used by different studies to design mRNA vaccines against SARS-CoV-2. We also discuss the challenges and limitations of reverse vaccinology and suggest future directions for its improvement. We conclude that reverse vaccinology is a promising and powerful approach to designing mRNA vaccines against SARS-CoV-2 and other emerging pathogens.
Emergence of Genomic Diversity in the Spike Protein of the “Omicron” Variant
Authors: Basak Surajit , Kayet Pratanu , Ghosh Manisha , Chatterjee Joyeeta , Dutta Shanta
Published: October 2023

SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus) has constantly been evolving into different forms throughout its spread in the population. Emerging SARS-CoV-2 variants, predominantly the variants of concern (VOCs), could have an impact on the virus spread, pathogenicity, and diagnosis. The recently emerged “Omicron” variant has exhibited rapid transmission and divergence. The spike protein of SARS-CoV-2 has consistently been appearing as the mutational hotspot of all these VOCs. In order to determine a deeper understanding of the recently emerged and extremely divergent “Omicron”, a study of amino acid usage patterns and their substitution patterns was performed and compared with those of the other four successful variants of concern (“Alpha”, “Beta”, “Gamma”, and “Delta”). We observed that the amino acid usage of “Omicron” has a distinct pattern that distinguishes it from other VOCs and is significantly correlated with the increased hydrophobicity in spike proteins. We observed an increase in the non-synonymous substitution rate compared with the other four VOCs. Considering the phylogenetic relationship, we hypothesized about the functional interdependence between recombination and the mutation rate that might have resulted in a shift in the optimum of the mutation rate for the evolution of the “Omicron” variant. The results suggest that for improved disease prevention and control, more attention should be given to the significant genetic differentiation and diversity of newly emerging variants.
Increased Presence of Circulating Cell-Free, Fragmented, Host DNA in Pigs Infected with Virulent African Swine Fever Virus
Authors: Olesen Ann Sofie , Lohse Louise , Johnston Camille Melissa , Rasmussen Thomas Bruun , Bøtner Anette , Belsham Graham J.
Published: October 2023

African swine fever virus (ASFV) causes severe hemorrhagic disease in domestic pigs and wild boar, often with high case fatality rates. The virus replicates in the circulating cells of the monocyte–macrophage lineage and within lymphoid tissues. The infection leads to high fever and a variety of clinical signs. In this study, it was observed that ASFV infection in pigs resulted in a >1000-fold increase in the level of circulating cell-free DNA (cfDNA), derived from the nuclei of host cells in the serum. This change occurred in parallel with the increase in circulating ASFV DNA. In addition, elevated levels (about 30-fold higher) of host mitochondrial DNA (mtDNA) were detected in the serum from ASFV-infected pigs. For comparison, the release of the cellular enzyme, lactate dehydrogenase (LDH), a commonly used marker of cellular damage, was also found to be elevated during ASFV infection, but later and less consistently. The sera from pigs infected with classical swine fever virus (CSFV), which causes a clinically similar disease to ASFV, were also tested but, surprisingly, this infection did not result in the release of cfDNA, mtDNA, or LDH. It was concluded that the level of cfDNA in the serum is a sensitive host marker of virulent ASFV infection.
NEURO-COVAX: An Italian Population-Based Study of Neurological Complications after COVID-19 Vaccinations
Authors: Salsone Maria , Signorelli Carlo , Oldani Alessandro , Alberti Valerio Fabio , Castronovo Vincenza , Mazzitelli Salvatore , Minerva Massimo , Ferini-Strambi Luigi
Published: October 2023

Objective: In this Italian population-based study, we aimed to evaluate the neurological complications after the first and/or second dose of COVID-19 vaccines and factors potentially associated with these adverse effects. Methods: Our study included adults aged 18 years and older who received two vaccine doses in the vaccination hub of Novegro (Milan, Lombardy) between 7 and 16 July 2021. The NEURO-COVAX questionnaire was able to capture the neurological events, onset and duration. That data that were digitized centrally by the Lombardy region were used to match the demographic/clinical characteristics and identify a vulnerability profile. Associations between vaccine lines and the development of complications were assessed. Digital healthcare system matching was also performed to evaluate severe neurological complications (Guillain-Barrè syndrome, Bell’s palsy, transverse myelitis, encephalitis) and the incidence of hospital admissions and/or the mortality rate after two doses of the vaccines. Results: The NEURO-COVAX-cohort included 19.108 vaccinated people: 15.368 with BNT162b2, 2077 with mRNA-1273, 1651 with ChAdOx1nCov-19, and 12 with Ad26.COV2.S who were subsequently excluded. Approximately 31.2% of our sample developed post-vaccination neurological complications, particularly with ChAdOx1nCov-19. A vulnerable clinical profile emerged, where over 40% of the symptomatic people showed comorbidities in their clinical histories. Defining the neurological risk profile, we found an increased risk for ChAdOx1nCov-19 of tremors (vs. BNT162b2, OR: 5.12, 95% CI: 3.51–7.48); insomnia (vs. mRNA-1273, OR: 1.87, 95% CI: 1.02–3.39); muscle spasms (vs. BNT162b2, OR: 1.62, 95% CI: 1.08–2.46); and headaches (vs. BNT162b2, OR: 1.49, 95% CI: 0.96–1.57). For mRNA-1273, there were increased risks of parethesia (vs. ChAdOx1nCov-19, OR: 2.37, 95% CI: 1.48–3.79); vertigo (vs. ChAdOx1nCov-19, OR: 1.68, 95% CI: 1.20–2.35); diplopia (vs. ChAdOx1nCov-19, OR: 1.55, 95% CI: 0.67–3.57); and sleepiness (vs. ChAdOx1nCov-19, OR: 1.28, 95% CI: 0.98–1.67). In the period that ranged from March to August 2021, no one was hospitalized and/or died of severe complications related to COVID-19 vaccinations. Discussion: This study estimates the prevalence and risk for neurological complications potentially associated with COVID-19 vaccines, thus improving the vaccination guidelines and loading in future personalized preventive medicine.