bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy Colonialism in Europe: A Participatory Analysis of the Case of Granada (Spain)
Authors: Sánchez Contreras Josefa , Matarán Ruiz Alberto , Villodres Ramírez Luis , Jiménez Martín Celia , Gámez Rodríguez Guillermo , Martín Pérez Rafael , Campos-Celador Álvaro
Published: January 2024

The energy crisis and the exacerbation of climate change, along with the associated geopolitical tensions, including the war in Ukraine, are accelerating the energy transition in Europe. A transition from fossil energy sources to renewable energy sources that have a low Energy Return Rate, involves, among many other issues, the use of wide areas to locate the necessary infrastructure for production, transport and storage, altering territories with agricultural, cultural and ecological values. This process is based on the deployment of renewable energy megaprojects in peripheric areas of the continent, mostly in the southern states creating a wide range of social conflicts and resistances. We analyse this process in the case study of the province of Granada, a peripheric territory of south-east Spain considering the category of energy colonialism and the six dimensions that characterise it, arguing that this is a proper approach to address internal colonialism related to the corporate energy transition. We also want to demonstrate the importance of using participatory methodologies for this analysis, so we have developed an online survey, semi-structured interviews and participatory cartography workshops, always focusing on the citizens and stakeholders who are resisting the deployment of renewable energy megaprojects in the province of Granada. The obtained results allow us to confirm the necessity of using participatory methodologies and the colonial aspect of this deployment, including the characteristics of social resistance, the territorial impacts, the land-grabbing process and the inequalities in the production, distribution and use of energy. We conclude with the need to articulate a decolonial energy transition where participatory methods constitute a fundamental tool both to attend the resistances and to build the alternatives.
The Orientation of Evidentials in Attitude Contexts: A Case Study Based on Narratives in Paraguayan Guarani
Authors: Pancheva Roumyana , Zubizarreta Maria Luisa
Published: January 2024

This paper examines the orientation of evidentials in complements of attitude verbs, with Paraguayan Guarani evidential ra’e as a case study. It argues that embedded evidentials can be directed either towards the speaker or towards a matrix attitude-holder argument (e.g., the subject of the attitude verb) and that a syntactic representation of the evidence-acquisition event, with its pronominal subject, in the lower end of the CP field, is well-poised to capture this potential ambiguity. Language-particular properties can also play a determining role in the orientation of the embedded evidential, as is the case of the subordinator ha in Paraguayan Guarani. It is argued that this subordinator requires the presence of a Complementizer specified with a (strong) Modal component (which encodes certainty/commitment on the part of the attitude holder with respect to the embedded proposition) and that this property biases the orientation of ra’e towards the matrix attitude-holder argument.
The Role of Language Experience in the Acquisition of Spanish Gender Agreement: A Study with Nonce Nouns
Authors: Montrul Silvina , Mason Sara Ann , Armstrong Andrew
Published: January 2024

Why is learning the gender of nouns so difficult for some bilinguals? We test the hypothesis that different language learning backgrounds or life experience with Spanish determine how learners follow different morphosyntactic cues for gender assignment in Spanish by testing learners with early and late language experience in an experiment with invented nouns. A total of 44 monolingually raised native speakers, 44 heritage speakers, and 44 L2 learners of Spanish were trained to learn 24 nonce words in Spanish presented in four input conditions that manipulated the number and type of cues to gender marking (determiner, word marker, adjective). After the learning sessions, the participants completed a word naming task, an elicited production task, and a debriefing questionnaire. The L2 learners were different than native speakers and heritage speakers in learning nonce nouns. They used morphosyntactic cues differently, relying on adjectives as their most-used strategy to assign gender, unlike native speakers and heritage speakers who used all cues. Our findings confirm processing differences between L2 learners and heritage speakers and suggest language learning background determines how learners discover reliable morphosyntactic cues to the gender of nouns in the input.
On the Importance of the Recovery Procedure in the Semi-Analytical Solution for the Static Analysis of Curved Laminated Panels: Comparison with 3D Finite Elements
Authors: Tornabene Francesco , Viscoti Matteo , Dimitri Rossana
Published: January 2024

The manuscript presents an efficient semi-analytical solution with three-dimensional capabilities for the evaluation of the static response of laminated curved structures subjected to general external loads. A two-dimensional model is presented based on the Equivalent Single Layer (ESL) approach, where the displacement field components are described with a generalized formulation based on a higher-order expansion along the thickness direction. The fundamental equations are derived from the Hamiltonian principle, and the solution is found by means of Navier’s approach. Then, an efficient recovery procedure, derived from the three-dimensional elasticity equations and based on the Generalized Differential Quadrature (GDQ) method, is adopted for the derivation of the three-dimensional solution. Some examples of investigation are presented, where the numerical predictions of refined three-dimensional Finite-Element-based models are matched with a high level of accuracy. The model is validated for both straight and curved panels, taking into account different lamination schemes and load shapes. Furthermore, it is shown that the numerical solution to the elasticity problem in the recovery procedure is determining and accurately predicting the three-dimensional static response of the doubly-curved shell solid.
A Comparative Study on Impact Resistance of Cylindrical Structures with Cushioning Energy Absorbing Rings under Double Impact Loading
Authors: Zhang Bo , Feng Shunshan
Published: January 2024

In this paper, the impact resistance of a cylindrical structure with a buffer ring and an energy-absorbing ring under double impact loads is studied. Based on ABAQUS 2023 finite element software, a simulation model of a buffer ring structure with three different sibs was established, and the specimens were subjected to double impact loading. The results show that the impact resistance of the structure decreases with the increase in curvature radius. The increase in the thickness of the panel can effectively reduce the deformation difference between the center point of the panel and the maximum displacement point. The buffer ring composed of cell structure with negative Poisson’s ratio effect has better shock resistance under explosion load, while the buffer ring with hexagonal cellular structure has excellent kinetic energy shock resistance.
Accelerating Elastic Property Prediction in Fe-C Alloys through Coupling of Molecular Dynamics and Machine Learning
Authors: Risal Sandesh , Singh Navdeep , Yao Yan , Sun Li , Risal Samprash , Zhu Weihang
Published: January 2024

The scarcity of high-quality data presents a major challenge to the prediction of material properties using machine learning (ML) models. Obtaining material property data from experiments is economically cost-prohibitive, if not impossible. In this work, we address this challenge by generating an extensive material property dataset comprising thousands of data points pertaining to the elastic properties of Fe-C alloys. The data were generated using molecular dynamic (MD) calculations utilizing reference-free Modified embedded atom method (RF-MEAM) interatomic potential. This potential was developed by fitting atomic structure-dependent energies, forces, and stress tensors evaluated at ground state and finite temperatures using ab-initio. Various ML algorithms were subsequently trained and deployed to predict elastic properties. In addition to individual algorithms, super learner (SL), an ensemble ML technique, was incorporated to refine predictions further. The input parameters comprised the alloy’s composition, crystal structure, interstitial sites, lattice parameters, and temperature. The target properties were the bulk modulus and shear modulus. Two distinct prediction approaches were undertaken: employing individual models for each property prediction and simultaneously predicting both properties using a single integrated model, enabling a comparative analysis. The efficiency of these models was assessed through rigorous evaluation using a range of accuracy metrics. This work showcases the synergistic power of MD simulations and ML techniques for accelerating the prediction of elastic properties in alloys.
Experimental Investigations on the Ferromagnetic Resonance and Absorbing Properties of a Ferrofluid in the Microwave Range
Authors: Malaescu Iosif , Marin Catalin N. , Fannin Paul C.
Published: January 2024

Measurements of complex magnetic permeability, μ(f,H) = μ′(f,H) − iμ″(f,H) and dielectric permittivity ε(f,H) = ε′(f,H) − iε″(f,H), in the frequency range, f of (0.4–7) GHz, and polarizing field, H of (0–135) kA/m, were performed, for a kerosene-based ferrofluid with magnetite nanoparticles. Based on these measurements, the phenomenon of ferromagnetic resonance was highlighted and some microwave propagation parameters of the ferrofluid were determined: the attenuation constant, α(f,H), and the reflection coefficient, R(f,H), at the air-material interface, at the normal incidence. Knowing these parameters we proposed a theoretical model establishing for the first time an equation that allows the calculation of the overall reflection coefficient, Rw(f,H), at the normal incidence of the wave, for a ferrofluid of thickness d, deposited on a totally reflective support, following multiple internal reflections of the electromagnetic wave in the material. The results show that by increasing both, H, and d, the parameter, Rw(f,H) presents a minimum that decreases from 0.90 (for d = 2 mm) to 0.64 (for d = 10 mm), at frequency f = 5 GHz, which indicates an increase in the absorption of the electromagnetic wave by the ferrofluid. The obtained results are useful in the study of some materials that could be used as electromagnetic absorbers in the microwave range, by the determination of the overall reflection coefficient, Rw(f,H), controlled both by the thickness, d, of the absorber and by the external applied field, H.
The m-Component Connectivity of Leaf-Sort Graphs
Authors: Wang Shiying , Li Hongmei , Zhao Lina
Published: January 2024

Connectivity plays an important role in measuring the fault tolerance of interconnection networks. As a special class of connectivity, m-component connectivity is a natural generalization of the traditional connectivity of graphs defined in terms of the minimum vertex cut. Moreover, it is a more advanced metric to assess the fault tolerance of a graph G. Let G=(V(G),E(G)) be a non-complete graph. A subset F(F⊆V(G)) is called an m-component cut of G, if G−F is disconnected and has at least m components (m≥2). The m-component connectivity of G, denoted by cκm(G), is the cardinality of the minimum m-component cut. Let CFn denote the n-dimensional leaf-sort graph. Since many structures do not exist in leaf-sort graphs, many of their properties have not been studied. In this paper, we show that cκ3(CFn)=3n−6 (n is odd) and cκ3(CFn)=3n−7 (n is even) for n≥3; cκ4(CFn)=9n−212 (n is odd) and cκ4(CFn)=9n−242 (n is even) for n≥4.
Keyword Pool Generation for Web Text Collecting: A Framework Integrating Sample and Semantic Information
Authors: Wu Xiaolong , Feng Chong , Li Qiyuan , Zhu Jianping
Published: January 2024

Keyword pools are used as search queries to collect web texts, largely determining the size and coverage of the samples and provide a data base for subsequent text mining. However, how to generate a refined keyword pool with high similarity and some expandability is a challenge. Currently, keyword pools for search queries aimed at collecting web texts either lack an objective generation method and evaluation system, or have a low utilization rate of sample semantic information. Therefore, this paper proposed a keyword generation framework that integrates sample and semantic information to construct a complete and objective keyword pool generation and evaluation system. The framework includes a data phase and a modeling phase, and its core is in the modeling phase, where both feature ranking and model performance are considered. A regression model about a topic vector and word vectors is constructed for the first time based on word embedding, and keyword pools are generated from the perspective of model performance. In addition, two keyword generation methods, Recursive Feature Introduction (RFI) and Recursive Feature Introduction and Elimination (RFIE), are also proposed in this paper. Different feature ranking algorithms, keyword generation methods and regression models are compared in the experiments. The results show that: (1) When using RFI to generate keywords, the regression model using ranked features has better prediction performance than the baseline model, and the number of generated keywords is refiner, and the prediction performance of the regression model using tree-based ranked features is significantly better than that of the one using SHAP-based ranked features. (2) The prediction performance of the regression model using RFI with tree-based ranked features is significantly better than that using Recursive Feature Elimination (RFE) with tree-based one. (3) All four regression models using RFI/RFE with SHAP- based/tree-based ranked features have significantly higher average similarity scores and cumulative advantages than the baseline model (the model using RFI with unranked features). (4) Light Gradient Boosting Machine (LGBM) using RFI with SHAP-based ranked features has significantly better prediction performance, higher average similarity scores, and cumulative advantages. In conclusion, our framework can generate a keyword pool that is more similar to the topic, and more refined and expandable, which provides certain research ideas for expanding the research sample size while ensuring the coverage of topics in web text collecting.
On a Class of Nonlinear Elliptic Equations with General Growth in the Gradient
Authors: Betta M. Francesca , Mercaldo Anna , Volpicelli Roberta
Published: January 2024

In this paper, we prove an existence and uniqueness result for a class of Dirichlet boundary value problems whose model is −Δpu=β|∇u|q+c|u|p−2u+fin Ω,u=0on ∂Ω, where Ω is an open bounded subset of RN, N≥2, 1<p<N, Δpu is the so-called p-Laplace operator, and p−1<q<p. We assume that β is a positive constant, c and f are measurable functions belonging to suitable Lorentz spaces. Our approach is based on Schauder fixed point theorem.
Genetic Diversity and Virulence Variation of Metarhizium rileyi from Infected Spodoptera frugiperda in Corn Fields
Authors: Peng Yuejin , Yao Yunhao , Pang Jixin , Di Teng , Du Guangzu , Chen Bin
Published: January 2024

Metarhizium rileyi is an entomopathogenic fungus that naturally infects the larvae of Spodoptera frugiperda, and has biocontrol potential. To explore more natural entomopathogenic fungi resources, a total of 31 strains were isolated from 13 prefectures in Yunnan Province. All the strains were identified using morphology and molecular biology. The genetic diversity of the 31 isolates of M. rileyi was analyzed using inter-simple sequence repeat (ISSR) techniques. Seven primers with good polymorphism were selected, and fifty-four distinct amplification sites were obtained by polymerase chain reaction amplification. Among them, 50 were polymorphic sites, and the percentage of polymorphic sites was 94.44%. The thirty-one strains were divided into eight subpopulations according to the regions. The Nei’s gene diversity was 0.2945, and the Shannon information index was 0.4574, indicating that M. rileyi had rich genetic diversity. The average total genetic diversity of the subpopulations in the different regions was 0.2962, the gene diversity within the populations was 0.1931, the genetic differentiation coefficient was 0.3482 (>0.25), and the gene flow was 0.9360 (<1). The individual cluster analysis showed that there was no obvious correlation between the genetic diversity of the strains and their geographical origin, which also indicated that the virulence of the strains was not related to their phylogeny. Thus, the genetic distance of the different populations of M. rileyi in Yunnan Province was not related to the geographical distance. The virulence of those 32 strains against the 3rd-instar larvae of S. frugiperda were varied with the differences in geographical locations. On the 10th day of inoculation, seventeen strains had an insect mortality rate of 70.0%, and seven strains had an insect mortality rate of 100%. The half-lethal times of the M. rileyi SZCY201010, XSBN200920, and MDXZ200803 strains against the S. frugiperda larvae were less than 4 d. Thus, they have the potential to be developed into fungal insecticidal agents.
Mitigating Age-Related Cognitive Decline and Oxidative Status in Rats Treated with Catechin and Polyphenon-60
Authors: Tejada Silvia , Sarubbo Fiorella , Jiménez-García Manuel , Ramis Margarida R. , Monserrat-Mesquida Margalida , Quetglas-Llabrés Maria Magdalena , Capó Xavier , Esteban Susana , Sureda Antoni , Moranta David
Published: January 2024

Aging is a normal physiological process influenced by the combination of multiple mechanisms, primarily oxidative stress and neuroinflammation, which impact general physiology and brain function. Phenolic compounds have demonstrated the ability to slow down the aging process of the brain due to their antioxidant and anti-inflammatory effects. This study assessed the protective properties of catechin and polyphenon-60 in non-pathologically aged rats regarding visuo-spatial learning and the oxidative status of the frontal cortex. Old animals were treated with catechin or green tea extract (polyphenon-60) for 36 days, daily. Healthy old and young rats were used as controls. During the first training phase, treated rats executed the test better, locating the target in less time compared with the controls. Biomarkers of oxidative stress (catalase activities, superoxide dismutase, glutathione reductase, and glutathione S-transferase) were reduced in the brain of old animals, although their activities were partially improved after both antioxidant treatments. Furthermore, the rise in the production of reactive oxygen species and malondialdehyde levels—a marker of lipid peroxidation—in the frontal cortex of aged animals was significantly ameliorated after the interventions. In conclusion, old rats exhibited enhanced cognitive function and reduced stress levels following the administration of catechin and polyphenon-60.
The Role of the FODMAP Diet in IBS
Authors: Bertin Luisa , Zanconato Miriana , Crepaldi Martina , Marasco Giovanni , Cremon Cesare , Barbara Giovanni , Barberio Brigida , Zingone Fabiana , Savarino Edoardo Vincenzo
Published: January 2024

The low FODMAP (fermentable oligosaccharide, disaccharide, monosaccharide, and polyol) diet is a beneficial therapeutic approach for patients with irritable bowel syndrome (IBS). However, how the low FODMAP diet works is still not completely understood. These mechanisms encompass not only traditionally known factors such as luminal distension induced by gas and water but also recent evidence on the role of FOMAPs in the modulation of visceral hypersensitivity, increases in intestinal permeability, the induction of microbiota changes, and the production of short-chain fatty acids (SCFAs), as well as metabolomics and alterations in motility. Although most of the supporting evidence is of low quality, recent trials have confirmed its effectiveness, even though the majority of the evidence pertains only to the restriction phase and its effectiveness in relieving abdominal bloating and pain. This review examines potential pathophysiological mechanisms and provides an overview of the existing evidence on the effectiveness of the low FODMAP diet across various IBS subtypes. Key considerations for its use include the challenges and disadvantages associated with its practical implementation, including the need for professional guidance, variations in individual responses, concerns related to microbiota, nutritional deficiencies, the development of constipation, the necessity of excluding an eating disorder before commencing the diet, and the scarcity of long-term data. Despite its recognized efficacy in symptom management, acknowledging these limitations becomes imperative for a nuanced comprehension of the role of a low FODMAP diet in managing IBS. By investigating its potential mechanisms and evidence across IBS subtypes and addressing emerging modulations alongside limitations, this review aims to serve as a valuable resource for healthcare practitioners, researchers, and patients navigating the intricate landscape of IBS.
Advances in Antitumor Effects Using Liposomal Citrinin in Induced Breast Cancer Model
Authors: Moura Michely Laiany Vieira , de Menezes Ag-Anne Pereira Melo , de Oliveira Filho José Williams Gomes , do Nascimento Maria Luiza Lima Barreto , dos Reis Antonielly Campinho , Ribeiro Alessandra Braga , da Silva Felipe Cavalcanti Carneiro , Nunes Adriana Maria Viana , Rolim Hercília Maria Lins , de Carvalho Melo Cavalcante Ana Amélia , Sousa João Marcelo de Castro e
Published: January 2024

The study aimed to evaluate the antitumor and toxicogenetic effects of liposomal nanoformulations containing citrinin in animal breast carcinoma induced by 7,12-dimethylbenzanthracene (DMBA). Mus musculus virgin females were divided into six groups treated with (1) olive oil (10 mL/kg); (2) 7,12-DMBA (6 mg/kg); (3) citrinin, CIT (2 mg/kg), (4) cyclophosphamide, CPA (25 mg/kg), (5) liposomal citrinin, LP-CIT (2 μg/kg), and (6) LP-CIT (6 µg/kg). Metabolic, behavioral, hematological, biochemical, histopathological, and toxicogenetic tests were performed. DMBA and cyclophosphamide induced behavioral changes, not observed for free and liposomal citrinin. No hematological or biochemical changes were observed for LP-CIT. However, free citrinin reduced monocytes and caused hepatotoxicity. During treatment, significant differences were observed regarding the weight of the right and left breasts treated with DMBA compared to negative controls. Treatment with CPA, CIT, and LP-CIT reduced the weight of both breasts, with better results for liposomal citrinin. Furthermore, CPA, CIT, and LP-CIT presented genotoxic effects for tumor, blood, bone marrow, and liver cells, although less DNA damage was observed for LP-CIT compared to CIT and CPA. Healthy cell damage induced by LP-CIT was repaired during treatment, unlike CPA, which caused clastogenic effects. Thus, LP-CIT showed advantages for its use as a model of nanosystems for antitumor studies.
Cation-Selective Actuator–Sensor Response of Microcrystalline Cellulose Multi-Walled Carbon Nanotubes of Different Electrolytes Using Propylene Carbonate Solvent
Authors: Elhi Fred , Le Quoc Bao , Kiefer Rudolf
Published: January 2024

Microcrystalline cellulose (MC) with 50 wt.% multi-walled carbon nanotube (MCNT) composites is obtained through extrusion, forming MC-MCNT fiber. In this study, we concentrate on three different electrolytes in propylene carbonate (PC) which have the same anions (TF−, trifluoro-methanesulfonate CF3SO3−) but different cations, EDMI+ (1-ethyl-2,3-dimethylimidazolium), Li+ (lithium ion), and TBA+ (tetrabutylammonium). Cyclic voltammetry and square wave potential steps, in combination with linear actuation measurements in a potential range of 0.7 V to −0.2 V, were conducted. Our goal in this work was to establish a cation-selective actuator–sensor device capable of distinguishing different cations. The linear actuation of MC-MCNT fiber had its main expansion at discharge due to the incorporation of TF− in the MC-MCNT fiber with the cations. In the following order, TBA+ > EDMI+ > Li+ had the best stress, strain, charge density, diffusion coefficients, and long-term stability. Chronopotentiometric measurements revealed that the cations in the PC solvent can be differentiated by their ion sizes. Further characterization of the MC-MCNT fiber was completed using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), and FTIR and Raman spectroscopy.
Application of Chitosan-Based Hydrogel in Promoting Wound Healing: A Review
Authors: Che Xueyan , Zhao Ting , Hu Jing , Yang Kaicheng , Ma Nan , Li Anning , Sun Qi , Ding Chuanbo , Ding Qiteng
Published: January 2024

Chitosan is a linear polyelectrolyte with active hydroxyl and amino groups that can be made into chitosan-based hydrogels by different cross-linking methods. Chitosan-based hydrogels also have a three-dimensional network of hydrogels, which can accommodate a large number of aqueous solvents and biofluids. CS, as an ideal drug-carrying material, can effectively encapsulate and protect drugs and has the advantages of being nontoxic, biocompatible, and biodegradable. These advantages make it an ideal material for the preparation of functional hydrogels that can act as wound dressings for skin injuries. This review reports the role of chitosan-based hydrogels in promoting skin repair in the context of the mechanisms involved in skin injury repair. Chitosan-based hydrogels were found to promote skin repair at different process stages. Various functional chitosan-based hydrogels are also discussed.
A Comprehensive Review of Microgrid Energy Management Strategies Considering Electric Vehicles, Energy Storage Systems, and AI Techniques
Authors: Khan Muhammad Raheel , Haider Zunaib Maqsood , Malik Farhan Hameed , Almasoudi Fahad M. , Alatawi Khaled Saleem S. , Bhutta Muhammad Shoaib
Published: January 2024

The relentlessly depleting fossil-fuel-based energy resources worldwide have forbidden an imminent energy crisis that could severely impact the general population. This dire situation calls for the immediate exploitation of renewable energy resources to redress the balance between power consumption and generation. This manuscript confers about energy management tactics to optimize the methods of power production and consumption. Furthermore, this paper also discusses the solutions to enhance the reliability of the electrical power system. In order to elucidate the enhanced reliability of the electrical system, microgrids consisting of different energy resources, load types, and optimization techniques are comprehensively analyzed to explore the significance of energy management systems (EMSs) and demand response strategies. Subsequently, this paper discusses the role of EMS for the proper consumption of electrical power considering the advent of electric vehicles (EVs) in the energy market. The main reason to integrate EVs is the growing hazards of climate change due to carbon emissions. Moreover, this paper sheds light on the growing importance of artificial intelligence (AI) in the technological realm and its incorporation into electrical systems with the notion of strengthening existing smart grid technologies and to handle the uncertainties in load management. This paper also delineates the different methodologies to effectively mitigate the probability of facing cyber-attacks and to make the smart grids invulnerable.
Quantitative Analysis of Near-Infrared Spectroscopy Using the BEST-1DConvNet Model
Authors: Li Gang , Deng Shuangcheng
Published: January 2024

In the quest for enhanced precision in near-infrared spectroscopy (NIRS), in this study, the application of a novel BEST-1DConvNet model for quantitative analysis is investigated against conventional support vector machine (SVM) approaches with preprocessing such as multiplicative scatter correction (MSC) and standard normal variate (SNV). We assessed the performance of these methods on NIRS datasets of diesel, gasoline, and milk using a Fourier Transform Near-Infrared (FT-NIR) spectrometer having a wavelength range of 900–1700 nm for diesel and gasoline and 4000–10,000 nm for milk, ensuring comprehensive spectral capture. The BEST-1DConvNet’s effectiveness in chemometric predictions was quantitatively gauged by improvements in the coefficient of determination (R2) and reductions in the root mean square error (RMSE). The BEST-1DConvNet model achieved significant performance enhancements compared to the MSC + SNV + 1D + SVM model. Notably, the R2 value for diesel increased by approximately 48.85% despite a marginal RMSE decrease of 0.92%. R2 increased by 11.30% with a 3.32% RMSE reduction for gasoline, and it increased by 8.71%, accompanied by a 3.51% RMSE decrease for milk. In conclusion, the BEST-1DConvNet model demonstrates superior predictive accuracy and reliability in NIRS data analysis, marking a substantial leap forward in spectral analysis technology. This advancement could potentially streamline their integration into various industrial applications and highlight the role of convolutional neural networks in future chemometric methodologies.
Integrated Waterflooding Effect Evaluation Methodology for Carbonate Fractured–Vuggy Reservoirs Based on the Unascertained Measure–Mahalanobis Distance Theory
Authors: Su Zezhong , Gao Shihui , Li Zhiyuan , Li Tiantai , Kang Nan
Published: January 2024

The waterflooding effect evaluation of carbonate fractured–vuggy reservoirs constitutes a comprehensive multiple-information decision-making process involving quantitative unascertained measure theory. This paper establishes a novel comprehensive methodology to evaluate the waterflooding effects of carbonate fractured–vuggy reservoirs for the first time. A new evaluation grading criteria is proposed using the Mahalanobis distance method based on the multi-index comprehensive unascertained measure theory derived from a modified five-scale analytical hierarchy process–entropy weight method. The actual field data from the carbonate fractured–vuggy reservoirs and the nine evaluation indices are specifically applied to demonstrate the calculation process for the construction of the grading system model on the waterflooding effects and to verify the accuracy of the Mahalanobis distance method by comparing the calculation results with the Minkowski and Euclidean distance methods. The proposed methodology facilitates the effective evaluation of the waterflooding strategies implemented in carbonate fractured–vuggy reservoirs with three categories; the ones with outstanding performance usually demonstrated favorable index characteristics, with substantial contributions to the enhanced oil recovery, manifesting with complete well patterns, a balance in the injection–production dynamics, excellent waterflooding utilization, and control competence. In contrast, fractured–vuggy units with fair waterflooding performance revealed limitations in the enhanced oil recovery. It can also be inferred that the mediocre waterflooding performance of the fractured–vuggy units is associated with incomplete well patterns, an imbalance in the injection–production dynamics, low waterflooding utilization, and a negligible waterflooding effect. The results in this study show that this newly proposed integrated model can effectively assess the waterflooding effects quantitatively and provide a more precise scientific basis for evaluating the waterflooding effects in carbonate fractured–vuggy reservoirs, with potential applicability in other fields.
Kabir and Pedagogy: Teaching the Politics of Religion through the Hagiography of an Indian Saint
Authors: Burchett Patton
Published: January 2024

This essay discusses the virtues of hagiology-driven teaching and the pedagogical value of the saint in the religious studies classroom, focusing on how a series of class assignments and activities centered on the Indian devotional saint Kabir function in an undergraduate introductory-level religious studies course to effectively engage student learning, and develop students’ understanding of the politics of religion and the crucial interplay of affect, memory, and storytelling in religious life.
A Method for Low Sidelobe Substrate-Integrated Waveguide Slot Antenna Design Applied for Millimeter-Wave Radars
Authors: Wang Shuqi , Zhou Bin , Fang Guangyou
Published: January 2024

With the development of millimeter-wave radar systems, substrate-integrated waveguide (SIW) slot antennas have been widely used. This paper presents a computational approach for calculating the equivalent normalized admittance of slot in low sidelobe SIW longitudinal slot antennas. In contrast to the existing methods, this method takes into account the impact of the N-slots coupling on the admittance. Through this method, fitting functions for resonant length and conductance are obtained, which describe the relationship between the resonant length, resonant conductance, and offset of slots. Moreover, based on the two fitting functions, a low sidelobe SIW longitudinal slot linear antenna is designed for millimeter-wave radar applications at 77 GHz. This antenna consists of a transition from the standard WR-12 waveguide to the SIW and a set of radiating slots. The simulation results indicate an impedance bandwidth of 4.8% and a gain of 13.2 dBi. The sidelobe level in the H-plane is below −28 dB, which meets the desired specifications and confirms the accuracy of the presented method.
Regional Analysis of Dominant Factors Influencing Leaf Chlorophyll Content in Complex Terrain Regions Using a Geographic Statistical Model
Authors: Chu Tianjia , Li Jing , Zhao Jing , Gu Chenpeng , Mumtaz Faisal , Dong Yadong , Zhang Hu , Liu Qinhuo
Published: January 2024

Chlorophyll is a vital indicator of vegetation growth; exploring its relationship with external influencing factors is essential for studies such as chlorophyll remote sensing retrieval and vegetation growth monitoring. However, there has been limited in-depth exploration of the spatial distribution of leaf chlorophyll content (LCC) and its influencing factors across large-scale areas with varying climates and terrains. To investigate the primary influencing factors and degrees of various environmental factors on LCC, this study employed the Geodetector Model (GDM) and the LCC satellite products in Sichuan Province in 2020 to investigate the impact of relationships between nine environmental factors (meteorology, topography, and vegetation types) and the ecosystem LCC at a regional scale. The results indicated the following: (1) Elevation (q-value = 49.31%) is the primary factor determining photosynthesis in Sichuan Province, followed by temperature (46.10%) and vegetation types (40.73%). The impact of topographical factors on LCC distribution is higher than that of meteorological factors and vegetation types in terrain with complex topography. The elevation effectively distinguishes the variations in climate factors and vegetation types. (2) Combining the influencing factors pairwise increased the combined q-values. The combination of elevation with other factors yielded the highest combined q-value. (3) The q-values for all influencing factors are higher in winter and spring and lowest in summer. Different influencing factors exhibited more substantial constraints on vegetation photosynthesis during winter and spring, significantly reducing influence during summer. (4) The different primary factors drive or constrain vegetation photosynthesis in different climate zones due to their distinct temperature and humidity characteristics. The findings of this study provide a basis for future research on vegetation change analysis and dynamic monitoring of vegetation LCC in different terrains.
A Joint Convolutional Cross ViT Network for Hyperspectral and Light Detection and Ranging Fusion Classification
Authors: Xu Haitao , Zheng Tie , Liu Yuzhe , Zhang Zhiyuan , Xue Changbin , Li Jiaojiao
Published: January 2024

The fusion of hyperspectral imagery (HSI) and light detection and ranging (LiDAR) data for classification has received widespread attention and has led to significant progress in research and remote sensing applications. However, existing common CNN architectures suffer from the significant drawback of not being able to model remote sensing images globally, while transformer architectures are not able to capture local features effectively. To address these bottlenecks, this paper proposes a classification framework for multisource remote sensing image fusion. First, a spatial and spectral feature projection network is constructed based on parallel feature extraction by combining HSI and LiDAR data, which is conducive to extracting joint spatial, spectral, and elevation features from different source data. Furthermore, in order to construct local–global nonlinear feature mapping more flexibly, a network architecture coupling together multiscale convolution and a multiscale vision transformer is proposed. Moreover, a plug-and-play nonlocal feature token aggregation module is designed to adaptively adjust the domain offsets between different features, while a class token is employed to reduce the complexity of high-dimensional feature fusion. On three open-source remote sensing datasets, the performance of the proposed multisource fusion classification framework improves about 1% to 3% over other state-of-the-art algorithms.
Research on Financial Poverty Alleviation Aid for Increasing the Incomes of Low-Income Chinese Farmers
Authors: Pan Huibo , Yao Lili , Zhang Chenhe , Zhang Yuchi , Gao Yuying
Published: January 2024

Unlike the definition of absolute poverty in international society, rural poverty in China is characterized by farmers’ low ability to increase their income, and the unsustainability of income increases. This study examines farming households’ issues with increasing their incomes via financial aid from the International Fund for Agricultural Development (IFAD). Through quantile regression and stepwise regression models, this paper studies two ways in which IFAD loan projects can affect farmers’ income: by directly promoting increases in farmers’ income and by indirectly promoting increases in farmers’ income through newly operational agricultural entities. This paper uses the entropy weight and comprehensive evaluation methods to construct an IFAD evaluation index system to evaluate the endogenous development ability of farmers participating in IFAD loan projects. Our empirical results show that IFAD projects significantly and positively affect farmers’ income. Our heterogeneity analysis shows that IFAD projects have varied effects on farmers’ income growth at different income levels; the lower the income level, the more pronounced the promotion. IFAD loan projects promote farmers’ incomes through newly operational agricultural entities, the mechanism of which is their ESG performances. On average, the anti-poverty masses and areas participating in IFAD loan projects show a robust endogenous development impetus.
Integrating Cargo Bikes and Drones into Last-Mile Deliveries: Insights from Pilot Deliveries in Five Greek Cities
Authors: Athanasopoulos Konstantinos , Chatziioannou Ioannis , Boutsi Argyro-Maria , Tsingenopoulos Georgios , Soile Sofia , Chliverou Regina , Petrakou Zoe , Papanikolaou Efstathios , Karolemeas Christos , Kourmpa Efthymia , Papadaki Kalliopi , Tzika Eleftheria , Ioannidis Charalabos , Potsiou Chryssy , Vlastos Thanos
Published: January 2024

Currently, there is a growing consensus that the use of more sustainable urban freight transportation has the potential to offer major energy and efficiency benefits which can be achieved through the appropriate combination of cargo bikes and the integration of drones into the urban logistics system. This study presents the results of a stepwise regression analysis that examines the role, benefits, and impact of electric vehicles such as e-bikes, cargo bikes, and drones for intermodal freight transportation in five Greek cities to support the green logistics paradigm. The results show that between routes of almost equal length, the most bicycle-friendly routes, such as routes along pedestrian areas or residential streets, should be avoided, as they reduce delivery speed and increase delivery costs in terms of energy and time expenditure. In addition, priority roads, which usually have higher traffic speeds and more trucks, are preferred by cyclists due to the quality of the road surface, even though the feeling of safety is lower on such roads. Finally, regarding drones, energy consumption is relatively low in the 0–5 mph and 6–10 mph wind speed ranges, indicating efficient energy use. In the 11–15 mph and 16–20 mph wind speed ranges, energy efficiency is significantly lower than the battery capacity, indicating that the cargo drone exhibits excessive energy consumption under these conditions.
Hot In-Place Recycled Asphalt Mixtures: RAP Analysis, Compaction Characteristics and Field Evaluation
Authors: Wang Teng , Zhao Xin , Zheng Lele , Mao Chengxin , Wang Li , Falchetto Augusto Cannone , Guo Dedong
Published: January 2024

The substantial accumulation of reclaimed asphalt pavement (RAP) poses a pressing issue in road construction. The hot in-place recycling (HIR) technique has garnered widespread attention due to its high recycling rates of RAP and minimal environmental hazards. This study focuses on the RAP analysis, compaction characteristics, and field evaluation of hot in-place recycled asphalt pavements (HIRAP). Firstly, a novel test method of RAP analysis was proposed to evaluate the suitability of RAP. Subsequently, compaction tests reveal the compaction characteristics of hot in-place recycled asphalt mixture (HIRAM). Finally, the field performance of HIRAP was assessed. The research findings indicate that the RAP analysis method can accurately characterize the status of RAP. Increasing the RAP temperature improves the compaction characteristics of HIRAM. The field tests show that using HIR technology improves the performance of the pavement, in particular with a compaction of 99.7%. This study will establish a theoretical foundation for further promoting the HIR technique.
Do Sustainably Reared Marine Sponges Represent A Potential New Product in Aquariology? A Citizen Science-Based Approach
Authors: Aguilo-Arce Joseba , Schiavo Antonella , Trani Roberta , Longo Caterina
Published: January 2024

Marine sponges have historically been targeted for different purposes, mainly as bath sponges or more recently as a source of bioactive metabolites. However, their use as ornamental species for aquariology is less thoroughly studied. In light of the rise in the importance of sustainable production systems and to valorize the biomass obtained from them, this work assessed the market potential of sustainably reared marine sponges in Italian aquariology. Information was obtained by means of an anonymous questionnaire distributed using social media and printed QR codes targeting Italian aquariophily groups. A total of 101 people from almost all Italian regions participated in the study. Among the people with marine aquariums, almost two-thirds had marine sponges (obtained mainly from fishing discards and trusted shops), and those without them stated that there was no availability in the specialized shops. However, when people were asked about a hypothetical change in purchase intention or frequency of these invertebrates, 68.3% of the respondents showed a positive attitude toward the idea of acquisition. This study constitutes the first preliminary assessment of the valorization potential for sustainably cultivated sponges as ornamental species, which shows a promising prospective in the Italian aquariology sector.
Disparities in Urban Park Visitation Patterns among Socioeconomically Vulnerable Communities during the COVID-19 Pandemic
Authors: Lee Jae Ho , Ahn Yonghan , Kang Dongryeol , Kim Hyunsik
Published: January 2024

Urban parks played an important role during the COVID-19 pandemic among urban dwellers. Numerous studies have shown that park visitations increased or decreased during the pandemic depending on the parks’ contexts, locations, and populations. However, a lack of research has been conducted regarding the impact of COVID-19 on vulnerable and non-vulnerable communities. Therefore, this study seeks to identify the differences between socioeconomic levels in responses to COVID-19′s impact on urban park visits. To observe park users’ movements in real-world scenarios, mobile signaling data were used to capture their movements. Then, using Repeated Measures ANOVA (RM ANOVA), the effectiveness of park visit patterns was statistically verified by considering two variables: “time” and “vulnerability”. The results showed that park visits increased during the early stages of the COVID-19 pandemic regardless of the vulnerability. As COVID-19 spread, underserved communities experienced decreased park visits, demonstrating park inequality after the pandemic. The comparisons in this study provide recommendations for park managers and policymakers in terms of reducing park inequality.
Creating Mortars through the Alkaline Activation of Ceramic Waste from Construction: Case Studies on Their Applicability and Versatility in Conservation
Authors: Fugazzotto Maura , Mazzoleni Paolo , Stroscio Antonio , Barone Germana
Published: January 2024

This paper aimed to investigate the possibility of using alkaline-based binders made from the industrial waste produced by ceramic tiles in the field of conservation and the restoration of monuments and archaeological heritage. Geopolymer mortars, which are environmentally sustainable products obtained by chemical consolidation at room temperature, are studied for their versatility in applications as reintegration or bedding mortars and pre-cast elements, namely bricks, tiles or missing parts for archaeological pottery, as an alternative to traditional not sustainable products. Starting from a well-established formulation, the function of the product, meaning its technical characteristics and its workability, was optimized by changing the aggregates used, by adding a Ca-rich compound or by changing the liquid/solid ratio with the use of tap water. The possibility of tailoring the finishing of the obtained products was also evaluated. X-ray diffraction analysis showed the influence of adding the additive with the presence of newly formed phases, which positively affect the product’s workability. On the contrary, no important variations were observed with the increase in the water content of the same formulation, opening up the possibility of managing it according to the required fluidity of the final product. Good results were observed, jumping above the laboratory scale and overcoming criticalities linked to the variabilities on site and the higher volume of materials used for industrial processes. The present research also demonstrates that ceramic-based geopolymers are suitable for application in a large variety of cultural heritage projects and with different purposes. Therefore, the paper encourages the use of alkali-activated mortars for green restoration, specifically given the wide range of ceramic materials.