bluuebunny/crossref_metadata_2025_split huggingface dataset:
Public, Private and Public-Private Partnerships (PPP) to Implement a One Health Approach to Combat Antimicrobial Resistance in Colombia
Authors: Cediel-Becerra Natalia , Rodriguez-Moreno Marcela , Germán A. , Chair Vasquez N. , Collins Roseanna 
Published: November 2024

Abstract
The establishment of public-private partnerships (PPPs) within Colombia, Latin America, is a recent, innovative effort within the nation’s agricultural industry to tackle antimicrobial resistance (AMR) under a One Health approach. PPPs are a formal alliance between representatives from the public and private sectors that aim to promote cross-sectoral collaboration, stewardship and accountability. Members agree on shared objectives and responsibilities, resources and risks to establish monitoring, prevention and mitigation activities against AMR within the farming industry. Key learnings of this initiative within the context of Colombia include: maximisation of results when monitoring is assigned to the private sector, and this may apply to other lower-middle-income countries (LMICs); objectives are better achieved when they are pre-defined according to time, budget and human resource constraints of member institutions; and confidentiality agreements must be consistent with the sensitive nature of surveillance information. Barriers to implementation were also identified, such as frequent changes of government personnel at decision making levels that make governance planning and adaptation challenging, while legal formalities and bureaucracy hinder formalisation of agreements. The success of this PPP is a useful example for other LMICs to aid in the control and prevention of animal diseases, promotion of food safety and reduction in poor animal health which limit commerce, while at the same time, minimising production loss and ensuring the provision of a fair income for producers.

Information
© The Authors 2024
Wheat Leaf Rust, Caused by
Puccinia triticina
, and Mitigation Through Host Genetic Resistance
Authors: McCallum Brent , Hiebert Colin , Wang Xiben , Bakkeren Guus 
Published: November 2024

Abstract

The obligate fungal pathogen
Puccinia triticina
causes leaf rust symptoms on wheat worldwide. Epidemics of leaf rust occur during periods of mild weather with high relative humidity. The pathogen infects leaves, causing orange to red pustules, containing millions of urediniospores, reducing the photosynthetic area and causing desiccation and yield loss. Wind-borne urediniospores are produced in continuous asexual cycles on wheat plants. Genetic resistance is the primary control strategy. There are over 80 known leaf rust (
Lr
) resistance genes, and most are race-specific and are active from the seedling stage to maturity. A few
Lr
genes are nonrace-specific and confer partial resistance to leaf rust and other diseases at the adult plant stage. Combining
Lr
genes that confer seedling and adult plant resistance has been particularly successful and durable. Pathogen populations are genetically diverse, and races evolve continuously to evade recognition by
Lr
genes. This results in boom-and-bust cycles when new cultivars with race-specific
Lr
genes are resistant for some years, but become susceptible, due to evolution of the
P. triticina
population. Surveillance of
P. triticina
for the evolution of races helps to develop wheat cultivars with
Lr
genes that will be resistant to the most prevalent races.

Information
© The Authors 2024
Multiple crossings during dynamical symmetry restoration and implications for the quantum Mpemba effect
Authors: Chalas Konstantinos , Ares Filiberto , Rylands Colin , Calabrese Pasquale 
Published: November 2024

Abstract
Local relaxation after a quench in 1D quantum many-body systems is a well-known and very active problem with rich phenomenology. Except in pathological cases, the local relaxation is accompanied by the local restoration of the symmetries broken by the initial state that are preserved by unitary evolution. Recently, the entanglement asymmetry has been introduced as a probe to study the interplay between symmetry breaking and relaxation in an extended quantum system. In particular, using the entanglement asymmetry, it has been shown that the more a symmetry is initially broken, the faster it may be restored. This surprising effect, which has also been observed in trapped-ion experiments, can be seen as a quantum version of the Mpemba effect, and is manifested by the crossing at a finite time of the entanglement asymmetry curves of two different initial symmetry-breaking configurations. In this paper we show that, by tuning the initial state, the symmetry dynamics in free fermionic systems can display much richer behavior than seen previously. In particular, for certain classes of initial states, including the ground states of free fermionic models with long-range couplings, the entanglement asymmetry can exhibit multiple crossings. This illustrates that the existence of the quantum Mpemba effect can only be inferred by examining the late-time behavior of the entanglement asymmetry.
Optimization of Thermal and Rheological Performance in Non-Polar Binary Fluids Using Hybrid CuO Nanoparticles
Authors: Rohini B , Kingson Solomon Jeevaraj A , Suvitha A , Sangeetha R , Revathi V 
Published: November 2024

Abstract
Nanofluid is a novel type of technological fluid with numerous applications. Copper oxide (CuO) nanoparticles were dispersed in the binary fluids (Cyclohexane + Diethyl amine (DEA) and (1-4 dioxane + DEA) to create a nonpolar hybrid CuO nanofluid. The thermal conductivity (K) and viscosity (ῃ) of a nonpolar hybrid CuO nanofluid were determined at low concentrations (0.01M to 0.06M) and temperatures ranging from 298K to 318K. The transient hotwire approach is utilized for K measurements, while the viscometer is employed for viscosity measurements. As concentration increases, K drops, yet there is an increase owing to uniform variance in temperatures (T).ῃ changes with concentration and temperature. The results show that the hybrid CuO nanofluid has a phenomenal heat transfer improvement compared to the binary mixtures. The non-polar hybrid CuO nanofluid’s thermal conductivity increases by 15% to 20%, while its viscosity increases by 18% to 25%.
Eliminating metal artifacts in dental computed tomography using an elaborate sinogram normalization interpolation method with CNR-based metal segmentation
Authors: Lim Younghwan , Park Sungmin , Jeon Duhee , Kim Woosung , Lee Soohyun , Cho Hyosung 
Published: November 2024

Abstract
Metal artifact reduction (MAR) in dental cone-beam computed tomography (CBCT) is critical for improving its clinical usefulness and remains a challenging problem. This study presents an elaborate sinogram normalization interpolation (SNI) method with contrast-to-noise ratio (CNR)-based metal segmentation to eliminate metal artifacts in dental CBCT. The proposed MAR method involves three main steps: (1) CNR-based segmentation of a metal trace in the sinogram domain; (2) generation of a residual artifact-reduced prior sinogram; and (3) sinogram completion using the prior sinogram, followed by filtered-backprojection (FBP)-based CBCT reconstruction and metal insertion processes. To verify the efficacy of the proposed method, simulations and experiments were performed using numerical and physical dental phantoms with several metal inserts. The quality of the resulting CBCT images was quantitatively evaluated using the structural similarity (SSIM) metric and compared to those obtained with other interpolation-based MAR methods. A tabletop setup for the micro-CT system was used in the experiment, which comprised an X-ray tube operated under tube conditions of 70 kV
p
and 5 mA and a flat-panel detector with a pixel size of 198 μm. Our results indicate that the CNR-based metal segmentation method precisely identified traces of metallic objects on the sinogram, and thereby, the proposed SNI-based MAR method considerably reduced metal artifacts in dental CBCT images without introducing any contrast anomalies. The SSIM values of the CBCT images obtained with the proposed MAR method were 0.99 and 0.95 for the simulation and experiment, respectively, which are approximately 11% and 9% greater than those with a simple threshold-based linear interpolation method, respectively, improving the image quality. The proposed MAR method can be applied to reduce metal artifacts in real-world dental CBCT systems.
Spatial Variation of Pollutant (NO2, SO2 & CO) and Its Impact Factors in Jakarta: An Application of Sentinel-5P Products
Authors: Iqbal M. , Susilo Bowo , Hizbaron D.R 
Published: November 2024

Abstract
This study investigates the impact of transportation, manufacturing, and energy sectors on air quality in Jakarta using Geographically Weighted Regression (GWR) and remote sensing data. Utilizing datasets from Sentinel-5P for NO2, SO2, and CO concentrations, and predictor variables including road density, industrial activity, and energy production, the research aims to quantify the spatial heterogeneity of air pollution. The findings reveal significant spatial variations in pollutant concentrations across Jakarta and its neighbouring provinces, Banten and West Java, during the dry and wet months of 2023. High NO2 levels were primarily linked to dense traffic in central Jakarta, while elevated SO2 and CO concentrations were associated with industrial and energy activities in the peripheral regions. Seasonal analysis indicated that meteorological factors play a crucial role in pollutant dispersion. The integration of remote sensing data with GWR provided a robust framework for environmental monitoring, addressing gaps in traditional air quality observation methods. This research contributes to the broader understanding of urban air pollution dynamics and offers a replicable model for other regions facing similar challenges.
Application and Impact of Automation in Crimping Processes
Authors: Dacian Ilca , Tiberiu Manescu , Gilbert-Rainer Gillich 
Published: November 2024

Abstract
This paper investigates the Subassembly Process Automation (SPA) program’s application and impact on industrial manufacturing processes, particularly underscoring its efficacy in refining production accuracy and efficiency. It explores SPA’s systematic advancements and the incorporation of meticulous quality control strategies, focusing on how it streamlines operations, boosts efficiency, and ensures adherence to industry norms. The SPA program integrates automation for comprehensive process oversight, including job initiation, ongoing production, and critically, scrap reduction, thereby markedly diminishing waste and upholding rigorous quality standards. Offering an indepth evaluation of SPA’s capabilities, the paper illustrates its role in enhancing production flow and supporting environmental sustainability through effective scrap management. By analysing its implementation in crimping operations, from equipment preparation to production execution, the research highlights SPA’s essential contribution to reducing errors, maximizing resource efficiency, and maintaining exceptional manufacturing quality.
Crimp Height influence over Resistivity in Wiring Crimping Process
Authors: Dragomir Florin , Tiberiu Manescu , Gilbert-Rainer Gillich 
Published: November 2024

Abstract
The main purpose of this paper is to present the influence between the crimp height and the resistivity for a crimp joint between a copper contact and a wire copper stranded cable using statistical relevant analysis. The experiment followed the analysis of 45 crimped assemblies grouped in 3 main categories to simulate a potential validation procedure according to the international validation process requirements from: DIN (“Deutsches Institut fu r Normung”) with the corresponding Romanian standard SR EN 60352-2:2006 and SAE/USCAR-21 REVISION 3. The baseline used was the behaviour of the resistivity versus the pre-set crimp height of the crimped joints before and after thermal shock test to enable us to conclude if we have a significant relation between the crimp height of the assembly joint and the resistivity.
Quality Assessment of Aluminum Alloys for Automotive Rims
Authors: Sapta Doru , Socalici Ana , Birtok Baneasa Corneliu , Putan Vasile 
Published: November 2024

Abstract
This paper presents experimental research conducted at a factory specializing in the development of aluminum alloys and the semi-continuous production of bars intended for rim manufacturing. The semi-finished products are made of 6082 aluminum alloy and undergo forging processes to obtain rims. The charge load consists of various types of aluminum waste and primary aluminum in different proportions, depending on the quality of the waste in the experimental recipes. The elaboration of the aluminum alloy takes place in melting furnaces with a capacity of 80 tons, equipped with two chambers. The casting is performed using a semi-continuous casting installation, and the cast semi-finished products undergo further heat treatment. The casting process involves the addition of alloying elements, in the form of wire, which serve to refine the structure. Experimental data were processed, and correlations between the qualitative characteristics of the alloy and the elements in the chemical composition, as well as grain size, were analyzed. From the obtained correlation analysis, it is observed that the alloying elements refine the grain size, while the grain size and quality of the resulting product are of interest for industrial practice.
Influence of curing time and temperature on the mechanical properties of resins manufactured through stereolithography
Authors: Coșa Alexandru-Viorel , Baban Marian-Vasile , Șerban Dan-Andrei 
Published: November 2024

Abstract
Additive manufacturing technologies are widely used and provide unique advantages over other manufacturing techniques. However, to achieve the optimal properties of an additive manufactured product, knowledge about the specific tool and parameters is required. A suitable approach to understand the parameters and the influence on the final properties is to investigate the variations of a mechanical property based on the fluctuation of the manufacturing parameters. This study focuses on determining the influence of the curing temperature and time under UV light (405nm wavelength) on the tensile properties of specimens obtained through stereolithography (SLA). This aspect was attained by manufacturing batches of specimens from a urethane dimethacrylate (UDMA) based resin (commercial name Formlabs Tough 2000®) and then curing them for different periods of time (from uncured up to 180 minutes). The samples were tested and, based on the resulting stiffness and strength, the optimal curing time of 90 minutes was established. The value of this parameter was used to investigate the influence of the temperature at which the specimens are cured, with a variation from 25 °C to 80 °C, resulting with an optimal curing temperature of 60 °C. The study also concluded that after a certain temperature, the stiffness is declining, even though the strength of the specimens reaches a plateau-like region.
Impact of Aging on Tensile Properties of EPDM, TPV, and eco-TPV: A Comparative Study Across Diverse Environments
Authors: Foltuț Daniel , Șoșoi Georgiana-Iulia , Vălean Estera , Pospisil Jan , Pascal Dragoș-Toader , Șerban Viorel-Aurel 
Published: November 2024

Abstract
This study examines the effects of aging on the tensile characteristics of Ethylene Propylene Diene Monomer (EPDM), Thermoplastic Vulcanizates (TPV), and Eco-friendly Thermoplastic Vulcanizates (Eco TPV) in different conditions. The samples underwent thermal aging at a temperature of 90°C and were immersed in sulfuric acid solutions with varying concentrations (1M, 0.1M, and 0.001M) for a duration of 1000 hours at the same temperature. The findings revealed that EPDM demonstrated the maximum tensile strength and a moderate level of elongation and breakage. Furthermore, it retained substantial mechanical integrity after undergoing aging, thereby establishing it as the most resilient material among those evaluated. The thermoplastic vulcanizate (TPV) exhibited intermediate tensile strength and elongation, but experienced significant deterioration when exposed to very acidic environments while Eco TPV had lower tensile strength but good chemical stability. The stress-strain behavior and compression set tests emphasized EPDM’s exceptional durability and ability to recover elastically. The pH measurements of the immersion solutions indicated an elevation caused by the release of alkaline chemicals from the rubber components, especially in the 1M solution.
Vibration behaviour of additively manufactured AlSi10Mg specimens
Authors: Öhl Christian , Linul Emanoil , Valentin Galatanu Sergiu 
Published: November 2024

Abstract
Additive manufacturing is in continuous development, and the obtained components still have some shortcomings. The vast majority of mechanical characterizations are performed on polymer materials, using in particular the material extrusion process, while metallic components face not negligible deficiencies. This paper presents an experimental investigation of the vibration behaviour of selective laser melting (SLM) 3D printed specimens. The specimens were printed “on-edge” from AlSi10Mg aluminium alloys and subjected to fatigue tests. By using an electrodynamic shaker, controller, acceleration transducer, and laser vibrometer, the tests have been performed and the data analysed. After the tests, a correlation was obtained by using a finite element analysis (FEA). The damping coefficients (alpha and beta) are obtained from the experimental data. These coefficients are then used to check the accuracy of each FEA model. The results reveal the correlation between structural damping and anisotropy of additive manufacturing specimens, and their impact on high-cycle fatigue performance.
304L Austenitic Stainless Steel Corrosion Studies in Neutral Environment in Presence of Sulfite Ions
Authors: Lăboșel Mihaela-Alexandra , Rudenko Nataliia , Dima George-Daniel , Laurențiu Dan Mircea , Vaszilcsin Nicolae 
Published: November 2024

Abstract
This paper examined the influence of the sulfite concentration introduced in the electrolyte added to the neutral solution (1 mol L-1 Na2SO4) on the corrosion process of 304L stainless steel material. 304L. The accelerated effect of sulfite ions under corrosion rate of 304L austenitic stainless steel was demonstrated using electrochemical techniques such as linear sweep voltammetry at a low scan rate −1 mV s−1, the Tafel slope method, chronoamperometry, and electrochemical impedance spectroscopy. Electrochemical studies were conducted using a BioLogic SP150 potentiostat/galvanostat.
Stainless steels are the most varied and intricate group among all steels. Among them, 304L austenitic stainless steel is one of the most commonly utilized alloys, prized for its excellent corrosion resistance and strength, hygienic and aesthetic properties, affordability, good formability, and effective weldability. [1-3]. In modern industry, the amount of austenitic stainless steel represents only about 2% of the total steel production manufactured globally. This type of steel is commonly employed in chemical engineering, metal extraction, desalination and wastewater treatment plants, the oil and gas sector, transportation and aerospace industries, the food and beverage sector, as well as in architecture and construction engineering. [1].
Bacterial diversity in rice field soil and sludge soil samples: a comparative metagenomics-based study
Authors: Singh Nidhi , Singh Veer , Mishra Vishal , Chaturvedi Vivek K , Vamanu Emanuel , Singh Mohan P 
Published: November 2024

Abstract
Soil contains several organic, and inorganic substances and a large number of bacterial diversity. This bacterial diversity is also involved in biomass degradation and plant growth promotion. Metagenomic sequencing was used to analyze bacterial diversity in the rice field soil and sludge samples. Amplicon sequencing of the V3-V4 region of the 16S rRNA gene revealed that representative sequences clustered were 0.4 million in both rice and sludge samples. The Venn diagram demonstrates the overall identified OTUs was 359 Operational Taxonomic Units (OTUs). OTUs were classified into more than 30 phyla, 50 classes, and 90 genera. The metagenomic analysis revealed that 82 and 85 taxa are exclusively unique to the bacterial communities of the rice and sludge soils, respectively. The metagenomic study also revealed that Proteobacteria, Bacteroidetes, Chloroflexi, Acidobacteria and other unknown bacteria were reported in 16S rRNA Illumina MiSeq in the sludge and rice soil samples. The most abundant groups in rice field soil were Proteobacteria, Chloroflexi, Acidobacteria, Actinobacteria, and Bacteroidetes which increase the soil nutrient and influence the growth of the plants. Bacteroidetes are the most dominant group in sludge soil than rice field soil. This comparative analysis provides insights into the ecological roles and adaptive strategies of soil bacteria in different environmental contexts, offering valuable information for sustainable soil management and bioremediation practices.
MSMGE-CNN: a multi-scale multi-graph embedding convolutional neural network for motor related EEG decoding
Authors: Wang Binren , Miao Minmin , Zhang Ke , Liu Wenzhe , Sheng Zhenzhen , Xu Baoguo , Hu Wenjun 
Published: November 2024

Abstract
Deep learning technique has been widely used for decoding motor related electroencephalography (EEG) signals, which has considerably driven the development of motor related brain–computer interfaces (BCIs). However, traditional convolutional neural networks (CNNs) cannot fully represent spatial topology information and dynamic temporal characteristics of multi-channel EEG signals, resulting in limited decoding accuracy. To address such challenges, a novel multi-scale multi-graph embedding CNN (MSMGE-CNN) is proposed in this study. The proposed MSMGE-CNN contains two crucial components: multi-scale time convolution and multi-graph embedding. Specifically, we design a multi-branch CNN architecture with mixed-scale time convolutions based on EEGNet to sufficiently extract robust time domain features. Afterward, we embed multi-graph information obtained based on physical distance proximity and functional connectivity of multi-channel EEG signals into the time-domain features to capture rich spatial topological dependencies via multi-graph convolution operation. We extensively evaluated the proposed method on three benchmark EEG datasets commonly used for motor imagery/execution (MI/ME) classification and obtained accuracies of 79.59% (BCICIV-2a Dataset), 69.77% (OpenBMI Dataset) and 96.34% (High Gamma Dataset), respectively. These results powerfully demonstrate that MSMGE-CNN outperforms several state-of-the-art algorithms. In addition, we further conducted a series of ablation experiments to validate the rationality of our network architecture. Overall, the proposed MSMGE-CNN method dramatically improves the accuracy and robustness of MI/ME-EEG decoding, which can effectively enhance the performance of motor related BCI system.