bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mapping annual 10-m soybean cropland with spatiotemporal sample migration
Authors: Zhang Hongchi , Lou Zihang , Peng Dailiang , Zhang Bing , Luo Wang , Huang Jianxi , Zhang Xiaoyang , Yu Le , Wang Fumin , Huang Linsheng , Liu Guohua , Gao Shuang , Hu Jinkang , Yang Songlin , Cheng Enhui 
Published: May 2024

AbstractChina, as the world’s biggest soybean importer and fourth-largest producer, needs accurate mapping of its planting areas for global food supply stability. The challenge lies in gathering and collating ground survey data for different crops. We proposed a spatiotemporal migration method leveraging vegetation indices’ temporal characteristics. This method uses a feature space of six integrals from the crops’ phenological curves and a concavity-convexity index to distinguish soybean and non-soybean samples in cropland. Using a limited number of actual samples and our method, we extracted features from optical time-series images throughout the soybean growing season. The cloud and rain-affected data were supplemented with SAR data. We then used the random forest algorithm for classification. Consequently, we developed the 10-meter resolution ChinaSoybean10 maps for the ten primary soybean-producing provinces from 2019 to 2022. The map showed an overall accuracy of about 93%, aligning significantly with the statistical yearbook data, confirming its reliability. This research aids soybean growth monitoring, yield estimation, strategy development, resource management, and food scarcity mitigation, and promotes sustainable agriculture.
Exploration of the photothermal role of curcumin-loaded targeted carbon nanotubes as a potential therapy for melanoma cancer
Authors: Kargar Bahareh , Fazeli Mehdi , Sobhani Zahra , Hosseinzadeh Saeid , Solhjoo Aida , Akbarizadeh Amin Reza 
Published: May 2024

AbstractIn this research, the hydrophilic structure of multi-walled carbon nanotubes (MWCNTs) was modified by synthesizing polycitric acid (PCA) and attaching folic acid (FA) to create MWCNT–PCA–FA. This modified nanocomplex was utilized as a carrier for the lipophilic compound curcumin (Cur). Characterization techniques including TGA, TEM, and UV–visible spectrophotometry were used to analyze the nanocomplex. The mechanism of cancer cell death induced by MWCNT–PCA–FA was studied extensively using the MTT assay, colony formation analysis, cell cycle assessment via flow cytometry, and apoptosis studies. Furthermore, we assessed the antitumor efficacy of these targeted nanocomplexes following exposure to laser radiation. The results showed that the nanocomposites and free Cur had significant toxicity on melanoma cancer cells (B16F10 cells) while having minimal impact on normal cells (NHDF cells). This selectivity for cancerous cells demonstrates the potential of these compounds as therapeutic agents. Furthermore, MWCNT–PCA–FA/Cur showed superior cytotoxicity compared to free Cur alone. Colony formation studies confirmed these results. The researchers found that MWCNT–FA–PCA/Cur effectively induced programmed cell death. In photothermal analysis, MWCNT–PCA–FA/Cur combined with laser treatment achieved the highest mortality rate. These promising results suggest that this multifunctional therapeutic nanoplatform holds the potential for combination cancer therapies that utilize various established therapeutic methods.
The effects of probiotics supplementation on Helicobacter pylori standard treatment: an umbrella review of systematic reviews with meta-analyses
Authors: Yang Zihan , Zhou Yueyang , Han Ziying , He Kun , Zhang Yuelun , Wu Dong , Chen Hongda 
Published: May 2024

AbstractHelicobacter pylori infection, a worldwide health issue, is typically treated with standard antibiotic therapies. However, these treatments often face resistance and non-compliance due to side effects. In this umbrella review, we aimed to comprehensively assess the impact of probiotics supplementation in different preparations on Helicobacter pylori standard treatment. We searched PubMed, Embase and Cochrane Central Register of Controlled Trials in the Cochrane Library from inception to June 1, 2023, to identify systematic reviews with meta-analyses that focused on eradication rates, total side effects and other outcomes of interest. The most comprehensive meta-analysis was selected for data extraction. AMSTAR 2 was used to assess quality of meta-analyses. Overall, 28 unique meta-analyses based on 534 RCTs were included. The results suggests that probiotics supplementation with pooled probiotic strains was significantly associated with improved eradication rates (RR 1.10, 95% CI 1.06–1.14) and reduced risk of total side effects (RR 0.54, 95% CI 0.42–0.70) compared with standard therapy alone. Single-strained or multi-strained preparation of probiotics supplementation showed similar results. Despite Bifidobacterium spp. showing the highest potential for eradication, the study quality was critically low for most meta-analyses, necessitating further high-quality research to explore the optimal probiotic strains or their combinations for Helicobacter pylori treatment.aq_start?>Kindly check and confirm the edit made in article title.
The fine line between automation and augmentation in website usability evaluation
Authors: Esposito Andrea , Desolda Giuseppe , Lanzilotti Rosa 
Published: May 2024

AbstractArtificial Intelligence (AI) systems are becoming widespread in all aspects of society, bringing benefits to the whole economy. There is a growing understanding of the potential benefits and risks of this type of technology. While the benefits are more efficient decision processes and industrial productivity, the risks may include a potential progressive disengagement of human beings in crucial aspects of decision-making. In this respect, a new perspective is emerging that aims at reconsidering the centrality of human beings while reaping the benefits of AI systems to augment rather than replace professional skills: Human-Centred AI (HCAI) is a novel framework that posits that high levels of human control do not contradict high levels of computer automation. In this paper, we investigate the two antipodes, automation vs augmentation, in the context of website usability evaluation. Specifically, we have analyzed whether the level of automation provided by a tool for semi-automatic usability evaluation can support evaluators in identifying usability problems. Three different visualizations, each one corresponding to a different level of automation, ranging from a full-automation approach to an augmentation approach, were compared in an experimental study. We found that a fully automated approach could help evaluators detect a significant number of medium and high-severity usability problems, which are the most critical in a software system; however, it also emerged that it was possible to detect more low-severity usability problems using one of the augmented approaches proposed in this paper.
Heteroepitaxial GaAs thin-films on flexible, large-area, single-crystal-like substrates for wide-ranging optoelectronic applications
Authors: Radhakrishnan Gokul , Kim Kyunghoon , Droopad Ravi , Goyal Amit 
Published: May 2024

AbstractRecent advances in semiconductor based electronic devices can be attributed to the technological demands of ever increasing, application specific markets. These rapidly evolving markets for devices such as displays, wireless communication, photovoltaics, medical devices, etc. are demanding electronic devices that are increasingly thinner, smaller, lighter and flexible. High-quality, III-V epitaxial thin-films deposited on single-crystal substrates have yielded extremely high-performance, but are extremely expensive and rigid. Here we demonstrate heteroepitaxial deposition of GaAs thin-films on large-grained, single-crystal-like, biaxially-aligned, flexible, metallic substrates. We use molecular beam epitaxy (MBE) for the controlled growth of high quality GaAs layers on lattice matched Ge capped, flexible metal substrates. The structural, optical, interfacial and electrical characteristics and properties of the heteroepitaxial GaAs layers are analyzed and discussed. The results show that heteroepitaxial GaAs layers with good crystalline and optoelectronic properties can be realized for flexible, III-V based semiconductor devices. III-V materials integrated on large-grained, single-crystal-like, flexible, metallic substrates offer a potential route towards fabrication of large-area, high-performance electronic devices.
Accelerating material property prediction using generically complete isometry invariants
Authors: Balasingham Jonathan , Zamaraev Viktor , Kurlin Vitaliy 
Published: May 2024

AbstractPeriodic material or crystal property prediction using machine learning has grown popular in recent years as it provides a computationally efficient replacement for classical simulation methods. A crucial first step for any of these algorithms is the representation used for a periodic crystal. While similar objects like molecules and proteins have a finite number of atoms and their representation can be built based upon a finite point cloud interpretation, periodic crystals are unbounded in size, making their representation more challenging. In the present work, we adapt the Pointwise Distance Distribution (PDD), a continuous and generically complete isometry invariant for periodic point sets, as a representation for our learning algorithm. The PDD distinguished all (more than 660 thousand) periodic crystals in the Cambridge Structural Database as purely periodic sets of points without atomic types. We develop a transformer model with a modified self-attention mechanism that combines PDD with compositional information via a spatial encoding method. This model is tested on the crystals of the Materials Project and Jarvis-DFT databases and shown to produce accuracy on par with state-of-the-art methods while being several times faster in both training and prediction time.
Combined effect of seasons and life history in an anuran strengthens the response and relationship between their physiology and gut microbiota
Authors: Park Jun-Kyu , Do Yuno 
Published: May 2024

AbstractGut microbiota impact host physiology, though simultaneous investigations in ectothermic vertebrates are rare. Particularly, amphibians may exhibit more complex interactions between host physiology and the effects of gut microbiota due to the combination of seasonal changes and complex life histories. In this study, we assessed the relationships among food resources, gut bacterial communities, and host physiology in frogs (Phelophylax nigromaculatus), taking into account seasonal and life history variations. We found that food sources were not correlated with physiological parameters but had some relationships with the gut bacterial community. Variations in gut bacterial community and host physiology were influenced by the combined effects of seasonal differences and life history, though mostly driven by seasonal differences. An increase in Firmicutes was associated with higher fat content, reflecting potential fat storage in frogs during the non-breeding season. The increase in Bacteroidetes resulted in lower fat content in adult frogs and decreased immunity in juvenile frogs during the breeding season, demonstrating a direct link. Our results suggest that the gut microbiome may act as a link between food conditions and physiological status, and that the combined effect of seasons and life history could reinforce the relationship between gut microbiota and physiological status in ectothermic animals. While food sources may influence the gut microbiota of ectotherms, we contend that temperature-correlated seasonal variation, which predominately influences most ectotherms, is a significant factor.
Cinnamaldehyde ameliorates STZ-induced diabetes through modulation of autophagic process in adipocyte and hepatic tissues on rats
Authors: Ghazal Nesma A. , Agamia Yara T. , Meky Basant K. , Assem Nagwa M. , Abdel-Rehim Wafaa M. , Shaker Sara A. 
Published: May 2024

AbstractType 2 diabetes mellitus is a worldwide public health issue. In the globe, Egypt has the ninth-highest incidence of diabetes. Due to its crucial role in preserving cellular homeostasis, the autophagy process has drawn a lot of attention in recent years, Therefore, the purpose of this study was to evaluate the traditional medication metformin with the novel therapeutic effects of cinnamondehyde on adipocyte and hepatic autophagy in a model of high-fat diet/streptozotocin-diabetic rats. The study was conducted on 40 male albino rats, classified into 2 main groups, the control group and the diabetic group, which was subdivided into 4 subgroups (8 rats each): untreated diabetic rats, diabetic rats received oral cinnamaldehyde 40 mg/kg/day, diabetic rats received oral metformin 200 mg/kg/day and diabetic rats received a combination of both cinnamaldehyde and metformin daily for 4 weeks. The outcomes demonstrated that cinnamaldehyde enhanced the lipid profile and glucose homeostasis. Moreover, Cinnamaldehyde had the opposite effects on autophagy in both tissues; by altering the expression of genes that control autophagy, such as miRNA 30a and mammalian target of rapamycin (mTOR), it reduced autophagy in adipocytes and stimulated it in hepatic tissues. It may be inferred that by increasing the treatment efficacy of metformin and lowering its side effects, cinnamaldehyde could be utilized as an adjuvant therapy with metformin for the treatment of type 2 diabetes.
Control strategy for current limitation and maximum capacity utilization of grid connected PV inverter under unbalanced grid conditions
Authors: Joshi Jyoti , Jately Vibhu , Kala Peeyush , Sharma Abhishek , Lim Wei Hong , Azzopardi Brian 
Published: May 2024

AbstractUnder grid voltage sags, over current protection and exploiting the maximum capacity of the inverter are the two main goals of grid-connected PV inverters. To facilitate low-voltage ride-through (LVRT), it is imperative to ensure that inverter currents are sinusoidal and remain within permissible limits throughout the inverter operation. An improved LVRT control strategy for a two-stage three-phase grid-connected PV system is presented here to address these challenges. To provide over current limitation as well as to ensure maximum exploitation of the inverter capacity, a control strategy is proposed, and performance the strategy is evaluated based on the three generation scenarios on a 2-kW grid connected PV system. An active power curtailment (APC) loop is activated only in high power generation scenario to limit the current’s amplitude below the inverter’s rated current. The superior performance of the proposed strategy is established by comparison with two recent LVRT control strategies. The proposed method not only injects necessary active and reactive power but also minimizes overcurrent with increased exploitation of the inverter’s capacity under unbalanced grid voltage sag.
Multiscale and multimodal imaging for three-dimensional vascular and histomorphological organ structure analysis of the pancreas
Authors: Salg Gabriel Alexander , Steinle Verena , Labode Jonas , Wagner Willi , Studier-Fischer Alexander , Reiser Johanna , Farjallah Elyes , Guettlein Michelle , Albers Jonas , Hilgenfeld Tim , Giese Nathalia A. , Stiller Wolfram , Nickel Felix , Loos Martin , Michalski Christoph W. , Kauczor Hans-Ulrich , Hackert Thilo , Dullin Christian , Mayer Philipp , Kenngott Hannes Goetz 
Published: May 2024

AbstractExocrine and endocrine pancreas are interconnected anatomically and functionally, with vasculature facilitating bidirectional communication. Our understanding of this network remains limited, largely due to two-dimensional histology and missing combination with three-dimensional imaging. In this study, a multiscale 3D-imaging process was used to analyze a porcine pancreas. Clinical computed tomography, digital volume tomography, micro-computed tomography and Synchrotron-based propagation-based imaging were applied consecutively. Fields of view correlated inversely with attainable resolution from a whole organism level down to capillary structures with a voxel edge length of 2.0 µm. Segmented vascular networks from 3D-imaging data were correlated with tissue sections stained by immunohistochemistry and revealed highly vascularized regions to be intra-islet capillaries of islets of Langerhans. Generated 3D-datasets allowed for three-dimensional qualitative and quantitative organ and vessel structure analysis. Beyond this study, the method shows potential for application across a wide range of patho-morphology analyses and might possibly provide microstructural blueprints for biotissue engineering.
Statistical downscaling of GRACE terrestrial water storage changes based on the Australian Water Outlook model
Authors: Kalu Ikechukwu , Ndehedehe Christopher E. , Ferreira Vagner G. , Janardhanan Sreekanth , Currell Matthew , Kennard Mark J. 
Published: May 2024

AbstractThe coarse spatial resolution of the Gravity Recovery and Climate Experiment (GRACE) dataset has limited its application in local water resource management and accounting. Despite efforts to improve GRACE spatial resolution, achieving high resolution downscaled grids that correspond to local hydrological behaviour and patterns is still limited. To overcome this issue, we propose a novel statistical downscaling approach to improve the spatial resolution of GRACE-terrestrial water storage changes (ΔTWS) using precipitation, evapotranspiration (ET), and runoff data from the Australian Water Outlook. These water budget components drive changes in the GRACE water column in much of the global land area. Here, the GRACE dataset is downscaled from the original resolution of 1.0° × 1.0° to 0.05° × 0.05° over a large hydro-geologic basin in northern Australia (the Cambrian Limestone Aquifer—CLA), capturing sub- grid heterogeneity in ΔTWS of the region. The downscaled results are validated using data from 12 in-situ groundwater monitoring stations and water budget estimates of the CLA’s land water storage changes from April 2002 to June 2017. The change in water storage over time (ds/dt) estimated from the water budget model was weakly correlated (r = 0.34) with the downscaled GRACE ΔTWS. The weak relationship was attributed to the possible uncertainties inherent in the ET datasets used in the water budget, particularly during the summer months. Our proposed methodology provides an opportunity to improve freshwater reporting using GRACE and enhances the feasibility of downscaling efforts for other hydrological data to strengthen local-scale applications.
AAGCN: a graph convolutional neural network with adaptive feature and topology learning
Authors: Wang Bin , Cai Bodong , Sheng Jinfang , Jiao Wenzhe 
Published: May 2024

AbstractIn recent years, there has been a growing prevalence of deep learning in various domains, owing to advancements in information technology and computing power. Graph neural network methods within deep learning have shown remarkable capabilities in processing graph-structured data, such as social networks and traffic networks. As a result, they have garnered significant attention from researchers.However, real-world data often face challenges like data sparsity and missing labels, which can hinder the performance and generalization ability of graph convolutional neural networks. To overcome these challenges, our research aims to effectively extract the hidden features and topological information of graph convolutional neural networks. We propose an innovative model called Adaptive Feature and Topology Graph Convolutional Neural Network (AAGCN). By incorporating an adaptive layer, our model preprocesses the data and integrates the hidden features and topological information with the original data’s features and structure. These fused features are then utilized in the convolutional layer for training, significantly enhancing the expressive power of graph convolutional neural networks.To evaluate the effectiveness of the adaptive layer in the AAGCN model, we conducted node classification experiments on real datasets. The results validate its ability to address data sparsity and improve the classification performance of graph convolutional neural networks.In conclusion, our research primarily focuses on addressing data sparsity and missing labels in graph convolutional neural networks. The proposed AAGCN model, which incorporates an adaptive layer, effectively extracts hidden features and topological information, thereby enhancing the expressive power and classification performance of these networks.
Autocorrelation analysis of a phenotypic screen reveals hidden drug activity
Authors: Dubach Richard A. , Dubach J. Matthew 
Published: May 2024

AbstractPhenotype based screening is a powerful tool to evaluate cellular drug response. Through high content fluorescence imaging of simple fluorescent labels and complex image analysis phenotypic measurements can identify subtle compound-induced cellular changes unique to compound mechanisms of action (MoA). Recently, a screen of 1008 compounds in three cell lines was reported where analysis detected changes in cellular phenotypes and accurately identified compound MoA for roughly half the compounds. However, we were surprised that DNA alkylating agents and other compounds known to induce or impact the DNA damage response produced no measured activity in cells with fluorescently labeled 53BP1—a canonical DNA damage marker. We hypothesized that phenotype analysis is not sensitive enough to detect small changes in 53BP1 distribution and analyzed the screen images with autocorrelation image analysis. We found that autocorrelation analysis, which quantifies fluorescently-labeled protein clustering, identified higher compound activity for compounds and MoAs known to impact the DNA damage response, suggesting altered 53BP1 recruitment to damaged DNA sites. We then performed experiments under more ideal imaging settings and found autocorrelation analysis to be a robust measure of changes to 53BP1 clustering in the DNA damage response. These results demonstrate the capacity of autocorrelation to detect otherwise undetectable compound activity and suggest that autocorrelation analysis of specific proteins could serve as a powerful screening tool.
Harnessing eDNA metabarcoding to investigate fish community composition and its seasonal changes in the Oslo fjord
Authors: Carvalho Cintia Oliveira , Gromstad William , Dunthorn Micah , Karlsen Hans Erik , Schrøder-Nielsen Audun , Ready Jonathan Stuart , Haugaasen Torbjørn , Sørnes Grete , de Boer Hugo , Mauvisseau Quentin 
Published: May 2024

AbstractIn the face of global ecosystem changes driven by anthropogenic activities, effective biomonitoring strategies are crucial for mitigating impacts on vulnerable aquatic habitats. Time series analysis underscores a great significance in understanding the dynamic nature of marine ecosystems, especially amidst climate change disrupting established seasonal patterns. Focusing on Norway's Oslo fjord, our research utilises eDNA-based monitoring for temporal analysis of aquatic biodiversity during a one year period, with bi-monthly sampling along a transect. To increase the robustness of the study, a taxonomic assignment comparing BLAST+ and SINTAX approaches was done. Utilising MiFish and Elas02 primer sets, our study detected 63 unique fish species, including several commercially important species. Our findings reveal a substantial increase in read abundance during specific migratory cycles, highlighting the efficacy of eDNA metabarcoding for fish composition characterization. Seasonal dynamics for certain species exhibit clear patterns, emphasising the method's utility in unravelling ecological complexities. eDNA metabarcoding emerges as a cost-effective tool with considerable potential for fish community monitoring for conservation purposes in dynamic marine environments like the Oslo fjord, contributing valuable insights for informed management strategies.