bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fabrication of pure Bi2WO6 and Bi2WO6/MWCNTs nanocomposite as potential antibacterial and anticancer agents
Authors: Rhoomi Zeena R. , Ahmed Duha S. , Jabir Majid S. , Qadeer Abdul , Ismael Alaa B. , Swelum Ayman A. 
Published: April 2024

AbstractAn essential research area for scientists is the development of high-performing, inexpensive, non-toxic antibacterial materials that prevent the transfer of bacteria. In this study, pure Bi2WO6 and Bi2WO6/MWCNTs nanocomposite were prepared by hydrothermal method. A series of characterization results by using XRD FTIR, Raman, FESEM, TEM, and EDS analyses, reveal the formation of orthorhombic nanoflakes Bi2WO6 by the addition of NaOH and pH adjustment to 7. Compared to pure Bi2WO6, the Bi2WO6/MWCNTs nanocomposite exhibited that CNTs are efficiently embedded into the structure of Bi2WO6 which results in charge transfer between metal ion electrons and the conduction or valence band of Bi2WO6 and MWCNTs and result in shifting to longer wavelength as shown in UV–visible and PL. The results confirmed that MWCNTs are stuck to the surface of the microflowers, and some of them embedded inside the Bi2WO6 nanoflakes without affecting the structure of Bi2WO6 nanoflakes as demonstrated by TEM. In addition, Pure Bi2WO6 and the Bi2WO6/MWCNTs nanocomposite were tested against P. mirabilis and S. mutans., confirming the effect of addition MWCNTs materials had better antibacterial activity in opposition to both bacterial strains than pure Bi2WO6. Besides, pure Bi2WO6 and the Bi2WO6/MWCNTs nanocomposite tested for cytotoxicity against lung MTT test on Hep-G2 liver cancer cells, and flow-cytometry. Results indicated that pure Bi2WO6 and the Bi2WO6/MWCNTs nanocomposite have significant anti-cancer efficacy against Hep-G2 cells in vitro. In addition, the findings demonstrated that Bi2WO6 and Bi2WO6/MWCNTs triggered cell death via increasing ROS. Based on these findings, it appears that pure Bi2WO6 and the Bi2WO6/MWCNTs nanocomposite have the potential to be developed as nanotherapeutics for the treatment of bacterial infections, and liver cancer.
Real space iterative reconstruction for vector tomography (RESIRE-V)
Authors: Pham Minh , Lu Xingyuan , Rana Arjun , Osher Stanley , Miao Jianwei 
Published: April 2024

AbstractTomography has had an important impact on the physical, biological, and medical sciences. To date, most tomographic applications have been focused on 3D scalar reconstructions. However, in some crucial applications, vector tomography is required to reconstruct 3D vector fields such as the electric and magnetic fields. Over the years, several vector tomography methods have been developed. Here, we present the mathematical foundation and algorithmic implementation of REal Space Iterative REconstruction for Vector tomography, termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates between the projections and a 3D reconstruction. Each iteration consists of a forward step using the Radon transform and a backward step using its transpose, then updates the object via gradient descent. Incorporating with a 3D support constraint, the algorithm iteratively minimizes an error metric, defined as the difference between the measured and calculated projections. The algorithm can also be used to refine the tilt angles and further improve the 3D reconstruction. To validate RESIRE-V, we first apply it to a simulated data set of the 3D magnetization vector field, consisting of two orthogonal tilt series, each with a missing wedge. Our quantitative analysis shows that the three components of the reconstructed magnetization vector field agree well with the ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D magnetization vector field of a ferromagnetic meta-lattice consisting of three tilt series. Our 3D vector reconstruction reveals the existence of topological magnetic defects with positive and negative charges. We expect that RESIRE-V can be incorporated into different imaging modalities as a general vector tomography method. To make the algorithm accessible to a broad user community, we have made our RESIRE-V MATLAB source codes and the data freely available athttps://github.com/minhpham0309/RESIRE-V.
Increasing obsidian diversity during the Chalcolithic Period at Yeghegis-1 Rockshelter (Armenia) reveals shifts in land use and social networks
Authors: Frahm Ellery , Saribekyan Mariam , Mkrtchyan Satenik , Furquim Laura , Avagyan Ara , Sahakyan Lilit , Azatyan Karen , Roberts Patrick , Fernandes Ricardo , Yepiskoposyan Levon , Amano Noel , Antonosyan Mariya 
Published: April 2024

AbstractThe newly excavated rockshelter of Yeghegis-1 in Armenia reflects an occupation of five centuries, as attested by radiocarbon dates from ∼ 4100 to 4000 cal BCE in the lowest layer to ∼ 3600–3500 cal BCE at the top. It is a partially collapsed cave in which pastoralists, we hypothesize, wintered with their herds. The stone tool assemblage is predominantly obsidian (92.1%), despite the shelter being > 60 km on foot from the nearest sources. We use obsidian sourcing to investigate two purported trends in the Southern Caucasus during the Chalcolithic Period: (1) occupation of more varied high-altitude environments and (2) more expansive social networks. Our data show both trends were dynamic phenomena. There was a greater balance in use of the nearest pasturelands over time, perhaps linked to risk management and/or resource sustainability. During later occupations, artifacts from distant sources reveal more extensive connections. This increase in connectivity likely played a central role in the shifts in societal complexity that gave rise to widely shared material culture throughout the Armenian Highlands around the start of the Early Bronze Age. In such a model, greater social connectivity becomes a key mechanism for, rather than a product of, the spread of cultural and/or technological innovations.
Insights into the genetic architecture of cerebellar lobules derived from the UK Biobank
Authors: Carrión-Castillo Amaia , Boeckx Cedric 
Published: April 2024

AbstractIn this work we endeavor to further understand the genetic architecture of the cerebellum by examining the genetic underpinnings of the different cerebellar lob(ul)es, identifying their genetic relation to cortical and subcortical regions, as well as to psychiatric disorders, as well as traces of their evolutionary trajectories. We confirm the moderate heritability of cerebellar volumes, and reveal genetic clustering and variability across their different substructures, which warranted a detailed analysis using this higher structural resolution. We replicated known genetic correlations with several subcortical volumes, and report new cortico-cerebellar genetic correlations, including negative genetic correlations between anterior cerebellar lobules and cingulate, and positive ones between lateral Crus I and lobule VI with cortical measures in the fusiform region. Heritability partitioning for evolutionary annotations highlighted that the vermis of Crus II has depleted heritability in genomic regions of “archaic introgression deserts”, but no enrichment/depletion of heritability in any other cerebellar regions. Taken together, these findings reveal novel insights into the genetic underpinnings of the different cerebellar lobules.
Investigations on Xenopus laevis body composition and feeding behavior in a laboratory setting
Authors: Böswald Linda F. , Matzek Dana , von La Roche Dominik , Stahr Bianca , Bawidamann Pascal , Popper Bastian 
Published: April 2024

AbstractThe African clawed frog, Xenopus laevis, has been used as a laboratory animal for decades in many research areas. However, there is a lack of knowledge about the nutritional physiology of this amphibian species and the feeding regimen is not standardized. The aim of the present study was to get more insights into the nutrient metabolism and feeding behavior of the frogs. In Trial 1, adult female X. laevis were fed either a Xenopus diet or a fish feed. After 4 weeks, they were euthanized, weighed, measured for morphometrics and dissected for organ weights and whole-body nutrient analysis. There were no significant differences between the diet groups regarding the allometric data and nutrient contents. The ovary was the major determinant of body weight. Body fat content increased with body weight as indicator of energy reserves. In Trial 2, 40 adult female frogs were monitored with a specifically developed digital tracking system to generate heat-maps of their activity before and up to 25 min after a meal. Three diets (floating, sinking, floating & sinking) were used. The main feed intake activity was fanning the feed into the mouth, peaking until 20 min after the meal. The different swimming characteristics of the diets thereby influenced the activity of the animals. Our dataset helps to adjust the feeding needs to the physical composition and also to meet the natural behavioral patterns of feed intake as a prerequisite of animal wellbeing and animal welfare in a laboratory setting.
Breakthrough electroneutron multi-response miniature dosimetry/spectrometry in medical accelerator
Authors: Sohrabi Mehdi , Malekitakbolagh Maryam , Nedaei Hasan Ali 
Published: April 2024

AbstractBreakthrough multi-response miniature dosimetry/spectrometry of electroneutrons (EN) was made on surface and in-depths of whole-body polyethylene phantom under 10 cm × 10 cm electron beam of 20 MV Varian Clinac 2100C electron medical accelerator commonly applied for prostate treatment. While dosimetry/spectrometry of photoneutrons (PN) has been well characterized for decades, those of ENs lagged behind due to very low EN reaction cross section and lack of sensitive neutron dosimeters/spectrometers meeting neutron dosimetry requirements. Recently, Sohrabi “miniature neutron dosimeter/spectrometer” and “Stripe polycarbonate dosimeter” have broken this barrier and determined seven EN ambient dose equivalent (ENDE) (µSv.Gy–1) responses from electron beam and from albedo ENs including beam thermal (21 ± 2.63), albedo thermal (43 ± 3.70), total thermal (64 ± 6.33), total epithermal (32 ± 3.90), total fast (112.00), total thermal + epithermal (l96 ± 10), and total thermal + epithermal + fast (208 ± 10.23) ENs. Having seven ENDE responses of this study and seven PNDE responses of previous study with the same accelerator obtained at identical conditions by the same principle author provided the opportunity to compare the two sets of responses. The PNDE (µSv.Gy–1) responses have comparatively higher values and 22.60 times at isocenter which provide for the first time breakthrough ENDE responses not yet reported in any studies before worldwide.
Immunotherapy and drug sensitivity predictive roles of a novel prognostic model in hepatocellular carcinoma
Authors: Gao Xiaoge , Ren Xin , Wang Feitong , Ren Xinxin , liu Mengchen , Cui Guozhen , Liu Xiangye 
Published: April 2024

AbstractHepatocellular carcinoma (HCC) is one of the most significant causes of cancer-related deaths in the worldwide. Currently, predicting the survival of patients with HCC and developing treatment drugs still remain a significant challenge. In this study, we employed prognosis-related genes to develop and externally validate a predictive risk model. Furthermore, the correlation between signaling pathways, immune cell infiltration, immunotherapy response, drug sensitivity, and risk score was investigated using different algorithm platforms in HCC. Our results showed that 11 differentially expressed genes including UBE2C, PTTG1, TOP2A, SPP1, FCN3, SLC22A1, ADH4, CYP2C8, SLC10A1, F9, and FBP1 were identified as being related to prognosis, which were integrated to construct a prediction model. Our model could accurately predict patients’ overall survival using both internal and external datasets. Moreover, a strong correlation was revealed between the signaling pathway, immune cell infiltration, immunotherapy response, and risk score. Importantly, a novel potential drug candidate for HCC treatment was discovered based on the risk score and also validated through ex vivo experiments. Our finds offer a novel perspective on prognosis prediction and drug exploration for cancer patients.
Regional food self-sufficiency potential in the European Alpine space
Authors: Pecher Caroline , Marsoner Thomas , Tasser Erich 
Published: April 2024

AbstractThe sustainability of the food system needs to be improved, including shortening supply chains and promoting the consumption of regional food. Here, we explore the current potential for regional food self-sufficiency in the European Alpine space by calculating the current regional food/feed energy balance, deriving the regional per capita land footprint based on current food/feed consumption rates, and modelling the current potential for regional food/feed self-sufficiency. We show that 59% of the 560 Pcal of energy currently available in the study area comes from domestic production, and almost 60% of the energy is used for livestock consumption, with high regional variability. The resulting land footprints range from 2301 to 2975 m2 cap−1 y−1. Taking into account changes in cropping patterns, partial intensification, but no expansion of agricultural land, the European Alpine space could produce 89% of its current food demand domestically, with high regional variability due to population density, availability of agricultural land, crop yields, climatic conditions and dietary habits. These findings highlight the potential and limitations of regional mountain food systems and call for new strategies to improve sustainability. Reducing the current high consumption of animal products would reduce the land footprint and increase the potential for food self-sufficiency.
Analyzing the effect of public private partnership mode on sewage treatment in China
Authors: Wen Xin , Meng Fange , Li Shiheng 
Published: April 2024

AbstractThe public–private partnership (PPP) mode is one of the main ways to promote environmental governance through marketization in the sewage treatment industry. This mode is crucial for environmental protection and livelihood improvement. In order to investigate the impact of PPP mode on sewage treatment, the influence of financial development and the government–business relationship on the effectiveness of sewage treatment under PPP mode, and the role of government in this context, an empirical model is established. To achieve this, data from 284 prefecture-level and above cities in China from 2009 to 2017 has been selected as research samples. The total amount of regional sewage treatment PPP projects is used as the proxy variable for participation in the PPP mode. The findings reveal that the PPP mode of sewage treatment effectively reduces the intensity and amount of sewage discharge. Moreover, the results indicate that a higher level of financial development and a more perfect financial system are associated with better sewage treatment effects under the PPP mode. Similarly, a more harmonious government–business relationship and a higher health index of this relationship correspond to improved sewage treatment effects under the PPP mode. The government should actively enhance government transparency, formulate appropriate corporate taxes and fees, clarify the responsibilities and obligations of the government and enterprises, and optimize the business environment in order to optimize the sewage treatment effect of the PPP mode.
Estimating SARS-CoV-2 infection probabilities with serological data and a Bayesian mixture model
Authors: Glemain Benjamin , de Lamballerie Xavier , Zins Marie , Severi Gianluca , Touvier Mathilde , Deleuze Jean-François ,   SAPRIS-SERO study group, Carrat Fabrice , Ancel Pierre-Yves , Charles Marie-Aline , Severi Gianluca , Touvier Mathilde , Zins Marie , Kab Sofiane , Renuy Adeline , Le-Got Stephane , Ribet Celine , Pellicer Mireille , Wiernik Emmanuel , Goldberg Marcel , Artaud Fanny , Gerbouin-Rérolle Pascale , Enguix Mélody , Laplanche Camille , Gomes-Rima Roselyn , Hoang Lyan , Correia Emmanuelle , Barry Alpha Amadou , Senina Nadège , Allegre Julien , Szabo de Edelenyi Fabien , Druesne-Pecollo Nathalie , Esseddik Younes , Hercberg Serge , Deschasaux Mélanie , Charles Marie-Aline , Benhammou Valérie , Ritmi Anass , Marchand Laetitia , Zaros Cecile , Lordmi Elodie , Candea Adriana , de Visme Sophie , Simeon Thierry , Thierry Xavier , Geay Bertrand , Dufourg Marie-Noelle , Milcent Karen , Rahib Delphine , Lydie Nathalie , Lusivika-Nzinga Clovis , Pannetier Gregory , Lapidus Nathanael , Goderel Isabelle , Dorival Céline , Nicol Jérôme , Robineau Olivier , Lai Cindy , Belhadji Liza , Esperou Hélène , Couffin-Cadiergues Sandrine , Gagliolo Jean-Marie , Blanché Hélène , Sébaoun Jean-Marc , Beaudoin Jean-Christophe , Gressin Laetitia , Morel Valérie , Ouili Ouissam , Deleuze Jean-François , Ninove Laetitia , Priet Stéphane , Villarroel Paola Mariela Saba , Fourié Toscane , Ali Souand Mohamed , Amroun Abdenour , Seston Morgan , Ayhan Nazli , Pastorino Boris , de Lamballerie Xavier , Lapidus Nathanaël , Carrat Fabrice 
Published: April 2024

AbstractThe individual results of SARS-CoV-2 serological tests measured after the first pandemic wave of 2020 cannot be directly interpreted as a probability of having been infected. Plus, these results are usually returned as a binary or ternary variable, relying on predefined cut-offs. We propose a Bayesian mixture model to estimate individual infection probabilities, based on 81,797 continuous anti-spike IgG tests from Euroimmun collected in France after the first wave. This approach used serological results as a continuous variable, and was therefore not based on diagnostic cut-offs. Cumulative incidence, which is necessary to compute infection probabilities, was estimated according to age and administrative region. In France, we found that a “negative” or a “positive” test, as classified by the manufacturer, could correspond to a probability of infection as high as 61.8% or as low as 67.7%, respectively. “Indeterminate” tests encompassed probabilities of infection ranging from 10.8 to 96.6%. Our model estimated tailored individual probabilities of SARS-CoV-2 infection based on age, region, and serological result. It can be applied in other contexts, if estimates of cumulative incidence are available.
An efficient lightweight network for image denoising using progressive residual and convolutional attention feature fusion
Authors: Tiantian Wang , Hu Zhihua , Guan Yurong 
Published: April 2024

AbstractWhile deep learning has become the go-to method for image denoising due to its impressive noise removal capabilities, excessive network depth often plagues existing approaches, leading to significant computational burdens. To address this critical bottleneck, we propose a novel lightweight progressive residual and attention mechanism fusion network that effectively alleviates these limitations. This architecture tackles both Gaussian and real-world image noise with exceptional efficacy. Initiated through dense blocks (DB) tasked with discerning the noise distribution, this approach substantially reduces network parameters while comprehensively extracting local image features. The network then adopts a progressive strategy, whereby shallow convolutional features are incrementally integrated with deeper features, establishing a residual fusion framework adept at extracting encompassing global features relevant to noise characteristics. The process concludes by integrating the output feature maps from each DB and the robust edge features from the convolutional attention feature fusion module (CAFFM). These combined elements are then directed to the reconstruction layer, ultimately producing the final denoised image. Empirical analyses conducted in environments characterized by Gaussian white noise and natural noise, spanning noise levels 15–50, indicate a marked enhancement in performance. This assertion is quantitatively corroborated by increased average values in metrics such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Feature Similarity Index for Color images (FSIMc), outperforming the outcomes of more than 20 existing methods across six varied datasets. Collectively, the network delineated in this research exhibits exceptional adeptness in image denoising. Simultaneously, it adeptly preserves essential image features such as edges and textures, thereby signifying a notable progression in the domain of image processing. The proposed model finds applicability in a range of image-centric domains, encompassing image processing, computer vision, video analysis, and pattern recognition.
A blind image super-resolution network guided by kernel estimation and structural prior knowledge
Authors: Zhang Jiajun , Zhou Yuanbo , Bi Jiang , Xue Yuyang , Deng Wei , He Wenlin , Zhao Tao , Sun Kai , Tong Tong , Gao Qinquan , Zhang Qing 
Published: April 2024

AbstractThe goal of blind image super-resolution (BISR) is to recover the corresponding high-resolution image from a given low-resolution image with unknown degradation. Prior related research has primarily focused effectively on utilizing the kernel as prior knowledge to recover the high-frequency components of image. However, they overlooked the function of structural prior information within the same image, which resulted in unsatisfactory recovery performance for textures with strong self-similarity. To address this issue, we propose a two stage blind super-resolution network that is based on kernel estimation strategy and is capable of integrating structural texture as prior knowledge. In the first stage, we utilize a dynamic kernel estimator to achieve degradation presentation embedding. Then, we propose a triple path attention groups consists of triple path attention blocks and a global feature fusion block to extract structural prior information to assist the recovery of details within images. The quantitative and qualitative results on standard benchmarks with various degradation settings, including Gaussian8 and DIV2KRK, validate that our proposed method outperforms the state-of-the-art methods in terms of fidelity and recovery of clear details. The relevant code is made available on thislinkas open source.
Hydrous mantle plume promoted the generation of continental flood basalts in the Tarim large igneous province
Authors: Bi Yao , Chen Huan , Hanski Eero , Kuritani Takeshi , Wu Hong-Xiang , Zhang Feng-Qi , Liu Jia , Gu Xiao-Yan , Xia Qun-Ke 
Published: April 2024

AbstractRecent research on the water content of large igneous provinces (LIPs) has revealed that water has a significant impact on the formation of LIPs. However, most studies focus on the water content of mafic–ultramafic rocks, while relatively little attention has been paid to the water content of continental flood basalts (CFB), which form the major part of LIPs and are characterized by huge volumes (> 1 × 105 km3) and short eruption times. Here, we determined water contents of clinopyroxene crystals from the Akesu diabase, which is co-genetic with flood basalts of the Tarim LIP in China. Based on these measurements, we obtained a water content of higher than 1.23 ± 0.49 wt.% for the parental magma to the Tarim CFB and a minimum water content of 1230 ± 490 ppm for the mantle source, thus indicating the presence of a hydrous mantle plume. Combined with previous studies, our results suggest that water plays a key role in the formation of the Tarim LIP. Additionally, the whole-rock compositions of the Akesu diabase indicate a contribution of pyroxenite in the mantle source. This is consistent with a model, in which water was brought into the Tarim mantle plume by a subducted oceanic plate that entered the deep mantle.