bluuebunny/crossref_metadata_2025_split huggingface dataset:
A programmable topological photonic chip
Authors: Dai Tianxiang , Ma Anqi , Mao Jun , Ao Yutian , Jia Xinyu , Zheng Yun , Zhai Chonghao , Yang Yan , Li Zhihua , Tang Bo , Luo Jun , Zhang Baile , Hu Xiaoyong , Gong Qihuang , Wang Jianwei 
Published: May 2024

AbstractControlling topological phases of light allows the observation of abundant topological phenomena and the development of robust photonic devices. The prospect of more sophisticated control with topological photonic devices for practical implementations requires high-level programmability. Here we demonstrate a fully programmable topological photonic chip with large-scale integration of silicon photonic nanocircuits and microresonators. Photonic artificial atoms and their interactions in our compound system can be individually addressed and controlled, allowing the arbitrary adjustment of structural parameters and geometrical configurations for the observation of dynamic topological phase transitions and diverse photonic topological insulators. Individual programming of artificial atoms on the generic chip enables the comprehensive statistical characterization of topological robustness against relatively weak disorders, and counterintuitive topological Anderson phase transitions induced by strong disorders. This generic topological photonic chip can be rapidly reprogrammed to implement multifunctionalities, providing a flexible and versatile platform for applications across fundamental science and topological technologies.
Electric recycling of Portland cement at scale
Authors: Dunant Cyrille F. , Joseph Shiju , Prajapati Rohit , Allwood Julian M. 
Published: May 2024

AbstractCement production causes 7.5% of global anthropogenic CO2 emissions, arising from limestone decarbonation and fossil-fuel combustion1–3. Current decarbonation strategies include substituting Portland clinker with supplementary materials, but these mainly arise in emitting processes, developing alternative binders but none yet promises scale, or adopting carbon capture and storage that still releases some emissions4–8. However, used cement is potentially an abundant, decarbonated feedstock. Here we show that recovered cement paste can be reclinkered if used as a partial substitute for the lime–dolomite flux used in steel recycling nowadays. The resulting slag can meet existing specifications for Portland clinker and can be blended effectively with calcined clay and limestone. The process is sensitive to the silica content of the recovered cement paste, and silica and alumina that may come from the scrap, but this can be adjusted easily. We show that the proposed process may be economically competitive, and if powered by emissions-free electricity, can lead to zero emissions cement while also reducing the emissions of steel recycling by reducing lime flux requirements. The global supply of scrap steel for recycling may treble by 2050, and it is likely that more slag can be made per unit of steel recycled. With material efficiency in construction9,10, future global cement requirements could be met by this route.
Metals strengthen with increasing temperature at extreme strain rates
Authors: Dowding Ian , Schuh Christopher A. 
Published: May 2024

AbstractThe strength of materials depends on the rate at which they are tested, as defects, for example dislocations, that move in response to applied strains have intrinsic kinetic limitations1–4. As the deformation strain rate increases, more strengthening mechanisms become active and increase the strength4–7. However, the regime in which this transition happens has been difficult to access with traditional micromechanical strength measurements. Here, with microballistic impact testing at strain rates greater than 106 s−1, and without shock conflation, we show that the strength of copper increases by about 30% for a 157 °C increase in temperature, an effect also observed in pure titanium and gold. This effect is counterintuitive, as almost all materials soften when heated under normal conditions. This anomalous thermal strengthening across several pure metals is the result of a change in the controlling deformation mechanism from thermally activated strengthening to ballistic transport of dislocations, which experience drag through phonon interactions1,8–10. These results point to a pathway to better model and predict materials properties under various extreme strain rate conditions, from high-speed manufacturing operations11 to hypersonic transport12.
A whole-slide foundation model for digital pathology from real-world data
Authors: Xu Hanwen , Usuyama Naoto , Bagga Jaspreet , Zhang Sheng , Rao Rajesh , Naumann Tristan , Wong Cliff , Gero Zelalem , González Javier , Gu Yu , Xu Yanbo , Wei Mu , Wang Wenhui , Ma Shuming , Wei Furu , Yang Jianwei , Li Chunyuan , Gao Jianfeng , Rosemon Jaylen , Bower Tucker , Lee Soohee , Weerasinghe Roshanthi , Wright Bill J. , Robicsek Ari , Piening Brian , Bifulco Carlo , Wang Sheng , Poon Hoifung 
Published: May 2024

AbstractDigital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles1–3. Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important slide-level context4. Here we present Prov-GigaPath, a whole-slide pathology foundation model pretrained on 1.3 billion 256 × 256 pathology image tiles in 171,189 whole slides from Providence, a large US health network comprising 28 cancer centres. The slides originated from more than 30,000 patients covering 31 major tissue types. To pretrain Prov-GigaPath, we propose GigaPath, a novel vision transformer architecture for pretraining gigapixel pathology slides. To scale GigaPath for slide-level learning with tens of thousands of image tiles, GigaPath adapts the newly developed LongNet5 method to digital pathology. To evaluate Prov-GigaPath, we construct a digital pathology benchmark comprising 9 cancer subtyping tasks and 17 pathomics tasks, using both Providence and TCGA data6. With large-scale pretraining and ultra-large-context modelling, Prov-GigaPath attains state-of-the-art performance on 25 out of 26 tasks, with significant improvement over the second-best method on 18 tasks. We further demonstrate the potential of Prov-GigaPath on vision–language pretraining for pathology7,8 by incorporating the pathology reports. In sum, Prov-GigaPath is an open-weight foundation model that achieves state-of-the-art performance on various digital pathology tasks, demonstrating the importance of real-world data and whole-slide modelling.
Geolocated fish spawning habitats
Authors: Oremus Kimberly L. , Rising James , Ramesh Nandini , Ostroski Audrey J. 
Published: May 2024

AbstractFish spawning locations are a crucial input into fisheries management and conservation plans, and many stocks are especially sensitive to the environmental conditions within these localized zones. Globally collated data on spawning locations across many species has been unavailable, hindering global stock assessments and analyses of sustainable development and global environmental change. To address this, we created a geocoded fish spawning dataset using qualitative spawning information from FishBase and Science and Conservation of Fish Aggregations (SCRFA). We cleaned and geocoded the spawning locations of 1,045 marine fish species into 2,931 regions. Each spawning region is defined by one or more polygons, and most spawning regions are associated with spawning months. The resulting dataset covers oceans globally. This dataset will be useful to scientists studying marine fish population dynamics and their interactions with the physical environment on regional to large scales.
The first chromosomal-level genome assembly and annotation of white suckerfish Remora albescens
Authors: Zhou Chaowei , Liu Qi , Qu Yinquan , Qiao Ying , Gao Tianxiang , Wang Danyang 
Published: May 2024

AbstractRemora albescens, also known as white suckerfish, recognized for its distinctive suction-cup attachment behavior and medicinal significance. In this study, we produced a high-quality chromosome-level genome assembly of R. albescens through the integration of 23.87 Gb PacBio long reads, 64.54 Gb T7 short reads, and 88.63 Gb Hi-C data. Initially, we constructed a contig-level genome assembly totaling 605.30 Mb with a contig N50 of 23.12 Mb. Subsequently, employing Hi-C technology, approximately 99.68% (603.38 Mb) of the contig-level genome was successfully assigned to 23 pseudo-chromosomes. Through the integration of homologous-based predictions, ab initio predictions, and RNA-sequencing methods, we successfully identified a comprehensive set of 22,445 protein-coding genes. Notably, 96.36% (21,629 genes) of these were effectively annotated with functional information. The genome assembly achieved an estimated completeness of 98.1% according to BUSCO analysis. This work promotes the applicability of the R. albescens genome, laying a solid foundation for future investigations into genomics, biology, and medicinal importance within this species.
Metricizing policy texts: Comprehensive dataset on China’s Agri-policy intensity spanning 1982–2023
Authors: Wu Yehui , Wang Canyu , Ji Rongbiao , Li Yadong , Yang Junkui , Wang Yixuan , Li Rujia , Wu Mengyao , Chen Jiaojiao , Yang Jianping 
Published: May 2024

AbstractDue to the lack of direct assessment metrics, existing studies on the intensity of agricultural policies often utilize indicators such as Gross Domestic Product (GDP) of agriculture or the quantity of agricultural policies as measures. Optimizing methods for analyzing the intensity of agricultural policies will significantly impact parameter selection in agricultural policy research and the evaluation of policy effectiveness. In this study, we constructed a Chinese Agricultural Policy Corpus using agricultural policies released by various governmental agencies at the national level in China from 1982 to April 2023. We quantified the values of agricultural domain terms in the corpus and evaluated the intensity of each agricultural policy document. The validation results of this study indicate a strong correlation between the intensity of agricultural policies and agricultural GDP. The trend in agricultural GDP changes lags behind policy intensity by 2.5 years (at a 95% confidence level), thus validating the rationality of our constructed corpus, agricultural policy scoring dataset, and methodology.
A bi-directional segmentation method for prostate ultrasound images under semantic constraints
Authors: Li Zexiang , Du Wei , Shi Yongtao , Li Wei , Gao Chao 
Published: May 2024

AbstractDue to the lack of sufficient labeled data for the prostate and the extensive and complex semantic information in ultrasound images, accurately and quickly segmenting the prostate in transrectal ultrasound (TRUS) images remains a challenging task. In this context, this paper proposes a solution for TRUS image segmentation using an end-to-end bidirectional semantic constraint method, namely the BiSeC model. The experimental results show that compared with classic or popular deep learning methods, this method has better segmentation performance, with the Dice Similarity Coefficient (DSC) of 96.74% and the Intersection over Union (IoU) of 93.71%. Our model achieves a good balance between actual boundaries and noise areas, reducing costs while ensuring the accuracy and speed of segmentation.
Investigation into the application of remimazolamin conjunction with low-dose propofolfor pediatricfiberoptic bronchoscopy
Authors: Chen Wenjing , Bao Wenjuan , Shi Jing , Shi Lei , Cui Jianli 
Published: May 2024

AbstractThis study delves into the effectiveness of combining remimazolam with low-dose propofol in pediatric fiberoptic bronchoscopy. Ninety children scheduled for fiberoptic bronchoscopy in our hospital were enrolled as research participants. Based on the intraoperative anesthetic drug regimen, the children were divided into three groups: group R (remimazolam 0.2–0.4 mg/kg), group P (propofol 1–3 mg/kg), and group RP (remimazolam0.2 mg/kg, propofol 0.5 mg/kg). Immediately post-anesthesia, group P exhibited lower blood pressure and heart rate (HR) compared to both group R and group RP (P < 0.05). As bronchoscope approached the glottis and epiglottis, group P continued to display lower blood pressure and HR compared to group R and group RP (P < 0.05). During lavage, group P maintained lower blood pressure and HR compared to both the R and RP groups (P < 0.05). Immediately post-anesthesia, group P demonstrated lower SpO2 compared to the R and RP groups (P < 0.05).During lavage, group P maintained lower SpO2 than group R and group RP (P < 0.05). In comparison with group R and group PR, group P showed shortened induction and recovery times (P < 0.05). The one-time entry success rate into the microscope was higher in group R than in group P, with the RP group showing an intermediate decreased (P < 0.05). Moreover, the cough score in R group was higher than in the P and RP groups (P < 0.05). Furthermore, the satisfaction rates of the RP group exceeded those of the R and P groups (P < 0.05). Remimazolam combined with low-dose propofol effectively balances the strengths and weaknesses of remimazolam and propofol, ensuring more stable hemodynamics, a lower incidence of adverse reactions, and optimal surgical conditions in pediatric fiberoptic bronchoscopy.
Comprehensive data mining reveals RTK/RAS signaling pathway as a promoter of prostate cancer lineage plasticity through transcription factors and CNV
Authors: Wei Guanyun , Zhang Xu , Liu Siyuan , Hou Wanxin , Dai Zao 
Published: May 2024

AbstractProstate cancer lineage plasticity is a key driver in the transition to neuroendocrine prostate cancer (NEPC), and the RTK/RAS signaling pathway is a well-established cancer pathway. Nevertheless, the comprehensive link between the RTK/RAS signaling pathway and lineage plasticity has received limited investigation. In particular, the intricate regulatory network governing the interplay between RTK/RAS and lineage plasticity remains largely unexplored. The multi-omics data were clustered with the coefficient of argument and neighbor joining algorithm. Subsequently, the clustered results were analyzed utilizing the GSEA, gene sets related to stemness, multi-lineage state datasets, and canonical cancer pathway gene sets. Finally, a comprehensive exploration of the data based on the ssGSEA, WGCNA, GSEA, VIPER, prostate cancer scRNA-seq data, and the GPSAdb database was conducted. Among the six modules in the clustering results, there are 300 overlapping genes, including 3 previously unreported prostate cancer genes that were validated to be upregulated in prostate cancer through RT-qPCR. Function Module 6 shows a positive correlation with prostate cancer cell stemness, multi-lineage states, and the RTK/RAS signaling pathway. Additionally, the 19 leading-edge genes of the RTK/RAS signaling pathway promote prostate cancer lineage plasticity through a complex network of transcriptional regulation and copy number variations. In the transcriptional regulation network, TP63 and FOXO1 act as suppressors of prostate cancer lineage plasticity, whereas RORC exerts a promoting effect. This study provides a comprehensive perspective on the role of the RTK/RAS pathway in prostate cancer lineage plasticity and offers new clues for the treatment of NEPC.
Optimal and scalable entanglement distribution over crossbar quantum networks
Authors: Ciobanu Bogdan-Călin , Verzotti Luca Perju , Popescu Pantelimon George 
Published: May 2024

AbstractCrossbar networks are a cornerstone of network architectures, capable of operating both as standalone interconnections or as integral switching components in complex, multi-stage systems. The main advantages of crossbar networks are their non-blocking operation and unparalleled minimal latency. With the advent of large scale quantum networks, crossbars might be an important asset towards the Quantum Internet. This study proposes a solution for the problem of distributing entanglement within crossbar quantum networks. Entangled particles are a consumable resource in quantum networks, and are being used by most quantum protocols. By ensuring that nodes within quantum networks are being supplied with entanglement, the reliability and efficiency of the network is maintained. By providing an efficient, scalable framework that can be used to achieve optimal entanglement distribution within crossbar quantum networks, this study offers a theoretical achievement which can be also used for enhancing quantum network performance. An algorithm for selecting an optimal entanglement distribution configuration is proposed and fully tested on realistic possible configurations.
The molecular evolution of cancer associated genes in mammals
Authors: MacDonald Nick , Raven Nynke , Diep Wendy , Evans Samantha , Pannipitiya Senuri , Bramwell Georgina , Vanbeek Caitlin , Thomas Frédéric , Russell Tracey , Dujon Antoine M. , Telonis-Scott Marina , Ujvari Beata 
Published: May 2024

AbstractCancer is a disease that many multicellular organisms have faced for millions of years, and species have evolved various tumour suppression mechanisms to control oncogenesis. Although cancer occurs across the tree of life, cancer related mortality risks vary across mammalian orders, with Carnivorans particularly affected. Evolutionary theory predicts different selection pressures on genes associated with cancer progression and suppression, including oncogenes, tumour suppressor genes and immune genes. Therefore, we investigated the evolutionary history of cancer associated gene sequences across 384 mammalian taxa, to detect signatures of selection across categories of oncogenes (GRB2, FGL2 and CDC42), tumour suppressors (LITAF, Casp8 and BRCA2) and immune genes (IL2, CD274 and B2M). This approach allowed us to conduct a fine scale analysis of gene wide and site-specific signatures of selection across mammalian lineages under the lens of cancer susceptibility. Phylogenetic analyses revealed that for most species the evolution of cancer associated genes follows the species’ evolution. The gene wide selection analyses revealed oncogenes being the most conserved, tumour suppressor and immune genes having similar amounts of episodic diversifying selection. Despite BRCA2’s status as a key caretaker gene, episodic diversifying selection was detected across mammals. The site-specific selection analyses revealed that the two apoptosis associated domains of the Casp8 gene of bats (Chiroptera) are under opposing forces of selection (positive and negative respectively), highlighting the importance of site-specific selection analyses to understand the evolution of highly complex gene families. Our results highlighted the need to critically assess different types of selection pressure on cancer associated genes when investigating evolutionary adaptations to cancer across the tree of life. This study provides an extensive assessment of cancer associated genes in mammals with highly representative, and substantially large sample size for a comparative genomic analysis in the field and identifies various avenues for future research into the mechanisms of cancer resistance and susceptibility in mammals.
A novel plant type, leaf disease and severity identification framework using CNN and transformer with multi-label method
Authors: Yang Bin , Li Mingwei , Li Fei , Wang Yongbo , Liang Qiaokang , Zhao Ruiyuan , Li Caihong , Wang Jianwu 
Published: May 2024

AbstractThe growth of plants is threatened by numerous diseases. Accurate and timely identification of these diseases is crucial to prevent disease spreading. Many deep learning-based methods have been proposed for identifying leaf diseases. However, these methods often combine plant, leaf disease, and severity into one category or treat them separately, resulting in a large number of categories or complex network structures. Given this, this paper proposes a novel leaf disease identification network (LDI-NET) using a multi-label method. It is quite special because it can identify plant type, leaf disease and severity simultaneously using a single straightforward branch model without increasing the number of categories and avoiding extra branches. It consists of three modules, i.e., a feature tokenizer module, a token encoder module and a multi-label decoder module. The LDI-NET works as follows: Firstly, the feature tokenizer module is designed to enhance the capability of extracting local and long-range global contextual features by leveraging the strengths of convolutional neural networks and transformers. Secondly, the token encoder module is utilized to obtain context-rich tokens that can establish relationships among the plant, leaf disease and severity. Thirdly, the multi-label decoder module combined with a residual structure is utilized to fuse shallow and deep contextual features for better utilization of different-level features. This allows the identification of plant type, leaf disease, and severity simultaneously. Experiments show that the proposed LDI-NET outperforms the prevalent methods using the publicly available AI challenger 2018 dataset.
The use of bones as tools in Late Lower Paleolithic of Central Italy
Authors: Marinelli Flavia , Moncel Marie-Helénè , Lemorini Cristina 
Published: May 2024

AbstractThe Latium area in Italy has yielded rich evidence of Lower Paleolithic sites with both faunal remains, artefacts, and human fossil remains, such as the Ceprano human skull. Many are the sites where lithic industry has been found in association with bone industry. Medium and large animals were a key resource because they provided an enormous amount of meat and fat. However, they were extensively exploited for their bones, rich in marrow, and as raw material for tool production. Bone tools are so far few documented for early period of time and especially for the Middle Pleistocene in Western Europe. We report here evidence of bone tools and their efficiency of use for hominin groups living in the Frosinone-Ceprano basin during the MIS 11/10, a key period which records behavioral innovations and onset of the Neanderthal behaviors. In three sites, Isoletta, Colle Avarone and Selvotta, several bone tools and bone flakes have been discovered (MIS 11/10). They were associated to stone artefacts part of the hominins tool-kit. Technological and use-wear analyses conducted on these bone industries, dated between 410 and 430 ka, yield relevant results to understand the effectiveness of the bones tools found associated with lithic series, including handaxes.
Altered static and dynamic functional network connectivity in primary angle-closure glaucoma patients
Authors: Wang Yuanyuan , Shu Yongqiang , Cai Guoqian , Guo Yu , Gao Junwei , Chen Ye , Lv Lianjiang , Zeng Xianjun 
Published: May 2024

AbstractTo explore altered patterns of static and dynamic functional brain network connectivity (sFNC and dFNC) in Primary angle-closure glaucoma (PACG) patients. Clinically confirmed 34 PACG patients and 33 age- and gender-matched healthy controls (HCs) underwent evaluation using T1 anatomical and functional MRI on a 3 T scanner. Independent component analysis, sliding window, and the K-means clustering method were employed to investigate the functional network connectivity (FNC) and temporal metrics based on eight resting-state networks. Differences in FNC and temporal metrics were identified and subsequently correlated with clinical variables. For sFNC, compared with HCs, PACG patients showed three decreased interactions, including SMN-AN, SMN-VN and VN-AN pairs. For dFNC, we derived four highly structured states of FC that occurred repeatedly between individual scans and subjects, and the results are highly congruent with sFNC. In addition, PACG patients had a decreased fraction of time in state 3 and negatively correlated with IOP (p < 0.05). PACG patients exhibit abnormalities in both sFNC and dFNC. The high degree of overlap between static and dynamic results suggests the stability of functional connectivity networks in PACG patients, which provide a new perspective to understand the neuropathological mechanisms of optic nerve damage in PACG patients.