bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prefrontal signals precede striatal signals for biased credit assignment in motivational learning biases
Authors: Algermissen Johannes , Swart Jennifer C. , Scheeringa René , Cools Roshan , den Ouden Hanneke E. M. 
Published: January 2024

AbstractActions are biased by the outcomes they can produce: Humans are more likely to show action under reward prospect, but hold back under punishment prospect. Such motivational biases derive not only from biased response selection, but also from biased learning: humans tend to attribute rewards to their own actions, but are reluctant to attribute punishments to having held back. The neural origin of these biases is unclear. Specifically, it remains open whether motivational biases arise primarily from the architecture of subcortical regions or also reflect cortical influences, the latter being typically associated with increased behavioral flexibility and control beyond stereotyped behaviors. Simultaneous EEG-fMRI allowed us to track which regions encoded biased prediction errors in which order. Biased prediction errors occurred in cortical regions (dorsal anterior and posterior cingulate cortices) before subcortical regions (striatum). These results highlight that biased learning is not a mere feature of the basal ganglia, but arises through prefrontal cortical contributions, revealing motivational biases to be a potentially flexible, sophisticated mechanism.
Intrinsically stretchable light-emitting drawing displays
Authors: Zhang Jiaxue , Lu Qianying , Wu Ming , Sun Yuping , Wang Shaolei , Wang Xiaoliang , Lu Ming-Hui , Kong Desheng 
Published: January 2024

AbstractStretchable displays that combine light-emitting capabilities with mechanical compliance are essential building blocks of next-generation wearable electronics. However, their widespread applications are currently limited by complex device architecture, limited pixel density, and immature fabrication processes. In this study, we present the device design and material developments of intrinsically stretchable light-emitting drawing displays that can show arbitrary hand-drawing features. The alternating-current electroluminescent display uses a simplified architecture comprising coplanar interdigitated liquid metal electrodes, an electroluminescent layer, and a dielectric encapsulation layer. Ink patterns on the device are coupled with the interdigitated electrodes under alternating voltage stimulations, generating localized electric fields for bright emissions. Various inks are prepared for painting, stamping, and stencil printing. Arbitrary luminous features on the devices can be either long-lasting or transient in characteristics. These skin-like devices are made entirely of compliant materials that can withstand bending, twisting, and stretching manipulations. Due to the excellent mechanical deformability, the drawing displays can be conformally laminated on the skin as body-integrated optoelectronic communication devices for graphic information.
Quantifying quantum coherence of multiple-charge states in tunable Josephson junctions
Authors: He Jiangbo , Pan Dong , Liu Mingli , Lyu Zhaozheng , Jia Zhongmou , Yang Guang , Zhu Shang , Liu Guangtong , Shen Jie , Shevchenko Sergey N. , Nori Franco , Zhao Jianhua , Lu Li , Qu Fanming 
Published: January 2024

AbstractCoherence and tunneling play central roles in quantum phenomena. In a tunneling event, the time that a particle spends inside the barrier has been fiercely debated. This problem becomes more complex when tunneling repeatedly occurs back and forth, and when involving many particles. Here we report the measurement of the coherence time of various charge states tunneling in a nanowire-based tunable Josephson junction; including single charges, multiple charges, and Cooper pairs. We studied all the charge tunneling processes using Landau-Zener-Stückelberg-Majorana (LZSM) interferometry, and observed high-quality interference patterns under a microwave drive. In particular, the coherence time of the charge states tunneling back and forth was extracted from the interference fringes in Fourier space. In addition, our measurements show the break-up of Cooper pairs, from a macroscopic quantum coherent state to individual particle states. Besides the fundamental research interest, our results also establish LZSM interferometry as a powerful technique to explore the coherence time of charges in hybrid devices.
Choroid plexus volume enlargement in first-episode antipsychotic-naïve schizophrenia
Authors: Zeng Jiaxin , Zhang Tianwei , Tang Biqiu , Li Siyi , Yao Li , Bishop Jeffrey R. , Sweeney John A. , Li Zhenlin , Qiu Changjian , Gu Shi , Gong Qiyong , Zhang Wenjing , Lui Su 
Published: January 2024

AbstractInvestigation of the choroid plexus in schizophrenia has seen growing interest due to its role in the interaction between neuroinflammation and brain dysfunction. Most previous studies included treated and long-term ill patients, while antipsychotics and illness course might both affect the choroid plexus. Here, we recruited first-episode antipsychotic-naïve schizophrenia patients, performed high-resolution structural brain scan and manually extracted choroid plexus volume. Choroid plexus volume was compared between patients and healthy controls after controlling for age, sex and intracranial volume. Age and sex effects were examined on choroid plexus volume in patient and healthy control groups respectively. In patients, we also examined the correlation of choroid plexus volume with volume measures of cortical and subcortical gray matter, white matter, lateral ventricular as well as symptom severity and cognitive function. Schizophrenia patients showed significantly enlarged choroid plexus volume compared with healthy controls. Choroid plexus volume was positively correlated with age in only patient group and we found significantly larger choroid plexus volumes in males than females in both patient and healthy control groups, while the sex effects did not differ between groups. Choroid plexus volume was only found correlated with lateral ventricular volume among the brain volume measures. No significant correlation between choroid plexus volume and clinical ratings or cognitive performance was observed. Without potential confounding effects of pharmacotherapy or illness course, our findings indicated the enlargement of choroid plexus in schizophrenia might be an enduring trait for schizophrenia.
Space charge governs the kinetics of metal exsolution
Authors: Weber Moritz L. , Šmíd Břetislav , Breuer Uwe , Rose Marc-André , Menzler Norbert H. , Dittmann Regina , Waser Rainer , Guillon Olivier , Gunkel Felix , Lenser Christian 
Published: January 2024

AbstractNanostructured composite electrode materials play a major role in the fields of catalysis and electrochemistry. The self-assembly of metallic nanoparticles on oxide supports via metal exsolution relies on the transport of reducible dopants towards the perovskite surface to provide accessible catalytic centres at the solid–gas interface. At surfaces and interfaces, however, strong electrostatic gradients and space charges typically control the properties of oxides. Here we reveal that the nature of the surface–dopant interaction is the main determining factor for the exsolution kinetics of nickel in SrTi0.9Nb0.05Ni0.05O3–δ. The electrostatic interaction of dopants with surface space charge regions forming upon thermal oxidation results in strong surface passivation, which manifests in a retarded exsolution response. We furthermore demonstrate the controllability of the exsolution response via engineering of the perovskite surface chemistry. Our findings indicate that tailoring the electrostatic gradients at the perovskite surface is an essential step to improve exsolution-type materials in catalytic converters.
Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data
Authors: Zheng Wei , Wuyun Qiqige , Li Yang , Zhang Chengxin , Freddolino Lydia , Zhang Yang 
Published: January 2024

Abstract
Leveraging iterative alignment search through genomic and metagenome sequence databases, we report the DeepMSA2 pipeline for uniform protein single- and multichain multiple-sequence alignment (MSA) construction. Large-scale benchmarks show that DeepMSA2 MSAs can remarkably increase the accuracy of protein tertiary and quaternary structure predictions compared with current state-of-the-art methods. An integrated pipeline with DeepMSA2 participated in the most recent CASP15 experiment and created complex structural models with considerably higher quality than the AlphaFold2-Multimer server (v.2.2.0). Detailed data analyses show that the major advantage of DeepMSA2 lies in its balanced alignment search and effective model selection, and in the power of integrating huge metagenomics databases. These results demonstrate a new avenue to improve deep learning protein structure prediction through advanced MSA construction and provide additional evidence that optimization of input information to deep learning-based structure prediction methods must be considered with as much care as the design of the predictor itself.
Labeled temperate hardwood tree stomatal image datasets from seven taxa of Populus and 17 hardwood species
Authors: Wang Jiaxin , Renninger Heidi J. , Ma Qin 
Published: January 2024

AbstractMachine learning (ML) algorithms have shown potential in automatically detecting and measuring stomata. However, ML algorithms require substantial data to efficiently train and optimize models, but their potential is restricted by the limited availability and quality of stomatal images. To overcome this obstacle, we have compiled a collection of around 11,000 unique images of temperate broadleaf angiosperm tree leaf stomata from various projects conducted between 2015 and 2022. The dataset includes over 7,000 images of 17 commonly encountered hardwood species, such as oak, maple, ash, elm, and hickory, and over 3,000 images of 55 genotypes from seven Populus taxa. Inner_guard_cell_walls and whole_stomata (stomatal aperture and guard cells) were labeled and had a corresponding YOLO label file that can be converted into other annotation formats. With the use of our dataset, users can (1) employ state-of-the-art machine learning models to identify, count, and quantify leaf stomata; (2) explore the diverse range of stomatal characteristics across different types of hardwood trees; and (3) develop new indices for measuring stomata.
A dataset of digital holograms of normal and thalassemic cells
Authors: Abbasian Vahid , Darafsheh Arash 
Published: January 2024

AbstractDigital holographic microscopy (DHM) is an intriguing medical diagnostic tool due to its label-free and quantitative nature, providing high-contrast images of phase samples. By capturing both intensity and phase information, DHM enables the numerical reconstruction of quantitative phase images. However, the lateral resolution is limited by the diffraction limit, which prompted the recent suggestion of microsphere-assisted DHM to enhance the DHM resolution straightforwardly. The use of such a technique as a medical diagnostic tool requires testing and validation of the proposed assays to prove their feasibility and viability. This paper publishes 760 and 609 microsphere-assisted DHM images of normal and thalassemic red blood cells obtained from a normal and thalassemic male individual, respectively.
PatagoniaMet: A multi-source hydrometeorological dataset for Western Patagonia
Authors: Aguayo Rodrigo , León-Muñoz Jorge , Aguayo Mauricio , Baez-Villanueva Oscar Manuel , Zambrano-Bigiarini Mauricio , Fernández Alfonso , Jacques-Coper Martin 
Published: January 2024

AbstractWestern Patagonia (40–56°S) is a clear example of how the systematic lack of publicly available data and poor quality control protocols have hindered further hydrometeorological studies. To address these limitations, we present PatagoniaMet (PMET), a compilation of ground-based hydrometeorological data (PMET-obs; 1950–2020), and a daily gridded product of precipitation and temperature (PMET-sim; 1980–2020). PMET-obs was developed considering a 4-step quality control process applied to 523 hydrometeorological time series obtained from eight institutions in Chile and Argentina. Following current guidelines for hydrological datasets, several climatic and geographic attributes were derived for each catchment. PMET-sim was developed using statistical bias correction procedures, spatial regression models and hydrological methods, and was compared against other bias-corrected alternatives using hydrological modelling. PMET-sim was able to achieve Kling-Gupta efficiencies greater than 0.7 in 72% of the catchments, while other alternatives exceeded this threshold in only 50% of the catchments. PatagoniaMet represents an important milestone in the availability of hydro-meteorological data that will facilitate new studies in one of the largest freshwater ecosystems in the world.
A publicly available newborn ear shape dataset for medical diagnosis of auricular deformities
Authors: Ren Liu-Jie , Luo Fei , Yang Zhi-Wei , Chen Li-Li , Wang Xin-Yue , Li Chen-Long , Xie You-Zhou , Wang Ji-Mei , Zhang Tian-Yu , Wang Shuo , Fu Yao-Yao 
Published: January 2024

AbstractEarly and accurate diagnosis of ear deformities in newborns is crucial for an effective non-surgical correction treatment, since this commonly seen ear anomalies would affect aesthetics and cause mental problems if untreated. It is not easy even for experienced physicians to diagnose the auricular deformities of newborns and the classification of the sub-types, because of the rich bio-metric features embedded in the ear shape. Machine learning has already been introduced to analyze the auricular shape. However, there is little publicly available datasets of ear images from newborns. We released a dataset that contains quality-controlled photos of 3,852 ears from 1,926 newborns. The dataset also contains medical diagnosis of the ear shape, and the health data of each newborn and its mother. Our aim is to provide a freely accessible dataset, which would facilitate researches related with ear anatomies, such as the AI-aided detection and classification of auricular deformities and medical risk analysis.
An annotated wing interferential pattern dataset of dipteran insects of medical interest for deep learning
Authors: Cannet Arnaud , Simon-chane Camille , Histace Aymeric , Akhoundi Mohammad , Romain Olivier , Souchaud Marc , Jacob Pierre , Sereno Darian , Bousses Philippe , Sereno Denis 
Published: January 2024

AbstractSeveral Diptera species are known to transmit pathogens of medical and veterinary interest. However, identifying these species using conventional methods can be time-consuming, labor-intensive, or expensive. A computer vision-based system that uses Wing interferential patterns (WIPs) to identify these insects could solve this problem. This study introduces a dataset for training and evaluating a recognition system for dipteran insects of medical and veterinary importance using WIPs. The dataset includes pictures of Culicidae, Calliphoridae, Muscidae, Tabanidae, Ceratopogonidae, and Psychodidae. The dataset is complemented by previously published datasets of Glossinidae and some Culicidae members. The new dataset contains 2,399 pictures of 18 genera, with each genus documented by a variable number of species and annotated as a class. The dataset covers species variation, with some genera having up to 300 samples.
Open source and reproducible and inexpensive infrastructure for data challenges and education
Authors: DeWitt Peter E. , Rebull Margaret A. , Bennett Tellen D. 
Published: January 2024

AbstractData sharing is necessary to maximize the actionable knowledge generated from research data. Data challenges can encourage secondary analyses of datasets. Data challenges in biomedicine often rely on advanced cloud-based computing infrastructure and expensive industry partnerships. Examples include challenges that use Google Cloud virtual machines and the Sage Bionetworks Dream Challenges platform. Such robust infrastructures can be financially prohibitive for investigators without substantial resources. Given the potential to develop scientific and clinical knowledge and the NIH emphasis on data sharing and reuse, there is a need for inexpensive and computationally lightweight methods for data sharing and hosting data challenges. To fill that gap, we developed a workflow that allows for reproducible model training, testing, and evaluation. We leveraged public GitHub repositories, open-source computational languages, and Docker technology. In addition, we conducted a data challenge using the infrastructure we developed. In this manuscript, we report on the infrastructure, workflow, and data challenge results. The infrastructure and workflow are likely to be useful for data challenges and education.
East Australian Current velocity, temperature and salinity data products
Authors: Sloyan Bernadette M. , Cowley Rebecca , Chapman Christopher C. 
Published: January 2024

AbstractThe East Australian Current (EAC) is the complex, highly energetic western boundary current that flows along the east coast of Australia. The EAC and its associated turbulent eddies dominate the marine climate of the Coral and Tasman Seas and the eastern Australian continental shelf. Here we present a series of consistent EAC data products that combines in situ temperature, salinity and velocity observations from the Australian Integrated Marine Observing System (IMOS) and Commonwealth Scientific and Industrial Research Organisation (CSIRO) EAC mooring array and North Stradbroke Island reference site. The EAC data products are produced from over 1000 individual instrument files collected during six 18-month deployments in the East Australian Current (EAC) off Brisbane, Australia at 27 °S between 2012–2022. The mooring individual instrument files are combined, interpolated onto a common vertical, temporal (hourly and daily) and spatial grid. The ITCOMPSOM method is used to fill missing data in the time series. These data product can be used to investigate intra- and interannual EAC variability and boundary current dynamics.
Faunal remains data from Paleolithic-early Iron Age archaeological sites in the Qinghai-Tibet Plateau in China
Authors: Ren Kaidi , Ren Lele 
Published: January 2024

AbstractAccording to published archaeological sources, zooarchaeological data collection on the Qinghai-Tibet Plateau and its marginal and transitional areas is inadequate, and relevant datasets have not been published. For this reason, we collected and collated relevant information. Our database provides the geographical location, elevation, cultural type and faunal assemblage of each site on the Qinghai-Tibet Plateau and its periphery for which zooarchaeological data have been published from the Paleolithic to the Early Iron Age. The patterns of human faunal resource use, habitat patterns, and animal abundance and spatial distribution on the Qinghai-Tibet Plateau and its surrounding areas during the Prehistoric-Early Iron Age are represented in this dataset. The data provide a reference for further understanding prehistoric-early Iron Age human behavior, subsistence patterns and material and cultural exchanges between East and West on the Qinghai-Tibet Plateau and its environs.
Prediction model of spontaneous combustion risk of extraction borehole based on PSO-BPNN and its application
Authors: Wang Wei , Liang Ran , Qi Yun , Cui Xinchao , Liu Jiao 
Published: January 2024

AbstractThe feasibility and accuracy of the risk prediction of gas extraction borehole spontaneous combustion is improved to avoid the occurrence of spontaneous combustion in the gas extraction borehole. A gas extraction borehole spontaneous combustion risk prediction model (PSO-BPNN model) coupling the PSO algorithm with BP neural network is established through improving the connection weight and threshold values of BP neural network by the particle swarm optimization (PSO) algorithm. The prediction results of the PSO-BPNN model are compared and analyzed with that of the BP neural network model (BPNN model), GA-BPNN model, SSA-BPNN model and MPA-BPNN model. The results showed as follows: the average relative error of the PSO-BPNN model was 4.38%; the average absolute error was 0.0678; the root mean square error was 0.0934; and the determination coefficient was 0.9874. Compared with the BPNN model, the average relative error, average absolute error and root mean square error decreased by 9.35%, 0.1707 and 0.2056 respectively; and the determination coefficient increased by 0.1169. Compared with the GA-BPNN model, the average relative error, average absolute error and root mean square error decreased by 3.19%, 0.0602 and 0.0821 respectively; and the determination coefficient increased by 0.0320. Compared with the SSA-BPNN model, the average relative error, average absolute error and root mean square error decreased by 5.70%, 0.0820 and 0.1100 respectively; and the determination coefficient increased by 0.0474. Compared with the MPA-BPNN model, the average relative error, average absolute error and root mean square error decreased by 3.50%, 0.0861 and 0.1125 respectively; and the determination coefficient increased by 0.0488, proving that the PSO-BPNN model is more accurate than the BPNN model, GA-BPNN model, SSA-BPNN model and MPA-BPNN model as for prediction. When the PSO-BPNN model was applied to three extraction boreholes A, B, and C in a coal mine of Shanxi, the prediction results were better than the BPNN model, GA-BPNN model, SSA-BPNN model and MPA-BPNN model, proving the accuracy and stability of the PSO-BPNN model in predicting risk of borehole spontaneous combustion in other mine.
Diversity, habitat endemicity and trophic ecology of the fauna of Loki’s Castle vent field on the Arctic Mid-Ocean Ridge
Authors: Eilertsen Mari Heggernes , Kongsrud Jon Anders , Tandberg Anne Helene Solberg , Alvestad Tom , Budaeva Nataliya , Martell Luis , Ramalho Sofia P. , Falkenhaug Tone , Huys Rony , Oug Eivind , Bakken Torkild , Høisæter Tore , Rauch Cessa , Carvalho Francisca C. , Savchenko Alexandra S. , Ulvatn Tone , Kongshavn Katrine , Berntsen Cassandra Mari , Olsen Bernt Rydland , Pedersen Rolf Birger 
Published: January 2024

AbstractLoki’s Castle Vent Field (LCVF, 2300 m) was discovered in 2008 and represents the first black-smoker vent field discovered on the Arctic Mid-Ocean Ridge (AMOR). However, a comprehensive faunal inventory of the LCVF has not yet been published, hindering the inclusion of the Arctic in biogeographic analyses of vent fauna. There is an urgent need to understand the diversity, spatial distribution and ecosystem function of the biological communities along the AMOR, which will inform environmental impact assesments of future deep-sea mining activities in the region. Therefore, our aim with this paper is to provide a comprehensive inventory of the fauna at LCVF and present a first insight into the food web of the vent community. The fauna of LCVF has a high degree of novelty, with five new species previously described and another ten new species awaiting formal description. Most of the new species from LCVF are either hydrothermal vent specialists or have been reported from other chemosynthesis-based ecosystems. The highest taxon richness is found in the diffuse venting areas and may be promoted by the biogenic habitat generated by the foundation species Sclerolinum contortum. The isotopic signatures of the vent community of LCVF show a clear influence of chemosynthetic primary production on the foodweb. Considering the novel and specialised fauna documented in this paper, hydrothermal vents on the AMOR should be regarded as vulnerable marine ecosystems and protective measures must therefore be implemented, especially considering the potential threat from resource exploration and exploitation activities in the near future.