bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reversal treatment and clinical outcomes in acute intracranial haemorrhage associated with oral anticoagulant use: protocol of a planned systematic review and meta-analysis
Authors: Tallroth Mattias , Östlundh Linda , Büki András , Cao Yang , von Euler Mia , Ström Jakob O 
Published: February 2025

Introduction
Reversal treatment is commonly used for managing oral anticoagulant (OAC)-associated intracranial haemorrhages. Its effects on mortality are still understudied, particularly in various subtypes of intracranial haemorrhages. This systematic review and meta-analysis aims to synthesise the available data to study the impact of reversal therapies on mortality following various OAC-associated acute intracranial haemorrhages.

Methods and analysis
This protocol follows the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Protocols, and the final review will be reported in accordance with the PRISMA reporting guidelines. This systematic review and meta-analysis will include studies that assess contemporary reversal treatment in comparison to no reversal treatment, in cases of OAC-associated intracranial haemorrhage. Stratification will be performed for the types of bleeding as well as OAC at bleeding onset. Preliminary searches to determine search term inclusions were conducted in May–August 2024 in the electronic databases Embase, PubMed, Scopus and Web of Science without language and publication date restrictions. Randomised controlled studies, non-randomised controlled trials, and observational studies will be considered for the final meta-analysis. Three reviewers (MT, JOS and AB) will screen titles and abstracts, and one reviewer (MT) will subsequently conduct full-text screening.
Risks of bias will be assessed by MT using tools such as Risk of Bias 2, Risk Of Bias In Non-randomised Studies - of Interventions and the Newcastle-Ottawa Scale. Heterogeneity among the study results will be assessed using the I² statistic. If appropriate, a random-effects meta-analysis model will be performed. Subgroup analyses and meta-regression (if applicable) will be performed to assess sources of heterogeneity among (1) intracranial haemorrhage types, (2) OAC drugs and (3) study types, with randomised controlled trials being the primary focus.

Ethics and dissemination
Ethical approval is not needed as this project involves previously published data. We intend to publish the results in a peer-reviewed journal.

PROSPERO registration number
CRD42024556420.
An Innovative Onion Disease Classification Framework Using Smart IoT Assisted Multi-Scale Attention-Based ResNeXt with SPP via Modified Cat–Mouse Optimizer
Authors: Vhatkar Kapil , Kathole Atul B. , Katti Jayashree , Dharmale Gulbakshee 
Published: February 2025

The application of smart agriculture is enabled by the Internet of Things (IoT) and cloud-based platforms, and these techniques have reshaped conventional methods of farming. Producers may prevent onions from spoilage by using storage procedures. However, humans can fail to identify the decaying onions, in which case managers may depend on sensors and deep learning strategies for detecting the decomposition of onions. The conventional techniques estimate data improperly because of external factors, and the system that covers the IoT framework encountered several challenges while using the currently accessible techniques to recognize onion disease. Hence, an IoT-based onion disease classification framework using deep learning is proposed for increasing the onion yield by recognizing the onion disease. At first, the required data are collected using the IoT devices. Further, the region of interest (ROI) detection process is done using the developed adaptive residual fully convolutional network (ARFCN), and finally, the ROI cropped images are attained with the support of the ARFCN technique. Here, the variables of the ARFCN approach are tuned with the help of a revised random parameter-based cat and mouse optimizer (RRP-CMO). The preservation of valuable regions is highly augmented by the ROI detection process. In addition to that, the acquired image from the dataset has few unwanted regions, and it is removed by the ROI detection process. The cropped images are then preceded for disease classification using the proposed multi-scale attention-based ResNeXt with spatial pyramid pooling (MARSPP). The final classification results are validated with various conventional algorithms and classifiers.
The Effect of Sodium 1-Naphthalene Sulfonate and Sodium Dodecyl Sulfate Additives on Electrodeposition of Iron in Acidic Sulfate Electrolytes
Authors: Kong Dong , Chen Desheng , Zhao Hongxin , Zhen Yulan , Wang Lina , Liang Jianye , Yuan Zhangfu 
Published: February 2025

Abstract
This study investigated the effects of two additives, sodium 1-naphthalenesulfonate (SNS) and sodium dodecyl sulfate (SDS), on electrodeposition of iron in acidic sulfate baths. Focusing on their influence on cathodic polarization and back-dissolution, as well as changes in the morphological characteristics and crystallographic orientation of iron deposits, the study utilized electrochemical assessments and morphological evaluations. Results indicate that SNS and SDS significantly reduce the nucleation overpotential (NOP) of iron, from 351 to 154 and 127 mV with optimal concentrations at 1 g/L and 0.1 g/L, respectively. Both additives enhance the corrosion potential (Ec), thereby improving corrosion resistance. The additives can also reduce solution resistance (Rs) and charge transfer resistance (Rct), facilitating faster Fe²⁺ ion charge transfers and reducing dissolution of deposited iron. Moreover, SNS and SDS synergistically adjust the crystallographic plane orientation of Fe, promoting the formation of the (110) and (211) planes while suppressing the (200) planes, resulting in finer iron grains. Additionally, the TChkl index reaches a maximum value of 1.69. These findings underscore the crucial role of SNS and SDS in optimizing the iron electrodeposition process and enhancing the quality and stability of electrodeposited iron.
Latest Updates and Future Perspective on Hybrid Halide Perovskite CH3NH3PbI3 in Humidity Sensing and Energy Conversion Applications
Authors: Gupta Khushboo , Kumar Manish , Singh Dharm Veer , Chaudhary Vishal , Srivastava Abhay Nanda , Thakur O. P. , Dwivedi D.K. , Siqueiros J.M. , Herrera Oscar Raymond , Sharma subhash 
Published: February 2025

Abstract
The hybrid halide perovskite CH3NH3PbI3-based humidity sensors demonstrate significant progress in detection range, response time, and durability. These improvements are attributed to the ionic conductivity of the material, tunable bandgap, and defect engineering. Simultaneously, their progress in energy conversion devices, such as solar cells, has achieved remarkable efficiency gains, exceeding 25%. The key challenges for commercializing these devices are moisture-induced degradation, lead toxicity, and scalability. Therefore, future research should prioritize stabilizing the material through novel encapsulation strategies, exploring lead-free alternatives, and developing multifunctional devices that synergistically exploit humidity sensitivity and energy conversion capabilities.
Impact of SnS2/Fe Nanofiller on PVA/PVP Blended Polymer: Structural, Electrical and Radiation Shielding Properties
Authors: Mohamed Mohamed Bakr , El naggar A M , Heiba Zein K. , Kamal A M 
Published: February 2025

Abstract
Structure and morphology of PVA/PVP/SnS2/Fe-doped blends were considered employing X-ray diffraction and scanning electron microscopy. Maximum dielectric value was attained in the PVA/PVP/1 wt % SnS2/Fe blended polymers. Relaxation time was affected by the amount of filler. Energy density and AC conductivity were improved as the blend loaded with 5 wt % SnS2/Fe. Radiation parameters for all blends were explored using the Phy-X/PSD program. All blends exhibited relatively elevated MAC values at lower energy, specifically 15 keV. MAC diminished to 0.095 cm²/g for all blends when energy increased to 0.5 MeV. Doped blends had enhanced photon attenuation capacities. Doped samples exhibited superior attenuation properties. The doped blend with 10 wt% SnS2/Fe required the least thickness to attenuate photons at select energies relative to other blended polymers. At 0.5 MeV, the TF values were 89.33%, 89.03%, 89.83%, 88.02%, and 86.77% for samples with x values of 0, 1, 3, 5, and 10, respectively. At 5 cm thickness, TF % values were 56.88, 55.92, 58.50, 52.83, and 49.17 for samples with x values of 0, 1, 3, 5, and 10, respectively. At a distance of 1 cm, RPE values were 10.67%, 10.97%, 10.17%, 11.98%, and 13.23% for samples with x values of 0, 1, 3, 5, and 10, respectively. At 5 cm, RPE values rose to 43.12%, 44.08%, 41.49%, 47.17%, and 50.83% for the corresponding blends, respectively
Physicochemical Evaluation of PMMA Doped TiO2 Nanoparticles and Their Antimicrobial Features
Authors: Bakr Ahmed M , Darwish Abdelfattah , Elawady Mohamed , Hamed Ahmed A. , Azab Ali , Elzwawy Amir 
Published: February 2025

Abstract
Herein, the authors have explored the effect of incorporating TiO2 (0.01, 0.05, and 0.1 wt%) into the PMMA network. The crystal structure of the pure and doped PMMA displayed amorphous to crystalline shift with a 17 nm for TiO2 and 10 nm of PMMA/TiO2 with the highest wt %. Maximum reflectance scopes 62% for PMMA/TiO2 0.1 wt% at 456 nm. The reduced bandgap from 4.2 for PMMA to 3.3 eV for PMMA/TiO2 0.1 wt% potentilally by the emergence of energy levels. Fourier transform infrared spectroscopy demonstrated the resembling spectroscopy without shifts in representative peaks except for the increase in the peak cited at 450 cm-1, accredited to the Ti-O bond. The dielectric features verified the insertion of TiO2 into PMMA matrix triggered the permittivity improvement, offering interfaces for the charges accumulation. The Antimicrobial specifications of the PMMA and PMMA/ TiO2 were examined versus B. Subtilis, S. aureus, K. pneumoniae, E. Coli, C. albicans, and A. niger. The advanced TiO2 wt % the larger antimicrobial activity, particularly regarding gram-negative bacteria. Highest activity demonstrated 67.42% versus K. pneumoniae for PMMA/TiO2 0.1 wt%, although the antifungal activity against C. albicans and A. niger was inconsequential.
Design and Optimization of THz Refractive Index Diamond Shaped Hollow Core Biosensor for Brain Tissue Detection and Behaviour Prediction
Authors: N Vithyalakshmi , M S Mohamed Mallick , Mubarakali Azath , Elshafie Hashim 
Published: February 2025

Abstract
The diagnosis of brain tumors remains a challenging and resource-intensive task due to the complexity of brain tissue and the limitations of existing diagnostic tools. Biosensors operating in THz regime can be used to monitor changes in the characteristics of brain tissues, including refractive index, However, the technical drawbacks of such systems are high costs, long signal acquisition tim,e and the need for high-performance calculations. In this research, we proposed a Terahertz (THz) refractive index-based novel diamond hollow-core biosensor for examining various brain tissues. The biosensor has a sensitivity range of 1.30 to 1.40 RI and a figure of merit that falls between 51000 nm RIU⁻¹, allowing for precise and accurate real-time diagnosis. The second contribution involves applying advanced optimization approach to optimize the model parameters. With a sensitivity of 99.45%, specificity of 99.78%, precision of 99.51%, and total accuracy of 99.93% in identifying malignant brain tissues, performance analysis shows exceptional results.
TRAPping the effects of tobacco smoking: the regulation and function of Acp5 expression in lung macrophages
Authors: Willems Suzanne H. , Qian Shilei , Lång Pernilla , Overtoom Bjarne E. , Alimostafazadeh Sina , Fuentes-Mateos Rocío , Vasse Gwenda F. , van der Veen T. Anienke , Vlasma Jelmer , De Jager Marina H. , Guryev Victor , Fejer Gyorgy , Andersson Göran , Melgert Barbro N. 
Published: February 2025

Tartrate-resistant acid phosphatase (TRAP, gene Acp5) is highly expressed in alveolar macrophages with proposed roles in lung inflammation and lung fibrosis development. We previously showed that its expression and activity are higher in lung macrophages of smokers and COPD patients, suggesting involvement in smoke-induced lung damage. In this study we explored the function of TRAP and regulation of its different mRNA transcripts (Acp5 201-206) in lung tissue exposed to cigarette smoke to elucidate its function in alveolar macrophages. In mice exposed to cigarette smoke or air for 4-6 weeks, higher Acp5 mRNA expression in lung tissue after smoking was mainly driven by transcript Acp5-202, which originates from macrophages. Expression of Acp5-202 correlated with transcription factors previously found to drive proliferation of macrophages. Treating fetal liver progenitors-derived alveolar-like macrophages (MPI macrophages) with cigarette smoke extract resulted in more proliferation compared to nontreated cells. In contrast, Acp5-deficient MPI macrophages and MPI macrophages treated with a TRAP inhibitor proliferated significantly less than control macrophages. Mechanistically this lack of proliferation after TRAP inhibition was associated with higher presence of phosphorylated β-catenin compared to nontreated controls. Phosphorylation of β-catenin is known to mark it for ubiquitination and degradation by the proteasome, preventing its activity in promoting cell proliferation. In conclusion, our findings provide strong evidence for TRAP stimulating alveolar macrophage proliferation by dephosphorylating β-catenin. By driving proliferation, TRAP likely helps sustain alveolar macrophage populations during smoke exposure, either compensating for their loss due to smoking or increasing their numbers to better manage smoke-induced damage.
A model of intra-tumor and inter-patient heterogeneity explains clinical trials of curative combination therapy for lymphoma
Authors: Pomeroy Amy E. , Palmer Adam C. 
Published: February 2025

Abstract
Models of tumor drug response have illuminated important concepts in oncology, but there remains a need for theory that combines intra-tumor and inter-patient heterogeneity to explain patient outcomes, especially for curative treatments. We present a mathematical model of multi-drug therapy that describes both cell-to-cell and patient-to-patient heterogeneity as distributions of drug sensitivity, and apply it to simulate curative combination therapies for Diffuse Large B-Cell Lymphoma (DLBCL). Simulated trials reproduced Progression-Free Survival and changes in circulating tumor DNA observed under standard therapy, and accurately predicted success or failure of nine randomized trials of first-line combinations based on drugs’ efficacies in relapsed/refractory DLBCL. Finally, we used the model to explore how drug synergies, biomarkers, and subtype-specific endpoints could improve the chance of success of targeted combination therapies. This study offers a quantitative model of curative drug combinations and suggests that predictive simulations could aid the design of new regimens with curative intent.
Security without Exclusivity: Hybrid Alignment under U.S.-China Competition
Authors: Greitens Sheena Chestnut , Kardon Isaac B. 
Published: February 2025

Abstract
This article explores an emerging dynamic in the international system: Countries across the world are engaged in simultaneous security cooperation with both China and the United States. China and the United States, however, do not provide the same types of security goods. The United States primarily offers regional security—assistance that improves partners’ capabilities to deter or deny external threats to their territory. China primarily offers regime security—assistance that builds partners’ capabilities to control their territory and populations, and often, to prevent threats to a regime's hold on power. Many countries benefit from both types of assistance, and neither China nor the United States is in a strong position to demand exclusivity from third countries. As a result, a growing number of countries are developing nonexclusive, differentiated security relationships with both great powers. We call this phenomenon “security hybridization” and demonstrate that it is theoretically and empirically distinct from traditional balancing and omnibalancing. We illustrate this dynamic with two case studies—Vietnam and the United Arab Emirates. Each country engages in defense cooperation with the United States and, simultaneously, pursues increasingly robust internal security cooperation with China. Security hybridization distinguishes today's great power competition from Cold War rivalry and will likely shape patterns of domestic and global security in the years ahead.
Approximating Human-Level 3D Visual Inferences With Deep Neural Networks
Authors: O’Connell Thomas P. , Bonnen Tyler , Friedman Yoni , Tewari Ayush , Sitzmann Vincent , Tenenbaum Joshua B. , Kanwisher Nancy 
Published: February 2025

Abstract
Humans make rich inferences about the geometry of the visual world. While deep neural networks (DNNs) achieve human-level performance on some psychophysical tasks (e.g., rapid classification of object or scene categories), they often fail in tasks requiring inferences about the underlying shape of objects or scenes. Here, we ask whether and how this gap in 3D shape representation between DNNs and humans can be closed. First, we define the problem space: after generating a stimulus set to evaluate 3D shape inferences using a match-to-sample task, we confirm that standard DNNs are unable to reach human performance. Next, we construct a set of candidate 3D-aware DNNs including 3D neural field (Light Field Network), autoencoder, and convolutional architectures. We investigate the role of the learning objective and dataset by training single-view (the model only sees one viewpoint of an object per training trial) and multi-view (the model is trained to associate multiple viewpoints of each object per training trial) versions of each architecture. When the same object categories appear in the model training and match-to-sample test sets, multi-view DNNs approach human-level performance for 3D shape matching, highlighting the importance of a learning objective that enforces a common representation across viewpoints of the same object. Furthermore, the 3D Light Field Network was the model most similar to humans across all tests, suggesting that building in 3D inductive biases increases human-model alignment. Finally, we explore the generalization performance of multi-view DNNs to out-of-distribution object categories not seen during training. Overall, our work shows that multi-view learning objectives for DNNs are necessary but not sufficient to make similar 3D shape inferences as humans and reveals limitations in capturing human-like shape inferences that may be inherent to DNN modeling approaches. We provide a methodology for understanding human 3D shape perception within a deep learning framework and highlight out-of-domain generalization as the next challenge for learning human-like 3D representations with DNNs.
Requesting Confirmation or Reconfirmation across Languages: An Introduction
Authors: König Katharina , Pfeiffer Martin 
Published: February 2025

Abstract
This special issue presents a collection of conversation-analytic and interactional-linguistic studies concerned with the cross-linguistic analysis of requests for confirmation (RfC) and requests for reconfirmation (RfRCs) as two distinct types of polar questions. In this paper, we outline a characterisation of the two actions with reference to their epistemic gradient and their sequential design, which does not take specific linguistic resources as its starting point and thus lends itself to comparative analysis. We review previous research on the linguistic design of RfCs and RfRCs and the responses they invite in different languages before we summarise the main findings of the papers in this issue. The final section discusses perspectives for future research on interactional and epistemic styles across languages.
A new species of Elisama Giebel, 1856 (Blattaria: Blattulidae) discovered in mid-Cretaceous Kachin amber of northern Myanmar
Authors: SENDI HEMEN 
Published: February 2025

Elisama Giebel, 1856 is a cockroach genus of the family Blattulidae Vishniakova, 1982 ranging from the Late Jurassic to the Late Cretaceous. Elisama kacerovae sp. nov. is herein described based on a completely preserved adult, and it is the first representative of the genus in Cenomanian northern Myanmar amber. It differs from other species of Elisama in being smaller in size, having a darkly striated pronotum with translucent nota and in the forewing with stem of M appressing R in the basal half of the wing. Elisama shares a dark macula on the forewings with Vrtula Vršanský, 2008, Huablattula Qiu, Wang et Che, 2019, Svabula Vršanský, 2005, Nogueroblatta Martínez-Delclòs, 1993 and Spono Vršanský, 2024. Some blattulid genera, such as the former four, are likely in need of revision. Except for E. globosa from Mdeyrij-Hammana amber in Lebanon, all species were discovered in sedimentary rocks of former Gondwana and Laurasia. It is possible that representatives of Elisama mainly prospered in less humid environments with milder climate instead of tropical forest ecosystems, where they were apparently rare in the fossil record, although taphonomic bias cannot be ruled out completely.
A unified interpretation of variability in precipitation isotope ratios
Authors: Siler Nicholas , Fiorella Richard P. , Kukla Tyler 
Published: February 2025

Abstract
Several mechanisms have been proposed to explain why the isotope ratios of precipitation vary in space and time and why they correlate with other climate variables like temperature and precipitation. Here we argue that this behavior is best understood through the lens of radiative transfer, which treats the depletion of atmospheric vapor transport by precipitation as analogous to the attenuation of light by absorption or scattering. Building on earlier work by Siler et al. (2021), we introduce a simple model that uses the equations of radiative transfer to approximate the two-dimensional pattern of the oxygen isotope composition of precipitation (δp) from monthly-mean hydrologic variables. The model accurately simulates the spatial and seasonal variability in δp within a state-of-the-art climate model, and permits a simple decomposition of δp variability into contributions from gradients in evaporation and the length scale of vapor transport. Outside the tropics, δp is mostly controlled by gradients in evaporation, whose dependence on temperature explains the positive correlation between δp and temperature (i.e., the temperature effect). At low latitudes, δp is mostly controlled by gradients in the transport length scale, whose inverse relationship with precipitation explains the negative correlation between δp and precipitation (i.e., the amount effect). This suggests that the temperature and amount effects are both mostly explained by variability in upstream rainout, but they reflect distinct mechanisms governing rainout at different latitudes.