bluuebunny/crossref_metadata_2025_split huggingface dataset:
Laminated Carbon Based Flexible Printed Perovskite Solar Cells Passivated with Tin(II) Phthalocyanine
Authors: Mussakhanuly Nursultan , Yerlanuly Yerassyl , Parkhomenko Hryhorii P. , Niyetullayeva Adiya , Azamat Aidana K. , Sultanov Assanali , Kukhayeva Zarina , Ng Annie , Jumabekov Askhat N. 
Published: January 2025

AbstractProduction scalability, efficiency, and stability challenges continue to impede the commercial viability of perovskite solar cells (PSCs). In this study, a multifunctional passivation technique is introduced, designed to enhance the efficiency and stability of printable, air‐processed PSCs with laminated carbon electrodes. This findings indicate that tin(II) phthalocyanine (SnPC) molecules act as an interfacial layer between the absorber and the hole‐transporting layer (HTL), effectively passivating surface trap states and facilitating hole extraction. Optimal SnPC surface treatment reduces the trap density in the perovskite layer from 2.1 × 1015 to 1.5 × 1015 cm−3, increases carrier mobility (from 2.7 × 10−3 to 2.8 × 10−3 cm2 Vs−1), and extends carrier lifetime. SEM, AFM, EDS, and XPS analyses confirm the presence of SnPC on the perovskite layer surface and its influence on surface morphology. Devices treated with an optimal SnPC concentration exhibit significant efficiency improvements, from 6.4% to 8.5%, along with a threefold increase in photo‐stability. Thus, SnPC may serve as a passivating buffer layer for the perovskite surface, offering protection against photo‐degradation.
Monolithic Integrated Multi‐Parameter Light‐Field Sensor Based on Tailored Disordered Nanostructures
Authors: Ha Yingli , Wang Lijun , Guo Yinghui , Pu Mingbo , She Senwei , Liu Zhenyu , Xu Mingfeng , Zhang Fei , Luo Xiangang 
Published: January 2025

AbstractLight fields carry abundant information, including intensity, spectral, and polarization, which have been widely studied in imaging, quantum technologies, and communications. However, conventional cameras are typically limited to capturing intensity alone, neglecting other crucial dimensions of information, which restricts their application scope. Disordered nanostructures significantly enhance light scattering and absorption, thereby broadening the spectral response range and enabling the sensitive detection of multi‐dimensional physical information, including angle, wavelength, and polarization state. Here, by combining disordered nanostructures with silicon‐on‐insulator (SOI) waveguides, an integrated light‐field sensor that integrates angle, wavelength, and polarization detection is successfully realized. The sensor, with a compact integration footprint of 32 × 32 µm2, demonstrated angle detection with a resolution of 3.2° within elevation angles ranging from −20° to 20°, and spectral reconstruction with a resolution of 3.25 nm across wavelengths from 1520 to 1550 nm. Additionally, azimuth and polarization state detection functionalities are further validated. This multi‐parameter, highly integrated design enhances the performance of photonic integrated circuits (PICs) and shows great potential for applications in LIDAR, satellite communication, and optical interconnection.
Ambient‐Air‐Processed, Solution‐Based Organic Photovoltaics and Photodetectors
Authors: Nasrollahi Bahareh , Jailani Javith Mohammed , Loftus Jacob , Pecunia Vincenzo 
Published: January 2025

AbstractOrganic photovoltaics (OPVs) and organic photodetectors (OPDs), which use conjugated polymers and molecules as photoactive materials, hold significant promise for energy harvesting and sensing applications due to their customizable optoelectronic properties, potential mechanical flexibility, and compatibility with low‐cost, high‐throughput manufacturing. However, OPV and OPD research to date has typically relied on device fabrication in controlled environments (e.g., glove boxes filled with inert gases) and vacuum‐deposited (rather than solution‐processed) electrodes, limiting scalability and increasing manufacturing complexity and cost. This review explores these challenges by surveying the development of ambient‐air‐processed, solution‐based (APSB) OPVs and OPDs, which not only use solution‐processed electrodes but are also entirely fabricated under ambient conditions. Various solution processing techniques, solution‐processed electrodes, and the performance of APSB OPVs and OPDs are comprehensively examined, offering insights for future research to advance these technologies toward ultra‐low‐cost optoelectronics and energy harvesting.
High‐Performance and Ultrafast Single Germanium Nanowire Photodetectors
Authors: Echresh Ahmad , Shaikh Mohd Saif , Catuneanu Mircea Traian , Arora Himani , Zhou Shengqiang , Erbe Artur , Helm Manfred , Rebohle Lars , Jamshidi Kambiz , Berencén Yonder , Georgiev Yordan M. 
Published: January 2025

AbstractSemiconductor nanowire‐based photodetectors with high sensitivity and fast photoresponse in the near‐infrared wavelength range are crucial for applications in light‐wave communication switches, as well as environmental and atmospheric sensing. However, to advance this field, it is essential to develop innovative fabrication techniques that improve device performance. Here, the fabrication of an axial p–n junction along single germanium nanowires (Ge NWs) and their photoresponse characterization at near‐infrared wavelengths are reported. The resulting devices exhibit rectifying current–voltage characteristics with a high rectification ratio in dark conditions and operate with high sensitivity at zero bias under illumination. A high responsivity of 1.72 AW−1, a low noise‐equivalent power of 5.68 × 10−11 , and a high‐frequency response with a 3dB cut‐off frequency of 2.85 GHz are determined under 850 nm laser illumination at reverse bias. The high sensitivity of the Ge NW‐based photodetectors is ascribed to the radial built‐in electric field, which increases the carrier lifetime. In addition, the small size of the Ge NWs results in very small capacitance, leading to very fast response. These results have significant potential for advancing high‐speed and low‐power photodetectors in next‐generation optical communication systems and integrated optoelectronic devices.
Behavior Identification of Silicone‐Ethanol Soft Actuator Based on Statistical Analysis
Authors: Zamyad Hojat , Sahebian Samaneh , Safaie Javad 
Published: January 2025

AbstractSilicone‐ethanol actuator is a new type of artificial muscle that expands and contracts based on the switching of the ethanol phase between liquid and gas states within the elastomeric matrix. However, there is a lack of accurate ranking of the parameters that affect its performance. This research uses cutting‐edge statistical and qualitative methods to rank the behavioral characteristics of this actuator. In this research, the effect of the power intensity on the performance and structural changes of the silicone‐ethanol actuator is investigated, for the first time. It is found that the use of more intense power increased the response speed of the actuator, but also intensifies its structural damage. Also, the results show that energy and temperature are the most crucial variables in predicting the dynamic behavior of the silicone‐ethanol actuator while ethanol content and applied power are the most important functional characteristics in the long term. It is hoped that this scientific approach will be leveraged to distinguish real from dummy behavioral indices of the other newfound smart materials, where there is no complete knowledge of their governing physical and chemical equations.
Positive Feedback Regulation between KLF5 and XPO1 Promotes Cell Cycle Progression of Basal like Breast Cancer
Authors: Tang Yu , Liu Rui , Zhu Jing , He Qian , Pan Chenglong , Zhou Zhongmei , Sun Jian , Li Fubing , Zhang Longlong , Shi Yujie , Yao Jing , Jiang Dewei , Chen Ceshi 
Published: January 2025

AbstractBasal‐like breast cancer (BLBC), overlapping with the subgroup of estrogen receptor (ER), progesterone receptor (PR), and HER2 triple‐negative breast cancer, has the worst prognosis and limited therapeutics. The XPO1 gene encodes nuclear export protein 1, a promising anticancer target which mediates nucleus‐cytoplasm transport of nuclear export signal containing proteins such as tumor suppressor RB1 and some RNAs. Despite drugs targeting XPO1 are used in clinical, the regulation of XPO1 expression and functional mechanism is poorly understood, especially in BLBC. This study finds that KLF5 is a transcription factor of XPO1, which increases RB1 nuclear export and cell proliferation in BLBC cells. Furthermore, XPO1 interacts with the RNA‐binding protein PTBP1 to export FOXO1 mRNA to cytoplasm and thus activates the FOXO1‐KLF5 axis as a feedback. This work demonstrates that XPO1 inhibitor KPT‐330 in combination with CDK4/6 inhibitor additively suppressed BLBC tumor growth in vivo. These results reveal a novel positive feedback regulation loop between KLF5 and XPO1 and provide a novel treatment strategy for BLBC.
Decoding the Implications of Zinc in the Development and Therapy of Leukemia
Authors: Zhu Bo , Yang Chunhao , Hua Siqi , Li Kaiqiang , Shang Pengyou , Li Zhonghua , Qian Wei , Xue Shunkang , Zhi Qi , Hua Zichun 
Published: January 2025

AbstractZinc plays a central role in the hematological development. Therapeutic interventions with zinc are shown to improve the health status of patients with malignancies by stimulating the immune system and reducing side effects. Despite the abnormal zinc homeostasis in leukemia, the role and mechanisms of zinc signaling in leukemia development remain poorly understood. Recently, some important breakthroughs are made in laboratory and clinical studies of zinc in leukemia, such as the role of zinc in regulating ferroptosis and the effects of zinc in immunotherapy. Zinc‐based strategies are urgently needed to refine the current zinc intervention regimen for side‐effect free therapy in chemotherapy‐intolerant patients. This review provides a comprehensive overview of the role of zinc homeostasis in leukemia patients and focuses on the therapeutic potential of zinc signaling modulation in leukemia.
Mitochondrial Protein MjEF‐Tu is Secreted into Host Plants by Nematodes Eliciting Immune Signaling and Resistance
Authors: Lin Borong , Huang Shaozhen , Li Zhiwen , Huang Qiuling , Song Handa , Fang Tianyi , Liao Jinling , Gheysen Godelieve , Zhuo Kan 
Published: January 2025

AbstractLittle is known about plant‐parasitic animal‐derived pathogen‐associated molecular pattern (PAMP)/ pattern‐recognition receptor (PRR) pairs. Additionally, mitochondrial proteins have not previously been reported to be secreted into hosts by pathogens. Here, it is found that the Meloidogyne javanica elongation factor thermo unstable (EF‐Tu) (MjEF‐Tu) located in the nematode mitochondria is up‐regulated and secreted into the host plant during nematode parasitism. MjEF‐Tu interacts with the PRR Arabidopsis thaliana EF‐Tu receptor (AtEFR), triggering the plant hallmark defence responses mediated by AtEFR. An 18‐aa sequence (Nelf18) in the N terminus of the nematode EF‐Tu contributes to the immunogenic activity. M. javanica water extract and mitochondrial extract also induce plant immunity sensed by AtEFR, owing to the presence of MjEF‐Tu. In addition, Nelf18 enhances plant resistance to nematode, virus, and bacterial infections depending on AtEFR. These findings first demonstrate that mitochondrial proteins from pathogens can be secreted into hosts and function as a cross‐kingdom signal and identified the first plant‐parasitic animal‐derived proteinaceous PAMP/PRR pair, providing novel insights into host‐pathogen interactions.
Epigenetic Impacts of Non‐Coding Mutations Deciphered Through Pre‐Trained DNA Language Model at Single‐Cell Resolution
Authors: Liu Zhe , Gu An , Bao Yihang , Lin Guan Ning 
Published: January 2025

AbstractDNA methylation plays a critical role in gene regulation, affecting cellular differentiation and disease progression, particularly in non‐coding regions. However, predicting the epigenetic consequences of non‐coding mutations at single‐cell resolution remains a challenge. Existing tools have limited prediction capacity and struggle to capture dynamic, cell‐type‐specific regulatory changes that are crucial for understanding disease mechanisms. Here, Methven, a deep learning framework designed is presented to predict the effects of non‐coding mutations on DNA methylation at single‐cell resolution. Methven integrates DNA sequence with single‐cell ATAC‐seq data and models SNP‐CpG interactions over 100 kbp genomic distances. By using a divide‐and‐conquer approach, Methven accurately predicts both short‐ and long‐range regulatory interactions and leverages the pre‐trained DNA language model for enhanced precision in classification and regression tasks. Methven outperforms existing methods and demonstrates robust generalizability to monocyte datasets. Importantly, it identifies CpG sites associated with rheumatoid arthritis, revealing key pathways involved in immune regulation and disease progression. Methven's ability to detect progressive epigenetic changes provides crucial insights into gene regulation in complex diseases. These findings demonstrate Methven's potential as a powerful tool for basic research and clinical applications, advancing this understanding of non‐coding mutations and their role in disease, while offering new opportunities for personalized medicine.
A Novel Missense Mutation of the ABL1 Gene in a Child With Congenital Heart Defects and Skeletal Malformations Syndrome
Authors: Chen Ting‐Yi , Chen Yi , Tang Lan‐Fang 
Published: January 2025

ABSTRACTCongenital heart defects and skeletal malformations syndrome (CHDSKM) is a rare autosomal dominant genetic disorder characterized by specific clinical features, including dysmorphic facial traits, congenital heart defects, skeletal abnormalities, joint issues, and failure to thrive. The novelty of this case lies in the identification of a novel mutation in the ABL1 gene, expanding the genetic spectrum associated with this syndrome. A 5.9‐year‐old boy was referred to the clinic due to growth retardation and intellectual disability. Clinical evaluation revealed several hallmark features of CHDSKM, including distinct facial dysmorphisms such as a broad forehead, frontal bossing, micrognathia, low‐set ears, and short palpebral fissures. The patient was diagnosed with congenital heart defects, including a ventricular septal defect, atrial septal defect, and patent ductus arteriosus. Skeletal malformations included scoliosis and finger contractures. Additionally, he exhibited developmental delay, gastrointestinal issues such as umbilical hernia and intestinal malrotation, intellectual disability, and dysgenesis of the corpus callosum, which are atypical for this syndrome. Molecular genetic analysis identified a de novo mutation (c.898C>G) in exon 5 of the ABL1 gene, resulting in a novel missense mutation (p.Gln300Glu). This case emphasizes the importance of considering CHDSKM in the differential diagnosis of children with growth and developmental concerns. The identification of a novel mutation in the ABL1 gene highlights the critical role of early molecular genetic testing, which can facilitate improved management and support for affected individuals and their families.
Predicting conversion in cognitively normal and mild cognitive impairment individuals with machine learning: Is the CSF status still relevant?
Authors: Russo Mirella , Nardini Davide , Melchiorre Sara , Ciprietti Consuelo , Polito Gaetano , Punzi Miriam , Dono Fedele , Santilli Matteo , Thomas Astrid , Sensi Stefano L. ,   the Alzheimer's Disease Neuroimaging Initiative
Published: January 2025

AbstractINTRODUCTIONMachine learning (ML) helps diagnose the mild cognitive impairment–Alzheimer's disease (MCI‐AD) spectrum. However, ML is fed with data unavailable in standard clinical practice. Thus, we tested a novel multi‐step ML approach to predict cognitive worsening.METHODSWe selected cognitively normal and MCI participants from the Alzheimer's Disease Neuroimaging Initiative dataset and categorized them on total tau/amyloid beta 1‐42 ratios. ML was applied to predict the 3‐year conversion with standard clinical data (SCD), assess the model's accuracy, and identify the role of cerebrospinal fluid (CSF) biomarkers in this approach. Shapley Additive Explanations (SHAP) analysis was carried out to explore the automated decisional process.RESULTSThe model achieved 84% accuracy across the entire cohort, 86% in patients with negative CSF, and 88% in individuals with AD‐like CSF. SHAP analysis identified differences between CSF‐positive and ‐negative patients in predictors of conversion and cut‐offs.CONCLUSIONSThe approach yielded good prediction accuracy using SCD. However, CSF‐based categorizations are needed to improve predictive accuracy.Highlights
Machine learning algorithms can predict cognitive decline with standard and routinely used clinical data.
Classification according to cerebrospinal fluid biomarkers enhances prediction accuracy.
Different cut‐offs could be applied to neuropsychological tests to predict conversion.
Low‐Dimensional Hetero‐Interlayer Enabling Sub‐Bandgap Photovoltaic Conversion for Perovskite Solar Cells
Authors: Wu Yutong , Chang Bohong , Li Hui , Wang Lian , Liu Zhen , Yin Longwei 
Published: January 2025

AbstractActualizing sub‐band gap photovoltaic conversion is effective in remitting energy loss and pushing theoretical efficiency limits for perovskite solar cells (PSCs). Herein, a zero‐dimensional organic metal halide based on hydroxyquinoline (HQ) is developed to sensitize PSCs for near‐infrared region gain to implement sub‐band gap photovoltaic conversion for enhancing power‐conversion‐efficiency (PCE) of PSCs. [ZnI4]2− skeletons containing heavy atoms intensify the direct singlet‐to‐triplet state transition of organic chromophores HQ. Meanwhile, the triplet energy of HQ is close to resonance with perovskite band gap, favoring the energy transfer to perovskite and exciting the additional electron‐hole pairs, which was observed by transient absorption spectroscopy, confirming the sensitization of perovskite to increase sub‐band gap photocurrent. HQ2ZnI4 modifies electronic and crystal structure, optimizes energy‐level arrangement, and acts as a protective layer, realizing considerable PCEs in small (6.25 mm2)‐/larger‐area (1 cm2) devices and excellent operational stability. This low‐cost strategy brings vitality to the light management of PSCs and expands low‐dimensional materials.
Preparation of Mesocarbon Microbeads (MCMBs) by the Copolycondensation of High‐Temperature Coal Tar Pitch and Ethylene Tar Pitch
Authors: Tianao Yu , Yilin Fang , Yaming Zhu , Junxia Cheng , Ying Wang , Xuefei Zhao 
Published: January 2025

ABSTRACTMesocarbon microbeads (MCMBs) are a kind of typical spherical functional synthetic carbon materials widely used in various fields. However, MCMBs produced through thermal polycondensation using high coal tar pitch exhibit certain defects that limit their further development. These include challenges in controlling particle size, low yield, and difficulties in regulating their internal microstructure and surface morphology. In this study, MCMBs were prepared via the copolycondensation of high‐temperature coal tar pitch (HCTP) and ethylene tar pitch (ETP). The effect of ETP addition on the formation process, microstructure, and electrochemical properties of the resulting MCMBs was investigated. Polarizing microscopy, scanning electron microscopy (SEM), laser particle size analysis, single‐crystal X‐ray diffraction (XRD), Raman spectroscopy, and electrochemical impedance spectroscopy (EIS) were employed to analyze the MCMBs. The addition of ETP was found to modify the molecular structure of the blended pitch and promote the formation of MCMBs during the copolymerization process. Furthermore, the MCMBs obtained via this method exhibited excellent sphericity, uniform particle size distribution, reduced structural defects, and lower charge transfer resistance (Rct). Notably, when the ETP content was 7%, the MCMBs achieved an average particle size of 19.65 μm, a particle size uniformity index (U) of 1.12, and the lowest charge transfer resistance of 2.947 Ω after carbonization.
Negative Probability
Authors: Polson Nick , Sokolov Vadim 
Published: January 2025

ABSTRACTNegative probabilities arise primarily in physics, statistical quantum mechanics, and quantum computing. Negative probabilities arise as mixing distributions of unobserved latent variables in Bayesian modeling. Our goal is to provide a link between these two viewpoints. Bartlett provides a definition of negative probabilities based on extraordinary random variables and properties of their characteristic function. A version of the Bayes rule is given with negative mixing weights. The classic half‐coin distribution and Polya‐Gamma mixing are discussed. Heisenberg's principle of uncertainty and the duality of scale mixtures of Normals is also discussed. A number of examples of dual densities with negative mixing measures are provided including the Linnik and Wigner distributions. Finally, we conclude with directions for future research.
Advancements in Silicon Anodes for Enhanced Lithium‐Ion Batteries Performance: Innovations Toward Next‐Gen Superbatteries
Authors: Saidi Norshahirah Mohamad , Abdah Muhammad Amirul Aizat Mohd , Mustafa Muhammad Norhaffis , Walvekar Rashmi , Khalid Mohammad , Khosla Ajit 
Published: January 2025

ABSTRACTSilicon (Si)‐based materials have emerged as promising alternatives to graphite anodes in lithium‐ion (Li‐ion) batteries due to their exceptionally high theoretical capacity. However, their practical deployment remains constrained by challenges such as significant volume changes during lithiation, poor electrical conductivity, and the instability of the solid electrolyte interphase (SEI). This review critically examines recent advancements in Si‐based nanostructures to enhance stability and electrochemical performance. Distinct from prior studies, it highlights the application of Si anodes in commercial domains, including electric vehicles, consumer electronics, and renewable energy storage systems, where prolonged cycle life and improved power density are crucial. Special emphasis is placed on emerging fabrication techniques, particularly scalable and cost‐effective methods such as electrospinning and sol–gel processes, which show promise for industrial adoption. By addressing both the technical innovations and economic considerations surrounding Si anodes, this review provides a comprehensive roadmap for overcoming existing barriers, paving the way for next‐generation, high‐performance batteries.