bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metasurface Enabled Multi‐Target and Multi‐Wavelength Diffraction Neural Networks
Authors: Chi Haoxiang , Zang Xiaofei , Zhang Teng , Wang Guannan , Fan Zhiyuan , Zhu Yiming , Chen Xianzhong , Zhuang Songlin 
Published: September 2024

AbstractBenefiting from low power consumption and high processing speed, there is a growing interest in diffraction neural networks (DNNs), which are typically showcased with 3D printing devices, leading to large volumes, high costs, and low levels of integration. Metasurfaces can desirably manipulate wavefronts of electromagnetic waves, providing a compact platform for mimicking DNNs with novel functions. Although multi‐wavelength and multi‐target recognition provides a richer and more detailed understanding of complex environments, existing architectures are primarily trained to classify a single target at a specific wavelength. A metasurface approach is proposed to design multiplexed DNNs that can classify multiple targets and spatial sequences across various wavelengths in multiple channels. To realize multi‐task processing, the dielectric metasurface is designed based on phase and wavelength multiplexing, which can integrate multi‐target DNNs with different tasks such as operating at distinct wavelengths and classifying diverse targets. The efficacy of this method is exemplified through the numerical simulation and experimental demonstration of recognizing a single target with two wavelengths, two targets at a single wavelength, and two targets at dual wavelengths. This compact metasurface approach enables the design of multi‐target and multi‐wavelength DNNs, opening a new window to develop massively parallel processing and versatile artificial intelligence systems.
Atomistic Simulations Reveal Crucial Role of Metal Ions for Ligand Binding in Guanidine‐I Riboswitch
Authors: Franke Leon , Globisch Christoph , Karakurt Mehmet Can , Stephan Theresa , Peter Christine 
Published: September 2024

AbstractRiboswitches are structured ribonucleic acid (RNA) segments that act as specific sensors for small molecules in bacterial metabolism. Due to the flexible nature of these highly charged macromolecules, molecular dynamics simulations are instrumental to investigating the mechanistic details of their regulatory function. In the present study, the guanidine‐I riboswitch serves as an example of how atomistic simulations can shed light on the effect of ions on the structure and dynamics of RNA and on ligand binding. Relying on two orthologous crystal structures from different bacterial species, it is demonstrated how the ion setup crucially determines whether the simulation yields meaningful insights into the conformational stability of the RNA, functionally relevant residues and RNA‐ligand interactions. The ion setup in this context includes diffuse ions in solution and bound ions associated directly with the RNA, in particular a triad of 2 Mg2+ ions and a K+ ion in close proximity to the guanidinium binding site. A detailed investigation of the binding pocket reveals that the K+ from the ion triad plays a decisive role in stabilizing the ligand binding by stabilizing important localized interactions, which in turn contribute to the overall shape of the folded state of the RNA.
A Homozygous Variant in NAA60 Is Associated with Primary Familial Brain Calcification
Authors: Chen Xinhui , Shi Yihua , Fu Feng , Wang Lebo , Yu Hongying , Yang Dehao , Wang Xinchen , Ying Chenxin , Wang Haoyu , Lin Zhiru , Wang Haotian , Zhang Fan , Zheng Xiaosheng , Guo Yuru , Wang Yaoting , Zeng YiHeng , Zhao Miao , Chen Yiling , Li Jiaxiang , Xia Haibin , Chen Jiawen , Wang Bo , Wu Sheng , Xie Fei , Feng Jianhua , Cen Zhidong , Luo Wei 
Published: September 2024

AbstractBackgroundPrimary familial brain calcification (PFBC) is a monogenic disorder characterized by bilateral calcifications in the brain. The genetic basis remains unknown in over half of the PFBC patients, indicating the existence of additional novel causative genes. NAA60 was a recently reported novel causative gene for PFBC.ObjectiveThe aim was to identify the probable novel causative gene in an autosomal recessive inherited PFBC family.MethodsWe performed a comprehensive genetic study on a consanguineous Chinese family with 3 siblings diagnosed with PFBC. We evaluated the effect of the variant in a probable novel causative gene on the protein level using Western blot, immunofluorescence, and coimmunoprecipitation. Possible downstream pathogenic mechanisms were further explored in gene knockout (KO) cell lines and animal models.ResultsWe identified a PFBC co‐segregated homozygous variant of c.460_461del (p.D154Lfs*113) in NAA60. Functional assays showed that this variant disrupts NAA60 protein localization to Golgi and accelerated protein degradation. The mutant NAA60 protein alters its interaction with the PFBC‐related proteins PiT2 and XPR1, affecting intracellular phosphate homeostasis. Further mass spectrometry analysis in NAA60 KO cell lines revealed decreased expression of multiple brain calcification–associated proteins, including reduced folate carrier (RFC), a folate metabolism–related protein.ConclusionsOur study replicated the identification of NAA60 as a novel causative gene for autosomal recessive PFBC, demonstrating our causative variant leads to NAA60 loss of function. The NAA60 loss of function disrupts not only PFBC‐related proteins (eg, PiT2 and XPR1) but also a wide range of other brain calcification–associated membrane protein substrates (eg, RFC), and provided a novel probable pathogenic mechanism for PFBC. © 2024 International Parkinson and Movement Disorder Society.
Bone metastasis scintigram generation using generative adversarial learning with multi‐receptive field learning and two‐stage training
Authors: Lin Qiang , Xie An , Zeng Xianwu , Cao Yongchun , Man Zhengxing , Hao Yusheng , Liu Caihong , Huang Xiaodi 
Published: September 2024

AbstractBackgroundDeep learning is the primary method for conducting automated analysis of SPECT bone scintigrams. The lack of available large‐scale data significantly hinders the development of well‐performing deep learning models, as the performance of a deep learning model is positively correlated with the size of the dataset used. Therefore, there is an urgent demand for an automated data generation method to enlarge the dataset of SPECT bone scintigrams.PurposeWe introduce a deep learning‐based generation model that can generate realistic but not identical samples from the original SPECT bone scintigrams.MethodsFollowing the generative adversarial learning architecture, a bone metastasis scintigram generation model christened BMS‐Gen is proposed. First, BMS‐Gen takes multiple input conditions and employs multi‐receptive field learning to ensure that the generated samples are as realistic as possible. Second, BMS‐Gen adopts generative adversarial learning to retain the diversity of the generated samples. Last, BMS‐Gen uses a two‐stage training strategy to improve the quality of the generated samples.ResultsExperimental evaluation conducted on a set of clinical data of SPECT BM scintigrams has shown the performance of the proposed BMS‐Gen, achieving the best overall scores of 1678.0, 69.33, and 19.51 for FID (Fréchet Inception Distance), MSE (Mean Square Error), and PSNR (Peak Signal‐to‐Noise Ratio) metrics. The introduction of samples generated by BMS‐Gen contributes a maximum (minimum) increase of 3.01% (0.15%) on the F‐1 score and a maximum (minimum) increase of 6.83% (2.21%) on the DSC score for the image classification and segmentation tasks, respectively.ConclusionsThe proposed BMS‐Gen model can be used as a promising tool for augmenting the data of bone scintigrams, greatly facilitating the development of deep learning‐based automated analysis of SPECT bone scintigrams.
Impact of neutrophil‐to‐lymphocyte ratio on the effect of hyperglycemia at admission on clinical outcomes after endovascular thrombectomy
Authors: Tang Tao , Zhang Dawei , Wang Fang , Fan Tieping , Thomas Aline M. , Lan Xiaoyan , Zhao Manhong , Li Di , Zhao Xinghui 
Published: September 2024

AbstractBackgroundThe neutrophil‐to‐lymphocyte ratio (NLR) is highly associated with stress responses to acute disorders and may be useful for differentiating hyperglycemia after stroke that is induced by stress or other causes. This study aims to evaluate whether the NLR modifies the effect of hyperglycemia at admission on clinical outcome after thrombectomy.MethodsWe retrospectively enrolled 343 patients that underwent endovascular thrombectomy for acute anterior circulation large‐vessel occlusion between January 2019 and June 2022. NLR at admission was used to dichotomize patients into low‐NLR and high‐NLR groups according to its median value. The primary outcome was 90‐day functional independence (modified Rankin Scale Score 0–2). Secondary outcomes were 24 h symptomatic intracranial hemorrhage and 90‐day mortality.ResultsOverall, hyperglycemia at admission decreased the likelihood of functional independence (adjusted odds ratio [OR]: 0.34, 95% confidence interval [95% CI]: 0.19–0.60, p < 0.001). There was a significant interaction between the NLR and hyperglycemia at admission on functional independence (p = 0.024). Hyperglycemia at admission was negatively associated with functional independence in low‐NLR patients (adjusted OR: 0.18, 95% CI: 0.07–0.42, p < 0.001), but not in high‐NLR patients (adjusted OR: 0.67, 95% CI: 0.30–1.48, p = 0.320). Interactions between the NLR and hyperglycemia at admission on 24 h symptomatic intracerebral hemorrhage (p = 0.734) and 90‐day mortality (p = 0.657) were not significant.ConclusionsThe NLR modified the detrimental effect of hyperglycemia at admission on functional independence after thrombectomy. Low‐NLR patients with hyperglycemia were at a high risk of poor outcomes, and might more likely benefit from aggressive glucose‐lowering treatment.
Recovery and restoration of glass fibers from end‐of‐life composite waste through pyrolysis and partial oxidation processes combined with hot alkaline surface treatments
Authors: Rafay A. , Irfan M. , Naqvi S. R. , Umer M. A. , Rehman M. A. , Saleem M. , Butt M. S. , Khan A. U. 
Published: September 2024

AbstractEnvironmental hazards caused by the ever‐increasing end‐of‐life (EoL) glass fiber reinforced polymer (GFRPs) composite waste is of major concern for the sustainable development of the industry. Compared to land filling or incineration, pyrolysis is one of the most promising environmentally friendly methods of disposal of EoL GFRPs. Pyrolysis not only results in recovery of clean glass fibers but other valuable products, such as oils. However, long processing time at elevated temperature leads to aggravation of already existed surface flaws along with the structural changes. Therefore, thermal conditioning of glass fibers results in severe deterioration of the strength in recovered fibers and hence limiting the use of recovered fibers to low end‐products. In this study, a new strategy was adopted where instead of complete cleaning of the fibers at pyrolysis stage, the fibers were partially oxidized and the complete removal of char from the surface of glass was done during hot alkaline etching. This strategy was opted to enhance the quality of the required fibers while reducing the processing time. The results showed ~200% increase in strength of fibers after the combined treatment of pyrolysis and post etching compared to the just pyrolyzed samples with etching time of just 1 min.Highlights
End‐of‐life panels of GFRPs were pyrolyzed under inert environment of Argon.
Residual char was partially removed through post oxidation under flowing air.
Hot alkaline etching resulted in complete removal of char and surface defects.
Partial oxidation and short etching cycles resulted in improved strength of recovered glass fibers.
Single‐ion conducting polymer electrolytes with temperature‐independent modulus using cellulose nanocrystal‐MXene and Poly(tetramethylene glycol)‐based waterborne polyurethane and PEO
Authors: Nourany Mohammad , Rostami Sasan , Talebi Farough 
Published: September 2024

AbstractWith the rapid progress of electric vehicles, the focus on high‐energy‐density anodes has increased substantially. Lithium metal (Li) possesses a high energy density of 3800 mAh/g. However, it poses safety issues for liquid electrolytes, mandating the use of safer replacements like solid polymer electrolytes (SPEs). In this regard, polyethylene oxide (PEO), as the most prominent SPE, shows the highest ionic conductivity (σ) among polymers despite facing challenges including loss of thermomechanical stability around 60°C and low lithium‐ion (Li+) transference number (). Here, we designed SPEs consisting of PEO, poly (tetramethylene glycol)‐based waterborne polyurethane (WPU), cellulose nanocrystal (CNC), and MXene. The presence of WPU was quite effective at increasing (). High CNC loading () made elastic modulus () independent of temperature with terminal , while improving σ and . These achievements were attributed to CNCs competing with over oxygen atoms of PEO and the formation of a strong CNC network. was able to increase σ from attributed to intercalation of PEO into its interlayer spaces while also increasing to 0.897. The SPEs showed a high electrochemical stability window. The optimal electrolyte showed high Coulombic efficiency and stable cycling performance.Highlights
Ionomeric units resulted in a high lithium‐ion transference number ()
Hydrogen bonding was partially responsible for increased

Cellulose nanocrystals (CNCs) increased ionic conductivity and

CNCs suppressed PEO spherulites' size and increased thermomechanical stability
MXene disrupts PEO crystal growth and provides a new route for conduction
Alias‐informed model selection (AIMS) for 7 and 8 factor no‐confounding 16‐run fractional factorial designs
Authors: Metcalfe Carly E. , Jones Bradley , Montgomery Douglas C. 
Published: September 2024

AbstractNonregular fractional factorial designs are a preferable alternative to regular resolution IV designs because they avoid confounding 2‐factor interactions. As a result, nonregular designs can estimate and identify a few active 2‐factor interactions. However, due to the sometimes complex alias structure of nonregular designs, standard factor screening strategies can fail to identify all active effects. We report on a screening technique that takes advantage of the alias structure of these nonregular designs. This alias‐informed‐model‐selection (AIMS) technique has been used previously for a specific 6‐factor nonregular design. We show how the AIMS technique can be applied to 7‐ and 8‐factor nonregular designs, completing the exposition of this method for all 16‐run 2‐level designs that are viable alternatives to standard Resolution IV fractional factorial designs. We compare AIMS to three other standard analysis methods for nonregular designs, stepwise regression, the lasso, and the Dantzig selector. AIMS consistently outperforms these methods in identifying the set of active factors.
Reliability test for degradation data based on ranked set sampling
Authors: Zhang Wenhan , Zhu Xiaojun , He Mu , Narayanaswamy Balakrishnan 
Published: September 2024

AbstractIn this article, we consider test for the two null hypotheses for and , two widely useful tests in reliability, based on ranked set sampling (RSS). We derive the likelihood ratio test as well as the associated exact and asymptotic results. Considering a fixed significance level and power of the test, we show that the proposed test statistic outperforms the existing test. In small sample cases, the proposed test leads to a much narrower confidence interval for the reliability function . Then, the test statistics obtained from simple random sampling and RSS schemes are compared through which, the efficiency of using RSS is demonstrated. For illustration, we apply the proposed test to a degradation data from the reliability literature. Upon using RSS, the cost of measurement gets reduced and efficiency gets improved, suggesting the importance and use of RSS data in reliability experiments and their design.
“It's Like They Are Using Our Data Against Us.” Counter‐Cartographies of AI Literacy
Authors: Aleman Ezequiel , Martinez Ricardo 
Published: September 2024

AbstractThis study explores how youth engage with literacy practices in the age of AI through the use of counter‐cartographies within the Nayah‐Irú curriculum. By critically examining digital platforms and the underlying algorithms, students embarked on a journey to understand and challenge the pervasive influence of artificial intelligence in their lives. The curriculum encouraged students to create alternative narratives (counter‐maps) that represent their unique experiences and perspectives, challenging the dominant discourses around technology and power. This process of counter‐mapping served as a powerful tool for fostering critical literacy and agency among the youth, enabling them to envision and advocate for transformative changes in their relationship with digital technologies. Educators played a key role in guiding these explorations, emphasizing the importance of a community‐centered approach to literacy that incorporates real‐world scenarios and addresses the socio‐cultural dynamics of AI. Through counter‐cartographies of AI literacy, students not only critiqued existing digital structures but also imagined new possibilities for engagement and resistance, highlighting the potential for youth to actively shape the discourse and practice of literacy practices in digital platforms.
Wide Range Near‐Zero Thermal Quenching of Orange–Yellow Phosphor via Impeding Self‐Oxidation of Eu2+ for Versatile Optoelectronic Applications
Authors: Ding Yang , Lu Xinyue , Maitra Soumyajit , Wang Yan , Mao Qinan , Liu Meijiao , Han Ning , Zhong Jiasong 
Published: September 2024

AbstractLi2SrSiO4:Eu2+ is a promising substitute for traditional Y3Al5O12:Ce3+ (YAG:Ce3+) owing to its strong orange–yellow emission of 4f‐5d transition originating from Eu2+ dopant, covering the more red‐light region. However, its inevitable luminescence thermal quenching at high temperatures and the self‐oxidation of Eu2+ strongly impede their applications. Their remediation remains highly challenging. Herein, an anti‐self‐oxidation(ASO) concept of Eu2+ in Li2SrSiO4 substrate by adding trivalent rare‐earth ions (A3+: A = La, Gd, Y, Lu) for highly efficient and stable orange–yellow light emission have been proposed. A significantly increased orange–yellow emission (202% improvement) from Li2Sr0.95A0.05SiO4:Eu2+ with a wide range near‐zero thermal quenching is obtained, superior to other Eu2+ activated phosphors. The presence of A3+ ions with various radii modifies the ASO degree of Eu2+ ions, achieving the tunable chemical state, composition, electronic configuration, crystal‐field strength, and luminescent characteristics of the developed phosphors. For the proof of the concept, a W‐LED device and a PDMS (Polydimethylsiloxane) luminescent film are fabricated, endowing excellent luminescence performance and thermal stability and the huge application prospects of Li2SrSiO4:Eu2+ in lighting and display fields.
Triadic Halobenzene Processing Additive Combined Advantages of Both Solvent and Solid Types for Efficient and Stable Organic Solar Cells
Authors: Park Jaeyeong , Jeong Seonghun , Sun Zhe , Mai Thi Le Huyen , Jeong Seokhwan , Yang Sangjin , Yang Changduk 
Published: September 2024

AbstractSolvent additives with a high boiling point (BP) and low vapor pressure (VP) have formed a key handle for improving the performance of organic solar cells (OSCs). However, it is not always clear whether they remain in the active‐layer film after deposition, which can negatively affect the reproducibility and stability of OSCs. In this study, an easily removable solvent additive (4‐chloro‐2‐fluoroiodobenzene (CFIB)) with a low BP and high VP is introduced, behaving like volatile solid additives that can be completely removed during the device fabrication process. In‐depth studies of CFIB addition into the D18‐Cl donor and N3 acceptor validate its dominant non‐covalent intermolecular interactions with N3 through effective electrostatic interactions. Such phenomena improve charge dynamics and kinetics by optimizing the morphology, leading to enhanced performance of D18‐Cl:N3‐based devices with a power conversion efficiency of 18.54%. The CFIB‐treated device exhibits exceptional thermal stability (T80 lifetime = 120 h) at 85 °C compared with the CFIB‐free device, because of its morphological robustness by evolving no residual CFIB in the film. The CFIB features a combination of advantages of solvent (easy application) and solid (high volatility) additives, demonstrating its great potential use in the commercial mass production of OSCs.
Delicate Regulation of Central Substituents Boosts Organic Photovoltaic Performance of Dimeric Acceptors
Authors: Jia Xinyuan , Li Yu , Cao Xiangjian , Bi Xingqi , Zhao Wenkai , Yao Zhaoyang , Long Guankui , Kan Bin , Guo Yaxiao , Li Chenxi , Wan Xiangjian , Chen Yongsheng 
Published: September 2024

AbstractDimeric acceptors are expected to satisfy both excellent power conversion efficiency (PCE) and operational stability of organic solar cells (OSCs). However, comparing to highly planar and symmetrical monomer‐like acceptors, the quite different steric/spatial configurations of dimeric acceptors affect device outcomes greatly. Herein, on basis of the same dimeric molecular platform that constructed by bridging central units of two monomer‐like acceptor, diverse substituents (─OCH3 for D1, ─CH3 for D2, and ─CF3 for D3) are grafted on central units to regulate the three dimensions (3D) geometries of dimeric acceptors delicately. A systematic investigation reveals the substituent‐dependent variation of energy level, absorption, and molecular packing behavior. Consequently, D2 acceptor, characteristic of more favorable configuration, affords a superior film morphology and charge transfer/transport dynamics in resulting OSCs, thus yielding an excellent PCE of 17.50% along with a good long‐term stability. This work manifests the crucially important role of central substituents in constructing high‐performance dimeric acceptors.
Space‐efficient data structures for the inference of subsumption and disjointness relations
Authors: Fuentes‐Sepúlveda José , Gatica Diego , Navarro Gonzalo , Rodríguez M. Andrea , Seco Diego 
Published: September 2024

AbstractConventional database systems function as static data repositories, storing vast amounts of facts and offering efficient query processing capabilities. The sheer volume of data these systems store has a direct impact on their scalability, both in terms of storage space and query processing time. Deductive database systems, on the other hand, require far less storage space since they derive new knowledge by applying inference rules. The challenge is how to efficiently obtain the required derivations, compared to having them in explicit form. In this study, we concentrate on a set of predefined inference rules for subsumption and disjointness relations, including their negations. We use compact data structures to store the facts and provide algorithms to support each type of relation, minimizing even further the storage space requirements. Our experimental findings demonstrate the feasibility of this approach, which not only saves space but is often faster than a baseline that uses well‐known graph traversal algorithms implemented on top of a traditional adjacency list representation to derive the relations.