bluuebunny/crossref_metadata_2025 huggingface dataset:
Construction of an oxygen vacancy-enriched triple perovskite oxide electrocatalyst for efficient and stable oxygen evolution in acidic media
Authors: Wu Yuanyuan , Xia Tixuan , Yang Lu , Guo Feifan , Jiang Wei , Lang Jihui , Ma Yunchao , Feng Jingdong , Che Guangbo , Liu Chunbo
Published: August 2024

A triple Sr2CaRu2IrO9 perovskite oxide with excellent performance as an acidic OER electrocatalyst has been successfully synthesized. It effectively controls excessive lattice oxygen participation in the OER through the LOM.
Pyruvic acid or DBU/O2 guided organophotoredox-catalyzed direct C–H alkylation/α-aminoalkylation of 1,2,4-triazine-3,5(2H,4H)-diones with amines
Authors: Cai Zhao-Nan , Cao Xiaohui , Zhang Hong-Yu , Zhang Yuecheng , Zhao Jiquan
Published: August 2024

Herein, we present an organophotoredox-catalyzed direct C–H alkylation/α-aminoalkylation of 1,2,4-triazine-3,5(2H,4H)-diones with amines in the presence of different additives. In addition, reaction mechanism were further revealed via DFT studies.
Preparation of Zn3Nb2O8 anode material for high-performance lithium/sodium-ion batteries
Authors: Yin Xuemin , Cheng Shuling , Zhang Yuyang , Liu Chencheng
Published: August 2024

A novel Zn3Nb2O8 with stump-like structure was prepared for the first time as anode materials for lithium/sodium-ion batteries. The Zn3Nb2O8-B anode materials present excellent long-life performance.
Visible light induced cooperative carbonylation and (hetero)aryl migration: synthesis of multi-carbonyl compounds
Authors: Yang Hefei , Wang Yuanrui , Wang Le-Cheng , Wu Xiao-Feng
Published: August 2024

A new carbonylative strategy for the synthesis of 1,4-diketones has been developed.
Oxidative esterification of ethylene glycol in methanol to methyl glycolate over Au/ZnO catalysts: effect of preparation methods
Authors: Ren Xueyang , Zheng Jie , Zhao Jinxian , Quan Yanhong , Ren Jun
Published: August 2024

The one-step oxidative esterification of ethylene glycol (EG) is an effective and promising route for methyl glycolate (MG) synthesis, during which the development of efficient catalysts is critically crucial.
A review of recent progress on enhancing the stability of CsPbX3 perovskite solar cells
Authors: Wang Junxiao , Wang Guangwei , Chen Bing
Published: August 2024

A review on improving illumination, heat, and moisture stability of perovskite solar cells.
The effect of interface heterogeneity on zinc metal anode cyclability
Authors: Simon J. T. , Šedajová V. , Tripathy D. , Smith H. E. , Clarke S. M. , Grey C. P. , Menkin S.
Published: August 2024

The surface of a zinc metal anode was mapped using SECM. Slow Zn2+ transport can be caused by an insulating SEI (ZHS or ZnO) or horizontally plated zinc. Fast Zn2+ transport can be caused by a protruding morphology or a more conducting SEI.
Customized A–D–A type molecule to construct a nitric oxide nanogenerator with enhanced antibacterial activity for infected wound healing
Authors: Wang Yunxia , Wang Xiaohuan , Zhang Chuangxin , Li Ruipeng , Li Jing , Shi Hu , Zhang Caihong , Feng Liheng
Published: August 2024

A tailored “A–D–A”-structured dual-function molecule is synthesized to construct a biofriendly and light-controlled NO nanogenerator for bacterial killing and wound healing.
Injectable and NIR-responsive CDN–POM hydrogels for combined non-inflammatory photo-immunotherapy
Authors: Jiang Hailong , Liu Die , Wang Jianing , Li Jingchao , Pang Xinrui , Shan Hong , Zhang Ke
Published: August 2024

Combinatorial non-inflammatory photothermal therapy and immunotherapy against breast tumor induced by CDN–POM hydrogels.
Purpose-built multicomponent supramolecular silver(i)-hydrogels as membrane-targeting broad-spectrum antibacterial agents against multidrug-resistant pathogens
Authors: Saha Ekata , Khan Afruja , Mallick Amirul Islam , Mitra Joyee
Published: August 2024

Design of supramolecular Ag(i)-hydrogels and their application as membrane-targeting materials to counter complicated multi-drug resistant infections.
Hybridized local and charge-transfer excited states of blue OLEDs based on phenanthroimidazole derivates with a narrow FWHM of 24 nm
Authors: Song Xiao , Zhu Shengbo , Liu Yongliang , Shi Tongyue , Yang Lei , He Yuan , Niu Xiaoling , Yang Zhongchen , Yuan Jinhu , Feng Zhen
Published: August 2024

Narrow FWHM achieved through fine tuning of excited state properties in HLCT materials.
Exploring the interplay of the water–methanol solvent admixture on the optoelectronic properties of spray pyrolyzed fluorine-doped tin oxide thin films and their potential use in solar cell fabrication
Authors: Zahra Musarrat , Saifullah Muhammad , Majeed Aleena , Hassan Samna , Shehzad Khurram , Anjum Mohsin Ali Raza , Mehboob Sheeraz , Rehan Muhammad , Gul Maria , Ambreen Jaweria
Published: August 2024

A FTO thin film, M90, prepared using 90 vol% CH3OH, exhibits the highest FOM, indicating its potential use in photovoltaics and other applications.
Power quality disturbance signal classification in microgrid based on kernel extreme learning machine
Authors: Jing Guoxiu , Wang Dengke , Xiao Qi , Shen Qianxiang , Huang Bonan
Published: August 2024

This paper presents a kernel extreme learning machine (KELM) integrated with the improved whale optimization algorithm (IWOA) to address the power quality disturbance (PQD) issue in microgrids. First, an adaptive variational mode decomposition method is employed to extract PQD signals in microgrids. Then, the IWOA is utilized to optimize the penalty factor and kernel function parameters for the KELM classifier model, thereby enhancing the performance of the classifier. Furthermore, the test results indicate that the proposed IWOA–KELM achieves high classification accuracy and rapid convergence for complex PQD signals.
Sparse decoupling imaging network for wideband two‐dimensional MIMO radar imaging using model‐assisted and attention mechanism
Authors: Ding Shanshan , Wen Zhijin , Liu Yang , Fan Nana
Published: August 2024

The problem of sparse decoupling radar imaging methods based on deep learning is researched. An improved model‐driven learning imaging network with a complex‐valued convolution block attention module plugged into each sub‐network is proposed. This method can solve the high sidelobe and coupling problem in sparse wideband Multiple‐Input Multiple‐Output (MIMO) radar. In addition, it can better focus on the target area and capture target information to boost model representation power. Experimental results verify the validity of the proposed method.
Synthesis of sparse rectangular planar arrays with weight function and improved grey wolf optimization algorithm
Authors: Tao Kui , Wang Bin , Tian Xue , Tang Qi , Xie Guihan
Published: August 2024

The present article proposes a novel hybrid approach for addressing the synthesis problem of rectangular planar arrays under multiple constraints, through joint optimization of the weight function and the improved grey wolf optimization (IGWO) algorithm. Firstly, the grey wolf optimization (GWO) algorithm is improved by using tent chaotic mapping, nonlinear convergence factor, dominant wolf dynamic belief strategy, and opposition‐based learning strategy to increase the population diversity and the ability to jump out of the local optimum. Secondly, the array elements are weighted using the weight function to generate the position distribution matrix, which reduces the thinned matrix optimization time and improves the optimization efficiency. Finally, the position distribution matrix is used to generate the thinned array, and the IGWO algorithm is applied to perform the sparse optimization with multiple constraints. The effectiveness of the method is verified through numerical simulation and full‐wave simulation experiments, demonstrating its capability to enhance array antenna performance and reduce peak sidelobe level (PSLL). These experimental results hold significant engineering implications and provide valuable references for addressing the array distribution problem under multiple constraints.
IoT and machine learning models for multivariate very short‐term time series solar power forecasting
Authors: Kyi Su , Taparugssanagorn Attaphongse
Published: August 2024

In solar energy generation, the inherent variability caused by cloud cover and weather events often leads to sudden fluctuations in power outputs. Addressing this challenge, the authors’ study focuses on very short‐term solar irradiance (SI) prediction. Leveraging multivariate time series datasets, the authors improve very short‐term SI predictions. To achieve accurate very short‐term SI predictions, the authors employ machine learning techniques throughout the forecasting process. Additionally, the authors’ work pioneers the integration of the Internet of Things (IoT) into solar power systems, a novel approach in the field. The authors leverage LoRa (long range) technology for low‐cost, low‐power, and long‐range wireless control networks. The authors’ study focuses on SI forecasting using long short‐term memory and bi‐directional long short‐term memory (Bi‐LSTM) models, achieving high accuracy. The SI forecasts are evaluated in terms of root‐mean‐square error (RMSE) and mean absolute error in relation to meteorological data and sky image data. The improvement in performance can be attributed to the Bi‐LSTM's bidirectional nature, allowing it to incorporate future information during training, thereby enhancing its predictive capabilities. Overall, the results suggest that the Bi‐LSTM model is more suitable for accurately forecasting SI, particularly in scenarios requiring short‐term predictions based on rapidly changing environmental factors.
Morphology, complete mitochondrial genome, and molecular phylogeny of Rhabdias macrocephalum n. sp. (Nematoda: Rhabdiasidae) from Diploderma splendidum (Reptilia: Agamidae)
Authors: Zeng Jia-Lu , Chen Hui-Xia , Xu Hong-Ru , Li Liang
Published: August 2024

Species of the genus Rhabdias Stiles & Hassall, 1905 are common parasitic nematodes occurring in the lungs of amphibians and reptiles worldwide. In the present study, Rhabdias macrocephalum n. sp. is described using integrated morphological methods (light and scanning electron microscopy) and molecular approaches (sequencing of the nuclear 28S and ITS regions, and mitochondrial cox1, cox2, and 12S genes) based on specimens collected from the green striped tree dragon Diploderma splendidum (Barbour & Dunn) (Reptilia: Agamidae) in China. The complete mitochondrial genome of R. macrocephalum n. sp. was sequenced and annotated: it is 14,819 bp in length, including 12 protein coding genes (missing atp8), 22 tRNA genes, 2 rRNA genes and three non-coding regions. The gene arrangement of R. macrocephalum n. sp. is different from all of the currently available mitogenomes of nematodes and represents a novel type of mitochondrial gene arrangement reported in Nematoda. Molecular phylogenetic results based on the ITS + 28S data support the monophyly of Entomelas, Pneumonema, Serpentirhabdias, and Rhabdias, and showed R. macrocephalum n. sp. forming a most basal lineage in Rhabdias.
Impact of the discharge of treated water on residents’ intention to return to areas near the TEPCO Fukushima Daiichi Nuclear Power Station a decade after the accident
Authors: Zabirova Aizhan , Matsunaga Hitomi , Orita Makiko , Kashiwazaki Yuya , Xiao Xu , Schneider Thierry , Takamura Noboru
Published: August 2024

This study evaluated factors independently associated with residents’ intention to return (ITR) to the affected areas near the TEPCO Fukushima Daiichi Nuclear Power Station (FDNPS), discharged ALPS-treated water (DTW), social capital (SC), health-related quality of life (HR-QOL), and radiation risk perceptions which are located within 20 km of the FDNPS. The concerns about DTW were investigated six months before authorities began discharging treated water into the Pacific Ocean, in August 2023. A multinomial logistic regression analysis revealed that residents who wanted to return were mostly concerned about the DTW (odds ratio [OR] = 1.48, 95% confidence interval [95% CI] = 1.05–2.09, p < 0.05). Compared to the residents who had already returned, the social cohesion score was lower in non-returnees (want to return, OR = 0.21, 95% CI = 0.09–0.43, p < 0.01; undecided, OR = 0.21, 95% CI = 0.11–0.41, p < 0.01; do not want to return, OR = 0.28, 95% CI = 0.15–0.53, p < 0.01). Residents of areas affected by the FDNPS accident remain concerned about various issues regarding radiation. These results provide important suggestions for how to provide appropriate support that addresses the specific concerns of former residents of affected areas.
Pneumonie durch Mycoplasma hominis bei einem Reifgeborenen – Ein
Fallbericht mit Literaturübersicht
Authors: Müller-Graff Inga , Paul Pia , Forster Johannes , Wirbelauer Johannes
Published: August 2024

Mykoplasmen sind zellwandlose Bakterien, die unterschiedliche menschliche Gewebe
besiedeln können – allerdings auch Infektionen hervorrufen können. Die fehlende
Zellwand führt zum einen zu einer erschwerten Kultivierung und zum anderen zu
Besonderheiten in der Behandlung, da sie resistent gegenüber
Beta-Laktam-Antibiotika sind. Mycoplasma hominis und Ureaplasma urealyticum,
zusammengefasst als genitale Mykoplasmen, können den Genitaltrakt
kolonialisieren. Während eine Besiedlung bei einem gesunden Erwachsenen meist
asymptomatisch ist, können sie in der Schwangerschaft durch Übertragung auf den
Feten oder während der Geburt neonatale Infektionen hervorrufen und insbesondere
bei Frühgeborenen zu erhöhter Morbidität und Mortalität beitragen. Bei reifen
Neugeborenen ist bei hoher Kolonisationsrate die pathogene Rolle von Mykoplasmen
und ihre Behandlung jedoch umstritten. Im Folgenden präsentieren wir ein reifes
Neugeborenes mit einer durch M. hominis hervorgerufenen neonatalen Pneumonie,
welche erfolgreich mit Clindamycin behandelt wurde. Genitale Mykoplasmen können
in Einzelfällen symptomatische Infektionen bei Neugeborenen hervorrufen und
sollten insbesondere bei einem protrahierten, Beta-Laktam refraktärem Verlauf
als potentielle Erreger in Erwägung gezogen werden.
Development and Validation of a Mobile Phone Application for Measuring Knee Range of Motion
Authors: Gong Matthew F. , Finger Logan E. , Letter Christina , Amirian Soheyla , Parmanto Bambang , O'Malley Michael , Klatt Brian A. , Tafti Ahmad P. , Plate Johannes F.
Published: August 2024

Knee range of motion (ROM) is an important indicator of knee function. Outside the clinical setting, patients may not be able to accurately assess knee ROM, which may impair recovery following trauma or surgery. This study aims to validate a smartphone mobile application developed to measure knee ROM compared to visual and goniometer ROM measurements. A knee ROM Android mobile application was developed to measure knee ROM. Patients ≥ 18 years old presenting to an orthopaedic clinic with native knee complaints were approached to participate. Knee ROM was measured bilaterally by an arthroplasty-trained surgeon using (1) vision, (2) goniometer, and (3) the mobile application. Measurements were compared in flexion and extension using a one-way analysis of variance with post hoc Tukey test (alpha = 0.05). Eighty-four knee ROM measurements (40 left, 44 right) were obtained in 47 patients. Median Kellgren–Lawrence grade from available radiographs was grade 3. In flexion, mobile application (117.6 ± 14.7 degrees) measurements were not significantly different from visual (116.1 ± 13.6 degrees) or goniometer (116.2 ± 13.6 degrees) measurements. In extension, mobile application (4.8 ± 7.3 degrees) measurements were significantly different from visual (1.9 ± 4.1 degrees) measurements on post hoc analysis (p < 0.01), while no differences were present compared to goniometer (3.1 ± 5.8 degrees) measurements. Our study found that a mobile application for evaluating knee ROM was noninferior to goniometer-based measurements performed by an arthroplasty-trained surgeon. Future studies will investigate this application's utility in (1) remote patient care, (2) accelerating recovery during rehabilitation, (3) detecting early postoperative complications including arthrofibrosis, and (4) adding additional functionalities to the application to provide more detail-oriented descriptive analyses of patient knee function.
A De novo Mutation in the COL1A1 Gene Leading to Severe Osteogenesis Imperfecta: Case Report and Review of the Literature
Authors: Lu Yurong , Tian Yijia , Liu Jinxiu , Wang Yifan , Wang Xietong
Published: August 2024

Introduction Osteogenesis imperfecta (OI) is the most common monogenic inherited skeletal dysplasia disorder. Mutations in the COL1A1/COL1A2 gene cause ∼85 to 90% of OI. Studies of cases have demonstrated that missense mutations are the primary cause of OI, with poor prognosis.

Case Description We report the case of a fetus with skeletal abnormalities and subcutaneous edema. Ultrasound imaging revealed suspected skeletal malformations, including hypoplastic long bones of all four limbs, poorly ossified calvarium, unrevealing nasal bones, and generalized subcutaneous edema. Whole-exome sequencing revealed a heterozygous mutation in COL1A1 (c.2174G > T/p.(G725V), NM_000088.3). According to the American College of Medical Genetics and Genomics guidelines, it was determined to be a pathogenic variant and identified as a de novo variant (PS2 + PP3_strong + PM2_supporting), which has not been reported in the HGMD, gnomAD, ClinVar, or other databases. This variation causes a glycine-to-valine substitution at position 725, located within the Gly-Xaa-Yaa repeat in the helical domain of the collagen molecule.

Conclusion The COL1A1 mutation (c.2174G > T/p.(G725V), NM_000088.3) is a novel pathogenic variant of severe OI. Our study expanded the OI COL1A1 gene variation profiles in the Chinese population and provided a theoretical foundation for prenatal diagnosis, genetic counseling, and obstetric management.
Neonatal and Maternal Outcomes in Nulliparous Individuals according to Prepregnancy Body Mass Index
Authors: Kawakita Tetsuya , Atwani Rula , Saade George
Published: August 2024

Objective This study aimed to examine the effect of incremental changes in body mass index (BMI, kg/m2) on the association with adverse pregnancy outcomes.

Study Design This was a retrospective cohort study of U.S. vital statistics Live Birth and Infant Death linked data from 2011 to 2020. We limited analyses to nulliparas with singleton pregnancies who delivered at 20 weeks or greater. Outcomes were compared according to the prepregnancy BMI category using 5 kg/m2 increments, with each of the other BMI categories sequentially as the referent. The composite neonatal outcome was defined as any neonatal death, neonatal intensive care unit (ICU), surfactant use, ventilation use, or seizure. Severe maternal morbidity was defined as any maternal ICU, transfusion, uterine rupture, and hysterectomy. Adjusted relative risks were calculated for each BMI category as a referent group, using modified Poisson regression and adjusting for confounders.

Results A total of 11,174,890 nulliparous individuals were included. From 2011 to 2020, the proportions of individuals with BMI 40 or greater, BMI 50 or greater, and BMI 60 or greater increased significantly (from 3.1 to 4.9%, from 0.4 to 0.6%, from 0.03 to 0.06%, respectively; all trend p-values < 0.001). As BMI deviated from normal BMI, risks of neonatal and maternal adverse outcomes increased progressively. For example, as BMI deviated from normal BMI (18.5–24.9), the risk of composite neonatal outcome increased by 2% in individuals with BMI < 18.5 and up to 2.11-fold in individuals with BMI, 65–69.9. When compared with BMI 40 to 44.9, BMI 35 to 39.9 was associated with an 8% decreased risk of composite neonatal outcome, whereas BMI 45 to 49.9 was associated with an 8% increased risk of composite neonatal outcome.

Conclusion Incremental increases in prepregnancy BMI are linked to higher risks of adverse pregnancy outcomes, highlighting the need for effective weight management before conception.

Key Points
Wada Demonstrates Ipsilateral Language Function in Dyke-Davidoff-Masson Syndrome
Authors: Shah Rutul , Gopinath Siby , Gohel Abhishek , Narayanan Sreelakshmi , Pillai Ashok , Kannan Ramiah Rajesh , Almashaikhi Talal
Published: August 2024

Dyke-Davidoff-Masson syndrome (DDMS) is usually described secondary to prenatal or perinatal insult and is characterized by seizures, cerebral hemiatrophy, hemiparesis/facial asymmetry, and learning disability. We report an adolescent-onset case who presented with drug-refractory seizures and was considered for hemispherotomy on the dominant side. This is the first case report of DDMS where Wada helped in lateralizing the language to the ipsilateral dominant hemisphere despite the atrophy of the left inferior frontal gyrus. Thus, Wada is recommended in all patients without language regression who are considered for dominant hemispherotomy.
Painful Os Peroneum Syndrome Secondary to Hydroxyapatite Deposition Disease
Authors: Chapala Shashank , Papineni Vijay Ram Kumar , Shah Asad Rabbani , Ballal Moez , Iyengar Karthikeyan P. , Botchu Rajesh
Published: August 2024

Painful os peroneum syndrome (POPS) is one of the uncommon causes of lateral foot pain in orthopaedic practice. POPS encompasses a spectrum of pathologies such as an acute or a chronic fracture, peroneus longus tenosynovitis, and attrition or partial rupture of the peroneus longus tendon. Herein, we reported the first case of POPS secondary to hydroxyapatite deposition disease in a 32-year-old female patient. The clinical presentation, the role of radiological interventions, particularly ultrasound-guided barbotage in its diagnosis and effective management, is highlighted.
Ecological footprints, carbon emissions, and energy transitions: the impact of artificial intelligence (AI)
Authors: Wang Qiang , Li Yuanfan , Li Rongrong
Published: August 2024

This study examines the multifaceted impact of artificial intelligence (AI) on environmental sustainability, specifically targeting ecological footprints, carbon emissions, and energy transitions. Utilizing panel data from 67 countries, we employ System Generalized Method of Moments (SYS-GMM) and Dynamic Panel Threshold Models (DPTM) to analyze the complex interactions between AI development and key environmental metrics. The estimated coefficients of the benchmark model show that AI significantly reduces ecological footprints and carbon emissions while promoting energy transitions, with the most substantial impact observed in energy transitions, followed by ecological footprint reduction and carbon emissions reduction. Nonlinear analysis indicates several key insights: (i) a higher proportion of the industrial sector diminishes the inhibitory effect of AI on ecological footprints and carbon emissions but enhances its positive impact on energy transitions; (ii) increased trade openness significantly amplifies AI’s ability to reduce carbon emissions and promote energy transitions; (iii) the environmental benefits of AI are more pronounced at higher levels of AI development, enhancing its ability to reduce ecological footprints and carbon emissions and promote energy transitions; (iv) as the energy transition process deepens, AI’s effectiveness in reducing ecological footprints and carbon emissions increases, while its role in promoting further energy transitions decreases. This study enriches the existing literature by providing a nuanced understanding of AI’s environmental impact and offers a robust scientific foundation for global policymakers to develop sustainable AI management frameworks.
Blue perovskite LEDs improved with in situ fabrication technique
Authors: Johnson-Groh Mara
Published: August 2024

Researchers have created bright blue perovskite LEDs, finishing the trifecta of LED colors needed to enable commercial applications.
Tailoring anisotropic synthetic inflow turbulence generator for wind turbine wake simulations
Authors: Ali Naseem , Gatti Davide , Kornev Nikolai
Published: August 2024

In computational fluid dynamics, defining precise boundary conditions, especially at inlets, is of great importance. Inlet flows typically exhibit natural turbulence, which is managed in various ways in scale-resolving simulations. Methods to establish turbulent inlet conditions are commonly created using natural transition, uncorrelated oscillations, periodic boundary conditions from auxiliary simulations, or synthetic turbulent fields. In this study, we explore a technique aimed at generating a divergence-free synthetic inflow turbulence with arbitrary anisotropy. The methodology is based on the conventional portrayal of turbulence as consisting of several coherent structures. While our approach adeptly emulates predefined statistical characteristics across different scales, its primary focus is on generating input parameters that impact the airflow within the wake of individual wind turbines and the atmospheric boundary layer within a wind farm. The results are compared with high-resolution velocity experimental measurements, large eddy simulations, and the digital filter-based inlet boundary condition already available in OpenFOAM. The findings demonstrate that the applied inflow generator outperforms the default OpenFOAM filter, particularly in the context of a single wind turbine.
Thermal contribution to current-driven antiferromagnetic-order switching
Authors: Yoo Myoung-Woo , Lorenz Virginia O. , Hoffmann Axel , Cahill David G.
Published: August 2024

In information technology devices, current-driven state switching is crucial in various disciplines including spintronics, where the contribution of heating to the switching mechanism plays an inevitable role. Recently, current-driven antiferromagnetic order switching has attracted considerable attention due to its implications for next-generation spintronic devices. Although the switching mechanisms can be explained by spin dynamics induced by spin torques, some reports have claimed that demagnetization above the Néel temperature due to Joule heating is critical for switching. Here, we present a systematic method and an analytical model to quantify the thermal contribution due to Joule heating in micro-electronic devices, focusing on current-driven octupole switching in the non-collinear antiferromagnet, Mn3Sn. The results consistently show that the critical temperature for switching remains relatively constant above the Néel temperature, while the threshold current density depends on the choice of substrate and the base temperature. In addition, we provide an analytical model to calculate the Joule-heating temperature, which quantitatively explains our experimental results. From numerical calculations, we illustrate the reconfiguration of magnetic order during cooling from a demagnetized state of polycrystalline Mn3Sn. This work provides not only deeper insights into magnetization switching in antiferromagnets, but also a general guideline for evaluating the Joule-heating temperature excursions in micro-electronic devices.
The path to scientifically sound biodiversity valuation in the context of the Global Biodiversity Framework
Authors: Fenichel Eli P. , Dean Monica F. , Schmitz Oswald J.
Published: August 2024

Successful implementation of the Kunming-Montreal Global Biodiversity Framework requires identifying a process for measuring and valuing changes in biodiversity that build on the recognition that economics and valuation must play a key role in “halting and reversing” biodiversity loss. Here, we discuss considerations for a practical path to valuing changes in biodiversity. Framing changes in the value of biodiversity as a summary of changes in certain natural assets enables leveraging existing approaches and international standards associated with environmental-economic accounting. We discuss why an approach that builds from individual species, evolutionary groups, or functional groups into a practical, hierarchical statistical classification system is better than the development of any one biodiversity index. We merge techniques from ecology and other natural sciences, national and environmental-economic accounting, and economics, which are all on the cusp of making measurement of the change in the value of biodiversity possible. The focus should be on scaling and integrating these approaches. The path forward appears to begin with imperfect but useful measures, grounded in robust concepts, while establishing ambition to further scale-up measurements—just like the past evolution of many other official statistical series.
Lipidomic scanning of self-lipids identifies headless antigens for natural killer T cells
Authors: Cheng Tan-Yun , Praveena T. , Govindarajan Srinath , Almeida Catarina F. , Pellicci Daniel G. , Arkins Wellington C. , Van Rhijn Ildiko , Venken Koen , Elewaut Dirk , Godfrey Dale I. , Rossjohn Jamie , Moody D. Branch
Published: August 2024

To broadly measure the spectrum of cellular self-antigens for natural killer T cells (NKT), we developed a sensitive lipidomics system to analyze lipids trapped between CD1d and NKT T cell receptors (TCRs). We captured diverse antigen complexes formed in cells from natural endogenous lipids, with or without inducing endoplasmic reticulum (ER) stress. After separating protein complexes with no, low, or high CD1d–TCR interaction, we eluted lipids to establish the spectrum of self-lipids that facilitate this interaction. Although this unbiased approach identified fifteen molecules, they clustered into only two related groups: previously known phospholipid antigens and unexpected neutral lipid antigens. Mass spectrometry studies identified the neutral lipids as ceramides, deoxyceramides, and diacylglycerols, which can be considered headless lipids because they lack polar headgroups that usually form the TCR epitope. The crystal structure of the TCR–ceramide–CD1d complex showed how the missing headgroup allowed the TCR to predominantly contact CD1d, supporting a model of CD1d autoreactivity. Ceramide and related headless antigens mediated physiological TCR binding affinity, weak NKT cell responses, and tetramer binding to polyclonal human and mouse NKT cells. Ceramide and sphingomyelin are oppositely regulated components of the “sphingomyelin cycle” that are altered during apoptosis, transformation, and ER stress. Thus, the unique molecular link of ceramide to NKT cell response, along with the recent identification of sphingomyelin blockers of NKT cell activation, provide two mutually reinforcing links for NKT cell response to sterile cellular stress conditions.
mTORC1 phosphorylates and stabilizes LST2 to negatively regulate EGFR
Authors: Battaglioni Stefania , Craigie Louise-Marie , Filippini Sofia , Maier Timm , Hall Michael N.
Published: August 2024

TORC1 (target of rapamycin complex 1) is a highly conserved protein kinase that plays a central role in regulating cell growth. Given the role of mammalian TORC1 (mTORC1) in metabolism and disease, understanding mTORC1 downstream signaling and feedback loops is important. mTORC1 recognizes some of its substrates via a five amino acid binding sequence called the TOR signaling (TOS) motif. mTORC1 binding to a TOS motif facilitates phosphorylation of a distinct, distal site. Here, we show that LST2, also known as ZFYVE28, contains a TOS motif (amino acids 401 to 405) and is directly phosphorylated by mTORC1 at serine 670 (S670). mTORC1-mediated S670 phosphorylation promotes LST2 monoubiquitination on lysine 87 (K87). Monoubiquitinated LST2 is stable and displays a broad reticular distribution. When mTORC1 is inactive, unphosphorylated LST2 is degraded by the proteasome. The absence of LST2 enhances EGFR (epidermal growth factor receptor) signaling. We propose that mTORC1 negatively feeds back on its upstream receptor EGFR via LST2.
Improved time complexity for spintronic oscillator ising machines compared to a popular classical optimization algorithm for the Max-Cut problem
Authors: Garg Neha , Singhal Sanyam , Aggarwal Nakul , Sadashiva Aniket , Muduli Pranaba K , Bhowmik Debanjan
Published: August 2024

Solving certain combinatorial optimization problems like Max-Cut becomes challenging once the graph size and edge connectivity increase beyond a threshold, with brute-force algorithms which solve such problems exactly on conventional digital computers having the bottleneck of exponential time complexity. Hence currently, such problems are instead solved approximately using algorithms like Goemans–Williamson (GW) algorithm, run on conventional computers with polynomial time complexity. Phase binarized oscillators (PBOs), also often known as oscillator Ising machines, have been proposed as an alternative to solve such problems. In this paper, restricting ourselves to the combinatorial optimization problem Max-Cut solved on three kinds of graphs (Mobius Ladder, random cubic, Erdös Rényi) up to 100 nodes, we empirically show that computation time/time to solution (TTS) for PBOs (captured through Kuramoto model) grows at a much lower rate (logarithmically:

O

(

log

(
N
)

), with respect to graph size N) compared to GW algorithm, for which TTS increases as square of graph size (

O

(N
2)). However, Kuramoto model being a physics-agnostic mathematical model, this time complexity/ TTS trend for PBOs is a general trend and is device-physics agnostic. So for more specific results, we choose spintronic oscillators, known for their high operating frequency (in GHz), and model them through Slavin’s model which captures the physics of their coupled magnetization oscillation dynamics. We thereby empirically show that TTS of spintronic oscillators also grows logarithmically with graph size (

O

(

log

(
N
)

), while their accuracy is comparable to that of GW. So spintronic oscillators have improved time complexity over GW algorithm. For large graphs, they are expected to compute Max-Cut values much faster than GW algorithm, as well as other oscillators operating at lower frequencies, while maintaining the same level of accuracy.
Quantum entropy couples matter with geometry
Authors: Bianconi Ginestra
Published: August 2024

We propose a theory for coupling matter fields with discrete geometry on higher-order networks, i.e. cell complexes. The key idea of the approach is to associate to a higher-order network the quantum entropy of its metric. Specifically we propose an action having two contributions. The first contribution is proportional to the logarithm of the volume associated to the higher-order network by the metric. In the vacuum this contribution determines the entropy of the geometry. The second contribution is the quantum relative entropy between the metric of the higher-order network and the metric induced by the matter and gauge fields. The induced metric is defined in terms of the topological spinors and the discrete Dirac operators. The topological spinors, defined on nodes, edges and higher-dimensional cells, encode for the matter fields. The discrete Dirac operators act on topological spinors, and depend on the metric of the higher-order network as well as on the gauge fields via a discrete version of the minimal substitution. We derive the coupled dynamical equations for the metric, the matter and the gauge fields, providing an information theory principle to obtain the field theory equations in discrete curved space.
Spatial frequency decomposition with bandpass filters for multiscale analyses and functional correlations
Authors: Brown Christopher A , Blateyron François , Berglund Johan , Murrison Adam J , Jeswiet Jack Jacob
Published: August 2024

To address the essential problem in surface metrology of establishing functional correlations spatial, frequencies in topographic measurements are progressively decomposed into a large number of narrow bands. Bandpass filters and commercially available software are used. These bands can be analyzed with conventional surface texture parameters, like average roughness, Sa, or other parameters, for detailed, multiscale topographic characterizations. Earlier kinds of multiscale characterization, like relative area, required specialized software performing multiple triangular tiling exercises. Multiscale regression analyses can test strengths of functional correlations over a range of scales. Here, friction coefficients are regressed against standard surface texture parameters over the range of scales available in a measurement. Correlation strengths trend with the scales of the bandpass filters. Using bandpass frequency, i.e., wavelength or scale, decompositions, the R2 at 25 μm, exceeds 0.9 for Sa compared with an R2 of only 0.2 using the broader band of conventional roughness filtering. These improved, scale-specific functional correlations can facilitate scientific understandings and specifications of topographies in product and process design and in designs of quality assurance systems.
Designing serious games to advance climate change adaptation
Authors: Nabong Emily , Opdyke Aaron
Published: August 2024

The escalating impact of climate change necessitates innovative strategies to enhance public understanding and action. This research delves into the potential of serious games as transformative tools for climate change education and adaptation. Despite their rising popularity, serious games face challenges in effectively conveying complex climate science concepts and achieving desired learning outcomes. This study builds upon existing frameworks to propose tailored guidelines for designing serious games focused on climate change adaptation. We anchor our guidelines on the Design, Play, Experience (DPE) framework to scaffold strategies to create more effective serious games for climate change adaptation. We propose 11 elements that should be considered between player engagement and design when creating serious games. Through iterative playtesting and community involvement, we underscore the significance of reflecting on language, comprehension, timing, and social dynamics. This work bridges the gap between scientific knowledge and actionable insights in the development of serious games to equip decision-makers and communities with the tools to combat the multifaceted challenges posed by climate change.
Gearbox fault diagnosis based on RGT-MFFIN and multi-sensor fusion image generation
Authors: Xie Guangpeng , Zhan Hongfei , Yu Junhe , Wang Rui , Cheng Youkang
Published: August 2024

In gearbox fault diagnosis based on vibration and torque state data, traditional one-dimensional time-frequency domain analysis methods often suffer from insufficient feature expression and mining, and require complex noise reduction and filtering preprocessing. To address this issue, this paper proposes a fusion image generation method that integrates the advantages of recurrence plot (RP) and Gramian angular summation field (GASF) to generate recurrence Gramian transformed (RGT) images. This approach integrates both global and local fault information, making the fault characteristics more intuitive and easier to analyze. Given that multi-sensor collaboration can enhance feature representation, feature-level fusion increases the computational burden, and decision-level fusion is prone to losing inter-sensor correlation information, this paper adopts data-level fusion for image sample enhancement. In the diagnostic method, the challenge of traditional convolutional neural networks (CNNs) in extracting diverse geometric linear structures from fused images is addressed by introducing deformable convolutional blocks for initial feature extraction. Additionally, a multi-scale feature fusion interaction network (MFFIN) is constructed. This network incorporates a channel-space interactive attention mechanism on top of multi-scale feature extraction, assigning weights to features according to their importance while facilitating the interaction of feature information. Finally, validation is carried out using public datasets, and the experimental results show that the proposed method demonstrates significant advantages in classification accuracy and robustness under variable operating conditions and noise, thereby proving its effectiveness and practicality.
Women are under-represented in adaptation policy research and are more likely to emphasise justice topics
Authors: Danilenko Diana , Andrijevic Marina , Sietsma Anne J , Callaghan Max , Khanna Tarun
Published: August 2024

This paper is the first to analyse the role of women authors in fostering justice-relevant topics in climate adaptation research. As representation, citation and payment patterns remain gender-biased across scientific disciplines, we explore the case of climate science, particularly adaptation, as its most human-oriented facet. In climate research and policy, there has been a recent surge of interest in climate justice topics: mentions of justice have increased almost tenfold in Intergovernmental Panel on Climate Change Working Group 2 reports between the latest assessment cycles (AR5 and AR6). We conduct a systematic examination of the topic space in the adaptation policy scholarship. As it is a vast and rapidly growing field, we use topic modelling, an unsupervised machine learning method, to identify the literature on climate justice and related fields, as well as to examine the relationship between topic prevalence and the gender of the authors. We find climate change adaptation policy research to be male dominated, with women holding 38.8% of first and 28.8% of last authorships. However, we observe topic-specific variability, whereby the share of female authors is higher among publications on justice-relevant topics. Female authorship is highly linked to topics such as Community, Local Knowledge, and Governance, but less to Food Security and Climate Finance. Our findings corroborate the evidence that female authors play a significant role in advancing the research and dialogue on the relationship between climate change and areas that have meaningful impact on lives of women and other marginalised groups.
Recent progress in Stevens–Johnson syndrome/toxic epidermal necrolysis: diagnostic criteria, pathogenesis and treatment
Authors: Hama Natsumi , Aoki Shigeki , Chen Chun-Bing , Hasegawa Akito , Ogawa Youichi , Vocanson Marc , Asada Hideo , Chu Chia-Yu , Lan Cheng-Che E , Dodiuk-Gad Roni P , Fujiyama Toshiharu , Hsieh Tyng-Shiuan , Ito Kousei , Jerschow Elina , Mizukawa Yoshiko , Nakajima Saeko , Nakamura Kazutoshi , Nicolas Jean-François , Satoh Takashi K , Shiohara Tatsuo , Takahashi Hayato , Tohyama Mikiko , Ueda Takahiro , Ura Katsuaki , Watanabe Hideaki , Yamaguchi Yukie , Nordmann Thierry M , Chung Wen-Hung , Naisbitt Dean , Pincelli Carlo , Pichler Werner J , French Lars E , Phillips Elizabeth , Abe Riichiro
Published: August 2024

Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) represent a severe spectrum of rare mucocutaneous reactions that are primarily drug-induced and characterized by significant morbidity and mortality. These conditions manifest in extensive skin detachment, distinguishing them from other generalized skin eruptions. The rarity and severity of SJS/TEN underscore the importance of accurate diagnostic criteria and effective treatments, which are currently lacking consensus. This review proposes new diagnostic criteria to improve specificity and global applicability. Recent advances in understanding the immunopathogenesis of SJS/TEN are explored, emphasizing the role of drug-specific T-cell responses and human leucocyte antigen polymorphisms in disease onset. The review also addresses current therapeutic approaches, including controversies surrounding the use of immunosuppressive agents and the emerging role of tumour necrosis factor-α inhibitors. Novel therapeutic strategies targeting specific pathogenic mechanisms, such as necroptosis and specific immune cell pathways, are discussed. Furthermore, the development of new drugs based on these insights, including targeted monoclonal antibodies and inhibitors, are examined. The review concludes by advocating for more robust and coordinated efforts across multidisciplinary medical fields to develop effective treatments and diagnostic tools for SJS/TEN, with the aim of improving patient outcomes and understanding the disease and its mechanisms.
Testing the genomic overlap between intraspecific mating traits and interspecific mating barriers
Authors: Yusuf Leeban H , Pascoal Sonia , Moran Peter A , Bailey Nathan W
Published: August 2024

Differences in interspecific mating traits, such as male sexual signals and female preferences, often evolve quickly as initial barriers to gene flow between nascent lineages, and they may also strengthen such barriers during secondary contact via reinforcement. However, it is an open question whether loci contributing to intraspecific variation in sexual traits are co-opted during the formation and strengthening of mating barriers between species. To test this, we used a population genomics approach in natural populations of Australian cricket sister species that overlap in a contact zone: Teleogryllus oceanicus and Teleogryllus commodus. First, we identified loci associated with intraspecific variation in T. oceanicus mating signals: advertisement song and cuticular hydrocarbon (CHC) pheromones. We then separately identified candidate interspecific barrier loci between the species. Genes showing elevated allelic divergence between species were enriched for neurological functions, indicating potential behavioral rewiring. Only two CHC-associated genes overlapped with these interspecific candidate barrier loci, and intraspecific CHC loci showed signatures of being under strong selective constraints between species. In contrast, 10 intraspecific song-associated genes showed high genetic differentiation between T. commodus and T. oceanicus, and 2 had signals of high genomic divergence. The overall lack of shared loci in intra vs. interspecific comparisons of mating trait and candidate barrier loci is consistent with limited co-option of the genetic architecture of interspecific mating signals during the establishment and maintenance of reproductive isolation.
Epibiont communities on mussels in relation to parasitism and location in the rocky intertidal zone
Authors: Davis Katherine M , Parfrey Laura Wegener , Harley Christopher D G , Holmes Keith , Schaefer Olivia , Gehman Alyssa-Lois
Published: August 2024

The factors shaping host–parasite interactions and epibiont communities in the variable rocky intertidal zone are poorly understood. California mussels, Mytilus californianus, are colonized by endolithic cyanobacterial parasites that erode the host shell. These cyanobacteria become mutualistic under certain abiotic conditions because shell erosion can protect mussels from thermal stress. How parasitic shell erosion affects or is affected by epibiotic microbial communities on mussel shells and the context dependency of these interactions is unknown. We used transplant experiments to characterize assemblages of epibiotic bacteria and endolithic parasites on mussel shells across intertidal elevation gradients. We hypothesized that living mussels, and associated epibacterial communities, could limit colonization and erosion by endolithic cyanobacteria compared with empty mussel shells. We hypothesized that shell erosion would be associated with compositional shifts in the epibacterial community and tidal elevation. We found that living mussels experienced less shell erosion than empty shells, demonstrating potential biotic regulation of endolithic parasites. Increased shell erosion was not associated with a distinct epibacterial community and was decoupled from the relative abundance of putatively endolithic taxa. Our findings suggest that epibacterial community structure is not directly impacted by the dynamic symbiosis between endolithic cyanobacteria and mussels throughout the rocky intertidal zone.