bluuebunny/crossref_metadata_2025_split huggingface dataset:
New insights into the structural role of EMILINs within the human skin microenvironment
Authors: Schiavinato Alvise , Marcous Fady , Zuk Alexandra V. , Keene Douglas R. , Tufa Sara F. , Mosquera Laura M. , Zigrino Paola , Mauch Cornelia , Eckes Beate , Francois Katrien , De Backer Julie , Hunzelmann Nicolas , Moinzadeh Pia , Krieg Thomas , Callewaert Bert , Sengle Gerhard 
Published: December 2024

AbstractSupramolecular extracellular matrix (ECM) networks play an essential role in skin architecture and function. Elastin microfibril interface-located proteins (EMILINs) comprise a family of three extracellular glycoproteins that serve as essential structural components of the elastin/fibrillin microfibril network, and exert crucial functions in cellular signaling. Little is known about the structural nature of EMILIN networks in skin. We therefore investigated the spatiotemporal localization of EMILIN-1, -2, -3 in human skin induced by aging, UV-exposure, fibrosis, and connective tissue disorder. Confocal immunofluorescence and immunogold electron microscopy analysis identified all EMILINs as components of elastic fibers and elastin-free oxytalan fibers inserted into the basement membrane (BM). Further, our ultrastructural analysis demonstrates cellular contacts of dermally localized EMILIN-1 positive fibers across the BM with the surface of basal keratinocytes. Analysis of skin biopsies and fibroblast cultures from fibrillin-1 deficient Marfan patients revealed that EMILINs require intact fibrillin-1 as deposition scaffold. In patients with scleroderma and the bleomycin-induced murine fibrosis model EMILIN-2 was upregulated. EMILIN-3 localizes to the tips of candelabra-like oxytalan fibers, and to specialized BMs engulfing hair follicles and sebaceous glands. Our data identify EMILINs as important markers to monitor rearrangements of the dermal ECM architecture induced by aging and pathological conditions.
Discrepancies in lacustrine bacterial lipid temperature reconstructions explained by microbial ecology
Authors: Liang Jie , Chevalier Manuel , Liu Keshao , Perfumo Amedea , Wang Mingda , Xie Haichao , Hou Juzhi , Herzschuh Ulrike , Chen Fahu 
Published: December 2024

AbstractBacterial lipid branched glycerol dialkyl glycerol tetraethers (brGDGTs) are a valuable tool for reconstructing past temperatures. However, a gap remains regarding the influence of bacterial communities on brGDGT profiles. Here, we identified two distinct patterns of brGDGTs from the surface sediments of 38 Tibetan Plateau lakes using an unsupervised clustering technique. Further investigation revealed that salinity and pH significantly change bacterial community composition, affecting brGDGT profiles and causing brGDGT-based temperatures to be overestimated by up to 2.7 ± 0.7 °C in haloalkaline environments. We subsequently used the trained clustering model to examine the patterns of bacterial assemblages in the global lacustrine brGDGT dataset, confirming the global applicability of our approach. We finally applied our approach to Holocene brGDGT records from the Tibetan Plateau, showing that shifts in bacterial clusters amplified temperature variations over timescales. Our findings demonstrate that microbial ecology can robustly diagnose and constrain site-specific discrepancies in temperature reconstruction.
The doctor will polygraph you now
Authors: Anibal James , Gunkel Jasmine , Awan Shaheen , Huth Hannah , Nguyen Hang , Le Tram , Bélisle-Pipon Jean-Christophe , Boyer Micah , Hazen Lindsey ,   Bridge2AI Voice Consortium, Bensoussan Yael , Elemento Olivier , Rameau Anais , Sigaras Alexandros , Ghosh Satrajit , Powell Maria , Ravitsky Vardit , Bélisle-Pipon Jean-Christophe , Dorr David , Payne Phillip , Johnson Alistair , Bahr Ruth , Bolser Donald , Rudzicz Frank , Lerner-Ellis Jordan , Awan Shaheen , Watts Stephanie , Siu Jennifer , Hanna Karim , Zesiewicz Theresa , Zhao Robin , Jayachandran Lochana , Cruz Samantha Salvi , Bensoussan Yael , Clifton David , Wood Bradford 
Published: December 2024

AbstractArtificial intelligence (AI) methods have been proposed for the prediction of social behaviors that could be reasonably understood from patient-reported information. This raises novel ethical concerns about respect, privacy, and control over patient data. Ethical concerns surrounding clinical AI systems for social behavior verification can be divided into two main categories: (1) the potential for inaccuracies/biases within such systems, and (2) the impact on trust in patient-provider relationships with the introduction of automated AI systems for “fact-checking”, particularly in cases where the data/models may contradict the patient. Additionally, this report simulated the misuse of a verification system using patient voice samples and identified a potential LLM bias against patient-reported information in favor of multi-dimensional data and the outputs of other AI methods (i.e., “AI self-trust”). Finally, recommendations were presented for mitigating the risk that AI verification methods will cause harm to patients or undermine the purpose of the healthcare system.
Age and Sex Differences in Infants' Neural Sensitivity to Emotional Prosodies in Spoken Words: A Multifeature Oddball Study
Authors: Kao Chieh , Zhang Yang 
Published: December 2024

Purpose:
This study aimed to investigate infants' neural responses to changes in emotional prosody in spoken words. The focus was on understanding developmental changes and potential sex differences, aspects that were not consistently observed in previous behavioral studies.

Method:
A modified multifeature oddball paradigm was used with emotional deviants (angry, happy, and sad) presented against neutral prosody (standard) within varying spoken words during a single electroencephalography recording session. The reported data included 34 infants (18 males, 16 females; age range: 3–12 months, average age: 7 months 26 days).

Results:
Infants exhibited distinct patterns of mismatch responses (MMRs) to different emotional prosodies in both early (100–200 ms) and late (300–500 ms) time windows following the speech onset. While both happy and angry prosodies elicited more negative early MMRs than the sad prosody across all infants, older infants showed more negative early MMRs than their younger counterparts. The distinction between early MMRs to angry and sad prosodies was more pronounced in younger infants. In the late time window, angry prosody elicited a more negative late MMR than the sad prosody, with younger infants showing more distinct late MMRs to sad and angry prosodies compared to older infants. Additionally, a sex effect was observed as male infants displayed more negative early MMRs compared to females.

Conclusions:
These findings demonstrate the feasibility of the modified multifeature oddball protocol in studying neural sensitivities to emotional speech in infancy. The observed age and sex effects on infants' auditory neural responses to vocal emotions underscore the need for further research to distinguish between acoustic and emotional processing and to understand their roles in early socioemotional and language development.

Supplemental Material:

https://doi.org/10.23641/asha.27914553
DPANet: Position‐aware feature encoding and decoding for accurate large‐scale point cloud semantic segmentation
Authors: Zhao Haoying , Zhou Aimin 
Published: December 2024

AbstractDue to the scattered, unordered, and unstructured nature of point clouds, it is challenging to extract local features. Existing methods tend to design redundant and less‐discriminative spatial feature extraction methods in the encoder, while neglecting the utilisation of uneven distribution in the decoder. In this paper, the authors fully exploit the characteristics of the imbalanced distribution in point clouds and design our Position‐aware Encoder (PAE) module and Position‐aware Decoder (PAD) module. In the PAE module, the authors extract position relationships utilising both Cartesian coordinate system and polar coordinate system to enhance the distinction of features. In the PAD module, the authors recognise the inherent positional disparities between each point and its corresponding upsampled point, utilising these distinctions to enrich features and mitigate information loss. The authors conduct extensive experiments and compare the proposed DPANet with existing methods on two benchmarks S3DIS and Semantic3D. The experimental results demonstrate that the method outperforms the state‐of‐the‐art approaches.
Intelligent islanding detection in smart microgrids using variance autocorrelation function‐based modal current envelope
Authors: Naseem Shanzah , Ahmad Sadiq , Aziz Saddam , Ali Muhammad , Hasan Kazi N. , Ahmad Ayaz , Shoukat Abdullah 
Published: December 2024

AbstractIslanding detection is a critical issue in grid‐connected distributed microgrid systems. Distributed generation in the current power system has caused many challenges. Consequently, detecting quick and effective islanding is the most critical issue to minimise equipment failure, avoid danger, and maintain grid safety. There are various techniques for islanding identification in microgrids. Three classifications have been applied to categorise these strategies, which are: active, passive, and hybrid. This paper proposes and demonstrates an efficient and accurate approach to islanding detection based on the Variance Autocorrelation Function of a Modal Current Envelope (VAMCE) technique. Demodulation techniques including synchronous real demodulation, square law demodulation, asynchronous complex square law demodulation, and the quadrature demodulation technique are employed to detect the envelope of the 3‐phase current signal. The VAMCE methodology is better suited for islanding detection because of its response to current sensitivity under islanding scenarios but not under normal conditions. Several simulations under various settings, including normal and islanded scenarios are used to analyse this method. These simulations have demonstrated different situations, such as when the system works normally and when it does not. The VAMCE along with the quadrature demodulation technique outperforms the others. The proposed solution is not only more accurate but also much faster compared to other methods. The proposed approach can identify normal and islanded situations in just 0.4 s.
Partial suppression of chaos in relativistic three-body problems
Authors: Di Cintio Pierfrancesco , Trani Alessandro Alberto 
Published: December 2024

Context. Recent numerical results seem to suggest that, in certain regimes of typical particle velocities, when the post-Newtonian (PN) force terms are included, the gravitational N-body problem (for 3 ≤ N ≲ 103) is intrinsically less chaotic than its classical counterpart, which exhibits a slightly larger maximal Lyapunov exponent Λmax.
Aims. In this work, we explore the dynamics of wildly chaotic, regular and nearly regular configurations of the three-body problem with and without the PN corrective terms, with the aim being to shed light on the behaviour of the Lyapunov spectra under the effect of the PN corrections.
Methods. Because the interaction of the tangent-space dynamics in gravitating systems – which is needed to evaluate the Lyapunov exponents – becomes rapidly computationally heavy due to the complexity of the higher-order force derivatives involving multiple powers of v/c, we introduce a technique to compute a proxy of the Lyapunov spectrum based on the time-dependent diagonalization of the inertia tensor of a cluster of trajectories in phase-space. In addition, we also compare the dynamical entropy of the classical and relativistic cases.
Results. We find that, for a broad range of orbital configurations, the relativistic three-body problem has a smaller Λmax than its classical counterpart starting with the exact same initial conditions. However, the other (positive) Lyapunov exponents can be either lower or larger than the corresponding classical ones, thus suggesting that the relativistic precession effectively reduces chaos only along one (or a few) directions in phase-space. As a general trend, the dynamical entropy of the relativistic simulations as a function of the rescaled speed of light falls below the classical value over a broad range of values.
Conclusions. We observe that analyses based solely on Λmax could lead to misleading conclusions regarding the chaoticity of systems with small (and possibly large) N.
Cross-border political ties: foreign firms’ campaign contributions and the crowding out of domestic competitors
Authors: Ayyagari Meghana , Knill April , Syvrud Kelsey 
Published: December 2024

AbstractA substantial body of literature has shown that political connections have benefited firms domestically, but their cross-border value for multinational enterprises (MNEs) remains understudied. This paper provides novel evidence on the strategic advantages MNEs gain through political ties in host countries and the consequences for domestic firms. Examining foreign companies’ contributions to US political campaigns through political action committees (PACs) sponsored by their US subsidiaries, we find that contributing foreign firms win significantly more U.S. government contracts than non-contributing foreign firms. Crucially, this increased access for foreign contributing firms crowds out government contract allocation to similar domestic firms that do not make political donations, even in regulated industries favoring domestic suppliers. Our findings demonstrate that MNEs can effectively leverage political connections as a non-market strategy to gain preferential treatment over local competitors in a host nation. However, these cross-border political ties come at the expense of domestic firms’ competitiveness, informing policy debates around restricting foreign corporate influence in domestic elections. From a managerial perspective, our findings suggest that strategic political ties are an important consideration for MNEs alongside traditional location factors when evaluating foreign investment decisions and navigating institutional complexities abroad.
Portable tunable interband cascade laser spectrometer using thin-film waveguides for food contaminant analysis
Authors: Femenias A. , Erdem M. , Fomina P. , Scheuermann J. , Blazhko U. , Freitag S. , Bosman A. J. , Weih R. , Koeth J. , Kohler A. , Krska R. , Salentijn G. I. J. , Ruggeri F. S. , Mizaikoff B. 
Published: December 2024

Interband cascade lasers (ICL) are high output power mid-infrared light sources with low power consumption, serving as a viable alternative to more commonly applied quantum cascade lasers. The integration of ICLs with thin-film waveguides facilitates miniaturized sensing platforms based on the principles of evanescent field absorption toward tailorable high-fidelity portable mid-infrared (MIR) sensing solutions for on-site chemical analysis. The analytical performance of a MIR sensing system is presented combining a tunable interband cascade laser emitting at a wavelength range of 5.88–6.09 µm (1702–1641 cm−1) with a 6 µm GaAs/AlGaAs thin-film waveguide as the active transducer for customized evanescent field absorption analysis of food contaminants. A comparison of the analytical performance of the developed tICL-based system vs conventional Fourier-transform infrared spectroscopy is presented for the exemplary analysis of the Fusarium mycotoxin deoxynivalenol, a persistent food contaminant resulting from fungal infection. The thin-film waveguide enhances the sensitivity compared to conventional attenuated total reflection systems, revealing improved detection limits. The compact design of the system, along with the favorable analytical figures-of-merit and automated data processing, confirm the potential of the developed tICL-based spectrometer for on-site detection of food contaminants at various stages along the food supply chain.
Depression and anxiety at 1- and 12-months post ischemic stroke: methods for examining individual change over time
Authors: Barker-Collo Suzanne , Krishnamurthi Rita , Nair Balakrishnan , Ranta Anna , Douwes Jeroen , Feigin Valery 
Published: December 2024

Background Depression is commonly studied post stroke, while anxiety is less studied. This study presents prevalence of depression and anxiety at 1- and 12-months post ischemic stroke alongside three methods for examining within-subjects change over time. Methods Participants were ischemic stroke patients of the Auckland Regional Community Stroke Study (ARCOS-V) with Hospital Anxiety and Depression Scale data at 1- (n = 343) and 12-months (n = 307). Change over time was examined using within-subjects repeated measures ANOVA, calculation of the Reliable Change Index, and a Sankey diagram of those meeting cut-off scores (>7) for caseness over time. Results Using repeated measures ANOVA, depression scores didn’t change significantly over time, while anxiety symptoms decreased significantly. When reliable change was calculated, 4.2% of individuals had reliable decreases in anxiety symptoms, while 5.7% had reliable decreases in depression symptoms. Those who had a reliable decrease in one tended to have a reliable decrease in the other. In the Sankey, the proportion of those meeting the cut-off score for anxiety did not change over time (12.8 and 12.7% at 1- and 12-months), while those meeting the cut-off for depression increased slightly (3.7–4.5%) and those meeting cut-offs for both decreased from 10.4 to 8.1%. Conclusion The three methods produced very different findings. Use of cut-off scores is common but has limitations. Calculation of clinically reliable change is recommended. Further work is needed to ensure depression and anxiety are monitored over time post-stroke, and both should be the subject of intervention efforts in both acute and late stages post-stroke.
The 2024 phononic crystals roadmap
Authors: Jin Yabin , Torrent Daniel , Rouhani Bahram Djafari , He Liangshu , Xiang Yanxun , Xuan Fu-Zhen , Gu Zhongming , Xue Haoran , Zhu Jie , Wu Qian , Huang Guoliang , García Pedro David , Arregui Guillermo , Chen Yi , Guenneau Sébastien , Wegener Martin , Kadic Muamer , Liu Yongquan , Li Jensen , Wang Yue-Sheng , Palermo Antonio , Romero-García V , Kuznetsova S , Cheron É , Lázaro Navarro M , Groby J-P , Pagneux V , Félix S , Garcia-Raffi L M , Hu Gengkai , Cai Runcheng , Rabczuk Timon , Zhuang Xiaoying , Gao Penglin , Qu Yegao , Hussein Mahmoud I , Nomura Masahiro , Pennec Yan , Cai Feiyan , Li Xinwei , Zhai Wei 
Published: December 2024

Abstract
Over the past 3 decades, phononic crystals experienced revolutionary development for understanding and utilizing mechanical waves by exploring interaction between mechanical waves and structures. With the significant advances in manufacture technologies from nanoscale to macroscale, phononic crystals attract researchers from diverse disciplines to study abundant directions such as bandgaps, dispersion engineering, novel modes, reconfigurable control, efficient design algorithms and so on. The aim of this roadmap is to present the current state of the art, an overview of properties, functions and applications of phononic crystals, opinions on the challenges and opportunities. The various perspectives cover wide topics on basic property, homogenization, machine learning assisted design, topological, non-Hermitian, nonreciprocal, nanoscale, chiral, nonlocal, active, spatiotemporal, hyperuniform properties of phononic crystals, and applications in underwater acoustics, seismic wave protection, vibration and noise control, thermal transport, sensing, acoustic tweezers, written by over 40 renown experts. It is also intended to guide researchers, funding agencies and industry in identifying new prospects for phononic crystals in the upcoming years.
Denoising graph attention wavelet network: an interpretable multi-sensor information fusion diagnostic method for rotating systems
Authors: Gao Lei , Liu Zhihao , Jia Sixiang , Gao Qinhe , Lei Haixia , Wang Dong 
Published: December 2024

Abstract
The strong noise and black-box nature of deep networks pose great challenges to the efficiency of utilizing multi-sensor data for fault diagnosis. To solve these issues, a denoising graph attention wavelet network (DGAWN) is proposed for multi-sensor information fusion fault diagnosis of rotating machinery. Considering the spatial relationship of multi-sensor measurement points, k-neighborhood graphs are first constructed to characterize the intrinsic association and topology of each sensor data. The graph attention mechanism is introduced into the DGAWN to enhance the feature mapping relationship of multi-sensor graph nodes. Importantly, a denoising graph wavelet convolution layer is developed by utilizing a graph wavelet operator followed by an adaptive thresholding denoising module, thus obtaining interpretable graph wavelet filter responses and enhancing noise immunity. With the synergy of the attention mechanism, the DGAWN model matches the interpretable features with fault attributes under noise environments by utilizing the locality and sparsity of the graph wavelet kernel. Finally, two challenging rotating machinery fault datasets are used to validate the proposed DGAWN method under noise environments. Compared with several state-of-the-art models, experimental results indicate that DGAWN achieves the highest average diagnostic accuracies of 99.9% and 100% and superior noise resistance.
Sensitivity calibration method of FBG strain sensor in high and low temperature conditions
Authors: Du Cuicui , Kong Deren 
Published: December 2024

Abstract
Strain and temperature sensitivity coefficients of fiber Bragg grating (FBG) sensors are of vital importance to measuring accuracy, especially in varying temperature conditions. To improve the measurement accuracy of the FBG strain sensor, its strain and temperature sensitivity coefficients must be calibrated before use. In this study, we designed a substrate FBG strain sensor using the metal packaging method and illustrated its packaging process. A sensitivity calibration method for FBG strain sensors under different high-low temperatures was proposed. Additionally, an equal-intensity cantilever beam with the same material as the application structures of the FBG strain sensor, which affords loads within the range of −2500 to 3000 μϵ was designed and manufactured. A modified coefficient of strain

δ

was introduced to modify the strain results according to the calibration principle of an equal-intensity cantilever beam. Furthermore, a FBG unstressed temperature compensation method was proposed to compensate for the temperature of the FBG strain sensor. To verify the performance of the proposed sensitivity calibration method, a series of calibration experiments under −55 °C, −20 °C, 0 °C, 20 °C, 50 °C, and 70 °C were implemented, which proved the excellent performance of the proposed calibration method. Finally, the temperature and strain sensitivity coefficients of the FBG strain sensor in the temperature range of −55 °C to 70 °C are achieved at 0.3022 nm °C−1 and 0.5039 pm μϵ
−1. The proposed sensitivity calibration method in high-low temperatures is simple and easy to implement. Meanwhile, the calibrated FBG strain sensor has prospective applications for strain measurement in structural health monitoring of aircraft, especially under varying temperature conditions.