bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification and prognostic biomarkers among ZDHHC4/12/18/24, and APT2 in lung adenocarcinoma
Authors: Bian Jing , Xiong Wenji , Yang Zhiguang , Li Minzhe , Song Demei , Zhang Yanli , Liu Chaoying 
Published: January 2024

AbstractS-palmitoylases and S-depalmitoylases are differentially expressed in various cancers and several malignant tumors and show a strong prognostic ability. Notwithstanding, the potential clinical impact of S-palmitoylases and S-depalmitoylases, particularly in the prognosis and progression of lung adenocarcinoma (LUAD), has not been clarified. Expression levels of S-palmitoylases and S-depalmitoylases in LUAD were investigated using TCGA. GEPIA was used to evaluate the mRNA levels of S-palmitoylases and S-depalmitoylases at different pathological stages. Metascape was used to investigate the biological significance of S-palmitoylases and S-depalmitoylases. The Kaplan–Meier plotter was used to analyze the prognostic value of S-palmitoylases and S-depalmitoylases. CBioportal was used to analyze gene alterations in S-palmitoylases and S-depalmitoylases. UALCAN was used to examine DNA promoter methylation levels of S-palmitoylases and S-depalmitoylases. Finally, we investigated the relationship between S-palmitoylases, S-depalmitoylases, and tumor-infiltrating immune cells using TIMER. Correlations with immune checkpoint-related genes were determined using the R packages reshape2, ggpubr, ggplot2, and corrplot. PCR was also performed to assess the degree of ZDHHC4/12/18/24 and APT2 transcript expression in lung adenocarcinoma and adjacent normal lung tissues. HPA was utilized to investigate protein levels of S-palmitoylases and S-depalmitoylases in LUAD and normal lung tissue. Our study found that ZDHHC2/3/4/5/6/7/9/12/13/16/18/20/21/23/24, APT1/2, PPT1, LYPLAL1, ABHD4/10/11/12/13 and ABHD17C mRNA expression was significantly upregulated in LUAD, whereas ZDHHC1/8/11/11B/14/15/17/19/22, ABHD6/16A and ABHD17A mRNA expression was significantly downregulated. The functions of the differentially expressed S-palmitoylases and S-depalmitoylases were mainly associated with protein-cysteine S-palmitoyltransferase and protein-cysteine S-acyltransferase activities. Patients with high expression of ZDHHC4/12/18/24, APT2, ABHD4, ABHD11 and ABHD12 had a shorter overall survival. Infiltration of six immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells) was closely associated with the expression of ZDHHC4/12/18/24 and APT2. ZDHHC4/12/18/24 and APT2 positively correlated with the immune checkpoint-related gene CD276. We assessed the mRNA levels of ZDHHC4/12/18/24 and APT2 using qRT-PCR and found increased expression of ZDHHC4/12/18/24 in LUAD compared with healty control lung tissues. ZDHHC4/12/18/24, and APT2 are potential prognostic biomarkers of LUAD. Their expression levels could be related to the tumor microenvironment in LUAD.
Differential temporal utility of passively sensed smartphone features for depression and anxiety symptom prediction: a longitudinal cohort study
Authors: Stamatis Caitlin A. , Meyerhoff Jonah , Meng Yixuan , Lin Zhi Chong Chris , Cho Young Min , Liu Tony , Karr Chris J. , Liu Tingting , Curtis Brenda L. , Ungar Lyle H. , Mohr David C. 
Published: January 2024

AbstractWhile studies show links between smartphone data and affective symptoms, we lack clarity on the temporal scale, specificity (e.g., to depression vs. anxiety), and person-specific (vs. group-level) nature of these associations. We conducted a large-scale (n = 1013) smartphone-based passive sensing study to identify within- and between-person digital markers of depression and anxiety symptoms over time. Participants (74.6% female; M age = 40.9) downloaded the LifeSense app, which facilitated continuous passive data collection (e.g., GPS, app and device use, communication) across 16 weeks. Hierarchical linear regression models tested the within- and between-person associations of 2-week windows of passively sensed data with depression (PHQ-8) or generalized anxiety (GAD-7). We used a shifting window to understand the time scale at which sensed features relate to mental health symptoms, predicting symptoms 2 weeks in the future (distal prediction), 1 week in the future (medial prediction), and 0 weeks in the future (proximal prediction). Spending more time at home relative to one’s average was an early signal of PHQ-8 severity (distal β = 0.219, p = 0.012) and continued to relate to PHQ-8 at medial (β = 0.198, p = 0.022) and proximal (β = 0.183, p = 0.045) windows. In contrast, circadian movement was proximally related to (β = −0.131, p = 0.035) but did not predict (distal β = 0.034, p = 0.577; medial β = −0.089, p = 0.138) PHQ-8. Distinct communication features (i.e., call/text or app-based messaging) related to PHQ-8 and GAD-7. Findings have implications for identifying novel treatment targets, personalizing digital mental health interventions, and enhancing traditional patient-provider interactions. Certain features (e.g., circadian movement) may represent correlates but not true prospective indicators of affective symptoms. Conversely, other features like home duration may be such early signals of intra-individual symptom change, indicating the potential utility of prophylactic intervention (e.g., behavioral activation) in response to person-specific increases in these signals.
A promise for neuronal repair: reprogramming astrocytes into neurons in vivo
Authors: Huang Lijuan , Lai Xinyu , Liang Xiaojun , Chen Jiafeng , Yang Yue , Xu Wei , Qin Qingchun , Qin Rongxing , Huang Xiaoying , Xie Minshan , Chen Li 
Published: January 2024

Abstract
Massive loss of neurons following brain injury or disease is the primary cause of central nervous system dysfunction. Recently, much research has been conducted on how to compensate for neuronal loss in damaged parts of the nervous system and thus restore functional connectivity among neurons. Direct somatic cell differentiation into neurons using pro-neural transcription factors, small molecules, or microRNAs, individually or in association, is the most promising form of neural cell replacement therapy available. This method provides a potential remedy for cell loss in a variety of neurodegenerative illnesses, and the development of reprogramming technology has made this method feasible. This article provides a comprehensive review of reprogramming, including the selection and methods of reprogramming starting cell populations as well as the signaling methods involved in this process. Additionally, we thoroughly examine how reprogramming astrocytes into neurons can be applied to treat stroke and other neurodegenerative diseases. Finally, we discuss the challenges of neuronal reprogramming and offer insights about the field.
Evaluation of lightning‐induced overvoltage on a 10 kV distribution line based on electromagnetic return‐stroke model using finite‐difference time‐domain
Authors: Duan Pan , Zhang Lianfang , Huang Xiaogang , Sun Jian , Qi Yue , Yang Qing 
Published: January 2024

AbstractAccurate simulation of lightning‐induced overvoltage for overhead distribution lines is helpful to prevent lightning trip accidents. An electromagnetic return‐stroke model was used to represent lightning and then a 3D finite‐difference time‐domain (FDTD) method was adopted to simulate the lightning‐induced overvoltage on a distribution line without a field‐line coupling model. How lightning‐induced overvoltage behave for different ground conductivity and varying distance between the distribution line and the lightning channel was analysed. The results showed that the overvoltage waveforms at the centre point of the line corresponding to lightning strikes on the lossy ground and an ideal ground (σ = ∞) were similar; however, the peak amplitudes of the waveform were affected by soil conductivity at a close distance. The relationship between magnitude of the overvoltage and distance can be described by a second‐order exponential decay equation. Finally, the overvoltage calculated using the proposed model was compared with those obtained based on Agrawal's model and measurements made using the newly developed intelligent insulator on site. From these comparisons, it could be concluded that the FDTD method with the electromagnetic return‐stroke model produces reasonably accurate results of the attenuated oscillation waveform, which can better reproduce the overvoltage on operational distribution lines.
An efficient power control strategy for active mitigation of blade in‐plane fatigue loading in PMSG‐based wind turbines
Authors: Safaeinejad Ali , Rahimi Mohsen , Zhou Dao , Blaabjerg Frede 
Published: January 2024

AbstractThis paper assesses the dynamic performance of permanent magnet synchronous generator‐based wind turbine (WT) regarding the blade in‐plane fatigue loads once the WT is controlled in power control mode. Blade in‐plane oscillations, associated with the poorly blade in‐plane modes, can be excited by turbulent winds or grid disturbances that may lead to damage of the blades and reduce the drive‐train reliability. To overcome this drawback, at first, a model with three degrees of freedom is extracted for the drive‐train system, and then, an active mitigation approach is proposed to mitigate the blade in‐plane oscillations. The proposed method can effectively suppress the blade in‐plane vibrations by adding a supplementary term into the power control loop that is proportional to the speed difference between the blade and generator. The speed difference between the blade and generator is obtained by estimation of the blade‐hub and hub‐generator shaft torsional torques. Next, the performance of the proposed active mitigation approach is examined by the modal and frequency response analyses and time‐domain simulations. Finally, it is shown that the proposed approach has superior performance over the conventional approaches based on the simplified drive‐train model and crossing the measured generator speed through a band‐pass filter.
Assessment of Microsurgery Simulation Course Access in Plastic Surgery Training Programs
Authors: Elver Ashlie A. , Egan Katie G. , Phillips Brett T. 
Published: January 2024

Abstract
Background Microsurgery requires complex skill development with a steep learning curve for plastic surgery trainees. Flap dissection courses and simulation exercises are useful to acquire these skills. This study aims to assess plastic surgery training programs' access to and interest in microsurgical courses.
Methods A survey was distributed to plastic surgery residency and microsurgery fellowship program directors (PDs). The survey collected program demographics and attendance of trainees at structured microsurgical skills or flap dissection courses. We assessed if PDs thought trainees would benefit from instructional courses.
Results There were 44 residency PD responses (44/105, 41.9%, 36 integrated, 8 independent), and 16 fellowship PD responses (16/42, 38.1%). For residency PDs, 54.5% (24/44) sent residents to flap courses, and 95% (19/20) of remaining PDs felt residents would benefit from attending. In addition, 59.1% of programs (26/44) sent residents to microsurgical skills courses, and 83.3% (15/18) of remaining PDs felt residents would benefit from attending. When examining fellowship PDs, 31.2% of programs (5/16) sent fellows to flap dissection courses and 10/11 of remaining PDs felt fellows would benefit from attending a course (90.1%). Half of programs (8/16) sent fellows to microsurgical skills courses, and 7/8 remaining PDs felt fellows would benefit from attending (87.5%).
Conclusion Only half of the plastic surgery trainees have access to microsurgical skills and flap dissection courses. The majority of residency and fellowship PDs feel that training courses are valuable. Expanding access to these courses could provide a significant benefit to microsurgical education in plastic surgery training.
DLTS analysis of interface and near-interface bulk defects induced by TCO-plasma deposition in carrier-selective contact solar cells
Authors: Hara Tomohiko , Ohshita Yoshio 
Published: January 2024

We investigate the electrical characteristics of defects at the SiO2/Si interface, within the adjacent Si crystal, and through the depth profile of the bulk defect using three-dimensional deep-level transient spectroscopy (3D-DLTS). These defects are introduced by the reactive plasma deposition technique employed for depositing transparent conductive oxides in the fabrication of carrier-selective contact-type solar cells. To control the surface potential near the Si surface, we apply a varying voltage to obtain DLTS signals as functions of both temperature and Fermi level at the SiO2/Si interface. Using machine learning for 3D-DLTS spectral analysis, we estimate the capture cross sections, energy levels, densities, and depth profiles of these process-induced defects. The experimental results indicate the existence of three types of electron traps within the bulk defects, ranging from the interface to a depth of ∼70 nm. The electrical properties of these bulk defects suggest the presence of oxygen-related defects within Si. On the other hand, regarding the properties of interface defects, the capture cross sections and the defect densities are estimated as a function of their energy levels. They suggest that the defects at the SiO2/Si interface are likely oxygen-related PL centers.
Bond dissociation energy of N2 measured by state-to-state resolved threshold fragment yield spectra
Authors: Wang Peng , Gong Shiyan , Li Yixuan , Mo Yuxiang 
Published: January 2024

The precise determination of the bond dissociation energy of N2 is crucial for thermochemistry database and theoretical calculations. However, there has been ongoing debate regarding its exact value. In this study, we used the velocity map imaging method combined with an extreme ultraviolet laser to measure the threshold fragment yield (TFY) spectra of N2 in the N(2D) + N(2D) photodissociation channels. By integrating the signals within a small circular area on the fragment velocity map images, we were able to obtain TFY spectra at nine different dissociation thresholds. These spectra are rotational state-resolved for the N2(J″) molecules and spin–orbit state-resolved for the dissociation channels involving N(2D) fragments. By employing the Wigner threshold law to simulate the TFY spectra and conducting statistical analysis on the comprehensive dataset, we determined the N2 bond dissociation energy to be 78 691.09 ± 0.15 cm−1. This work now places N2 among the few diatomic molecules with bond dissociation energies measured at sub-wavenumber precision.
UV-VUV absorption spectra of azido-based energetic plasticizer bis(1,3-diazido prop-2-yl)malonate in gas phase
Authors: Bhattacharya Atanu , Singh Param Jeet , Das Suman 
Published: January 2024

Ultraviolet and vacuum ultraviolet photo-absorption spectra of azido (–N3)-based energetic plasticizer, bis(1,3-diazido-prop-2-yl)-malonate (abbreviated as BDAzPM), in the gas phase is recorded at room temperature and in the photon energy range of 5.5–9.9 eV using a synchrotron radiation source. Complementary computational results obtained using the time-dependent density functional theory document the vertical transition energies and oscillator strengths. Comparison of the simulated spectra with the experimental absorption spectrum of BDAzPM reveals that the early part of the absorption spectrum of BDAzPM is of pure valence excitation character, whereas the later intense part of the absorption spectrum is dominated by mixed Rydberg and valence electronic excitations.
On the concept of “educational linguistics”
Authors: Halliday M. A. K. , Williams Geoff 
Published: January 2024

Abstract
This paper was first presented at a language in education conference and workshop held at Murdoch University, Western Australia in December 1989, convened by Michael O’Toole. The conference was one in a series held annually in universities around Australia during the previous decade. It was designed to promote dialogue between leading scholars and other participants, adopting as its theme “Discipline – Dialogue – Difference”. Halliday’s paper was the opening plenary, and it was responded to by Gunther Kress, whose paper follows in this issue.1
Precise in-situ fabrication of perovskite single crystal arrays via cosolvent based electrohydrodynamic printing
Authors: Yu Rui , Xie Wenshuo , Yang Weili , Yang Xinrui , Duan Yongqing 
Published: January 2024

Abstract
Single crystal (SC) perovskites exhibit superior stability and optoelectronic performance compared to polycrystalline ones, offering significant potential for high-performance and low-cost photovoltaic/optoelectronic applications. However, conventional SC growth processes often require intricate cutting or transferring of SC in the manufacturing of optoelectronic devices. High-resolution, in-situ, and scalable fabrication of perovskite SC arrays remain challenging. In this work, we propose a method for in-situ deposition of cosolvent based perovskite precursor solutions using electrohydrodynamic (EHD) printing technology. The addition of a cosolvent (which exhibits good chemical compatibility with the precursor and the main solvent, accompanied by lower solubility and vapor pressure) to the mixed solution promotes early-stage supersaturation and nucleation in the solution, enabling precise control over crystal morphology, size, and positioning through in-situ EHD printing. The effect of different cosolvent ratios on SC growth and the inhibition of parasitic crystallization by altering the contact angle of substrate were investigated. Finally, the parameters for precise control of the EHD printing process were investigated, enabling the growth of SC arrays ranging from 1 to 35 μm in size. This strategy offers a direct patterning approach for SC perovskite preparation without complex temperature control or multi-step operation. The printed patterns exhibit high resolution and excellent uniformity, offering significant potential for manufacturing SC-based perovskite optoelectronic devices with precise size and positioning control.
Carbon dioxide reduction utilizing a bismuth halide perovskite as immobilized photocatalyst in a 3D printed microreactor
Authors: Santamaria Cordero Jose A , Lopez Hannia , Ledezma Marisol , Pineda Leslie W , Duran J Esteban 
Published: January 2024

Abstract
The rising concerns about CO2 levels in the atmosphere and energy dependency on non-renewable sources, such as fossil fuels, could find an integral solution in CO2 photocatalytic reduction. The present work explores two alternatives to the main hindering factors for this reaction, i.e. the reactor configuration and the photocatalyst utilized. A microreactor was designed and 3D printed, providing a cheap and versatile reaction platform. Three bismuth halide perovskites, Cs3Bi2Cl9, Cs3Bi2I9, and Cs4MnBi2Cl12, were synthesized and characterized by their band gaps (Eg
); Cs3Bi2I9 presented the lowest Eg
and was therefore chosen for further evaluation as potential CO2-reduction photocatalyst. Aqueous-phase photocatalytic CO2 reduction was achieved using this perovskite in the microreactor, obtaining CO as a reduction product with maximal production rates of 737 μmol gcat
−1 h−1. The reaction system was evaluated under different flow rates and light intensities. A balance between space-time and reactant feed was found to define the behavior of CO concentration and production in the microreactor. For the light intensity, it was observed that as it increased, both CO production and concentration increased due to generating more electron–hole pairs, favoring the photocatalytic reaction. With these results, Cs3Bi2I9 perovskite immobilized in the designed microreactor demonstrates having great potential as an effective CO2 photocatalytic reduction system.
Performance analysis and prediction of tunable metasurface filter based on electrochemical metallization
Authors: Chen Zhiliang , Wu Kai , Li Zhongyang , Pu Xinyu , Bing Pibin , Zhang Hongtao , Tan Lian , Yao Jianquan 
Published: January 2024

Abstract
In this paper, a tunable metasurface filter based on electrochemical metallization is proposed. The finite element method is used to simulate the formation and rupture of the conductive filament (CF). The geometric structure of the metasurfaces filter is reconstructed by CF to achieve the purpose of tuning the transmission characteristics of the metasurface. Due to the formation of CF in the gap of separated rectangular gold patches, the proposed metasurface simultaneously exhibits the resonance characteristics of two separated rectangular gold patches and unseparated rectangular gold patches. Numerical calculations show that when the radius of the CF increases from 5 nm to 25 nm, the metasurface shows good tunable filtering characteristics, and its quality factor gradually increases. Finally, in order to solve the problem of consuming a lot of time to design metasurface, a deep neural network is used to predict the transmission curves corresponding to different metasurface structures. The results show that the mean square error of the training model is less than 1 × 10−3, which shows superior robustness and generalization, and greatly shortens the time required for design. This design paves a new way to develop optoelectronic devices, such as modulators, sensors and optical switches.
An improved attitude estimation algorithm for suppressing magnetic vector disturbance based on extended Kalman filter
Authors: Zong Yikai , Su Shujing , Gao Yuhong , Zhang Lili 
Published: January 2024

Abstract
This paper proposes an improved attitude estimation algorithm based on the extended Kalman filter (EKF), and it is applied to suppress the accuracy reduction in attitude estimation caused by fusing magnetometer data under large angular motion. In the proposed attitude estimation structure, the approximate variance of the estimated horizontal northbound magnetic vector is used to dynamically adjust the participation of magnetometer data in attitude estimation, as the approximate variance increases significantly under large angular motion and fusing magnetometer data will reduce estimation accuracy. A three-axis position-velocity controlled turntable is used to conduct rocking experiments for validating the proposed attitude estimation algorithm. The results show a significant improvement in yaw angle estimation accuracy with the proposed attitude estimation algorithm and correspondingly enhance the distribution of pitch and roll angle errors.
Deep learning-based wind noise prediction study for automotive clay model
Authors: Huang Lina , Wang Dengfeng , Cao Xiaolin , Zhang Xiaopeng , Huang Bingtong , He Yang , Grabner Gottfried 
Published: January 2024

Abstract
Analyzing and mitigating wind noise in automobiles is a significant issue within the realm of noise, vibration, and harshness. Due to the intricate nature of aeroacoustic generation mechanisms, current conventional methods for wind noise prediction exhibit limitations. Hence, deep learning methods are introduced to investigate wind noise in the side window area of an automotive clay model. During aeroacoustic wind tunnel experiments, side window vibration data and noise data from the driver were collected at experimental wind speeds of 100 km h−1, 120 km h−1, and 140 km h−1, respectively. These data samples were obtained to be used for training and validation of the wind noise model. Convolutional neural network (CNN), residual neural network (ResNet) and long short-term memory neural network (LSTM) algorithms were separately employed to reveal the complex nonlinear relationship between wind noise and its influencing factors, leading to the establishment of a wind noise prediction model. Simultaneously, these deep learning methods were compared with backpropagation neural network (BPNN), extreme learning machine (ELM), and support vector regression (SVR) methods. Conclusion indicates that the LSTM wind noise prediction model not merely exhibits higher accuracy, but furthermore demonstrates superior generalization capabilities, thereby substantiating the superiority of this method.