bluuebunny/crossref_metadata_2025_split huggingface dataset:
Astronomical image time series classification using CONVolutional attENTION (ConvEntion)
Authors: Bairouk Anass , Chaumont Marc , Fouchez Dominique , Paquet Jerome , Comby Frédéric , Bautista Julian 
Published: March 2023

Aims. The treatment of astronomical image time series has won increasing attention in recent years. Indeed, numerous surveys following up on transient objects are in progress or under construction, such as the Vera C. Rubin Observatory Legacy Survey for Space and Time (LSST), which is poised to produce huge amounts of these time series. The associated scientific topics are extensive, ranging from the study of objects in our galaxy to the observation of the most distant supernovae for measuring the expansion of the universe. With such a large amount of data available, the need for robust automatic tools to detect and classify celestial objects is growing steadily.
Methods. This study is based on the assumption that astronomical images contain more information than light curves. In this paper, we propose a novel approach based on deep learning for classifying different types of space objects directly using images. We named our approach ConvEntion, which stands for CONVolutional attENTION. It is based on convolutions and transformers, which are new approaches for the treatment of astronomical image time series. Our solution integrates spatio-temporal features and can be applied to various types of image datasets with any number of bands.
Results. In this work, we solved various problems the datasets tend to suffer from and we present new results for classifications using astronomical image time series with an increase in accuracy of 13%, compared to state-of-the-art approaches that use image time series, and a 12% increase, compared to approaches that use light curves.
Immune-mediated Gastritis in a Patient with metastatic Lung Cancer due to Therapy with the immune Checkpoint Inhibitor Pembrolizumab – Differences and Similarities in Comparison to “endogenous” autoimmune Type A Gastritis and a review of literature
Authors: Ecker Miriam Eva , Weckauf Helgard , Tebbe Sandra , Schuppert Frank 
Published: March 2023

Abstract
Immune checkpoint inhibitors are increasingly used in advanced malignant diseases and are
well-known for their good results. With the blockade of immune checkpoints, the probability of
immune-related adverse events is also increased.We present a 54-year-old female patient with advanced NSCLC. She was treated with
pembrolizumab and developed a stable disease under therapy. After six cycles, she presented
with massive epigastric pain to our emergency department. Gastroscopy showed severe
erosive-fibrinous pangastritis without the involvement of the esophagus, duodenum, or other
immune-related adverse effects. Histology showed the complete destruction of the gastric
mucosa. We concluded an immune-mediated gastritis by pembrolizumab, after the exclusion of
other differential diagnoses.Despite treatment with prednisolone and marked improvement of her symptoms, the mucosa was
never fully reconstituted into a healthy mucosa.Furthermore, we collected published reports of similar cases and conducted a comparison
with features of a typical, endogenous type A gastritis to highlight similarities and
differences.
A case of tracheobronchial amyloidosis with emphasis on differential diagnosis
Authors: Anyfanti Foteini , Dubak Marija , Bollow Matthias , Ewig Santiago 
Published: March 2023

AbstractTracheobronchial amyloidosis is a manifestation of amyloidosis of the respiratory tract characterized by focal or diffuse deposition of amyloid in the submucosa of the trachea and proximal bronchi. Tracheobronchial amyloidosis is not associated with systemic amyloidosis or pulmonary parenchymal involvement. It affects predominantly men aged over fifty. Depending on the part of the tracheobronchial tree that is affected, stenosis of the airways causes a variety of unspecific symptoms. Diagnosis is reached by means of typical presentation in CT scan followed by bronchoscopy and histopathological confirmation. Tracheobronchial amyloidosis should be borne in mind in the differential diagnosis of patients with chronic cough and/or dyspnea or recurrent respiratory infections.
Ultrafast time-resolved 2D imaging of laser-driven fast electron transport in solid density matter using an x-ray free electron laser
Authors: Sawada H. , Yabuuchi T. , Higashi N. , Iwasaki T. , Kawasaki K. , Maeda Y. , Izumi T. , Nakagawa Y. , Shigemori K. , Sakawa Y. , Curry C. B. , Frost M. , Iwata N. , Ogitsu T. , Sueda K. , Togashi T. , Glenzer S. H. , Kemp A. J. , Ping Y. , Sentoku Y. 
Published: March 2023

High-power, short-pulse laser-driven fast electrons can rapidly heat and ionize a high-density target before it hydrodynamically expands. The transport of such electrons within a solid target has been studied using two-dimensional (2D) imaging of electron-induced Kα radiation. However, it is currently limited to no or picosecond scale temporal resolutions. Here, we demonstrate femtosecond time-resolved 2D imaging of fast electron transport in a solid copper foil using the SACLA x-ray free electron laser (XFEL). An unfocused collimated x-ray beam produced transmission images with sub-micron and ∼10 fs resolutions. The XFEL beam, tuned to its photon energy slightly above the Cu K-edge, enabled 2D imaging of transmission changes induced by electron isochoric heating. Time-resolved measurements obtained by varying the time delay between the x-ray probe and the optical laser show that the signature of the electron-heated region expands at ∼25% of the speed of light in a picosecond duration. Time-integrated Cu Kα images support the electron energy and propagation distance observed with the transmission imaging. The x-ray near-edge transmission imaging with a tunable XFEL beam could be broadly applicable for imaging isochorically heated targets by laser-driven relativistic electrons, energetic protons, or an intense x-ray beam.
A study of core-excited states of organic molecules computed with the generalized active space driven similarity renormalization group
Authors: Huang Meng , Evangelista Francesco A. 
Published: March 2023

This work examines the accuracy and precision of x-ray absorption spectra computed with a multireference approach that combines generalized active space (GAS) references with the driven similarity renormalization group (DSRG). We employ the x-ray absorption benchmark of organic molecule (XABOOM) set, consisting of 116 transitions from mostly organic molecules [Fransson et al., J. Chem. Theory Comput. 17, 1618 (2021)]. Several approximations to a full-valence active space are examined and benchmarked. Absolute excitation energies and intensities computed with the GAS-DSRG truncated to second-order in perturbation theory are found to systematically underestimate experimental and reference theoretical values. Third-order perturbative corrections significantly improve the accuracy of GAS-DSRG absolute excitation energies, bringing the mean absolute deviation from experimental values down to 0.32 eV. The ozone molecule and glyoxylic acid are particularly challenging for second-order perturbation theory and are examined in detail to assess the importance of active space truncation and intruder states.
A wireless demodulation system based on a multi-parameter resonant sensor
Authors: Wang Hao , Liang Xiaorui , Zhang Juan , Zhang Lei , Xie Hao , Zhao Zhongliang , Tan Qiulin 
Published: March 2023

This paper proposes a wireless passive measurement system that supports real-time signal acquisition, multi-parameter crosstalk demodulation, and real-time storage and calculation. The system consists of a multi-parameter integrated sensor, an RF signal acquisition and demodulation circuit, and a multi-functional host computer software. The sensor signal acquisition circuit uses a wide frequency detection range (25 MHz–2.7 GHz) to meet the resonant frequency range of most sensors. Since the multi-parameter integrated sensors are affected by multiple factors, such as temperature and pressure, there will be interference between them, so the algorithm for multi-parameter decoupling is designed, and the software for sensor calibration and real-time demodulation is developed to improve the usability and flexibility of the measurement system. In the experiment, temperature and pressure dual-reference integrated surface acoustic wave sensors in the condition of 25–550 °C and 0–700 kPa are used for testing and verification. After experimental testing, the swept source of the signal acquisition circuit can meet the output accuracy in a wide frequency range, and the detection result of the sensor dynamic response is consistent with that of the network analyzer, with a maximum test error of 0.96%. Furthermore, the maximum temperature measurement error is 1.51%, and the maximum pressure measurement error is 5.136%. These results indicate that the proposed system has good detection accuracy and demodulation performance, and it can be used for multi-parameter wireless real-time detection and demodulation.
circNEIL3 inhibits tumor metastasis through recruiting the E3 ubiquitin ligase Nedd4L to degrade YBX1
Authors: Chen Shuang , Li Ke , Guo Jiawei , Chen Hai-Ning , Ming Yue , Jin Yang , Xu Fuyan , Zhang Tingting , Yang Yang , Ye Zixia , Liu Wenrong , Ma Hulin , Cheng Jian , Zhou Jian-Kang , Li Zhang , Shen Shu , Dai Lunzhi , Zhou Zong-Guang , Xu Heng , Peng Yong 
Published: March 2023

Distant metastasis is a major contributor to cancer-related mortality. However, the role of circRNAs in this process remains unclear. Herein, we profiled the circRNA expression in a cohort of 68 colorectal carcinoma (CRC) primary tumors and their paired liver metastatic lesions. By overlapping with the TGFβ-responsive circRNAs, circNEIL3 (hsa_circ_0001460) was identified as a TGFβ-repressive and metastasis-related circRNA. Functionally, circNEIL3 effectively inhibited tumor metastasis in both and in vivo and in vivo models of various cancer types. Mechanistically, circNEIL3 exerts its metastasis-repressive function through its direct interaction with oncogenic protein, Y-box-binding protein 1 (YBX1), which consequently promotes the Nedd4L-mediated proteasomal degradation of YBX1. Importantly, circNEIL3 expression was negatively correlated to YBX1 protein level and metastatic tendency in CRC patient samples. Collectively, our findings indicate the YBX1-dependent antimetastatic function of circNEIL3 and highlight the potential of circNEIL3 as a biomarker and therapeutic option in cancer treatment.
RETRACTED: Neurexin-2 restricts synapse numbers and restrains the presynaptic release probability by an alternative splicing-dependent mechanism
Authors: Lin Pei-Yi , Chen Lulu Y. , Zhou Peng , Lee Sung-Jin , Trotter Justin H. , Südhof Thomas C. 
Published: March 2023

α- and β-neurexins are extensively alternatively spliced, presynaptic cell-adhesion molecules that are thought to organize synapse assembly. However, recent data revealed that, in the hippocampus in vivo, the deletion of one neurexin isoform,
Nrxn2
, surprisingly increased excitatory synapse numbers and enhanced their presynaptic release probability, suggesting that
Nrxn2
restricts, instead of enabling, synapse assembly. To delineate the synaptic function and mechanism of action of
Nrxn2
, we examined cultured hippocampal neurons as a reduced system. In heterologous synapse formation assays, different alternatively spliced Nrxn2β isoforms robustly promoted synapse assembly similar to Nrxn1β and Nrxn3β, consistent with a general synaptogenic function of neurexins. Deletion of
Nrxn2
from cultured hippocampal neurons, however, caused a significant increase in synapse density and release probability, replicating the in vivo data that suggested a synapse-restricting function. Rescue experiments revealed that two of the four Nrxn2β splice variants (Nrxn2β-SS4+/SS5− and Nrxn2β-SS4+/SS5+) reversed the increase in synapse density in
Nrxn2
-deficient neurons, whereas only one of the four Nrxn2β splice variants (Nrxn2β-SS4+/SS5+) normalized the increase in release probability in
Nrxn2
-deficient neurons. Thus, a subset of
Nrxn2
splice variants restricts synapse numbers and restrains their release probability in cultured neurons.
Calibration of 10 nF capacitance standard from DC quantum Hall resistance using a digital impedance bridge
Authors: Tran Ngoc Thanh Mai , Kucera Jan , Kim Wan-Seop , Kim Dan Bee 
Published: March 2023

Abstract
This paper describes the calibration of a 10 nF capacitance standard traced to the DC quantum Hall resistance primary standard using a multi-purpose digital impedance bridge. The bridge can directly compare the unlike impedances in the fully digital (FD) mode, so the capacitance standard can be calibrated by a direct comparison against the AC resistance standard. The measurement ability of the bridge in the FD mode was evaluated in various angles, and the bridge voltage dependencies were improved by selecting appropriate impedances for the high current arms and also by using an additional injection circuit. Thereby, the measurement accuracy could reach up to 10−7 in relative terms. Based on the bridge evaluation, a 10 nF capacitance standard was calibrated against a 10 kΩ resistance standard, and the measurement value agreed with a reference value in the level of 10−7.
Computational study of 2D photonic crystal based biosensor for SARS-COV-2 detection
Authors: Miyan Hameed , Agrahari Rajan , Gowre Sanjay Kumar , Jain Pradip Kumar , Mahto Manpuran 
Published: March 2023

Abstract
A computational study to design a 2D-photonic crystal (PC) structure with a fluorescence-based biosensor has been demonstrated for the detection of the severe acute respiratory syndrome corona virus 2 (SARS-COV-2) virus in the lungs. The proposed sensor can detect the different concentrations of the virus without any pretreatment of the sample. The virus detection is performed by measuring the mid-gap wavelength from the dispersion diagram and a redshift in the mid-gap wavelength has been observed as the concentration of virus increases in the lung tissue. The plane wave expansion method is used to determine the dispersion diagram of the proposed PC. The interaction of incident light with the proposed PC-based biosensor has been analyzed to evaluate the shift in the mid-gap wavelength. A maximum sensitivity of about 1459.3 nm/RIU is obtained for r/a = 0.45 with a mid-gap wavelength shift of 145.93 nm at

n

net

= 1.49 concentration of SARS-COV-2. Moreover, a very small detection time has been observed with the proposed device as compared to conventional methods. This study provides a simple process to detect the presence of a virus within a short period and could be helpful in the development of a direct and easy-to-use portable detection kit in the future.
First-principles screening of surface-charge-transfer molecular dopants for n-type diamond
Authors: Xing Bangyu , Sang Dandan , Wang Xueting , Li Hongdong , Zhang Lijun 
Published: March 2023

Abstract
Surface charge transfer doping (SCTD) is an alternative approach to achieving n-type doped diamonds since the n-type bulk doping of diamonds remains a challenge, but so far efficient diamond n-type SCTD has not been achieved. Here we provide a comprehensive study of the n-type SCTD of the diamond by using first-principles calculations based on the density functional theory. Taking the principle that ionization potentials of the dopants must be higher than those of the diamond, we screened a series of molecules that may be suitable for diamond n-type SCTD doping. Methyl viologen and benzyl viologen provide the largest amount of transfer electron among the common n-type SCTD dopants for the oxygen and fluorine terminated (100) surface diamond, with the electron areal densities of

2.60
×

10

13

cm

−
2

and

9.20
×

10

12

cm

−
2

,

respectively. It is indicated that the transferred electron amount is positively correlated with the difference between the ionization potentials of the dopants and the electron affinity of the diamond, while the density of dopants also has a positive impact with a decreasing trend. The present work provides a useful understanding of the physical mechanism for the n-type SCTD of diamonds, and benefits the development of n-type SCTD diamond materials.
Deep learning enables MV-based real-time image guided radiation therapy for prostate cancer patients
Authors: Chrystall Danielle , Mylonas Adam , Hewson Emily , Martin Jarad , Keall Paul , Booth Jeremy , Nguyen Doan Trang 
Published: March 2023

Abstract

Objective. Using MV images for real-time image guided radiation therapy (IGRT) is ideal as it does not require additional imaging equipment, adds no additional imaging dose and provides motion data in the treatment beam frame of reference. However, accurate tracking using MV images is challenging due to low contrast and modulated fields. Here, a novel real-time marker tracking system based on a convolutional neural network (CNN) classifier was developed and evaluated on retrospectively acquired patient data for MV-based IGRT for prostate cancer patients. Approach. MV images, acquired from 29 volumetric modulated arc therapy (VMAT) prostate cancer patients treated in a multi-institutional clinical trial, were used to train and evaluate a CNN-based marker tracking system. The CNN was trained using labelled MV images from 9 prostate cancer patients (35 fractions) with implanted markers. CNN performance was evaluated on an independent cohort of unseen MV images from 20 patients (78 fractions), using a Precision–Recall curve (PRC), area under the PRC plot (AUC) and sensitivity and specificity. The accuracy of the tracking system was evaluated on the same unseen dataset and quantified by calculating mean absolute (±1 SD) and [1st, 99th] percentiles of the geometric tracking error in treatment beam co-ordinates using manual identification as the ground truth. Main results. The CNN had an AUC of 0.99, sensitivity of 98.31% and specificity of 99.87%. The mean absolute geometric tracking error was 0.30 ± 0.27 and 0.35 ± 0.31 mm in the lateral and superior–inferior directions of the MV images, respectively. The [1st, 99th] percentiles of the error were [−1.03, 0.90] and [−1.12, 1.12] mm in the lateral and SI directions, respectively. Significance. The high classification performance on unseen MV images demonstrates the CNN can successfully identify implanted prostate markers. Furthermore, the sub-millimetre accuracy and precision of the marker tracking system demonstrates potential for adaptation to real-time applications.
Reduced-order modeling and analysis of dynamic cerebral autoregulation via diffusion maps
Authors: dos Santos K R M , Katsidoniotaki M I , Miller E C , Petersen N H , Marshall R S , Kougioumtzoglou I A 
Published: March 2023

Abstract

Objective. A data-driven technique for parsimonious modeling and analysis of dynamic cerebral autoregulation (DCA) is developed based on the concept of diffusion maps. Specifically, first, a state-space description of DCA dynamics is considered based on arterial blood pressure, cerebral blood flow velocity, and their time derivatives. Next, an eigenvalue analysis of the Markov matrix of a random walk on a graph over the dataset domain yields a low-dimensional representation of the intrinsic dynamics. Further dimension reduction is made possible by accounting only for the two most significant eigenvalues. The value of their ratio indicates whether the underlying system is governed by active or hypoactive dynamics, indicating healthy or impaired DCA function, respectively. We assessed the reliability of the technique by considering healthy individuals and patients with unilateral internal carotid artery (ICA) stenosis or occlusion. We computed the sensitivity of the technique to detect the presumed side-to-side difference in the DCA function of the second group (assuming hypoactive dynamics on the occluded or stenotic side), using McNemar’s chi square test. The results were compared with transfer function analysis (TFA). The performance of the two methods was also compared under the assumption of missing data. Main results. Both diffusion maps and TFA suggested a physiological side-to-side difference in the DCA of ICA stenosis or occlusion patients with a sensitivity of 81% and 71%, respectively. Further, both two methods suggested the difference between the occluded or stenotic side and any two sides of the healthy group. However, the diffusion maps captured additional difference between the unoccluded side and the healthy group, that TFA did not. Furthermore, compared to TFA, diffusion maps exhibited superior performance when subject to missing data. Significance. The eigenvalues ratio derived using the diffusion maps technique can be potentially used as a reliable and robust biomarker for assessing how active the intrinsic dynamics of the autoregulation is and for indicating healthy versus impaired DCA function.
Negative capacitance gate-all-around PZT silicon nanowire with high-K/metal gate MFIS structure for low SS and high I
on/I
off
Authors: Kumar Vivek , Maurya Ravindra Kumar , Malvika  , Rawat Gopal , Mummaneni Kavicharan 
Published: March 2023

Abstract
In the present work, a high-k dielectric hafnium dioxide and lead zirconate titanate (PZT) have been incorporated as a ferroelectric (FE) layer in the gate stack. The Ion/Ioff ratio obtained of the order of 1013, and the subthreshold swing 49.7 mV dec−1 are the most captivating findings of the device which outshines earlier findings. There is a significant improvement in the on-state current (I
on) and off-state current (I
off). Furthermore, comparatively high value of transconductance (g
m) and transconductance generation factor (g
m/I
d), due to the incorporation of 20 nm PZT NC FE layer, insinuates that the device could be used in low power applications. These enticing findings of the proposed PZT GAA-NCFET nanowire could pave the way for low power devices.
Implementation of artificial neural network based control for power quality enhancement of proton exchange membrane fuel cell powered distributed generation system
Authors: Singh Shubham Kumar , Agarwal Anshul 
Published: March 2023

Abstract
In this paper, a fuel cell and battery-based distributed generation system is demonstrated. A proton exchange membrane fuel cell is the primary power generator in this decentralized system, with a lead-acid battery providing backup power. A boost converter regulates the fuel cell’s output power to ensure its optimal performance. A bidirectional buck-boost converter has been employed to integrate battery using slope compensated current control. 5-level cascaded H-Bridge inverter is used to convert available DC power into AC power while integrating DG systems with the grid and improving power quality. The artificial neural network has been trained and used to generate the estimated reference current for sinusoidal pulse width modulation techniques. The artificial neural network has been fine-tuned using the scaled conjugate gradient with the performance value 0.094056. The THD of grid current has been reduced by 12.5% and 8.14% approximately for 30 Ω resistive, 30 mH inductive load and 20 Ω resistive, 15 mH inductive load respectively. The system has been simulated in Matlab/Simulink, and the findings have been validated. The results demonstrate the effectiveness of the methodology.