bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cardiovascular complications are resolved by tuna protein hydrolysate supplementation in rats fed with a high-fat diet
Authors: Maneesai Putcharawipa , Wattanathorn Jintanaporn , Potue Prapassorn , Khamseekaew Juthamas , Rattanakanokchai Siwayu , Thukham-Mee Wipawee , Muchimapura Supaporn , Pakdeechote Poungrat 
Published: July 2023

AbstractThis study is aimed to investigate whether tuna protein hydrolysate (TPH) supplementation could alleviate cardiovascular complications induced by a high-fat diet (HFD) in rats. Rats were fed a HFD for 16 weeks and given TPH (100 mg/kg, 300 mg/kg, or 500 mg/kg) or metformin (100 mg/kg) (n = 8) for the last four weeks. TPH had the following effects: resolved their impaired glucose tolerance, hyperglycemia, dyslipidemia, obesity, and hypertension (p < 0.05); alleviated left ventricular dysfunction and hypertrophy (p < 0.05), and vascular dysfunction and hypertrophy (p < 0.05); adipocyte hypertrophy; increases in circulating leptin and tumor necrosis factor (TNF-α) were mitigated (p < 0.05); increased renin-angiotensin system (RAS), oxidative stress, and decreased nitric oxide metabolites were modulated (p < 0.05). TPH restored the expression of angiotensin II receptor type 1 (AT1R)/NADPH oxidase 2 (NOX2), endothelial nitric oxide synthase (eNOS), nuclear factor erythroid 2-related factor (Nrf2)/heme oxygenase-1 (HO-1), and peroxisome proliferator-activated receptor γ (PPARγ)/the nuclear factor kappa B (NF-κB) protein in cardiovascular tissue (p < 0.05). In metabolic syndrome (MS) rats, metformin and TPH had comparable effects. In conclusion, TPH alleviated cardiovascular complications related to MS. It suppressed RAS, oxidative stress, and inflammation that were associated with modulation of AT1R/NOX2, eNOS, Nrf2/HO-1, and PPARγ/NF-κB expression.
Identification of genotype–biochemical phenotype correlations associated with fructose 1,6-bisphosphatase deficiency
Authors: Sakuma Ikki , Nagano Hidekazu , Hashimoto Naoko , Fujimoto Masanori , Nakayama Akitoshi , Fuchigami Takahiro , Taki Yuki , Matsuda Tatsuma , Akamine Hiroyuki , Kono Satomi , Kono Takashi , Yokoyama Masataka , Nishimura Motoi , Yokote Koutaro , Ogasawara Tatsuki , Fujii Yoichi , Ogawa Seishi , Lee Eunyoung , Miki Takashi , Tanaka Tomoaki 
Published: July 2023

AbstractFructose-1,6-bisphosphatase (FBPase) deficiency, caused by an FBP1 mutation, is an autosomal recessive disorder characterized by hypoglycemic lactic acidosis. Due to the rarity of FBPase deficiency, the mechanism by which the mutations cause enzyme activity loss still remains unclear. Here we identify compound heterozygous missense mutations of FBP1, c.491G>A (p.G164D) and c.581T>C (p.F194S), in an adult patient with hypoglycemic lactic acidosis. The G164D and F194S FBP1 mutants exhibit decreased FBP1 protein expression and a loss of FBPase enzyme activity. The biochemical phenotypes of all previously reported FBP1 missense mutations in addition to G164D and F194S are classified into three functional categories. Type 1 mutations are located at pivotal residues in enzyme activity motifs and have no effects on protein expression. Type 2 mutations structurally cluster around the substrate binding pocket and are associated with decreased protein expression due to protein misfolding. Type 3 mutations are likely nonpathogenic. These findings demonstrate a key role of protein misfolding in mediating the pathogenesis of FBPase deficiency, particularly for Type 2 mutations. This study provides important insights that certain patients with Type 2 mutations may respond to chaperone molecules.
Lite‐weight semantic segmentation with AG self‐attention
Authors: Liu Bing , Gao Yansheng , Li Hai , Zhong Zhaohao , Zhao Hongwei 
Published: July 2023

AbstractDue to the large computational and GPUs memory cost of semantic segmentation, some works focus on designing a lite weight model to achieve a good trade‐off between computational cost and accuracy. A common method is to combined CNN and vision transformer. However, these methods ignore the contextual information of multi receptive fields. And existing methods often fail to inject detailed information losses in the downsampling of multi‐scale feature. To fix these issues, we propose AG Self‐Attention, which is Enhanced Atrous Self‐Attention (EASA), and Gate Attention. AG Self‐Attention adds the contextual information of multi receptive fields into the global semantic feature. Specifically, the Enhanced Atrous Self‐Attention uses weight shared atrous convolution with different atrous rates to get the contextual information under the specific different receptive fields. Gate Attention introduces gating mechanism to inject detailed information into the global semantic feature and filter detailed information by producing “fusion” gate and “update” gate. In order to prove our insight. We conduct numerous experiments in common semantic segmentation datasets, consisting of ADE20 K, COCO‐stuff, PASCAL Context, Cityscapes, to show that our method achieves state‐of‐the‐art performance and achieve a good trade‐off between computational cost and accuracy.
Time‐varying long‐range navigation signal channel modelling based on Dirichlet process mixtures method
Authors: Ma Hongyu , Pu Yurong , Zhao Zhenzhu , Du Zhonghong , Du Yongxing , Zhao Yuchen , Xi Xiaoli 
Published: July 2023

AbstractA model of the LOng‐RAnge Navigation signal can provide a mathematical model for the development of related technology research. The propagation variations of the signal exhibit non‐stationary and non‐linear characteristics due to the time‐varying nature of the atmospheric dielectric constant in the channel. A Dirichlet process mixtures method is used by the authors to model the statistical properties of radio wave attenuation, and the Gibbs sampling method is used to flexibly estimate the parameters of the model. The model as a non‐parametric model can be applied to capture the dynamics of time‐varying signals with the parameters being adaptively inferred. A receiver is used as a measurement device to obtain real propagation data to check the performance of the model. Kullback–Leibler Divergence (KL‐Div) was used to evaluate different datasets. The results showed that the model's statistical properties were consistent. Its flexibility allows it to represent complex distributions without prior knowledge.
Induction heating of planetary interiors in white dwarf systems
Authors: Kislyakova K. G. , Noack L. , Sanchis E. , Fossati L. , Valyavin G. G. , Golabek G. J. , Güdel M. 
Published: July 2023

Context. White dwarfs are the last evolutionary stage for the majority of main-sequence stars. With nuclear burning having ceased, these stars are slowly cooling. There is observational evidence indicating that planetary remnants, and possibly even planets, orbit a considerable fraction of the known white dwarf population. These objects are interesting targets for transit observations due to their large planet-to-star radius ratio. Especially interesting is the possible outgassing from such objects and their eventual observational prospects.
Aims. Here, we investigate whether electromagnetic induction heating can drive additional volcanic outgassing from small planetary remnants orbiting white dwarfs. This mechanism can be important for such bodies in addition to tidal heating due to the extremely strong magnetic fields of some white dwarfs and close orbital distances of planets to their host stars.
Methods. We calculated the heating and related magmatic effects for a Moon-sized body around a magnetized white dwarf using an analytical model for induction heating and a numerical model for interior processes. We also calculated induction heating inside asteroid-sized bodies.
Results. We show that induction heating can melt the mantle of a Moon-sized object within a geologically short time and contribute to desiccation of small asteroids on extremely tight orbits. These findings can have important implications for the evolution of rocky bodies orbiting white dwarfs and the potential detection of their outgassing.
Cracking the puzzle of CO2 formation on interstellar ices
Authors: Molpeceres G. , Enrique-Romero J. , Aikawa Y. 
Published: July 2023

Context. Carbon dioxide (CO2) is one of the dominant components of interstellar ices. Recent observations show CO2 exists more abundantly in polar (H2O-dominated) ice than in apolar (H2O-poor) ice. Formation of CO2 ice is primarily attributed to the reaction between CO and OH, which has a barrier.
Aims. We investigate the title reaction in H2O ice and CO ice to quantify the efficiency of the reaction in polar ice and apolar ice.
Methods. Highly accurate quantum chemical calculations were employed to analyze the stationary points of the potential energy surfaces of the title reaction in the gas phase on H2O and CO clusters. Microcanonical transition state theory was used as a diagnostic tool for the efficiency of the reaction under interstellar medium conditions. We simulated the kinetics of ice chemistry, considering different scenarios involving non-thermal processes and energy dissipation.
Results. The CO + OH reaction proceeds through the remarkably stable intermediate HOCO radical. On the H2O cluster, the formation of this intermediate is efficient, but the subsequent reaction leading to CO2 formation is not. Conversely, HOCO formation on the CO cluster is inefficient without external energy input. Thus, CO2 ice cannot be formed by the title reaction alone either on an H2O cluster or a CO cluster.
Conclusions. In the polar ice, CO2 ice formation is possible via CO + OH → HOCO followed by HOCO + H → CO2 + H2, as demonstrated by abundant experimental literature. In apolar ice, CO2 formation is less efficient because HOCO formation requires external energy. Our finding is consistent with the JWST observations. Further experimental work using low-temperature OH radicals is encouraged.
Are Antiphospholipid Antibodies a Surrogate Risk Factor for Thrombosis in Sepsis?
Authors: Thachil Jecko , Favaloro Emmanuel J. , Lippi Giuseppe 
Published: July 2023

AbstractAntiphospholipid syndrome (APS) is a hypercoagulable state caused by antiphospholipid antibodies (aPL). APS clinically manifests with arterial or venous or microvascular thrombi and/or pregnancy complications. It is well-known that the development of aPL can be a transient phenomenon and thus the current diagnostic criterion for APS requires repeat laboratory testing several weeks apart before a definitive diagnosis is made. However, transient presence of aPL may also be pathogenic. In this article, we attempt to give historical and clinical evidence for the importance of these antibodies, even when transient, and call for further research into mechanisms by which these antibodies may promote thrombosis and pregnancy morbidities.
Thermoelectric response of Janus monolayer M2P2S3Se3 (M = Zn and Cd)
Authors: Feng Zhuyu , Huang Yuhong , Lin Shujing , Yuan Hongkuang , Chen Hong 
Published: July 2023

Thermoelectric transport properties of Janus monolayers M2P2S3Se3 (M = Zn and Cd) are investigated by the first-principles based transport theory. The Zn2P2S3Se3 and Cd2P2S3Se3 monolayers are indirect-gap semiconductors. The high polarizability of M-Se/S bonds in the MS3Se3 distorted octahedrons leads to anharmonic phonon behavior, which produces an intrinsic lattice thermal conductivity (κl) as low as 1.06 and 1.99 W m−1 K−1 at 300 K for Zn2P2S3Se3 and Cd2P2S3Se3 monolayers, respectively. The lower κl of the Zn2P2S3Se3 monolayer is mainly attributed to more pronounced flat modes of the phonon dispersion in a frequency range of 1–1.7 THz caused by the softer Zn–Se/S bonds. The polar optical phonon scattering of carriers surprisingly plays a dominant role in carrier transport of both the monolayers, which greatly suppresses the electrical conductivity and thereby the power factor by about an order of magnitude. The predicted figure of merit (zT) increases monotonically with the temperature at the optimal carrier density, and at the operating temperature of 1200 K, it reaches an optimal value of 0.86 at an optimal electron density of ∼1.5×1013 cm−2 for the n-type Zn2P2S3Se3 monolayer and 0.30 at an optimal electron density of ∼7×1012 cm−2 for the n-type Cd2P2S3Se3 monolayer.
The effects of incident light wavelength difference on the collective stimulated Brillouin scattering in plasmas
Authors: Wang Qiang , Li Zhichao , Liu Zhanjun , Gong Tao , Zhang Wenshuai , Xu Tao , Li Bin , Li Ping , Li Xin , Zheng Chunyang , Cao Lihua , Liu Xincheng , Pan Kaiqiang , Zhao Hang , Liu Yonggang , Deng Bo , Hou Lifei , Li Yingjie , Liu Xiangming , Li Yulong , Peng Xiaoshi , Guan Zanyang , Wang Qiangqiang , Che Xingsen , Li Sanwei , Yin Qiang , Zhang Wei , Xia Liqiong , Wang Peng , Jiang Xiaohua , Guo Liang , Li Qi , He Minqing , Hao Liang , Cai Hongbo , Zheng Wudi , Zou Shiyang , Yang Dong , Wang Feng , Yang Jiamin , Zhang Baohan , Ding Yongkun , He Xiantu 
Published: July 2023

The first laser–plasma interaction experiment using lasers of eight beams grouped into one octad has been conducted on the Shenguang Octopus facility. Although each beam intensity is below its individual threshold for stimulated Brillouin backscattering (SBS), collective behaviors are excited to enhance the octad SBS. In particular, when two-color/cone lasers with wavelength separation 0.3 nm are used, the backward SBS reflectivities show novel behavior in which beams of longer wavelength achieve higher SBS gain. This property of SBS can be attributed to the rotation of the wave vectors of common ion acoustic waves due to the competition of detunings between geometrical angle and wavelength separation. This mechanism is confirmed using massively parallel supercomputer simulations with the three-dimensional laser–plasma interaction code LAP3D.
Elimination of the bias-stress effect in ligand-free quantum dot field-effect transistors
Authors: Tolentino Jason , Gibbs Markelle , Abelson Alex , Law Matt 
Published: July 2023

Field-effect transistors (FETs) made from colloidal quantum dot (QD) solids commonly suffer from current–voltage hysteresis caused by the bias-stress effect (BSE), which complicates fundamental studies of charge transport in QD solids and the use of QD FETs in electronics. Here, we show that the BSE can be eliminated in n-channel PbSe QD FETs by first removing the QD ligands with a dose of H2S gas and then infilling the QD films with alumina by atomic layer deposition (ALD). The H2S-treated, alumina-infilled FETs have stable, hysteresis-free device characteristics (total short-term stability), indefinite air stability (total long-term stability), and a high electron mobility of up to 14 cm2 V−1 s−1, making them attractive for QD circuitry and optoelectronic devices. The BSE-free devices are utilized to conclusively establish the dependence of the electron mobility on temperature and QD diameter. We demonstrate that the BSE in these devices is caused by both electron trapping at the QD surface and proton drift within the film. The H2S/alumina chemistry produces ligand-free PbSe/PbS/Al2O3 interfaces that lack the traps that cause the electronic part of the BSE, while full alumina infilling stops the proton motion responsible for the ionic part of the BSE. Our matrix engineering approach should aid efforts to eliminate the BSE, boost carrier mobilities, and improve charge transport in other types of nanocrystal solids.
Embodied action in remote online interaction
Authors: Garcia Angela Cora 
Published: July 2023

Abstract
In this paper I use a conversation analytic approach to investigate how participants in a meeting held remotely
via Zoom use embodied action to solicit selection as next speaker. When hand raising is not immediately successful, participants
use embodied actions to withdraw, modify, upgrade, downgrade or reissue gestures in pursuit of selection as next speaker. Due to
the technological affordances and limitations of the remote meeting environment, participants’ gestures and hand positions differ
from what would typically occur in face-to-face interaction, resulting in frequent gestures near the face that provide for both
visibility to the Zoom audience and easy transition to a raised hand position when necessary. I discuss these results in terms of
our understanding of how technologically mediated virtual interaction through the internet impacts the use of embodied action, and
how participants coordinate their embodied action and responses to it with turn taking and sequence completion.
A neural network approach to kinetic Mie polarimetry for particle size diagnostics in nanodusty plasmas
Authors: Schmitz Alexander , Petersen Andreas , Greiner Franko 
Published: July 2023

Abstract
The analysis of the size of nanoparticles is an essential task in plasma technology and dusty plasmas. Light scattering techniques, based on Mie theory, can be used as a non-invasive and in-situ diagnostic tool for this purpose. However, the standard back-calculation methods require expertise from the user. To address this, we introduce a neural network that performs the same task. We discuss how we set up and trained the network to analyze the size of plasma-grown amorphous carbon nanoparticles (a:C–H) with a refractive index n in the range of real(n) =

1.4
−
2.2

and imag(n) =

0.04
i
−
0.1
i

and a radius of up to several hundred nanometers, depending on the used wavelength. The diagnostic approach is kinetic, which means that the particles need to change in size due to growth or etching. An uncertainty analysis as well as a test with experimental data are presented. Our neural network achieves results that agree with those of prior fitting algorithms while offering higher methodical stability. The model also holds a major advantage in terms of computing speed and automation.
SCE-SLAM: a real-time semantic RGBD SLAM system in dynamic scenes based on spatial coordinate error
Authors: Song Shiyu , Chen Ji , Zhong Yujiang , Zhang Wei , Hou Wenbo , Zhang Liumingyuan 
Published: July 2023

Abstract
Simultaneous localization and mapping (SLAM) is one of the prerequisite technologies for intelligent mobile robots to accomplish various tasks in unknown environments. In recent years, many excellent SLAM systems have emerged, but most of them have a basic assumption that the environment is static, which results in their poor performance in dynamic environments. To solve this problem, this paper presents SCE-SLAM: a novel real-time semantic RGB-D SLAM system that is built on the RGB-D mode of ORB-SLAM3. SCE-SLAM tightly combines semantic and geometric information. Considering the real-time requirements, the semantic module provides semantic prior knowledge for the geometric module using the latest and fastest object detection network YOLOv7. Then, a new geometric constraint method is proposed to filter dynamic feature points. This method takes full advantage of depth images and semantic information to recover three-dimensional (3D) feature points and the initial camera pose. A 3D coordinate error is used as a threshold, and SCE-SLAM removes dynamic points using the K-means clustering algorithm. In this way, SCE-SLAM effectively reduces the impact of dynamic points. Furthermore, we validate SCE-SLAM with challenging dynamic sequences of the TUM dataset. The results demonstrate that SCE-SLAM significantly improves the localization accuracy and system robustness in all kinds of dynamic environments.
Camera calibration approach using polarized light based on high-frequency component variance weighted entropy for pose measurement
Authors: Zhang Zimiao , He Linjie , Wu Yanan , Zhang Fumin 
Published: July 2023

Abstract
The camera’s intrinsic parameters calibration directly affects monocular pose measurement accuracy. To improve the calibration accuracy of the camera’s intrinsic parameters, the polarizing device is used to eliminate the high-brightness areas in the images collected for camera calibration. However, an unsuitable polarizing angle will reduce the image’s contrast. This causes the texture information of the image to be lost or makes the extracted feature change in the direction of grayscale value decline, ultimately affecting the feature extraction. Aiming at this issue, this paper proposed a camera calibration approach using polarized light based on high-frequency component variance weighted entropy (HVE). We determined the suitable polarizing angle according to the two-dimensional homography matrix describing the mapping between the target plane and normalized imaging plane for each calibration location. Under the suitable polarizing angle, we determined the optimal exposure time according to the HVE. The images collected under suitable polarizing angles and the optimal exposure time were used to finish the camera calibration. The suitable polarizing angles and optimal exposure time can ensure the image’s contrast and texture information. The experimental findings demonstrate that our approach can increase the camera calibration accuracy and thus pose measurement accuracy. In the −45° to +45° range, the average pose measurement error is less than 0.05° and lowered by 0.08° (62%) compared to that performed using the intrinsic parameters calibrated with the images collected under no polarizing device. In the 0–20 mm range, the average pose measurement error is less than 0.028 mm and lowered by 0.05 mm (64%) compared to that performed using the intrinsic parameters calibrated with the images collected under no polarizing device.
Deep learning with CBAM-based CNN for batch process quality prediction
Authors: Zhao Xiaoqiang , Tuo Benben , Hui Yongyong 
Published: July 2023

Abstract
Data-driven quality prediction model has been widely used in product estimation of batch processes. However, the initial conditions of different batches in batch process are different, and the multiphase characteristics and nonlinearity in batch are not conducive to the quality prediction. To solve these problems, a model for batch process quality prediction based on a convolutional neural network (CNN) is proposed. Firstly, in order to enhance data characteristics and reduce model computing time, a maximum information coefficient (MIC) method based on mutual information is used to select variables according to the correlation between process variables and quality variables. Secondly, the quality prediction model of convolutional block attention module (CBAM)-CNN based on the attention mechanism is established. On the one hand, an improved CBAM is fused into the CNN. The input feature mapping is re-calibrated to focus on useful feature information and weaken irrelevant redundant information in each sliding window. On the other hand, by introducing an improved convolutional module with double-band skip connection lines, the backpropagation speed of the CBAM-CNN model is accelerated, which can effectively avoid the occurrence of the overfitting problem. Finally, the data of batch process is used as the input of the prediction model. The superiority and effectiveness of the proposed model are verified by predicting the quality variable of the penicillin fermentation process simulation benchmark and the industrial-scale penicillin fermentation process. It is proved that the proposed model has better generalization performance in the quality prediction of the penicillin fermentation process with different control strategies.
On Feldman–Katok metric and entropy formulas
Authors: Cai Fangzhou , Li Jie 
Published: July 2023

Abstract
In this paper, we study the Feldman–Katok metric and give corresponding entropy formulas by replacing Bowen metric with Feldman–Katok metric. It turns out that the Feldman–Katok metric is the weakest one, in the sense of allowing desynchrony and jump in the process of measuring orbit segments’ distance, that makes the entropy formulas valid. Some related topics are also discussed.