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Background: 25-Hydroxyvitamin D (25OHD) and insulin-like growth factor 1 (IGF1) are crucial for bone health. Some studies have shown that they interact, whereas others have indicated no association. However, it remains inconclusive whether the interaction between the two is dose dependent. Herein, we explored the relationship between 25OHD and IGF1 by conducting a cross-sectional study. Methods: This study involved 6,046 individuals from the Third National Health and Nutrition Examination Survey (NHANES III). The dependent and independent variables were IGF1 and 25OHD levels, respectively. The covariates included age, sex, race, BMI, exercise, smoking behavior, alcohol intake, diabetes, and serum calcium level. Multiple linear regression and generalized additive model were employed to analyze the relationship between 25OHD and IGF1. Interaction and hierarchical analyses were also performed. Results: The 25OHD and IGF1 levels positively correlated after adjusting for covariates (β = 0.16, 95% CI: 0.04–0.29, P = 0.0103). Smooth curve fitting demonstrated a curvilinear relationship. When the 25OHD level was < 75 nmol/L, a positive correlation (β = 0.43, 95% CI: 0.25–0.62, P < 0.0001) was observed. When the 25OHD level was > 75 nmol/L, a negative correlation was observed (β = −0.53, 95% CI: −0.90 to −0.15, P = 0.0057). Conclusion: This study demonstrated a nonlinear relationship between 25OHD and IGF1. It suggests that keeping the 25OHD level within a specific range may be more conducive to bone health. Additionally, when IGF1 is used to evaluate the efficacy and safety of recombinant human growth hormone (rhGH) in growth hormone deficiency treatment, the effect of 25OHD on the actual IGF1 level should be taken into account. [ABSTRACT FROM AUTHOR]

Chirality or handedness distinguishes an object from its mirror images, such as the spread thumb, index finger, and middle finger of the right and left hand. In mathematics, it is described by the outer product of three vectors that obey a right-hand vs. left-hand rule. The chirality of ground state magnetic textures defined by the vectors of magnetization, its gradient, and an electric field from broken inversion symmetry can be fixed by a strong relativistic spin–orbit interaction. This review focuses on the chirality observed in the excited states of the magnetic order, dielectrics, and conductors that hold transverse spins when they are evanescent. Even without any relativistic effect, the transverse spin of the evanescent waves is locked to the momentum and the surface normal of their propagation plane. This chirality thereby acts as a generalized spin–orbit interaction, which leads to the discovery of various chiral interactions between magnetic, phononic, electronic, photonic, and plasmonic excitations in spintronics that mediate the excitation of quasiparticles into a single direction, leading to phenomena such as chiral spin and phonon pumping, chiral spin Seebeck, spin skin, magnonic trap, magnon Doppler, chiral magnon damping, and spin diode effects. Intriguing analogies with electric counterparts in the nano-optics and plasmonics exist. After a brief review of the concepts of chirality that characterize the ground state chiral magnetic textures and chirally coupled magnets in spintronics, we turn to the chiral phenomena of excited states. We present a unified electrodynamic picture for dynamical chirality in spintronics in terms of generalized spin–orbit interaction and compare it with that in nano-optics and plasmonics. Based on the general theory, we subsequently review the theoretical progress and experimental evidence of chiral interaction, as well as the near-field transfer of the transverse spins, between various excitations in magnetic, photonic, electronic and phononic nanostructures at GHz time scales. We provide a perspective for future research before concluding this article. [ABSTRACT FROM AUTHOR]

Depth estimation is crucial for scene understanding and downstream tasks, especially the self-supervised training methods showing great potential. The overall structure and local details of the scene are essential for improving the quality of depth estimation. The proposal of Monodepth2 has led to significant progress in self-supervised monocular depth estimation. However, Monodepth2 uses the most basic encoder–decoder architecture. The limited data flow information of the network leads to a large semantic gap between the encoder and the decoder, which reduces the accuracy of the network for fine-grained feature recognition. Monodepth2 adopts Resnet18 pre-trained on the Imagenet dataset as the encoder. This traditional convolutional pooling structure results in a loss of pixel information in the network at every scale. In order to solve this problem, this paper proposes an improved DepthNet. The network adopts Hrnet in semantic segmentation as the base encoder, which adopts an advanced multi-scale fusion method in the whole process, thus avoiding the loss of pixel information. An additional densely connected U-Net is employed at the decoder side to provide more information flow. Furthermore, the semantic gap between the encoder and decoder is reduced by adding different numbers of residual connections and channel attention on each layer. The network structure can be regarded as a collection of fully convolutional networks. Since the deep features of the network have a higher correlation with the vertical position, we add a spatial location attention module to the deep-level network to reduce this semantic gap. The approach performs significantly well on the KITTI dataset benchmark, with several performance criteria comparable to supervised monocular depth inference methods. • This work is a deep estimation network for scene reconstruction and scene understanding. This network redesigns the self-supervised monocular depth framework from an entirely new perspective. The network uses HrNet from the field of semantic segmentation as the base encoder, which employs a progressive multi-scale fusion approach throughout, thus avoiding the loss of pixel information. • An additional densely connected U-Net is used at the decoder side to provide further information flow. To reduce the semantic gap between codecs, we add a different number of residual connections and channel attention on each layer. The network is not trained with the help of other auxiliary networks, and the performance of the depth estimation is improved only by stimulating the network's potential. • This work achieves best-in-class accuracy in monocular depth estimation. When the model in this paper is used for 3D scene reconstruction, it can perform a complete recovery of the scene structure. [ABSTRACT FROM AUTHOR]

Vision-based localization and mapping for agricultural environment is challenging due to unstructured scene with less distinguishable landmarks and more repetitive textures, scale drift caused by wide and distant view, illumination variations and abrupt movements. To address these challenges, we propose a scale-aware stereo direct odometry with online photometric calibration for agricultural environment. We first propose a scale-aware stereo direct image alignment method to explicitly capture the scale at tracking stage. Then we optimize the scale and affine brightness parameters of stereo frames to keep the scale consistency in the sliding window. Furthermore, we incorporate online photometric calibration to resist illumination changes and exposure differences of image sequence. The proposed system achieves new state-of-the-art results on two public agricultural datasets, demonstrating its effectiveness in challenging agricultural environments. [ABSTRACT FROM AUTHOR]

In space gravitational wave detection missions, the laser heterodyne interference signal (LHI signal) has a high-dynamic characteristic due to the Doppler shift. Therefore, the three beat-notes frequencies of the LHI signal are changeable and unknown. This may further lead to the unlocking of the digital phase-locked loop (DPLL). Traditionally, fast Fourier transform (FFT) has been used as a method for frequency estimation. However, the estimation accuracy cannot meet the requirement of space missions because of the limited spectrum resolution. In order to improve the multi-frequency estimation accuracy, a method based on center of gravity (COG) is proposed. The method improves the estimation accuracy by using the amplitude of the peak points and the neighboring points of the discrete spectrum. For different windows that may be used for signal sampling, a general expression for multi-frequency correction of the windowed signal is derived. Meanwhile, a method based on error integration to reduce the acquisition error is proposed, which solves the problem of acquisition accuracy degradation caused by communication codes. The experimental results show that the multi-frequency acquisition method is able to accurately acquire the three beat-notes of the LHI signal and meet the requirement of space missions. [ABSTRACT FROM AUTHOR]

In this paper, the wake and potential flow effects of the rotor–stator interaction in a centrifugal pump with guide vanes are investigated from the view of the separation of turbulent and acoustic pressure fluctuations. The highest vibration levels in pumps are, in general, originated in the potential flow and wake effects. However, it is challenging to distinguish their effects on flow evolution. The pellicular mode decomposition method is applied to innovatively separate potential flow and wake disturbances in a centrifugal pump. By pellicular, we mean an infinitely thin layer of air located on the monitoring surface. The pellicular modes are a set of acoustic modes, with which a set of normalized orthogonal basis can be constructed. The impacts of potential flow and wake disturbances are visualized and evaluated quantitatively. The results show that only a very limited region is where the potential flow disturbance works. The higher the harmonics, the smaller the disturbance range. The wake disturbance is responsible for the modal pressure field. Modal pressure fields with low diametrical nodes decay more slowly than those with low harmonics. In addition, special attention is paid to the impact of the geometric asymmetry of the volute on the impeller force. The circular volute with a two-stage pressure drop improves the radial force of the impeller. More deep understandings on the mechanism of the rotor–stator interaction are reached by decoupling the potential flow and wake disturbances. This work serves as a guide for further research in fault diagnosis and vibration control of centrifugal pumps. [ABSTRACT FROM AUTHOR]

Background: LIN28B plays a critical role in the Warburg effect. However, its underlying mechanism remains elusive. Recently, it has been reported that LIN28B could collaborate with IGF2BP3, which can bind to m6A-modified c-MYC transcripts. Therefore, this study investigated if LIN28B recognises methylated c-MYC mRNA to promote the Warburg effect in gastric cancer. Methods: Effects of LIN28B on gastric cancer were confirmed in vitro and in vivo. On the basis of bioinformatics analysis, the association between LIN28B and c-MYC mRNA was shown using RNA immunoprecipitation (RIP) and luciferase reporter assays. The role of m6A was identified by RNA pull-down assays. We further performed RIP-seq to search for long non-coding RNAs (lncRNAs) participating in the LIN28B binding process. Chromatin immunoprecipitation was used to show the impact of c-MYC on transcription of LIN28B and lncRNAs. Results: LIN28B was identified to stabilize c-MYC mRNA by recognizing m6A. Furthermore, the interaction between c-MYC mRNA and LIN28B is speculated to be supported by LOC101929709, which binds to both LIN28B and IGF2BP3. Functional experiments revealed that LOC101929709 promotes the proliferation, migration and glycolysis of gastric cancer. Mechanistically, LOC101929709 enriched in the cytoplasm helps LIN28B stabilize c-MYC mRNA. Moreover, c-MYC promoted the transcription of both LOC101929709 and LIN28B. Additionally, LOC101929709 also activated the PI3K/AKT pathway. Conclusions: The c-MYC/LOC101929709/LIN28B axis promotes aerobic glycolysis and tumour progression. Thus, LOC101929709 can be a novel potential target for gastric cancer treatment. [ABSTRACT FROM AUTHOR]

The center path of the 21 June 2020 solar eclipse, which passed through Guam (13.62°N, 144.86°E, 94.6% obscuration), United States, at the end of its journey, provides a peculiar opportunity to study the ionospheric changes as the moon shadow moves into the nightside. In this study, remote-sensing observations of the ionosphere taken from the ionosonde, and total electron content from the International GNSS Service over Guam were analyzed to examine the related ionospheric changes. Independent in situ observations of electron density (Ne), electron (Te) and ion temperatures (Ti) from DMSP-F17 at ~850 km, and Ne and Te from Swarm-B at ~540 km were also studied. With a significant enhancement of the critical frequency and downward movement of F2-layer, the ionosphere was compressed as the moon shadow swept over Guam near its sunset hours. Neutral wind observations from the Ionospheric Connection Explorer (ICON) showed the westward reversed wind occurring in the F-region near sunset. The westward wind disturbance and downward press over the Western Pacific suggest changes in the electrodynamics in the ionosphere and thermosphere near sunset at the end of the solar eclipse, which further contributes to ~85% decrease of Ne and 157% enhancement of Te at ~540 km near midnight. [ABSTRACT FROM AUTHOR]

Using the observations of the 630-nm all-sky imagers (ASIs) located in the geomagnetic conjugate points in the American sector from 2014 to 2017, this study statistically analyzed the features of conjugate equatorial plasma bubbles (EPBs), including their occurrence rate, zonal width, location and zonal drift velocity. The results show that the occurrence rate of the EPBs that occur simultaneously at geomagnetic conjugate points is ∼84%. The zonal widths of the EPBs are mainly ∼100 km, and the width differences of EPBs between the northern and southern hemispheres are mainly within ±30 km. The zonal displacements of the center locations of the northern and southern EPBs are within ±50 km. The zonal drift velocities of the northern and southern EPBs are nearly equal. However, it should be noted that the velocity of the EPBs in the northern hemisphere is 10% faster than that in the southern hemisphere. The results suggest that conjugate EPBs are common. Moreover, the non-conjugate EPBs in the northern and southern hemisphere can occur occasionally, which is probably associated with the different ionospheric backgrounds between the two hemispheres. The features of the conjugate EPBs as shown in this study provides support for the nowcasting of EPBs in the conjugate hemispheres. [ABSTRACT FROM AUTHOR]

Background: To evaluate the value of ultrasound-guided vacuum-assisted excision (US-guided VAE) in the treatment of intraductal papillomas, including intraductal papillomas with atypical ductal hyperplasia (ADH), and to evaluate the lesion characteristic features affecting the local recurrence rate. Materials and methods: Between August 2011 and December 2020, 91 lesions of 91 patients underwent US-guided VAE and were diagnosed with intraductal papilloma with or without ADH. The recurrence rate of intraductal papilloma was evaluated on follow-up US. The lesion characteristic features were analyzed to identify the factors affecting the local recurrence rate. Results: The local recurrence rate of intraductal papillomas removed by US-guided VAE was 7.7% (7/91), with the follow-up duration 12–92 months (37.4 ± 23.9 months). Of the 91 patients, five cases diagnosed as intraductal papilloma with ADH did not recur, with the follow-up time 12–47 months (26.4 ± 14.4 months). There were no malignant transformation in all 91 cases during the follow-up period. All 7 patients recurred 7–58 months (22.8 ± 19.2 months) after US-guided VAE. There were no significant differences between the non-recurrence and recurrence groups in terms of age, side, distance from nipple, lesion size, BI-RADS category, with ADH, or history of excision (p > 0.05). Conclusions: US-guided VAE is an effective method for the treatment of intraductal papilloma, including intraductal papilloma with ADH. It avoids invasive surgical excision, but regular follow-up is recommended to prevent recurrence or new onset due to multifocality. Any suspicious lesions during the follow-up should be actively treated. [ABSTRACT FROM AUTHOR]

This paper combs the domestic and foreign research status of biological methods from three aspects: the principle, application and research progress of treatment technology, and comprehensively analyzes the advantages and disadvantages of nitrification, denitrification, and Anammox (Anammox). A more scientific method to understand the research status and development trend of biological treatment of nitrogenous wastewater; it is pointed out that nitrogen, as a nutrient, can be directly recycled; it is stated that the deammonia nitrogen technology can focus on the process combination and ammonia nitrogen recovery in the future, and the large-scale application still needs our further research and discussion. [ABSTRACT FROM AUTHOR]

Atmospheric gravity waves (GWs) in the mesosphere-lower thermosphere (MLT) are crucial for the understanding of general circulation. However, their dynamical characteristics are hardly retrieved due to the difficulty in the high-resolution observation of wind. Therefore, this paper uses eight years (2013–2020) of meteor radar measurements in the MLT region at Mohe station (53.5°N, 122.3°E), China, to retrieve high-temporal-resolution mesospheric wind data and further evaluate the temporal variation of GW kinetic energy. As the detected meteor trails exceed 6, the wind velocity is recalculated using the least square algorithm method, significantly increasing the temporal resolution of wind from 1 h up to 5 min. This resolution is sufficiently high for the investigation of GW kinetic energy, which exhibits a high spatial-temporal variability. For instance, it is enhanced in the winter season during the period of 0200–1400 UT and in the spring season during the period of 0800–1300 UT. The similarity between the climatological characteristics of GWs in MLT and the seasonal variation of GW total energy in the troposphere, determined from high-resolution radiosondes near to Mohe station, suggests that the meteorology in the lower atmosphere could be an important source of GWs in the MLT region. [ABSTRACT FROM AUTHOR]

The genus Monochamus within the subfamily Lamiinae is the main vector of Bursaphelenchus xylophilus , which causes pine wilt disease and induces substantial economic and ecological losses. Only three complete mitochondrial genomes of the genus Monochamus have been sequenced to date, and no comparative mitochondrial genomic studies of Lamiinae have been conducted. Here, the mitochondrial genomes of two Monochamus species, M. saltuarius and M. urussovi , were newly sequenced and annotated. The composition and order of genes in the mitochondrial genomes of Monochamus species are conserved. All transfer RNAs exhibit the typical clover-leaf secondary structure, with the exception of trnS1. Similar to other longhorn beetles, Lamiinae mitochondrial genomes have an A + T bias. All 13 protein-coding genes have experienced purifying selection, and tandem repeat sequences are abundant in the A + T-rich region. Phylogenetic analyses revealed congruent topologies among trees inferred from the five datasets, with the monophyly of Acanthocinini, Agapanthiini, Batocerini, Dorcaschematini, Pteropliini, and Saperdini receiving high support. The findings of this study enhance our understanding of mitochondrial genome evolution and will provide a basis for future studies of population genetics and phylogenetic investigations in this group. [ABSTRACT FROM AUTHOR]

Background: Medication-related osteonecrosis of the jaw (MRONJ) is a well-known severe adverse reaction of antiresorptive, antiangiogenic or targeted therapies, and usually occurs after tooth extraction. This review is aimed at determining the efficacy of any intervention of tooth extraction to reduce the risk of MRONJ in patients taking antiresorptive drugs, and present the distribution of evidence in these clinical questions. Methods: Primary studies and reviews were searched from nine databases (Medline, EMBase, Cochrane Library, Scopus, WOSCC, Inspec, KCI-KJD, SciELO and GIM) and two registers (ICTRP and ClinicalTrials.gov) to 30 November 2022. The risk of bias was assessed with the ROBIS tool in reviews, and the RoB 2 tool and ROBINS-I tool in primary studies. Data were extracted and then a meta-analysis was undertaken between primary studies where appropriate. Results: Fifteen primary studies and five reviews were included in this evidence mapping. One review was at low risk of bias, and one randomized controlled trial was at moderate risk, while the other eighteen studies were at high, serious or critical risk. Results of syntheses: (1) there was no significant risk difference found between drug holiday and drug continuation except for a subgroup in which drug continuation was supported in the reduced incidence proportion of MRONJ for over a 3-month follow-up; (2) the efficacy of the application of autologous platelet concentrates in tooth extraction was uncertain; (3) there was no significant difference found between different surgical techniques in any subgroup analysis; and (4) the risk difference with antibacterial prophylaxis versus control was −0.57, 95% CI −0.85 to −0.29. Conclusions: There is limited evidence to demonstrate that a drug holiday is unnecessary (and may in fact be potentially harmful) in dental practice. Primary closure and antibacterial prophylaxis are recommended despite limited evidences. All evidence have been graded as either of a low or very low quality, and thus further high-quality randomized controlled trials are needed to answer this clinical question. [ABSTRACT FROM AUTHOR]

Context: Isomerization processes between glucose and fructose catalyzed by four different organic ligands are investigated with quantum chemistry methods in this study. These organic ligands are the carboxylic pendant group, sulfonic pendant group, amino pendant group, and 1H-imidazole ligand. After guessing and verifying a variety of elementary reactions, transition states and energy barriers that are relevant to the optimum pathways have been confirmed. The effective barriers under the catalysis of the carboxylic pendant group, sulfonic pendant group, amino pendant group, and 1H-imidazole ligand are 97.5 kJ mol−1, 134.7 kJ mol−1, 146.7 kJ mol−1, and 167.7 kJ mol−1, respectively. Then, based on the conclusions of the non-solvation model, the effective barriers in solvents are briefly investigated. The implicit model predicts that solvents bring little improvement or setback to catalyzed reaction models. The explicit model shows that the proton transfer with the participant of water molecules can improve the catalytic performance of Lewis bases in these reactions. The detailed reaction mechanism combing and reliable reaction templates provided in this work will be useful for catalysis designs for glucose transformation to fructose. Methods: This work used the computational level of ωB97M-D3BJ/def2-SVP and the software package of ORCA 4.2. For solvent effects, energies of the gas phase were corrected by the combination of C-PCM and SMD. [ABSTRACT FROM AUTHOR]

Background: N6-methyladenosine is the most abundant eukaryotic mRNA modification and alters a wide range of cellular processes in cancer. Therefore, defining the molecular details are critical for understanding the regulatory mechanism of m6A modification. Results: We found that METTL3, a core m6A methyltransferase component, is upregulated and functions as an oncogene in cervical cancer. Mechanistically, METTL3 induces the degradation of m6A-modified transcripts of NR4A1 though YTHDF2-DDX6 pathway. In addition, NR4A1 overexpression attenuates the malignant progression through recruiting the LSD1/HDAC1/CoREST transcriptional repression complex to AKT1 promoter. Conclusions: Our findings reveal that m6A regulates cervical cancer cellular progression through manipulating NR4A1 pathway. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) regulate gene expression at the post-transcriptional level. The miRNA miR-106b-5p has been linked to epilepsy, but its specific role and mechanism of action remain unclear. This was investigated in the present study using a mouse model of pilocarpine-induced status epilepticus and an in vitro system of HT22 hippocampal cells treated with Mg2+-free solution and cocultured with BV2 microglia cells. We found that inhibiting miR-106b-5p expression promoted microglia M2 polarization, reduced the inflammatory response, and alleviated neuronal injury. These effects involved modulation of the repulsive guidance molecule A (RGMa)–Rac1–c-Jun N-terminal kinase (JNK)/p38–mitogen-activated protein kinase (MAPK) signaling axis. Our results suggest that therapeutic strategies targeting miR-106b-5p or downstream factors can be effective in preventing epileptogenesis or treating epilepsy. [ABSTRACT FROM AUTHOR]

A novel method for assembling pyrrolidine-2,4-diones from 1,5-enenitriles and acetone/acetonitrile via a cyclization/hydrolysis has been established under metal-catalyst- and base-free conditions, with Oxone as a green oxidant and H2 O as an additive at 90–110 ℃. This strategy is highlighted by cyclization/hydrolysis of alkyl cyanides, achieving direct C(sp3)–H oxidative functionalization, and giving full conversion of the substrates with excellent functional group compatibility. [ABSTRACT FROM AUTHOR]

Background: As segmentectomy had become commonly used for Non-Small Cell Lung Cancer (NSCLC) treatment, which had the advantages of radical operation, however, it remains controversial owing to procedural complexity and risk of increased complications compared with wedge resection. We evaluated operative and postoperative outcomes of simple segmentectomy compared to wedge resection in ground-glass opacity (GGO) diameter between 2 cm and 3 cm NSCLC. Methods: We retrospectively reviewed 1600 clinical GGO diameter between 2 cm and 3 cm NSCLC patients who received simple segmentectomy and wedge resection between Jan 2011 and Jan 2015. Participants were matched 1:1 on their propensity score for two groups. Clinic-pathologic, operative, and postoperative results of two groups were compared. Results: After using propensity score methods to create a matched cohort of participants with simple segmentectomy group similar to that wedge resection, there were no significant differences detected in tumor size, margin distance, histology, age, sex, preoperative comorbidities and preoperative pulmonary function. Overall complications in simple segmentectomy group were more than wedge resection group (21% vs 3%, p = 0.03). Median operative time (110.6 vs. 71.2 min; p = 0.01) and prolonged air leakage (12% vs. 3%; p = 0.02) was significantly longer in the simple segmentectomy group. There was no difference in recurrence free survival (RFS) and overall survival (OS) of 5-years between simple segmentectomy group and wedge resection group. Postoperative pulmonary function in simple segmentectomy group recovered more slowly than wedge resection group. Conclusion: Wedge resection may have comparable efficacy as simple segmentectomy for GGO diameter between 2 cm and 3 cm NSCLC, but lead to less complications, less surgical procedure and faster recovery of pulmonary function. [ABSTRACT FROM AUTHOR]

The Amaryllidaceae alkaloid (−)-galanthamine (1) is a reversible, competitive acetylcholinesterase inhibitor deployed clinically to treat the dementia associated with Alzheimer's disease. Here, we describe a six-step synthesis of this natural product from simple, readily accessible starting materials. Enantioselective 1,2-reduction, Mitsunobu coupling, Heck cyclization and diastereoselective allylic oxidation reactions are used in our approach, which provides the shortest synthetic route to compound 1 reported to date. A simple modification to the closing stages of the sequence allows equally facile access to (−)- N- norgalanthamine (2), a compound with a range of distinctive biological properties. The concise and operationally simple synthetic protocols reported here could obviate the need to manipulate naturally sourced galanthamine in the pursuit of analogues required for pharmacological studies. Abbreviated total syntheses of the title alkaloids, the first of which is used in the symptomatic treatment of Alzheimer's disease, are reported. [ABSTRACT FROM AUTHOR]

In space gravitational-wave-detection missions, inertial sensors are used as the core loads, and their acceleration noise needs to reach 3 × 10 − 15   ms − 2 / Hz at a frequency of 0.1   mHz , which corresponds to the capacitive sensing system; the capacitive sensing noise on the sensitive axis needs to reach 1   aF / Hz . Unlike traditional circuit noise evaluation, the noise in the mHz frequency band is dominated by the thermal noise and the 1 / f noise of the device, which is a challenging technical goal. In this paper, a low-frequency, high-precision resonant capacitor bridge method based on a planar transformer is used. Compared with the traditional winding transformer, the developed planar transformer has the advantages of low temperature drift and low 1 / f noise. For closed-loop measurements of capacitive sensing circuits and sensitive structures, the minimum capacitive resolution in the time domain is about 3   aF , which is far lower than the scientific measurement resolution requirement of 5.8   fF for gravitational wave detection. The capacitive sensing noise is converted to 1.095   aF / Hz in the frequency band of 10   mHz – 1   Hz . Although there is a gap between the closed-loop measurement results and the final index, the measurement environment is an experimental condition without temperature control on the ground; additionally, in China, the measurement integrity and actual measurement results of the capacitive sensing function have reached a domestic leading level. This is the realization of China's future space gravitational wave exploration. [ABSTRACT FROM AUTHOR]

Background: Evidences shows that socioeconomic status is reversely associated with the risk of morbidity and mortality for people with cardiovascular disease via pro-inflammation mechanism, but the population profile is not deeply defined on. We aimed to investigate the impact of medical insurance coverage on postoperative systemic inflammatory reaction in two kinds of disease populations undergoing distinct cardiac procedures.Methods: A total of 515 patients receiving open mitral valve procedure with high-total expense from May 2013 through May 2021 in Sichuan Provincial People's Hospital were retrospectively collected and stratified according to medical insurance reimbursement: low coverage with high out-pocket (< 30%), medium coverage (≤ 60%, but ≥ 30%), and high coverage (> 60%). Another 118 cases undergoing atrium septum defect (ASD) or patent foramen ovale (PFO) occlusion and taking on consistent low-total expense and low-coverage (< 30%) were also classified according to their insured conditions. The postoperative systemic inflammatory response indexes were high sensitivity C-reactive protein (hs-CRP) and the neutrophil-lymphocyte ratio (NLR).Results: Low insurance reimbursement population undergoing open mitral valve procedure had a higher level of hs-CRP and NLR but not troponin I protein or lactate within 48 h postoperatively, and higher thoracic drainage, longer ventilation use and stay in intensive care unit. No significant difference in inflammatory indexes existed among diverse medical insurance coverage in population undergoing ASD/PFO occlusion.Conclusions: Higher inflammatory reaction and weaker clinical recovery was associated with lower insurance coverage population undergoing open mitral valve procedure but not ASD/PFO interventional occlusion procedure. [ABSTRACT FROM AUTHOR]

An I2/K2S2O8 mediated multiple β‐C(sp3)−H functionalization reaction for the construction of polysubstituted furans has been established from readily available ethyl ketones and dimethyl sulfoxide. This transformation features dimethyl sulfoxide as a multipurpose precursor, acting as the precursor of the oxygen, methyl, and sulfur methyl units. Six new chemical bonds, involving two C−C, two C−O, and one C−S bonds were formed sequentially during the intermolecular oxidative annulation process. [ABSTRACT FROM AUTHOR]

In this paper, we propose an efficient method for robust and accurate 3D self-portraits using a single RGBD camera. Our method can generate detailed and realistic 3D self-portraits in seconds and shows the ability to handle subjects wearing extremely loose clothes. To achieve highly efficient and robust reconstruction, we propose PIFusion, which combines learning-based 3D recovery with volumetric non-rigid fusion to generate accurate sparse partial scans of the subject. Meanwhile, a non-rigid volumetric deformation method is proposed to continuously refine the learned shape prior. Moreover, a lightweight bundle adjustment algorithm is proposed to guarantee that all the partial scans can not only “loop” with each other but also remain consistent with the selected live key observations. Finally, to further generate realistic portraits, we propose non-rigid texture optimization to improve the texture quality. Additionally, we also contribute a benchmark for single-view 3D self-portrait reconstruction, an evaluation dataset that contains 10 single-view RGBD sequences of a self-rotating performer wearing various clothes and the corresponding ground-truth 3D models in the first frame of each sequence. The results and experiments based on this dataset show that the proposed method outperforms state-of-the-art methods on accuracy, efficiency, and generality. [ABSTRACT FROM AUTHOR]

In this study, we employ three types of satellite data from two different limb sounders: the FORMOSAT-3/COSMIC (F3/C) radio occultation (RO) technique and the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument to study the vertical coupling of the 16-09-2015 Chile tsunami-induced perturbations from the stratosphere to the ionosphere. All three types of datasets, including temperature profiles from 10 to 55 km and 16 to 107 km, and electron density profiles from 120 to 550 km, recognized perturbations of different scales at different heights after the Chile tsunami. The vertical scales identified by the wavelet analysis are from 1–2 km, 5–9 km, and 25–50 km in the stratosphere, mesosphere, and ionosphere, respectively. Meanwhile, as a comparison and validation of the reliability, we also revisited the 11-03-2011 Tohoku earthquake/tsunami-related perturbations from the stratosphere to the ionosphere using the same data. It is believed that the two tsunamis both disturbed the whole atmosphere space, and the scale of these signals gradually increases with the increase in altitude but decreases with time. In addition, the tsunami-related ionospheric gravity wavefronts are examined by the F3/C observations. Another interesting point is that the temperature perturbations recorded by the SABER from 70–100 km altitude are found to arrive earlier than the 2015 tsunami wavefront. The findings in this study suggest that the limb-sounding technique is a useful instrument for detecting the tsunami-coupling gravity wave and benefits the tsunami warning system. [ABSTRACT FROM AUTHOR]

With the development of industrialization and urbanization, the consumption and pollution of water resources are becoming more and more serious. Water quality monitoring is an extremely important technical means to protect water resources. However, the current popular water quality monitoring methods have their shortcomings, such as a low signal-to-noise ratio of satellites, poor time continuity of unmanned aerial vehicles, and frequent maintenance of in situ underwater probes. A non-contact near-surface system that can continuously monitor water quality fluctuation is urgently needed. This study proposes an automatic near-surface water quality monitoring system, which can complete the physical equipment construction, data collection, and processing of the application scenario, prove the feasibility of the self-developed equipment and methods and obtain high-performance retrieval results of four water quality parameters, namely chemical oxygen demand (COD), turbidity, ammoniacal nitrogen (NH3-N), and dissolved oxygen (DO). For each water quality parameter, fourteen machine learning algorithms were compared and evaluated with five assessment indexes. Because the ensemble learning models combine the prediction results of multiple basic learners, they have higher robustness in the prediction of water quality parameters. The optimal determination coefficients ( R 2 ) of COD, turbidity, NH3-N, and DO in the test dataset are 0.92, 0.98, 0.95, and 0.91, respectively. The results show the superiority of near-surface remote sensing, which has potential application value in inland, coastal, and various water bodies in the future. [ABSTRACT FROM AUTHOR]

Background: Violent behavior in patients with schizophrenia (SCZ) is a major social problem. The early identification of SCZ patients with violence can facilitate implementation of targeted intervention. Methods: A total of 57 male SCZ patients were recruited into this study. The general linear model was utilized to compare differences in structural magnetic resonance imaging (sMRI) including gray matter volume, cortical surface area, and cortical thickness between 30 SCZ patients who had exhibited violence and 27 SCZ patients without a history of violence. Based on machine learning algorithms, the different sMRI features between groups were integrated into the models for prediction of violence in SCZ patients. Results: After controlling for the whole brain volume and age, the general linear model showed significant reductions in right bankssts thickness, inferior parietal thickness as well as left frontal pole volume in the patients with SCZ and violence relative to those without violence. Among seven machine learning algorithms, Support Vector Machine (SVM) have better performance in differentiating patients with violence from those without violence, with its balanced accuracy and area under curve (AUC) reaching 0.8231 and 0.841, respectively. Conclusions: Patients with SCZ who had a history of violence displayed reduced cortical thickness and volume in several brain regions. Based on machine learning algorithms, structural MRI features are useful to improve predictive ability of SCZ patients at particular risk of violence. [ABSTRACT FROM AUTHOR]

Hydrogen sulfide (H2S) removal from various industrial gases is crucial because it can cause huge damage to humans, the environment, and industrial production. Zeolite possesses huge specific surface area and well-developed pore structure, making it a promising adsorbent for H2S removal. This review attempts to comprehensively compile the current studies in the literature on H2S removal in gas purification processes using zeolites, including experimental and simulation studies, mechanism theory, and practical applications. Si/Al ratio, cations of zeolite, industrial gas composition and operating conditions, and H2S diffusion in zeolites affect desulfurization performance. However, further efforts are still needed to figure out the influence rules of the factors above and H2S removal mechanisms. Based on an extensive compilation of literature, we attempt to shed light on new perspectives for further research in the future. [ABSTRACT FROM AUTHOR]

The stated skein algebra of a punctured bordered surface (or equivalently, a marked surface) is a generalization of the well-known Kauffman bracket skein algebra of unmarked surfaces and can be considered as an extension of the quantum special linear group O q 2 (S L 2) from a bigon to general surfaces. We show that the stated skein algebra of a punctured bordered surface with non-empty boundary can be embedded into quantum tori in two different ways. The first embedding can be considered as a quantization of the map expressing the trace of a closed curve in terms of the shear coordinates of the enhanced Teichmüller space, and is a lift of Bonahon-Wong's quantum trace map. The second embedding can be considered as a quantization of the map expressing the trace of a closed curve in terms of the lambda length coordinates of the decorated Teichmüller space, and is an extension of Muller's quantum trace map. We explain the relation between the two quantum trace maps. We also show that the quantum cluster algebra of Muller is equal to a reduced version of the stated skein algebra. As applications we show that the stated skein algebra is an orderly finitely generated Noetherian domain and calculate its Gelfand-Kirillov dimension. [ABSTRACT FROM AUTHOR]

Underfloor air distribution (UFAD) systems are increasingly used for their advantages in improving energy savings, indoor air quality, and thermal comfort. In UFAD systems, an underfloor plenum delivers conditioned air to the air supply diffusers. The distribution of internal air velocity and static pressure in plenums determines the uniformity of the airflow to the occupied zones. As a result, the plenum has a detrimental effect on the characteristics of the supply air and, thus, the resulting indoor air quality and thermal comfort. Nevertheless, most existing studies on underfloor plenums focused on small-scale plenums with a single internal air duct. Large plenums and multiple air ducts in UFAD equipped in large premises are underexplored. In this study, a circular underfloor plenum with a large scale (radius of 15 m, height difference of 0.9−2.9 m) and 503 under-seat diffusers in a conference room was studied using computational fluid dynamics (CFD) simulation (ANSYS Fluent (16.0)). The distributions of airflow velocity and static pressure inside the plenum were analyzed and compared to one concentrated air supply mode and three uniform air supply modes. Based on the air velocity at the center of under-seat diffusers, the outgoing airflow uniformity from the diffusers under four cases was evaluated by the index of air velocity uniformity. The results showed that the multiple supply ducts with bottom air outlets yielded the best uniformity of supply air. The findings of this paper are expected to provide a technical basis for realizing the optimal design of the UFAD system in terms of uniformity of supply air. [ABSTRACT FROM AUTHOR]

In this paper, the mechanism of the rotor–stator interaction in a centrifugal pump with guide vanes is studied numerically and theoretically. The dynamic mode decomposition method is employed to decouple and reconstruct the unsteady flow. A diametrical mode theory suitable for centrifugal pumps with guided vanes is proposed to determine the source of harmonics with higher amplitudes quickly. The results show that the dominant frequencies of the pressure pulsation in the volute and guide vanes are the blade passing frequency and its harmonic frequencies, and the corresponding flow structure is stable and has higher modal energy. The rotor–stator interaction effect around the impeller outlet is most pronounced. The potential flow effect works on the impeller and guide vanes but decays rapidly. The pressure pulsation caused by the wake effect propagates downstream and persists for long distances, which is the main reason for forming the modal pressure field in the volute. The modal reconstruction can reproduce the dynamic evolution process of the pressure field at the characteristic frequencies. The propagation characteristics of the modal pressure field in the volute can be accurately predicted by theoretical analysis. This research can provide an essential reference for fault diagnosis and vibration control of the centrifugal pump. [ABSTRACT FROM AUTHOR]

Background: The number of metastatic axillary lymph nodes (ALNs) play a crucial role in the staging, prognosis and therapy of patients with breast cancer. Purpose: To predict the number of metastatic ALNs in breast cancer via radiomics. Material and Methods: We enrolled 197 patients with breast cancer who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). A total of 3386 radiomic features were extracted from the early- and delayed-phase subtraction images. To classify the number of metastatic ALNs, logistic regression was used to develop a radiomic signature and nomogram. Results: The radiomic signature were constructed to distinguish the N0 group from the N+ (metastatic ALNs ≥ 1) group, which yielded area under the curve (AUC) values of 0.82 and 0.81 in the training and test group, respectively. Based on the radiomic signature and BI-RADS category, a nomogram was further developed and showed excellent predictive performance with AUC values of 0.85 and 0.89 in the training and test groups, respectively. Another radiomic signature was constructed to distinguish the N1 (1–3 ALNs) group from the N2–3 (≥4 metastatic ALNs) group and showed encouraging performance with AUC values of 0.94 and 0.84 in training and test group, respectively. Conclusions: We developed a nomogram and a radiomic signature that can be used to predict ALN metastasis and distinguish the N1 from the N2-3 group. Both nomogram and radiomic signature may be potential tools to assist clinicians in assessing ALN metastasis in patients with breast cancer. [ABSTRACT FROM AUTHOR]

As the current mainstream method for electricity theft detection, the data-driven detection model's performance noticeably deteriorates in new regions due to variances in electricity consumption characteristics. Moreover, owing to the lack of theft labels in new regions without on-site inspections, training a high-accuracy theft detection model becomes challenging. To address these issues, this study proposes a novel two-stage generalizable approach for electricity theft detection in new regions. In this approach, Stage 1 presents an adaptation method based on Deep Subdomain Adaptation Network (DSAN). This stage precisely aligns electricity consumption features between different regions. It transfers the characteristics of electricity consumption curves from the established region to the unlabeled new region, successfully adapting the model to the latter. Next, in Stage 2, an enhancement method based on Core-Set Active Learning (CSAL) is proposed to select the representative electricity consumption samples in the new region for fine-tuning. At the early stage of on-site inspections, Stage 2 rapidly and stably enhances the model's performance within limited costs, providing reliable guidance for regular on-site inspections. Stage 1 innovatively transfers a lot of learned features for the theft detection model, and Stage 2 further learns new regions' representative samples combined with inspections for the first time. They complement each other in terms of rich information on electricity consumption behaviors and new regions' electricity consumption characteristics. Finally, experiments on real-world datasets in China demonstrate the superiority of our proposed approach. The results show its high detection performance and rapid enhancement in unlabeled new regions, providing strong support for anti-electricity theft work. • A novel two-stage generalizable approach for electricity theft detection in new regions is proposed. • A precise adaptation method for electricity theft detection in unlabeled new regions is presented. • A rapid enhancement method during the early stage of on-site inspections in new regions is provided. • The effectiveness and superiority are verified on two real-world electricity datasets. [ABSTRACT FROM AUTHOR]

[Display omitted] • An overview of MOF-derived materials for electrocatalytic and photocatalytic CO 2 reduction is presented. • The relationship between the morphology, electronic structure of MOF-derived materials and their performances of electrocatalytic and photocatalytic CO 2 reduction are explored. • The challenges and opportunities of MOF-derived materials for electrocatalytic and photocatalytic CO 2 reduction are outlined. The extensive combustion of fossil fuels along with uncontrolled release of carbon dioxide (CO 2) has led to severe environmental contamination and global greenhouse effects. Carbon neutrality and low-carbon development are urgent demands for the enduring progress of human society. The utilization of electrocatalytic and photocatalytic reduction reaction to convert CO 2 into valuable chemicals is viewed as a hopeful approach for addressing environmental issues and energy crises. Metal-organic frameworks (MOFs) are discovered to have extensive applications in the areas of electrocatalysis and photocatalysis because of their high porosity, versatile compositions and structural tunability. With the help of designed MOF structures and specific synthesis methods, it is convenient and targeted to regulate the morphologies and electronic structures of MOF-derived materials with higher stability, further affecting their catalytic performance towards CO 2 reduction. In order to enhance catalytic performance to meet application requirements, it is essential to investigate the relationship between the morphologies, electronic structures of MOF-derived materials and their performances. In this review, to reveal the reaction mechanisms and provide theoretical support for catalyst design, the fundamentals of CO 2 reduction through electrocatalytic and photocatalytic pathways are discussed. Subsequently, an overview of the developments in MOF-derived materials for electrocatalytic and photocatalytic CO 2 reduction is presented, focusing on different optimization strategies such as morphology control and electronic modification. Finally, we outline the difficulties and opportunities for advancing MOF-derived materials in electrocatalytic and photocatalytic CO 2 reduction, along with the strategies for developing electrocatalysts and photocatalysts with excellent performance. [ABSTRACT FROM AUTHOR]

Optimizing the semiconductor-metal interaction is the key to developing metal single-atom cocatalysts with 100 % metal atom utilization and unique electronic properties. Metal atom sites are exclusively coordinated with semiconductor, featuring a chemical-bond-driven tunable interaction. Here vacancy defect-rich ZnO nanorods (NRs) are fabricated by a facile hydrothermal approach. Au nanoparticles (NPs) are preferentially anchored on surface zinc vacancy sites of ZnO NRs in an ultra-low concentration (10−4 mol/L) of HAuCL 4 solution. The Au/ZnO nanohybrids exhibit an excellent photocatalytic activity toward removal of Rhodamine B and levofloxacin. Combining ferromagnetism and valence-band XPS spectra analysis, it is demonstrated that the strong interaction of surface vacancy defects in ZnO and Au generates a distinct upshift of the valence band edge, resulting from the antibonding interaction between O 2p and Au 5d orbitals which significantly weakens the Au–O bonds. This facilitates the release of the lattice oxygen and thus generates more oxygen vacancies. The remarkable photoactivity of defective Au/ZnO is due to the synergistic interaction between the intrinsic oxygen vacancy and Au. Optimizing the hybridization of transition metal d and O 2p states at the atomic scale can induce more active-sites, improve atomic utilization efficiency and thus provide a new approach for enhancing photoactivity. • ZnO nanorods with vacancy defects were fabricated. • Au nanoparticles were anchored on surface zinc vacancy sites of ZnO nanorods. • Defective Au/ZnO achieved photocatalytic removal of rhodamine B and levofloxacin. • The Au–O antibonding orbital interactions enhance the photocatalytic activity. [ABSTRACT FROM AUTHOR]

Objectives: To establish normative values and identify potential factors influencing pancreatic iodine uptake using dual-energy CT (DECT).This retrospective study included participants without pancreatic diseases undergoing DECT at two institutions with different platforms. Their protocols both included arterial phase (AP), portal venous phase (PP), and equilibrium phase (EP), defined as 35 s–40 s, 60 s–70 s, and 150 s–180 s after injection of contrast agent, respectively. Both iodine concentration (IC) and normalised IC (NIC) were measured. Demographic features, local measurements of the pancreas and visceral fat area (VFA) were considered as potential factors influencing iodine uptake using multivariate linear regression analyses.A total of 562 participants (median age 58 years [interquartile range: 47–67], with 282 men) were evaluated. The mean IC differed significantly between two institutions (all p < 0.001) across three contrast-enhanced phases, while the mean NIC showed no significant differences (all p > 0.05). The mean values of NIC were 0.22 at AP, 0.43 at PP and 0.45 at EP. NICAP was independently affected by VFA (β = 0.362, p < 0.001), smoking (β = −0.240, p = 0.001), and type-II diabetes (β = −0.449, p < 0.001); NICPP by VFA (β = −0.301, p = 0.017) and smoking (β = −0.291, p < 0.001); and NICEP by smoking (β = −0.154, p = 0.10) and alcohol consumption (β = −0.350, p < 0.001) with statistical power values over 0.81.NIC values were consistent across institutions. Abdominal obesity, smoking, alcohol consumption, and diabetes are independent factors influencing pancreatic iodine uptake.This study has provided reference normative values, influential factors and effective normalisation methods of pancreatic iodine uptake in multiphase dual-energy CT for future studies in this area as a new biological marker.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.Materials and methods: To establish normative values and identify potential factors influencing pancreatic iodine uptake using dual-energy CT (DECT).This retrospective study included participants without pancreatic diseases undergoing DECT at two institutions with different platforms. Their protocols both included arterial phase (AP), portal venous phase (PP), and equilibrium phase (EP), defined as 35 s–40 s, 60 s–70 s, and 150 s–180 s after injection of contrast agent, respectively. Both iodine concentration (IC) and normalised IC (NIC) were measured. Demographic features, local measurements of the pancreas and visceral fat area (VFA) were considered as potential factors influencing iodine uptake using multivariate linear regression analyses.A total of 562 participants (median age 58 years [interquartile range: 47–67], with 282 men) were evaluated. The mean IC differed significantly between two institutions (all p < 0.001) across three contrast-enhanced phases, while the mean NIC showed no significant differences (all p > 0.05). The mean values of NIC were 0.22 at AP, 0.43 at PP and 0.45 at EP. NICAP was independently affected by VFA (β = 0.362, p < 0.001), smoking (β = −0.240, p = 0.001), and type-II diabetes (β = −0.449, p < 0.001); NICPP by VFA (β = −0.301, p = 0.017) and smoking (β = −0.291, p < 0.001); and NICEP by smoking (β = −0.154, p = 0.10) and alcohol consumption (β = −0.350, p < 0.001) with statistical power values over 0.81.NIC values were consistent across institutions. Abdominal obesity, smoking, alcohol consumption, and diabetes are independent factors influencing pancreatic iodine uptake.This study has provided reference normative values, influential factors and effective normalisation methods of pancreatic iodine uptake in multiphase dual-energy CT for future studies in this area as a new biological marker.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.Results: To establish normative values and identify potential factors influencing pancreatic iodine uptake using dual-energy CT (DECT).This retrospective study included participants without pancreatic diseases undergoing DECT at two institutions with different platforms. Their protocols both included arterial phase (AP), portal venous phase (PP), and equilibrium phase (EP), defined as 35 s–40 s, 60 s–70 s, and 150 s–180 s after injection of contrast agent, respectively. Both iodine concentration (IC) and normalised IC (NIC) were measured. Demographic features, local measurements of the pancreas and visceral fat area (VFA) were considered as potential factors influencing iodine uptake using multivariate linear regression analyses.A total of 562 participants (median age 58 years [interquartile range: 47–67], with 282 men) were evaluated. The mean IC differed significantly between two institutions (all p < 0.001) across three contrast-enhanced phases, while the mean NIC showed no significant differences (all p > 0.05). The mean values of NIC were 0.22 at AP, 0.43 at PP and 0.45 at EP. NICAP was independently affected by VFA (β = 0.362, p < 0.001), smoking (β = −0.240, p = 0.001), and type-II diabetes (β = −0.449, p < 0.001); NICPP by VFA (β = −0.301, p = 0.017) and smoking (β = −0.291, p < 0.001); and NICEP by smoking (β = −0.154, p = 0.10) and alcohol consumption (β = −0.350, p < 0.001) with statistical power values over 0.81.NIC values were consistent across institutions. Abdominal obesity, smoking, alcohol consumption, and diabetes are independent factors influencing pancreatic iodine uptake.This study has provided reference normative values, influential factors and effective normalisation methods of pancreatic iodine uptake in multiphase dual-energy CT for future studies in this area as a new biological marker.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.Conclusion: To establish normative values and identify potential factors influencing pancreatic iodine uptake using dual-energy CT (DECT).This retrospective study included participants without pancreatic diseases undergoing DECT at two institutions with different platforms. Their protocols both included arterial phase (AP), portal venous phase (PP), and equilibrium phase (EP), defined as 35 s–40 s, 60 s–70 s, and 150 s–180 s after injection of contrast agent, respectively. Both iodine concentration (IC) and normalised IC (NIC) were measured. Demographic features, local measurements of the pancreas and visceral fat area (VFA) were considered as potential factors influencing iodine uptake using multivariate linear regression analyses.A total of 562 participants (median age 58 years [interquartile range: 47–67], with 282 men) were evaluated. The mean IC differed significantly between two institutions (all p < 0.001) across three contrast-enhanced phases, while the mean NIC showed no significant differences (all p > 0.05). The mean values of NIC were 0.22 at AP, 0.43 at PP and 0.45 at EP. NICAP was independently affected by VFA (β = 0.362, p < 0.001), smoking (β = −0.240, p = 0.001), and type-II diabetes (β = −0.449, p < 0.001); NICPP by VFA (β = −0.301, p = 0.017) and smoking (β = −0.291, p < 0.001); and NICEP by smoking (β = −0.154, p = 0.10) and alcohol consumption (β = −0.350, p < 0.001) with statistical power values over 0.81.NIC values were consistent across institutions. Abdominal obesity, smoking, alcohol consumption, and diabetes are independent factors influencing pancreatic iodine uptake.This study has provided reference normative values, influential factors and effective normalisation methods of pancreatic iodine uptake in multiphase dual-energy CT for future studies in this area as a new biological marker.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.Clinical relevance statement: To establish normative values and identify potential factors influencing pancreatic iodine uptake using dual-energy CT (DECT).This retrospective study included participants without pancreatic diseases undergoing DECT at two institutions with different platforms. Their protocols both included arterial phase (AP), portal venous phase (PP), and equilibrium phase (EP), defined as 35 s–40 s, 60 s–70 s, and 150 s–180 s after injection of contrast agent, respectively. Both iodine concentration (IC) and normalised IC (NIC) were measured. Demographic features, local measurements of the pancreas and visceral fat area (VFA) were considered as potential factors influencing iodine uptake using multivariate linear regression analyses.A total of 562 participants (median age 58 years [interquartile range: 47–67], with 282 men) were evaluated. The mean IC differed significantly between two institutions (all p < 0.001) across three contrast-enhanced phases, while the mean NIC showed no significant differences (all p > 0.05). The mean values of NIC were 0.22 at AP, 0.43 at PP and 0.45 at EP. NICAP was independently affected by VFA (β = 0.362, p < 0.001), smoking (β = −0.240, p = 0.001), and type-II diabetes (β = −0.449, p < 0.001); NICPP by VFA (β = −0.301, p = 0.017) and smoking (β = −0.291, p < 0.001); and NICEP by smoking (β = −0.154, p = 0.10) and alcohol consumption (β = −0.350, p < 0.001) with statistical power values over 0.81.NIC values were consistent across institutions. Abdominal obesity, smoking, alcohol consumption, and diabetes are independent factors influencing pancreatic iodine uptake.This study has provided reference normative values, influential factors and effective normalisation methods of pancreatic iodine uptake in multiphase dual-energy CT for future studies in this area as a new biological marker.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.Key Points: To establish normative values and identify potential factors influencing pancreatic iodine uptake using dual-energy CT (DECT).This retrospective study included participants without pancreatic diseases undergoing DECT at two institutions with different platforms. Their protocols both included arterial phase (AP), portal venous phase (PP), and equilibrium phase (EP), defined as 35 s–40 s, 60 s–70 s, and 150 s–180 s after injection of contrast agent, respectively. Both iodine concentration (IC) and normalised IC (NIC) were measured. Demographic features, local measurements of the pancreas and visceral fat area (VFA) were considered as potential factors influencing iodine uptake using multivariate linear regression analyses.A total of 562 participants (median age 58 years [interquartile range: 47–67], with 282 men) were evaluated. The mean IC differed significantly between two institutions (all p < 0.001) across three contrast-enhanced phases, while the mean NIC showed no significant differences (all p > 0.05). The mean values of NIC were 0.22 at AP, 0.43 at PP and 0.45 at EP. NICAP was independently affected by VFA (β = 0.362, p < 0.001), smoking (β = −0.240, p = 0.001), and type-II diabetes (β = −0.449, p < 0.001); NICPP by VFA (β = −0.301, p = 0.017) and smoking (β = −0.291, p < 0.001); and NICEP by smoking (β = −0.154, p = 0.10) and alcohol consumption (β = −0.350, p < 0.001) with statistical power values over 0.81.NIC values were consistent across institutions. Abdominal obesity, smoking, alcohol consumption, and diabetes are independent factors influencing pancreatic iodine uptake.This study has provided reference normative values, influential factors and effective normalisation methods of pancreatic iodine uptake in multiphase dual-energy CT for future studies in this area as a new biological marker.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies.Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake.Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions. [ABSTRACT FROM AUTHOR]

Advance care planning is typically initiated during the last six months of a patient's life. However, due to the progressive decline in the decision-making process in individuals with dementia, their involvement in advance care planning is limited to the early stages of the disease. Currently, there is no consensus on the optimal timing for initiating advance care planning for people with dementia, and a comprehensive review of the literature addressing this matter is lacking. To explore the experiences and perspectives of people with dementia, their family caregivers, and health care professionals with regard to the optimal timing for initiating advance care planning. A meta-synthesis was conducted. The following eight electronic databases were searched: PubMed, Embase, Web of Science, Cochrane Library, CINAHL and CNKI, WanFang and Vip. This review uses thematic synthesis to systematically synthesize qualitative evidence and report findings according to The Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) and the Joanna Briggs Institute Manual for Evidence Synthesis. Study selection and data extraction were conducted independently by two researchers, and quality was evaluated using the Joanna Briggs Institute's Qualitative Research Standard Assessment tool. Twenty-one studies were selected for this review. This review involved an overarching theme: The utilization of pivotal elements to transition from delayed initiation to comprehensive implementation. Three themes emerge, including the prerequisites for initiating advance care planning, not ready to start advance care planning and struggling along narrow roads. For health care professionals, the selection of an opportune moment to initiate advance care planning for people with dementia is not only a challenge but also a crucial prerequisite for the successful implementation of advance care planning. Health care professionals' experience, attitude toward advance care planning, trust relationship with patients, cultural differences among people with dementia and their caregivers, and economic disparities all influence health care professionals' judgment of the timing for initiating advance care planning. Determining the optimal timing for initiating advance care planning is a complex process that requires a comprehensive consideration of the realities faced by health care professionals, people with dementia and their caregivers. Therefore, it is imperative to provide relevant training to health care professionals to ensure the successful implementation of advance care planning. [ABSTRACT FROM AUTHOR]

Objectives: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer’s axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer.Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model’s performance against sonographer’s diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection.In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer’s diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer’s diagnostic ability, increasing accuracy from 71.9% to 79.2%.The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery.Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer’s axillary diagnosis.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.Methods: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer’s axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer.Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model’s performance against sonographer’s diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection.In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer’s diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer’s diagnostic ability, increasing accuracy from 71.9% to 79.2%.The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery.Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer’s axillary diagnosis.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.Results: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer’s axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer.Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model’s performance against sonographer’s diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection.In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer’s diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer’s diagnostic ability, increasing accuracy from 71.9% to 79.2%.The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery.Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer’s axillary diagnosis.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.Conclusion: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer’s axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer.Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model’s performance against sonographer’s diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection.In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer’s diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer’s diagnostic ability, increasing accuracy from 71.9% to 79.2%.The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery.Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer’s axillary diagnosis.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.Clinical relevance statement: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer’s axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer.Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model’s performance against sonographer’s diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection.In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer’s diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer’s diagnostic ability, increasing accuracy from 71.9% to 79.2%.The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery.Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer’s axillary diagnosis.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.Key Points: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer’s axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer.Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model’s performance against sonographer’s diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection.In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer’s diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer’s diagnostic ability, increasing accuracy from 71.9% to 79.2%.The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery.Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer’s axillary diagnosis.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making. [ABSTRACT FROM AUTHOR]

With the proposal of the carbon peaking and neutrality targets, non-intrusive load monitoring (NILM) is crucial for energy saving and demand response. How to achieve accurate load identification (LI) is the key to the application of NILM. However, it faces a major challenge: how to identify loads accurately from massive incremental unlabeled data streams. To tackle this challenge, we propose a novel method that combines class incremental learning (CIL) and semi-supervised learning (SSL). Our method prevents catastrophic forgetting by preserving samples, distilling knowledge and aligning weights in incremental tasks. Moreover, our method leverages a semi-supervised learning structure called the Temporal Ensembling to exploit unlabeled data and overcome the semi-supervised problem in incremental learning. We test our method on PLAID and WHITED public datasets and demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

Understanding the temperature fields/profiles in aluminum dust flames is critical to the design of aluminum-based sustainable fuels and the development of aluminum combustion simulation tools. Although emission spectroscopy has been applied in aluminum flames, the signals in most works were integrated along the recording path and over the whole flame and, therefore, the measurements could not provide information of the flame spatial structure. In addition, the details of the diagnostic method were scarcely introduced. This work develops a dual-range emission spectroscopy diagnostic system for 1D measurements of the liquid temperature and the flame temperature of aluminum flames. The important aspects for diagnostics, such as the instrument specifications, signal acquisition strategy, data processing, accuracy and precision, are introduced and quantified in detail. The continuous spectrum from the liquid phase of Al (L) and/or Al 2 O 3(L) , rovibrational AlO spectrum from the micro-diffusion flame, and 2D flame luminosity are recorded simultaneously. Based on Planck's law, a linear fitting method is implemented to derive a continuous spectrum temperature. A nonlinear minimization framework based on the stick spectrum is introduced to fit the AlO spectra and derive a AlO temperature. The accuracy and precision are quantified by a comparison of the average temperatures against the equilibrium temperatures and the standard deviations. The effectiveness of this technique for temperature measurements of aluminum dust flames is verified by the agreement of the continuous spectrum temperature and the AlO temperature in the post-flame region. The 1D distribution of the continuous spectrum temperature indicates the boiling of Al and the dissociation/condensation of Al 2 O 3 from upstream to downstream through the flame. The 1D temperature distributions also present a lag of the continuous spectrum temperature compared to the AlO temperature, indicating that the continuous spectrum temperature is dominated by the Al fuel droplets and the Al 2 O 3 caps, instead of the Al 2 O 3 nanometric droplets. [ABSTRACT FROM AUTHOR]

Background. Cardiovascular disease is a common disease with high prevalence, disability, and mortality. Exercise therapy can improve cardiac functional reserve and life quality of patients, but the benefits of different exercise intensities for cardiovascular patients are still controversial. In this study, literature search and meta-analysis were used to explore the effect of 2 intensities of exercise on the rehabilitation effect of cardiovascular patients. Methods. We searched Embase, Wiley online library, PubMed, Science Direct, and Clinicaltrials to look for randomized controlled trial (RCT) studies of high-intensity interval training (HIIT) versus moderate continuous training (MCT). After screening the inclusion criteria for the literature and assessing the risk of bias, a software analysis was performed using the R language toolkit to obtain forest plots and funnel maps. Results. 10 articles were included in this study into the quantitative analysis, and 520 patients participated in the study; meta-analysis results showed that after HIIT intervention, the VO2 peak index of patients was higher than that of the MCT group (MD = 1.39 , 95% CI (0.10, 2.68), Z = 2.12 , P = 0.0344), the peak heart rate HR peak was higher than that of the MCT training (MD = 7.71 , 95% CI (5.12, 10.30), Z = 5.84 , P < 0.0001), the respiratory exchange rate (maximum RER) was higher than that of the MCT training (MD = 0.02 , 95% CI (0.00, 0.04), Z = 2.36 , P = 0.0184), and the quality of life was higher than that of the MCT training (MD = 0.39 , 95% CI (0.07, 0.71), Z = 2.40 , P = 0.0165). Discussion. Compared with moderate continuous training, high intensity interval training is more conducive to improve the cardiopulmonary function of cardiovascular patients and improve their physical life quality. [ABSTRACT FROM AUTHOR]

The study on the flow behaviors of oil and water two phases in porous media and their influencing factor is very important to adjust the porous carbonate reservoir development strategy and enhance the oil recovery. Based on the CT (computed tomography) scanning of real carbonate reservoir core sample, the micropore structure was reconstructed, and the effects of different factors (injection rate, oil-to-water viscosity ratio, and contact angle) and secondary development methods (higher injection rate and water displacement direction optimization) on the flow behavior of oil and water two phases were explored by numerical simulation in this paper. It is found from the study that the pores in the porous carbonate reservoirs have good structural connectivity. During the displacement process, the oil-water interface mainly resides at the pore throat junction with a large change of pore size, and the Haines jumps exist in the oil-water movement; the areal sweep efficiency of the water phase is jointly affected by the viscosity effect, interfacial tension, pore structure, and injection rate. Under the minimum injection rate and oil-to-water viscosity ratio, the maximum oil recovery can be obtained, and the oil recovery is 52.62% and 57.01%, respectively. The recovery efficiency and swept area are better in a water-wet system than oil-wet system. During the secondary development, the remaining oil is hardly displaced even with the injection rate increased by a factor of 50, and it shows improvement after 250 times of initial injection rate. Changing the position of water inlet and the produced fluid outlet results in better recovery since the remaining oil near the new inlet and outlet can be effectively produced. [ABSTRACT FROM AUTHOR]

The development of multi‐pixel receivers on the millimetre‐wave and terahertz bands demands on the integration of key waveguide devices. In this paper, two waveguide bandpass filters operating at the W‐band are developed based on the layered integration architecture. First, the traditional fourth‐order waveguide filter is perpendicularly folded to realise dual‐layered arrangement, meanwhile a cross‐coupling between layers is introduced to obtain the standard quasi‐elliptical response. Then, two layered approaches including 5‐layer and 3‐layer are proposed to fabricate filter prototypes integrating with 90° curved waveguides based on the computer numerical control (CNC) technology. Finally, the measurement exhibits that both filters have achieved the 3 dB fractional bandwidth of 14.8% from 85 to 98.5 GHz, low insertion loss of 0.6 dB (5‐layer) and 0.4 dB (3‐layer), the return loss with better than 20 dB, as well as two obvious transmission zeros in the out‐of‐band. Besides, the layering error analysis and performance comparison of both filters are discussed, which verify the feasibility of the layered integration for CNC‐machined W‐band waveguide filters. [ABSTRACT FROM AUTHOR]

The void fraction of composite tape winding products is one of the key characteristic parameters affecting the quality and mechanical properties of composite products. In this paper, the leading cause of void formation in the winding process is analyzed, and the critical winding process variables, including winding velocity, consolidation force, and roller temperature, which influence the void content of the products are proposed. Then, the thermal model, inter-laminar, and intra-laminar void content model for prepreg tape winding process are developed aim at control products void content. The effect rule of multi-parameter on void content is discussed. The accuracy of the theoretical model is also validated by comparing predicted results with experimental data. Moreover, based on the predicted model, the multidimensional mapping relationships and three-dimension (3D) process window for tape winding is obtained in order to provide the theoretical basis for control the void content of tape winding products. The model predictions and experimental results show that a combination of high winding temperature, strong pressure and low winding velocity can help to reduce the final void content of winding products. Using the combination of process parameters in this 3D process window for tape winding, the void content of the product can be controlled within 1%. [ABSTRACT FROM AUTHOR]

The sweet potato is very sensitive to low temperature. Our previous study revealed that IbMPK3-overexpressing transgenic sweet potato (M3) plants showed stronger low-temperature stress tolerance than wild-type plants (WT). However, the mechanism of M3 plants in response to low-temperature stress is unclear. To further analyze how IbMPK3 mediates low-temperature stress in sweet potato, WT and M3 plants were exposed to low-temperature stress for 2 h and 12 h for RNA-seq analysis, whereas normal conditions were used as a control (CK). In total, 3436 and 8718 differentially expressed genes (DEGs) were identified in WT at 2 h (vs. CK) and 12 h (vs. CK) under low-temperature stress, respectively, whereas 1450 and 9291 DEGs were detected in M3 plants, respectively. Many common and unique DEGs were analyzed in WT and M3 plants. DEGs related to low temperature were involved in Ca2+ signaling, MAPK cascades, the reactive oxygen species (ROS) signaling pathway, hormone transduction pathway, encoding transcription factor families (bHLH, NAC, and WRKY), and downstream stress-related genes. Additionally, more upregulated genes were associated with the MAPK pathway in M3 plants during short-term low-temperature stress (CK vs. 2 h), and more upregulated genes were involved in secondary metabolic synthesis in M3 plants than in the WT during the long-time low-temperature stress treatment (CK vs. 12 h), such as fatty acid biosynthesis and elongation, glutathione metabolism, flavonoid biosynthesis, carotenoid biosynthesis, and zeatin biosynthesis. Moreover, the interaction proteins of IbMPK3 related to photosynthesis, or encoding CaM, NAC, and ribosomal proteins, were identified using yeast two-hybrid (Y2H). This study may provide a valuable resource for elucidating the sweet potato low-temperature stress resistance mechanism, as well as data to support molecular-assisted breeding with the IbMPK3 gene. [ABSTRACT FROM AUTHOR]

Background: The study aims to evaluate the accuracy of the generative adversarial networks (GAN) for reconstructing bony midfacial defects. Methods: According to anatomy, the bony midface was divided into five subunit structural regions and artificial defects are manually created on the corresponding CT images. GAN is trained to reconstruct artificial defects to their previous normal shape and tested. The clinical defects are reconstructed by the trained GAN, where the midspan defects were used for qualitative evaluation and the unilateral defects were used for quantitative evaluation. The cosine similarity and the mean error are used to evaluate the accuracy of reconstruction. The Mann–Whitney U test is used to detect whether reconstruction errors were consistent in artificial and unilateral clinical defects. Results: This study included 518 normal CT data, with 415 in training set and 103 in testing set, and 17 real patient data, with 2 midspan defects and 15 unilateral defects. Reconstruction of midspan clinical defects assessed by experts is acceptable. The cosine similarity in the reconstruction of artificial defects and unilateral clinical defects is 0.97 ± 0.01 and 0.96 ± 0.01, P = 0.695. The mean error in the reconstruction of artificial defects and unilateral clinical defects is 0.59 ± 0.31 mm and 0.48 ± 0.08 mm, P = 0.09. Conclusion: GAN-based virtual reconstruction technology has reached a high accuracy in testing set, and statistical tests suggest that it can achieve similar results in real patient data. This study has preliminarily solved the problem of bony midfacial defect without reference. [ABSTRACT FROM AUTHOR]

Herein, we report the development of a method for highly regio‐, stereo‐, and enantioselective B−H bond insertion reactions of α‐silylcarbenes generated from 1‐silylcyclopropenes in the presence of a chiral copper(I)/bisoxazoline catalyst for the construction of chiral γ,γ‐disubstituted allylic gem‐silylboranes, which cannot be prepared by any other known methods. This reaction is the first highly enantioselective carbene insertion reaction of α‐silylcarbenes ever to be reported. The method shows general applicability for various 3,3‐disubstituted silylcyclopropenes and exclusively affords E‐products. The novel chiral γ,γ‐disubstituted allylic gem‐silylborane products are versatile allylic bimetallic reagents with high stability and have great synthetic potential, especially for the construction of complex molecules with continuous chiral centers. [ABSTRACT FROM AUTHOR]

Herein, we report the development of a method for highly regio‐, stereo‐, and enantioselective B−H bond insertion reactions of α‐silylcarbenes generated from 1‐silylcyclopropenes in the presence of a chiral copper(I)/bisoxazoline catalyst for the construction of chiral γ,γ‐disubstituted allylic gem‐silylboranes, which cannot be prepared by any other known methods. This reaction is the first highly enantioselective carbene insertion reaction of α‐silylcarbenes ever to be reported. The method shows general applicability for various 3,3‐disubstituted silylcyclopropenes and exclusively affords E‐products. The novel chiral γ,γ‐disubstituted allylic gem‐silylborane products are versatile allylic bimetallic reagents with high stability and have great synthetic potential, especially for the construction of complex molecules with continuous chiral centers. [ABSTRACT FROM AUTHOR]