Background: The aim of this study was to investigate the risk of obstructive sleep apnea (OSA) among ankylosing spondylitis (AS) patients in a nationwide population. Methods: We conducted a nationwide cohort study between 2003 and 2013 using the Taiwan National Health Insurance Research Database. The AS cohort included 2210 patients who were newly diagnosed between 2003 and 2013. Randomly selected non-AS controls were matched at a 1:4 ratio based on age, sex and index date. The endpoint of OSA was occurrence or the end of 2013. Cumulative incidences, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated after adjusting for age, gender, comorbidities and co-medications. Multivariate analyses were performed using Cox proportional hazards model. Due to violation of the proportionality assumption, landmark analysis was conducted to explore the risk of OSA during specific follow-up periods. Results: The adjusted HR (aHR) of OSA for the AS group was 2.826 (95% C.I. = 1.727–4.625) compared to the control group. On landmark analysis, aHR was 7.919 (95% C.I. = 3.169–19.792) for AS group 0–24 months from index date, and decreased to 1.816 (95% C.I. = 0.944–3.494) at ≥ 24 months from index date. On subgroup analyses increased risks of OSA in AS group compared to the control group were found for both males and females (aHRs were 4.533 (95% C.I. = 1.441–14.262) and 2.672 (95% C.I. = 1.522–4.692) for females and males, respectively). On age stratified analysis, there was significant risk only for the 40–59 age group with aHR of 3.913 (95% C.I. = 1.890–8.102). Conclusions: A higher risk of developing OSA was found among newly diagnosed AS cohort during the 12-year follow-up period, especially within 2 years after AS index date and in the 40–59 age group.

Idiopathic scoliosis (IS) is an unexplained dysplasia of the spine that can occur at any age, with idiopathic scoliosis making up the largest proportion of the total population worldwide, approximately 2-3%. Scoliosis is not just a cosmetic defect, but the development of the spinal deformity can lead to cardiovascular and respiratory lesions, often resulting in serious health problems. Treatment of the condition usually involves major surgery, which is both a physical and financial burden for patients. In order to clarify the aetiology of IS and provide a theoretical basis for new diagnostic and treatment methods IS, it is important to use different animal models for experiments. Zebrafish is an emerging model animal with a short reproductive cycle, minimal breeding expenses, and other beneficial traits including in vitro fertilisation, in vitro development, and embryo transparency. As a result, genetic alteration and observation are simpler than with traditional model animals. This study examines the history of animal models for IS research, focuses on the benefits and drawbacks of zebrafish as an IS model and the advances it provides to IS research, and anticipates zebrafish application prospects in IS research.

Liquid biopsy is a rapidly emerging field which involves the minimal/non-invasive assessment of signature somatic mutations through analysis of circulating tumor DNA (ctDNA) shed by tumor cells in bodily fluids. The broad, unmet need for liquid biopsy lung cancer detection is the lack of multiplex platform that can detect a mutation panel of lung cancer genes using minimum amount of sample, especially for ultra-short ctDNA (usctDNA). Here we developed a non-PCR and non-NGS-based single droplet based multiplexing microsensor technology “Electric Field-Induced Released and Measurement (EFIRM) Liquid Biopsy” (m-eLB) for lung can-cer-associated usctDNA. The m-eLB provides multiplexable assessment of usctDNA within a single droplet of biofluid in only one well of micro-electrodes, as each electrode coated with dif-ferent probes for the ctDNA. In this m-eLB prototype, it demonstrates accuracy for 3 tyrosine ki-nase inhibitor related EGFR target sequences in synthetic nucleotides. The accuracy for the multi-plexing assay has an AUC of 0.98 for L858R, Ex19del, AUC of 0.94 for Ex19 deletion and AUC of 0.93 for T790M. By combining the 3 EGFR assay together, the AUC was 0.97 for the multiplexing assay.

The CuCrSn alloy is promising as high-strength and high-conductivity Cu alloy due to its relative low smelting requirement, while thus far reports on the CuCrSn alloy is still quite lacked. In this study, the microstructure and properties of Cu-0.20Cr-0.25Sn (wt%) specimens prepared under different rolling and aging combinations were comprehensively characterized, in order to reveal the effects of cold rolling and aging on the CuCrSn alloy. The results show that increasing the aging temperature from 400 ºC to 450 ºC can obviously accelerates the precipitation, and the cold rolling before aging significantly increases the initial microhardness and promotes the precipitation. Whereas, the deformation hardening will be eliminated during the aging process, making the microhardness even decrease monotonically when the aging temperature and the rolling ratio before aging are high. Performing the cold rolling after the aging can maximize the effects of precipitation strengthening and deformation strengthening, and its adverse impact on the conductivity is not serious. A tensile strength of 506.5 MPa and a conductivity of 70.33% IACS were obtained with such a treatment, only the elongation decreases. Different strength-conductivity combinations of the CuCrSn alloy can be achieved through appropriate combinations of the aging and post aging cold rolling conditions.

In this work, numerical simulations for the absorption and scattering efficiencies of spheroid core–shell nanoparticles (CSNs) were conducted and studied using the discrete-dipole approximation method. The characteristics of surface plasmon resonances (SPR) depend upon shell thickness, the compositions of the core and shell materials, and the aspect ratio of the constructed CSNs. We used different core@shell compositions, specifically Au@SiO₂, Ag@SiO₂, Au@TiO₂, Ag@TiO₂, Au@Ag, and Ag@Au, for extinction spectra analysis. We also investigated coupled resonance mode wavelengths by adjusting the composition’s layer thickness and aspect ratio. In this study, we show that the extinction efficiency of the Ag@TiO₂ core–shell nanoparticles (CSNPs) was higher than that of the others, and we examined the impact of TiO₂ shell thickness and Ag core radius on SPR peak positions. From the extinction spectra we found that the Ag@TiO₂ nanoparticle had better refractive index sensitivity and figure of merit when the aspect ratio was set to 0.3. All of the experimental results proved that the tunability of these plasmonic resonances was highly dependent on the material used, the layer thickness, and the aspect ratio of the core@shell CSNPs.

The flowering of Amorphophallus bulbifer plays an important role in its reproduction. The flowers and leaves of A. bulbifer cannot grow at the same time. However, the physiological and molecular mechanisms involved in flower bud and leaf bud formation are still unclear. In this study, the flower buds and leaf buds of A. bulbifer in the early stage of growth were used as research materials, transcriptome and metabolome analyses were carried out, and the soluble sugar and starch contents of A. bulbifer corms were determined. Transcriptome analysis revealed 5 542 differentially expressed genes (DEG) between flower buds and leaf buds, 3 107 of which were upregulated and 2 435 of which were downregulated. Enrichment analysis of the KEGG pathway showed that these differential genes were enriched mainly in the plant hormone signal transduction, DNA replication and fatty acid elongation pathways. Plant hormone signal transduction, DNA replication and fatty acid elongation pathways. A total of 5 296 significant differentially abundant metabolites were screened out by nontargeted metabolomics analysis. The differentially abundant metabolites were functionally classified in the HMDB, and 118 were successfully matched, including 17 that were highly expressed in flower buds. The differentially abundant metabolites in the flower buds were mainly enriched in pathways such as amino acid metabolism, isoquinoline alkaloid biosynthesis and pyrimidine metabolism. Targeted metabolomics analysis revealed that the contents of ABA, ZT and iPA in flower buds were significantly greater than those in leaf buds, while the opposite trend was observed for IAA. The analysis of soluble sugar and starch contents showed that the starch and soluble sugar contents in flower buds were significantly greater than those in leaf buds. The results of this study showed that flower bud development in A. bulbifer was regulated by amino acids, starch, ABA, ZT, iPA, IAA and other hormones. These findings could lead to valuable genetic resources for further study of A. bulbifer flowering and provide a deeper understanding of the molecular basis of A. bulbifer flowering.

Tight gas, a category of Deep Green Energy Resources, rely on advanced intelligent monitoring methods for their extraction. Conventional logging for reservoir evaluation relies on logging data and the manual setting of evaluation criteria to classify reservoirs. However, the complexity and heterogeneity of tight reservoirs pose challenges in accurately identifying target layers by using traditional well-logging techniques. Machine learning may hold the key to solving this problem, as it enables computers to learn without being explicitly programmed and manually added rules. Therefore, it is possible to make reservoir evaluation via using machine learning methods. In this paper, the reservoir quality index (RQI) and porous geometric parameters obtained from the optimized inversion of the spherical-tubular model are adopted to evaluate the reservoir. Then, three different machine learning approaches, the random forest (RF) algorithm, support vector machine (SVM) algorithm, and extreme gradient boosting (XGB) algorithm, are utilized for reservoir classification. The selected dataset covers more than 7,000 samples from five wells. The data from four wells are arranged as the training dataset, and the data of the remaining one well is designed as the testing dataset to calculate the prediction accuracies of different machine learning algorithms. Among them, accuracies of RF, SVM, and XGB are all higher than 90%, and XGB owns the highest result by reaching 97%. Machine learning based approaches can greatly assist reservoir prediction by implementing the well-logging data. The research highlights the application of reservoir classification with a higher prediction accuracy by combining machine learning algorithms with NMR logging based pore structure characterization, which can provide a guideline for sweet spot identification within the tight formation. This not only optimizes resource extraction but also aligns with the global shift towards clean and renewable energy sources, promoting sustainability and reducing the carbon footprint associated with conventional energy production. In summary, the fusion of machine learning and NMR logging based reservoir evaluation plays a crucial role in advancing both energy efficiency and the transition to cleaner energy sources.

Deep learning methods have been widely used in PolSAR image classification. To learn the polarimetric information, many deep learning methods expect to learn high-level semantic features from original PolSAR data. However, only original data cannot learn multiple scattering features and complex structures for extremely heterogeneous terrain objects. In addition, deep learning methods always cause edge confusion due to the high-level features. To overcome these shortages, we propose a double-channel CNN network combined with an edge-preserving MRF model(DCCNN-MRF) for PolSAR image classification. Firstly, to combine complex matrix data and multiple scattering features together, a double-channel convolution network(DCCNN) is developed, which consists of a Wishart-based complex matrix and multi-feature subnetworks. The Wishart-based complex matrix network can learn the statistical characteristics and channel correlation well, and the multi-feature network can learn high-level semantic features well. Then, a unified network framework is designed to fuse two kinds of features to enhance advantageous features and reduce redundant ones. Finally, an edge preserving MRF model is designed to combine with the DCCNN network. In the MRF model, a sketch map-based edge energy function is designed by defining adaptive weighted neighborhood for edge pixels. Experiments are conducted on four real PolSAR data sets with different sensors and bands. Experimental results demonstrate the effectiveness of the proposed DCCNN-MRF method.

Two-dimensional MXene synthesized from MAX phase ceramic has the good electrical conductivity, promising to be used as electrodes. In this study, Nb4C3Tx MXene and low-entropy (Nb0.8Ti0.05V0.05Zr0.05Ta0.05)4C3Tx MXene were prepared by etching Nb4AlC3 and (Nb0.8Ti0.05V0.05Zr0.05Ta0.05)4AlC3 ceramics in the HF acid at 60 oC. By investigating the electrochemical properties of lithium batteries, it was found that the Nb4C3Tx and (Nb0.8Ti0.05V0.05Zr0.05Ta0.05)4C3Tx could provide the specific capacities of 163.7 mAh·g-1 and 130 mAh·g-1 after 50 cycles at a current density of 0.1 A·g-1, respectively, and maintain the coulombic efficiency close to 100%, good for the utilization of electrodes in the lithium batteries.

We investigated the effect of C. psittaci and H9N2 coinfection on HD11 cells in vitro, expecting to find the potential pathogenesis of airsacculitis caused by co-infection of C. psittaci and H9N2. HD11 cells were infected with C. psittaci and/or H9N2 in a different order, and effects of the co-infection on iNOS expression and activity, NO synthesis, cell phagocytosis, and cytokines levels in HD11 cells were determined. Results showed that C. psittaci and H9N2 can significantly aggravate the mortality of HD11 cells compared to the effects of infection with one pathogen alone. In addition, infection with C. psittaci can increase the replication of H9N2 in HD11 cells, whereas decrease the iNOS level and enzyme activity as well as NO concentration of HD11 cells by H9N2 infection. We also found that C. psittaci infection alone can significantly decrease the phagocytosis of HD11 cells, compared to H9N2 infection alone. Furthermore, infection with C. psittaci can increase the mRNA expressions of type Th2 cytokines IL-6 and IL-10 of HD11 cells by H9N2 infection. All the above data indicated that primary C. psittaci infection is able to aggravate H9N2 invasion by down-regulating functions of HD11 cells

The utilization of optical antennas for active control of far-field radiation at the subwavelength scale is crucial in various scientific and technological applications. We propose a thermally tunable disk design of indium tin oxide (ITO) and aluminum gallium nitride (Al0.18Ga0.82As), enabling a switch between absorption and scattering. Furthermore, the control of far-field radiation pattern can be easily realized by combining ITO and Al0.18Ga0.82As to enhance or suppress emission. Our results demonstrate that hybrid structure can be dynamically tuned with temperature variations. In the proposed design, a frequency is achieved at the epsilon-near-zero wavelength of 1240 nm. The thermal tunability of hybrid structure introduces new multifunctional possibilities for light manipulation, thereby enhancing the potential applications of new devices in the near-infrared range.

Objective: To evaluate the clinical efficacy of antibiotic bone cement plus lateral bone repositioning for severe diabetic foot and its impact on wound healing rate. Methods: Sixty patients with hemodialysis anemia admitted to the endocrinology department of our hospital from July 2020 to July 2021 were included and randomly assigned to receive antibiotic bone cement plus lateral bone repositioning (observation group) or vacuum sealing drainage (VSD) (control group). Outcome measures included skin temperature of the affected limb, ankle-brachial index, sensory threshold, foot wound healing, dorsalis pedis artery hemodynamics, lower limb function and clinical efficacy. Results: Antibiotic bone cement plus lateral bone repositioning resulted in significantly higher treatment efficiency and transcutaneous partial pressure of oxygen, smaller wound, and lower trauma pH versus VSD, suggesting that antibiotic bone cement plus lateral bone repositioning contributes to potentiating the treatment efficacy and reducing the foot ulcer trauma, thereby facilitating rapid recovery. Patients given antibiotic bone cement plus lateral bone repositioning had larger vascular internal diameter and blood flow and better sensory conduction velocity of the common peroneal nerve and the motor conduction velocity of the tibial nerve versus those given VSD, indicating its vascular and neurological benefits. Conclusion: Antibiotic bone cement plus lateral bone repositioning enhances the treatment efficiency, boosts trauma healing, and promotes postoperative functional recovery of patients.

Plant community assembly is the central issue in community ecology. As plant traits differ in different life history stages, the form, intensity and mechanism of interspecific interactions may change with the ontogenetic process of plants. However, our understanding of interspecific interaction mechanisms during germination is still limited. Here, we conducted a laboratory germination experiment using 5 dominant species in Chongming Dongtan (Spartina alterniflora, Scirpus mariqueter, Phragmites australis, Suaeda glauca and Tripolium vulgare) to assess their germination performance in control (monoculture), allelopathy and mixture treatments. The results indicated that seeds could affect germination performance of neighbours through both allelopathy and microenvironment modification. Salinity of the solution in petri dishes after germination decreased in all treatments, and was negatively correlated with the number of total germinated seeds. Seed leachate of invasive Spartina alterniflora inhibited the germination of native Scirpus mariqueter and Phragmites australis, but not the two halophytes Suaeda glauca and Tripolium vulgare. The salt absorption by Spartina alterniflora seeds had the opposite effects compared with that of its seed leachate. On the other hand, seed leachate of native species promoted the germination of invasive Spartina alterniflora. The effect of microenvironment modification of Scirpus mariqueter and Phragmites australis was positive, whereas that of Suaeda glauca and Tripolium vulgare was neutral or negative. Considering seed-to-seed interactions is an important perspective to understand the underlying mechanisms of community dynamics, species diversity maintenance and invasion of alien species, and can improve the effectiveness in the management of invaded coastal wetlands.

Silicon photonics is emerging as a competitive platform for electronic-photonic integrated circuits (EPICs) at the 2 µm wavelength band where GeSn photodetectors (PDs) have proven to be efficient PDs. Here, we present a comprehensive theoretical study of GeSn vertical p-i-n homojunction waveguide photodetectors (WGPDs) that have a strain-free and defect-free GeSn active layer for 2-µm Si-based EPICs. The use of a narrow-gap GeSn alloy as the active layer can fully cover entire the 2 µm wavelength band. The waveguide structure allows for decoupling the photon-absorbing path and the carrier-collection path, thereby allowing for simultaneous achievement of high-responsivity and high-bandwidth (BW) operation at the 2-µm wavelength band. We present the theoretical models to calculate the carrier saturation velocities, optical absorption coefficient, responsivity, 3-dB bandwidth, zero-bias resistance, and detectivity, and optimize this device structure to achieve highest performance at the 2-µm wavelength band. The results indicate that the performance of the GeSn WGPD has strong dependence on the Sn composition and geometric parameters. The optimally designed GeSn WGPD with 10% Sn concentration can give responsivity of 1.55 A/W, detectivity of 6.12×1010 cmHz½W-1 at 2 µm wavelength, and ~97 GHz BW. Therefore, this optimally designed GeSn WGPD is a potential candidate for silicon photonic EPICs offering high-speed optical communications.

This paper provides an overview of the current state-of-the-art digital twin and digital thread technology in industrial operations. Both are transformational technologies that have the advantage of improving the efficiency of current design and manufacturing. Digital twin is an important element of the Industry 4.0 digitalization process; however, the huge amount of data that are generated and collected by digital twin offer challenges in handling, processing and storage. The paper aims to report on the development of a new framework that combines the digital twin and digital thread for better data management in order to drive innovation, improve the production process and performance, and to ensure continuity and traceability of information. The digital twin/thread framework incorporated behavior simulation and physical control components, in which these two components rely on the connectivity between the twin and thread for information flow and exchange to drive innovation. The twin/thread framework encompasses specifications that include organizational architecture layout, security, user access, cloud computing set-up, and hardware and software requirements. It is envisaged that the framework will be applicable to enhancing optimization of operational processes and traceability of information in the physical world, especially in Industry Shipyard 4.0.

Soil microbial fuel cells (sMFC) are a novel technique that use organic matters in soils as an alternative energy source. External resistance (ER) is a key factor influencing sMFC performance and, furthermore, alters the soil’s biological and chemical reactions. However, little information is available on how the microbial community and soil component changes in sMFC with different ER. Therefore, the effects of anodes of sMFC at different ER (2000 Ω, 1000 Ω, 200 Ω, 80 Ω and 50 Ω) were examined by measuring organic matter (OM) removal efficiency, trace elements in porewater and bacterial community structure in contaminated paddy soil. The results indicated that ER has significant effects on sMFC power production, OM removal efficiency and bacterial beta diversity. Moreover ER influences iron, arsenic and nickel concentration as well in soil porewater. In particular, greater current densities were observed at lower ER (2.4mA, 50Ω) compared to a higher ER (0.3mA, 2000Ω). The removal efficiency of OM increased with decreasing ER whereas it decreased with soil distance away from the anode. Furthermore, principal coordinate analysis (PCoA) revealed that ER may shape the bacterial communities that develop in the anode vicinity but have minimal effect on that of the bulk soil. The current study illustrates that lower ER can be used to selectively enhance the relative abundance of electrogenic bacteria and lead to high OM removal.

In wideband radar systems, the performance of motion parameters estimation can significantly affect the performance of object detection and the quality of inverse synthetic aperture radar (ISAR) imaging. Although the traditional motion parameters estimation methods can reduce the range migration (RM) and Doppler frequency migration (DFM) effects in ISAR imaging, the computational complexity is high. In this paper, we propose a new fast non-searching motion parameters estimation method based on cross-correlation of adjacent echoes (CCAE) for wideband LFM signals. A cross-correlation operation is carried out for two adjacent echo signals, then the motion parameters can be calculated by estimating the frequency of the correlation result. The proposed CCAE method can be applied directly to the stretching system, which is commonly adopted in wideband radar systems. Simulational results demonstrate that the new method can achieve better estimation performances, with much lower computational cost, compared with existing methods. The experimental results on real radar data sets are also evaluated to verify the effectiveness and superiority of the proposed method compared to the state-of-the-art existing methods.

In this paper, an extendable fuzzy robust speed controller suitable for induction motor drive system was proposed. Firstly, the two-degrees-of-freedom (2DOF) robust control technology with feedforward control and disturbance elimination method was adopted. Upon parameter variation and load disturbance, the motor drive system could utilize a robust controller to generate compensation signals and reduce the impact on controlling performance of the motor drive system. The magnitude of the compensation signal was adjusted via the weighting factor. However, should a fixed weighting factor be adopted, system instability might be generated easily when time delay and saturation of control force occur. Based on the above, the smart method of extendable fuzzy theory (EFT) was adopted in this paper to adjust adequate weighting factors, where the controlling performance of the induction motor drive system could be improved accordingly. The method divided the speed difference between motor speed command and actual speed of the induction motor, and the variation rate for such speed difference into 20 regional categories. The correlation degree between the speed difference of actual feedback, variation rate for speed difference and each regional category was then calculated, where more suitable weighting factor was selected. Therefore, the proposed extendable fuzzy robust 2DOF controller with variable weighting factor designed will allow better performance for response in speed tracking and load regulation. Lastly, the simulation software Matlab/Simulink was applied to simulate the utilization of the controlling method proposed for the induction motor drive system. For both the response in speed tracking and load regulation, the simulation results proved that the extendable fuzzy robust speed controller proposed provided better controlling performance than the conventional robust controller.

Water area segmentation in remote sensing is of great importance for flood monitoring. To overcome some challenges in this task, we construct the Water Index and Polarization Information (WIPI) multi-modality dataset and propose a multi-Modality Fusion and Gated multi-Filter U-Net (MFGF-UNet) convolutional neural network. The WIPI dataset enhances the water information and reduces the data dimension. In particular, the Cloud-Free label provided in the database effectively mitigates the issue of scarcity of labeled samples Since a single form or uniform kernel size cannot handle the variety in size and shape of water bodies, we proposed the gated multi-filter inception (GMF-Inception) module in our MFGF-UNet. Moreover, we utilize the attention mechanism by introducing the Gated Channel Transform (GCT) skip connection and integrating GCT into GMF- Inception to further improve model performance. Extensive experiments on three benchmarks, including WIPI, Chengdu and GF2020 datasets demonstrate that our method achieves favorable performance with lower complexity and better robustness against six competing approaches. For example, on WIPI, Chengdu and GF2020 datasets, the proposed MFGF-UNet model achieves F1 of 0.9191, 0.7410, and 0.8421, respectively, which average F1 on three datasets is 0.0045 higher than the U-Net model and reduces 62% average GFLOPs. New WIPI dataset, code and trained models have been released on GitHub

The present study was to investigate effects of total flavonoids from Taraxacum mongolicum Hand.-Mazz. (FT) on fermentation quality, antioxidant status and microbial community of Caragana korshinskii Kom. (CK) silage. CK was ensiled with no additive (CON), 1% FT and 2% FT on a fresh weight (FW) basis for 60 days. The results showed that 1% FT and 2% FT groups displayed higher DM content than CON group, and 2% FT group had the best effect on nutrient preservation. Compared with CON and 1% FT groups, 2% FT group exhibited the best silage fermentation quality and the highest antioxidant activity, including increased lactic acid, acetic acid concentrations and the activities of antioxidant enzymes, as well as decreased pH and the ammonia nitrogen (NH₃-N) concentration. Moreover, 2% FT addition significantly affected the microbial community, such as increased abundance of Lactobacillus and decreased abundances of Pseudomonas and unidentified Cyanobacteria. The abundances of Lactobacillus parafarraginis and Lactobacillus brevis were negatively correlated to pH, while they were positively correlated with T-AOC, GSH-Px and CAT activities. In conclusion, 2% FT may be used as additives to inhibit the growth of undesirable microorganisms and promote fermentation quality and antioxidant activity of CK silage.

The search for a continuous continental record of interglacial periods in semi-arid regions is problematic due to the absence of stable and continuous sedimentary systems over time in this type of climate. In this work, a relatively stable basin is described and analyzed during the last interglacial in a semi-arid region of the western Mediterranean. For this purpose a geomorphological, stratigraphic and sedimentological study has been carried out, with dating through 230Th. A semi-endorrheic Pleistocene basin has been identified, with two units that correspond to a fluvial-lacustrine system (unit P1) and an alluvial system (unit P2). Unit P1 has been dated in the MIS 5e interglacial episode. A framework is described in which the Aljezares Quaternary basin can be considered as a possible source of paleoenvironmental and paleoclimatic information in semi-arid regions from the last interglacial period in future studies.

The theory of electron spin has been proposed for a century, but the study of quantum effects in biological molecules is still in its infancy. Chirality-induced spin selectivity (CISS) is a very modern theory that can explain many biochemical phenomena. In this paper, we propose a new theoretical model based on CISS theory and quantum chemistry theory, which can well explain the theoretical explanation of the chiral selectivity of chiral proteins. Moreover, this theory can predict the spin state of corresponding chiral molecules. Taking L-DOPA and AADC enzyme as examples, this theoretical model solves the theoretical explanation of AADC enzyme's chiral catalysis selectivity problem and successfully predicts the spin state of L-DOPA and D-DOPA's valence electrons.

Group IV alloys of GeSn have been extensively investigated as a competing material alternative in short-wave to mid-infrared photodetectors (PDs). The relatively large defect densities present in GeSn alloys are the major challenge in developing practical devices, owing to the low-temperature growth and lattice mismatch with Si or Ge substrates. In this paper, we comprehensively analyze the impact of defects on the performance of GeSn p-i-n homojunction PDs. We first present our theoretical models to calculate various contributing components of the dark current including minority carrier diffusion in p- and n-regions, carrier generation-recombination in the active intrinsic region, as well as the tunneling effect. We then analyze the effect of defect density in the GeSn active region on carrier mobilities, scattering times and the dark current. A higher defect density increases the dark current, resulting in reduction in detectivity of GeSn p-i-n PDs. In addition, at low Sn concentrations, defect-related dark current density is dominant, while the generation dark current becomes dominant at a higher Sn content. These results point to the importance of minimizing defect densities in the GeSn material growth and device processing, particularly for higher Sn compositions necessary to expand the cutoff wavelength to mid- and long-wave infrared regime. The study provides more of realistic expectations and guidelines for evaluating GeSn p-i-n PDs as a competitor to the III-V and II-VI-based infrared PDs currently on the commercial market.

The effects of 1%~5% cold compression on the mechanical properties, microstructure and residual stress of 7050 aluminum alloy were investigated, and the results were applied to the complex die forging with stiffener structure. The results show that with the increase of cold compression, the tensile strength of forging decreases gradually, but the conductivity and fracture toughness of the forging have little change. TEM microstructure shows that with larger cold compression (5%), the dislocation density was relatively higher, which promoted the precipitation and growth of precipitated phases at positions with higher dislocation density during aging process. The ultrasonic tests of residual stress show that with the increase of cold compression, the residual stress in the forging decreases first, and then increases when cold compression reaches 5%. The results of the die forging of 7050 aluminum alloy with bar structure show that the residual stress of the die forging is obviously eliminated after 2-4% cold compression, and the deformation after machining is obviously less than of the uncompressed forgings. The combination of bar and web is more beneficial to the uniform distribution of residual stress of the die forging with bar structure.

Transcription factors (TFs) in the homeodomain-leucine zipper (HD-ZIP) family serve as essential regulators of plant development and control responses to environmental stimuli. To date, however, the HD-ZIP gene family in Prunus nana remains to be fully characterized. Accordingly, a genome-wide analysis of P. nana HD-ZIP family genes was performed using the most recent genomic data available, leading to the classification of 30 HD-ZIP TFs. These genes were annotated and subjected to systematic analyses of phylogenetic relationships, protein physicochemical properties, sequence-based structural characteristics, chromosomal distributions, and associated cis-acting regulatory elements. High levels of diversity were observed with respect to the gene structures for these PnaHD-Zip genes and the cis-regulatory elements found in the promoter regions upstream of these genes, suggesting that they play diverse roles in a range of biological contexts. These 30 PnaHD-Zip genes were further classified into four subgroups based on the results of phylogenetic, gene structure, and conserved motif analyses. Subsequent qPCR analyses indicated that PnaHD-Zip1 and PnaHD-Zip7 expression levels tended to increase was continuously inhibited in response to cold stress, suggesting that proteins in this HD-ZIP gene family may exhibit distinct responses to low-temperature stress exposure. Overall, these results offer a robust foundation for future studies seeking to explore the functional roles that HD-ZIP TFs play as regulators of cold stress tolerance in P. nana, in addition to offering more general insight regarding the regulatory functions and characteristics of these different HD-ZIP genes in P. nana.

This article presents, for the first time, the efficacy and curing depth analysis of photo-thermal dual polymerization in metal (Fe) polymer composites for 3D printing of a 3-component (A/B/M) system based on the proposed mechanism of our group, in which the co initiators A and B are Irgacure-369, and charge-transfer complexes (CTC), respectively; and the monomer M is TMPTA filled by Fe. Our formulas show the depth of curing (Zc) is an increasing function of the light intensity, but a decreasing function of the Fe and photoinitiator concentrations. Zc is enhanced by the additive [B] which produces extra thermal radical for polymerization under high temperature. The heat (or temperature) increase in the system has two components : (i) due to the light absorption of Fe filler, and (ii) heat released from the exothermic photopolymerization of the monomer. The heat is transported to the additive (or co-initiator) [B] to produce extra radical R' and enhance the monomer conversion function (CF). The CF has two opposite trends in their time profiles: (i) for small Fe concentration (F), it is a time decaying function; and (ii) for large Fe, it is a time increasing profile. This switching feature predicted by our formula is also justified by our measured data. The Fe filler leads to temperature increase, but also limits the light penetration leading to lower CF and Zc, which could be overcome by the additive initiator [B] in thick polymers. the new finding of optimal Fe for maximal CF and Zc are explored theoretically.

Enterovirus 71 (EV71) is an etiological agent of hand foot and mouth disease and can also cause neurological complications in young children. However, there are no approved drugs to treat EV71 infections. In this study, we conducted an antiviral drug screening by using a Food and Drug Administration (FDA)-approved drug library. We identified five drugs that showed dose-dependent inhibition of viral replication. Sertraline was further characterized because it exhibited the most potent antiviral activity with the highest selectivity index among the five hits. The antiviral activity of sertraline was noted for other EV serotypes. The drug’s antiviral effect is not likely associated with its approved indications as an antidepressant and its mode-of-action as a selective serotonin reuptake inhibitor. The time-of-addition assay revealed that sertraline inhibited an EV71 infection at the entry stage. We also showed that sertraline partitioned into acidic compartments, such as endolysosomes, to neutralize the low pH levels. In agreement with the findings, the antiviral effect of sertraline could be relieved greatly by exposing virus-infected cells to extracellular low-pH culture media. Together, we have identified an FDA-approved antidepressant with the new indication for the broad-spectrum EV inhibition by blocking viral entry through the alkalization of the endolysosomal route.

In the permanent magnet synchronous motor (PMSM) drive system, the unwilling and ear-piercing vibro-acoustics caused by high-frequency sideband harmonics becomes unacceptable in the electric vehicle application. In this paper, a modified space vector pulse-width modulation (SVPWM) technique implemented with hybrid carrier frequency modulation (HCFM) is provided to reduce the sideband current harmonic components and vibro-acoustic responses. The principle and implementation of the proposed HCFM technique are firstly presented, in which the fixed carrier frequency is improved with the sawtooth and random signal-based coupling modulation based on the rotor position. For verification, the experiment tests are carried out on a prototype 12/10 PMSM and microcontroller unit. The effectiveness of the HCFM technique can hence be confirmed, in which the sideband vibro-acoustics reduction shows more effectively than that in conventional random PWM. The proposed approach may provide a new route in noise-cancelling and electromagnetic compatibility for the electric drive powertrain.

This study aimed at the investigation of the effect of substrate preheating on residual stress in laser powder bed fusion using a physics-based analytical model. In this study, an analytical model is proposed to predict the residual stress through the calculation of preheating affected temperature profile and thermal stress. The effect of preheating is super-positioned with initial temperature in the modeling of temperature profile using a moving heat source approach; the resultant temperature gradient is then employed to predict the thermal stress from a point body load approach. If the thermal stress exceeds the yield strength of the material, then the residual stress under cyclic heating and cooling will be calculated based on the incremental plasticity and kinematic hardening behavior of metal. IN718 is used as a material example to pursue this investigation. To validate the predicted residual stress, experimental measurements are conducted using X-ray diffraction on IN718 samples manufactured via laser powder bed fusion under different process conditions. Results showed that preheating of the substrate could reduce the residual stress in an additively manufactured part due to the reduction in temperature gradient and resultant shrinkage stresses. However, the excessive preheating could have an opposite impact on residual stress accumulation. Moreover, the results confirm that the proposed model is a valuable tool for the prediction of residual stress- eliminating the costly experiments and time-consuming finite element simulations.

Dynamic visualizations have been developed to exchange information that transforms over time across a broad range of professional and academic contexts. However, these visual tools may impose substantial demands on the learner’s cognitive resources that are very limited in current knowledge. Cognitive load theory has been used to improve learning from dynamic visualizations by providing certain design techniques to manage learner cognitive load without adding any oral/written explanations. This systematic review examined a series of experimental studies assessing the roles of these design techniques in learning tactical scenes of play through dynamic visualizations. Electronic databases PubMed and Google Scholar were used to search relevant articles. Eleven studies were eventually included for the systematic review based on the eligibility criteria. The present review revealed that adapting design techniques to the level of learners’ expertise, type of depicted knowledge, and level of content complexity is a crucial part of effective learning.

The 2019 novel coronavirus (2019-nCoV) causes novel coronavirus pneumonia (NCP). Given that approved drug repurposing becomes a common strategy to quickly find antiviral treatments, a collection of FDA-approved drugs can be powerful resources for new anti-NCP indication discoveries. In addition to synthetic compounds, Chinese Patent Drugs (CPD), also play a key role in the treatment of virus related infections diseases in China. Here we compiled major components from 38 CPDs that are commonly used in the respiratory diseases and docked them against two drug targets, ACE2 receptor and viral main protease. According to our docking screening, 10 antiviral components, including hesperidin, saikosaponin A, rutin, corosolic acid, verbascoside, baicalin, glycyrrhizin, mulberroside A, cynaroside, and bilirubin, can directly bind to both host cell target ACE2 receptor and viral target main protease. In combination of the docking results, the natural abundance of the substances, and botanical knowledge, we proposed that artemisinin, rutin, glycyrrhizin, cholic acid, hyodeoxycholic acid, puerarin, oleanic acid, andrographolide, matrine, codeine, morphine, chlorogenic acid, and baicalin (or Yinhuang Injection containing chlorogenic acid and baicalin) might be of value for clinical trials during a 2019-nCov outbreak.

A variety of myricetin derivatives bearing ferulic acid amide scaffolds were designed and synthesized. The structures of all title compounds were determined by 1 H NMR, 13 C NMR, 19 F NMR and HRMS. Preliminary bioassays suggested that some of the target compounds exhibited remarkable antiviral activities. In particular, compound 4l possessed significant protection activity against tobacco mosaic virus (TMV), with an half maximal effective concentration (EC50) value of 196.11 μg/mL, which was better than commercial agent ningnamycin (447.92 μg/mL). Meanwhile, microscale thermophoresis (MST) indicated that compound 4l have strong binding capability to tobacco mosaic virus coat protein (TMV-CP) with dissociation constant (Kd) values of 0.34 μmol/L, which was better than ningnamycin (0.52 μmol/L). These results suggest that novel myricetin derivatives bearing ferulic acid amide scaffolds may be considered as an activator for antiviral agents.

Information-theoretically provable unique true random numbers, which cannot be correlated or controlled by an attacker, can be generated based on quantum measurement of vacuum state and universal-hashing randomness extraction. Quantum entropy in the measurements decides the quality and security of the random number generator (RNG). At the same time, it directly determines the extraction ratio of true randomness from the raw data, in other words, it obviously affects quantum random bits generating rate. In this work, we commit to enhancing quantum entropy content in the vacuum noise based quantum RNG. We have taken into account main factors in this proposal to establish the theoretical model of quantum entropy content, including the effects of classical noise, the optimum dynamical analog-digital convertor (ADC) range, the local gain and the electronic gain of the homodyne system. We demonstrate that by amplifying the vacuum quantum noise, abundant quantum entropy is extractable in the step of post-processing even classical noise excursion, which may be deliberately induced by an eavesdropper, is large. Based on the discussion and the fact that the bandwidth of quantum vacuum noise is infinite, we propose large dynamical range and moderate TIA gain to pursue higher local oscillator (LO) amplification of vacuum quadrature and broader detection bandwidth in homodyne system. High true randomness extraction ratio together with high sampling rate is attainable. Experimentally, an extraction ratio of true randomness of 85.3% is achieved by finite enhancement of the laser power of the LO when classical noise excursions of the raw data is obvious.

The Anderson insulating states in Au nanoparticle assembly are identified and studied under the application of magnetic fields and gate voltages. When the inter-nanoparticle tunneling resistance is smaller than the quantum resistance, the system showing zero Mott gap can be insulating at very low temperature. In contrast to Mott insulators, Anderson insulators exhibit great negative magnetoresistance, inferring charge de-localization in a strong magnetic field. When probed by the electrodes spaced by ~200 nm, they also exhibit interesting gate-modulated current similar to the multi-dot single electron transistors. These results reveal the formation of charge puddles due to interplay of disorder and quantum interference at low temperatures.

A reinforcement learning algorithm is proposed to improve the accuracy of short-term load forecasting (STLF) in this article. The proposed model integrates radial basis function neural network (RBFNN), support vector regression (SVR), and adaptive annealing learning algorithm (AALA). In the proposed methodology, firstly, the initial structure of RBFNN is determined by using SVR. Then, an AALA with time-varying learning rates is used to optimize the initial parameters of SVR-RBFNN (AALA-SVR-RBFNN). In order to overcome the stagnation for searching optimal RBFNN, a particle swarm optimization (PSO) is applied to simultaneously find promising learning rates in AALA. Finally, the short-term load demands are predicted by using the optimal RBFNN. The performance of the proposed methodology is verified on the actual load dataset from Taiwan Power Company (TPC). Simulation results reveal that the proposed AALA-SVR-RBFNN can achieve a better load forecasting precision as compared to various RBFNNs.

Supervised land-use/land-cover (LULC) classifications are typically conducted using class assignment rules derived from a set of multiclass training samples. Consequently, classification accuracy varies with the training data set and is thus associated with uncertainty. In this study, we propose a bootstrap resampling and reclassification approach that can be applied for assessing not only the uncertainty in classification results of the bootstrap-training data sets, but also the classification uncertainty of individual pixels in the study area. Two measures of pixel-specific classification uncertainty, namely the maximum class probability and Shannon entropy, were derived from the class probability vector of individual pixels and used for the identification of unclassified pixels. Unclassified pixels that are identified using the traditional chi-square threshold technique represent outliers of individual LULC classes, but they are not necessarily associated with higher classification uncertainty. By contrast, unclassified pixels identified using the equal-likelihood technique are associated with higher classification uncertainty and they mostly occur on or near the borders of different land-cover.

Public transportation scheduling aims to optimize the allocation of transportation resources, enhance transportation efficiency, and increase passenger satisfaction, which is crucial for building a sustainable urban transportation system. As a complement to public transportation, shared bikes provide users with a solution for the last mile of travel, compensating for the lack of flexibility in public transportation and helping to improve its utilization rate. Due to the characteristics of shared bikes, such as peak usage periods in the morning and evening and significant fluctuations in demand across different areas, the optimization of shared bike dispatch can better meet user needs, thereby reducing vehicle vacancy rates and increasing operating revenue. Addressing this issue, this paper designs a comprehensive decision-making approach for spatio-temporal demand prediction and bike dispatch optimization. For demand prediction, we designed a T-GCN based bike demand prediction model. In terms of dispatch optimization, we considered factors such as dispatch capacity, distance restrictions, and dispatch costs, and designed an optimization solution based on genetic algorithms. Finally, this paper validates the approach using shared bike operating data, shows that T-GCN can effectively predict short-term demand for shared bikes. Meanwhile, the optimization model based on genetic algorithms provides a complete dispatch solution verifying the model’s effectiveness. The shared bike dispatch approach proposed in this paper, which combines demand prediction with resource scheduling. This scheme can also be extended to other transportation scheduling problems with uncertain demand, such as store replenishment delivery and intercity inventory dispatch.

Blocking the interaction of the SARS-CoV-2 spike protein with the human angiotensin-converting enzyme II (hACE2) protein serves as a therapeutic strategy for treating COVID-19. Traditional Chinese medicine (TCM) treatments containing bioactive products could alleviate the symptoms of severe COVID-19. However, the emergence of SARS-CoV-2 variants has complicated the process of developing broad-spectrum drugs. As such, the aim in this study was to explore the efficacy of TCM treatments for SARS-CoV-2 variants through targeting the interaction of the viral spike protein with the hACE2 receptor. The antiviral activity was systematically evaluated using a pseudovirus system. Scutellaria baicalensis was found to be effective against SARS-CoV-2 infection through affecting the interaction of viral spike protein with the hACE2 protein. The active molecules of S. baicalensis were identified and analyzed. Baicalein and baicalin, a flavone and a flavone glycoside, respectively, found in S. baicalensis, exhibited strong inhibitory activities, targeting the viral spike protein or hACE2 protein, respectively. Under optimized conditions, virus infection was inhibited by 98% via baicalein-treated pseudovirus and baicalin-treated hACE2. In summary, we identified the potential SARS-CoV-2 inhibitors of the interaction of the Omicron spike protein and hACE2 receptor from S. baicalensis. Future studies on the therapeutic application of baicalein and baicalin against SARS-CoV-2 variants are needed.

Simultaneous Localization and Mapping (SLAM), as one of the core technologies in intelligent robotics, has gained substantial attention in recent years. Addressing the limitations of SLAM systems in dynamic environments, this research proposes a system specifically designed for plant factory transportation environments, named GY-SLAM. GY-SLAM incorporates a lightweight target detection network GY based on YOLOv5, which utilizes GhostNet as the backbone network. This integration is further enhanced with CoordConv coordinate convolution, CARAFE up-sampling operators, and SE attention mechanism, leading to simultaneous improvements in detection accuracy and model complexity reduction. While improving [email protected] by 0.514%, the model simultaneously reduces the number of parameters by 43.976%, computational cost by 46.488%, and model size by 41.752%. Additionally, the system constructs pure static octree maps and grid maps. Tests conducted on the TUM dataset and a proprietary dataset demonstrate that GY-SLAM significantly outperforms ORB-SLAM3 in dynamic scenarios in terms of system local-ization accuracy and robustness. It shows a remarkable 92.58% improvement in RMSE for Absolute Trajectory Error (ATE). Compared to YOLOv5s, the GY model brings a 41.5944% improvement in detection speed and a 17.7975% increase in SLAM operation speed to the system, indicating strong competitiveness and real-time capabilities. These results validate the effectiveness of GY-SLAM in dynamic environments and provide substantial support for the automation of logistics tasks by robots in specific contexts.

The concentration of heavy metals in sediment is an important factor for assessing the quality of the nearshore environment. Geochemical background values are the normal concentrations of heavy metals in the natural environment. The use of different background values results in different evaluation results. Heavy metal (Cu, Pb, Zn, Cr, Cd, As, and Hg) concentration profiles along a sediment core were investigated to obtain background values and assess the depositional processes and contamination levels in Laizhou Bay. Apart from As and Hg, all other metals had similar distribution patterns and could be divided into four stages since marine isotope stage (MIS) 2. The results of the enrichment factor, geoaccumulation index, Pearson’s correlation coefficient, Nemerow pollution index, principal component analysis, and potential ecological risk index showed that element enrichment or contamination in the core sediments was absent and that all heavy metals were mainly naturally sourced. The changes in heavy metals since MIS 2 in the core sediments were predominantly related to the sedimentary environment, sediment sources, and mean grain size. The average values of the heavy metals in the U2 unit formed during the Middle Holocene can be used as reference values for background values.

The lengthy maturation period is the key cause of the reduced hot pepper market value. An experiment was performed to assess the effects of R/B/W light qualities on reducing the maturation period. The maturation period was shortened by 16 days under 4R:1B:5W compared to the control. The appearance of the first flower is a limiting factor affecting the maturation period. It exhibited a dark purple color and an abnormal petal under 4R:1B:5W compared to the control, which was associated with increased contents of flavonoids, total organic acids, and phenolics and decreased total amino acid and carbohydrate contents. Plant hormone, flavonoid, ABC transporters, key metabolites (such as amino acid, carbohydrate, organic acid) was associated with first flower development. Ethylene response factors (ERFs) mediated by light, especially ERF021, were identified as potential hub regulators during the development of the first flower due to their involvement in all the associated metabolic pathways.

Field-effect transistor (FET)-based biosensors stand as powerful analytical tools for detecting trace-specific biomolecules in diverse sample matrices, especially in the realms of pandemics and infectious diseases. The primary concern in applying these biosensors is their stability, a factor directly impacting the accuracy and reliability of sensing over extended durations. The risk of biosensor degradation is substantial, potentially jeopardizing sensitivity and selectivity and leading to inaccurate readings, including the possibility of false positives or negatives. This paper delves into the documented degradation of silicon nanobelt FET (NBFET) biosensors induced by buffer solutions. The results highlight a positive correlation between immersion time and the threshold voltage of NBFET devices. Secondary ion mass spectrometry analysis demonstrates a gradual increase in sodium and potassium ion concentrations within the silicon as immersion days progress. This outcome is ascribed to the nanobelt's exposure to the buffer solution during the biosensing period, enabling ion penetration from the buffer into the silicon. The study emphasizes the critical need to address buffer solution-induced degradation to ensure the long-term stability and performance of FET-based biosensors in practical applications.

The management of blunt abdominopelvic trauma with combined hemoperitoneum and pelvic fractures is challenging for trauma surgeons. Although angioembolization can achieve hemostasis in most visceral organ injuries and pelvic fractures after blunt abdominal trauma, it cannot effectively control hemorrhage in patients with blunt bowel mesenteric injury (BBMI). This study aimed to determine the risk factors associated with hemodynamically unstable patients with BBMI and to test the hypothesis that pelvic fracture is an independent risk factor for patients with unstable BBMI and concomitant pelvic fracture to guide the therapeutic sequence for difficult-to-manage patients. This retrospective study reviewed the data of hospitalized patients with trauma between 2009 and 2021 and included 158 adult patients with surgically proven BBMI. The patients were divided on the basis of the presence of a shock episode before emergency laparotomy. The shock group included 44.3% of all patients in the study (n = 70). Clinical injury severity and prognosis for patients in the shock group were poorer than those for patients in the non-shock group, and more invasive treatments and transfusions were performed for patients in the shock group than for those in the non-shock group. Pelvic fractures were more frequently associated in the shock group than in the non-shock group (21.4% vs. 5.7%; p = 0.003). In multivariate analysis, the presence of intracerebral hemorrhage (odds ratio [OR] = 10.87, 95% confidence intervals [CIs]: 1.70–69.75) and rib fracture (OR = 5.94, 95% CIs = 1.06–33.45) were identified as independent predictors of shock, whereas the effect of pelvic fracture did not achieve statistical significance (OR = 2.94, 95% CIs = 0.66–13.13) after adjusting for confounding factors. For patients with BBMI, outcomes need to be improved during early diagnosis and treatments should be expeditiously performed on the basis of the rapid identification of unstable hemodynamic status. In unstable patients with concomitant pelvic fractures, we support the current management algorithm that recommends performing laparotomy first.

In this comprehensive survey, we delve into the multifaceted role of palmitoylation across vari-ous cell death modalities in the oncological context. From its intricate correlations with tumor-igenesis, steered by the DHHC family, to the counter-process of depalmitoylation mediated by enzymes like PPT1. Innovations in detection methodologies have paralleled our growing under-standing, transitioning from rudimentary techniques to sophisticated modern methods. Central to our discourse are agents like GNS561 and DC661, promising heralds in palmitoylation-targeted cancer therapy. Collectively, this review accentuates palmitoylation's transformative potential in oncology, foreshadowing groundbreaking therapeutic strategies and deepening our molecular comprehension of cancer dynamics.

In view of the limitations of the existing eccentricity error separation method of the rotary table, an eccentricity error separation method based on the phase feature of the moiré signal of single reading head is proposed herein. A grating pair transmission model is established based on the analysis of the principle of the rotary table, thereby the influence of eccentricity error on the phase feature of the moiré signal in the rotation course of the rotary table is clarified, and the corresponding model between the phase feature spectral components and the eccentricity error is established. The verification experiments of the proposed method are carried out based on the laboratory-made circuit system. After verifying the accuracy of the data acquisition of the laboratory-made circuit board, the verification experiments of the eccentricity error separation effect of the proposed method are carried out. The experimental data are compared with those of the traditional method and the results show that the error between the two methods is 2.34μm and the relative error is 2.3%.

In this study, seventeen faceted gem-quality chrysoberyls exhibiting an attractive canary yellow color were investigated by a series of gemological, spectral, and chemical methods. Microscopic observation reveals distinct growth lines and inclusions, including CO2 fluids, carbon, and mineral crystals such as calcite, quartz, sillimanite, and mica, identified by the Raman spectrum. The FTIR spectrum exhibits the 2405 and 2160 cm-1 feature peaks and a 3223 cm-1 peak in all samples, which can be accompanied by the 3112 cm-1 shoulder, 3301, and 3412 and 3432 cm-1 peaks. The UV-Vis spectrum shows a Fe-related peak at 440 nm, along with the 650–660 nm band and the absorption band in the blue zone of the visible light. The chemical results of EDXRF reveal a V-poor, Cr-poor, and Fe-rich feature. The spectral and chemical results could contribute to explaining the origin of the canary yellow color, which originates from the abundant amount of Fe with very little influence from Cr or V.

Our image recognition system mainly judges whether the left upper limb in the image is the left upper limb or the right upper limb through our deep learning model in the image. The doctor then could give the correct surgical position. From the experimental results, it could be found that the precision rate and recall rate of the intelligent image recognition system proposed in this paper for preventing the upper limb dislocation surgery could reach 98% and 93%, respectively. It proved that our artificial intelligent image recognition system, AIIRS, could indeed assist orthopedic surgeons to prevent the occurrence of left and right dislocation in upper limb surgery. At the same time, this paper also completes the IRB application approval through the prototype experimental results and will conduct the second phase of human trials in the future. It showed that the research results of this paper will be of great benefit and research value to upper limb orthopedic surgery.

Long-term storage may reduce the nutritional quality of brown rice, so the present study was aimed to evaluate the nutritive values and application in pig diets. In Exp.1, 18 Landrace × Yorkshire (L × Y) barrows with initial body weight (IBW) of 25.48 ± 3.21 kg were randomly assigned to three treatments, which included corn diet, one-year stored brown rice (BR1) diet and six-year stored brown rice (BR6) diet, to determine the digestible energy (DE) and metabolisable energy (ME) value of stored brown rice. In Exp. 2, 24 barrows (L × Y; IBW: 22.16 ± 2.42 kg) fixed with ileal T-cannula were randomly allotted to four dietary treatments, including corn diet, two stored brown rice diets and nitrogen-free diet, to evaluate the amino acid (AA) digestibility of stored brown rice. In Exp. 3 and 4, 108 crossbred weaned piglets (L × Y; IBW: 9.16 ± 0.89 kg) and 90 crossbred growing pigs (L × Y; IBW: 48.28 ± 3.51 kg) were allotted to 3 treatment diets, including control diet and two stored brown rice diets, respectively, to investigate the application of stored brown rice in weaned piglet and growing-finishing pig diets. Results showed that: 1) The DE and ME of corn and stored brown rice showed no significant differences (P > 0.05), while the apparent ileal digestibility (AID) of arginine, histidine, aspartic acid, and the standardized ileal digestibility (SID) of arginine and histidine were higher in stored brown rice compared to corn (P < 0.05). 2) Compared with the control diet, the stored brown rice diets showed no significant effects on growth performance, nutrient apparent total tract digestibility (ATTD) and serum biochemical indices (P > 0.05), but decreased digestive enzymes activities in duodenum, jejunum and ileum of piglets (P < 0.05). 3) Compared with the control diet, the stored brown rice diets showed no significant effects on growth performance, carcass traits, meat quality, fatty acids profiles in the longissimus dorsi muscle of growing-finishing pigs (P > 0.05). In conclusion, the brown rice stored for 6 years under good conditions has no obvious changes in available energy and nutrient values. Although it may reduce digestive enzyme activity in small intestine of the piglets, the stored brown rice showed no obvious adverse effect on growth performance and meat quality, and can be effectively used in pig diet.

Our image recognition system mainly judges whether the left upper limb in the image is the left upper limb or the right upper limb through our deep learning model in the image. The doctor then could give the correct surgical position. From the experimental results, it could be found that the precision rate and recall rate of the intelligent image recognition system proposed in this paper for preventing the upper limb dislocation surgery could reach 98% and 93%, respectively. It proved that our intelligent image recognition system could indeed assist orthopedic surgeons to prevent the occurrence of left and right dislocation in upper limb surgery. At the same time, this paper also completes the IRB application approval through the prototype experimental results and will conduct the second phase of human trials in the future. It showed that the research results of this paper will be of great benefit and research value to upper limb orthopedic surgery.

Foliage-feeding fall armyworm (Spodoptera frugiperda) and root-feeding western corn rootworm (Diabrotica virgifera virgifera) are maize (Zea mays L.) pests that cause significant yield losses. Jasmonic acid (JA) play pivotal defense role against insects. 12-oxo-phytodienoic acid (12-OPDA) is converted into JA by peroxisome-localized OPDA reductases (OPR). However, little is known about the physiological functions of cytoplasmic OPRs. Here, we show that disruption of ZmOPR2 reduced wound-induced JA production and defense against FAW while accumulating more JA catabolites. Overexpression of ZmOPR2 in Arabidopsis enhanced JA production and defense against beet armyworm (Spodoptera exigua). In addition, lox10opr2 double mutants were more susceptible than either single mutant, suggesting that ZmOPR2 and ZmLOX10 uniquely and additively contributed to defense. In contrast to the defensive role of ZmOPR2 and ZmLOX10 in leaves, single mutants did not display any alteration in root herbivory defense against WCR. Feeding on lox10opr2 double mutants resulted in increased WCR mortality associated with greater herbivory-induced production of insecticidal death acids and ketols. Thus, ZmOPR2 and ZmLOX10 cooperatively inhibit synthesis of these metabolites during herbivory by WCR. We conclude that ZmOPR2 and ZmLOX10 regulate JA-mediated resistance in leaves against FAW while suppressing insecticidal oxylipin synthesis in roots during WCR infestation.

COVID-19 is a highly infectious respiratory illness caused by SARS-CoV-2, and acute lung injury (ALI) is the major cause of COVID-19. The challenge in studying SARS-CoV-2 pathogenicity is the limited availability of animal models. Therefore, it is necessary to establish animal models that can reproduce multiple characteristics of ALI to study therapeutic applications. The present study established a mouse model that has features of ALI that are similar to COVID-19 syndrome to investigate the role of ACE2 and the administration of the Chinese herbal prescription NRICM101 in ALI. Mice with genetic modifications, including overexpression of human ACE2 (K18-hACE2 TG) and absence of ACE2 (mACE2 KO), were intratracheally instillated with hydrochloric acid. The acid intratracheal instillation induced severe immune cell infiltration, cytokine storms, and pulmonary disease in mice. Compared with K18-hACE2 TG mice, mACE2 KO mice exhibited dramatically increased levels of multiple inflammatory cytokines (IL-6, TNF-α, and TGF-β1) in bronchoalveolar lavage fluid, histological evidence of lung injury, and dysregulation of MAPK and MMP activation. In mACE2 KO mice, NRICM101 could ameliorate the disease progression of acid-induced ALI. In conclusion, the established mouse model provided an effective platform for researchers to investigate pathological mechanisms and develop therapeutic strategies for ALI, including COVID-19-related ALI.

In modern security situations, tracking multiple human objects in real-time within challenging urban environments is a critical capability for enhancing situational awareness, minimizing response time, and increasing overall operational effectiveness. Tracking multiple entities enables informed decision-making, risk mitigation, and the safeguarding of civil-military operations to ensure safety and mission success. This paper presents a multi-modal electro-optical/infrared (EO/IR) and radio frequency (RF) fused sensing (MEIRFS) platform for real-time human object detection, recognition, classification, and tracking in challenging environments. By utilizing different sensors in a complementary manner, the robustness of the sensing system is enhanced, enabling reliable detection and recognition results across various situations. Specifically designed Radar tag and thermal tag can be used to discriminate friendly and non-friendly objects. The system incorporates deep learning-based image fusion and human object recognition and tracking (HORT) algorithms to ensure accurate situation assessment. After integrating into an all-terrain robot, multiple ground tests were conducted to verify the consistent HORT in various environments. The MEIRFS sensor system has been designed to meet the Size, Weight, Power, and Cost (SWaP-C) requirements for installation on autonomous ground and aerial vehicles.

The images captured by UAVs during inspection often contain numerous small targets related to transmission lines, which are critical and vulnerable elements for ensuring the safe operation of these lines. However, due to various factors such as the small size of the targets, low resolution, complex background, and potential line aggregation, achieving accurate and real-time detection becomes challenging. To address these issues, this paper proposes a detection algorithm called P2-ECA-EIOU-YOLOv5 (P2E-YOLOv5). Firstly, in order to address the challenges posed by the complex background and environmental interference that impact small targets, an ECA attention module is integrated into the network. This module effectively enhances the network's focus on small targets while concurrently mitigating the influence of environmental interference. Secondly, considering the characteristics of small target size and low resolution, a new high-resolution detection head is introduced, which is more sensitive to small targets. Lastly, the network utilizes the EIOU-Loss as the regression Loss function to improve the positioning accuracy of small targets, as they tend to aggregate. Experimental results demonstrate that the proposed P2E-YOLOv5 detection algorithm achieves an accuracy P of 96.0% and an average accuracy (mAP) of 97.0% for small target detection in transmission lines.

With the popularization of natural gas and the requirements for environmental protection, the development and utilization of natural gas is particularly important. The status of natural gas in China's oil and gas exploration and development is constantly improving, and the country is paying more and more attention to the exploitation and utilization of natural gas. The Upper Paleozoic tight sandstone in the Ordos Basin is characterized by low porosity, low permeability and large area of concealed gas reservoirs. By injecting CO2 into the formation, the recovery of natural gas can be improved, and at the same time, the stable storage of CO2 can be achieved to achieve a win-win situation of CO2 emission reduction and utilization. Injecting greenhouse gas CO2 into gas reservoirs for storage and improving recovery has also become a hot research issue. In order to improve the recovery efficiency of tight sandstone gas reservoir, this paper takes the complex tight sandstone of Upper Paleozoic in Ordos Basin as the research object, through indoor physical simulation experiments, carried out the influence of displacement rate, fracture dip angle, core permeability, core dryness and wetness on CO2 gas displacement efficiency and storage efficiency, and analyzed the influence of different factors on CO2 gas displacement efficiency and storage efficiency to improve the recovery and storage efficiency. The research results show that under different conditions, when the CO2 injection pore volume is less than 1PV, the relationship between the CH4 recovery rate and the CO2 injection pore volume is linear, and the tilt angle is 45 °. When the CO2 injection pore volume exceeds 1PV, the CH4 recovery rate increases slightly with the increase of displacement speed, the recovery rate of CO2 displacement CH4 is between 87% - 97%, and the CO2 breakthrough time is 0.7PV-0.9PV. In low-permeability and low-speed displacement cores, the diffusion of CO2 molecules is more significant. The lower the displacement speed is, the earlier the breakthrough time of CO2 is, and the final recovery of CH4 slightly decreases. Gravity has a great impact on CO2 storage and enhanced recovery. The breakthrough of high injection and low recovery of CO2 is earlier, and the recovery of CH4 is about 3.3% lower than that of low injection and high recovery. The bound water makes the displacement phase CO2 partially dissolved in the formation water, and the CO2 breakthrough lags about 0.1PV. Ultimately, CH4 recovery factor and CO2 storage rate are higher than those of dry core displacement. The research results provide theoretical data support for CO2 injection to improve recovery and storage efficiency in complex tight sandstone gas reservoirs.

Fifteen new diterpenoids, namely xishaklyanes A-O (1-15), along with three known related ones (16-18), were isolated from the soft coral Klyxum molle collected from Xisha Islands, South China Sea. The stereochemistry of the new compounds were elucidated by a combination of detailed spectroscopic analyses, chemical syntheses, quantum chemical calculations and comparison with the reported data. The absolute configuration of compound 18 was established by the modified Mosher's method for the first time. In bioassay, some of these compounds exhibited considerable antibacterial activities on fish pathogenic bacteria, and compound 4 showed the most effective activity with MIC of 0.225 g/mL against Lactococcus garvieae.

Soil enzyme activity can be affected by both production and degradation, as enzymes can be degraded by proteases. However, the impact of nutrient addition on enzyme activity is often solely attributed to changes in enzyme production without fully considering degradation. Here, we demonstrated that the activities of β-1,4-glucosidase (BG), β-D-cellobiohydrolase (CBH), β-1,4-Xylosidase (BX), and β-1,4-N-acetyl-glucosaminnidase (NAG) were comparable in nitrogen (N) and phosphorus (P) fertilized soils and the unfertilized control under field conditions, but the reduction in activity was substantially greater in the fertilized soils during short-term laboratory incubation. The results show that the interruption of the natural, continuous supply of organic matter or non-soil microbial-derived enzymes, which typically occurs under field conditions, leads to a more significant reduction in apparent enzyme activities in fertilized soils compared to unfertilized control. This may be attributed to the higher abundance of protease in fertilized soils, resulting in faster enzyme degradation. Interestingly, P fertilization alone did not have a similar effect, indicating that N fertilization is likely the main cause of the larger decreases in enzyme activity during incubation in fertilized soils compared to unfertilized control soils, despite our study site being poor in P and rich in N. These findings highlight the importance of considering enzyme degradation when investigating material dynamics in forest ecosystems, including the impact of nutrient addition on enzyme activity, as enzyme production alone may not fully explain changes in apparent enzyme activity.

The integration of deep learning methods, especially Convolutional Neural Networks (CNN), and Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) has been widely deployed in the field of radar signal processing. Nevertheless, these methods are frequently regarded as black-box models due to the limited visual interpretation of their internal feature representation and parameter organization. In this paper, we propose an innovative approach named C-RISE, which builds upon the RISE algorithm to provide a post-hoc interpretation technique for black-box models used in SAR Images Target Recognition. C-RISE generates saliency maps that effectively visualize the significance of each pixel. Our algorithm outperforms RISE by clustering masks that capture similar fusion features into distinct groups, enabling more appropriate weight distribution and increased focus on the target area. Furthermore, we employ Gaussian blur to process the masked area, preserving the original image structure with optimal consistency and integrity. C-RISE has been extensively evaluated through experiments, and the results demonstrate superior performance over other interpretation methods based on perturbation when applied to neural networks for SAR image target recognition. Furthermore, our approach is highly robust and transferable compared to other interpretable algorithms, including white-box methods.

With the rapid development of the Internet of Things (IoT), there are dramatic increasing number of devices in the network, which causes the challenge that only using infrastructure such as based station cannot provide service with all devices with high quality. Therefore, due to their flexibility and economy, unmanned aerial vehicles (UAV) are widely used to increase the performance of IoT networks. UAVs can not only provide communication services for IoT devices in the absence of a network, but they can also perform video surveillance, cargo transportation, pesticide spraying, and other specialized tasks. However, due to the complexity of the scenario and the need for real-time decision making, it is challenging to schedule UAVs in the network using traditional optimization methods, and growing attention has focused on using AI to optimize UAVs in the network. In this paper, we focus on the AI-enabled UAV optimization method in IoT networks and give a comprehensive scope on what and how to use AI-enabled methods to increase the performance of UAV-assisted IoT networks. Moreover, a brief analysis of the challenges of using AI methods in IoT networks and some potential research directions are given.

Vehicle driveability is one of the important vehicle attributes in range-extender electric vehicles due to the electric motor torque characteristics at low-speed events. The process of validating and rectifying vehicle driveability attributes is typically utilised by a physical vehicle prototype that can be expensive and required several design iterations. In this paper, a model-based energy method to assess vehicle driveability is presented based on a high-fidelity 49 degree-of-freedom powertrain and vehicle systems. Multibody dynamics components were built according to their true centre of gravity relative to the vehicle datum for providing an accurate system interaction. The work covered a frequency at less than 20 Hz. The results that consisted of the component frequency domination are structured and examined to identify the low-frequency sensitivity based on different operating parameters such as a road surface coefficient. An energy path technique was also implemented on the dominant component by decoupling its compliances to study the effect on the vehicle driveability and low-frequency response. The outcomes of the research provided a good understanding of the interaction across the sub-systems levels. The powertrain rubber mounts were the dominant components that controlled the low-frequency contents (< 15.33 Hz) and can change the vehicle driveability quality.

Exercise training influences the risk of vascular thrombosis in patients with peripheral arterial disease (PAD). Mitochondrial functionalities in platelets involve the cellular bioenergetics and thrombogenesis. This study aimed to elucidate the effect of cycling exercise training (CET) on platelet mitochondrial bioenergetics in PAD patients. Forty randomly selected patients with PAD engaged in general rehabilitation (GR) with CET (i.e., cycling exercise at ventilation threshold for 30 min/day, 3 days/week) (GR+CET, n=20) or to a control group that only received GR course (n=20) for 12 weeks. Systemic aerobic capacity and platelet mitochondrial bioenergetics that included oxidative phosphorylation (OXPHOS) and electron transport system (ETS) were measured using automatic gas analysis and high-resolution respirometry, respectively. The experimental results demonstrated that GR+CET for 12 weeks significantly (i) elevated VO2peak and lowered VE-VCO2 slope, (ii) raised resting ankle-brachial index and enhanced cardiac output response to exercise, (iii) increased the distance in 6-minute walk test and raised the Short Form-36 physical/mental component scores, and (iv) enhanced capacities of mitochondrial OXPHOS and ETS in platelets by activating FADH2 (Complex II)-dependent pathway. Moreover, changes in VO2peak levels were positively associated with changes in platelet OXPHOS and ETS capacities. However, no significant changes in systemic aerobic capacity, platelet mitochondrial bioenergetics, and health-related quality of life (HRQoL) occurred following GR alone. Hence, we conclude that CET effectively increases the capacities of platelet mitochondrial bioenergetics by enhancing Complex II activity in patients with PAD. Moreover, the exercise regimen also enhanced functional exercise capacity, consequently improving HRQoL in PAD patients.

The manuscript reported the synthesis of Al2O3 nano-coating onto quartz fiber by plasma electrolysis spray for enhanced thermal conductivity and stability. The nano- and micro-sized clusters were partially observed on the coating, while most coating was relatively smooth. It was suggested that the formation of a ceramic coating was followed as the nucleation-growth raw, that is, the formation of the coating clusters was dependent on the fast grow-up partially, implying the inhomogeneous energy distribution in the electrolysis plasma. The deposition of the Al2O3 coating increased the annealing tensile strength from 19.2 MPa to 58.1 MPa. The thermal conductivity of the coated quartz fiber was measured to be 1.17 W m-1 K-1, increased by ~45% compared to the bare fiber. The formation mechanism of the Al2O3 coating was preliminarily discussed. We believe that the thermally conductive quartz fiber with high thermal stability by plasma electrolysis spray will find a wide range of applications in industries.

Torenia Concolor Lindley var. formosama Yamazaki ethanolic extract (TCEE) is reported to have anti-inflammatory and anti-obesity properties. However, the effects of TCEE and its underlying mechanisms in the activation of endothelial nitric oxide synthase (eNOS) have not yet been investigated. Increasing the endothelium-derived nitric oxide (NO) production has been known to be beneficial against the development of cardiovascular diseases. In this study, we investigated the effect of TCEE on eNOS activation and NO-related endothelial function and inflammation by using in vitro system. In endothelial cells (ECs), TCEE increased NO production in a concentration-dependent a manner without affecting the expression of eNOS. In addition, TCEE increased the phosphorylation of eNOS at serine 635 residue (Ser635) and Ser1179, Akt at Ser473, calmodulin kinase II (CaMKII) at threonine residue 286 (Thr286) and AMP-activated protein kinase (AMPK) at Thr172. Moreover, TCEE-induced NO production, and EC proliferation, migration and tube formation were diminished by pretreatment with LY294002 (an Akt inhibitor), KN62 (a CaMKII inhibitor) and compound C (an AMPK inhibitor). Additionally, TCEE attenuated the tumor necrosis factor-α-induced inflammatory response as evidenced by the expression of adhesion molecules in ECs and monocyte adhesion onto ECs. These inflammatory effects of TCEE were abolished by L-NG-nitroarginine methyl ester (a NOS inhibitor). Collectively, our findings suggest that TCEE confers protection from endothelial dysfunction by activating the Akt/CaMKII/AMPK/eNOS/NO signaling pathway.

Currently, data regarding optimal treatment modality, response, and outcome specifically for N3 head and neck cancer are lacking. This study aimed to compare the treatment outcomes between definitive concurrent chemoradiotherapy (CCRT) to the neck and upfront neck dissection followed by adjuvant CCRT. 93 N3 squamous cell carcinoma head and neck cancer patients were included. Primary tumor treatment was divided to definitive CCRT (CCRT group) or curative surgery followed by adjuvant CCRT (surgery group). Neck treatment was also classified into two treatment modalities: definitive CCRT to the neck (CCRT group) or curative neck dissection followed by adjuvant CCRT (neck dissection group). Overall, the 2-year overall survival (OS), local recurrence-free survival (LRFS), regional recurrence-free survival (RRFS), and distant metastasis-free survival (DMFS) were 51.8%, 47.3%, 45.6%, and 43.6%, respectively. In both oropharyngeal cancer and nonoropharyngeal cancer patients, in terms of OS, LRFS, RRFS or DMFS no difference was noted regarding primary tumor treatment (CCRT vs. surgery) or neck treatment (CCRT vs. neck dissection). In summary, N3 neck patients treated with definitive CCRT can achieve similar outcomes to those treated with upfront neck dissection followed by adjuvant CCRT. Cautions should be made to avoid overtreatment for this group of patients.

Background: Hypoalbuminemia is known to be associated with adverse outcome in critical illness. In this study, we attempted to identify if hypoalbuminemia on emergency department (ED) arrival a reliable predictor for in-hospital mortality in necrotizing fasciitis (NF). patients. Method: A retrospective cohort study of hospitalized patients with NF was conducted in a tertiary teaching hospital in Taiwan between March 2010 and March 2018. Blood samples were collected in the ED upon arrival, and serum albumin levels were determined. we evaluated the predictive value of serum albumin level at ED presentation for in-hospital mortality. All collected data were statistically analyzed. Result: Of the 707 NF patients, 40 (5.66%) died in the hospital. The mean serum albumin level was 3.1 ± 0.9 g/dL and serum albumin levels were significantly lower in the non-survivor group than in the survivor group (2.8± 0.7 g/dL vs. 3.5 ± 0.8 g/dL). In the multivariable logistic regression model, albumin was associated with in-hospital mortality significantly (odds ratio[OR] 0.92, 95% confidential interval (CI) 0.88–0.96, P <0.001). The area under-the-receiver-operating-characteristic curve (AUC) for in-hospital survival was 0.77 (95% CI 0.72–0.82) and corresponding sensitivity, specificity, positive predictive value, negative predictive value, positive and negative likelihood ratio were 66%, 74%, 33%, 88%, 2.25 and 0.48, respectively. High sensitivity (96%) was shown at albumin level of 4.0 g/dL and high specificity (91%) was shown at level of 2.5 g/dL. Conclusion: Initial serum albumin levels were independently associated with in-hospital mortality among adult patients with necrotizing fasciitis and demonstrated fair discriminative performance in the prediction of in-hospital mortality. NF patients with hypoalbuminemia on ED arrival should be closely monitored for signs of deterioration and consider early and aggressive intervention to prevent mortality.

This paper presents tea leaves moisture monitoring system based on RF reflectometry techniques. The system was divided into two parts which are the sensor and reflectometer parts. The large coaxial probe was used as a sensor of the system. The reflectometer part plays a role as signal generator and also data acquisition. The reflectometer-sensor system was operated with a graphical user interface at 1.529 GHz at room temperature. The system was able to measure the moisture content of tea leaves ranging 0% m.c to 50% m.c on a wet basis. In this study, up to five kinds of tea leaves bulk were tested. The mean of absolute errors in the moisture measurement for tea leaves was ±2.

Three new secoiridoid constituents Gonocarin A-C (1-3) and a new derivative Gonocarin A monoacetate (4), along with two known lignins pinoresinol (5) and paulownin (6) were isolated from the seed of Gonocaryum calleryanum (Baill.) Becc. The structures of the new metabolites were determined on the basis of extensive spectroscopic analysis, particularly mass spectroscopy and 2D NMR (1H–1H COSY, HMQC, HMBC, and NOESY) spectroscopy. When mouse macrophages RAW264.7 were treated with compounds 1-6 together with LPS -stimulated, a concentration-dependent inhibition of nitric oxide (NO) and tumor necrosis factor (TNF-α) productions were detected. The results confirmed that the Gonocaryum calleryanumrrg could be a potential anti-inflammatory agent.

China’s transportation industry has made rapid progress, which has led to a mass of carbon emissions. However, it is still unclear how the carbon emission from transport sector is punctuated by shifts in underlying drivers. This paper aims to examine the process of China’s carbon emissions from transport sector as well as its major driving forces during the period of 2000 to 2015 at the provincial level. We firstly estimate the carbon emissions from transport sector at the provincial level based on the fuel and electricity consumption using a top-down method. We find that the carbon emission per capita is steadily increasing across the nation, especially in the provinces of Chongqing and Inner Mongolia. However, the carbon emission intensity is decreasing in most provinces of China, except in Yunnan, Qinghai, Chongqing, Zhejiang, Heilongjiang, Jilin, Inner Mongolia, Henan and Anhui. We then quantify the effect of socio-economic factors and their regional variations on the carbon emissions using panel data model. The results show that the development of secondary industry is the most significant variable in both the entire nation level and the regional level, while the effects of the other variables vary across regions. Among these factors, population density is the main motivator of the increasing carbon emissions per capita from transport sector for both the whole nation and the western region, whereas the consumption level per capita of residents and the development of tertiary industry are the primary drivers of per capita carbon emissions for the eastern and central region.

Large-scale volumetric fracturing is generally used during shale gas development. The return rate of fracturing fluid is low, and a large amount of slickwater will be retained in the reservoir. The adsorption and desorption of partially hydrolyzed polyacrylamide (HPAM), an additive commonly used in slickwater, on the surface of shale was studied using Longmaxi Shale from the Sichuan Basin. The experimental results showed that the mass ratio of the HPAM solution to shale reached saturation adsorption at 20:1 when the concentration of HPAM solution was 1000 mg/L and 25:1 when the concentration of HPAM solution was 500 mg/L. The mass ratio of the HPAM solution to shale was fixed at 25:1, and the adsorption equilibrium was reached at a HPAM concentration of 1000 mg/L when the aqueous solution temperature was 30°C and 800 mg/L when the aqueous solution temperature was 60°C. The Langmuir adsorption model yielded a better fit than the Freundlich adsorption model. The adsorption equilibrium time at 30°C was at 60 min for a HPAM concentration of 500 mg/L, while for a concentration of 1000 mg/L, it was at 90 min. The adsorption equilibrium time at 60°C was 40 min for a HPAM concentration of 500 mg/L, whereas it was 60 min for a HPAM concentration at 1000 mg/L. The pseudo-second order kinetics model yielded better fits than the pseudo-first order kinetics model. The adsorption of HPAM on shale was strong, and the adsorbed HPAM resembled cobwebs adhering to the shale surface. HPAM on the surface of shale after adsorption could resist the desorption capacity of water. However, when the amount of adsorbed HPAM on shale increased significantly, the amount of residual HPAM on the surface of the shale decreased rapidly during desorption in deionized water. The desorption of HPAM on the shale surface followed a modified desorption model. The higher the concentration of HPAM adsorbed on the shale surface was, the easier it was to desorb, the easier it was to be removed from the shale.

CdZnTe (CZT) is a new type of compound semiconductor that has emerged in recent years. Compared to other semiconductor materials, it possesses an ideal bandgap, high density, and high electron mobility, rendering it an excellent room-temperature composite semiconductor material for X-ray and γ-ray detectors. Due to the exceptional performance of CZT material, detectors manufactured using it exhibit high energy resolution, spatial resolution, and detection efficiency. They also have the advantage of operating at room temperature. CZT array detectors, furthermore, demonstrate outstanding spatial detection and three-dimensional imaging capabilities. Researchers worldwide have conducted extensive studies on this subject. This paper, building upon this foundation, provides a comprehensive analysis of CZT crystals and CZT array detectors, summarizes existing research to offer valuable insights for envisioning new detector methodologies.

At present, failure definition and damage characteristic curve (DCC) analysis included in the framework to assess bitumen fatigue cracking performance have an inconsistency in ranking bitumen fatigue behaviour. This study utilized two types of self-healing polymers (STP and IPA1w) to modify the neat asphalt (NA), and research four different types of bitumens: NA, STP-modified bitumen, IPA1w-modified bitumen, and styrene-butadiene-styrene modified bitumen (SBSB), to evaluate the above-mentioned framework. All bitumens were subjected to short-term and long-term aging and tested utilizing the Linear amplitude sweep (LAS) test and simplified viscoelastic-continuum-damage (S-VECD) model. The results showed that the SBSB exhibited the highest numbers of loading cycles (in long-term aging analysis) to reach failure points at 25°C, 28°C, and 31°C which were 2290, 2340, and 2510, respectively. However, this bitumen failed to exhibit the best performance in terms of DCC assessment under the same conditions, confirming the above-mentioned inconsistency. Besides, the current failure criterion could not accurately predict bitumen fatigue behaviour under certain test conditions because two R2 values were below 0.1. As a result, this study proposed a new failure definition and failure criterion to overcome these issues. The proposed failure definition agreed with the DCC analysis to rank bitumen fatigue performance, and the proposed failure criterion showed R2 values higher than 0.9. The new framework presented the modified bitumen containing 0.5% of STP as the asphalt binder with the best fatigue cracking performance, according to the selected test conditions.

With the global warming and the frequent occurrences of harsh environments, mooring line failures are frequent. Response analysis of the platform structure and its residual mooring system under multiple mooring line failures is needed. Therefore, it is necessary to investigate the change law of platform motion response after mooring line failure to find out the reasons for the change. Studies for different failure combinations of mooring lines show that the variation of the steady-state equilibrium position of the platform is closely related to the stiffness, with a clear functional. The duration and amplitude of the transient response are mainly influenced by the Morison drag force. And it was found that the suspended mooring line reduced the motion responses. It is also found that the mooring line failure increased the effective tension and suspension length of the riser. Based on the improved Dezert-Smarandache theory (DSmT), it is calculated that mooring line failure has little effect on the failure probability in different zones of the riser.

The present study investigated the insulin-like growth factors (IGFs) and their receptors and binding proteins among different pig breeds during weaning. Sixty Duroc (DR), Taoyuan black (TB), and Xiangcun black (XB) piglets (20 piglets per breed) were selected at 21 and 24 days of age (three days of post-weaning) to analyze organ indices, plasma concentrations of IGF and IGF-binding proteins (IGFBPs) using ELISA kits, and gene expression of IGF system-related components in different tissues. The plasma IGFBP-3 level in TB piglets was higher (P > 0.05) than in the XB and DR piglets at 21 days of age. At 21 days of age, compared with the DR piglets, the IGF-1 expression was lower (P < 0.05) in the kidney but was higher (P < 0.05) in the spleen of XB and TB piglets. At 24 days of age, the IGF-1 expression was higher (P < 0.05) in the kidney of TB piglets than in the XB and DR piglets, while IGFBP-3 in the stomach and IGFBP-4 in the liver of XB and TB piglets were lower (P < 0.05) compared with the DR piglets. Weaning down-regulated (P < 0.05) the IGF-1 expression in the jejunum, spleen, and liver of piglets, while up-regulated (P < 0.05) IGFBP-3 expression in the stomach, IGFBP-4 in the liver, IGFBP-5 in the ileum, and IGFBP-6 in the jejunum of DR piglets. Spearman’s correlation analysis showed a negative correlation (P < 0.05) between plasma IGFBP-2 and IGFBP-5 and the organ index of piglets. Collectively, there were significant differences in IGF system components among different pig breeds. The IGF system components were altered during weaning, which might be involved in weaning stress to decrease the growth of piglets.

Selenium (Se) is an essential trace element for human beings and Se supplementation is of great significance. In this paper, high selenized Gastrodia elata Blume Polysaccharides (SeGEP) were obtained through pre-sulfation before conducting the selenylation modification process, which owned a maximum Se content reach to 2.29%. UV, FT-IR, NMR, SEM, EDX, HPLC, size-exclusion chromatography and periodate oxidation analysis showed that the seleninic group had been successfully introduced into GEP with the substitution position at C-6 of glucose. Immunostimulating assays were conducted in vitro and in vivo on RAW 264.7 cells and cyclophosphamide (CTX)-induced mice model, respectively. The results showed that Se-GEP enhanced RAW264.7 cells proliferation, cell phagocytosis, and secretion of nitric oxide (NO) and interleukin (IL)-1β factors. In addition, Se-GEP enhanced the immunologic activity of CTX-treated mice by increasing the spleen and thymus indices, enhancing the phagocytic function, and activating both Th1 and Th2 lymphocytes. The current outcome also suggested that Se-GEP with covalently bonding Se group possessing increased safety and has a potential dietary selenium nutrient for improving human immunity.

Plant endophytic fungi and rhizosphere soil fungi are often reported as biocontrol agents against plant pathogens or with plant growth promotion potential. Four treatments were performed in field and greenhouse experiments where cucumber plants were inoculated with Trichoderma harzianum and Fusarium oxysporum in 2022. The roots, stems and leaves of cucumber plants and their rhizosphere soil were collected twice individually from the field and greenhouse for isolation of cucumber endophytic and rhizosphere soil fungi. All 74 genera and 1275 fungal strains were sequenced by rDNA ITS. The PDA media yielded the highest number of genera isolated from cucumber plants, rhizosphere soil and both compared to other media. There were no significant differences among the 4 media for the isolation of cucumber endophytic fungi. The best media for isolating fungi from roots and stems were MRBA and PDA, respectively. PDA and CZA had higher isolation efficiency for the rhizosphere soil fungi than MRBA. The 28 fungal genera had high isolation efficiency, and the endophytic Trichoderma strains were best isolated by MEA. It is suggested that PDA can be used as a basic medium, and different media can be considered for specific fungal genera.

The most recent outbreak of 2019 novel coronavirus, named as COVID-19, caused pneumonia epidemic in Wuhan with 2,121 deaths cases as of February 20^th 2020. Identification of effective antiviral agents to combat the novel coronavirus is urgently needed. Citrus fruit peel or wild citrus are rich in flavonoid, and is clinically documented for roles in relief of cough and promotion of digestive health. Therefore, citrus fruits are assumed to possess antivirus activities or enhance the host immunity. A previous study found that hesperetin could act as a high potent inhibitor of SARS-CoV 3CLpro. We determined six flavonoid compounds content of in three citrus species by using LC-MS technique. The content of naringin and naringenin was at higher levels in pummelo. Hesperetin and hesperidin were highly accumulated in mandarin and sweet orange. The subsequent in vitro and in vivo experiments indicated that naringin could inhibit the expression of the proinflammatory cytokines (COX-2, iNOS, IL-1β and IL-6) induced by LPS in Raw macrophage cell line, and may restrain cytokine through inhibiting HMGB1 expression in a mouse model. The results revealed that naringin may have a potential application for preventing cytokine storm. We simulated molecular docking to predict the binding affinity of those flavonoids to bind Angiotensin-converting enzyme 2 (ACE 2), which is a receptor of the coronavirus. Consideration of the potential anti-coronavirus and anti-inflammatory activity of flavonoids, the citrus fruit or its derived phytochemicals are promising in the use of prevention and treatment of 2019-nCoV infection.

Transition-metal-catalyzed amide bond formation from alcohols and amines is an atom-economic and eco-friendly route. Herein, we identified a highly active in situ N-heterocyclic carbene (NHC)/ruthenium (Ru) catalytic system for this amide synthesis. Various substrates, including sterically hindered ones, could be directly transformed into the corresponding amides with the catalyst loading as low as 0.25 mol%. In this system, we replaced the p-cymene ligand of the Ru source with a relatively labile cyclooctadiene (cod) ligand so as to more efficiently obtain the corresponding poly-carbene Ru species. Expectedly, the weaker cod ligand could be more easily substituted with multiple mono-NHC ligands. Further HR-MS analyses revealed that two tetra-carbene complexes were probably generated from the in situ catalytic system.

Nasopharyngeal carcinoma (NPC) has not been thoroughly studied, and the pathogenesis of NPC is unclear. Scientists have neither discovered effective therapies nor achieved a desirable prognosis. Some studies have found that the regulation of intra- and extracellular ion channels hinges directly on cell apoptosis, and treatment with Gambogenic acid (GNA) brings changes to the volume-sensitive outwardly rectifying chloride (VSOR Cl-) current of CNE-2Z cells recorded by the patch clamp method. Nevertheless, rarely have any researchers probed into the relevance between this variation and the anti-tumor mechanism of GNA. This paper is suggested that GNA activates the VSOR Cl- current on the CNE-2Z cell membrane, and the activation of VSOR Cl- currents by GNA in CNE-2Z cells is blocked by the chloride channel blockers DIDS and DCPIB. GNA induces the down-regulation of GRP78 and up-regulation of ATF4 as well as chop proteins, which is evidence for the induction of CNE-2Z cell apoptosis, and this correlates with ER stress. GNA can activate the VSOR Cl- channel and lead to the occurrence of ER stress, thus inducing the apoptosis of CNE-2Z cells and inhibiting the proliferation of CNE-2Z cells.

Astragalus membranaceus (AM) and Panax ginseng (PG) are two herbal products with a long history of clinical usage in traditional Chinese medicine (TCM), used in treating a variety of diseases especially in stimulating or inhibiting the immune system. To elucidate the immunity effect of these two traditional Chinese medicine on animal model, four pharmacodynamic indexes (spleen index, thymus index, splenic lymphocyte proliferation and cytotoxic activity of natural killer (NK) cells) were observed on mice. Furthermore, metabolic profiles of plasma were also analyzed by ultra-performance liquid chromatography quadrupole-time-of-flight mass spectrometry (UPLC-Q/TOF-MS, LC-MS) method. All mice were intragastric administrated at three doses (low dose, moderate dose and high dose) once daily for 30 days. Principal components analysis (PCA) and orthogonal projection to latent structure discriminant analysis (OPLS-DA) were performed on LC-MS spectra of plasma, showing that all administration groups developed the disturbance of internal milieu, compared to the blank control (BC) group. Besides, correlation analysis was conducted between pharmacodynamic index and metabolic index. It indicated that uracil, lysoPC(18:3(6Z,9Z,12Z)), sphinganine, LPA(0:0/16:0), UDP-glucuronate, PC(14:0/18:0) were five main endogenous substances, much closely related to four immunological indexes. Glycerophospholipid metabolism was found in both AM and PG groups. Pyrimidine metabolism and sphingolipid metabolism were closely regulated in AM groups. Energy metabolism (starch and sucrose metabolism, Pentose and glucuronate interconversions, together with glycerolipid metabolism) and glycerolipid metabolism were found in PG groups. These findings could contribute to the understanding of mice plasmatic metabolic profiling after long-term administration. Comparative immune-related metabolomic analysis of AM and PG was obtained on the base of pathway analysis of immune-related biomarkers. PG groups trended to have effect on cytotoxic activity of NK cells. AM groups trended to effect thymus index. Our work provides a detailed interpretation of immunological characteristics in different traditional Chinese medicine on metabonomic level.

The morphological and compositional complexities of keratinized components make feathers ingenious skin appendages adapted to diverse ecological needs. Frizzling feathers, characterized by their distinct curling phenotypes, offer a unique model to explore the intricate morphogenesis in developing a keratin-based bioarchitecture over a wide range of morphospace. Here, we investigated the heterogeneous allocation of α- and β-keratins in flight feather shafts of homozygous and heterozygous frizzle chickens by analyzing the medulla-cortex integrations using quantitative morphology characterizations across scales. Our results reveal intriguing construction of frizzling feather shaft through modified medulla development, leading to a perturbed balance of the internal biomechanics and, therefore, introducing the inherent natural frizzling compared to those from wild-type chickens. We elucidate how the localized developmental suppression of the α-keratin in the medulla interferes with the growth of the hierarchical keratin organization by changing the internal stress in the frizzling feather shaft. This research not only offers insights into the morphogenetic origin of the inherent bending of frizzling feathers but also facilitates our in-depth understanding of the developmental strategies toward the diverse integuments adapted for ecological needs.

Applied talent is not only a builder of human civilization but also a promoter of economic development. They not only need systematic and solid engineering theoretical knowledge but also rich engineering practical experience. Applied undergraduate colleges are the cradle for cultivating applied talent and shoulder the important mission of cultivating various types of applied talent for society. With the rapid development of higher education, the number of applied undergraduate institutions has sharply increased, but the quality of applied talent cultivated by them has shown a significant decline, which greatly restricts the pace of industrial development in the world. This article proposes a new concept of promoting the "three certificates" (graduation certificate, degree certificate, and skill certificate) education model in applied undergraduate colleges, which is of great significance for the country to cultivate composite talents with the ability of "product design, production management, and product processing" at the same time.

Porcine sapovirus (PoSaV) is a significant pathogen causing diarrhea with high morbidity and mortality rates. Given its zoonotic characteristics, this study conducts a comprehensive genetic evolutionary analysis of PoSaV. Results confirmed PoSaV as the primary RNA virus in piglet feces (27.54%). Phylogenetic analysis identifies the prevalent PoSaV strain SHCM/Mega2023 in the GIII genogroup, involving a recombinant event with MK962338 and KT922089. The time tree revealed that the GIII genogroup exhibits the widest divergence time span, indicating a high likelihood of viral recombination. Further selective pressure calculations demonstrate that PoSaV was under purifying selection (dN/dS &lt; 1), with seven positively selected sites in VP1 protein which might be related to the antigencity. In conclusion, this study presents a novel genomic evolution of PoSaV, offering valuable insights into antigenicity and vaccine research.

In this paper, based on the pseudo-totem pole (PTP) circuit, a family of five-level PTP dual boost converters (PDBC) is proposed. Dual boost converter has some unique advantages such as no bridge arm shoot-through risk and no switch body diode reverse recovery problem, so that it has a good application prospect. Compared with conventional three-level PTP converters, PDBCs has higher power density, higher efficiency, and low voltage and current stress. The topological derivation process, working principle, modulation and strategy of the topology are analyzed firstly. Further, the number of power devices, the switches voltage and current stress of the proposed topology is analyzed. Finally, a representative five-level PDBC experimental prototype is designed with AC input 220V/50Hz, DC output 400V/1kW, and peak efficiency of 98.27%. The experimental results show that the five-level PDBC proposed in this paper has higher efficiency and verify the correctness of the topology.

We recently found that in human osteoblasts Homer1 complexes to CaSR and mediates AKT initiation via mTORC2 leading to beneficial effects in osteoblasts including -catenin stabilization and mTORC1 activation (doi: 10.1074/jbc.RA118.006587). Herein we further investigated the relationship between Homer1 and CaSR and demonstrate a link between the protein levels of CaSR and Homer1 in human osteoblasts in primary culture. Thus, when siRNA was used to suppress the CaSR, we observed upregulated Homer1 levels and when siRNA was used to suppress Homer1 we observed downregulated CaSR protein levels using immunofluorescence staining of cultured osteoblasts as well as western blot analyses of cell protein extracts. This finding was confirmed in vivo as the bone cells from osteoblast specific CaSR(-/-) mice showed increased Homer1 expression compared to wild-type. Furthermore, when the commonly used osteosarcoma cell lines MG63 and SAOS-2 were compared to primary osteoblasts, higher levels of Homer1 protein were associated with increased protein levels of the CaSR as well as mTOR and Rictor. CaSR and Homer1 protein were both expressed in osteocytes embedded in the long bones of wild-type mice, and immunofluorescent studies of these cells revealed that Homer1 protein sub-cellular localization was markedly altered in the osteocytes of CaSR(-/-) mice compared to wt. The study identifies additional roles for Homer1 in the control of the protein level and subcellular localization of CaSR in cells of the osteoblast lineage, in addition to its established role of mTORC2 activation downstream of the receptor.

The design, facilities and conditions inside a classroom play a significant role in the teaching and learning experience for both students and lecturers. Prior studies of primary schoolchildren indicate three design principles affecting student learning, namely: naturalness, individualisation and stimulation. The current study extends these investigations to Higher Education through a survey of undergraduate students and university lecturers aimed at determining the most critical factors in undergraduate classroom design. One-to-one interviews were conducted with students and lecturers (n. 31) at the University of Nottingham, Malaysia Campus. Interviewees were encouraged to express their opinions, comments, concerns and suggestions through open-ended questions. The interviews were recorded and then transcribed and coded using NVivo10. Results show a strong desire among lecturers and students for improved classroom equipment, greater flexibility in classroom arrangement, more attractive decoration and for the addition of natural elements to the classroom environment. Of the three design principles, individualisation and naturalness emerged most strongly from the interviews and appear to be more important factors for undergraduates than stimulation. These findings could make a novel and significant contribution to the physical aspects of classroom design in Higher Education settings. Educational institutions are increasingly employing non-traditional classroom designs, which are expected to provide for more flexible, collaborative, and active learning and teaching experiences. Taking into consideration the environmental psychology of teaching and learning, several of the reported design attributes can serve as benchmarks for upgrading current classroom design and facilities in the future, as institutions look to upgrade their physical infrastructures to meet the changing demands of teachers and learners arising from technological innovations and shifts in our understanding of the methods and purposes of Higher Education.

It is always a difficult task to assign the peaks recorded from vibrational spectrum. Herein we explored a new pathway of density functional theory (DFT) simulation to present three kinds of spectra of ice XIV and can be referenced as inelastic neutron scattering (INS), IR, and Raman experimental spectrum. The INS spectrum is proportional to phonon density of states (PDOS) while the photon scattering signals reflect the normal vibration frequencies near the Brillouin zone (BZ) center. Based on good agreements with experimental data, we identified the relative frequency and made scientific assignments by normal vibration modes analysis. The debating two hydrogen bond (H-bond) peaks among ice phases from INS have been discussed and the dynamic process of H-bond vibrations were found to be classified into two basic modes. we deduce that two H-bond modes are a general rule among ice family and more works are ongoing to investigate this subject.

Fracture grouting has been a widely used mitigation measure against seepage in the Yellow River Embankment. However, there is currently a lack of systematic investigation for evaluating the anti-seepage effectiveness of fracture grouting employed in this longest river embankment in China. Therefore, in this work, laboratory and in-situ experiments are carried out for investigating the reinforcement effect of fracture grouting in the Jinan Section of the Yellow River Embankment. In particular, firstly, the laboratory tests concentrate on studying the optimum strength improvement for cement-silicate grout by varying the content of backfilled fly ash and bentonite as admixtures. Flexural strength and Scanning Electron Microscope photographs are investigated for assessing the strength and compactness improvement. Subsequently, based on the obtained optimum admixtures content, in-situ grouting tests are carried out in the Jinan Section of the Yellow River Embankment to evaluate the anti-seepage effectiveness of fracture grouting, where geophysical prospecting and pit prospecting methods are employed. Laboratory results show that, compared with pure cement-silicate grouts, the gelation time of the improved slurry is longer and gelation time increases as fly ash content increases. The optimum mixing proportion of the compound cement-silicate grout is 70% cement, 25% fly ash and 5% bentonite, and the best volume ratio is 2 for the investigated cases. Geophysical prospecting using the Ground Penetrating Radar and High Density Resistivity methods can reflect the anti-seepage effectiveness of fracture grouting on site. It shows that the grouting material mainly flows along the axial direction of the embankment. The treatment that is used to generate directional fracture is proved to be effective. The injection hole interval distance is suggested to be 1.2 m, where the lapping effect of the grouting veins is relatively significant. For the investigated cases, the average thickness of the grouting veins is approximately 6.0 cm and the corresponding permeability coefficient is averagely 1.6 × 10⁻⁶ cm/s, which meets the anti-seepage criterion in practice.

This paper develops a novel energy universal service bus system (EUSBS) based on emerging energy Internet (E-net) technologies. This EUSBS is a unified identification and plug-and-play interface platform to which high penetration distributed energy and equipment (DEE), including photovoltaic (PV), fans, electric vehicle charging stations (EVCSs), energy storage equipment (ESE), and commercial and residential users (CRUs), can access in a coordinated control and optimized utilization mode. First, the functions design, overall framework and topology architecture design of the EUSBS are expounded, among which the EUSBS is mainly composed of a hardware system and a software platform. Moreover, several future application scenarios are presented. Then, the hardware part of EUSBS is designed and developed, including the framework design of this hardware subsystem, and development of the hardware equipment for PV access, fans access, EVCS access, ESE access, and CRU access. The hardware subsystem consists of smart socket, and household/floor/building concentrators. Based on this, the prototypes development of EUSBS hardware equipment is completely demonstrated. Third, the software part of the EUSBS is developed as a cloud service platform for electricity use data analysis of DEE. This software subsystem contains the power quality & energy efficiency analysis module, optimization control module, information and service module, and data monitoring and electricity behavior analysis module. Based on this design, the software interfaces are developed. Finally, an application study on energy management and optimization of a smart commercial building is conducted to evaluate the functions and practicality of this EUSBS. The EUSBS developed in this paper is able to overcome difficulties in big data collection and utilization on sides of distribution network and electricity utilization, and eventually implement a deep information-energy fusion and a friendly supply-demand interaction between the grid and users. This contribution presents a detailed and systematic development scheme of the EUSBS, and moreover, the laboratory prototypes of the hardware and software subsystems have been developed based on E-net technologies. This paper can provide some thoughts and suggestions for the research of active distribution network and comprehensive energy management and optimization in power systems, as well as references and guidance for researchers to carry out research regarding energy management, optimization and coordinated control of the smart buildings.

The study aims to explore gender differences in smoking and drinking in three Asian cities—Hanoi, Shanghai and Taipei, and assesses the magnitude of these gender differences across cities. A total of 17,016 adolescents and young adults, aged 15 to 24 years, residing in both urban and rural area of Hanoi, Shanghai and Taipei were selected by multistage sampling methods and surveyed by face to face interview. The gender differences are significant for smoking-only, drinking-only, and both behaviors in each city. With respect to smoking-only, males are more than 30.66 times as likely to report it compared with females in Hanoi, followed by Shanghai and Taipei. The above trend holds true when further examining drinking-only and both smoking and drinking. The magnitude of gender differences in smoking-only, drinking-only, and both behaviors widely vary across the three cities. Future research is needed to further examine the mechanisms behind these gender differences and how these differences may be utilized to prevent and reduce smoking and drinking in the adolescent and young adult population.

Oil-Gan, also known as emblica, is the fruit of the genus Phyllanthus emblica L. The fruits of these trees are high in nutrients and have excellent effects on health care and development values. There are many methods for the management of diabetic nephropathy (DN). However, there is a lack of effective drugs for treating DN from throughout the disease course. The primary aim of this study was to examine the protective effects (including urine analyses, the measurement of inflammatory cytokine levels, and histological examination) and mechanisms of action of an ethyl acetate extract of P. emblica (EPE) on db/db mice, an animal model of diabetic nephropathy, as well as a secondary aim of examining the expression levels of protein kinase Cα (PKCα) in the kidney and its downregulation of vascular endothelial growth factor (VEGF) and fibrosis gene transforming growth factor-β1 (TGF-β1) by Western blot analyses. Eight db/m C57BLKS/J mice were used as the control group. Forty db/db mice were randomly divided into five groups. Treatments included vehicle, EPE1, EPE2, EPE3 (at doses of 100, 200, or 400 mg/kg EPE), or the comparative drug aminoguanidine for 8 weeks. After 8 weeks of treatment, blood samples were collected for analyses of blood glucose, insulin, and HbA1c levels, and pancreatic and kidney tissues were dissected for histological analyses. The present study indicated that the administration of EPE to db/db mice effectively controlled hyperglycemia and hyperinsulinemia by markedly lowering blood glucose, insulin, and glycosylated HbA1c levels. Administration of EPE to db/db mice decreased the levels of BUN and creatinine both in blood and urine and reduced urinary albumin excretion and the albumin creatine ratio (UACR) in urine. Moreover, EPE treatment decreased the blood levels of inflammatory cytokines, including kidney injury molecule-1 (KIM-1), C-reactive protein (CRP), and NLR family pyrin domain containing (NLRP3). Our findings showed that EPE not only had antihyperglycemic effects but also improved renal function in db/db mice. Histological examination of the kidney by immunohistochemistry indicated that EPE can improve kidney function by ameliorating glomerular morphological damage following glomerular injury; alleviating proteinuria by upregulating the expression of nephrin, a biomarker of early glomerular damage; and inhibiting glomerular expansion and tubular fibrosis. Moreover, the administration of EPE to db/db mice increased the expression levels of p- PKCα/t-PKCα but decreased the expression levels of VEGF and renal fibrosis biomarkers (TGF-β1, collagen IV, p-Smad2, p-Smad3, and Smad4), as shown by Western blot analyses. These results implied that EPE as a supplement has a protective effect against renal dysfunction through the amelioration of insulin resistance as well as the suppression of nephritis and fibrosis in a DN model.

Since the outbreak of the COVID-19 pandemic, patients infected with COVID-19 may experience abnormal heart rates, posing potential health risks. This study proposes a non-contact method for measuring heart rate (HR) and heart rate variability (HRV) to effectively reduce the risk of infection and assist healthcare professionals in more accurate diagnosis and treatment. In this study, except for the different image acquisition method, other research processes and methods are similar to the research methods in [15]. The image acquisition method is changed from forehead image to palm image. The new non-contact measurement performance of the proposed method can effectively not only avoid infection concerns but also obtain heart rate and HRV quickly and conveniently, providing higher accuracy for physiological parameters, root mean square error (RMSE), and mean absolute percentage error (MAPE) compared to those in recently published papers.

The dual-station Interferometric Synthetic Aperture Radar (InSAR) system can overcome the physical limitations imposed by the baseline of single-station dual-antenna InSAR. It provides greater flexibility and can enhance elevation measurement accuracy through a well-designed baseline configuration.Unmanned aerial vehicles (UAV) equipped with dual-station InSAR, with relatively low cost and high flexibility, are useful for mapping and land resource exploration. However, due to challenges including spatiotemporal synchronization and motion errors, there are limited reports on UAV-borne dual-station InSAR. This paper proposes a comprehensive method for processing data from small UAV-borne dual-station InSAR by integrating two-way synchronization chain signals. The proposed method includes compensation for time and phase synchronization errors, trajectory refinement with synchronized chain and Position and Orientation System (POS) data, high-precision dual-station InSAR imaging and interferometric processing. Height inversion results based on the proposed method is also provided, demonstrating the effectiveness of the proposed method and improving interferometric accuracy at calibration points from 0.66 meters to 0.42 meters.

For underwater vehicles navigating in Arctic Sea ice-covered waters, fatigue damage is a crucial issue. Many scholars have conducted low-temperature fatigue analysis on low-temperature ma-terials and substrate platforms for ships, and the results show that low-temperature is beneficial for improving the mechanical properties of materials. However, they mainly focus on low-temperature performance experiments and simulation analysis of standard components of materials, and there are very few fatigue life experimental studies on underwater vehicle me-chanical structures. This paper conducts experimental investigations on a scaled model of an underwater vehicle rudder mechanism in a polar environment laboratory. Using a comparative analysis method involving simulations and experiments, the low-temperature fatigue test data of the scaled underwater vehicle rudder mechanism are analyzed, and the quantified analysis be-tween fatigue and different low-temperature loading cycles, as well as the influence of icing on the fatigue life, is explored. It is indicated that the arctic environment can decrease the fatigue life of the underwater vehicle rudder mechanism by deteriorating its material properties. The paper builds the foundation for the fatigue life of an underwater vehicle rudder mechanism in arctic low-temperature environments.

Age-related macular degeneration (AMD) is a leading cause of blindness worldwide. In late-stage AMD, geographic atrophy (GA) of dry AMD or choroidal neovascularization (CNV) of neovascular AMD results in macular atrophy (MA), leading to significant visual loss. Despite the development of innovative therapies, there are currently no established effective treatments for MA. As a result, early detection of MA is critical in identifying later central macular involvement throughout time. Accurate and early diagnosis is achieved through a combination of clinical examination and imaging techniques. Our review of the literature depicted advances in retinal imaging to identify biomarkers of progression and risk factors for late AMD. Imaging methods like fundus autofluorescence (FAF), near-infrared reflectance (NIR), widefield imaging, optical coherence tomography (OCT), multicolor confocal scanning laser ophthalmoscopy (cSLO), and optical coherence tomography angiography (OCTA) can be used to detect and monitor the progression of retinal atrophy. Multifocal electroretinogram (ERG) and microperimetry are methods for quantifying visual function to map disease progression. The evolving diverse imaging modalities optimize detection of pathology anatomy and measurement of visual function; they may also contribute to the understanding of the underlying mechanistic pathways, particularly the underlying MA changes in late AMD.

Continuous greenhouse gas emissions are causing global warming and impacting the habitats of many animals. Researchers in the field of electric power are making efforts to mitigate this situation. Operating and maintaining the power grid in an economic, low-carbon, and stable is challenging. To address the issue, we propose a grid dispatching technique that combines prediction technology, reinforcement learning, and optimization technology. Prediction technology can forecast future power demand and solar power generation, while reinforcement learning and optimization technology can make charging and discharging decisions for energy storage devices based on current and future grid conditions. In the power system, the aggregation of distributed energy resources increases uncertainty, particularly due to the fluctuating generation of renewable energy. This requires the use of advanced predictive control techniques to ensure long-term economic and decarbonization goals. In this paper, we present a real-time dispatching framework that integrates deep learning-based prediction, reinforcement learning-based decision-making, and stochastic optimization techniques. The framework can rapidly adapt to target uncertainty caused by various factors in real-time data distribution and control processes. The proposed framework achieved global Champion in the NeurIPS Challenge 2022 competition and demonstrated its effectiveness in practical scenarios of intelligent building energy management.

Emerging evidence demonstrated that using a new manufacturing technology to produce γ-aminobutyric acid (GABA)-fortified oolong (GO) tea could relieve human stress and exert versatile physiological benefits. The purpose of this human research aims to investigate therapeutic effects of daily GO tea consumption on the improvement of blood pressure, relaxation-related brain waves and quality of life (QOL) during a period of 28 consecutive days. Total polyphenols, major catechins and free amino acids were analyzed via HPLC assay. Changes of heart rate, blood pressure, α-brain wave (index of relaxation) and eight-item QOL score were investigated on day 0, 7, 14, 21 and 28, respectively. The chemical analysis results showed that GO tea contained the most abundant amino acids and GABA, contributing to the relaxation activity. Among all study participants, daily drinking GO tea could reduce systolic blood pressure on day 21 and diastolic blood pressure on day 28 (p &lt; 0.05, respectively). For participants with pre-hypertension, GO tea could effectively reduce heart rate, systolic and diastolic blood pressure on day 28 (p &lt; 0.05). At the end of the study, incremental changes in alpha-brain wave and QOL scores were also demonstrated (p &lt; 0.05, respectively). This study recommended that GO tea might potentially serve as a natural source of alternative therapy to benefit blood pressure, stress-relief and QOL.

Vitamin E, a potent antioxidant, is a necessary and complex micronutrient for cows. During the transition period, vitamin E deficiency (VED) is among the highest prevalent micronutrient deficits in dairy cows. It may eventually result in oxidative stress and immunological malfunction, and it increases the risk of peripartum disorders. At present, detailed data on blood metabolites in VED cows are limited. Consequently, the purpose of this research was to examine the alterations in the serum metabolic profile of VED cows throughout the early postpartum period. Using comprehensive 1H nuclear magnetic resonance (1H NMR), the alterations in serum metabolic activities of VED cows were analyzed. In total, 28 multiparous Holstein cows were assigned according to serum α-tocopherol (α-Toc) concentrations into a normal (α-Toc ≥ 4 μg/mL, n = 14) and VED (α-Toc &lt; 3 μg/mL, n = 14) groups at 21 days postpartum, and their blood samples were collected for biochemical and 1H NMR analyses. A t-test on independent samples as well as multivariate statistics were used to assess the findings. In comparison with normal cows, VED cows showed significantly worse body condition scores, milk yield, and dry matter intake (p &lt; 0.05). Significantly higher levels of serum non-esterified fatty acids, aspartate aminotransferase, low-density lipoprotein, and malonaldehyde were found in VED-affected cows, as well as lesser concentrations of serum albumin, high-density lipoprotein, and total antioxidant capacity in comparison with normal cows (p &lt; 0.01), while other vitamins and minerals concentrations showed no distinction between the groups (p &gt; 0.05). Furthermore, 24 upregulated serum metabolites were identified under VED conditions. The metabolomics pathway analysis of these metabolites demonstrated that a global metabolic response to VED in cows was represented by changes in 11 metabolic pathways, comprising energy, carbohydrate, and amino acid metabolism. These outcomes suggest that VED cows were more likely to experience a negative energy balance characterized by alterations of common systemic metabolic processes and develop oxidative stress, inflammation, and ultimately liver injury. This study provides the first evidence of metabolic changes in cows with VED.

In response to the structural optimization problem of PCB stator coreless disc motors, the orthogonal response surface method was used to optimize the motor structure, determine the basic parameters of the motor preliminarily, and conduct orthogonal experiments on the motor parameters based on the optimization design objectives, The optimization factors were the quantity of magnetic pole of the motor rotor, the ratio of main/auxiliary pole size, the thicknessof the permanent magnet, and the air gap length.The motor torque，the amplitude of magnetic density of the air gap and waveform distortion rateare used as optimization objectives. The motor parameters that make the motor torque reach the maximum, the air gap magnetic density maximum, and the waveform distortion rate minimum. Due to the use of PCB plates instead of motor stator cores in PCB coreless disc motors,The service life of the PCB board during motor operation will be reduced with the temperature rise generated by the stator winding To solve this problem, the response surface analysis of the motor is carried out to reduce the temperature rise of the stator windings during the operation of the motor. PCB board and stator winding are the main factors affecting the temperature rise of the motor.Taking the thickness of the PCB board, the hole diameter on the board, and the uneven width of the stator winding as optimization factors, the motor parameters with the lowest temperature rise of the motor winding are obtained. Simulation analysis is conducted using Ansys/Maxwell software, and the results prove the feasibility of optimization.

The structural stability of γ-boron is investigated using Raman spectra under high pressures up to 126 GPa at ambient temperature. The pressure dependence of all the Raman-active modes of the γ-boron is reported. We also observe amusing changes within the B3g and B1g Raman-active vibrational modes, which results in the phenomenon of merging first and then separating of the Raman peaks. In addition to the Raman measurements, the changes in crystal structure and force constants are calculated to reasonably explain the discrepancy between the two Raman modes in response to pressure. The results of the continuous shifts for all Raman modes with increasing pressure indicate that γ-boron remains stable below this pressure value, with no changes in either symmetry or structure.

Hepatitis B is a potentially life-threatening infectious disease caused by the hepatitis B virus (HBV), which affects the liver. Every year, about 390,000 people die from HBV-related diseases in China, about 86 million people are carriers of HBV, accounting for about 6% of the total population, and 30 million people are chronically infected. From 2002 to 2007, though China government launched “The Global Alliance for Vaccines and Immunization (GAVI)” program to reduce HBV infection in children, but the number of hepatitis B cases in China remains high. Reasonable estimation of potential HBV carriers is crucial to prevention and control the spread hepatitis B virus. This study is based on the case data from the National Bureau of Statistics of China from 2003 to 2021. We build a dynamic model that includes potential hepatitis B virus carriers, use nonlinear least squares and genetic algorithms to fit the parameters in the model, and calculate the reproduction number of hepatitis B virus transmission in the population and obtain R_c=1.741. The number of potential hepatitis B virus carriers is estimated to be 449,535 (95%CI [415651 to 483420]) based on our model, which is 30.49% of the total number of hepatitis B cases, and the simulation results show the number of chronic hepatitis B incidence decreases as the vaccination rate α increases, increasing α by 20%, the number of chronic hepatitis B incidence decreases by 169,469 on average.

In Taiwan, peanuts are classified by hand. The kernel quality is judged based on the appearance of peanuts. The identification takes considerable time and labor. Fatigue can induce misrecogni-tion or grade cognition instability due. Peanut defects are generally divided into health, underde-velopment, insect bite, and rupture. This study employed two imaging methods push-boom FX10 and Snapshot. Deep learning was used to detect peanut defects. A push-broom instrument was used for testing. There were 1,560 peanuts, including 240 good and 240 bad ones. There were a total of 1,080 good peanuts and bad peanuts in the test set data, the band selection was used, and a CNN model was built. Based on the results from three methods, 3DCNN could classify with 97%accuracy. The Snapshot was used to achieve the real-time design of a lightweight CNN model. Finally, five bands were selected using PCA, and the screening could be accurate and efficient. The maximum overall accuracy was about 98.5%. Kappa was 97.3% with real-time recognition. This will be a major advantage in the future practical application and commercialization processes. This technique can reduce labor costs, achieve intelligent detection and intelligent grading, and bring breakthroughs to smart agriculture for other crops as well.