We investigate the use of amplitude amplification on the gate-based model of quantum computing as a means for solving combinatorial optimization problems. This study focuses primarily on quadratic unconstrained binary optimization (QUBO) problems, which are well-suited for qubit superposition states. Specifically, we demonstrate circuit designs which encode QUBOs as ‘cost oracle’ operations $U_{\mathrm{C}}$, which distribute phases across the basis states proportional to a cost function. We then show that when $U_{\mathrm{C}}$ is combined with the standard Grover diffusion operator $U_{\mathrm{s}}$, one can achieve high probabilities of measurement for states corresponding to optimal and near optimal solutions while still only requiring O($\frac{\pi }{4}\sqrt{2^N/M}$) iterations. In order to achieve these probabilities, a single scalar parameter $p_{\mathrm{s}}$ is required, which we show can be found through a variational quantum–classical hybrid approach and can be used for heuristic solutions. Full article

The Tibetan Plateau, known as the “Roof of the World” and “The Third Pole," harbors numerous saline lakes primarily distributed in the Northern Tibetan Plateau. However, the challenging conditions of high altitude, low oxygen level, and harsh climate have limited investigations into the actinobacteria from these saline lakes. This study focuses on investigating the biodiversity and bioactive secondary metabolites of cultivable actinobacteria isolated from the sediments of four saline lakes on the Northern Tibetan Plateau. A total of 255 actinobacterial strains affiliated with 21 genera in 12 families of 7 orders were recovered by using the pure culture technique and 16S rRNA gene phylogenetic analysis. To facilitate a high-throughput bioactivity evaluation, 192 isolates underwent OSMAC cultivation in a miniaturized 24-well microbioreactor system (MATRIX cultivation). The antibacterial activity of crude extracts was then evaluated in a 96-well plate antibacterial assay. Forty-six strains demonstrated antagonistic effects against at least one tested pathogen, and their underlying antibacterial mechanisms were further investigated through a dual-fluorescent reporter assay (pDualrep2). Two Streptomyces strains (378 and 549) that produce compounds triggering DNA damage were prioritized for subsequent chemical investigations. Metabolomics profiling involving HPLC-UV/vis, UPLC-QTOF-MS/MS, and molecular networking identified three types of bioactive metabolites belonging to the aromatic polyketide family, i.e., cosmomycin, kidamycin, and hedamycin. In-depth analysis of the metabolomic data unveiled some potentially novel anthracycline compounds. A genome mining study based on the whole-genome sequences of strains 378 and 549 identified gene clusters potentially responsible for cosmomycin and kidamycin biosynthesis. This work highlights the effectiveness of combining metabolomic and genomic approaches to rapidly identify bioactive chemicals within microbial extracts. The saline lakes on the Northern Tibetan Plateau present prospective sources for discovering novel actinobacteria and biologically active compounds. Full article

OTT (over-the-top) streaming is a subscription-based video service model that delivers video-on-demand content, films, and series directly to end-users over the Internet, bypassing the need for traditional satellite receiver systems. The most popular OTT service providers include Netflix, Hulu, Amazon Prime, and Disney+. During the COVID-19 pandemic, the viewership rates and subscriber numbers for OTT platforms rapidly increased. Like various other products and systems, usability problems can substantially impact user satisfaction, loyalty, and the intention to continue using OTT services. Therefore, this study aimed to conceptualize the usability of OTT platforms and develop an OTT Usability Measurement Scale for the usability evaluation of OTT platforms based on the Apple tvOS Guidelines and the literature. OTT platform usability was conceptualized with nine constructs, including Accessibility and Customization, Account Management, Data Entry and Search, Branding, Privacy, Navigation, Help, Content, and Design, and the concepts were measured with a scale including 48 items. The validity of the developed scale was tested through two separate survey studies conducted with Netflix web application users. The first survey involved 650 participants. At this stage, an exploratory factor analysis was used to evaluate the scale’s measurement properties, and the developed factor structure was confirmed. In the second stage, a survey with 600 participants was conducted, and a confirmatory factor analysis was applied to validate the scale properties. Furthermore, a nomological validation of the developed scale was performed, examining the relationship between the acquired OTT factors and elements such as continued intention to use, satisfaction, and brand loyalty. As a result of the nomological validation, it was observed that the privacy and design factors significantly affected each of the three dependent variables. Full article

High-quality development of agricultural and rural areas is the foundation of national modernization and sustainable development in China. Therefore, the evaluation of the degree of development of modernization of China’s agricultural and rural areas and the summarization of its main characteristics are crucial. However, studies on rural modernization and coordinated development are limited. Here, we developed a statistical evaluation system to effectively identify and assess the levels of agricultural and rural modernization, urban–rural integration, and agricultural rural coordination. We found that agricultural and rural modernization in China has continued to improve, but low scores were attributed to the factors of coordinated development of urban–rural areas, livable ecological environment, farmer prosperity, industrial structure upgrade, and resource allocation efficiency, limiting high-quality agricultural and rural development. Agricultural and rural modernization is lower in the central and western regions, compared to that in the eastern regions, but it is picking up the pace, indicating convergence. Rural modernization is lower than agricultural modernization and the two subsystems are not sufficiently coordinated, especially in undeveloped areas. Furthermore, the regional differences in rural modernization are greater than those in agricultural modernization. The system developed here can provide valuable experience for developing countries to open new paths toward modernization. Full article

A permanent magnet synchronous motor (PMSM) is a nonlinear, strongly coupled, controlled object with time-varying, fractional-order characteristics. It is difficult to achieve the ideal control effect by using the traditional control method when motor parameter changes and load perturbations occur during the operation of the PMSM, so a fractional-order adaptive fuzzy backstepping control method is proposed to improve the system’s fast response and anti-jamming ability in the case of sudden changes in rotational speed, load perturbations and other conditions. Initially, the fractional order theory is introduced, backstepping control is utilized to decompose the system into multiple subsystems, and a fractional order-based Lyapunov function is designed for each subsystem to ensure the system’s stability. Suitable control laws, as well as parameter adaptive laws, are derived through rigorous mathematical derivation. Finally, a fractional order adaptive fuzzy backstepping controller (FOAB-FPID) is designed by combining the advantages of fuzzy control. Then a mechanical simulation model of the PMSM is established to verify the validity of the designed controller, followed by three sets of comparative experiments: PID, fuzzy PID (F-PID), and integer-order adaptive fuzzy backstepping (IOAB-FPID), which are selected to simulate the PMSM under the control of the four controllers. Finally, it is validated on the constructed PMSM experimental platform. Simulation and experimental results show that FOAB-FPID can adaptively adjust system parameters during sudden speed changes, achieve real-time speed tracking, and maintain speed stability under load perturbations and internal parameter uptake. Compared with the three control strategies, reached PMSM system has better acceleration, fast response performance, and better anti-disturbance ability, which proves the rationality and effectiveness of the FOAB-FPID control method. Full article

Endometrial cancer (EC) is the second most common malignancy of the female reproductive system worldwide. The updated EC classification emphasizes the significant role of various signaling pathways such as PIK3CA-PIK3R1-PTEN and RTK/RAS/β-catenin in EC pathogenesis. Some of these pathways are part of the EGF system signaling network, which becomes hyperactivated by various mechanisms and participates in cancer pathogenesis. In EC, the expression of ErbB receptors is significantly different, compared with the premenopausal and postmenopausal endometrium, mainly because of the increased transcriptional activity of ErbB encoding genes in EC cells. Moreover, there are some differences in ErbB-2 receptor profile among EC subgroups that could be explained by the alterations in pathophysiology and clinical behavior of various EC histologic subtypes. The fact that ErbB-2 receptor expression is more common in aggressive EC histologic subtypes (papillary serous and clear cell) could indicate a future role of ErbB-targeted therapies in well-defined EC subgroups with overexpression of ErbB receptors. Full article

Our objective is to develop a video reflection removal algorithm that is both easy to compute and effective. Unlike previous methods that depend on machine learning, our approach proposes a local image reflection removal technique that combines image completion and lighting compensation. To achieve this, we utilized the MSER image region feature point matching method to reduce image processing time and the spatial area of layer separation regions. In order to improve the adaptability of our method, we implemented a local image reflection removal technique that utilizes image completion and lighting compensation to interpolate layers and update motion field data in real-time. Our approach is both simple and efficient, allowing us to quickly obtain reflection-free video sequences under a variety of lighting conditions. This enabled us to achieve real-time detection effects through video restoration. This experiment has confirmed the efficacy of our method and demonstrated its comparable performance to advanced methods. Full article

Polarimetric synthetic aperture radar (PolSAR) image classification has been an important area of research due to its wide range of applications. Traditional machine learning methods were insufficient in achieving satisfactory results before the advent of deep learning. Results have significantly improved with the widespread use of deep learning in PolSAR image classification. However, the challenge of reconciling the complex-valued inputs of PolSAR images with the real-valued models of deep learning remains unsolved. Current complex-valued deep learning models treat complex numbers as two distinct real numbers, providing limited assistance in PolSAR image classification results. This paper proposes a novel, complex-valued deep learning approach for PolSAR image classification to address this issue. The approach includes amplitude-based max pooling, complex-valued nonlinear activation, and a cross-entropy loss function based on complex-valued probability. Amplitude-based max pooling reduces computational effort while preserving the most valuable complex-valued features. Complex-valued nonlinear activation maps feature into a high-dimensional complex-domain space, producing the most discriminative features. The complex-valued cross-entropy loss function computes the classification loss using the complex-valued model output and dataset labels, resulting in more accurate and robust classification results. The proposed method was applied to a shallow CNN, deep CNN, FCN, and SegNet, and its effectiveness was verified on three public datasets. The results showed that the method achieved optimal classification results on any model and dataset. Full article

Winter wheat is a major food source for the inhabitants of North China. However, its yield is affected by drought stress during the growing period. Hence, it is necessary to develop drought-resistant winter wheat varieties. For breeding researchers, yield measurement, a crucial breeding indication, is costly, labor-intensive, and time-consuming. Therefore, in order to breed a drought-resistant variety of winter wheat in a short time, field plot scale crop yield estimation is essential. Unmanned aerial vehicles (UAVs) have developed into a reliable method for gathering crop canopy information in a non-destructive and time-efficient manner in recent years. This study aimed to evaluate strategies for estimating crop yield using multispectral (MS) and hyperspectral (HS) imagery derived from a UAV in single and multiple growth stages of winter wheat. To accomplish our objective, we constructed a simple linear regression model based on the single growth stages of booting, heading, flowering, filling, and maturation and a multiple regression model that combined these five growth stages to estimate winter wheat yield using 36 vegetation indices (VIs) calculated from UAV-based MS and HS imagery, respectively. After comparing these regression models, we came to the following conclusions: (1) the flowering stage of winter wheat showed the highest correlation with crop yield for both MS and HS imagery; (2) the VIs derived from the HS imagery performed better in terms of estimation accuracy than the VIs from the MS imagery; (3) the regression model that combined the information of five growth stages presented better accuracy than the one that considered the growth stages individually. The best estimation regression model for winter wheat yield in this study was the multiple linear regression model constructed by the VI of ‘’ derived from HS imagery, incorporating the five growth stages of booting, heading, flowering, filling, and maturation with r of 0.84 and RMSE of 0.69 t/ha. The corresponding central wavelengths were 782 nm, 874 nm, 762 nm, and 890 nm, respectively. Our study indicates that the multiple temporal VIs derived from UAV-based HS imagery are effective tools for breeding researchers to estimate winter wheat yield on a field plot scale. Full article

With the advancement of intelligent shipping, current traffic management systems have become inadequate to meet the requirements of intelligent supervision. In particular, with regard to ship violations, on-site boarding is still necessary for inspection. This paper presents a novel approach for enhancing ships’ management and service capabilities through scientific knowledge graph technology to develop a ship knowledge graph. The proposed approach extracts key characteristics of ship violations from the ship knowledge graph, such as monitoring ships, expired ship certificates, multiple ship tracks, inconsistent ship tracks with port reports, and ships not reported to the port for a long time. Combining the characteristics of ship violations, the approach uses reasoning and identification techniques to detect specific instances of falsely licensed ships and other violations. The development of the ship knowledge graph analysis system enables the identification and verification of illegal ships using fake license plates, while also improving the effective utilization of maritime data and enhancing the ability to make informed decisions related to ship safety. By leveraging cognitive approaches and knowledge graphs, this study offers the potential to develop an intelligent decision-making system for maritime traffic management. Full article

Lactate dehydrogenase (LDH) is an enzyme that catalyzes the reversible conversion of lactate to pyruvate while reducing NAD⁺ to NADH (or oxidizing NADH to NAD⁺). Due to its central role in the Warburg effect, LDH-A isoform has been considered a promising target for treating several types of cancer. However, research on inhibitors targeting LDH-B isoform is still limited, despite the enzyme’s implication in the development of specific cancer types such as breast and lung cancer. This study aimed to identify small-molecule compounds that specifically inhibit LDH-B. Our in silico analysis identified eight commercially available compounds that may affect LDH-B activity. The best five candidates, namely tucatinib, capmatinib, moxidectin, rifampicin, and acetyldigoxin, were evaluated further in vitro. Our results revealed that two compounds, viz., tucatinib and capmatinib, currently used for treating breast and lung cancer, respectively, could also act as inhibitors of LDH-B. Both compounds inhibited LDH-B activity through an uncompetitive mechanism, as observed in in vitro experiments. Molecular dynamics studies further support these findings. Together, our results suggest that two known drugs currently being used to treat specific cancer types may have a dual effect and target more than one enzyme that facilitates the development of these types of cancers. Furthermore, the results of this study could be used as a new starting point for identifying more potent and specific LDH-B inhibitors. Full article

BK (BKPyV) and JC (JCPyV) polyomaviruses are widespread in humans. Transmission at an early age and the role of parents in spreading these viruses through the family are incompletely understood. Our aim was to determine the seroprevalence of BKPyV and JCPyV in infants at the age of 1, 2, 6, 12, 24, and 36 months and to assess the frequency of BKPyV and JCPyV seroconversion. A variety of maternal and paternal covariates were also tested as potential predictors of these early childhood infections. We used multiplex serology to analyze antibodies to BKPyV and JCPyV from baseline to 3-year follow-up visits. We observed that there was nearly perfect correlation in BKPyV and JCPyV serum IgG antibody levels between the mother-infant pairs during the first year of the infant’s life. No correlation among BKPyV antibody titers were found in father–child pairs, whereas JCPyV antibody levels of the father and child had a significant correlation at the 2-year follow-up visit. BKPyV infection may be associated with a child’s predisposition to allergy. In conclusion, after the decay of maternal antibodies, children start to develop their own immunity toward BKPyV and JCPyV, and horizontal transmission of infection in the family can occur. Full article

The survival and function of tissues depend on appropriate vascularization. Blood vessels of the tissues supply oxygen, and nutrients and remove waste and byproducts. Incorporating blood vessels into engineered tissues is essential for overcoming diffusion limitations, improving tissue function, and thus facilitating the fabrication of thick tissues. Here, we present a modified ECM bioink, with enhanced mechanical properties and endothelial cell-specific adhesion motifs, to serve as a building material for 3D printing of a multiscale blood vessel network. The bioink is composed of natural ECM and alginate conjugated with a laminin adhesion molecule motif (YIGSR). The hybrid hydrogel was characterized for its mechanical properties, biochemical content, and ability to interact with endothelial cells. The pristine and modified hydrogels were mixed with induced pluripotent stem cells derived endothelial cells (iPSCs-ECs) and used to print large blood vessels with capillary beds in between. Full article

This paper introduces a novel fractional Ikeda-based memristor map and investigates its non-linear dynamics under commensurate and incommensurate orders using various numerical techniques, including Lyapunov exponent analysis, phase portraits, and bifurcation diagrams. The results reveal diverse and complex system behaviors arising from the interplay of different fractional orders in the proposed map. Furthermore, the study employs the sample entropy test to quantify complexity and validate the presence of chaos. Non-linear controllers are also presented to stabilize and synchronize the model. The research emphasizes the system’s sensitivity to the fractional order parameters, leading to distinct dynamic patterns and stability regimes. The memristor-based chaotic map exhibits rich and intricate behavior, making it an interesting and important area of research. Full article

The growing concern over the environmental impacts of industrial chemicals on aquatic ecosystems has prompted increased attention and regulation. Aromatic amines have drawn scrutiny due to their potential to disturb aquatic ecosystems. 4-chloroaniline and 3,4-dichloroaniline are chlorinated derivatives of aniline used as intermediates in the synthesis of pharmaceuticals, dyes, pesticides, cosmetics, and laboratory chemicals. While industrial applications are crucial, these compounds represent significant risks to aquatic environments. This article aims to shed light on aromatic amines’ ecological and ecotoxicological impacts on aquatic ecosystems, given as examples 4-chloroaniline and 3,4-dichloroaniline, highlighting the need for stringent regulation and management to safeguard water resources. Moreover, these compounds are not included in the current Watch List of the Water Framework Directive, though there is already some information about aquatic ecotoxicity, which raises some concerns. This paper primarily focuses on the inherent environmental problem related to the proliferation and persistence of aromatic amines, particularly 4-chloroaniline and 3,4-dichloroaniline, in aquatic ecosystems. Although significant research underscores the hazardous effects of these compounds, the urgency of addressing this issue appears to be underestimated. As such, we underscore the necessity of advancing detection and mitigation efforts and implementing improved regulatory measures to safeguard the water bodies against these potential threats. Full article

Traditional single-antenna systems have inherent limitations in terms of antenna gain, anti-interference capability, and flexibility. To overcome these challenges, satellite-mounted distributed antenna systems disperse multiple antennas at different positions on the satellite to improve the reception quality and signal-to-noise ratio of satellite signals, enhancing the performance of the satellite communication system without additional bandwidth or transmission power. However, the dispersed locations and long distances between antennas on the satellite result in less compact spacing compared to terrestrial distributed antennas, leading to the generation of a significant number of grating lobes. The distributed satellite cluster (DSC) approach revolutionizes the traditional mode of satellite utilization, enabling close collaboration among distributed loads. In this study, we analyzed the impact of grating lobes produced by DSC distributed antennas in geostationary Earth orbit (GEO) and simulated the grating lobe patterns of two 1 m circular aperture satellite antenna arrays in GEO. The simulation results revealed that the relative position change of the satellites affected the width and number of interference fringes in a certain ground area, while change in the carrier phase led to the translation of the interference fringes. To mitigate the grating lobes, we employed a sparse array technique. The simulation results demonstrated that the sparse array effectively suppressed the grating lobes but at the expense of a decrease in the sidelobe level and beamwidth. Full article

In this paper, a new bio-inspired metaheuristic algorithm named the Kookaburra Optimization Algorithm (KOA) is introduced, which imitates the natural behavior of kookaburras in nature. The fundamental inspiration of KOA is the strategy of kookaburras when hunting and killing prey. The KOA theory is stated, and its mathematical modeling is presented in the following two phases: (i) exploration based on the simulation of prey hunting and (ii) exploitation based on the simulation of kookaburras’ behavior in ensuring that their prey is killed. The performance of KOA has been evaluated on 29 standard benchmark functions from the CEC 2017 test suite for the different problem dimensions of 10, 30, 50, and 100. The optimization results show that the proposed KOA approach, by establishing a balance between exploration and exploitation, has good efficiency in managing the effective search process and providing suitable solutions for optimization problems. The results obtained using KOA have been compared with the performance of 12 well-known metaheuristic algorithms. The analysis of the simulation results shows that KOA, by providing better results in most of the benchmark functions, has provided superior performance in competition with the compared algorithms. In addition, the implementation of KOA on 22 constrained optimization problems from the CEC 2011 test suite, as well as 4 engineering design problems, shows that the proposed approach has acceptable and superior performance compared to competitor algorithms in handling real-world applications. Full article

The superconducting magnet energy storage (SMES) has become an increasingly popular device with the development of renewable energy sources. The power fluctuations they produce in energy systems must be compensated with the help of storage devices. A toroidal SMES magnet with large capacity is a tendency for storage energy because it has great energy density and low stray field. A key component in the creation of these superconducting magnets is the material from which they are made. The present work describes a comparative numerical analysis with finite element method, of energy storage in a toroidal modular superconducting coil using two types of superconducting material with different properties bismuth strontium calcium copper oxide (BSCCO) and yttrium barium copper oxide (YBCO). Regarding the design of the modular torus, it was obtained that for a 1.25 times increase of the critical current for the BSCCO superconducting material compared with YBCO, the dimensions of the BSCCO torus were reduced by 7% considering the same stored energy. Also, following a numerical parametric analysis, it resulted that, in order to maximize the amount of energy stored, the thickness of the torus modules must be as small as possible, without exceeding the critical current. Another numerical analysis showed that the energy stored is maximum when the major radius of the torus is minimum, i.e., for a torus as compact as possible. Full article

Introduction: There are several risk factors attributed to tuberculosis (TB) mortality and morbidity. There are few studies and systematic reviews showing the association of silicosis and tuberculosis at a country level. Very limited studies have been conducted using multi-country data in studying the association of incidence of silicosis with TB mortality and morbidity. Hence, the aim of this research was to explore the association of incidence of silicosis and other important risk factors with TB mortality and morbidity using multi-country data. Methods: Data from 217 WHO region countries were utilized, sourcing TB-related statistics from the Institute of Health Metrics and Evaluation and additional risk factors from the Demographic and Health Survey, Global Burden of Disease, and World Bank for 2019. Regression analysis was conducted to examine the association between silicosis incidence and TB outcomes. Results: The study found an average silicosis incidence of 121.92 per 100,000 population. Additionally, 62.69% of the sample population are exposed to air pollution from solid fuel cooking. Sanitation access stands at an average of 59.67%. Regression outcomes indicate that while alcohol consumption’s influence on TB is not statistically significant, a unit increase in silicosis incidence significantly elevates TB deaths (235.9, p = 0.005), YLL (9399.3, p = 0.011), and YLD (910.8, p = 0.002). Conclusion: The burden of silicosis is found to be one of the important determinants of deaths, YLL, and YLD due to tuberculosis. Country-specific strategies to prevent and control silicosis is a need of the hour. Full article

An imbalance in PI3K/AKT/mTOR pathway signaling in humans often leads to cancer. Therefore, the investigation of anti-cancer medications that inhibit PI3K and mTOR has emerged as a significant area of research. The aim of this study was to explore the effect of XIN-10, a dual PI3K/mTOR inhibitor, on the growth as well as antiproliferation of tumor cells and to investigate the anti-tumor mechanism of XIN-10 by further exploration. We screened three cell lines for more in-depth exploration by MTT experiments. From the AO staining, cell cycle and apoptosis, we found that XIN-10 had a more obvious inhibitory effect on the MCF-7 breast cancer cell line and used this as a selection for more in-depth experiments. A series of in vitro and in vivo experiments showed that XIN-10 has superior antiproliferative activity compared with the positive drug GDC-0941. Meanwhile, through the results of protein blotting and PCR experiments, we concluded that XIN-10 can block the activation of the downstream pathway of mTOR by inhibiting the phosphorylation of AKT(S473) as well as having significant inhibitory effects on the gene exons of PI3K and mTOR. These results indicate that XIN-10 is a highly potent inhibitor with low toxicity and has a strong potential to be developed as a novel PI3Kα/mTOR dual inhibitor candidate for the treatment of positive breast cancer. Full article

The blood coagulation response to decompression stress in humans has yet to be fully investigated. Here we utilised calibrated automated thrombogram (CAT) on samples from healthy volunteers exposed to decompression stress to investigate real-time thrombin generation. To induce decompression stress, fifteen apparently healthy males (age 20–50 yr) were exposed to two consecutive ascents to 25,000 ft for 60 min (1st ascent) and then 90 min (2nd ascent) while breathing 100% oxygen. Citrated blood samples were taken prior to exposure (T0), following the 2nd ascent (T8) and at 24 h (T24). Thrombin generation curves were obtained using Thrombinoscope^TM. Parameters determined were lag time (LAG), time to peak (TTP), peak thrombin (PEAK), endogenous thrombin potential (ETP) and velocity index (VEL). Of the 15 subjects, 12 had validated coagulation profiles. TTP and ETP showed no significant differences. However, there was a significant increase in VEL from T0 to T8 (p = 0.025) and from T8 to T24 (p = 0.043). A non-significant trend of an overall increase in PEAK was also observed from T0 to T8 (p = 0.069) and from T8 to T24 (p = 0.098). PEAK and VEL were found to be correlated. Taken together, these two parameters suggest an overall shift towards a more procoagulant profile following hypobaric stress. Full article

With the existing pressure sensors, it is difficult to achieve the unification of wide pressure response range and high sensitivity. Furthermore, the preparation of pressure sensors with excellent performance for sleep health monitoring has become a research difficulty. In this paper, based on material and microstructure synergistic enhancement mechanism, a hybrid pressure sensor (HPS) integrating triboelectric pressure sensor (TPS) and piezoelectric pressure sensor (PPS) is proposed. For the TPS, a simple, low-cost, and structurally controllable microstructure preparation method is proposed in order to investigate the effect of carbon nano-onions (CNOs) and hierarchical composite microstructures on the electrical properties of CNOs@Ecoflex. The PPS is used to broaden the pressure response range and reduce the pressure detection limit of HPS. It has been experimentally demonstrated that the HPS has a high sensitivity of 2.46 V/10⁴ Pa (50–600 kPa) and a wide response range of up to 1200 kPa. Moreover, the HPS has a low detection limit (10 kPa), a high stability (over 100,000 cycles), and a fast response time. The sleep monitoring system constructed based on HPS shows remarkable performance in breathing state recognition and sleeping posture supervisory control, which will exhibit enormous potential in areas such as sleep health monitoring and potential disease prediction. Full article

Exploring the factors influencing urban vibrancy can help policy development and advance urban planning and sustainable development. Previous studies have typically focused on the effects of physical environmental factors (e.g., built environment, urban landscape) on urban vibrancy, ignoring the role of non-physical environmental factors (e.g., urban psychological perceptions). In addition, these studies remain focused on relatively coarse spatial units and lack the exploration of finer-grained spatial structures. In this study, a novel framework is proposed to analyze urban vibrancy and its influencing factors at a more fine-grained street level. Firstly, two types of urban sensing data, POIs and Weibo check-ins, are integrated to portray the spatial distribution patterns of urban vibrancy on the streets. Secondly, a full convolutional network (FCN-8s) is used to segment the streetscape images of Beijing and use them as a basis to extract potential visual–spatial features and urban psychological perceptual features that influence urban vibrancy. Thirdly, we reveal the deeper causes of the impact of psychological perception on urban vibrancy. Finally, an improved ridge regression model is proposed to model the relationship between features and vibrancy, reducing the covariance between features while avoiding the reduction of important features. Satisfactory regression model performances were attained with adjusted R² values of 0.706, 0.743, and 0.807 at each characteristic level. The results of the study show that: Urban vibrancy is highly dependent on the proposed visual–spatial and urban psychological perception characteristics at the street level. In particular, positive urban psychological perceptions (safety, lively, wealthy) are positively correlated with urban vibrancy, while negative street perceptions (boring) are negatively correlated with urban vibrancy. Unlike previous research scales, our study shows that urban vibrancy portrayal based on the street scale has a greater potential to demonstrate fine-grained vibrancy distribution compared to the neighborhood scale. These findings may provide important insights for people-oriented urban development and planning. Full article

To evaluate the tolerance of a high-fiber diet in Erhualian pigs (Er-HL), the present investigation systematically investigated the ramifications of varying wheat bran fiber levels, specified as total dietary fiber (TDF) values of 14.07%, 16.32%, 17.99%, and 18.85%, on growth performance, fiber digestibility and gut microbiota in Er-HL, large Large White pigs (L-LW, the same physiological stage as the Er-HL) and small Large White pigs (S-LW, the same body weight as the Er-HL). Our results revealed that fiber levels exerted no discernable impact on growth performance (average daily feed intake (ADFI), and average daily gain (ADG)) of Er-HL (p > 0.05). Conversely, L-LW exhibited a decrease in ADFI and ADG with increasing fiber levels (p < 0.05). Notably, the apparent total tract digestibility (ATTD) of various fiber components, including neutral detergent fiber (NDF), acid detergent fiber (ADF), hemicellulose, TDF and insoluble dietary fiber (IDF), in Er-HL were significantly higher than those in S-LW and L-LW irrespective of diets (p < 0.05). The ATTD of cellulose and hemicellulose in Er-HL significantly decreased with increasing fiber levels (p < 0.05), yet remained statistically indifferent when comparing the 7%-wheat-bran-replaced diet (7% WRB, TDF 16.32%) to the basal diet (TDF 14.07%) (p > 0.05). The cecal microbiota of Er-HL had higher richness estimators (Chao1 and ACE) than those of S-LW and L-LW irrespective of diets (p < 0.01). Breed serves as a pivotal determinant in shaping swine gut microbiota. Thirteen genera were selected as the key bacteria related to high fiber digestibility of Er-HL. Further functional examination of these key genera elucidated an enrichment of pathways pertinent to carbohydrate metabolism in Er-HL samples compared with S-LW and L-LW samples. In summary, Er-HL exhibited high-fiber tolerance both in terms of growth performance and fiber digestibility compared with Large White pigs. Specifically, the ATTD of NDF, ADF, hemicellulose, IDF and TDF were significantly higher in Er-HL compared with L-LW and S-LW, irrespective of diets. Fiber level exerted no discernable impact on growth performance (ADFI, ADG) and the ATTD of fiber (NDF, ADF, IDF and TDF) in Er-HL. The optimum fiber level of the Er-HL was identified as 7% WRB (TDF 16.32%). Thirteen genera were ascertained to significantly contribute to high fiber digestibility of Er-HL, correlating with an enhancement of carbohydrate metabolism pathways. Full article