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Prostate cancer (PCa) is initially sensitive to androgen deprivation therapy (ADT) but ultimately develops resistance and progresses to castration-resistant prostate cancer (CRPC) with a poor prognosis. This study indicated that some PCa patients and mice were more sensitive to ADT and entered CRPC later, which was related to the gut microbiota, especially the enrichment of Akkermansia muciniphila (AKK). Untargeted metabolomics analysis found that serum inosine level was upregulated in the treatment-sensitive group and significantly correlated with AKK. Furthermore, we revealed that intestinal permeability and serum lipopolysaccharide (LPS) levels increased in treatment-resistant mice. LPS stimulated the upregulation of p-NF-κB p65 and AR in tumors. Supplementing AKK metabolite inosine could alleviate intestinal barrier damage and reduce serum LPS level, ultimately inhibiting castration resistance via the LPS/NF-κB/AR axis. Finally, we constructed a predictive model for CRPC combining gut microbiota and clinical information (AUC = 0.729). This study revealed the potential mechanism of gut microbiota on CRPC and provided potential therapeutic targets and prognostic indicators.

This research compared how different levels of dietary crude protein (CP) and apparent metabolizable energy (AME) affect the growth performance, nitrogen utilization, serum parameters, protein synthesis, and amino acid (AA) metabolism in broilers aged 1 to 10 days. In a 4 × 3 factorial experimental design, the broilers were fed four levels of dietary CP (20%, 21%, 22%, and 23%) and three levels of dietary AME (2800 kcal/kg, 2900 kcal/kg, and 3000 kcal/kg). A total of 936 one-day-old male Arbor Acres broilers were randomly allocated to 12 treatments with 6 replications each. Growth performance, nitrogen utilization, serum parameter, gene expression of protein synthesis, and AA metabolism were evaluated at 10 d. The results revealed no interaction between dietary CP and AME levels on growth performance (p > 0.05). However, 22% and 23% CP enhanced body weight gain (BWG), the feed conversion ratio (FCR), total CP intake, and body protein deposition but had a detrimental effect on the protein efficiency ratio (PER) compared to 20% or 21% CP (p < 0.05). Broilers fed diets with 2800 kcal/kg AME showed increased feed intake (FI) and inferior PER (p < 0.05). Broilers fed diets with 3000 kcal/kg AME showed decreased muscle mRNA expression of mammalian target of the rapamycin (mTOR) and Atrogin-1 compared to those fed diets with 2800 kcal/kg and 2900 kcal/kg AME (p < 0.05). Increasing dietary CP level from 20% to 23% decreased muscle mTOR and increased S6K1 mRNA expression, respectively (p < 0.05). The muscle mRNA expression of Atrogin-1 was highest for broilers fed 23% CP diets (p < 0.05). The mRNA expression of betaine homocysteine methyltransferase (BHMT) and Liver alanine aminotransferase of the 22% and 23% CP groups were higher than those of 20% CP (p < 0.05). Significant interactions between dietary CP and AME levels were observed for muscle AMPK and liver lysine-ketoglutarate reductase (LKR) and branched-chain alpha-keto acid dehydrogenase (BCKDH) mRNA expression (p < 0.05). Dietary AME level had no effect on muscle AMPK mRNA expression for broilers fed 21% and 22% CP diets (p > 0.05), whereas increasing dietary AME levels decreased AMPK mRNA expression for broilers fed 23% CP diets (p < 0.05). The mRNA expression of LKR and BCKDH was highest for broilers fed the diet with 2800 kcal/kg AME and 22% CP, while it was lowest for broilers fed the diet with 3000 kcal/kg AME and 20% CP. The findings suggest that inadequate energy density hindered AA utilization for protein synthesis, leading to increased AA catabolism for broilers aged 1 to 10 days, and a dietary CP level of 22% and an AME level of 2900 to 3000 kcal/kg may be recommended based on performance and dietary protein utilization.

Current challenges in collecting and analyzing subway vibration data include the absence of standardized data collection methods, limitations in data analysis techniques, and an unclear understanding of the effects of geological conditions on vibrations. This study investigated vertical vibrations of tunnel walls and the ground above tunnels under different geological conditions of soft soil and rock strata at horizontal distances of 0, 15 m, and 30 m from the tunnel center line during train passages. The collected data underwent Fourier transformation and 1/3 octave processing to extract spectral characteristics and analyze transmission losses across different frequency bands. Our findings revealed two vibration peaks in the transmission process for both soft soil and rock formation geology. Specifically, high-frequency vibrations in soft soil experienced greater attenuation when transmitted from the tunnel wall to the ground at 0 m, while low-frequency vibrations in rock formations showed greater attenuation. We also observed a vibration amplification phenomenon at 15 m under soft soil geology conditions. Although low-frequency vibrations below 12.5 Hz showed slight attenuation within a 30 m test distance under both geological conditions, vibrations above 40 Hz experienced significant attenuation. These results offer valuable insights for reducing vibrations in subway superstructures and planning subway lines under diverse geological conditions. Furthermore, this study serves not only as a basis for mitigating vibrations in metro spans and designing metro lines in various geological contexts but also establishes a scientific foundation for future research.

A series of well-defined diblock copolymers, namely, 3,4-polyisoprene-block-syndiotactic-1,2-polybutadiene (3,4-PI-b-s-1,2-PBD), with a soft–hard block sequence were synthesized via an in situ sequential polymerization process using a robust iron-based catalytic system Fe(acac)3/(isocyanoimino) triptenylphosphorane (IITP)/AliBu3. This catalyst exhibits vigorous activity and temperature tolerance, achieving a polymerization activity of 5.41 × 106 g mol(Fe)−1 h−1 at 70 °C with a [IP]/[Fe] ratio of 15,000. Moreover, the quasi-living polymerization characteristics of the catalyst were verified through kinetic experiments. The first-stage polymerization of isoprene (IP) is performed at 30 °C to give a soft 3,4-PI block, and then a quantitative amount of 1,3-butadiene was added in situ to the quasi-living polymerization system to produce a second hard s-1,2-PBD. The s-1,2-PBD segments in block copolymers display a rodlike morphology contrasting with the spherulitic morphology characteristic of s-1,2-PBD homopolymers. The precise tunability of the length of the soft and hard chain segments of these novel elastic materials with the feed ratio of IP and BD, endowing them with outstanding mechanical properties and excellent dynamic mechanical properties, which are expected to be promising high-performance rubber materials.

An in-depth understanding of Se uptake and metabolism in plants is necessary for developing Se biofortification strategies. Thus, hydroponic experiments were conducted to investigate the associated processes and mechanisms of organic Se (selenomethionine (SeMet) and selenomethionine-oxide (SeOMet)) uptake, translocation, transformation and their interaction in wheat, in comparison to inorganic Se. The results showed that Se uptake by the roots and the root-to-shoot translocation factor under the SeMet treatment were higher than those under the selenite, selenate and SeOMet treatments. The uptake and translocation of SeMet were higher than those of SeOMet within 72 h, although the differences gradually narrowed with time. The uptake of SeMet and SeOMet was also sensitive to the aquaporin inhibitor: AgNO3 addition resulted in 99.5% and 99.9% inhibitions of Se in the root in the SeMet and SeOMet treatments, respectively. Once absorbed by the root, they rapidly assimilated to other Se forms, and SeMet and Se-methyl-selenocysteine (MeSeCys) were the dominant species in SeMet- and SeOMet-treated plants, while notably, an unidentified Se form was also found in the root and xylem sap under the SeMet treatment. In addition, within 16 h, SeOMet inhibited the uptake and translocation of SeMet, while the inhibition was weakened with longer treatment time. Taken together, the present study provides new insights for the uptake and transformation processes of organic Se within plants.

In a layer house, the CO2 (carbon dioxide) concentration above the upper limit can cause the oxygen concentration to be below the lower limit suitable for poultry. This leads to chronic CO2 poisoning in layers, which manifests as listlessness, reduced appetite, weak constitution, decreased production performance, and weakened resistance to disease. Regulating ventilation may ensure a suitable CO2 concentration in layer houses. Predicting the changes in CO2 concentration and regulating the CO2 concentration in advance are key to ensuring healthy large-scale breeding of layers. In recent years, machine learning and deep learning methods have been increasingly applied to this field. A CO2 prediction model for layer house is proposed based on a GRU (gated recurrent unit) and LSTM (long short-term memory). The temperature, humidity, and CO2 were determined as inputs to the model by the correlation coefficient. The datasets of the experimental layer house were continuously measured during June–July 2023, using a self-developed environmental monitor, and the monitored data were used as samples for model inputs. There were 22,000 time series data in the datasets. In this study, multivariate time series data were standardized via data pre-processing to improve model training. GRU and LSTM models were constructed. The models were trained using a training set. Then, these trained models were used to provide predictions on a test set. The prediction errors were calculated using the true values of the test set and the predicted values provided by the models. To test the performance of the model and accuracy of the predictions, predictions were made for different numbers of datasets. The results demonstrated that the combined prediction model had good generalization, stability, and convergence with high prediction accuracy. Due to the structure of the model, the stability of the LSTM model was higher than that of the GRU model, and its prediction accuracy and speed were lower than those of the GRU model. When the datasets of the GRU model were 15,000 to 17,000, The MAE of the GRU was 70.8077 to 126.7029 ppm, and the prediction time of the GRU is 16 to 24 ms. When the LSTM model’s datasets were 15,000–20,000, the MAE of LSTM was 78.8596 to 136.0896 ppm, and the prediction time of the GRU was 17 to 26 ms.

The study aims to develop a decision pathway based on HEAR score and 0 h high-sensitivity cardiac troponin T (hs-cTnT) to safely avoid a second troponin test for suspected non-ST elevation myocardial infarction (NSTEMI) in emergency departments. A HEAR score consists of history, electrocardiogram, age, and risk factors. A HEAR pathway is established using a Bayesian approach based on a predefined safety threshold of NSTEMI prevalence in the rule-out group. In total, 7131 patients were retrospectively enrolled, 582 (8.2%) with index visit NSTEMI and 940 (13.2%) with 180-day major adverse cardiovascular events (MACE). For patients with a low-risk HEAR score (0 to 2) and low 0 h hs-cTnT (

The stress phase angle (SPA), defined as the temporal phase angle between circumferential stress (CS) in the arterial wall and wall shear stress (WSS), is utilized to investigate the interactions between CS and WSS. SPA serves as an important parameter for the early diagnosis of cardiovascular disease. In this study, we proposed a novel method for measuring SPA using spectral domain optical coherence tomography (SD-OCT). The multi-M-mode scan strategy is adopted for interference spectrum acquisition. The phases of CS and WSS are extracted from the corresponding structural and flow velocity images of SD-OCT. The method is validated by measuring SPA in the outflow tract (OFT) of chick embryonic hearts and the common carotid artery of mice. To the best of our knowledge, this is the first time that OCT has been used for SPA measurement.

Reputation evaluation is an effective measure for maintaining secure Internet of Things (IoT) ecosystems, but there are still several challenges when applied in IoT-enabled pumped storage power stations (PSPSs), such as the limited resources of intelligent inspection devices and the threat of single-point and collusion attacks. To address these challenges, in this paper we present ReIPS, a secure cloud-based reputation evaluation system designed to manage intelligent inspection devices’ reputations in IoT-enabled PSPSs. Our ReIPS incorporates a resource-rich cloud platform to collect various reputation evaluation indexes and perform complex evaluation operations. To resist single-point attacks, we present a novel reputation evaluation model that combines backpropagation neural networks (BPNNs) with a point reputation-weighted directed network model (PR-WDNM). The BPNNs objectively evaluate device point reputations, which are further integrated into PR-WDNM to detect malicious devices and obtain corrective global reputations. To resist collusion attacks, we introduce a knowledge graph-based collusion device identification method that calculates behavioral and semantic similarities to accurately identify collusion devices. Simulation results show that our ReIPS outperforms existing systems regarding reputation evaluation performance, particularly in single-point and collusion attack scenarios.

During the harvesting of cut-stem vegetables, the structural parameters of cutters have an important influence on the harvesting effect. Structural parameters of stalks directly affect the cutting effect of the cutter. The thickness of the stalk xylem has a strong influence on the cutting stability and cutting surface effect of the cutter. In this paper, the effect of the broccoli stalk xylem on conventional toothless cutters was investigated using broccoli stalks as the cutting object. It was found that a thicker xylem leads to shear force fluctuations, which in turn affects the smooth operation of the cutting device. Taking locust mouthparts as the research object, a bionic multi-tooth cutting method is proposed in this paper to obtain the contour curve based on the locust upper jaw cutting tooth lobe. By establishing the regression equation, the contour curve of the cutting teeth is fitted accurately. The cutter edge is designed with the locust’s maxillary incisive lobe as the bionic object. ANSYS software was used to simulate the cutting of a double disc cutter and broccoli stalk. The effect of each factor was analyzed by response-surface regression to determine the optimal cutter speed, machine forward speed, cutting inclination, blade overlap, and optimal cutting position. The cutting test is verified via broccoli stalks and a cutting test bench to further determine the cutting device operating parameters. The optimal operating parameters of the cutting device were 0.239 m/s forward speed, 30.974-degree cutting edge angle, 10.066 mm blade overlap, and 467.511 rpm.

Optical coherence tomography (OCT) attenuation imaging is a technique that uses the optical attenuation coefficient (OAC) to distinguish the types or pathological states of tissues and has been increasingly used in basic research and clinical diagnosis. With the increasing application of swept-source OCT, scholars are increasingly inclined to explore deep tissues. Unfortunately, the accuracy of OAC calculation when exploring deep tissues has yet to be improved. Existing methods generally have the following problems: overestimation error, underestimation error, severe fluctuation, or stripe artifacts in the OAC calculation of the OCT tail signal. The main reason for this is that the influence of the noise floor on the OCT weak signal at the tail-end is not paid enough attention. The noise floor can change the attenuation pattern of the OCT tail signal, which can lead to severe errors in the OAC. In this paper, we proposed a Kalman filter-based OAC optimal algorithm to solve this problem. This algorithm can not only eliminate the influence of the noise floor, but can also effectively protect the weak signal at the tail-end from being lost. The OAC of deep tissues can be calculated accurately and stably. Numerical simulation, phantom, and in vivo experiments were tested to verify the algorithm’s effectiveness in this paper. This technology is expected to play an essential role in disease diagnosis and in the evaluation of the effectiveness of treatment methods.

Two important phenomena of the solar wind–magnetosphere–ionosphere coupling are auroral particle precipitation and the formation of ions flowing upward from the ionosphere. They have opposite transport directions of energy and substance. Based on the observations of particle precipitation and ion drift from the DMSP F13 satellite in January and July 2005, the ionospheric ion upflows in dayside auroral oval (0600–1800 MLT) can be divided into five types according to the velocity of ion upflows and the spectrum characteristics of auroral particle precipitation, and the distribution for different types of ion upflows is studied. The results show that the ion upflows mainly occur in the geomagnetic latitude (MLAT) range of 70–80°.The main magnetospheric source region of ion upflows (type A and D) caused by the accelerated electron (mainly the soft electron) corresponds to Low Latitude Boundary Layer (LLBL) and Cusp, and ion upflows of type B and C (related to the process of ambipolar diffusion caused by electron acceleration) mainly occur in LLBL and Boundary Plasma Sheet (BPS), while ion upflows of type E without electron acceleration mainly occur in the central plasma sheet (CPS).The dawn–dusk asymmetry is obvious in the winter season, with the ion upflows mainly occurring on the dawn/dusk side ionosphere. However, the ion upflows in summer mainly occur at the magnetic noon, with a symmetric distribution centered at the magnetic noon. The occurrence of ion upflow in winter is significantly higher than that in summer, and it is significantly enhanced during the period of moderate geomagnetic activity. The upward region expands to the lower latitude when the geomagnetic activity is enhanced. The effect of interplanetary magnetic field (IMF) components has also been studied in this paper. When IMF Bx is negative, the upflow occurrence increases in the region of 1500–1800 MLT and 0600–0900 MLT, with the MLAT range below 70°. The direction of IMF By may lead to the high-incidence area reverse at the prenoon or postnoon region. The occurrence of ion upflows with the MLAT range below 75° increases significantly when IMF is southward. Type A ion upflow has the highest velocity of ion upflows, followed by type E, and type D has the lowest. The average velocity of ion upflows in winter is significantly higher than that in summer.

Reservoirs are an integral part of the global carbon cycle and generally considered to be methane (CH4) emission hot spots. Although remarkable research achievements have been made concerning CH4 ebullition from inland waters, such as rivers, lakes, and ponds, few have been devoted to CH4 ebullition from plateau reservoirs. The present study focused on CH4 ebullition from the Dahejia Reservoir located in the upper reaches of the Yellow River. We analyzed the spatial and temporal characteristics of CH4 ebullition flux across the water-atmosphere interface between July and August 2021. We also evaluated the influence of microbes on CH4 ebullition flux. The results showed that (1) CH4 ebullition was the dominant mode of CH4 emissions in the study site, which contributed to 78.85 ± 20% of total CH4 flux. (2) The mean CH4 ebullition flux in the nighttime (0.34 ± 0.21 mg m−2 h−1) was significantly higher than that in the daytime (0.19 ± 0.21 mg m−2 h−1). The mean CH4 ebullition flux first decreased and then increased from the upstream (0.52 ± 0.57 mg m−2 h−1) to the downstream (0.43 ± 0.3 mg m−2 h−1) of the Yellow River. (3) Sediment microbes affected the CH4 ebullition flux primarily by changing the microbial community abundance. The regression analysis showed that CH4 ebullition flux had a significantly linear negative correlation with microbial abundance in sediments. The redundancy analysis further showed CH4 ebullition flux was significantly positively correlated with the abundances of Firmicutes and Actinobacteria, and negatively with that of Proteobacteria and Chloroflexi. Among abiotic variables, CH4 ebullition flux was closely related to total phosphorus, total organic carbon, pH and nitrate nitrogen.

Glucocorticoids inhibit angiogenesis in the femoral head, which fails to nourish the bone tissue and leads to osteonecrosis. Restoring angiogenesis is not only essential for vessel formation, but also crucial for osteogenesis. Poly (L-lactic acid) (PLLA) is commonly used in the bone tissue engineering field. Panax notoginseng saponins (PNS) and osteopractic total flavone (OTF) promote angiogenesis and osteogenesis, respectively. We designed a sequentially releasing PLLA scaffold including PLLA loaded with OTF (inner layer) and PLLA loaded with PNS (outer layer). We assessed the osteogenic effect of angiogenesis in this scaffold by comparing it with the one-layered scaffold (PLLA embedded with OTF and PNS) in vivo. Results from the micro-CT showed that the data of bone mineral density (BMD), bone volume (BV), and percent bone volume (BV/TV) in the PO-PP group were significantly higher than those in the POP group (p < 0.01). Histological analyses show that the PO-PP scaffold exhibits better angiogenic and osteogenic effects compared with the one-layered scaffold. These might result from the different structures between them, where the sequential release of a bi-layer scaffold achieves the osteogenic effect of vascularization by initially releasing PNS in the outer layer. We further explored the possible mechanism by an immunohistochemistry analysis and an immunofluorescence assay. The results showed that the protein expressions of vascular endothelial growth factor (VEGF) and platelet endothelial cell adhesion molecule-1(CD31) in the PO-PP scaffold were significantly higher than those in the POP scaffold (p < 0.01); the protein expressions of osteocalcin (OCN), osteopontin (OPN), and alkaline phosphatase (ALP) in the PO-PP scaffold were significantly higher than those in the POP scaffold (p < 0.05). Upregulating the expressions of angiogenic and osteogenic proteins might be the possible mechanism.

Rice blast is a worldwide fungal disease that seriously affects the yield and quality of rice. Identification of resistance genes against rice blast disease is one of the effective ways to control this disease. However, panicle blast resistance genes, which are useful in the fields, have rarely been studied due to the difficulty in phenotypic identification and the environmental influences. Here, panicle blast resistance-3 (Pb3) was identified by a genome-wide association study (GWAS) based on the panicle blast resistance phenotypes of 230 Rice Diversity Panel I (RDP-I) accessions with 700,000 single-nucleotide polymorphism (SNP) markers. A total of 16 panicle blast resistance loci (PBRLs) within three years including one repeated locus PBRL3 located in chromosome 11 were identified. In addition, 7 genes in PBRL3 were identified as candidate genes by haplotype analysis, which showed significant differences between resistant and susceptible varieties. Among them, one nucleotide-binding domain and Leucine-rich Repeat (NLR) gene Pb3 was highly conserved in multiple resistant rice cultivars, and its expression was significantly induced after rice blast inoculation. Evolutionary analysis showed that Pb3 was a typical disease resistance gene containing coiled-coil, NB-ARC, and LRR domains. T-DNA insertion mutants and CRISPR lines of Pb3 showed significantly reduced panicle blast resistance. These results indicate that Pb3 is a panicle blast resistance gene and GWAS is a rapid method for identifying panicle blast resistance in rice.

The virtual lens model has important value in ophthalmic research, clinical diagnosis, and treatment. However, the establishment of personalized lens models and the verification of accommodation accuracy have not been paid much attention. We proposed a personalized lens model establishment and the accommodation accuracy evaluation method based on sweep-source optical coherence tomography (SS-OCT). Firstly, SS-OCT is used to obtain a single lens image in the maximum accommodation state. After refraction correction, boundary detection, and curve fitting, the central curvature radius, thickness, and lens nucleus contour of the anterior and posterior surfaces of the lens were obtained. Secondly, a personalized finite element model improved from Burd’s model was established using these individual parameters, and the adaptation process of the lens model was simulated by pulling the suspensory ligament. Finally, the shape and refractive power changes of the real human lens under different accommodation stimuli were collected and compared with the accommodation process of the finite element model. The results show that the accommodation process of the finite element model is highly consistent with that of the real lens. From the un-accommodation state to the maximum-accommodation state, the difference rate of all geometric and refractive parameters between the two is less than 5%. Thus, the personalized lens finite element model obtained by the calibration and correction of the existing model can accurately simulate the regulation process of a specific human lens. This work helps to provide a valuable theoretical basis and research ideas for the study of clinical diagnosis and treatment of related diseases.

Aiming at the existing single-motor agricultural tractors, which often have a mismatch between power and working conditions and a poor operation effect under different tillage modes, this paper designs a torque allocation strategy for agricultural electric tractors under different tillage modes. Firstly, the torque is divided into basic and compensating, and a calculation model is established. Then, the Particle Swarm Optimization algorithm is used to find the optimal demand torque position, and fuzzy control rules allocate the motor torque in combination with the battery SOC. Finally, the strategy’s effectiveness in different tillage modes is verified by MATLAB/Simulink simulation and bench test. The test results show that the strategy can distribute the motor torque stably according to the load torque change and pedal opening under three PTO transitions and the plowing and rotary tillage modes. The main and speed control motors respond in about 3 s with good real-time performance. The drive wheel torque can reach 1600 N·m during plowing and rotating operation. The PTO torque can reach 60 N·m during the rotating process. The maximum torque of the output shaft can reach 150 N·m with good plowing performance. During all operations, the SOC of the battery shows a steady linear decrease, and the battery discharge has stability.

Sorghum is an important grain crop in many countries worldwide, yet it often suffers from high levels of fragmentation during harvest due to varying maturity. To this end, a study was conducted to investigate the crushing characteristics of sorghum grains subjected to compression and impact loading at different moisture contents. By configuring sorghum kernels with varying ranges of water and determining their physical parameters, such as length, width, etc., the geometric mean diameter of sorghum kernels was 3.105–3.550 mm, and the sphericity was above 75%. Compression tests were conducted on sorghum kernels in the triaxial direction. The compression energy was calculated to be 13.409–19.229 J on the X-axis, 16.313–21.409 J on the Y-axis, and 17.609–24.741 J on the Z-axis. In contrast, the apparent contact modulus of elasticity was calculated, with the maximum modulus of elasticity up to 72 MPa in the Z-axis direction, and the variations in the X-axis and Y-axis were approximate. Finally, mechanical impact tests were conducted to measure the critical angle of seed breakage, and a mathematical model was established to predict the impact of mechanical breakage force. The error between the predicted and experimental values was within 3%. This paper conducted compression and impact mechanics tests on sorghum seeds at different moisture contents to provide a design basis for sorghum harvesting and processing and other harvesting equipment.

Highlight removal is a fundamental and challenging task that has been an active field for decades. Although several methods have recently been improved for facial images, they are typically designed for a single image. This paper presents a lightweight optimization method for removing the specular highlight reflections of multi-view facial images. This is achieved by taking full advantage of the Lambertian consistency, which states that the diffuse component does not vary with the change in the viewing angle, while the specular component changes the behavior. We provide non-negative constraints on light and shading in all directions, rather than normal directions contained in the face, to obtain physically reliable properties. The removal of highlights is further facilitated through the estimation of illumination chromaticity, which is done by employing orthogonal subspace projection. An important practical feature of the proposed method does not require face reflectance priors. A dataset with ground truth for highlight removal of multi-view facial images is captured to quantitatively evaluate the performance of our method. We demonstrate the robustness and accuracy of our method through comparisons to existing methods for removing specular highlights and improvement in applications such as reconstruction.

The Cre-loxP system produces structural variations, such as deletion, duplication, inversion and translocation, at specific loci and induces chromosomal rearrangements in the genome. To achieve chromosomal rearrangements in Kluyveromyces marxianus, the positions and sequences of centromeres were identified in this species for the first time. Next, a Cre-loxP system was established in K. marxianus. In this system, the Cre recombinase was expressed from a leaky LAC4 promoter in a plasmid to alleviate the cytotoxicity of Cre, and the unstable plasmid contained a panARS element to facilitate the clearance of the plasmid from the cells. By using LAC4 as a reporter gene, the recombination frequencies between loxP sites or loxPsym sites were 99% and 73%, respectively. A K. marxianus strain containing 16 loxPsym sites in the genome was constructed. The recombination frequency of large-scale chromosomal rearrangements between 16 loxPsym sites was up to 38.9%. Our study provides valuable information and tools for studying chromosomal structures and functions in K. marxianus.

Rice blast is one of the main diseases in rice and can occur in different rice growth stages. Due to the complicated procedure of panicle blast identification and instability of panicle blast infection influenced by the environment, most cloned rice resistance genes are associated with leaf blast. In this study, a rice panicle blast resistance gene, Pb2, was identified by genome-wide association mapping based on the panicle blast resistance phenotypes of 230 Rice Diversity Panel 1 (RDP1) accessions with 700,000 single-nucleotide polymorphism (SNP) markers. A genome-wide association study identified 18 panicle blast resistance loci (PBRL) within two years, including 9 reported loci and 2 repeated loci (PBRL2 and PBRL13, PBRL10 and PBRL18). Among them, the repeated locus (PBRL10 and PBRL18) was located in chromosome 11. By haplotype and expression analysis, one of the Nucleotide-binding domain and Leucine-rich Repeat (NLR) Pb2 genes was highly conserved in multiple resistant rice cultivars, and its expression was significantly upregulated after rice blast infection. Pb2 encodes a typical NBS-LRR protein with NB-ARC domain and LRR domain. Compared with wild type plants, the transgenic rice of Pb2 showed enhanced resistance to panicle and leaf blast with reduced lesion number. Subcellular localization of Pb2 showed that it is located on plasma membrane, and GUS tissue-staining observation found that Pb2 is highly expressed in grains, leaf tips and stem nodes. The Pb2 transgenic plants showed no difference in agronomic traits with wild type plants. It indicated that Pb2 could be useful for breeding of rice blast resistance.

Port environmental problems have gradually become the primary concern of port authorities. The future trend of port carbon emissions is crucial to port authorities and managers in formulating regulations and optimizing operation schedules. Owing to the limitations of current prediction methods and the complex social–environmental impact, the estimation results of port carbon emissions have insufficient accuracy to support port development in the future. In this work, the stochastic impacts by regression on population, affluence, and technology (STIRPAT)–long short-term memory (LSTM)–autoregressive integrated moving average with explanatory variable (ARIMAX) integrated model is proposed for the estimation of the carbon emission of Port of Los Angeles to improve the reliability of emission prediction. Macroeconomic indicators that affect port throughput are selected using the principal component analysis—multiple linear regression model. The chosen indicators are then combined with long-term historical port throughput data as the input of the multivariate autoregressive integrated moving average (ARIMAX) model to predict port throughput. Indicators related to port carbon emissions are verified by the STIRPAT model. The LSTM–ARIMAX integrated model is then applied to estimate the emission tendency, which can be useful in developing corresponding carbon reduction strategies and further understanding port emissions. Results show that the proposed method can significantly improve the estimation accuracy for port emission by 11% compared with existing techniques. Energy conservation strategies are also put forward to assist port authorities in achieving the peak clipping of port carbon emission.

Ports offer an effective way to facilitate the global economy. However, massive carbon emission during port operating aggravates the atmospheric pollution in port cities. Capturing characteristics of port carbon emission is vital to reduce GHG (greenhouse gas) in the maritime realm as well as to achieve China’s carbon neutral objective. In this work, an integrated framework is proposed for exploring the driving factors of China ports’ emissions combined with stochastic effects on population, affluence and technology regression (STIRPAT), Global Malmquist-Luenberger (GML) and multiple linear regression (MLR). The port efficiency is estimated for each port and the potential driving factors of carbon emission are explored. The results indicate that port carbon emissions have a strong connection with port throughput, productivity, containerization and intermodal transshipment. It is worth noting that the containerization ratio and port physical facility with fossil-free energy improvement have positively correlated with carbon emissions. However, the specific value of waterborne transshipment shows a complex impact on carbon dioxide emission as the ratio increases. The findings reveal that China port authorities need to improve containerization ratio and develop intermodal transportation; meanwhile, it is responsible for port authorities to update energy use and improve energy efficiency in ways to minimize the proportion of non-green energy consumption in accordance with optimizing port operation management including peak shaving and intelligent management systems under a new horizon of clean energy and automatic equipment.

Meloxicam (MLX) is a non-steroidal anti-inflammatory drug used to treat rheumatoid arthritis and osteoarthritis. However, its poor water solubility limits the dissolution process and influences absorption. In order to solve this problem and improve its bioavailability, we prepared it in nanocrystals with three different particle sizes to improve solubility and compare the differences between various particle sizes. The nanocrystal particle sizes were studied through dynamic light scattering (DLS) and laser scattering (LS). Transmission electron microscopy (TEM) was used to characterize the morphology of nanocrystals. The sizes of meloxicam-nanocrystals-A (MLX-NCs-A), meloxicam-nanocrystals-B (MLX-NCs-B), and meloxicam-nanocrystals-C (MLX-NCs-C) were 3.262 ± 0.016 μm, 460.2 ± 9.5 nm, and 204.9 ± 2.8 nm, respectively. Molecular simulation was used to explore the distribution and interaction energy of MLX molecules and stabilizer molecules in water. The results of differential scanning calorimetry (DSC) and powder X-ray diffraction (PXRD) proved that the crystalline state did not change in the preparation process. Transport studies of the Caco-2 cell model indicated that the cumulative degree of transport would increase as the particle size decreased. Additionally, plasma concentration–time curves showed that the AUC0–∞ of MLX-NCs-C were 3.58- and 2.92-fold greater than those of MLX-NCs-A and MLX-NCs-B, respectively. These results indicate that preparing MLX in nanocrystals can effectively improve the bioavailability, and the particle size of nanocrystals is an important factor in transmission and absorption.

Cerebral edema is a serious complication of ischemic cerebrovascular disease and mannitol is a commonly used dehydrating agent for relieving cerebral edema. However, the edema state and surrounding vascular perfusion level during mannitol treatment remains unclear, which affects the clinical application of the medicine. In this paper, we demonstrated the role of swept-source optical coherence tomography (OCT) in the evaluation of mannitol efficacy using mouse models. The OCT-based angiography and attenuation imaging technology were used to obtain the cerebral vascular perfusion level and cerebral edema state at different times. Vascular parameters and edema parameters were quantified and compared. Experimental results show that mannitol can significantly reduce the water content in the central region of edema, effectively inhibiting the rapid growth of the edema area, and restoring cerebral blood flow. On average, the edema area decreased by 33% after 2 h, and the vascular perfusion density increased by 12% after 5 h. This work helps to provide a valuable theoretical basis and research ideas for the clinical treatment of cerebral edema.

Infectious bursal disease (IBD), caused by the infectious bursal disease virus (IBDV), is a highly contagious and immunosuppressive disease in chickens worldwide. The novel variant IBDV (nvIBDV) has been emerging in Chinese chicken farms since 2017, but there are no available vaccines that can provide effective protection. Herein, the capsid protein VP2 from nvIBDV strain FJ-18 was expressed in Kluyveromyces marxianus with the aim to produce nvIBDV subviral particles (SVPs). Two recombinant strains constructed for expression of nvIBDV VP2 (nvVP2) and His-tagged VP2 (nvHVP2) formed two types of nvIBDV subviral particles (SVPs), namely nvVP2-SVPs and nvHVP2-SVPs. TEM scans showed that both SVPs were about 25 nm in diameter, but there was a large portion of nvVP2-SVPs showing non-spherical particles. Molecular dynamics simulations indicate that an N-terminal His tag strengthened the interaction of the nvHVP2 monomer and contributed to the assembly of SVPs. Vaccination of chicks with the nvHVP2-SVPs provided 100% protection against novel variant IBDV infection when challenged with the FJ-18 strain, as well as the classical strain BC6/85. By contrast, vaccination with the nvVP2-SVPs only provided 60% protection against their parent FJ-18 strain, suggesting that the stable conformation of subviral particles posed a great impact on their protective efficacy. Our results showed that the nvHVP2-SVPs produced by the recombinant K. marxianus strain is an ideal vaccine candidate for IBDV eradication.

A thermoelectric module is a device that converts electrical energy into thermal energy through a mechanism known as the Peltier effect. A Peltier device has hot and cold sides/substrates, and heat can be pumped from the cold side to the hot side under a given voltage. By applying it in buildings and attaching it to building envelope components, such as walls, as a heating and cooling device, the heating and cooling requirements can be met by reversing the voltage applied on these two sides/substrates. In this paper, we describe a novel, panelized, ground source, radiant system design for space heating and cooling in buildings by utilizing the Peltier effect. The system is equipped with water pipes that are attached to one side of the panel and connected with a ground loop to exchange heat between the cold/hot sides of the thermoelectric module and the underground region. The ground loop is inserted in boreholes, similar to those used for a vertical closed-loop Ground Source Heat Pump (GSHP) system, which could be more than a hundred meters deep. Experiments were conducted to evaluate the feasibility of the developed panel system applied in buildings. The results show that: (1) the average cooling Coefficients Of Performance (COP) of the system are low (0.6 or less) even though the ground is used as a heat sink, and thus additional studies are needed to improve it in the future, such as to arrange the thermoelectric modules in cascade and/or develop a new thermoelectric material that has a large Seebeck coefficient; and (2) the developed system using the underground region as the heat source has the potential of meeting heating loads of a building while maintaining at a higher system coefficient of performance (up to ~3.0) for space heating, compared to conventional heating devices, such as furnaces or boilers, especially in a region with mild winters and relatively warm ground.

The objective of this study was to investigate the physico-chemical properties of concrete made with recycled brick-concrete aggregate, which was the mixture from waste concrete and waste clay brick in a 7:3 ratio. Specifically, this paper investigated the mechanical properties, freeze-thaw resistance, and distribution of water-soluble chloride ions of concrete containing RBCA and fly ash (FA) against combined freeze-thaw and sodium chloride attack. Concrete containing RBCA replacement of natural coarse aggregate and fly ash replacement of Portland cement was subjected to 45 freeze-thaw cycles containing sodium chloride solution. It was discovered that the mechanical properties and freeze-thaw resistance to sodium chloride attack gradually decreased with increasing RBCA content. At the same time, a replacement level of 15% FA by weight resulted in significant improvements in compressive strength and resistance to combined freeze-thaw and chloride attack. Furthermore, using a replacement of 30% FA by weight markedly improved the resistance to chloride ion penetration of concrete due to the lowest water-soluble chloride content.

In this paper, ZnO-TiO2-rGO nanocomposites were successfully synthesized by the hydrothermal method. The morphology and structure of the synthesized nanomaterials were characterized by SEM, XRD, HRTEM, and XPS. Butanone is a typical ketone product. The vapors are extremely harmful once exposed, triggering skin irritation in mild cases and affecting our breathing in severe cases. In this paper, the gas-sensing properties of TiO2, ZnO, ZnO-TiO2, and ZnO-TiO2-rGO nanomaterials to butanone vapor were studied. The optimum operating temperature of the ZnO-TiO2-rGO sensor is 145 °C, which is substantially lower than the other three sensors. The selectivity for butanone vapor is greatly improved, and the response is 5.6 times higher than that of other organic gases. The lower detection limit to butanone can reach 63 ppb. Therefore, the ZnO-TiO2-rGO sensor demonstrates excellent gas-sensing performance to butanone. Meanwhile, the gas-sensing mechanism of the ZnO-TiO2-rGO sensor to butanone vapor was also analyzed.

Syncytium formation, i.e., cell–cell fusion resulting in the formation of multinucleated cells, is a hallmark of infection by paramyxoviruses and other pathogenic viruses. This natural mechanism has historically been a diagnostic marker for paramyxovirus infection in vivo and is now widely used for the study of virus-induced membrane fusion in vitro. However, the role of syncytium formation in within-host dissemination and pathogenicity of viruses remains poorly understood. The diversity of henipaviruses and their wide host range and tissue tropism make them particularly appropriate models with which to characterize the drivers of syncytium formation and the implications for virus fitness and pathogenicity. Based on the henipavirus literature, we summarized current knowledge on the mechanisms driving syncytium formation, mostly acquired from in vitro studies, and on the in vivo distribution of syncytia. While these data suggest that syncytium formation widely occurs across henipaviruses, hosts, and tissues, we identified important data gaps that undermined our understanding of the role of syncytium formation in virus pathogenesis. Based on these observations, we propose solutions of varying complexity to fill these data gaps, from better practices in data archiving and publication for in vivo studies, to experimental approaches in vitro.

In this paper, gas sensing characteristics of sulfur-doped graphene oxide (S-GO) are firstly presented. The results of the sensing test revealed that, at room temperature (20 °C), S-GO has the optimal sensitivity to NH3. The S-GO gas sensor has a relatively short response and recovery time for the NH3 detection. Further, the sensing limit of ammonia at room temperature is 0.5 ppm. Theoretical models of graphene and S-doped graphene are established, and electrical properties of the graphene and S-doped graphene are calculated. The enhanced sensing performance was ascribed to the electrical properties’ improvement after the graphene was S-doped.

With the vigorous development of big data and the 5G era, in the process of communication, the number of information that needs to be forwarded is increasing. The traditional end-to-end communication mode has long been unable to meet the communication needs of modern people. Therefore, it is particularly important to improve the success rate of information forwarding under limited network resources. One method to improve the success rate of information forwarding in opportunistic social networks is to select appropriate relay nodes so as to reduce the number of hops and save network resources. However, the existing routing algorithms only consider how to select a more suitable relay node, but do not exclude untrusted nodes before choosing a suitable relay node. To select a more suitable relay node under the premise of saving network resources, a routing algorithm based on intuitionistic fuzzy decision-making model is proposed. By analyzing the real social scene, the algorithm innovatively proposes two universal measurement indexes of node attributes and quantifies the support degree and opposition degree of node social attributes to help node forward by constructing intuitionistic fuzzy decision-making matrix. The relay nodes are determined more accurately by using the multi-attribute decision-making method. Simulation results show that, in the best case, the forwarding success rate of IFMD algorithm is 0.93, and the average end-to-end delay, network load, and energy consumption are the lowest compared with Epidemic algorithm, Spray and Wait algorithm, NSFRE algorithm, and FCNS algorithm.

This article demonstrates the one-pot reaction, an efficient and environmentally friendly organic synthesis method, utilized to prepare the silanized silica-encapsulated calcium carbonate@natural rubber composites (SSC@NR), following first mixing the calcium carbonate (CaCO3) solution, silica (SiO2) sol solution and a small amount of Si-69 solution, to modify the surface of CaCO3 particles, and then wet mixing with natural rubber latex. The obtained silanized silica-encapsulated calcium carbonate (SSC) particles were tested by TGA, FTIR and XRD, to substantiate the effect of surface modification. Moreover, the effects of the amount of SSC on the Mooney viscosity, curing characteristics, physical and mechanical properties and dynamic mechanical properties of the SSC@NR were investigated. The results show that the surface of modified CaCO3 is effectively coated with SiO2 particles by means of physical and chemical combination, to achieve the effect of surface coating. When the optimum amount of SSC filler is 40 phr, the SSC can form better physical adsorption and chemical combination with the NR molecular chains and can be evenly dispersed in the rubber matrix, resulting in the conspicuous improvement of physical and mechanical properties, such as the tensile strength, tear strength, elongation at break and abrasion resistance. Meanwhile, the compound with SSC has preferable processability and dynamic mechanical properties.

We report the novel crystal structure and characterization of symmetrical, homodimeric humanized heavy-chain-only antibodies or dimers (HC2s). HC2s were found to be significantly coexpressed and secreted along with mAbs from transient CHO HC/LC cotransfection, resulting in an unacceptable mAb developability attribute. Expression of full-length HC2s in the absence of LC followed by purification resulted in HC2s with high purity and thermal stability similar to conventional mAbs. The VH and CH1 portion of the heavy chain (or Fd) was also efficiently expressed and yielded a stable, covalent, and reducible dimer (Fd2). Mutagenesis of all heavy chain cysteines involved in disulfide bond formation revealed that Fd2 intermolecular disulfide formation was similar to Fabs and elucidated requirements for Fd2 folding and expression. For one HC2, we solved the crystal structure of the Fd2 domain to 2.9 Å, revealing a highly symmetrical homodimer that is structurally similar to Fabs and is mediated by conserved (CH1) and variable (VH) contacts with all CDRs positioned outward for target binding. Interfacial dimer contacts revealed by the crystal structure were mutated for two HC2s and were found to dramatically affect HC2 formation while maintaining mAb bioactivity, offering a potential means to modulate novel HC2 formation through engineering. These findings indicate that human heavy-chain dimers can be secreted efficiently in the absence of light chains, may show good physicochemical properties and stability, are structurally similar to Fabs, offer insights into their mechanism of formation, and may be amenable as a novel therapeutic modality.

We present a real-time Truncated Signed Distance Field (TSDF)-based three-dimensional (3D) semantic reconstruction for LiDAR point cloud, which achieves incremental surface reconstruction and highly accurate semantic segmentation. The high-precise 3D semantic reconstruction in real time on LiDAR data is important but challenging. Lighting Detection and Ranging (LiDAR) data with high accuracy is massive for 3D reconstruction. We so propose a line-of-sight algorithm to update implicit surface incrementally. Meanwhile, in order to use more semantic information effectively, an online attention-based spatial and temporal feature fusion method is proposed, which is well integrated into the reconstruction system. We implement parallel computation in the reconstruction and semantic fusion process, which achieves real-time performance. We demonstrate our approach on the CARLA dataset, Apollo dataset, and our dataset. When compared with the state-of-art mapping methods, our method has a great advantage in terms of both quality and speed, which meets the needs of robotic mapping and navigation.

Lectin receptor-like kinases (LecRLKs) are a class of membrane proteins found in plants that are involved in diverse functions, including plant development and stress responses. Although LecRLK families have been identified in a variety of plants, a comprehensive analysis has not yet been undertaken in cucumber (Cucumis sativus L.). In this study, 46 putative LecRLK genes were identified in the cucumber genome, including 23 G-type and 22 L-type, and one C-type LecRLK gene. They were unequally distributed on all seven chromosomes, with a clustering tendency. Most of the genes in the cucumber LecRLK (CsLecRLK) gene family lacked introns. In addition, there were many regulatory elements associated with phytohormones and stress on these genes’ promoters. Transcriptome data demonstrated distinct expression patterns of CsLecRLK genes in various tissues. Furthermore, we found that each member of the CsLecRLK family had its own unique expression pattern under hormone and stress treatment by the quantitative real-time PCR (qRT-PCR) analysis. This study provides a better understanding of the character and function of the LecRLK gene family in cucumber and opens up the possibility to exploring the roles that LecRLKs might play in the life cycle of cucumber.

With the flourishing of big data and the 5G era, the amount of data to be transmitted in the communication process is increasing, and end-to-end communication in traditional social networks has been unable to meet the current communication needs. Therefore, in order to improve the success rate of data forwarding, social networks propose that the sender of the message should reasonably choose the next hop node. However, existing routing and forwarding algorithms do not take into account nodes that are live in different scenarios, and the applicable next hop node metrics are also different. These algorithms only consider the forwarding preferences of the nodes during working hours and do not consider the forwarding preferences of the nodes during non-working hours. We propose a routing algorithm based on fuzzy decision theory, which aims at a more accurate decision on selecting the next hop. A routing and forwarding algorithm based on fuzzy decision is proposed in this paper. This algorithm symmetrical divides scenes in opportunistic social networks into working time and non-working time according to real human activity. In addition, metrics are designed symmetrically for these two scenarios. Simulation results demonstrate that, in the best case, the proposed scheme presents an average delivery ratio of 0.95 and reduces the average end-to-end delay and average overhead compared with the epidemic routing algorithm, the EIMSTalgorithm, the ICMT algorithm, and the FCNSalgorithm.

Accurate motion capture plays an important role in sports analysis, the medical field and virtual reality. Current methods for motion capture often suffer from occlusions, which limits the accuracy of their pose estimation. In this paper, we propose a complete system to measure the pose parameters of the human body accurately. Different from previous monocular depth camera systems, we leverage two Kinect sensors to acquire more information about human movements, which ensures that we can still get an accurate estimation even when significant occlusion occurs. Because human motion is temporally constant, we adopt a learning analysis to mine the temporal information across the posture variations. Using this information, we estimate human pose parameters accurately, regardless of rapid movement. Our experimental results show that our system can perform an accurate pose estimation of the human body with the constraint of information from the temporal domain.

Non-contact human body measurement plays an important role in surveillance, physical healthcare, on-line business and virtual fitting. Current methods for measuring the human body without physical contact usually cannot handle humans wearing clothes, which limits their applicability in public environments. In this paper, we propose an effective solution that can measure accurate parameters of the human body with large-scale motion from a Kinect sensor, assuming that the people are wearing clothes. Because motion can drive clothes attached to the human body loosely or tightly, we adopt a space-time analysis to mine the information across the posture variations. Using this information, we recover the human body, regardless of the effect of clothes, and measure the human body parameters accurately. Experimental results show that our system can perform more accurate parameter estimation on the human body than state-of-the-art methods.

In one-shot color structured light systems, the color of stripe patterns are typically distorted with respect to color crosstalk, ambient light and the albedo of the scanned objects, leading to mismatch in the correspondence of color stripes between the projected and captured images. In this paper, an adaptive color calibration and Discrete Trend Transform algorithm are presented to achieve high-resolution 3D reconstructions. The adaptive color calibration, according to the relative albedo in RGB channels, can improve the accuracy of labeling stripe by alleviating the effect of albedo and ambient light while decoding the color. Furthermore, the Discrete Trend Transform in the M channel makes the color calibration an effective method for detecting weak stripes due to the uneven surfaces or reflectance characteristics of the scanned objects. With this approach, the presented system is suitable for scanning moving objects and generating high-resolution 3D reconstructions without the need of dark laboratory environments.

This paper focuses on developing a novel technique based on machine vision for detection of foreign substances in injections. Mechanical control yields spin/stop movement of injections which helps to cause relative movement between foreign substances in liquid and an ampoule bottle. Foreign substances are classified into two categories: subsiding-slowly object and subsiding-fast object. A sequence of frames are captured by a camera and used to recognize foreign substances. After image preprocessing like noise reduction and motion detection, two different methods, Moving-object Clustering (MC) and Frame Difference, are proposed to detect the two categories respectively. MC is operated to cluster subsiding-slowly foreign substances, based on the invariant features of those objects. Frame Difference is defined to calculate the difference between two frames due to the change of subsiding-fast objects. 200 ampoule samples filled with injection are tested and the experimental result indicates that the approach can detect the visible foreign substances effectively.

Climatic variability can lead to large‐scale alterations in the hydrologic cycle, some of which can be characterized in terms of indices involving precipitation depth, duration and frequency. This study evaluated the spatiotemporal behavior of precipitation indices over the Kentucky River watershed for both the baseline period of 1986–2015 and late‐century time frame of 2070–2099. Historical precipitation data were collected from 16 weather stations in the watershed, while future rainfall time‐series were obtained from an ensemble of 10 Coupled Model Intercomparison Project Phase 5 (CMIP5) global circulation models under two future emission pathways: Representative Concentration Pathways (RCP) 4.5 and 8.5. Annual trends in seven precipitation indices were analyzed: total precipitation on wet days (PRCPTOT), maximum length (in days) of dry and wet periods (CDD and CWD, respectively), number of days with precipitation depth ≥20 mm (R20mm), maximum five‐day precipitation depth (RX5day), simple daily precipitation index (SDII) and standardized precipitation index (SPI, a measure of drought severity). Non‐parametric Mann–Kendall test results indicated significant trends for only ≈11% of the stationindex combinations, corresponding to generally increasing trends in PRCPTOT, CWD, R20mm and RX5day and negative trends for the others. Projected magnitudes for PRCPTOT, CDD, CWD, RX5day and SPI, indices associated with the macroweather regime, demonstrated general consistency with trends previously identified and indicated modest increases in PRCPTOT and CWD, slight decrease in CDD, mixed results for RX5day, and increased non‐drought years in the late century relative to the baseline period. Late‐century projections for the remaining indices (SDII, R20mm) demonstrated behavior counter to trends in the trends identified in the baseline period data, suggesting that these indices—which are more closely linked with the weather regime and daily GCM outputs—were relatively less robust.

In this paper, we present a novel automatic pipeline to build personalized parametric models of dynamic people using a single RGB camera. Compared to previous approaches that use monocular RGB images, our system can model a 3D human body automatically and incrementally, taking advantage of human motion. Based on coarse 2D and 3D poses estimated from image sequences, we first perform a kinematic classification of human body parts to refine the poses and obtain reconstructed body parts. Next, a personalized parametric human model is generated by driving a general template to fit the body parts and calculating the non-rigid deformation. Experimental results show that our shape estimation method achieves comparable accuracy with reconstructed models using depth cameras, yet requires neither user interaction nor any dedicated devices, leading to the feasibility of using this method on widely available smart phones.