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In the field of remote sensing, change detection in remote sensing images is vital. It is an important tool in urban planning, land use, and resource management. By leveraging the powerful self-learning capabilities of deep learning, it cannot only significantly improve the accuracy and efficiency of change detection but also handle complex land features. However, current methods have not yet achieved the ideal utilization of spatial information relationships and high and low semantic features between dual-temporal images, leading to fuzzy detection boundaries and limited accuracy. To address these issues, this article proposes a multiscale differential feature optimization network. This network first concatenates remote sensing bitemporal images that contain temporal relationships along the depth dimension, and then uses 3-D convolutional technology to extract multilayer feature information. To further improve the detection effect, we designed a multiscale differential feature optimization module to extract spatial semantic feature information from different levels of feature maps. In order to fully extract the fused feature information and enhance the focus on edges and small details, we have introduced a feature enhancement upsample module and a deep supervision strategy. Furthermore, we use a mixed loss function to calculate the loss value, achieving high-precision identification of change areas. The experimental results on the LEVIR-CD dataset and WHU-CD dataset show that compared with various state-of-the-art methods, the proposed method in this article has significant advantages in terms of the F1-score and intersection over union index. Specifically, the F1-scores on the LEVIR-CD dataset and WHU-CD dataset reached 90.91% and 92.23%, respectively. The extracted change area boundaries are clearer, and the false negative and false positive rates are lower, demonstrating the strong robustness of the network model. The experimental results demonstrate that the proposed multiscale differential feature optimization network has made significant progress in the task of remote sensing image change detection, providing new perspectives and methodologies for future research in this field.

ObjectiveWhen a fire occurs in the multi-storey dwelling section of a ship, the temperature distribution pattern during the spread of smoke along corridors and ladder openings is significantly different from that of a building fire. Therefore, it is necessary to fully understand the characteristics of fire smoke in crew cabins. MethodsAn experimental study on the temperature distribution characteristics of fire smoke in single and multi-storey corridors is carried out in a 1︰5 scaled down ship model by changing the size of the heptane oil pool and the states of ladder openings. ResultsIn the case of a single-storey spread of fire smoke, the vertical temperature distribution in the corridor shows an obvious thermal stratification phenomenon with a height of over 0.4 m. In the case of a multi-storey spread, the vertical temperature gradient in the corridors is lowered and the thermal stratification height is reduced to 0.2 m or less; the vertical thermal stratification height within the corridors is reduced at corners and turnouts; the smoke temperature continues to decrease during horizontal spreading; and the temperature distribution satisfies the exponential decay law. ConclusionsThe thermal stratification height in a multi-storey corridor is significantly reduced compared with a single-storey spread of fire smoke, and the temperature attenuation coefficient k in the horizontal spread process increases as the size of the fire source increases. The results of this study can provide theoretical support for the fire risk assessment and fire protection design of ships.

Background: The hypoglycemic effects of Chinese bayberry leaves proanthocyanidins (BLPs) have been demonstrated. It is unclear, nevertheless, whether BLPs reduced postprandial blood glucose levels by regulating glucose uptake and glucose transport.Method: This study investigated the effect of BLPs (25, 50, and 100 μg/mL) on glucose uptake and glucose transport in human intestinal epithelial cells (Caco-2 cells). The uptake of 2-Deoxy-2-[(7-nitro-2,1,3-benzoxadiazol-4-yl) amino]-D-glucose (2-NBDG) and disaccharidases activity in Caco-2 cells were measured. The glucose transport ability across the cell membrane was determined using the established Caco-2 monolayer model. The transcript and protein levels of key glucose transporters were analyzed using real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting, respectively.Results: The results showed that BLPs significantly decreased glucose uptake and disaccharidases activity (p < 0.05). Otherwise, BLPs treatment obviously inhibited glucose transport across the Caco-2 monolayer in both simulated-fast (5 mM glucose) and simulated-fed (25 mM glucose) conditions. It was attributed to the suppression of glucose transporter2 (GLUT2) and sodium-dependent glucose cotransporter 1 (SGLT1) by BLPs. BLPs were found to significantly downregulated the transcript level and protein expression of glucose transporters (p < 0.05). Meanwhile, the mRNA expression of phospholipase C (PLC) and protein kinase C (PKC) involved in the signaling pathway associated with glucose transport were decreased by BLPs.Conclusion: These results suggested that BLPs inhibited intestinal glucose transport via inhibiting the expression of glucose transporters. It indicated that BLPs could be potentially used as a functional food in the diet to modulate postprandial hyperglycemia.

The piston pump is one of the key components of the hydraulic system. The valve plate, one of the key friction pairs of piston pumps, contributes most to the dynamical stability and operational reliability of the pump. Existing research on the valve plate of the piston pump does not mention the outer dead center (ODC) damage, which is necessary when considering the dynamic characteristics of the piston pump facing failure. This paper establishes a flow area model and a fluid-domain simulation model of the valve plate of the piston pump under normal and damaged conditions. The dynamic characteristics in the pressure and vibration signals under ODC damage are analyzed. A piston pump testing with ODC damage is carried on to verify the proposed models. The simulation and the experimental signals are compared by extracting the fault features of the valve plate ODC damage.

Abstract Black carbon (BC) plays an important role in the climate system because of its strong warming effect, yet the magnitude of this effect is highly uncertain owing to the complex mixing state of aerosols. Here we build a unified theoretical framework to describe BC’s mixing states, linking dynamic processes to BC coating thickness distribution, and show its self-similarity for sites in diverse environments. The size distribution of BC-containing particles is found to follow a universal law and is independent of BC core size. A new mixing state module is established based on this finding and successfully applied in global and regional models, which increases the accuracy of aerosol climate effect estimations. Our theoretical framework links observations with model simulations in both mixing state description and light absorption quantification.

In this paper, based on the feasible method and sensors for the full-scale prestressed monitor, the novel optical fiber sensors and the traditional monitoring sensors will be set up into two prestressed concrete beams with the same geometrical dimensions, material properties, and construction conditions, etc. to investigate the working state of the novel sensors and obtain the evolution law of prestress loss of the prestressed feature component under the static load. The results show that the evolution law of prestress loss of the loaded beam under the condition of no damage state and initial crack is the same as the non-loaded one; however, the prestress loss increases with the increase of time under the situation with the limit crack. The total loss of the prestressed beam with the limit crack is 36.4% without damage. The prestress loss of the prestressed beam under the static load increase with the development of the crack (injury).

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COVID-19 is a disease caused by a virus named SARS-CoV-2. SARS-CoV-2 is a single-stranded positive-sense RNA virus. Reverse transcription quantitative PCR (RT–qPCR) assays are the gold standard molecular test for detection of RNA viruses. The aim of this study was to construct an RNA-positive control based on MS2 phage-like particles (MS2 VLPs) to detect SARS-CoV-2 RNA. pCDFDuet-1 was used as a one-plasmid double-expression system to construct MS2 VLPs containing ssRNA of SARS-CoV-2. The sequence encoding one copy of maturase, His-tag and coat protein dimer was cloned and inserted into MCS1 of the plasmid; the fragment encoding protein N and ORF1ab from SARS-CoV-2 was cloned and inserted into MCS2. The prepared plasmid was transformed into Escherichia coli strain BL2 (DE3), and expression of the construct was induced by 1 mM isopropyl-L-thio-D-galactopyranoside (IPTG) at 30°C for 12 hours. MS2 VLPs were purified and collected with Ni-NTA affinity chromatography columns. The size and shape of the MS2 VLPs were verified by transmission electron microscopy, and the stability of MS2 VLP packaged RNA was evaluated by treatment with RNase A. Effects of storage temperature and buffer on MS2 VLP stability were also investigated. The results showed that SARS-CoV-2 MS2 VLPs could be successfully produced by this one-plasmid double-expression system. MS2 VLPs showed high stability and may be used as a positive control in molecular diagnosis of COVID-19.

The mission of hypersonic vehicles faces the problem of highly nonlinear dynamics and complex environments, which presents challenges to the intelligent level and real-time performance of onboard guidance algorithms. In this paper, inverse reinforcement learning is used to address the hypersonic entry guidance problem. The state-control sample pairs and state-rewards sample pairs obtained by interacting with hypersonic entry dynamics are used to train the neural network by applying the distributed proximal policy optimization method. To overcome the sparse reward problem in the hypersonic entry problem, a novel reward function combined with a sophisticated discriminator network is designed to generate dense optimal rewards continuously, which is the main contribution of this paper. The optimized guidance methodology can achieve good terminal accuracy and high success rates with a small number of trajectories as datasets while satisfying heating rate, overload, and dynamic pressure constraints. The proposed guidance method is employed for two typical hypersonic entry vehicles (Common Aero Vehicle-Hypersonic and Reusable Launch Vehicle) to demonstrate the feasibility and potential. Numerical simulation results validate the real-time performance and optimality of the proposed method and indicate its suitability for onboard applications in the hypersonic entry flight.

Near Inertial Oscillations (NIOs) are ocean oscillations forced by intermittent winds. They are most energetic at mid-latitudes, particularly in regions with atmospheric storm tracks. Wind-driven, large-scale NIOs are quickly scattered by ocean mesoscale eddies (with sizes ranging from 100 to 400 km), causing a significant portion of the NIO energy to propagate into the subsurface ocean interior. This kinetic energy pathway illustrates that the wind energy input to NIO is critical for maintaining deep ocean stratification and thus closing the total energy budget, as emphasised by numerous modelling studies. However, this wind energy input to NIO remains poorly observed on a global scale. A remote sensing approach that observes winds and ocean currents co-located in time and space with high resolution is necessary to capture the intermittent air-sea coupling. The current satellite observations do not meet these requirements. This study assesses the potential of a new satellite mission concept, Ocean DYnamics and Surface Exchange with the Atmosphere (OSYSEA), to recover wind-forced NIOs from co-located winds and currents. To do this, we use an Observation System Simulation Experiment (OSSE) based on hourly observations of ocean surface currents and surface winds from five surface moorings covering latitudes from 15° to 50°. ODYSEA wind and current observations are expected to have a spatial resolution of 10 km with about a 12 h sampling frequency in mid-latitudes. Results show that NIOs can be recovered with high accuracy using the ODYSEA spatial and temporal resolution, but only if observations are made over a wide area of 1800 km. A narrower swath (1000 km) may lead to significant aliasing.

A self-aware posttensioned prestressing intelligent reinforcement system with force and sensors is proposed by combining the advantages of posttensioned prestressing reinforcement technology and intelligent structure. A static test study is then conducted with brick masonry members (wall pieces) as reinforcement objects. The experimental results demonstrate that the intelligent strand can be deployed using the same process, tensioning apparatus, and anchoring equipment as ordinary strand. Furthermore, the mechanical performance indexes with and without intelligent strands are very close, and the differences in percentages of cracking load, cracking displacement, yielding load, yielding displacement, ultimate load, and ultimate displacement are 20%, 9%, 9%, 10%, 2%, and 26%.

Chinese bayberry (Myrica rubra Sieb. et Zucc.) leaves proanthocyanidins (BLPs) were natural bioactive compounds in the treatment of obesity and diabetes with a unique structural characteristic. This study aimed to investigate the effect of BLPs on hepatic glucose metabolism in insulin-resistant HepG2 cells and elucidate the underlying mechanism. With the supplementation of BLPs, the glucose consumption and glucose uptake in IR-HepG2 cells were increased. BLPs promoted glycogen synthesis via up-regulating p-GSK3β and GYS2 expression, and attenuated gluconeogenesis by down-regulating PEPCK and G6Pase expression. It was attributed to the activation of PI3K/AKT signal pathway by BLPs, which was confirmed using the PI3K inhibitor LY294002. Moreover, BLPs remarkably reduced the expression of miR-29a, miR-423 and miR-122, which involved in hepatic glucose metabolism. Our results provide an insight of the hypoglycemic potential of BLPs on the hepatic glucose metabolism, suggesting that BLPs can be further used as a novel ingredient in functional food.

Bayberry leaves proanthocyanidins (BLPs) were distributed in natural plant food, considered to have the potential for metabolic syndrome. In this study, we raised Drosophila melanogaster on high sugar diet (HSD) from the egg stage to induce hyperglycemia, and the ameliorative effect of BLPs was assessed based on this model. Phenotypical, biochemical, and molecular analyses related to diabetes mellitus pathogenesis were measured. Flies exposed to BLPs were found to suppress the HSD-induced high glucose and high triglycerides levels. Moreover, BLPs showed an inhibitory effect on carbohydrate digestive enzymes (α-amylase and α-glucosidase) activity and mRNA expression, exhibiting the potential for carbohydrate digestion retardation. Transcriptional levels of key genes associated with glycolipid metabolism were further evaluated, including dilp, InR, and downstream dAKT-dFOXO-PEPCK, together with E78, SREBP, FAS, and LSD genes, were all downregulated after BLPs-exposure, suggesting the ameliorative effect of BLPs on dysbiosis associated with the insulin signaling pathway. This study provided a new functional compound, which is beneficial to further antidiabetic therapy studies.

The Group ACYW135 meningococcal polysaccharide vaccine (MPV-ACYW135) is a classical common vaccine used to prevent Neisseria meningitidis serogroups A, C, Y, and W135, but studies on the vaccine at the transcriptional level are still limited. In the present study, mRNAs and lncRNAs related to immunity were screened from the spleens of mice inoculated with MPV-ACYW135 and compared with the control group to identify differentially expressed mRNAs and lncRNAs in the immune response. The result revealed 34375 lncRNAs and 41321 mRNAs, including 405 differentially expressed (DE) lncRNAs and 52 DE mRNAs between the MPV group and the control group. Results of GO and KEGG enrichment analysis turned out that the main pathways related to the immunity of target genes of those DE mRNAs and DE lncRNAs were largely associated with positive regulation of T cell activation, CD8-positive immunoglobulin production in mucosal tissue, alpha-beta T cell proliferation, negative regulation of CD4-positive, and negative regulation of interleukin-17 production, suggesting that the antigens of MPV-ACYW135 capsular polysaccharide might activate T cell related immune reaction in the vaccine inoculation. In addition, it was noted that Bach2 (BTB and CNC homolog 2), the target gene of lncRNA MSTRG.17645, was involved in the regulation of immune response in MPV-ACYW135 vaccination. This study provided a preliminary catalog of both mRNAs and lncRNAs associated with the proliferation and differentiation of body immune cells, which was worthy of further research to enhance the understanding of the biological immune process regulated by MPV-ACYW135.

The kinetic energy transfer between the atmosphere and oceans, called wind work, affects ocean dynamics, including near-inertial oscillations and internal gravity waves, mesoscale eddies, and large-scale zonal jets. For the most part, the recent numerical estimates of global wind work amplitude are almost five times larger than those reported 10 years ago. This large increase is explained by the impact of the broad range of spatial and temporal scales covered by winds and currents, the smallest of which has only recently been uncovered by increasingly high-resolution modeling efforts. However, existing satellite observations do not fully sample this broad range of scales. The present study assesses the capabilities of ODYSEA, a conceptual satellite mission to estimate the amplitude of wind work in the global ocean. To this end, we use an ODYSEA measurement simulator fed by the outputs of a km scale coupled ocean–atmosphere model to estimate wind work globally. The results indicate that compared with numerical truth estimates, the ODYSEA instrument performs well globally, except for latitudes north of 40∘N during summer due to unresolved storm evolution. This performance is explained by the wide-swath properties of ODYSEA (a 1700 km wide swath with 5 km posting for winds and surface currents), its twice-a-day (daily) coverage at mid-latitudes (low latitudes), and the insensitivity of the wind work to uncorrelated errors in the estimated wind and current.

This paper introduces an improved sequential convex programming algorithm using adaptive non-uniform discretization for the hypersonic entry problem. In order to ensure real-time performance, an inverse-free precise discretization based on first-order hold discretization is adopted to obtain a high-accuracy solution with fewer temporal nodes, which would lead to constraint violation between the temporal nodes due to the sparse time grid. To deal with this limitation, an adaptive non-uniform discretization is developed, which provides a search direction for purposeful clustering of discrete points by adding penalty terms in the problem construction process. Numerical results show that the proposed method has fast convergence with high accuracy while all the path constraints are satisfied over the time horizon, thus giving potential to real-time trajectory planning.

Transposons are accepted as evolutionary catalysts but how they do so remains less clear. Analyzing 100 animal genomes finds that terminal inverted repeat-type transposable elements catalyze new gene structures and new genes in animals via both transposition-independent and -dependent mechanisms.

Citrus germplasm programs can benefit from high-throughput polymerase chain reaction (PCR)-based methods for the detection of graft-transmissible pathogens in propagative materials. These methods increase diagnostic capacity, and thus contribute to the prevention of disease spread from nurseries to citrus orchards. High quality nucleic acids, as determined by purity, concentration, and integrity, are a prerequisite for reliable PCR detection of citrus pathogens. Citrus tissues contain high levels of polyphenols and polysaccharides, which can affect nucleic acid quality and inhibit PCR reactions. Various commercially available RNA isolation methods are used for citrus and include: phenol-chloroform (TRIzol®, Thermo Fisher Scientific); silica columns (RNeasy® Plant Mini Kit, Qiagen); and magnetic beads-based methods (MagMAX™-96 Viral RNA Isolation Kit, Thermo Fisher Scientific). To determine the quality of RNA and its impact on the detection of graft-transmissible citrus pathogens in reverse transcription (RT) PCR-based assays, we compared these three RNA isolation methods. We assessed RNA purity, concentration, and integrity from citrus inoculated with different viruses and viroids. All three RNA isolation methods produced high quality RNA, and its use in different RT-PCR assays resulted in the detection of all targeted citrus viruses and viroids with no false positive or negative results. TRIzol® yielded RNA with the highest concentration and integrity values but some samples required serial dilutions to remove PCR inhibitors and detect the targeted pathogens. The RNeasy® kit produced the second highest concentration and purity of RNA, and similar integrity to TRIzol®. MagMAX™ isolation also provided high quality RNA but most importantly produced RNA with consistent results clustered around a median value for concentration, purity, and integrity. Subsequently, MagMAX™-96 was combined with the semi-automated MagMAX™ Express-96 Deep Well Magnetic Particle Processor, for high-throughput sample processing. MagMAX™-96 enabled the diagnostic laboratory of the Citrus Clonal Protection Program-National Clean Plant Network at the University of California, Riverside to process over 16,500 samples from citrus budwood source trees between 2010 and 2019. This high-throughput approach dramatically reduced the incidence of viroids in citrus nurseries and was key to the successful implementation of the mandatory Citrus Nursery Stock Pest Cleanliness Program in California.

Diacylglycerol acyltransferase 2 (DGAT2) catalyzes the final step in triglyceride synthesis and plays an important role in the synthesis of fat, but the effects of its expression on intramuscular fat (IMF) content and muscle development are still unknown. In this study, we investigated the expression of the DGAT2 gene and its associations with IMF content and breast muscle fiber characteristics in pigeons. The spatiotemporal expression profile of the pigeon DGAT2 gene in breast muscle showed that the mRNA expression level of DGAT2 gene in subcutaneous fat was the highest (p < 0.01) among eight tissues from 0 to 4 weeks of age, and showed an upward trend week by week, followed by liver (p < 0.05). Moreover, both mRNA and protein levels of the DGAT2 gene in breast muscle showed an upward trend from 0 to 4 weeks (p < 0.05), accompanied by the upregulation of MYOD1 and MSTN. In addition, the paraffin section analysis results revealed that the diameter and cross-sectional area of pectoralis muscle fiber significantly increased with age (p < 0.05), and a significant positive correlation was shown between the DGAT2 gene expression level and muscle fiber diameter (p < 0.05). Furthermore, correlation analysis suggested that the mRNA expression level of the pigeon DGAT2 gene was significantly (p < 0.01) correlated with IMF content in breast muscle. These results imply that the DGAT2 gene has a close relationship with IMF content and breast muscle fiber characteristics in pigeons, indicating that the DGAT2 gene might be used as a candidate gene marker-assisted breeding in pigeons.

This paper presents a novel control method that combines sliding mode controllers, disturbance observers and an exact robust differentiator to solve the underactuated microsatellite electromagnetic docking control problem, in which each docking satellite is equipped with only one single electromagnetic coil. The far-field model of electromagnetic force/torque is given and its model error is analyzed; and a six-degree-of-freedom (6-DOF) docking dynamics model using the far-field model is established. The generation method of the desired trajectory and desired attitude in the docking process is presented; and then an improved exact robust differentiator based on the 3rd-order sliding mode is proposed to produce the desired angular velocity and angular acceleration. In the presence of model uncertainties, external disturbances and input constraints, a disturbance observer-based sliding mode control scheme for underactuated microsatellite electromagnetic docking is developed. The whole closed-loop control system contains an inner-loop attitude controller and an outer-loop position controller. Numerical simulation results are presented to validate the effectiveness and the superior properties of the proposed control scheme.

Reproductive efficiency is of significant importance in pork production for it has a great impact on economic success. Ovulation rate is an early component of reproduction efficiency of pigs, and it contributes to the upper limit of litter size. In this study, we used the newly developed recombinant pig follicle stimulating hormone (rpFSH) instead of traditional PMSG to increase ovulation rate of pigs in order to achieve higher litter size, for it was better at stimulating ovulation, and showed more cheaper and greener. However, relatively little is known about the underlying genetic bases and molecular mechanisms. Consequently, an experiment was carried out in ovaries of replacement gilts to screen the key genes and lncRNAs that affect the fecundity of pigs by RNA-seq technology. Twenty gilts were divided into two groups, including 10 rpFSH treatment pigs and 10 control animals. After slaughtering and collecting the phenotypic data, ovaries of five pigs in each group were selected for RNA-seq. Total RNA was extracted to construct the library and then sequence on an Illumina Hiseq 4000 system. A comprehensive analysis of mRNAs and long non-coding RNAs (lncRNAs) from 10 samples was performed with bioinformatics. The phenotypic data showed that rpFSH treatment groups had the higher (P < 0.01) ovarian weight and more mature follicles. The RNA-seq results showed that a total of 43,499 mRNAs and 21,703 lncRNAs were identified, including 21,300 novel lncRNAs and 403 known lncRNAs, of which 585 mRNAs and 398 lncRNAs (P < 0.05) were significantly differentially expressed (DE) between the two groups of rpFSH treatment group and controlled group. GO and KEGG annotation analysis indicated that the target genes of DE lncRNAs and DE mRNAs were related to prolactin receptor activity, mitophagy by induced vacuole formation, and meiotic spindle. Moreover, we found that NR5A2 (nuclear receptor subfamily 5, group A, member 2), a target gene of lncRNA MSTRG.3902.1, was involved in regulating follicular development, ovulation, and estrogen production. Our study provided a catalog of lncRNAs and mRNAs associated with ovulation of rpFSH treatment, and they deserve further study to deepen the understanding of biological processes in the regulation of ovaries of rpFSH treatment pigs.

The 23-valent pneumococcal vaccine (PPV23) is a classical common vaccine used to prevent pneumococcal disease. In past decades, it was thought that vaccination with this vaccine induces humoral immunity, thereby reducing the disease associated with infection with 23 common serotypes of Streptococcus pneumoniae (Sp). However, for this polysaccharide vaccine, the mechanism of immune response at the transcriptional level has not been fully studied. To identify the lncRNAs (long noncoding RNAs) and mRNAs in spleens related to immunity after PPV23 vaccination in mice, high-throughput RNA sequencing of spleens between a PPV23 treatment group and a control group were performed and evaluated in this study. The RNA-seq results identified a total of 41,321 mRNAs and 34,375 lncRNAs, including 55 significantly differentially expressed (DE) mRNAs and 389 DE lncRNAs (p < 0.05) between the two groups. GO and KEGG annotation analysis indicated that the target genes of DE lncRNAs and DE mRNAs were related to T-cell costimulation, positive regulation of alpha–beta T-cell differentiation, the CD86 biosynthetic process, and the PI3K-Akt signaling pathway, indicating that the polysaccharide component antigens of PPV23 might activate a cellular immune response during the PPV23 immunization process. Moreover, we found that Trim35 (tripartite motif containing 35), a target gene of lncRNA MSTRG.9127, was involved in regulating immunity. Our study provides a catalog of lncRNAs and mRNAs associated with immune cells’ proliferation and differentiation, and they deserve further study to deepen the understanding of the biological processes in the regulation of PPV23 during humoral immunity and cellular immunity.

A high-precision online trajectory optimization method combining convex optimization and Radau pseudospectral method is presented for the large attitude flip vertical landing problem of a starship-like vehicle. During the landing process, the aerodynamic influence on the starship-like vehicle is significant and non-negligible. A planar landing dynamics model with pitching motion is developed considering that there is no extensive lateral motion modulation during the whole flight. Combining the constraints of its powered descent landing process, a model of the fuel optimal trajectory optimization problem in the landing point coordinate system is given. The nonconvex properties of the trajectory optimization problem model are analyzed and discussed, and the advantages of fast solution and convergence certainty of convex optimization, and high discretization precision of the pseudospectral method, are fully utilized to transform the strongly nonconvex optimization problem into a series of finite-dimensional convex subproblems, which are solved quickly by the interior point method solver. Hardware-in-the-loop simulation experiments verify the effectiveness of the online trajectory optimization method. This method has the potential to be an online guidance method for the powered descent landing problem of starship-like vehicles.

Breathing wall (BW) based on air-permeable porous medium offers an alternative solution for utilizing the conductive heat loss of building envelope to preheat the infiltration ventilation airflow within porous medium. However, current studies neglect the influence of pressure drop within porous medium on the energy performance of BW, which may lead to an overestimation or non-optimal design. In this study, we proposed a framework to determine the critical insulation thickness of BW for minimizing its convective heat loss and pressure drop related energy loss. An analytical model was developed and validated to calculate the heat loss of BW under third-type boundary condition. Darcy's law was applied to estimate the pressure drop of infiltration airflow and its associated energy loss. Case studies were conducted to identify the critical insulation thickness of BW. The critical thickness of BW under different scenarios was investigated. The results demonstrate the existence of critical thickness, which yields the lowest overall heat loss of BW. A larger infiltration airflow rate or lower air permeability of porous medium will result in a downward trend of this critical thickness. The outcomes of this study can provide a design guideline of BW for maximizing its energy saving potential.

Cinnamaldehyde is an aromatic aldehyde isolated from the essential oil of cinnamon. It has been proved to possess various bioactivities such as anti-inflammation, anti-bacteria and antihypertensive. Nevertheless, early weaning could lead to intestinal stress, causing a range of intestinal health problems. The aim of this study is to explore the effects of cinnamaldehyde on gut barrier integrity, inflammatory responses, and intestinal microbiome of early weaned rats. In this study, treatment with cinnamaldehyde (100 or 200 mg/kg bodyweight/day) for 2 weeks significantly promoted the production of mucins in the colonic epithelial tissue of rats. Cinnamaldehyde supplementation significantly upregulated the expression of Muc2, TFF3 and the tight junction proteins (ZO-1, claudin-1, and occludin). Hematoxylin and eosin staining results showed that colonic histopathological changes were recovered by cinnamaldehyde supplementation. The mRNA expression of IL-6 and TNF-α were significantly decreased in the cinnamaldehyde groups while the TNF-α protein levels were significantly decreased in the two cinnamaldehyde groups. Cinnamaldehyde treatment obviously attenuated the activation of NF-κB signaling pathway in rat colonic tissue and suppressed the production of inflammatory cytokines. Furthermore, cinnamaldehyde supplementation remodeled the gut microbiome structure, at the genus level, Akkermansia, Bacteroides, Clostridium III, Psychrobacter, Intestinimonas were increased, whereas those of Ruminococcus, Escherichia/Shigella were obviously decreased in the cinnamaldehyde treated groups. These findings indicated that cinnamaldehyde could effectively enhance intestinal barrier integrity, ameliorate inflammatory responses and remodel gut microbiome in early weaned rats.

The mission of spacecraft usually faces the problem of an unknown deep space environment, limited long-distance communication and complex environmental dynamics, which brings new challenges to the intelligence level and real-time performance of spacecraft onboard trajectory optimization algorithms. In this paper, the optimal control theory is combined with the neural network. Then, the state–control sample pairs and the state–costate sample pairs obtained from the high-fidelity algorithm are used to train the neural network and further drive the spacecraft to achieve optimal control. The proposed method is used on two typical spacecraft missions to verify the feasibility. First, the system dynamics of the hypersonic reentry problem and fuel-optimal moon landing problem are described and then formulated as highly nonlinear optimal control problems. Furthermore, the analytical solutions of the optimal control variables and the two-point boundary value problem are derived based on Pontryagin’s principle. Subsequently, optimal trajectories are solved offline using the pseudospectral method and shooting methods to form large-scale training datasets. Additionally, the well-trained deep neural network is used to warm-start the indirect shooting method by providing accurate initial costates, and thus the real-time performance of the algorithm can be greatly improved. By mapping the nonlinear functional relationship between the state and the optimal control, the control predictor is further obtained, which provides a backup optimal control variables generation strategy in the case of shooting failure, and ensures the stability and safety of the onboard algorithm. Numerical simulations demonstrate the real-time performance and feasibility of the proposed method.

The exhaust air window (EAW) can be regarded as a combination of exhaust air heat recovery unit and window system. The window can locally and directly utilize the exhaust air from each air-conditioned room to reduce the heat loss/gain through window. However, condensation may occur at the internal glazing surface of EAW in winter. To avoid the condensation risk of EAW, some prevention measures were proposed and estimated. In this study, a two-dimensional zonal model of EAW was established to calculate its temperature distribution, and to further identify whether condensation will occur under different boundary conditions. The calculated results were compared with the measured data for verifying the accuracy and reliability of model. A sensitivity analysis was conducted to identify the effects of indoor air temperature and relative humidity, exhaust airflow velocity, and adding a low-e coating on prevention of condensation in winter. The results indicated that adding a low-e coating or decreasing the indoor relative humidity can effectively reduce the critical outdoor temperature of condensation and prevent the occurrence of condensation within the EAW. It was estimated that even under the outdoor air temperature of −20 °C, condensation risk can be avoided by employing a low-e glazing.

Objective This retrospective study explored the association between calcium oxalate (CaOx) stones and metabolic syndrome. It also developed and validated a nomogram to aid in the prediction of CaOx stones. Methods This case-control study enrolled 150 patients with CaOx stones and 635 individuals without urolithiasis from October 2016 to October 2018. Student’s t-test, the chi-squared test, and logistic univariate and multivariate regression analyses were used. A nomogram for prediction of CaOx stones was established based on independent associated factors. The concordance index and calibration curves were plotted to determine nomogram accuracy. Results Female sex, age ≥66 years, blood pressure (systolic pressure ≥130 mmHg and/or diastolic pressure ≥85 mmHg), and blood uric acid level independently influenced the risk of CaOx stones, according to multivariate logistic regression analysis; these factors were included in the nomogram. The concordance index was 0.701 (95% confidence interval: 0.658–0.737). The standard curve showed a robust fit with the calibrated predictive curve. Conclusions Female sex, age ≥66 years, elevated blood pressure, and blood uric acid level independently influenced the risk of CaOx stones. Our nomogram for the prediction of CaOx stones may provide a clinical basis for the assessment of CaOx stone and facilitate early prevention efforts.

In order to solve the path planning problem of an intelligent vehicle in an unknown environment, this paper proposes a map construction and path planning method for mobile robots based on multi-sensor information fusion. Firstly, the extended Kalman filter (EKF) is used to fuse the ambient information of LiDAR and a depth camera. The pose and acceleration information of the robot is obtained through the pose sensor. The SLAM algorithm based on a fusion of LiDAR, a depth camera, and the inertial measurement unit was built. Secondly, the improved ant colony algorithm was used to carry out global path planning. Meanwhile, the dynamic window method was used to realize local planning and local obstacle avoidance. Finally, experiments were carried out on a robot platform to verify the reliability of the proposed method. The experiment results showed that the map constructed by multi-sensor information fusion was closer to the real environment, and the accuracy and robustness of SLAM were effectively improved. The turning angle of the path was smoothed using the improved ant colony algorithm, and the real-time obstacle avoidance was able to be realized using the dynamic window method. The efficiency of path planning was improved, and the automatic feedback control of the intelligent vehicle was able to be realized.

Shared electric vehicles (SEVs) are becoming a new way for urban residents to travel because of their environmental protection, energy saving, and sustainable development. However, at present, the operation mode of shared electric vehicles has the problem that the vehicle cannot be utilized efficiently. For this reason, this paper studied the mode of SEVs with ride-sharing (MSEVRS) and SEVs routing optimization under this mode. Firstly, the operation principle of MSEVRS is presented, which includes the collection of user demand information and SEVs information and the routing optimization of SEVs, both of which are completed by the user and SEVs management center. Secondly, the routing optimization model of SEVs with ride-sharing is proposed, in which the SEVs operation cost, user time cost, user rental cost, and user ride-sharing bonus are taken into account. And the genetic algorithm is designed to solve the model. Finally, a case study is carried out to illustrate the effectiveness of the proposed model. The results show that the proposed routing optimization model achieves the optimal SEVs route, realizes the MSEVRS, and improves the utilization rate of SEVs. Compared with the current SEVs mode (CSEVM), the MSEVRS reduces the number of vehicles, user rental cost, the total cost of users, and the total cost of user and company of SEVs. And the total distance is reduced, which means saving energy. Moreover, it shows that MSEVRS obtains a better cost performance and service for users and has a better application prospect.

The Kelp grouper Epinephelus moara is one of the most widely consumed and economically important marine fish in China. The species can tolerate a wide range of salinity, but genomic resources are not available, and the molecular mechanisms underlying adaptation to salinity at the transcriptomic level remain largely unclear. In this study, the transcriptomic responses of the liver of E. moara under low salinity were investigated using the Illumina digital gene expression system. After de novo assembly, 499,356 transcripts were generated and contributed 445,068 unigenes. A total of 14, 19, 33 and 3101 genes were differentially expressed following exposure to low salinity stress for 2, 6, 24 and 48 h, respectively. Only two genes were differentially expressed in all groups. Four genes related to metabolism and ambient salinity adaption were randomly selected to validate the differentially expressed genes (DEGs) by real-time PCR. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to analyse the functional significance of DEGs, including those responding to salinity through diverse biological processes, cellular components, molecular functions, and pathways associated with metabolic and osmotic responses. This work provides new insight into the response to salinity challenges in E. moara, and the findings expand our knowledge of the molecular basis of metabolic regulation mechanisms in this species. Additionally, the transcriptional data provide a valuable resource for future molecular and genetic studies on E. moara.

Abstract Background Islet transplantation is increasingly used in the diabetic patients to control the blood glucose level. However, the functional output of transplanted islets remains hampered due to the local inflammation, loss of islets, etc. To that end, in this study we explored to enhance the functional output of transplanted islets in diabetic mice by employing a drug-eluting scaffold with a payload of interleukin 4 (IL-4). Results According to the in vitro studies, the scaffold showed no cytotoxicity, a rapid release of IL-4 within a week and the IL-4 retained its bioactivity. During the 4-week time window after the islet transplantation, in vivo studies showed that the levels of blood insulin and C-peptide 2 in diabetic mice in the drug-eluting scaffold group significantly increased since week 2, which effectively reduced the blood glucose level. In addition, these mice demonstrated a stronger capability to withstand a rapid glucose spike as evidenced by the tolerance of sudden oral glucose challenge test result. A further mechanistic study suggested that the enhanced functional output could be attributed to the M2 polarization of macrophages as evidenced by the increase of CD163+/CD68+ macrophages in the islet tissues. A M2 polarization of macrophages is widely believed to exert an anti-inflammatory influence on local tissues, which could accelerate the resolution of local inflammation following the islet transplantation. Conclusion Our study shed a new light on the hyperglycemia management of diabetic patients following the islet transplantation.

Oceanic motions associated with horizontal scales smaller than 50 km remain unresolved in climate models. Here the authors show that motions in this scale range are critical to the global transport of heat between the ocean interior and the atmosphere, and are thus a key component of the Earth’s climate.

Deep waters of the Atlantic, Pacific and Indian Oceans upwell in the Southern Oceanbut the exact pathways are not fully characterized. Here the authors present a three dimensional view showing a spiralling southward path, with enhanced upwelling by eddy-transport at topographic hotspots.

Based on the method of deriving two-dimensional wavenumber spectrum by using instantaneous Doppler wavenumber in bistatic synthetic aperture radar, the analytical solution of two-dimensional wavenumber spectrum of multi-receiver synthetic aperture sonar (SAS) was deduced, and the analytical expression of the half-quasi-bistatic angle was obtained under the non-stop-and-go assumption. Based on the derived two-dimensional wavenumber spectrum, the ωk algorithm suitable for multi-sub-array SAS was proposed, which solved the problem that using the displacement phase centre approximation cannot well adapt to the wide mapping area imaging, and the correctness and validity of the algorithm have been verified by the simulation data and the lake experiment data.

The future international Surface Water and Ocean Topography (SWOT) Mission, planned for launch in 2021, will make high-resolution 2D observations of sea-surface height using SAR radar interferometric techniques. SWOT will map the global and coastal oceans up to 77.6° latitude every 21 days over a swath of 120 km (20 km nadir gap). Today’s 2D mapped altimeter data can resolve ocean scales of 150 km wavelength whereas the SWOT measurement will extend our 2D observations down to 15–30 km, depending on sea state. SWOT will offer new opportunities to observe the oceanic dynamic processes at scales that are important in the generation and dissipation of kinetic energy in the ocean, and that facilitate the exchange of energy between the ocean interior and the upper layer. The active vertical exchanges linked to these scales have impacts on the local and global budgets of heat and carbon, and on nutrients for biogeochemical cycles. This review paper highlights the issues being addressed by the SWOT science community to understand SWOT’s very precise sea surface height (SSH)/surface pressure observations, and it explores how SWOT data will be combined with other satellite and in situ data and models to better understand the upper ocean 4D circulation (x, y, z, t) over the next decade. SWOT will provide unprecedented 2D ocean SSH observations down to 15–30 km in wavelength, which encompasses the scales of “balanced” geostrophic eddy motions, high-frequency internal tides and internal waves. This presents both a challenge in reconstructing the 4D upper ocean circulation, or in the assimilation of SSH in models, but also an opportunity to have global observations of the 2D structure of these phenomena, and to learn more about their interactions. At these small scales, ocean dynamics evolve rapidly, and combining SWOT 2D SSH data with other satellite or in situ data with different space-time coverage is also a challenge. SWOT’s new technology will be a forerunner for the future altimetric observing system, and so advancing on these issues today will pave the way for our future.

Conceived as a major new tool for climate studies, the Surface Water and Ocean Topography (SWOT) satellite mission will launch in late 2021 and will retrieve the dynamics of the oceans upper layer at an unprecedented resolution of a few kilometers. During the calibration and validation (CalVal) phase in 2022, the satellite will be in a 1-day-repeat fast sampling orbit with enhanced temporal resolution, sacrificing the spatial coverage. This is an ideal opportunity – unique for many years to come – to coordinate in situ experiments during the same period for a focused study of fine scale dynamics and their broader roles in the Earth system. Key questions to be addressed include the role of fine scales on the ocean energy budget, the connection between their surface and internal dynamics, their impact on plankton diversity, and their biophysical dynamics at the ice margin.

The assembly consistency of a diesel engine will affect its nitrogen oxides (NOx) emission variation. In order to improve the NOx emissions of diesel engines, a study was carried out based on the assembly tolerance variation of the diesel engine’s combustion system. Firstly, a diesel engine which meets the Euro VI standards together with the experimental data is obtained. The mesh model and combustion model of the engine combustion system are built in the Converge software (version 2.4, Tecplot, Bellevue, DC, USA), and the experimental data is used to calibrate the combustion model obtained in the Converge software. Then, the four-factor and three-level orthogonal simulation experiments are carried out on the dimension parameters that include nozzle extension height, throat diameter, shrinkage diameter and combustion chamber depth. Through mathematical analysis on the experimental data, the results show that the variation of nozzle extension height and combustion chamber depth have a strong influence on NOx emission results, and the variation of combustion chamber diameter also has a weak influence on NOx production. According to the regression model obtained from the analysis, there is a quadratic function relating the nozzle extension height and NOx emissions and the amount of NOx increases with increasing nozzle extension height. The relationship between emission performance and size parameters is complex. In the selected size range, the influence of the variation of the chamber diameter on NOx is linear. The variation of the chamber depth also has an effect on NOx production, and the simulation results vary with the change of assembly tolerance variation. Thus, in the engine assembly process, it is necessary to strictly control the nozzle extension height and combustion chamber depth. The research results are useful to improve the NOx emission of diesel engine and provide a basis for the control strategy of selective catalytic reduction (SCR) devices.

A new fractional two-dimensional triangle function combination discrete chaotic map (2D-TFCDM) with the discrete fractional difference is proposed. We observe the bifurcation behaviors and draw the bifurcation diagrams, the largest Lyapunov exponent plot, and the phase portraits of the proposed map, respectively. On the application side, we apply the proposed discrete fractional map into image encryption with the secret keys ciphered by Menezes-Vanstone Elliptic Curve Cryptosystem (MVECC). Finally, the image encryption algorithm is analysed in four main aspects that indicate the proposed algorithm is better than others.

An improved understanding of the pluripotency maintenance of embryonic stem (ES) cells is important for investigations of early embryo development and for cell replacement therapy, but the mechanism behind pluripotency is still incompletely understood. Recent findings show that zinc, an essential trace element in humans, is critically involved in regulating various signaling pathways and genes expression. However, its role in ES cell fate determination remains to be further explored. Here we showed that 2μM zinc chloride (ZnCl2) transiently maintained mouse ES cell pluripotency in vitro. The cultured mouse ES cells remained undifferentiated under 2μM ZnCl2 treatment in leukemia inhibitory factor (LIF) withdrawal, retinoic acid (RA) or embryoid bodies (EBs) differentiation assays. In addition, ZnCl2 increased pluripotency genes expression and inhibited differentiation genes expression. Further mechanistic studies revealed that ZnCl2 transiently activated signal transducers and activators of transcription 3 (Stat3) signaling through promoting Stat3 phosphorylation. Inhibition of Stat3 signaling abrogated the effects of ZnCl2 on mouse ES cell pluripotency. Taken together, this study demonstrated a critical role of zinc in the pluripotency maintenance of mouse ES cells, as well as an important regulator of Stat3 signaling.

The original version of this Article contained errors in Fig. 6. In panel a, the grey highlights obscured the curves for CESM, CM2.6 and SOSE, and the labels indicating SWIR, KP, MR, PAR, and DP were inadvertently omitted. These have now been corrected in both the PDF and HTML versions of the Article.

A polyvinylidene fluoride (PVDF)-type chelating membrane bearing poly(amino phosphonic acid) groups, denoted as ethylenediamine tetra(methylene phosphonic acid) (EDTMPA)-tetrabutyl orthotitanate (TBOT)/PVDF, was employed to remove Ni(II) from the aqueous solution. The effects of coexisting Ca(II), Pb(II), citrate, nitrilotriacetic acid (NTA) and ethylenediaminetetraacetic acid (EDTA) on the Ni(II) adsorption by this chelating membrane were revealed using density functional theory (DFT) calculations. Pb(II) showed a more detrimental effect than Ca(II) on the Ni(II) uptake; EDTA interfered with the capture of Ni(II) more remarkably than citrate and NTA. The results derived from DFT calculations were consistent with the experimental data. Ni(II) and Pb(II) showed more excellent affinity to the EDTMPA-TBOT/PVDF membrane than Ca(II). The stabilities between Ni(II) and the [EDTMPA-TBOT]7− chelating ligand of the membrane and those between Ni(II) and the three aforementioned complexing reagents followed the sequence: [Ni(II)-(EDTMPA-TBOT)]5− > Ni(II)-EDTA > Ni(II)-NTA > Ni(II)-citrate. The complexation between Ni(II) and the chelating membrane was prominent with the presence of citrate, NTA and EDTA.

Grapevine leafroll disease (GLD) is caused by a complex of several virus species (grapevine leafroll-associated viruses, GLRaV) in the family Closteroviridae. Because of its increasing importance, it is critical to determine which species of GLRaV is predominant in each region where this disease is occurring. A structured sampling design, utilizing a combination of RT-PCR based testing and sequencing methods, was used to survey GLRaVs in Napa Valley (California, USA) vineyards (n = 36). Of the 216 samples tested for GLRaV-1, -2, -3, -4, -5, and -9, 62% (n = 134) were GLRaV positive. Of the positives, 81% (n = 109) were single infections with GLRaV-3, followed by GLRaV-2 (4%, n = 5), while the remaining samples (15%, n = 20) were mixed infections of GLRaV-3 with GLRaV-1, 2, 4, or 9. Additionally, 468 samples were tested for genetic variants of GLRaV-3, and of the 65% (n = 306) of samples positive for GLRaV-3, 22% were infected with multiple GLRaV-3 variants. Phylogenetic analysis utilizing sequence data from the single infection GLRaV-3 samples produced seven well-supported GLRaV-3 variants, of which three represented 71% of all GLRaV-3 positive samples in Napa Valley. Furthermore, two novel variants, which grouped with a divergent isolate from New Zealand (NZ-1), were identified, and these variants comprised 6% of all positive GLRaV-3 samples. Spatial analyses showed that GLRaV-3a, 3b, and 3c were not homogeneously distributed across Napa Valley. Overall, 86% of all blocks (n = 31) were positive for GLRaVs and 90% of positive blocks (n = 28) had two or more GLRaV-3 variants, suggesting complex disease dynamics that might include multiple insect-mediated introduction events.