Search

Brassica juncea is an important dietary vegetable cultivated and consumed in China for its edible stalks and leaves. The purple leaf mustard, which is rich in anthocyanins, is eye-catching and delivers valuable nutrition. However, the molecular mechanism involved in anthocyanin biosynthesis has not been well studied in B. juncea. Here, histological and transcriptome analyses were used to characterize the purple leaf color and gene expression profiles. Free-hand section analysis showed that the anthocyanin was mainly accumulated in the adaxial epidermal leaf cells. The anthocyanin content in the purple leaves was significantly higher than that in the green leaves. To investigate the critical genes and pathways involved in anthocyanin biosynthesis and accumulation, the transcriptome analysis was used to identify the differentially expressed genes (DEGs) between the purple and green leaves from the backcrossed BC3 segregation population in B. juncea. A total of 2,286 different expressed genes were identified between the purple and green leaves. Among them, 1,593 DEGs were up-regulated and 693 DEGs were down-regulated. There were 213 differently expressed transcription factors among them. The MYB and bHLH transcription factors, which may regulate anthocyanin biosynthesis, were up-regulated in the purple leaves. Interestingly, most of the genes involved in plant–pathogen interaction pathway were also up-regulated in the purple leaves. The late biosynthetic genes involved in anthocyanin biosynthesis were highly up-regulated in the purple leaves of B. juncea. The up regulation of BjTT8 and BjMYC2 and anthocyanin biosynthetic genes (BjC4H, BjDFR, and BjANS) may activate the purple leaf formation in B. juncea. This study may help to understand the transcriptional regulation of anthocyanin biosynthesis in B. juncea.

Tomato (Solanum lycopersicum), an economically important vegetable crop cultivated worldwide, often suffers massive financial losses due to Phytophthora infestans (P. infestans) spread and breakouts. Arbuscular mycorrhiza (AM) fungi mediated biocontrol has demonstrated great potential in plant resistance. However, little information is available on the regulation of mycorrhizal tomato resistance against P. infestans. Therefore, microRNAs (miRNAs) sequencing technology was used to analyse miRNA and their targets in the mycorrhizal tomato after P. infestans infection. Our study showed a lower severity of necrotic lesions in mycorrhizal tomato than in nonmycorrhizal controls. We investigated 35 miRNAs that showed the opposite expression tendency in mycorrhizal and nonmycorrhizal tomato after P. infestans infection when compared with uninfected P. infestans. Among them, miR319c was upregulated in mycorrhizal tomato leaves after pathogen infection. Overexpression of miR319c or silencing of its target gene (TCP1) increased tomato resistance to P. infestans, implying that miR319c acts as a positive regulator in tomato after pathogen infection. Additionally, we examined the induced expression patterns of miR319c and TCP1 in tomato plants exposed to salicylic acid (SA) treatment, and SA content and the expression levels of SA-related genes were also measured in overexpressing transgenic plants. The result revealed that miR319c can not only participates in tomato resistance to P. infestans by regulating SA content, but also indirectly regulates the expression levels of key genes in the SA pathway by regulating TCP1. In this study, we propose a novel mechanism in which the miR319c in mycorrhizal tomato increases resistance to P. infestans.

Abstract Few-layer graphitic carbon nanoribbons (GCN) with rich defective sites were prepared by pyrolysis at 800 oC in N2 of in situ-chelated Fe-polyaniline complexes synthesized via one-pot homogeneous Fenton-like oxidative polymerization of an acidic aniline solution. A minimal amount of iron (0.47 wt%) made a pivotal role in the nanoribbon growth and graphitization of GCN, and deposited highly dispersed iron species on GCN without post-synthesis acid leaching, which greatly simplified the synthesis procedure of GCN with improved yield. GCN exhibited high activity and stability for catalytic degradation of organic pollutants with peroxymonosulfate (PMS) mainly via non-radical pathways. The influences of various operating parameters on the catalytic performance of GCN were investigated. Scavenging tests, spin-trapping electron paramagnetic resonance spectra, electrochemical analyses, and theoretical calculations unveiled that 1O2 was the main reactive oxygen species generated from synergistic activation of PMS on GCN while GCN-mediated electron transfer made a minor contribution to organic degradation.

Abstract The camouflaged object segmentation model (COSM) has recently gained substantial attention due to its remarkable ability to detect camouflaged objects. Nevertheless, deep vision models are widely acknowledged to be susceptible to adversarial examples, which can mislead models, causing them to make incorrect predictions through imperceptible perturbations. The vulnerability to adversarial attacks raises significant concerns when deploying COSM in security-sensitive applications. Consequently, it is crucial to determine whether the foundational vision model COSM is also susceptible to such attacks. To our knowledge, our work represents the first exploration of strategies for targeting COSM with adversarial examples in the digital world. With the primary objective of reversing the predictions for both masked objects and backgrounds, we explore the adversarial robustness of COSM in full white-box and black-box settings. In addition to the primary objective of reversing the predictions for masked objects and backgrounds, our investigation reveals the potential to generate any desired mask through adversarial attacks. The experimental results indicate that COSM demonstrates weak robustness, rendering it vulnerable to adversarial example attacks. In the realm of COS, the projected gradient descent (PGD) attack method exhibits superior attack capabilities compared to the fast gradient sign (FGSM) method in both white-box and black-box settings. These findings reduce the security risks in the application of COSM and pave the way for multiple applications of COSM.

Abstract The intrinsic similarity between camouflaged objects and background environment impedes the automatic detection/segmentation of camouflaged objects, and novel network architectures for deep learning are promising to overcome this challenge and improve detection accuracy. However, these existing network architectures for distinguishing between camouflaged objects and their backgrounds do not account for the constraint of detection speed, which results in high computational complexity and the inability to meet the requirements of rapid detection. Therefore, based on the human visual system, this study proposes a single-stage lightweight camouflage object detection network using multilevel feature fusion, integrating features of various feature layers and receptive field sizes. Using three benchmark datasets for normal camouflaged objects, the lightweight network (LINet) model demonstrated an accuracy superior to those of six existing mainstream camouflaged object detection methods. Its detection speed, 126.3 frames per second, is significantly higher than those of the existing mainstream methods, enabling rapid detection with a maximum increase of 187.62%. The accuracy of LINet is the minimum and maximum for Resnet101 and Resnet152, respectively. These findings pave the way for diverse applications of camouflaged target detection algorithms.

As the new generation of artificial intelligence (AI) continues to evolve, weather big data and statistical machine learning (SML) technologies complement each other and are deeply integrated to significantly improve the processing and forecasting accuracy of fishery weather. Accurate fishery weather services play a crucial role in fishery production, serving as a great safeguard for economic benefits and personal safety, enabling fishermen to carry out fishery production better, and contributing to the sustainable development of the fishery industry. The objective of this paper is to offer an understanding of the present state of research and development in SML technology for simulating and forecasting fishery weather. Specifically, we analyze the current state of research and technical features of SML in weather and summarize the applications of SML in simulation and forecasting of fishery weather, which mainly include three aspects: fishery weather scenario generation, fishery weather forecasting, and fishery extreme weather warning. We also illustrate the main technical means and principles of SML technology. Finally, we summarize the most advanced SML fields and provide an outlook on their application value in the field of fishery weather.

IntroductionBreeding rice with drought tolerance for harsh environments is crucial for agricultural sustainability. Understanding the genetic underpinnings of drought tolerance is vital for developing resilient rice varieties. Genome-wide association studies (GWAS) have emerged as pivotal tools in unravelling the complex genetic architecture of traits like drought tolerance, capitalizing on the natural genetic diversity within rice germplasm collections.MethodsIn this study, a comprehensive panel of 210 rice varieties was phenotyped over ten days in controlled conditions, subjected to simulated drought stress using 20% PEG 6000 in petri dishes. Throughout the stress period, crucial traits such as germination percentage (GP), germination rate index (GRI), mean germination time (MGT), and seedling percentage (SP) were meticulously monitored.ResultsThe GWAS analysis uncovered a total of 38 QTLs associated with drought tolerance traits, including novel loci like qMGT-5.2, qSP-3, qSP7.2, and qGP-5.2. Additionally, RNA-seq analysis identified ten genes with significant expression differences under drought stress conditions. Notably, haplotype analysis pinpointed elite haplotypes in specific genes linked to heightened drought tolerance.DiscussionOverall, this study underscores the importance of GWAS in validating known genes while unearthing novel loci to enrich the genetic resources for enhancing drought tolerance in rice breeding programs.

Formation-containment control in multi-agent systems faces a critical challenge: how to stabilize all formation leaders when the $\alpha -$ leader’s influence diminishes over topology distance, especially under input delays? This challenge is particularly acute in PDE-based models, where information decay is intrinsic, making it difficult for the $\alpha -$ leader—a leader among leaders—to affect far-away agents, especially under speed constraints.Our work tackles this challenge by proposing a three-layer hierarchical control framework based on Partial Differential Equations (PDEs). Our key innovation is an integral-type delayed compensation input specifically designed for the $\alpha -$ leader. This control law uses kernel functions derived from backstepping transformation and equivalence principles, tailored to compensate for input delays. By providing the $L^{2}$ space expansion of these kernel functions, we show that formation control error for finite agents is acceptable, even with approximations.We organize formation leaders into a one-dimensional chain-like topology, categorizing them as leaders, anchors, or $\alpha -$ leaders based on their roles. For other agents, we derive distributed control laws from the discrete form of PDEs governing formation deployment. Followers converge to the convex hull spanned by leaders, forming an internal two-dimensional surface. This PDE-based approach ensures invariance in translation, rotation, and expansion.Our work also contributes to the mathematical foundations of PDE-based multi-agent systems. We discuss the numerical solution of kernel functions, offer a distributional interpretation, and—critically—analyze the discretization error between PDE and ODE models. This analysis reveals the relationship between stability, time step, spatial step, and control laws, addressing an often-ignored issue in the field.Simulation examples validate our theoretical findings, showing effective formation-containment control under our framework.

In this study, a MOF-199/Ag@Au SERS sensing structure was successfully synthesized by combining metal–organic frameworks (MOFs) with surface-enhanced Raman scattering (SERS) technology for the efficient detection of dopamine (DA), a biomarker for neurological diseases, in serum. Using electrochemical methods, a copper-based MOF (MOF-199) was synthesized in situ on copper substrates and further deposited with silver nanoparticles (AgNPs). Subsequently, gold nanoshells were encapsulated around these silver cores by in situ chemical deposition. This preparation process is simple, controllable, and inexpensive. Furthermore, a novel Azo reaction-based DA SERS method was proposed to detect 1 pM DA, which represents an improvement in sensitivity by two orders of magnitude compared to previous unlabeled SERS detection methods and by four orders of magnitude compared to another SERS approach proposed in this work. There was an excellent linear relationship (R2 = 0.976) between the SERS signal at 1140 cm−1 and the DA concentration (0.001 M~1 pM). The results indicate that the MOF-199/Ag@Au sensor structure can successfully achieve both the qualitative and quantitative detection of DA in serum, thus providing a robust technical basis for the application of SERS technology in the field of clinical neurological disease screening.

Aqueous electrolytes offer superior prospects for advanced energy storage. “Water-in-salt” (WIS) electrolytes exhibit a wide electrochemical stability window (ESW), but their low conductivity, high viscosity, and precipitation at low temperatures restrict their application. Herein, we report a novel localized “water-in-pyrrolidinium chloride” electrolyte (LWIP; 1 ​mol/L, N-propyl-N-methylpyrrolidinium chloride/(water and N,N-dimethylformamide, 1:4 by molality)) enabling high-voltage, low-temperature supercapacitors (SCs). The greatly improved ESW (3.451 ​V) is mainly attributed to the strong solvation between Cl− and water molecules, which broadens the negative stability. This water-binding mechanism is very different from that of a WIS electrolyte based on alkali metal salt. SCs using LWIP electrolytes not only yield a high operating voltage of 2.4 ​V and excellent capacity retention (82.8% after 15,000 cycles at 5 ​A ​g−1) but also operate stably at −20 ​°C. This work provides new approaches for the design and preparation of novel electrolytes.

In this work, phase-apodized silicon grating filters with varying sidewall corrugation width and location were investigated, while the resonance wavelength, extinction ratio, and rejection bandwidth were tuned flexibly. The grating filters with a waveguide width of 500 nm and grating period of 400 nm were fabricated and characterized as a proof of concept. The resonance wavelength of the device can be shifted by 4.54 nm by varying the sidewall corrugation width from 150 to 250 nm. The corresponding rejection bandwidth can be changed from 1.19 to 2.03 nm by applying a sidewall corrugation location offset from 50 to 200 nm. The experimental performances coincide well with the simulation results. The presented sidewall corrugation-modulated apodized grating can be expected to have great application prospects for optical communications and semiconductor lasers.

To address the challenges of reduced localization accuracy and incomplete map construction demonstrated using classical semantic simultaneous localization and mapping (SLAM) algorithms in dynamic environments, this study introduces a dynamic scene SLAM technique that builds upon direct sparse odometry (DSO) and incorporates instance segmentation and video completion algorithms. While prioritizing the algorithm’s real-time performance, we leverage the rapid matching capabilities of Direct Sparse Odometry (DSO) to link identical dynamic objects in consecutive frames. This association is achieved through merging semantic and geometric data, thereby enhancing the matching accuracy during image tracking through the inclusion of semantic probability. Furthermore, we incorporate a loop closure module based on video inpainting algorithms into our mapping thread. This allows our algorithm to rely on the completed static background for loop closure detection, further enhancing the localization accuracy of our algorithm. The efficacy of this approach is validated using the TUM and KITTI public datasets and the unmanned platform experiment. Experimental results show that, in various dynamic scenes, our method achieves an improvement exceeding 85% in terms of localization accuracy compared with the DSO system.

Abstract Background The combination of anti-programmed death-1 antibodies and chemotherapy is effective; however, there are no reliable outcome prediction factors. We investigated the prognostic factors based on 18Fluorine-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) quantitative and hematological parameters to predict progression-free survival (PFS) in relapsed/refractory classical Hodgkin lymphoma (R/R cHL) patients treated with immune checkpoint inhibitors (ICIs) and chemotherapy. Methods This retrospective study included 31 patients who underwent 18F-FDG PET/CT before and during treatment. Pretreatment metabolic and hematological parameters were evaluated using Cox regression analysis to identify predictors of PFS. Based on the cut-off values calculated using the receiver operating characteristic (ROC) curve, patients were classified into low-, intermediate-, and high-risk groups. Kaplan–Meier curves and the log-rank test were used to compare survival differences between the groups. Results Cox multivariable analysis indicted that the treatment response based on Lactate dehydrogenase (LDH), Lugano classification and SUVmax were independent predictors of PFS (P = 0.004, 0.007 and 0.039, respectively). The optimal cut-off values for SUVmax and LDH were 11.62 and 258.5 U/L, respectively (P

In this study, a hydrophobic, wear-resistant ultraviolet (UV)-curable coating was investigated as an alternative to traditional coatings with low hardness and high susceptibility to scratching. The SiO2 nanoparticles were ground and modified using high-energy ball milling, during which the surface energy of nano-SiO2 particles rapidly increased as their particle size decreased. Different proportions of modified nano-SiO2 particles were added to the coating and cured into a film. The structure of the composite coating was analyzed via infrared spectroscopy, scanning electron microscopy, and X-ray diffraction, which confirmed the successful preparation of the composite coating. The mechanical and optical property tests of the coating were investigated. With a 5% nano-SiO2 content, the hardness of the coating reached 5H, whereas the adhesion was poor (2B), and the flexibility was 1. The overall comprehensive performance of the coating was best when the addition amount was 3%. The coating exhibited good hardness, flexibility, and adhesion. The hardness of the coating reached 4H, the adhesion was 4B, the flexibility was 5, the coating haze was 12.38 HZ, and the contact angle was 118°.

ObjectiveWe evaluated the difference in parathyroid visualization on 18F-FCH PET/CT images obtained at 5 and 60 min, and quantitatively analyzed the mode of FCH uptake at different time points, to determine the best imaging time for FCH PET/CT.MethodsThis retrospective study included 73 patients with hyperparathyroidism (HPT) who underwent 18F-FCH PET/CT imaging between December 2017 and December 2021. The diagnostic efficiency of 5- and 60-min dual time point imaging for the diagnosis of hyperparathyroidism and parathyroid adenoma and hyperplasia, were compared using visual and quantitative analyses.ResultsDual-time 18F-FCH PET/CT imaging visual analysis had diagnostic value for HPT. The receiver operating characteristic curve of PET/CT quantitative parameters for the diagnosis of HPT and lesions showed that the parathyroid/thyroid SUVmax ratio for 60-min imaging had a higher sensitivity and specificity (based on patient, sensitivity: 90.90% and specificity: 85.71%; based on focus, sensitivity: 83.06% and specificity: 85.71%) compared to that for 5-min imaging. PET/CT quantitative parameters can distinguish parathyroid adenoma and hyperplasia. The 60-min parathyroid SUVmax value had the highest diagnostic value (cutoff: 3.945; area under the curve: 0.783).ConclusionThe quantitative parameters of 60min 18F-FCH PET/CT have more advantages in aiding in the pathologica diagnosis and clinical treatment of HPT.

Natural sand has a loose and porous structure with low strength, and is prone to many geoengineering problems that cause huge losses. In this study, an organic polymer-polymer-fiber blend was used to improve the strength of sand. Using a series of laboratory and numerical simulation tests, researchers have investigated the microdamage behavior of an organic polymer and fiber-treated sand in various types of mechanical tests and explored the improvement mechanism. The results showed that the polymer- and fiber-treated sand enhanced the integrity and exhibited differential damage responses under different test conditions. The increase in polymer content induced uniform force transfer, leading to a wider range of particle motion and crack initiation, whereas the fibers adhered and confined the surrounding particles, inducing an arching force chain and dispersive/buckling cracking. Polymer- and fiber-treated sands increased their energy-carrying capacity and improved their energy release, which affected the damage characteristics. Organic polymers, fibers, and sand particles were wrapped around each other to form an effective interlocking structure, which enhances the integrity and mechanical properties of sand. This study provides novel ideas and methods in the polymer-fiber composite treatment of sand in the microscopic field.

Infective endocarditis (IE) has been recognized as a biofilm-related disease caused by pathogenic microorganisms, such as bacteria and fungi that invade and damage the heart valves and endocardium. There are many difficulties and challenges in the antimicrobial treatment of IE, including multi-drug resistant pathogens, large dose of drug administration with following side effects, and poor prognosis. For the past few years, the development of nanotechnology has promoted the use of nanoparticles as antimicrobial nano-pharmaceuticals or novel drug delivery systems (NDDS) in antimicrobial therapy for chronic infections and biofilm-related infectious disease as these molecules exhibit several advantages. Therefore, nanoparticles have a potential role to play in solving problems in the treatment of IE, including improving antimicrobial activity, increasing drug bioavailability, minimizing frequency of drug administration, and preventing side effects. In this article, we review the latest advances in nanoparticles against drug-resistant bacteria in biofilm and recommends nanoparticles as an alternative strategy to the antibiotic treatment of IE.

Patients with atrial fibrillation (AF) suffer from a high risk of thrombosis. Currently, the CHA2DS2-VASc score is the most widely used tool for risk stratification in patients with AF, but it has disappointing accuracy and limited predictive value, especially in those with low scores. Thrombi in patients with AF mostly grow in their left atrial appendages (LAA), which is directly related to the abnormal morphology of the LAA or the left atrium and the unusual hemodynamic state around LAA, which may sensitively evaluate the risk of thrombosis complications in patients with AF and bring bases to clinical plans of medication and operation. Therefore, we investigated the research progress of hemodynamic and morphological studies about the predictive value of thrombosis risk in patients with AF, intending to discuss the prediction potential of morphological and hemodynamic indexes when compared with the presently used CHA2DS2-VASc system and how to build a more precise thromboembolic event prediction model for patients with AF.

With the aging of the population in worldwide, valvular heart disease has become one of the most prominent life-threatening diseases in human health, and heart valve replacement surgery is one of the therapeutic methods for valvular heart disease. Currently, commercial bioprosthetic heart valves (BHVs) for clinical application are prepared with xenograft heart valves or pericardium crosslinked by glutaraldehyde. Due to the residual cell toxicity from glutaraldehyde, heterologous antigens, and immune response, there are still some drawbacks related to the limited lifespan of bioprosthetic heart valves, such as thrombosis, calcification, degeneration, and defectiveness of re-endothelialization. Therefore, the problems of calcification, defectiveness of re-endothelialization, and poor biocompatibility from the use of bioprosthetic heart valve need to be solved. In this study, hydrogel hybrid heart valves with improved anti-calcification and re-endothelialization were prepared by taking decellularized porcine heart valves as scaffolds following grafting with double bonds. Then, the anti-biofouling zwitterionic monomers 2-methacryloyloxyethyl phosphorylcholine (MPC) and vascular endothelial growth factor (VEGF) were utilized to obtain a hydrogel-coated hybrid heart valve (PEGDA-MPC-DHVs@VEGF). The results showed that fewer platelets and thrombi were observed on the surface of the PEGDA-MPC-DHVs@VEGF. Additionally, the PEGDA-MPC-DHVs@VEGF exhibited excellent collagen stability, biocompatibility and re-endothelialization potential. Moreover, less calcification deposition and a lower immune response were observed in the PEGDA-MPC-DHVs@VEGF compared to the glutaraldehyde-crosslinked DHVs (Glu-DHVs) after subcutaneous implantation in rats for 30 days. These studies demonstrated that the strategy of zwitterionic hydrogels loaded with VEGF may be an effective approach to improving the biocompatibility, anti-calcification and re-endothelialization of bioprosthetic heart valves.

Atrial fibrillation (AF) is one of the most common sustained tachyarrhythmias worldwide, and its prevalence is positively correlated with aging. AF not only significantly reduces the quality of life of patients but also causes a series of complications, such as thromboembolism, stroke, and heart failure, increases the average number of hospitalizations of patients, and places a huge economic burden on patients and society. Traditional drug therapy and ablation have unsatisfactory success rates, high recurrence rates, and the risk of serious complications. Surgical treatment is highly traumatic. The nano drug delivery system has unique physical and chemical properties, and in the application of AF treatment, whether it is used to assist in enhancing the ablation effect or for targeted therapy, it provides a safer, more effective and more economical treatment strategy.

ObjectiveWe compared the efficacy of post-therapy whole-body scintigraphy (Tx-WBS) in terms of detecting lesions in patients with differentiated thyroid cancer (DTC) on days 3, 7, and 10 after 131I treatment, and we determined the optimal imaging time.MethodsClinical data from 161 DTC patients treated with 131I were collected. All patients underwent day 3 imaging, but only 98 patients underwent day 3 and day 7 imaging, and 63 patients underwent day 3 and day 10 imaging at the same time. And the thyroid bed uptake was visually graded. The radioactivity ratios of the thyroid bed, neck lymph nodes, lungs, and liver (to the background) were calculated to allow a semiquantitative analysis.ResultsVisual analysis showed that delayed imaging revealed more lymph node and lung radioactivity, early imaging showed more residual thyroid tissue, and significant differences in uptake were apparent at days 3, 7, and 10 (P < 0.001). Semiquantitative analysis revealed significant differences in the target-to-background ratios of the residual thyroid bed, lungs, and liver at days 3, 7, and 10. On these days, the imaging sensitivities in terms of detecting metastatic lymph nodes were 29.58%, 39.02%, and 19.35%, and the specificities were 75.56%, 75.86%, and 75% (P = 0.465, 0.154, and 0.763, respectively). In terms of lung metastasis detection, the sensitivities were 29.58%, 38.46%, and 13.33% respectively, and the specificities were 98.33%, 100%, and 95.83% (P < 0.001, < 0.001, and P=0.238).ConclusionMore residual thyroid tissue can be detected by imaging on day 3; imaging on day 7 more effectively detects lung metastases than does imaging on day 3 or 10.

With the increasing applications of unmanned aerial vehicles (UAVs) in surveying, mapping, rescue, etc., the security of autonomous flight in complex environments becomes a crucial issue. Deploying autonomous UAVs in complex environments typically requires them to have accurate dynamic obstacle perception, such as the detection of birds and other flying vehicles at high altitudes, as well as humans and ground vehicles at low altitudes or indoors. This work’s primary goal is to cope with both static and moving obstacles in the environment by developing a new framework for UAV planning and control. Firstly, the point clouds acquired from the depth camera are divided into dynamic and static points, and then the velocity of the point cloud clusters is estimated. The static point cloud is used as the input for the local mapping. Path finding is simplified by identifying key points among static points. Secondly, the design of a trajectory tracking and obstacle avoidance controller based on the control barrier function guarantees security for moving and static obstacles. The path-finding module can stably search for the shortest path, and the controller can deal with moving obstacles with high-frequency. Therefore, the UAV can deal with both long-term planning and immediate emergencies. The framework proposed in this work enables a UAV to operate in a wider field, with better security and real-time performance.

Abstract Background The aim of this study was to evaluate the diagnostic efficacy of 18F-fluorocholine (18F-FCH) PET/CT for uremic hyperparathyroidism (uHPT) compared to 99mTc-sestaMIBI SPECT/CT and ultrasonography (US). Methods A total of 17 uHPT patients with stage 5 chronic kidney disease (CKD) were prospectively enrolled. All patients underwent US, 99mTc-sestaMIBI SPECT/CT, and 18F-FCH within 2 months and received surgical treatment. Visual and quantitative methods were used for image analyses. Intraoperative localization and postoperative histological results of the reference standard as well as the sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of the three modalities were analyzed using Pearson’s χ 2 tests. In addition, the diagnostic efficacy of 18F-FCH PET/CT for uHPT was evaluated. The relationships between PET parameters and laboratory parameters were assessed using the Spearman correlation coefficient. Results A total of 63 parathyroid hyperplasia lesions were resected in 17 uHPT patients, and 53 lesions were detected using 18F-FCH PET/CT with no false-positive results. The sensitivity, specificity, accuracy, PPV, and NPV were 84.13%, 100%, 86.49%, 100%, and 52.38%, respectively. In comparison, the corresponding values for 99mTc-sestaMIBI SPECT/CT and US were 63.49%, 90.91%, 67.57%, 97.56%, and 30.30% and 61.90%, 81.82%, 64.86%, 95.12%, and 27.27%, respectively. The volume of hyper-functioning parathyroid glands was significantly different between lesions positive in 18F-FCH PET/CT and negative in 18F-FCH PET/CT (mean volume 1.36 ± 0.55 cm3 vs. 0.83 ± 0.26 cm3; P = 0.019). US misidentified intrathyroidal parathyroid hyperplasia as thyroid nodules in three patients, while 18F-FCH PET correctly identified the anatomy. No significant associations were observed between PET parameters and laboratory parameters in uHPT. Conclusion 18F-FCH PET/CT was more sensitive and accurate for uHPT than 99mTc-sestaMIBI SPECT/CT and US, and had better preoperative diagnostic efficacy, particularly for lesions diagnosed as a thyroid nodule by US.

With the increasing demand for human-computer interaction and health monitoring, human behavior recognition with device-free patterns has attracted extensive attention. The fluctuations of the Wi-Fi signal caused by human actions in a Wi-Fi coverage area can be used to precisely identify the human skeleton and pose, which effectively overcomes the problems of the traditional solution. Although many promising results have been achieved, no survey summarizes the research progress. This paper aims to comprehensively investigate and analyze the latest applications of human behavior recognition based on channel state information (CSI) and the human skeleton. First, we review the human profile perception and skeleton recognition progress based on wireless perception technologies. Second, we summarize the general framework of precise pose recognition, including signal preprocessing methods, neural network models, and performance results. Then, we classify skeleton model generation methods into three categories and emphasize the crucial difference among these typical applications. Furthermore, we discuss two aspects, such as experimental scenarios and recognition targets. Finally, we conclude the paper by summarizing the issues in typical systems and the main research directions for the future.

Nano-WO3 particles are expected to find use in new shielding materials because of their significant absorption of near-infrared light in the 1400–1600 nm and 1900–2200 nm bands and high transmittance of visible light. In this study, WO3 was ground and dispersed using high-energy ball-milling to prepare a nano-WO3 dispersion using BYK331 as the dispersant and ethanol as the solvent. The prepared nano-WO3 dispersion was added to a photo-curing system and cured using UV irradiation to form films. The cured films were characterized using FT-IR, SEM, XRD, and TGA. The results showed that the nano-WO3 powder was evenly dispersed in the coating. The infrared blocking rate of the film continuously improved and the visible light transmission rate continuously decreased with increasing amounts of nano-WO3.For the film containing 6 wt%nano-WO3, the infrared blocking rate of the coating is 90%, the visible light transmittance is 70%, the hardness of the coating is 3B, and the adhesion is 3H. The thermal stability of the coating is also improved.

Recent years have witnessed increasing research interest in human behavior recognition as it provides attractive applications in various sensing scenarios. Among these encouraging implementations, device-free behavior recognition based on WiFi channel state information (CSI) has attracted significant attention due to the popularity of WiFi devices and abundant channel characteristics from CSI. Meanwhile, the CSI signal provides us with additional benefits because it can propagate through a wall. This through-the-wall and device-free scheme not only enables us to identify specific human actions but also to infer person activities by collecting the data from different rooms. This paper presents a survey on the state-of-art progresses in device-free through-the-wall human behavior recognition based on CSI. Specifically, this paper first introduces the basic concept of CSI and describes the signal variation caused by human behavior. Then, it illustrates that different human behaviors can cause signal transformation. Therefore, the unique map relationship between action and signal variation can be leveraged to recognize human behavior. Next, it provides the general architecture of through-the-wall behavior recognition and highlights its core characteristic. It investigates the state-of-art applications in various scenarios and analyzes specific design schemes and implementations. Afterward, it discusses the various across wall applications and makes a detailed comparison between non-through-the-wall and through-the-wall applications. Meanwhile, it analyzes many factors that affect recognition accuracy and emphasizes performance differences under across wall scenarios. Finally, this paper concludes by summarizing the issues and challenges faced and providing insights into the possible solution and future research trend.

Recently, device-free human behavior recognition has become a hot research topic and has achieved significant progress in the field of ubiquitous computing. Among various implementation, behavior recognition based on WiFi CSI (channel state information) has drawn wide attention due to its major advantages. This paper investigates more than 100 latest CSI based behavior recognition applications within the last 6 years and presents a comprehensive survey from every aspect of human behavior recognition. Firstly, this paper reviews general behavior recognition applications using the WiFi signal and presents the basic concept of CSI and the fundamental principle of CSI-based behavior recognition. This paper analyzes the key components and core characteristics of the system architecture of human behavior recognition using CSI. Afterward, we divide the sensing procedures into many steps and summarize the typical studies from these steps, including base signal selection, signal preprocessing, and identification approaches. Next, based on the recognition technique, we classify the applications into three groups, including pattern-based, model-based, and deep learning-based approach. In every group, we categorize the state-of-the-art applications into three groups, including coarse-grained specific behavior recognition, fine-grained specific behavior recognition, and activity inference. It elaborates the typical behavior recognition applications from five aspects, including experimental equipment, experimental scenario, behavior, classifier, and system performance. Then, this paper presents comprehensive discussions about representative applications from the implementation view and outlines the major consideration when developing a recognition system. Finally, this article concludes by analyzing the open issues of CSI-based behavior recognition applications and pointing out future research directions.

With the rapid progress of the Internet of Things (IoT) technology, human behavior recognition has become an important research topic in the field of ubiquitous computing and has obtained quite a number of research achievements. Accurate human behavior recognition can enhance the quality of human-computer interaction and facilitate the development of various sensing applications. With the popularity of smartphones and the improved performance of sensors such as speakers and microphones built in smartphones, the behavior recognition technique based on ultrasound signal of the smartphone has gained more attention and achieved several research results. In this paper, we first review the common behavior recognition techniques including light, video, sound, and frequency radio and outline their main characteristics. Then, we introduce the fundamental principle of human behavior recognition based on ultrasound signals. Specifically, these systems treat speakers and microphones embedded in smartphones as the transceiver and leverage the received signal changes caused by human movement including phase differences, frequency shift, and time of flight (ToF) to recognize human behavior. Next, we investigate the state-of-the-art studies and applications and analyze the signal processing techniques such as data collection, signal preprocessing, feature description, and behavior recognition approach. Afterward, according to the purpose of these applications, we classify them into five groups and compare them in detail including hand gesture recognition, activity recognition, hand trajectory tracking, vital sign monitoring, and lip reading. Finally, we conclude by discussing the limitations, challenges, and open issues involved in behavior recognition based on ultrasound signal of smartphone.

With the rapid development of Internet of Things, hand gesture recognition has drawn wide attention in the field of ubiquitous computing because it provides us with simple and natural human-computer interaction mode. Among these various implementations, hand gesture recognition using ultrasonic signals of smartphone has become a hot research topic due to its various advantages. In this paper, we consider the smartphone as an active sonar sensing system to identify hand movements. Specifically, the speakers emit ultrasonic signal and the microphone on the same phone receives the changed echo affected by hand movements. This paper investigates the state-of-the-art hand gesture applications and presents a comprehensive survey on the characteristics of studies using the active sonar sensing system. Firstly, we review the existing research of hand gesture recognition based on acoustic signals. After that, we introduce the characteristics of ultrasonic signal and describe the fundamental principle of hand gesture recognition. Then, we focus on the typical methods used in these studies and present a detailed analysis on signal generation, feature extraction, preprocessing, and recognition methods. Next, we investigate the state-of-the-art ultrasonic-based applications of hand gesture recognition using smartphone and analyze them in detail from dynamic gesture recognition and hand tracking. Afterwards, we make a discussion about these systems from signal acquisition, signal processing, and performance evaluation to obtain some insight into development of the ultrasonic hand gesture recognition system. Finally, we conclude by discussing the challenges, insight, and open issues involved in hand gesture recognition based on ultrasonic signal of the smartphone.

Background Cytoplasmic male sterility (CMS) is not only important for exploiting heterosis in crop plants, but also as a model for investigating nuclear-cytoplasmic interaction. CMS may be caused by mutations, rearrangement or recombination in the mitochondrial genome. Understanding the mitochondrial genome is often the first and key step in unraveling the molecular and genetic basis of CMS in plants. Comparative analysis of the mitochondrial genome of the hau CMS line and its maintainer line in B. juneca (Brassica juncea) may help show the origin of the CMS-associated gene orf288. Results Through next-generation sequencing, the B. juncea hau CMS mitochondrial genome was assembled into a single, circular-mapping molecule that is 247,903 bp in size and 45.08% in GC content. In addition to the CMS associated gene orf288, the genome contains 35 proteinencoding genes, 3 rRNAs, 25 tRNA genes and 29 ORFs of unknown function. The mitochondrial genome sizes of the maintainer line and another normal type line "J163-4" are both 219,863 bp and with GC content at 45.23%. The maintainer line has 36 genes with protein products, 3 rRNAs, 22 tRNA genes and 31 unidentified ORFs. Comparative analysis the mitochondrial genomes of the hau CMS line and its maintainer line allowed us to develop specific markers to separate the two lines at the seedling stage. We also confirmed that different mitotypes coexist substoichiometrically in hau CMS lines and its maintainer lines in B. juncea. The number of repeats larger than 100 bp in the hau CMS line (16 repeats) are nearly twice of those found in the maintainer line (9 repeats). Phylogenetic analysis of the CMS-associated gene orf288 and four other homologous sequences in Brassicaceae show that orf288 was clearly different from orf263 in Brassica tournefortii despite of strong similarity. Conclusion The hau CMS mitochondrial genome was highly rearranged when compared with its isonuclear maintainer line mitochondrial genome. This study may be useful for studying the mechanism of natural CMS in B. juncea, performing comparative analysis on sequenced mitochondrial genomes in Brassicas, and uncovering the origin of the hau CMS mitotype and structural and evolutionary differences between different mitotypes. [ABSTRACT FROM AUTHOR]

Bleomycin, a glycopeptide antibiotic produced by the bacterium Streptomyces verticillus, has been demonstrated to be an effective mutagen in Arabidopsis thaliana. The objective of the present study was to determine the effect of bleomycin on embryo production and to assess the genetic variation of the doubled haploid (DH) populations by amplified fragment length polymorphism (AFLP). The effects of bleomycin on microspore embryogenesis and cell division were investigated using three concentrations of bleomycin in five semi-winter genotypes of Brassica napus viz. T8, T10, B409, P30, and DH1142. Inclusion of bleomycin in the culture medium at a concentration of 0.1 µg ml-1 for 30 min significantly improved embryo production and cell division in all five genotypes. Embryo production was induced at rates two- and four-fold higher than controls after bleomycin treatment. Fifty plants regenerated by microspore embryogenesis treated with bleomycin in addition to non-treated controls of T8, T10, and B409 were selected for AFLP analysis. The results suggest that microspore culture is capable of producing 0.095-0.114% genetic variation, and there was no effect of bleomycin treatment on genetic stabilisation of doubled haploid populations versus the non-treated control. [ABSTRACT FROM AUTHOR]

A novel cytoplasmic male sterility (CMS) was identified in Brassica juncea, named as hau CMS (00-6-102A). Subsequently, the male sterility was transferred to B. napus by interspecific hybridization. The hau CMS has stable male sterility. Flowers on the A line are absolutely male sterile, and seeds harvested from the line following pollinations with the maintainer gave rise to 100% sterile progeny. The anthers in CMS plants are replaced by thickened petal-like structures and pollen grains were not detected. In contrast, in other CMS systems viz. pol, nap, tour, and ogu, anthers are formed but do not produce viable pollen. The sterility of hau CMS initiates at the stage of stamen primordium polarization, which is much earlier compared with the other four CMS systems. We have successfully transferred hau CMS from B. juncea to B. napus. Restorer lines for pol, ogu, nap, and tour CMS systems were found to be ineffective to restore fertility in hau CMS. Sixteen out of 40 combinations of mitochondrial probe/enzyme used for RFLP analysis distinguished the hau CMS system from the other four systems. Among these sixteen combinations, five ones alone could distinguish the five CMS systems from each other. The evidence from genetic, morphological, cytological and molecular studies confirmed that the hau CMS system is a novel CMS system. [ABSTRACT FROM AUTHOR]

In practical applications, how to achieve a perfect balance between high accuracy and computational efficiency can be the main challenge for simultaneous localization and mapping (SLAM). To solve this challenge, we propose SD-VIS, a novel fast and accurate semi-direct visual-inertial SLAM framework, which can estimate camera motion and structure of surrounding sparse scenes. In the initialization procedure, we align the pre-integrated IMU measurements and visual images and calibrate out the metric scale, initial velocity, gravity vector, and gyroscope bias by using multiple view geometry (MVG) theory based on the feature-based method. At the front-end, keyframes are tracked by feature-based method and used for back-end optimization and loop closure detection, while non-keyframes are utilized for fast-tracking by direct method. This strategy makes the system not only have the better real-time performance of direct method, but also have high accuracy and loop closing detection ability based on feature-based method. At the back-end, we propose a sliding window-based tightly-coupled optimization framework, which can get more accurate state estimation by minimizing the visual and IMU measurement errors. In order to limit the computational complexity, we adopt the marginalization strategy to fix the number of keyframes in the sliding window. Experimental evaluation on EuRoC dataset demonstrates the feasibility and superior real-time performance of SD-VIS. Compared with state-of-the-art SLAM systems, we can achieve a better balance between accuracy and speed.

Aeroelastic tailoring of laminated composite structure demands relatively high computational time especially for dynamic problem. This paper presents an efficient method for aeroelastic dynamic response analysis with significantly reduced computational time. In this method, a relationship is established between the maximum aeroelastic response and quasi-steady deflection of a wing subject to a dynamic loading. Based on this relationship, the time consuming dynamic response can be approximated by a quasi-steady deflection analysis in a large proportion of the optimization process. This method has been applied to the aeroelastic tailoring of a composite wing of a tailless aircraft for minimum gust response. The results have shown that 20%–36% gust response reduction has been achieved for this case. The computational time of the optimization process has been reduced by 90% at the cost of accuracy reduction of 2~4% comparing with the traditional dynamic response analysis.