Kled: an ultra-fast and sensitive structural variant detection tool for long-read sequencing data.

Structural Variants (SVs) are a crucial type of genetic variant that can significantly impact phenotypes. Therefore, the identification of SVs is an essential part of modern genomic analysis. In this article, we present kled, an ultra-fast and sensitive SV caller for long-read sequencing data given the specially designed approach with a novel signature-merging algorithm, custom refinement strategies and a high-performance program structure. The evaluation results demonstrate that kled can achieve optimal SV calling compared to several state-of-the-art methods on simulated and real long-read data for different platforms and sequencing depths. Furthermore, kled excels at rapid SV calling and can efficiently utilize multiple Central Processing Unit (CPU) cores while maintaining low memory usage. The source code for kled can be obtained from https://github.com/CoREse/kled.

Synthesis of Mesoporous Catechin Nanoparticles as Biocompatible Drug-Free Antibacterial Mesoformulation.

While polyphenolic substances stand as excellent antibacterial agents, their antimicrobial properties rely on the auxiliary support of micro-/nanostructures. Despite offering a novel avenue for enhancing polymer performance, controllable fabrication of mesoporous polymeric nanomaterials encounters significant challenges due to intricate intermolecular forces. In this article, mesoporous catechin nanoparticles have been successfully fabricated using a balanced multivariate interaction approach. The harmonization of the water-ethanol ratio and ionic strength effectively balances the forces of hydrogen bonding and π-π stacking, facilitating the controlled assembly of mesostructures. The mesoporous catechin nanoparticles exhibit a uniform spherical structure (∼100 nm), open mesopores with a diameter of ∼15 nm, and a high surface area of ∼106 m2 g-1. While exhibiting a good biocompatibility and negative surface charge, the mesoporous catechins possess outstanding antibacterial ability and function as an antibiotic mesoformulation without the necessity of loading any drugs. This mesoformulation inhibits 50% in vitro Staphylococcus aureus growth with a low concentration of ∼10 µg mL-1 and achieves complete inhibition at ∼25 µg mL-1. In a mouse wound model, accelerated wound healing and complete closure within 6-8 days are achieved. Proteomics of bacteria reveals that the excellent antibacterial property is attributed to the synergetic effect of mesoformulation's mesostructure and the catechin molecule intervening in bacterial metabolism. Overall, this work may pave a novel way for the future exploration of polymer nanomaterials and antibiotic formulations.

A study on the application of radiomics based on cardiac MR non-enhanced cine sequence in the early diagnosis of hypertensive heart disease.

BACKGROUND: The prevalence of hypertensive heart disease (HHD) is high and there is currently no easy way to detect early HHD. Explore the application of radiomics using cardiac magnetic resonance (CMR) non-enhanced cine sequences in diagnosing HHD and latent cardiac changes caused by hypertension. METHODS: 132 patients who underwent CMR scanning were divided into groups: HHD (42), hypertension with normal cardiac structure and function (HWN) group (46), and normal control (NOR) group (44). Myocardial regions of the end-diastolic (ED) and end-systolic (ES) phases of the CMR short-axis cine sequence images were segmented into regions of interest (ROI). Three feature subsets (ED, ES, and ED combined with ES) were established after radiomic least absolute shrinkage and selection operator feature selection. Nine radiomic models were built using random forest (RF), support vector machine (SVM), and naive Bayes. Model performance was analyzed using receiver operating characteristic curves, and metrics like accuracy, area under the curve (AUC), precision, recall, and specificity. RESULTS: The feature subsets included first-order, shape, and texture features. SVM of ED combined with ES achieved the highest accuracy (0.833), with a macro-average AUC of 0.941. AUCs for HHD, HWN, and NOR identification were 0.967, 0.876, and 0.963, respectively. Precisions were 0.972, 0.740, and 0.826; recalls were 0.833, 0.804, and 0.863, respectively; and specificities were 0.989, 0.863, and 0.909, respectively. CONCLUSIONS: Radiomics technology using CMR non-enhanced cine sequences can detect early cardiac changes due to hypertension. It holds promise for future use in screening for latent cardiac damage in early HHD.

Lemon essential oil nanoemulsions: Potential natural inhibitors against Escherichia coli.

Lemon essential oil (LEO) is a common natural antibacterial substance, and encapsulating LEO into nanoemulsions (NEs) can improve their stability and broaden its application. Our study aimed to investigate the bacterial inhibitory effect of LEO-NEs against Escherichia coli (E. coli). Results showed that the minimum inhibitory concentration (MIC) of LEO-NEs was 6.25 mg/mL, and the time-kill curve showed that E. coli were significantly killed by LEO-NEs after 5 h of treatment at 1MIC. Flow-cytometry analysis showed that LEO-NEs adversely affected the cell-membrane depolarisation, cell-membrane integrity, and efflux pump function of E. coli. Confocal laser scanning microscopy demonstrated that 8MIC of LEO-NEs induced changes in the cell-membrane permeability and cell-wall integrity of E. coli. Proteomic results suggested that the mode of action LEO-NEs against E. coli was to enhance bacterial chemotaxis and significantly inhibit ribosomal assembly. They may also affect butyric acid, ascorbic acid and aldehyde metabolism, and sulphur-relay system pathways. In conclusion, LEO-NEs had potential application as a natural antibacterial agent for the control of E. coli in the food industry.

Untargeted Metabolomic Analyses and Antilipidemic Effects of Citrus Physiological Premature Fruit Drop.

Increasingly globally prevalent obesity and related metabolic disorders have underscored the demand for safe and natural therapeutic approaches, given the limitations of weight loss drugs and surgeries. This study compared the phytochemical composition and antioxidant activity of five different varieties of citrus physiological premature fruit drop (CPFD). Untargeted metabolomics was employed to identify variations in metabolites among different CPFDs, and their antilipidemic effects in vitro were assessed. The results showed that Citrus aurantium L. 'Daidai' physiological premature fruit drop (DDPD) and Citrus aurantium 'Changshan-huyou' physiological premature fruit drop (HYPD) exhibited higher levels of phytochemicals and stronger antioxidant activity. There were 97 differential metabolites identified in DDPD and HYPD, including phenylpropanoids, flavonoids, alkaloids, organic acids, terpenes, and lipids. Additionally, DDPD and HYPD demonstrated potential antilipidemic effects against oleic acid (OA)-induced steatosis in HepG2 hepatocytes and 3T3-L1 adipocytes. In conclusion, our findings reveal the outstanding antioxidant activity and antilipidemic effects of CPFD, indicating its potential use as a natural antioxidant and health supplement and promoting the high-value utilization of this resource.

Se-Elemental Concentration Gradient Regulation for Efficient Sb2(S,Se)3 Solar Cells With High Open-Circuit Voltages.

Antimony selenosulfide (Sb2(S,Se)3), featuring large absorption coefficient, excellent crystal structure stability, benign non-toxic characteristic, outstanding humidity and ultraviolet tolerability, has recently attracted enormous attention and research interest regarding its photoelectric conversion properties. However, the open-circuit voltage (Voc) for Sb2(S,Se)3-based photovoltaic devices is relatively low, especially for the device with a high power conversion efficiency (η). Herein, an innovative Se-elemental concentration gradient regulation strategy has been exploited to produce high-quality Sb2(S,Se)3 films on TiO2/CdS substrates through a thioacetamide(TA)-synergistic dual-sulfur source hydrothermal-processed method. The Se-elemental gradient distribution produces a favorable energy band structure, which suppresses the energy level barriers for hole transport and enhances the driving force for electron transport in Sb2(S,Se)3 film. This facilitates efficient charge transport/separation of photogenerated carriers and boosts significantly the Voc of Sb2(S,Se)3 photovoltaic devices. The champion TA-Sb2(S,Se)3 planar heterojunction (PHJ) solar cell displays an considerable η of 9.28 % accompanied by an exciting Voc rising to 0.70 V that is currently the highest among Sb2(S,Se)3-based solar cells with efficiencies exceeding 9.0 %. This research is anticipated to contribute to the preparation of high-quality Sb2(S,Se)3 thin film and the achievement of efficient inorganic Sb2(S,Se)3 PHJ photovoltaic device.

Germline and Mosaic Variants in PRKACA and PRKACB Cause a Multiple Congenital Malformation Syndrome.

PRKACA and PRKACB code for two catalytic subunits (Cα and Cß) of cAMP-dependent protein kinase (PKA), a pleiotropic holoenzyme that regulates numerous fundamental biological processes such as metabolism, development, memory, and immune response. We report seven unrelated individuals presenting with a multiple congenital malformation syndrome in whom we identified heterozygous germline or mosaic missense variants in PRKACA or PRKACB. Three affected individuals were found with the same PRKACA variant, and the other four had different PRKACB mutations. In most cases, the mutations arose de novo, and two individuals had offspring with the same condition. Nearly all affected individuals and their affected offspring shared an atrioventricular septal defect or a common atrium along with postaxial polydactyly. Additional features included skeletal abnormalities and ectodermal defects of variable severity in five individuals, cognitive deficit in two individuals, and various unusual tumors in one individual. We investigated the structural and functional consequences of the variants identified in PRKACA and PRKACB through the use of several computational and experimental approaches, and we found that they lead to PKA holoenzymes which are more sensitive to activation by cAMP than are the wild-type proteins. Furthermore, expression of PRKACA or PRKACB variants detected in the affected individuals inhibited hedgehog signaling in NIH 3T3 fibroblasts, thereby providing an underlying mechanism for the developmental defects observed in these cases. Our findings highlight the importance of both Cα and Cß subunits of PKA during human development.

CyanoPATH: a knowledgebase of genome-scale functional repertoire for toxic cyanobacterial blooms.

CyanoPATH is a database that curates and analyzes the common genomic functional repertoire for cyanobacteria harmful algal blooms (CyanoHABs) in eutrophic waters. Based on the literature of empirical studies and genome/protein databases, it summarizes four types of information: common biological functions (pathways) driving CyanoHABs, customized pathway maps, classification of blooming type based on databases and the genomes of cyanobacteria. A total of 19 pathways are reconstructed, which are involved in the utilization of macronutrients (e.g. carbon, nitrogen, phosphorus and sulfur), micronutrients (e.g. zinc, magnesium, iron, etc.) and other resources (e.g. light and vitamins) and in stress resistance (e.g. lead and copper). These pathways, comprised of both transport and biochemical reactions, are reconstructed with proteins from NCBI and reactions from KEGG and visualized with self-created transport/reaction maps. The pathways are hierarchical and consist of subpathways, protein/enzyme complexes and constituent proteins. New cyanobacterial genomes can be annotated and visualized for these pathways and compared with existing species. This set of genomic functional repertoire is useful in analyzing aquatic metagenomes and metatranscriptomes in CyanoHAB research. Most importantly, it establishes a link between genome and ecology. All these reference proteins, pathways and maps and genomes are free to download at http://www.csbg-jlu.info/CyanoPATH.

Construction of Core-Cross-Linked Polymer Micelles with High Biocompatibility and Stability for pH/Reduction Controllable Drug Delivery.

Polymer micelles have been studied extensively in drug delivery systems (DDS), and their stability is well known to directly affect drug delivery. In this article, a series of amphiphilic copolymers LA-PDPAn-PVPm were synthesized to prepare core-cross-linked nanoparticles (CNP) applied to controllable and targeted anticancer drug delivery. The copolymers could self-assemble in aqueous solution and form homogeneous spherical micelles with particle sizes of between 100 and 150 nm. A comparison between un-cross-linked UCNP and CNP showed that the cross-linking of LA could significantly improve the stability and responsive ability of the nanoparticles. From the in vitro-simulated drug release experiments, CNP was found to have great drug blocking ability under normal physiological conditions and could achieve rapid and efficient drug release under acidic/reducing conditions. In addition, cell experiments showed that CNP had superior biocompatibility and could target tumor cells for drug release. In conclusion, a drug carrier based on copolymer LA-PDPA-PVP realized effective controlled drug release due to the cross-linking of LA. The results will provide guidance for the design strategy of polymer micelles for drug carriers.

Endogenous glutamine is rate-limiting for anti-CD3 and anti-CD28 induced CD4+ T-cell proliferation and glycolytic activity under hypoxia and normoxia.

To meet the demand for energy and biomass, T lymphocytes (T cells) activated to proliferation and clonal expansion, require uptake and metabolism of glucose (Gluc) and the amino acid (AA) glutamine (Gln). Whereas exogenous Gln is converted to glutamate (Glu) by glutaminase (GLS), Gln is also synthesized from the endogenous pool of AA through Glu and activity of glutamine synthase (GS). Most of this knowledge comes from studies on cell cultures under ambient oxygen conditions (normoxia, 21% O2). However, in vivo, antigen induced T-cell activation often occurs under moderately hypoxic (1-4% O2) conditions and at various levels of exogenous nutrients. Here, CD4+ T cells were stimulated for 72 h with antibodies targeting the CD3 and CD28 markers at normoxia and hypoxia (1% O2). This was done in the presence and absence of the GLS and GS inhibitors, Bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl) ethyl sulfide (BPTES) and methionine sulfoximine (MSO) and at various combinations of exogenous Gluc, Gln and pyruvate (Pyr) for the last 12 h of stimulation. We found that T-cell proliferation, viability and levels of endogenous AA were significantly influenced by the availability of exogenous Gln, Gluc and Pyr as well as inhibition of GLS and GS. Moreover, inhibition of GLS and GS and levels of oxygen differentially influenced oxygen consumption rate (OCR) and extracellular acidification rate (ECAR). Finally, BPTES-dependent down-regulation of ECAR was associated with reduced hexokinase (HK) activity at both normoxia and hypoxia. Our results demonstrate that Gln availability and metabolism is rate-limiting for CD4+ T-cell activity.

Efficient Fe3C-CF Cathode Catalyst Based on the Formation/Decomposition of Li2-xO2 for Li-O2 Batteries.

Lithium-oxygen batteries have attracted considerable attention in the past several years due to their ultra-high theoretical energy density. However, there are still many serious issues that must be addressed before considering practical applications, including the sluggish oxygen redox kinetics, the limited capacity far from the theoretical value, and the poor cycle stability. This study proposes a surface modification strategy that can enhance the catalytic activity by loading Fe3C particles on carbon fibers, and the microstructure of Fe3C particle-modified carbon fibers is studied by multiple materials characterization methods. Experiments and density functional theory (DFT) calculations show that the discharge products on the Fe3C carbon fiber (Fe3C-CF) cathode are mainly Li2-xO2. Fe3C-CF exhibits high catalytic ability based on its promotion of the formation/decomposition processes of Li2-xO2. Consequently, the well-designed electrode catalyst exhibits a large specific capacity of 17,653.1 mAh g-1 and an excellent cyclability of 263 cycles at a current of 200 mA g-1.

Real and Pseudo Pedestrian Detection Method with CA-YOLOv5s Based on Stereo Image Fusion.

With the development of convolutional neural networks, the effect of pedestrian detection has been greatly improved by deep learning models. However, the presence of pseudo pedestrians will lead to accuracy reduction in pedestrian detection. To solve the problem that the existing pedestrian detection algorithms cannot distinguish pseudo pedestrians from real pedestrians, a real and pseudo pedestrian detection method with CA-YOLOv5s based on stereo image fusion is proposed in this paper. Firstly, the two-view images of the pedestrian are captured by a binocular stereo camera. Then, a proposed CA-YOLOv5s pedestrian detection algorithm is used for the left-view and right-view images, respectively, to detect the respective pedestrian regions. Afterwards, the detected left-view and right-view pedestrian regions are matched to obtain the feature point set, and the 3D spatial coordinates of the feature point set are calculated with Zhengyou Zhang's calibration method. Finally, the RANSAC plane-fitting algorithm is adopted to extract the 3D features of the feature point set, and the real and pseudo pedestrian detection is achieved by the trained SVM. The proposed real and pseudo pedestrian detection method with CA-YOLOv5s based on stereo image fusion effectively solves the pseudo pedestrian detection problem and efficiently improves the accuracy. Experimental results also show that for the dataset with real and pseudo pedestrians, the proposed method significantly outperforms other existing pedestrian detection algorithms in terms of accuracy and precision.

Structural and functional analyses of microbial metabolic networks reveal novel insights into genome-scale metabolic fluxes.

We present here an integrated analysis of structures and functions of genome-scale metabolic networks of 17 microorganisms. Our structural analyses of these networks revealed that the node degree of each network, represented as a (simplified) reaction network, follows a power-law distribution, and the clustering coefficient of each network has a positive correlation with the corresponding node degree. Together, these properties imply that each network has exactly one large and densely connected subnetwork or core. Further analyses revealed that each network consists of three functionally distinct subnetworks: (i) a core, consisting of a large number of directed reaction cycles of enzymes for interconversions among intermediate metabolites; (ii) a catabolic module, with a largely layered structure consisting of mostly catabolic enzymes; (iii) an anabolic module with a similar structure consisting of virtually all anabolic genes; and (iv) the three subnetworks cover on average ∼56, ∼31 and ∼13% of a network's nodes across the 17 networks, respectively. Functional analyses suggest: (1) cellular metabolic fluxes generally go from the catabolic module to the core for substantial interconversions, then the flux directions to anabolic module appear to be determined by input nutrient levels as well as a set of precursors needed for macromolecule syntheses; and (2) enzymes in each subnetwork have characteristic ranges of kinetic parameters, suggesting optimized metabolic and regulatory relationships among the three subnetworks.

Physiological determinants of biogeography: The importance of metabolic depression to heat tolerance.

A quantitative understanding of physiological thermal responses is vital for forecasting species distributional shifts in response to climate change. Many studies have focused on metabolic rate as a global metric for analyzing the sublethal effects of changing environments on physiology. Thermal performance curves (TPCs) have been suggested as a viable analytical framework, but standard TPCs may not fully capture physiological responses, due in part to failure to consider the process of metabolic depression. We derived a model based on the nonlinear regression of biological temperature-dependent rate processes and built a heart rate data set for 26 species of intertidal molluscs distributed from 33°S to ~40°N. We then calculated physiological thermal performance limits with continuous heating using T 1 / 2 H , the temperature at which heart rate is decreased to 50% of the maximal rate, as a more realistic measure of upper thermal limits. Results indicate that heat-induced metabolic depression of cardiac performance is a common adaptive response that allows tolerance of harsh environments. Furthermore, our model accounted for the high inter-individual variability in the shape of cardiac TPCs. We then used these TPCs to calculate physiological thermal safety margins (pTSM), the difference between the maximal operative temperature (95th percentile of field temperatures) and T 1 / 2 H of each individual. Using pTSMs, we developed a physiological species distribution model (pSDM) to forecast future geographic distributions. pSDM results indicate that climate-induced species range shifts are potentially less severe than predicted by a simple correlative SDM. Species with metabolic depression below the optimum temperature will be more thermal resistant at their warm trailing edges. High intraspecific variability further suggests that models based on species-level vulnerability to environmental change may be problematic. This multi-scale, mechanistic understanding that incorporates metabolic depression and inter-individual variability in thermal response enables better predictions about the relationship between thermal stress and species distributions.

Study on the views and methods of ultrasonic screening and diagnosis for abnormal aortic arch in infants.

BACKGROUND: The purpose of this study was to explore echocardiographic views and methods of aortic arch anomalies in infants, so as to improve the screening sensitivity and diagnostic accuracy. METHODS: 140 children with abnormal aortic arch diagnosed by ultrasound in Children's Hospital of Hebei Province from January 2014 to December 2019 were selected for retrospective analysis. All were confirmed by surgery or/and computerized tomography angiography. Series of views for aortic arch (the three-vessel and tracheal view, aortic arch short axis view, left aortic arch long axis view, aortic arch long axis continuous scan views) were performed in all cases on the basis of the routine views of echocardiography. The screening sensitivity and diagnostic coincidence rate of different echocardiographic views for aortic arch anomalies were analyzed. RESULTS: Among the 140 infants, right aortic arch were 21 cases (6/21 were accompanied by mirror branch and 15/21 were with aberrant left subclavian artery). Left aortic arch with aberrant right subclavian artery were 2 cases, and double aortic arch with both arches open were 20 cases. Double aortic arch with left arch atresia were 2 cases, and atresia of the proximal aorta with aortic arch dysplasia was 1 case. Coarctation of the aorta were 67 cases, and interruption of aortic arch were 27 cases. All the patients were correctly diagnosed except that 2 infants with interruption of aortic arch were incorrectly diagnosed as coarctation of the aorta, and 1 infant with coarctation of the aorta was misdiagnosed as interruption of aortic arch by echocardiography. The screening sensitivities of four views and four-view combination for abnormal aortic arch were 99.3, 73.6, 87.1, 99.3, and 100%; the diagnostic coincidence rates were 85.7, 27.1,66.4, 95.0%, and 97.9% respectively. On the basis of traditional left aortic long axis view, other three views had their own advantages. The screening sensitivity and diagnostic coincidence rate of four-view combination were significantly improved. CONCLUSIONS: The three-vessel trachea view is simple and feasible, which is suitable for screening abnormal aortic arch. The combination of four views conduces to improving screening sensitivity and diagnostic accuracy of aortic arch abnormalities.

Keratomycosis Caused by a Rare Pathogen, Myrothecium verrucaria.

PURPOSE: To report a case of keratomycosis caused by a very rare pathogen, Myrothecium verrucaria. METHODS: This is a case report. A 53-year-old man complaint of left eye redness, irritation, intermittent pain after ashes entered his left eye. The patient was examined by slit lamp, anterior segment OCT and in vivo confocal microscopy. The HRT III-RCM image showed massive interlocking white thin lines in the cornea stroma. Corneal scrapings were collected for pathogen culture and PCR test. M. verrucaria was isolated and identified. RESULTS: Hourly topical natamycin (5%) and voriconazole (10 mg/ml) was given as well as intravenous fluconazole (200 mg per day). Treatment was continued with oral itraconazole, 200 mg/day, topical natamycin (5%), 4 times/day, and pranoprofen, 4 times/day. The therapy was tapered off over one and half a month. The cornea lesion healed with scar formation two months later. CONCLUSIONS: This is the first case report of M. verrucaria keratomycosis in China. We are the first to show the characteristic of M. verrucaria on cornea with In vivo confocal microscopy. A combination treatment of tropical natamycin, voriconazole and systemic fluconazole was effective in the treatment of M. verrucaria.

CapsNet-SSP: multilane capsule network for predicting human saliva-secretory proteins.

BACKGROUND: Compared with disease biomarkers in blood and urine, biomarkers in saliva have distinct advantages in clinical tests, as they can be conveniently examined through noninvasive sample collection. Therefore, identifying human saliva-secretory proteins and further detecting protein biomarkers in saliva have significant value in clinical medicine. There are only a few methods for predicting saliva-secretory proteins based on conventional machine learning algorithms, and all are highly dependent on annotated protein features. Unlike conventional machine learning algorithms, deep learning algorithms can automatically learn feature representations from input data and thus hold promise for predicting saliva-secretory proteins. RESULTS: We present a novel end-to-end deep learning model based on multilane capsule network (CapsNet) with differently sized convolution kernels to identify saliva-secretory proteins only from sequence information. The proposed model CapsNet-SSP outperforms existing methods based on conventional machine learning algorithms. Furthermore, the model performs better than other state-of-the-art deep learning architectures mostly used to analyze biological sequences. In addition, we further validate the effectiveness of CapsNet-SSP by comparison with human saliva-secretory proteins from existing studies and known salivary protein biomarkers of cancer. CONCLUSIONS: The main contributions of this study are as follows: (1) an end-to-end model based on CapsNet is proposed to identify saliva-secretory proteins from the sequence information; (2) the proposed model achieves better performance and outperforms existing models; and (3) the saliva-secretory proteins predicted by our model are statistically significant compared with existing cancer biomarkers in saliva. In addition, a web server of CapsNet-SSP is developed for saliva-secretory protein identification, and it can be accessed at the following URL: http://www.csbg-jlu.info/CapsNet-SSP/. We believe that our model and web server will be useful for biomedical researchers who are interested in finding salivary protein biomarkers, especially when they have identified candidate proteins for analyzing diseased tissues near or distal to salivary glands using transcriptome or proteomics.

Cellular metabolism dictates T cell effector function in health and disease.

In a healthy person, metabolically quiescent T lymphocytes (T cells) circulate between lymph nodes and peripheral tissues in search of antigens. Upon infection, some T cells will encounter cognate antigens followed by proliferation and clonal expansion in a context-dependent manner, to become effector T cells. These events are accompanied by changes in cellular metabolism, known as metabolic reprogramming. The magnitude and variation of metabolic reprogramming are, in addition to antigens, dependent on factors such as nutrients and oxygen to ensure host survival during various diseases. Herein, we describe how metabolic programmes define T cell subset identity and effector functions. In addition, we will discuss how metabolic programs can be modulated and affect T cell activity in health and disease using cancer and autoimmunity as examples.

Green and efficient biosynthesis of pectin-based copper nanoparticles and their antimicrobial activities.

Herein, we reported a green biosynthesis method of copper nanoparticles (CuNPs) at microwave irradiation condition by using pectin as a stabilizer and ascorbic acid as a reducing agent. Under the optimum conditions, CuNPs1 and 2 were synthesized under microwave times 0 and 3 min, respectively. Transmission electron microscope and scanning electron microscope (SEM) tests showed that CuNPs1 and 2 had irregular polygon particles with average diameters of 61.9 ± 19.4 and 40.9 ± 13.6 nm, respectively. Zeta potentials of CuNPs1 and 2 were -45.2 and -48.7 mV, respectively. X-ray diffraction, Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and X-ray photoelectron spectroscopy techniques were used to characterize the properties of CuNPs. Furthermore, inhibition zone tests showed that CuNPs2 exhibited higher antimicrobial activities against Escherichia coli, Staphylococcus aureus, and Aspergillus japonicus than CuNPs1. The antibacterial activities were also studied by the bacterial growth kinetics in broth media, and CuNPs2 exhibited lower minimum bactericidal concentrations than CuNPs1.

Welding Seam Trajectory Recognition for Automated Skip Welding Guidance of a Spatially Intermittent Welding Seam Based on Laser Vision Sensor.

To solve the problems of low teaching programming efficiency and poor flexibility in robot welding of complex box girder structures, a method of seam trajectory recognition based on laser scanning displacement sensing was proposed for automated guidance of a welding torch in the skip welding of a spatially intermittent welding seam. Firstly, a laser scanning displacement sensing system for measuring angles adaptively is developed to detect corner features of complex structures. Secondly, a weld trajectory recognition algorithm based on Euclidean distance discrimination is proposed. The algorithm extracts the shape features by constructing the characteristic triangle of the weld trajectory, and then processes the set of shape features by discrete Fourier analysis to solve the feature vector used to describe the shape. Finally, based on the Euclidean distance between the feature vector of the test sample and the class matching library, the class to which the sample belongs is identified to distinguish the weld trajectory. The experimental results show that the classification accuracy rate of four typical spatial discontinuous welds in complex box girder structure is 100%. The overall processing time for weld trajectory detection and classification does not exceed 65 ms. Based on this method, the field test was completed in the folding special container production line. The results show that the system proposed in this paper can accurately identify discontinuous welds during high-speed metal active gas arc welding (MAG) welding with a welding speed of 1.2 m/min, and guide the welding torch to automatically complete the skip welding, which greatly improves the welding manufacturing efficiency and quality stability in the processing of complex box girder components. This method does not require a time-consuming pre-welding teaching programming and visual inspection system calibration, and provides a new technical approach for highly efficient and flexible welding manufacturing of discontinuous welding seams of complex structures, which is expected to be applied to the welding manufacturing of core components in heavy and large industries such as port cranes, large logistics transportation equipment, and rail transit.