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A silicon‐based room temperature (RT) continuous wave (CW) operation quantum well (QW) laser emitting at 850 nm is reported in this article. By applying the dislocation filter superlattice, the threading dislocation density of the GaAs pseudosubstrate on Si is reduced to 1.8 × 107 cm−2. The metal‐organic chemical vapor deposition‐grown laser structure with GaAs/GaAsP QW and InAlAs active region dislocation blocking layer are fabricated into broad‐stripe Fabry–Perot laser diodes. A typical threshold current and threshold current density of 286 mA and 715 Acm−2 are obtained with 2 mm cavity length and 20 um stripe width samples. A 94.2 mW single‐facet output power lasing around 854 nm and a 0.314 WA−1 slope efficiency is measured under RT CW operation. After a 10‐min aging process, the tested laser can operate stably under continuous operation conditions at RT and the lifetime can be approximated using an exponential fitting curve, indicating a good life reliability of this QW laser.

Background Escherichia coli is an important intestinal flora, of which pathogenic E. coli is capable of causing many enteric and extra-intestinal diseases. Antibiotics are essential for the treatment of bacterial infections caused by pathogenic E. coli; however, with the widespread use of antibiotics, drug resistance in E. coli has become particularly serious, posing a global threat to human, animal, and environmental health. While the drug resistance and pathogenicity of E. coli carried by tigers and leopards in captivity have been studied intensively in recent years, there is an extreme lack of information on E. coli in these top predators in the wild environment. Methods Whole genome sequencing data of 32 E. coli strains collected from the feces of wild Amur tiger (Panthera tigris altaica, n = 24) and North China leopard (Panthera pardus japonensis, n = 8) were analyzed in this article. The multi-locus sequence types, serotypes, virulence and resistance genotypes, plasmid replicon types, and core genomic SNPs phylogeny of these isolates were studied. Additionally, antimicrobial susceptibility testing (AST) was performed on these E. coli isolates. Results Among the E. coli isolates studied, 18 different sequence types were identified, with ST939 (21.9%), ST10 (15.6%), and ST3246 (9.4%) being the most prevalent. A total of 111 virulence genes were detected, averaging about 54 virulence genes per sample. They contribute to invasion, adherence, immune evasion, efflux pump, toxin, motility, stress adaption, and other virulence-related functions of E. coli. Sixty-eight AMR genes and point mutations were identified. Among the detected resistance genes, those belonging to the efflux pump family were the most abundant. Thirty-two E. coli isolates showed the highest rate of resistance to tetracycline (14/32; 43.8%), followed by imipenem (4/32; 12.5%), ciprofloxacin (3/32; 9.4%), doxycycline (2/32; 6.3%), and norfloxacin (1/32; 3.1%). Conclusions Our results suggest that E. coli isolates carried by wild Amur tigers and North China leopards have potential pathogenicity and drug resistance.

A coordinated interaction between osteogenesis and the osteoimmune microenvironment plays a vital role in regulating bone healing. However, disturbances in the pro- and anti-inflammatory balance hinder the therapeutic advantages of biomaterials. In this study, a novel composite hydrogel was successfully fabricated using graphene oxide (GO)-loaded processed pyritum (PP) in combination with poly(ethylene glycol) diacrylate (PEGDA) and carboxymethyl chitosan (CMC). Subsequently, the immunomodulatory effects and bone regenerative potential of PP/GO@PEGDA/CMC were investigated. The results demonstrated that the PP/GO@PEGDA/CMC hydrogel possessed excellent mechanical properties, swelling capacity, and stability. Moreover, PP/GO@PEGDA/CMC prominently promoted M2 polarization and increased the levels of anti-inflammatory factors (interleukin (IL)-4, IL-10, and transforming growth factor-β). These beneficial effects facilitated the proliferation and osteogenic differentiation of bone marrow mesenchymal stem cells in vitro. Additionally, the in vivo results further verified that the implantation of PP/GO@PEGDA/CMC markedly reduced local inflammation while enhancing bone regeneration at 8 weeks post-implantation. Therefore, the results of this study provide potential therapeutic strategies for bone tissue repair and regeneration by modulating the immune microenvironment.

Abstract Background Nanoscale connectomics, which aims to map the fine connections between neurons with synaptic-level detail, has attracted increasing attention in recent years. Currently, the automated reconstruction algorithms in electron microscope volumes are in great demand. Most existing reconstruction methodologies for cellular and subcellular structures are independent, and exploring the inter-relationships between structures will contribute to image analysis. The primary goal of this research is to construct a joint optimization framework to improve the accuracy and efficiency of neural structure reconstruction algorithms. Results In this investigation, we introduce the concept of connectivity consensus between cellular and subcellular structures based on biological domain knowledge for neural structure agglomeration problems. We propose a joint graph partitioning model for solving ultrastructural and neuronal connections to overcome the limitations of connectivity cues at different levels. The advantage of the optimization model is the simultaneous reconstruction of multiple structures in one optimization step. The experimental results on several public datasets demonstrate that the joint optimization model outperforms existing hierarchical agglomeration algorithms. Conclusions We present a joint optimization model by connectivity consensus to solve the neural structure agglomeration problem and demonstrate its superiority to existing methods. The intention of introducing connectivity consensus between different structures is to build a suitable optimization model that makes the reconstruction goals more consistent with biological plausible and domain knowledge. This idea can inspire other researchers to optimize existing reconstruction algorithms and other areas of biological data analysis.

“Feicheng” peach is popular for its unique aroma, but its defect of being highly sensitive to chilling injury (CI) often leads to aroma loss and internal browning. Essential oils (EOs) are often used to enhance the antioxidant capacity of plants and fruits, as well as to trigger their defense against biotic/abiotic stresses. This study aimed to examine the effect of cinnamon essential oil (CEO) vapor treatment on the aroma quality of peach fruit during cold storage using HS-GC-IMS. The results showed that 50 μL/L CEO vapor reduced the severity of internal browning (IB) in peaches at the stage of 7 ~ 21 d during refrigeration (Significantly, the L* value was higher and the IB index was lower than that of control, p

The increasing demand for accurate imaging spectral information in remote sensing detection has driven the development of hyperspectral remote sensing instruments towards a larger view field and higher resolution. As the core component of the spectrometer slit, the designed length reaches tens of millimeters while the precision maintained within the μm level. Such precision requirements pose challenges to traditional machining and laser processing. In this paper, a high-precision air slit was created with a large aspect ratio through MEMS technology on SOI silicon wafers. In particular, a MEMS slit was prepared with a width of 15 μm and an aspect ratio exceeding 4000:1, and a spectral spectroscopy system was created and tested with a Hg-Cd light source. As a result, the spectral spectrum was linear within the visible range, and a spectral resolution of less than 1 nm was obtained. The standard deviation of resolution is only one-fourth of that is seen in machined slits across various view fields. This research provided a reliable and novel manufacturing technique for high-precision air slits, offering technical assistance in developing high-resolution wide-coverage imaging spectrometers.

Bagging-free apple is more vulnerable to postharvest disease, which severely limits the cultivation pattern transformation of the apple industry in China. This study aimed to ascertain the dominant pathogens in postharvest bagging-free apples, to evaluate the efficacy of essential oil (EO) on inhibition of fungal growth, and to further clarify the molecular mechanism of this action. By morphological characteristics and rDNA sequence analyses, Botryosphaeria dothidea (B. dothidea) and Colletotrichum gloeosporioides (C. gloeosporioides) were identified as the main pathogens isolated from decayed bagging-free apples. Cinnamon and clove EO exhibited high inhibitory activities against mycelial growth both in vapor and contact phases under in vitro conditions. EO vapor at a concentration of 60 μL L−1 significantly reduced the incidence and lesion diameter of inoculated decay in vivo. Observations using a scanning electron microscope (SEM) and transmission electron microscope (TEM) revealed that EO changed the mycelial morphology and cellular ultrastructure and destroyed the integrity and structure of cell membranes and major organelles. Using RNA sequencing and bioinformatics, it was demonstrated that clove EO treatment impaired the cell membrane integrity and biological function via downregulating the genes involved in the membrane component and transmembrane transport. Simultaneously, a stronger binding affinity of trans-cinnamaldehyde and eugenol with CYP51 was assessed by in silico analysis, attenuating the activity of this ergosterol synthesis enzyme. Moreover, pronounced alternations in the oxidation/reduction reaction and critical materials metabolism of clove EO-treated C. gloeosporioides were also observed from transcriptomic data. Altogether, these findings contributed novel antimicrobial cellular and molecular mechanisms of EO, suggesting its potential use as a natural and useful preservative for controlling postharvest spoilage in bagging-free apples.

Pathological conditions in diabetic feet cause surface temperature variations, which can be captured quantitatively using infrared thermography. Thermal images captured during recovery of diabetic feet after active cooling may reveal richer information than those from passive thermography, but diseased foot regions may exhibit very small temperature differences compared with the surrounding area, complicating plantar foot segmentation in such cold-stressed active thermography. In this study, we investigate new plantar foot segmentation methods for thermal images obtained via cold-stressed active thermography without the complementary information from color or depth channels. To better deal with the temporal variations in thermal image contrast when planar feet are recovering from cold immersion, we propose an image pre-processing method using a two-stage adaptive gamma transform to alleviate the impact of such contrast variations. To improve upon existing deep neural networks for segmenting planar feet from cold-stressed infrared thermograms, a new deep neural network, the Plantar Foot Segmentation Network (PFSNet), is proposed to better extract foot contours. It combines the fundamental U-shaped network structure, a multi-scale feature extraction module, and a convolutional block attention module with a feature fusion network. The PFSNet, in combination with the two-stage adaptive gamma transform, outperforms multiple existing deep neural networks in plantar foot segmentation for single-channel infrared images from cold-stressed infrared thermography, achieving an accuracy of 97.3% and 95.4% as measured by Intersection over Union (IOU) and Dice Similarity Coefficient (DSC) respectively.

Reusing traction electric machine windings in electric vehicles as an integrated filtering inductor is a promising solution to reduce the size of the vehicle to grid (V2G) charging/discharging system. Obviously, the integrated inductors need to meet the requirements of traction and charging/discharging, which brings challenge for the design of traction machines. As one of the most popular traction electric machine types, the high-speed induction machine usually has large electrical time constant and consequently unacceptably long transient time in the design stage when finite element analysis is adopted. In this article, a method is proposed to quickly and accurately calculate the steady state performance of the induction machine by time-stepping transient magnetic finite element analysis. First, the stator current magnitude is ramped up from zero to full magnitude gradually to control the DC component in rotor flux and torque. Second, a multistep equivalent resistance method is adopted to decrease rotor time constant and suppress slot-tooth harmonic transient response. The proposed method can predict the FEA computation load before running the calculation, and it does not rely on the machine parameter and feedback signal. Its performance is tested by an example induction machine. The result shows that the proposed method can reduce the finite element calculation time of a high-speed operating point by 99%.

We determined the whole mtDNA genome of the Common Pochard (Aythya ferina) in the Ningxia Hui Autonomous Region, China. The complete mitochondrial genome is 16,599 bp in length and consists of 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and 1 control region (D-loop). The nucleotide composition is 29.34% A, 22.23% T, 15.66% G, and 32.77% C. Phylogenetic analysis results showed close genetic relationship between A. ferina and Aythya americana.

The Ferruginous Duck (Aythya nyroca) is a diving duck that is widely distributed in Asia, Africa, and Europe. We determined the complete mitogenome of the Ferruginous Duck gathered at Ningxia, China. The total length of the complete mitochondrial genome is 16,623 bp and it consists of 13 protein-coding, 22 tRNA, 2 rRNA genes, and 1 control region (CR). Only one overlap among the 13 protein-coding genes was found: ND4L/ND4. The CR is 1068 bp in length. The nucleotide composition is 29.66% A, 22.28% T, 15.35% G, 32.71% C. The result of phylogenetic analysis showed that there is close genetic relationship among Aythya nyroca and three ducks in the Genus Aythya.

We determined the whole mtDNA genome of the gray-headed lapwing (Vanellus cinereus) in Ningxia Hui Autonomous Region, China. The complete mitochondrial genome is 17,078 bp in length and consists of 13 protein-coding genes (PCGs), 22 tRNA genes, 2 rRNA genes, and 1 control region (D-loop). The nucleotide composition is 31.65% A, 23.50% T, 13.76% G, and 31.09% C. The result of phylogenetic analysis showed that there was close genetic relationship between V. cinereus and V. vanellus.

Sugar−acetic acid−ethanol−water mixture (SAEWM) trapping has initially shown the potential efficacy for monitoring or trapping insects. It is unknown how SAEWM-baited traps affect field number of oriental fruit moth (OFM), Grapholita molesta (Busck) (Lepidoptera: Tortricidae), the female/male ratio trapped, and the type of natural-enemy insects captured. This study investigated changes in seasonal population dynamics and diurnal flight rhythm of OFM, the number and female/male ratio of OFM and the numbers of Coccinellidae and Chrysopidae trapped by SAEWM in peach−apple mixed-planting orchards. The SAEWM performed well in trapping OFM, most of which were adult females, with the maximum trapping at 2.5 m above ground. The daily trapping peak occurred between 18:00 and 20:00, during each continuous monitoring period, with another peak occurring at 4:00−8:00, after the second monitoring period (2−5 July). However, the use of SAEWM also resulted in the trapping of Coccinellidae and Chrysopidae, of which peak trapping time partially overlapped with the second and third peak trapping times of OFM. We suggest the cessation of SAEWM trapping during the peak activity time of Coccinellidae and Chrysopidae, or application of alternative attractive mixture that do not trap the natural enemy insects, in order to protect the ecological balance in the field.

The development of natural essential oil as an alternative to synthetic chemicals in the control of postharvest decay is currently in the spotlight. In the present study, the efficacy of seven essential oils in suppressing Collelotrichum gloeosporioides identified from sweet cherry was evaluated in vitro and clove oil was proved to be the most promising inhibitor. Thus, the antifungal properties and potential mechanisms of clove oil in vitro and in vivo by fumigation and contact treatments were intensively investigated. For C. gloeosporioides, the minimal inhibitory concentrations (MIC) of clove oil in air and contact phase were 80 and 300 μL/L in vitro testing, respectively. Based on the radial growth of C. gloeosporioides mycelium in medium, the fumgitoxic ability of essential oil was observed in a dose-dependent manner, which was not as dramatic as that under in vivo conditions. Furthermore, scanning electron microscopy and transmission electron microscopy of C. gloeosporioides exposed to clove oil exhibited obviously deleterious morphological and ultrastructural alterations confirming the disruption of fungal cell wall and endomembrane system, which resulted in increasing in permeability and causing the loss of intracellular constituents. In future, essential oils, combined with nano-emulsification approaches, could be good candidates as safe and effective antifungal agents for fungal spoilage of fresh commodities.

In recent years, multi-focus image fusion has emerged as a prominent area of research, with transformers gaining recognition in the field of image processing. Current approaches encounter challenges such as boundary artifacts, loss of detailed information, and inaccurate localization of focused regions, leading to suboptimal fusion outcomes necessitating subsequent post-processing interventions. To address these issues, this paper introduces a novel multi-focus image fusion technique leveraging the Swin Transformer architecture. This method integrates a frequency layer utilizing Wavelet Transform, enhancing performance in comparison to conventional Swin Transformer configurations. Additionally, to mitigate the deficiency of local detail information within the attention mechanism, Convolutional Neural Networks (CNN) are incorporated to enhance region recognition accuracy. Comparative evaluations of various fusion methods across three datasets were conducted in the paper. The experimental findings demonstrate that the proposed model outperformed existing techniques, yielding superior quality in the resultant fused images. [ABSTRACT FROM AUTHOR]