远志多糖对力竭运动小鼠体内抗疲劳和体外抗氧化作用研究

为了探讨远志多糖的体内、外活性，采用力竭运动动物模型，给予受试动物低、中、高剂量（0.10、0.20、0.40 mg/g·d）远志多糖后，分别测定各组动物负重游泳时间、肝糖原、肌糖原、乳酸、尿素氮含量及乳酸脱氢酶的活力和体外抗氧化活性。结果表明，与空白对照组相较，低、中、高剂量的远志多糖分别延长小鼠的负重游泳时间96.6 s （P<0.05）、254.4 s （P<0.01）和421.8 s （P<0.01），肝糖原含量分别提高13.1%（P<0.05）、37.4%（P<0.01）和56.4%（P<0.01），肌糖原含量分别提高10.8%（P<0.05）、31.2%（P<0.01）和42.0%（P<0.01），运动后乳酸含量分别下降4.6%（P<0.05）、8.6%（P<0.01）和14.5%（P<0.01），尿素氮含量分别降低1.5%（P<0.05）、3.9%（P<0.01）和7.5%（P<0.01），乳酸脱氢酶活力分别提高10.4%（P<0.01）、14.0%（P<0.01）和19.9%（P<0.01）。当远志多糖浓度为4 mg/mL时，对羟基自由基清除率和DPPH自由基的清除率分别为61.3%和79.5%，表明远志多糖有助于缓解机体疲劳，且体外抗氧化性较好。     

WavNet — Visual saliency detection using Discrete Wavelet Convolutional Neural Network

In the recent advancements in image and video analysis, the detection of salient regions in the image becomes the initial step. This plays a crucial role in deciding the performance of such algorithms. In this work, a Multi-Resolution Feature Extraction (MRFE) technique that makes use of Discrete Wavelet Convolutional Neural Network (DWCNN) for generating features is employed. An Enhanced Feature Extraction (EFE) module extracts additional features from the high level features of the DWCNN, which are used to frame both channel as well as spatial attention models for yielding contextual attention maps. A new hybrid loss function is also proposed, which is a combination of Balanced Cross Entropy (BCE) loss and Edge based Structural Similarity (ESSIM) loss that effectively identifies and segments the salient regions with clear boundaries. The method is tested exhaustively with five different benchmark datasets and is proved superior to the existing state-of-the-art methods with a minimum Mean Absolute error (MAE) of 0.03 and F-measure of 0.956.     

Vulnerable objects detection for autonomous driving: A review

Object detection performed by Autonomous Vehicles (AV)s is a crucial operation that comes ahead of various autonomous driving tasks, such as object tracking, trajectories estimation, and collision avoidance. Dynamic road elements (pedestrians, cyclists, vehicles) impose a greater challenge due to their continuously changing location and behaviour. This paper presents a comprehensive review of the state-of-the-art object detection technologies focusing on both the sensory systems and algorithms used. It begins with a brief introduction on the autonomous driving operations and challenges. Then, different sensory systems employed on existing AVs are elaborated while illustrating their advantages, limitations and applications. Also, sensory systems employed by different research are reviewed. Moreover, due to the significant role Deep Neural Networks (DNN)s are playing in object detection tasks, different DNN-based networks are also highlighted. Afterwards, previous research on dynamic objects detection performed by AVs are reviewed in tabular forms. Finally, a conclusion summarizes the outcomes of the review and suggests future work towards the development of vehicles with higher automation levels.     

食品安全国家标准中维生素的测定方法及进展

人体所必需的营养素除了蛋白质、脂类、糖类等能量物质外,维生素也是不可或缺的营养物质,是评价其营养质量的关键指标。检测食品中的维生素含量,是有效保证其质量与安全的必要条件。因此,对现有国家标准食品中维生素的检测方法进行综述,总结各方法的前处理及检出限等,为增强检测工作效率,以及食品检测方法的研究和发展提供参考。     

Salt-assisted solution combustion synthesis of NiFe2O4: Effect of salt type

The effects of three types of salt including NaF, KCl, and NaCl on the properties of NiFe₂O₄ nanoparticles using salt-assisted solution combustion synthesis (SSCS) have been investigated. The synthesized powders were evaluated by SEM, TEM, FTIR, XRD, and VSM analysis. Also, the specific surface area (SSA), as well as size distribution and volume of the porosities of NiFe₂O₄ powders were determined by the BET apparatus. The visual observations showed that the intensity and time of combustion synthesis of nanoparticles have been severely influenced by the type of salt. The highest crystallinity was observed in the synthesized powder using NaCl. The SSA has also been correlated completely to the type of salt. The quantities of SSA was achieved about 91.62, 64.88, and 47.22 m²g^-1 for the powders synthesized by KCl, NaCl, and NaF respectively. Although the magnetic hysteresis loops showed the soft ferromagnetic behavior of the NiFe₂O₄ nanoparticles in all conditions, KCl salt could produce the particles with the least coercivity and remanent magnetization. Based on the present study, the salt type is a key parameter in the SSCS process for the preparation of spinel ferrites. Thermodynamic evaluation also showed that the melting point and heat capacity are important parameters for the proper selection of the salt.     

The Tumor Proteolytic Landscape: A Challenging Frontier in Cancer Diagnosis and Therapy

In recent decades, dysregulation of proteases and atypical proteolysis have become increasingly recognized as important hallmarks of cancer, driving community-wide efforts to explore the proteolytic landscape of oncologic disease. With more than 100 proteases currently associated with different aspects of cancer development and progression, there is a clear impetus to harness their potential in the context of oncology. Advances in the protease field have yielded technologies enabling sensitive protease detection in various settings, paving the way towards diagnostic profiling of disease-related protease activity patterns. Methods including activity-based probes and substrates, antibodies, and various nanosystems that generate reporter signals, i.e., for PET or MRI, after interaction with the target protease have shown potential for clinical translation. Nevertheless, these technologies are costly, not easily multiplexed, and require advanced imaging technologies. While the current clinical applications of protease-responsive technologies in oncologic settings are still limited, emerging technologies and protease sensors are poised to enable comprehensive exploration of the tumor proteolytic landscape as a diagnostic and therapeutic frontier. This review aims to give an overview of the most relevant classes of proteases as indicators for tumor diagnosis, current approaches to detect and monitor their activity in vivo, and associated therapeutic applications.     

Transmission line detection in aerial images: An instance segmentation approach based on multitask neural networks

Camera-based transmission line detection (TLD) is a fundamental and crucial task for automatically patrolling powerlines by aircraft. Motivated by instance segmentation, a TLD algorithm is proposed in this paper with a novel deep neural network, i.e., CableNet. The network structure is designed based on fully convolutional networks (FCNs) with two major improvements, considering the specific appearance characteristics of transmission lines. First, overlaying dilated convolutional layers and spatial convolutional layers are configured to better represent continuous long and thin cable shapes. Second, two branches of outputs are arranged to generate multidimensional feature maps for instance segmentation. Thus, cable pixels can be detected and assigned cable IDs simultaneously. Multiple experiments are conducted on aerial images, and the results show that the proposed algorithm obtains reliable detection performance and is superior to traditional TLD methods. Meanwhile, segmented pixels can be accurately identified as cable instances, contributing to line fitting for further applications.     

Synthesis and Properties of New Cleavable Cationic Surfactants Containing Carbonate Groups

A novel series of cleavable alkyltrimethylammonium surfactants with different hydrocarbon chain lengths (C8–16) were synthesized. A carbonate break site inserted between the polar head and the hydrocarbon chain makes these compounds hydrolyzable. The reagents used are renewable, (bio)degradable, or reusable. The hydrolysis of these cleavable surfactants will lead to the generation of fatty alcohols and choline, which is an essential biological nutrient. The surface activities in aqueous solution of the synthesized carbonates fulfill the requirement of being good surfactants. In addition, the cleavable compounds containing n-decyl and n-dodecyl chains showed similar or higher antimicrobial activities when compared to a non-cleavable analog.     

Engineering Bioactive M2 Macrophage-Polarized Anti-Inflammatory,Antioxidant, and Antibacterial Scaffolds for Rapid Angiogenesis and Diabetic Wound Repair

Diabetic wound healing still faces great challenges due to the excessive inflammation, easy infection, and impaired angiogenesis in wound beds. The immunoregulation of macrophages polarization toward M2 phenotype that facilitates the transition from inflammation to proliferation phase has been proved to be an effective way to improve diabetic wound healing. Herein, an M2 phenotype-enabled anti-inflammatory, antioxidant, and antibacterial conductive hydrogel scaffolds (GDFE) for producing rapid angiogenesis and diabetic wound repair are reported. The GDFE scaffolds are fabricated facilely through the dynamic crosslinking between polypeptide and polydopamine and graphene oxide. The GDFE scaffolds possess thermosensitivity, self-healing behavior, injectability, broad-spectrum antibacterial activity, antioxidant and anti-inflammatory ability, and electronic conductivity. GDFE effectively activates the polarization of macrophages toward M2 phenotype and significantly promotes the proliferation of dermal fibroblasts, the migration, and in vitro angiogenesis of endothelial cells through paracrine mechanisms. The in vivo results from a full-thickness diabetic wound model demonstrate that GDFE can rapidly promote the diabetic wound repair and skin regeneration, through fast anti-inflammation and angiogenesis and M2 macrophage polarization. This study provides highly efficient strategy for treating diabetic wound repair through designing the M2 polarization-enabled anti-inflammatory, antioxidant, and antibacterial bioactive materials.     

A comprehensive survey on computer vision based concepts,methodologies, analysis and applications for automatic gun/knife detection

The ability to detect gun and gun held in hand or other body parts is a typical human skill. The same problem presents an imperative task for computer vision system. Automatic observer independent detection of hand held gun or gun held in the other body part, whether it is visible or concealed, provides enhance security in vulnerable places and initiates appropriate action there. Compare to the automatic object detection systems, automatic detection of gun has very few successful attempts. In the present scope of this paper, we present an extensive survey on automatic detection of gun and define a taxonomy for this particular detection system. We also describe the inherent difficulties related with this problem. In this survey of published papers, we examine different approaches used in state-of-the-art attempts and compare performances of these approaches. Finally, this paper concludes pointing to the possible research gaps in related fields.