Evaluation of Heat Generation in Unidirectional Versus Oscillatory Modes During K‐Wire Insertion in Bone

Heat generation during insertion of Kirschner wires (K‐wires) may lead to thermal osteonecrosis and can affect the construct fixation. Unidirectional and oscillatory drilling modes are options for K‐wire insertion, but understanding of the difference in heat generation between the two modes is lacking. The goal of this study was to compare the temperature rise during K‐wire insertion under these two modes and provide technical guidelines for K‐wire placement to minimize thermal injury. Ten orthopedic surgeons were instructed to drill holes on hydrated ex vivo bovine bones under two modes. The drilling trials were evaluated in terms of temperature, thrust force, torque, drilling time, and tool wear. The analysis of variance showed that the oscillatory mode generated significantly lowered peak bone temperature rise (13% lower mean value, p = 0.036) over significantly longer drilling time (46% higher mean time, p < 0.001) than the unidirectional mode. Drilling time had significant effect on peak bone temperature rise under both modes (p < 0.001) and impact of peak thrust force was significant under oscillatory mode (p < 0.001). These findings suggest that the drilling mode choice is a compromise between peak temperature and bone exposure time. Shortening the drilling time was the key under both modes to minimize temperature rise and thermal necrosis risk. To achieve faster drilling, technique analysis found that “shaky” and intermittent drilling with moderate thrust force are preferred techniques by small vibration of the drill about the K‐wire axis and slight lift‐up of the K‐wire once or twice during drilling. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:1903–1909, 2019Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151349/1/jor24345_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151349/2/jor24345.pd

Ca1_xLixAl1_xSi1+xN3：Eu2+ solid solutions as broadband,color-tunable and thermally robust red phosphors for superior color rendition white light-emitting diodes

日前，我院解荣军教授及其合作者在半导体照明用稀土掺杂氮化物发光材料研究上取得突破性进展。稀土发光材料是半导体照明技术中最为关键的核心材料之一，决定了半导体照明器件的发光效率、显色指数、色温和可靠性等重要性能。解荣军教授及其合作者在长期研究氮化物发光材料及半导体照明器件的工作基础上，巧妙地通过发光材料的晶体结构局域调控和能带工程设计，研究和开发了具有宽谱发射、光谱可控的高可靠性氮化物固溶体红色发光材料，成功解决了半导体照明技术中的重要科学问题和关键技术难题。该论文的第一作者为中国计量大学光学与电子技术学院的王乐副教授，解荣军和王乐为共同通讯作者，厦门大学为第一通讯单位。合作单位还有日本国立材料研究所、重庆邮电大学和台湾大学。由于文章具有创新性和重要性，被选为当期封面文章。【Abstract】Color rendition, luminous efficacy and reliability are three key technical parameters for white light-emitting diodes (wLEDs) that are dominantly determined by down-conversion phosphors. However, there is usually an inevitable trade-off between color rendition and luminescence efficacy because the spectrum of red phosphor (that is, spectral broadness and position) cannot satisfy them simultaneously. In this work, we report a very promising red phosphor that can minimize the aforementioned trade-off via structure and band-gap engineering, achieved by introducing isostructural LiSi2N3 into CaAlSiN3:Eu2+. The solid solution phosphors show both substantial spectra broadening (88→117 nm) and blueshift (652→642 nm), along with a significant improvement in thermal quenching (only a 6% reduction at 150 °C), which are strongly associated with electronic and crystal structure evolutions. The broadband and robust red phosphor thus enables fabrication of super-high color rendering wLEDs (Ra=95 and R9=96) concurrently with the maintenance of a high-luminous efficacy (101 lm W−1), validating its superiority in high-performance solid state lightings over currently used red phosphors.We are grateful for the financial support from the JSPS KAKENHI (No. 23560811), the National Natural Science Foundation of China (Nos. 51272259, 61575182, 5157223 and 51561135015), the Natural Science Foundation of Zhejiang Province (No. Y16F050012) and the Taiwan Science and Technology Authority (No. ‘MOST’ 104-2113-M-002-012-MY3 and No. 104-2119-M-002-027-MY3)

Instance Segmentation of Tea Garden Roads Based on an Improved YOLOv8n-seg Model

In order to improve the efficiency of fine segmentation and obstacle removal in the road of tea plantation in hilly areas, a lightweight and high-precision DR-YOLO instance segmentation algorithm is proposed to realize environment awareness. Firstly, the road data of tea gardens in hilly areas were collected under different road conditions and light conditions, and data sets were generated. YOLOv8n-seg, which has the highest operating efficiency, was selected as the basic model. The MSDA-CBAM and DR-Neck feature fusion network were added to the YOLOv8-seg model to improve the feature extraction capability of the network and the feature fusion capability and efficiency of the model. Experimental results show that, compared with the YOLOv8-seg model, the DR-YOLO model proposed in this study has 2.0% improvement in [email protected] and 1.1% improvement in Precision. In this study, the DR-YOLO model is pruned and quantitatively compressed, which greatly improves the model inference speed with little reduction in AP. After deploying on Jetson, compared with the YOLOv8n-seg model, the Precision of DR-YOLO is increased by 0.6%, the [email protected] is increased by 1.6%, and the inference time is reduced by 17.1%, which can effectively improve the level of agricultural intelligent automation and realize the efficient operation of the instance segmentation model at the edge

Characterization a Novel Butyric Acid-Producing Bacterium Collinsella aerofaciens Subsp. Shenzhenensis Subsp. Nov.

Butyrate-producing bacteria can biosynthesize butyrate and alleviate inflammatory diseases. However, few studies have reported that the genus Collinsella has the ability to produce butyric acid. Here, our study depicts a Collinsella strain, which is a rod-shaped obligate anaerobe that is able to produce butyric acid. This microorganism was isolated from a human gut, and the optimal growth conditions were found to be 37 &deg;C on PYG medium with pH 6.5. The 16S rRNA gene sequence demonstrated that this microorganism shared 99.93% similarity with C. aerofaciens ATCC 25986T, which was higher than the threshold (98.65%) for differentiating two species. Digital DNA&ndash;DNA hybridization and average nucleotide identity values also supported that this microorganism belonged to the species C. aerofaciens. Distinct phenotypic characteristics between TF06-26 and the type strain of C. aerofaciens, such as the fermentation of D-lactose, D-fructose and D-maltose, positive growth under pH 5 and 0.2% (w/v) cholate, suggested this strain was a novel subspecies. Comparative genome analysis revealed that butyric acid kinase and phosphate butyryltransferase enzymes were coded exclusively by this strain, indicating a specific butyric acid-producing function of this C. aerofaciens subspecies within the genus Collinsella. Thus, Collinsella aerofaciens subsp. shenzhenensis subsp. nov. was proposed, with set strain TF06-26T (=CGMCC 1.5216T = DSM 105138T) as the type strain

Cutting Behavior of Cortical Bone in Different Bone Osteon Cutting Angles and Depths of Cut

Abstract Cortical bone is semi-brittle and anisotropic, that brings a challenge to suppress vibration and avoid undesired fracture in precise cutting process in surgeries. In this paper, a novel analytical model is proposed to represent cortical bone cutting processes. The model is utilized to predict the chip formations, material removal behavior and cracks propagation under varying bone osteon cutting angles and depths. Series of orthogonal cutting experiments were conducted on cortical bone to investigate the impact of bone osteon cutting angle and depth of cut on cutting force, crack initialization and propagation. The observed chip morphology highly agreed with the prediction of chip formation based on the analytical model. The curly, serrated, grainy and powdery chips formed when the cutting angle was set as 0°, 60°, 90°, and 120°, respectively. Cortical bone were removed dominantly by shearing at a small depth of cut from 10 to 50 μm, and by a mixture of pealing, shearing, fracture and crushing at a large depth of cut over 100 μm at different bone osteon angles. Moreover, its fracture toughness was calculated based on measured cutting force. It is found that the fluctuation of cutting force is suppressed and the bone material becomes easy to remove, which attributes to lower fracture toughness at bone osteon cutting angle 0°. When the cutting direction develops a certain angle to bone osteon, the fracture toughness increases then the crack propagation is inhibited to some extent and the fluctuation of cutting force comparatively decreases. There is a theoretical and practical significance for tools design and operational parameters choice in surgeries

Research on and Design of an Electric Drive Automatic Control System for Mine Belt Conveyors

Conveyor belts are widely used in ore transportation in large-scale mines for their long transportation range, high safety, and strong economic applicability. Coal mine belt conveyors are not only traditional, simple mechanical conveying devices but also automatic control system operating devices that integrate safety, stability, and low power consumption. In the process of coal mining, a conveyor belt control system also needs to be closely integrated with modern industrial systems and information systems, which greatly improves its work efficiency. The purpose of this article is to improve the methods for designing automatic control systems for electric motors in order to obtain mechanical characteristics close to a constant power line, which would ensure the reliable operation of belt conveyors. An automatic control system was designed based on the controller Siemens S7-1200; then, a mathematical model of an automated electric drive was developed. Based on the mathematical model, a simulation model of an automatic electric drive was built, and the modes were modeled. After designing, the obtained plots of transients completely corresponded to the required transients, which means that the Siemens frequency converter automatic control system (ACS) parameters were calculated quite accurately and the conveyor electric drive met all requirements

A Review of Target Recognition Technology for Fruit Picking Robots: From Digital Image Processing to Deep Learning

Machine vision technology has dramatically improved the efficiency, speed, and quality of fruit-picking robots in complex environments. Target recognition technology for fruit is an integral part of the recognition systems of picking robots. The traditional digital image processing technology is a recognition method based on hand-designed features, which makes it difficult to achieve better recognition as it results in dealing with the complex and changing orchard environment. Numerous pieces of literature have shown that extracting special features by training data with deep learning has significant advantages for fruit recognition in complex environments. In addition, to realize fully automated picking, reconstructing fruits in three dimensions is a necessary measure. In this paper, we systematically summarize the research work on target recognition techniques for picking robots in recent years, analyze the technical characteristics of different approaches, and conclude their development history. Finally, the challenges and future development trends of target recognition technology for picking robots are pointed out