The Role of Media Synchronicity Fit and Sense of Community in Live Streaming Platforms

To understand viewers’ sense of community in the live streaming environment, this research synthesizes media synchronicity theory and sense of community theory to develop a theoretical framework. We aim to examine the antecedents and consequences of the sense of community in live streaming platforms. We expect that viewers’ actual communication purpose (e.g., conveyance or convergence) will influence viewers\u27 sense of community in the live streaming context and further impact their activities in traditional third-party online communities. We first use experiments to validate the mechanism in our theoretical model and then collect observational data from Twitch, a popular live streaming platform, to test our hypotheses. Our results will provide theoretical contributions to the live streaming, online community, and communication literature. Our findings will provide practical implications for streamers in the live streaming platform

THE EFFECTS OF STATIC STRETCHING AFTER STRENUOUS TRAINING ON ULTRASTRUCTURE AND FLEXIBILITY OF RATS' GASTROCNEMIUS

The purpose of the present study was to investigate effects of static stretching after strenuous training on the ultrastructure and flexibility of rats' gastrocnemius. 24 male Sprague-Dawley rats were randomly divided into three groups: normal control (NC), training control(TC) and stretching group(ST). The results were as follows: 1) The myofilaments became supercontracted and Z discs were obscure in TC. On the contrary, the myofilaments arranged orderly and the Z lines were clear and the mitochondrial cristas were manifolded in ST. 2) Compared with NC, the ultimate tensile strength of gastrocnemius was increased in TC, while the Max. deformation of gastorcnemius was decreased. However, the Max. deformation in ST was increased than that of NC. The conclusion was that the ultrastructure of muscle was resumed and the ability of distortion and flexibility was improved by static stretching, which decreased the risk of injury

A cyber-physical machine tools platform using OPC UA and MTConnect

Cyber-Physical Machine Tools (CPMT) represent a new generation of machine tools that are smarter, well connected, widely accessible, more adaptive and more autonomous. Development of CPMT requires standardized information modelling method and communication protocols for machine tools. This paper proposes a CPMT Platform based on OPC UA and MTConnect that enables standardized, interoperable and efficient data communication among machine tools and various types of software applications. First, a development method for OPC UA-based CPMT is proposed based on a generic OPC UA information model for CNC machine tools. Second, to address the issue of interoperability between OPC UA and MTConnect, an MTConnect to OPC UA interface is developed to transform MTConnect information model and its data to their OPC UA counterparts. An OPC UA-based CPMT prototype is developed and further integrated with a previously developed MTConnect-based CPMT to establish a common CPMT Platform. Third, different applications are developed to demonstrate the advantages of the proposed CPMT Platform, including an OPC UA Client, an advanced AR-assisted wearable Human-Machine Interface and a conceptual framework for CPMT powered cloud manufacturing environment. Experimental results have proven that the proposed CPMT Platform can significantly improve the overall production efficiency and effectiveness in the shop floor

Electrical transport and magnetic properties of the triangular-lattice compound Zr2_2NiP2_2

We report the first investigation of the electrical and magnetic properties of the triangular-lattice compound Zr$_2$NiP$_2$ (space group $P$6$_3$/$mmc$). The temperature evolution of electrical resistivity follows the Bloch-Gr\"uneisen-Mott law, and exhibits a typically metallic behavior. No transition is visible by both electrical and magnetic property measurements, and nearly no magnetization is detected ($M_0$ $<$ 0.002$\mu_\mathrm{B}$/Ni) down to 1.8 K up to 7 T. The metallic and nonmagnetic characters are well understood by the first-principles calculations for Zr$_2$NiP$_2$.Comment: 16 pages, 4 figure

Knowledge-aware Deep Framework for Collaborative Skin Lesion Segmentation and Melanoma Recognition

Deep learning techniques have shown their superior performance in dermatologist clinical inspection. Nevertheless, melanoma diagnosis is still a challenging task due to the difficulty of incorporating the useful dermatologist clinical knowledge into the learning process. In this paper, we propose a novel knowledge-aware deep framework that incorporates some clinical knowledge into collaborative learning of two important melanoma diagnosis tasks, i.e., skin lesion segmentation and melanoma recognition. Specifically, to exploit the knowledge of morphological expressions of the lesion region and also the periphery region for melanoma identification, a lesion-based pooling and shape extraction (LPSE) scheme is designed, which transfers the structure information obtained from skin lesion segmentation into melanoma recognition. Meanwhile, to pass the skin lesion diagnosis knowledge from melanoma recognition to skin lesion segmentation, an effective diagnosis guided feature fusion (DGFF) strategy is designed. Moreover, we propose a recursive mutual learning mechanism that further promotes the inter-task cooperation, and thus iteratively improves the joint learning capability of the model for both skin lesion segmentation and melanoma recognition. Experimental results on two publicly available skin lesion datasets show the effectiveness of the proposed method for melanoma analysis.Comment: Pattern Recognitio