Numerical simulation of mould filling process for pressure plate and valve handle in LFC

In lost foam casting (LFC), the distribution of polymer beads during the bead filling process is not uniform, and the collision between polymer beads determines the distribution of two-phase flow of gas and solid. The interaction between the gas and solid phases reveals as coupling effect of the force that gas exerts on particles or vice versa, or that among particles. The gas-solid flow in filling process is nonlinearity, which makes the coupling effect an essential point to carry out a simulation properly. Therefore, information of each particle’s motion is important for acquiring the law of filling process. In bead filling process, compressed air is pressed into mold cavity, and discharged from gas vent, creating a pressure difference between outer and inner space near the gas vent. This pressure difference directly changes the spatial distribution and motion trace of gas and solid phases. In this paper, Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD) are employed to simulate the fluid dynamic character based on Newton’s Third Law of Motion. The simulation results of some casting products such as pressure plate and valve handle are compared with the result obtained from practical experiment in order to test the feasibility of DEM. The comparison shows that this DEM method can be a very promising tool in the mould filling simulation of beads’ movement

Segmentation for Fabric Weave Pattern Using Empirical Mode Decomposition Based Histogram

This paper is focused on the segmentation of the fabric weave patterns for the urgent requirement of fabric imitative design and redesign.The weave patterns related to the fabric yarn are determined by a new technology,which is called bidimensional mode decomposition based method. The proposed method first iteratively decompose the underlying fabric image into a number of intrinsic mode functions (IMFs). The first order IMF is applied to to calculate histogram and fabric weave pattern segmentation results are obtained by integrating corresponding threshold decision strategies such as double maxima algorithm or Otsu algorithm . In comparison with the original image-only based histogram segmentation method ,the presented method have a high precision. Simulation results show that BEMD based method is a promising approach for the segmentation of fabric weave pattern. DOI: http://dx.doi.org/10.11591/telkomnika.v11i4.237

MELK is an oncogenic kinase essential for mitotic progression in basal-like breast cancer cells

Despite marked advances in breast cancer therapy, basal-like breast cancer (BBC), an aggressive subtype of breast cancer usually lacking estrogen and progesterone receptors, remains difficult to treat. In this study, we report the identification of MELK as a novel oncogenic kinase from an in vivo tumorigenesis screen using a kinome-wide open reading frames (ORFs) library. Analysis of clinical data reveals a high level of MELK overexpression in BBC, a feature that is largely dependent on FoxM1, a master mitotic transcription factor that is also found to be highly overexpressed in BBC. Ablation of MELK selectively impairs proliferation of basal-like, but not luminal breast cancer cells both in vitro and in vivo. Mechanistically, depletion of MELK in BBC cells induces caspase-dependent cell death, preceded by defective mitosis. Finally, we find that Melk is not required for mouse development and physiology. Together, these data indicate that MELK is a normally non-essential kinase, but is critical for BBC and thus represents a promising selective therapeutic target for the most aggressive subtype of breast cancer. DOI: http://dx.doi.org/10.7554/eLife.01763.00

(1S,4S)-2-(2,4-Difluoro­phen­yl)-5-[(4-methyl­phen­yl)sulfon­yl]-2,5-diaza­bicyclo­[2.2.1]hepta­ne

In the title mol­ecule, C18H18F2N2O2S, the two benzene rings, which are oriented in opposite directions with respect to the rigid 2,5-diaza­bicyclo­[2.2.1]heptane core, form a dihedral angle of 17.2 (1)°. Weak inter­molecular C—H⋯O, C—H⋯F and C—H⋯N contacts consolidate the crystal packing

A secured framework for SDN-based edge computing in IoT-enabled healthcare system

The Internet of Things (IoT) consists of resource-constrained smart devices capable to sense and process data. It connects a huge number of smart sensing devices, i.e., things, and heterogeneous networks. The IoT is incorporated into different applications, such as smart health, smart home, smart grid, etc. The concept of smart healthcare has emerged in different countries, where pilot projects of healthcare facilities are analyzed. In IoT-enabled healthcare systems, the security of IoT devices and associated data is very important, whereas Edge computing is a promising architecture that solves their computational and processing problems. Edge computing is economical and has the potential to provide low latency data services by improving the communication and computation speed of IoT devices in a healthcare system. In Edge-based IoT-enabled healthcare systems, load balancing, network optimization, and efficient resource utilization are accurately performed using artificial intelligence (AI), i.e., intelligent software-defined network (SDN) controller. SDN-based Edge computing is helpful in the efficient utilization of limited resources of IoT devices. However, these low powered devices and associated data (private sensitive data of patients) are prone to various security threats. Therefore, in this paper, we design a secure framework for SDN-based Edge computing in IoT-enabled healthcare system. In the proposed framework, the IoT devices are authenticated by the Edge servers using a lightweight authentication scheme. After authentication, these devices collect data from the patients and send them to the Edge servers for storage, processing, and analyses. The Edge servers are connected with an SDN controller, which performs load balancing, network optimization, and efficient resource utilization in the healthcare system. The proposed framework is evaluated using computer-based simulations. The results demonstrate that the proposed framework provides better solutions for IoT-enabled healthcare systems. © 2013 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Venki Balasubramaniam” is provided in this record*

Waterbody type dependence of the spatial distribution of macroinvertebrate communities in temperate China

Distance-decay relationships (DDRs) are a useful method for describing the spatial distribution of biological communities. However, the patterns of macroinvertebrate DDRs and the mechanisms of community assembly in continuous lotic-lentic (river-lake) systems remain poorly understood. We compared the spatial and temporal patterns and biogeographic patterns of macroinvertebrate communities in different water types (river vs. lake) in the temperate zone of China. Data were collected from 152 sampling sites in the Daqing River Basin over two years, and multivariate statistical analyses were conducted. These results provide the first description of biogeographical patterns of macroinvertebrate communities in the Daqing River in temperate China. Macroinvertebrates from both the river and lake exhibited contrasting community compositions, likely due to habitat differences. All macroinvertebrate communities showed a significant distance-decay pattern in both waterbody types, with stronger DDRs in the lake. In the lake, spatial and environmental variables contributed to the spatial distribution of macroinvertebrate communities, while in the river, spatial variables were slightly more important than environmental variables. Spatial variables influenced macroinvertebrate community distribution directly and impacted environmental variables indirectly. Importantly, these communities were strongly driven by stochastic processes. Additionally, macroinvertebrate taxa formed ecologically and taxonomically distinct groups, potentially structured by both deterministic and stochastic processes. The normalized stochasticity ratio (NST) quantified the community-building process based on the neutral model, indicating that deterministic processes may dominate in rivers, while stochastic processes may dominate in lakes. The findings highlight the contrasting roles of deterministic and stochastic processes in shaping macroinvertebrate communities in lotic and lentic systems, providing new insights into the mechanisms of community assembly in continuous river-lake ecosystems