Conditional cross-border effects of terrorism in China

This paper explores whether the cross-border effect of ethnic violence is contingent on internal factors, such as domestic security measures, distribution of religious sites, availability of communication tools, and proximity to turbulent neighboring countries. Using county-level data from Xinjiang (1995–2012), our analyses show no support for direct violence-enhancing effects of outside terrorism in Xinjiang. When terrorist attacks increase globally or in neighboring countries, overall violence in Xinjiang diminishes. We attribute this to increased security measures by the government. However, the reduction in violence is highly conditional on local factors. We find that historical religiosity and geographic proximity to the border reduce the subsident effects of external terrorism.

Capillary network formation and structure in a modified discrete mathematical model of angiogenesis

Angiogenesis, as part of cancer development, involves hierarchical complicated events and processes. Multiple studies have revealed the significance of the formation and structure of tumor-induced capillary networks. In this study, a discrete mathematical model of angiogenesis is studied and modified to capture the realistic physics of capillary network formation. Modifications are performed on the mathematical foundations of an existing discrete model of angiogenesis. The main modifications are the imposition of the matrix density effect, implementation of realistic boundary and initial conditions, and improvement of the method of governing equations based on physical observation. Results show that endothelial cells accelerate angiogenesis and capillary formation as they migrate toward the tumor and clearly exhibit the physical concept of haptotactic movement. On the other hand, consideration of blood flow-induced stress leads to a dynamic adaptive vascular network of capillaries which intelligibly reflects the brush border effect . The present modified model of capillary network formation is based on the physical rationale that defines a clear mathematical and physical interpretation of angiogenesis, which is likely to be used in cancer development modeling and anti-angiogenic therapies.

DFT-Based Channel Estimation with Channel Response Mirroring for MIMO OFDM Systems

In this paper, DFT-Based channel estimation with channel response mirroring is proposed and analyzed. In General, pilot symbols for channel estimation in MIMO(Multi-Input Multi-Output) OFDM(Orthogonal Frequency-Division Multiplexing) Systems have a diamond shape in the time-frequency plane. An interpolation technique to estimate the channel response of sub-carriers between reference symbols is needed. Various interpolation techniques such as linear interpolation, low-pass filtering interpolation, cubic interpolation and DFT interpolation are employed to estimate the non-pilot sub-carriers. In this paper, we investigate the conventional DFT-based channel estimation for noise reduction and channel response interpolation. The conventional method has performance degradation by distortion called “edge effect” or “border effect”. In order to mitigate the distortion, we propose an improved DFT-based channel estimation with channel response mirroring. This technique can efficiently mitigate the distortion caused by the DFT of channel response discontinuity. Simulation results show that the proposed method has better performance than the conventional DFT-based channel estimation in terms of MSE.

FL-MISR: fast large-scale multi-image super-resolution for computed tomography based on multi-GPU acceleration

Multi-image super-resolution (MISR) usually outperforms single-image super-resolution (SISR) under a proper inter-image alignment by explicitly exploiting the inter-image correlation. However, the large computational demand encumbers the deployment of MISR in practice. In this work, we propose a distributed optimization framework based on data parallelism for fast large-scale MISR using multi-GPU acceleration named FL-MISR. The scaled conjugate gradient (SCG) algorithm is applied to the distributed subfunctions and the local SCG variables are communicated to synchronize the convergence rate over multi-GPU systems towards a consistent convergence. Furthermore, an inner-outer border exchange scheme is performed to obviate the border effect between neighboring GPUs. The proposed FL-MISR is applied to the computed tomography (CT) system by super-resolving the projections acquired by subpixel detector shift. The SR reconstruction is performed on the fly during the CT acquisition such that no additional computation time is introduced. FL-MISR is extensively evaluated from different aspects and experimental results demonstrate that FL-MISR effectively improves the spatial resolution of CT systems in modulation transfer function (MTF) and visual perception. Comparing to a multi-core CPU implementation, FL-MISR achieves a more than 50$$\times$$ × speedup on an off-the-shelf 4-GPU system.

Goodput Modelling and Optimisation of Channel Assignment For Planning IEEE 802.11Wireless Backhaul Networks

<p>IEEE 802.11Wireless backhaul networks (WBNs) provide scalable and cost-effective solutions for interconnecting small-cell networks and backbone networks or Internet. With newer and farther reaching applications being developed in IEEE 802.11 WBNs, such as smart grids and intelligent transportation systems, users expect high goodput and better fairness. However, some performance issues in IEEE 802.11 protocols such as border effect, exposed nodes and hidden nodes are exacerbated as network densification occurs, leading to goodput degradation and severe unfairness such as flow starvation (extreme low goodput). These issues may cause an IEEE 802.11 WBN to form a bottleneck and impact the overall network performance. Therefore, in-depth study is required in order to improve the IEEE 802.11 WBN planning to achieve better goodput and fairness. This research aims to improve IEEE 802.11 WBN planning through goodput modelling and optimising channel assignment. A novel simple goodput distribution model is proposed to predict goodput and fairness in IEEE 802.11 WBNs. Simulation results show that the proposed goodput model accurately predicts goodput with consideration of carrier sensing effect and traffic demands. Based on this goodput model, a new interference model is proposed to more realistically reflect both local and global interference in IEEE 802.11 WBNs. With the proposed interference model, two anti-starvation channel assignments have been developed to prevent flow starvation. Simulation validations show that the new anti-starvation channel assignments effectively prevent flow starvation and improve network fairness in IEEE 802.11 WBNs. This research also optimises channel assignment to achieve desired fairness and goodput. A multi-objective optimisation problem is formulated and a new fitness function is designed to evaluate a channel allocation with accurate prediction of goodput and fairness. Utilising the new fitness function, two multi-objective channel assignments have been developed to achieve both fairness and goodput. Compared with existing channel assignments through simulation, the proposed multi-objective channel assignments provide a set of feasible solutions that meet desired fairness and goodput. This research helps network planners or service providers to improve the IEEE 802.11 WBN planning from predicting network performance to optimising goodput and fairness. The proposed goodput model, interference model, and fitness function are also useful for node placement, and optimising routing and scheduling in IEEE 802.11 WBNs.</p>

Goodput Modelling and Optimisation of Channel Assignment For Planning IEEE 802.11Wireless Backhaul Networks

<p>IEEE 802.11Wireless backhaul networks (WBNs) provide scalable and cost-effective solutions for interconnecting small-cell networks and backbone networks or Internet. With newer and farther reaching applications being developed in IEEE 802.11 WBNs, such as smart grids and intelligent transportation systems, users expect high goodput and better fairness. However, some performance issues in IEEE 802.11 protocols such as border effect, exposed nodes and hidden nodes are exacerbated as network densification occurs, leading to goodput degradation and severe unfairness such as flow starvation (extreme low goodput). These issues may cause an IEEE 802.11 WBN to form a bottleneck and impact the overall network performance. Therefore, in-depth study is required in order to improve the IEEE 802.11 WBN planning to achieve better goodput and fairness. This research aims to improve IEEE 802.11 WBN planning through goodput modelling and optimising channel assignment. A novel simple goodput distribution model is proposed to predict goodput and fairness in IEEE 802.11 WBNs. Simulation results show that the proposed goodput model accurately predicts goodput with consideration of carrier sensing effect and traffic demands. Based on this goodput model, a new interference model is proposed to more realistically reflect both local and global interference in IEEE 802.11 WBNs. With the proposed interference model, two anti-starvation channel assignments have been developed to prevent flow starvation. Simulation validations show that the new anti-starvation channel assignments effectively prevent flow starvation and improve network fairness in IEEE 802.11 WBNs. This research also optimises channel assignment to achieve desired fairness and goodput. A multi-objective optimisation problem is formulated and a new fitness function is designed to evaluate a channel allocation with accurate prediction of goodput and fairness. Utilising the new fitness function, two multi-objective channel assignments have been developed to achieve both fairness and goodput. Compared with existing channel assignments through simulation, the proposed multi-objective channel assignments provide a set of feasible solutions that meet desired fairness and goodput. This research helps network planners or service providers to improve the IEEE 802.11 WBN planning from predicting network performance to optimising goodput and fairness. The proposed goodput model, interference model, and fitness function are also useful for node placement, and optimising routing and scheduling in IEEE 802.11 WBNs.</p>

Shuttle breeding in sunflower lines development

Shuttle breeding is a breeding system where generations undergo sequential evaluations at different locations, developed by N. Borlaug. Our study aims to demonstrate an opportunity of application shuttle breeding method in sunflower lines development and also to show its advantages and disadvantages. Experiments were mainly conducted at the Central Station (Krasnodar) of All-Russia Research Institute of Oil Crops (VNIIMK). Krasnodar region is situated in the Southern part of Russia near the Black Sea. Part of our work was made at Seed and Plant Improvement Institute (Karaj, Iran) and Experimental Station near Borozdjan (Busher Province of Iran). Released and experimental sunflower hybrids and lines of VNIIMK breeding were used as a material. The experimental design was randomized blocks with three replications. Each replication had four rows and two central rows were analyzed only to exclude the border effect. It is shown that the application of the shuttle breeding technique to sunflower was highly successful and results in elite line development.

The Dynamic Impact Response of 3D-Printed Polymeric Sandwich Structures with Lattice Cores: Numerical and Experimental Investigation

This paper proposes a dynamic drop weight impact simulation to predict the impact response of 3D printed polymeric sandwich structures using an explicit finite element (FE) approach. The lattice cores of sandwich structures were based on two unit cells, a body-centred cubic (BCC) and an edge-centred cubic (ECC). The deformation and the peak acceleration, referred to as the g-max score, were calculated to quantify their shock absorption characteristic. For the FE results verification, a falling mass impact test was conducted. The FE results were in good agreement with experimental measurements. The results suggested that the strut diameter, strut length, number and orientation, and the apparent material stiffness of the lattice cores had a significant effect on their deformation behavior and shock absorption capability. In addition, the BCC lattice core with a thinner strut diameter and low structural height might lead to poor shock absorption capability caused by structure collapse and border effect, which could be improved by increasing its apparent material stiffness. This dynamic drop impact simulation process could be applied across numerous industries such as footwear, sporting goods, personal protective equipment, packaging, or biomechanical implants.