Preparation and Properties of 1, 3, 5, 7-Tetranitro-1, 3, 5, 7-Tetrazocane-based Nanocomposites

A new insensitive explosive based on octahydro-1, 3, 5, 7-tetranitro-1, 3, 5, 7-tetrazocine (HMX) was prepared by spray drying using Viton A as a binder. The HMX sample without binder (HMX-1) was obtained by the same spray drying process also. The samples were characterised by Scanning Electron Microscope, and X-ray diffraction. The Differential Scanning Calorimetry and the impact sensitivity of HMX-1 and nanocomposites were also being tested. The nanocomposite morphology was found to be microspherical (1 μm to 7 μm diameter) and composed of many tiny particles, 100 nm to 200 nm in size. The crystal type of HMX-1 and HMX/Viton A agrees with raw HMX. The activation energy of raw HMX, HMX-1 and HMX/Viton A is 523.16 kJ mol-1, 435.74 kJ mol-1 and 482.72 kJ mol-1, respectively. The self-ignition temperatures of raw HMX, HMX-1 and HMX/Viton A is 279.01 °C, 277.63 °C, and 279.34 °C, respectively. The impact sensitivity order of samples is HMX/Viton A < HMX-1 < raw HMX from low to high.Defence Science Journal, Vol. 65, No. 2, March 2015, pp.131-134, DOI:http://dx.doi.org/10.14429/dsj.65.784

Prospects of Searching for Type Ia Supernovae with 2.5-m Wide Field Survey Telescope

Type Ia Supernovae (SNe Ia) are the thermonuclear explosion of a carbon-oxygen white dwarf (WD) and are well-known as a distance indicator. However, it is still unclear how WDs increase their mass near the Chandrasekhar limit and how the thermonuclear runaway happens. The observational clues associated with these open questions, such as the photometric data within hours to days since the explosion, are scarce. Thus, an essential way is to discover SNe Ia at specific epochs with optimal surveys. The 2.5-m Wide Field Survey Telescope (WFST) is an upcoming survey facility deployed in western China. In this paper, we assess the detecability of SNe Ia with mock observations of WFST. Followed by the volumetric rate, we generate a spectral series of SNe Ia based on a data-based model and introduce the line-of-sight extinction to calculate the brightness from the observer. By comparing with the detection limit of WFST, which is affected by the observing conditions, we can count the number of SNe Ia discovered by mock WFST observations. We expect that WFST can find more than $3.0\times10^{4}$ pre-maximum SNe Ia within one-year running. In particular, WFST could discover about 45 bright SNe Ia, 99 early-phase SNe Ia, or $1.1\times10^{4}$ well-observed SNe Ia with the hypothesized Wide, Deep, or Medium mode, respectively, suggesting WFST will be an influential facility in time-domain astronomy.Comment: Accepted by Univers

Emulating Complex Synapses Using Interlinked Proton Conductors

In terms of energy efficiency and computational speed, neuromorphic electronics based on non-volatile memory devices is expected to be one of most promising hardware candidates for future artificial intelligence (AI). However, catastrophic forgetting, networks rapidly overwriting previously learned weights when learning new tasks, remains as a pivotal hurdle in either digital or analog AI chips for unleashing the true power of brain-like computing. To address catastrophic forgetting in the context of online memory storage, a complex synapse model (the Benna-Fusi model) has been proposed recently[1], whose synaptic weight and internal variables evolve following a diffusion dynamics. In this work, by designing a proton transistor with a series of charge-diffusion-controlled storage components, we have experimentally realized the Benna-Fusi artificial complex synapse. The memory consolidation from coupled storage components is revealed by both numerical simulations and experimental observations. Different memory timescales for the complex synapse are engineered by the diffusion length of charge carriers, the capacity and number of coupled storage components. The advantage of the demonstrated complex synapse in both memory capacity and memory consolidation is revealed by neural network simulations of face familiarity detection. Our experimental realization of the complex synapse suggests a promising approach to enhance memory capacity and to enable continual learning.Comment: 6 figure

New cell separation technique for the isolation and analysis of cells from biological mixtures in forensic caseworks

Aim To isolate mucosal cells of the perpetrator in a sexual assault case from a complex mixture of his mucosal cells and the victim’s skin by micromanipulation prior to genomic analysis. Methods To capture and analyze mucosal cells we used the micromanipulation with on-chip low volume polymerase chain reaction (LV-PCR). Consensus DNA profiles were generated from 5 replicate experiments. Results and conclusions We validated the use of micromanipulation with on-chip LV-PCR for genomic analysis of complex biological mixtures in a fatal rape case. The perpetrator’s mucosal cells were captured from nipple swabs of the victim, and a single-source DNA profile was generated from cell mixtures. These data suggest that micromanipulation with on-chip LV-PCR is an effective forensic tool for the analysis of specific cells from complex samples

Role of a Genetic Variant on the 15q25.1 Lung Cancer Susceptibility Locus in Smoking-Associated Nasopharyngeal Carcinoma

Background: The 15q25.1 lung cancer susceptibility locus, containing CHRNA5, could modify lung cancer susceptibility and multiple smoking related phenotypes. However, no studies have investigated the association between CHRNA5 rs3841324, which has been proven to have the highest association with CHRNA5 mRNA expression, and the risk of other smoking-associated cancers, except lung cancer. In the current study we examined the association between rs3841324 and susceptibility to smoking-associated nasopharyngeal carcinoma (NPC). Methods: In this case-control study we genotyped the CHRNA5 rs3841324 polymorphism with 400 NPC cases and 491 healthy controls who were Han Chinese and frequency-matched by age (±5 years), gender, and alcohol consumption. Univariate and multivariate logistic regression analyses were used to calculate the odds ratio (OR) and 95% confidence intervals (95% CI)

Green investment decisions in supply chains: a game model with complete information

Prior literature on a two-level supply chain has mainly focused on the game between one manufacturer and one supplier. Exploring group game behavior in a green supply chain (GSC), our research develops and studies a sequential GSC game model consisting of a single manufacturer and three suppliers based on the characteristics of the textile and apparel industry clusters. In our GSC model, the manufacturer is the leader of the supply chain and the suppliers are either homogeneous or complementary. Through equilibrium analysis, we identify critical conditions that influence the behavior of the manufacturer and suppliers to improve the green investment in the supply chain. Our study provides a theoretical basis and a decision-making reference for promoting the cooperation in GSCs and improving the performance of the government’s environmental policies