Bio-inspired materials to control and minimise insect attachment

More than three quarters of all animal species on Earth are insects, successfully inhabiting most ecosystems on the planet. Due to their opulence, insects provide the backbone of many biological processes, but also inflict adverse impacts on agricultural and stored products, buildings and human health. To countermeasure insect pests, the interactions of these animals with their surroundings have to be fully understood. This review focuses on the various forms of insect attachment, natural surfaces that have evolved to counter insect adhesion, and particularly features recently developed synthetic bio-inspired solutions. These bio-inspired solutions often enhance the variety of applicable mechanisms observed in nature and open paths for improved technological solutions that are needed in a changing global society

Modelling the behaviour of microbulk Micromegas in Xenon/trimethylamine gas

We model the response of a state of the art micro-hole single-stage charge amplication device (`microbulk' Micromegas) in a gaseous atmosphere consisting of Xenon/trimethylamine at various concentrations and pressures. The amplifying structure, made with photo-lithographic techniques similar to those followed in the fabrication of gas electron multipliers (GEMs), consisted of a 100 um-side equilateral-triangle pattern with 50 um-diameter holes placed at its vertexes. Once the primary electrons are guided into the holes by virtue of an optimized field configuration, avalanches develop along the 50 um-height channels etched out of the original doubly copper-clad polyimide foil. In order to properly account for the strong field gradients at the holes' entrance as well as for the fluctuations of the avalanche process (that ultimately determine the achievable energy resolution), we abandoned the hydrodynamic framework, resorting to a purely microscopic description of the electron trajectories as obtained from elementary cross-sections. We show that achieving a satisfactory description needs additional assumptions about atom-molecule (Penning) transfer reactions and charge recombination to be made

Improved induction of anti-melanoma T cells by adenovirus-5/3 fiber modification to target human DCs

To mount a strong anti-tumor immune response, non T cell inflamed (cold) tumors may require combination treatment encompassing vaccine strategies preceding checkpoint inhibition. In vivo targeted delivery of tumor-associated antigens (TAA) to dendritic cells (DCs), relying on the natural functions of primary DCs in situ, represents an attractive vaccination strategy. In this study we made use of a full-length MART-1 expressing C/B-chimeric adenoviral vector, consisting of the Ad5 capsid and the Ad3 knob (Ad5/3), which we previously showed to selectively transduce DCs in human skin and lymph nodes. Our data demonstrate that chimeric Ad5/3 vectors encoding TAA, and able to target human DCs in situ, can be used to efficiently induce expansion of functional tumor-specific CD8⁺ effector T cells, either from a naïve T cell pool or from previously primed T cells residing in the melanoma-draining sentinel lymph nodes (SLN). These data support the use of Ad3-knob containing viruses as vaccine vehicles for in vivo delivery. "Off-the-shelf" DC-targeted Ad vaccines encoding TAA could clearly benefit future immunotherapeutic approaches

Micromegas detector developments for MIMAC

The aim of the MIMAC project is to detect non-baryonic Dark Matter with a directional TPC. The recent Micromegas efforts towards building a large size detector will be described, in particular the characterization measurements of a prototype detector of 10 $\times$ 10 cm$^2$ with a 2 dimensional readout plane. Track reconstruction with alpha particles will be shown.Comment: 8 pages, 7 figures Proceedings of the 3rd International conference on Directional Detection of Dark Matter (CYGNUS 2011), Aussois, France, 8-10 June 2011; corrections on author affiliation

Privacy Preserving and Time Series Analysis of Medical Dataset using Deep Feature Selection

A significant category of medical data that includes rich temporal and spatial information is time-series medical imaging. Since then, experts in a variety of domains, including clinical picture analysis, have been actively participating in the rapidly emerging subject of profound learning. This paper discusses profound learning processes and their applicability to clinical picture examination and mainly focused common machine learning techniques in the field of computer vision and how deep learning has transformed ML, ML models for deep learning and applications of deep learning to clinical image analysis. In fact, even before the term "deep learning" was coined, a variety of clinical picture investigation concerns, including harm and non-harm grouping, harm type characterisation, harm or organ division, and injury recognition, were addressed using picture input machine learning (PIML). Deep learning is predicted to be the key innovation for clinical picture examination in the upcoming few years. Picture input ML, including profound learning, is an exceptionally powerful, flexible, higher-throughput innovation that can raise the current level of execution in clinical picture examination. "Profound learning" or picture input ML, in clinical picture examination is a quickly developing, promising field. Picture input ML is supposed to turn into a significant field in clinical picture examination in the following couple of many years

The Impact of Differences Planting Date Against Morphological Characters of Some Wheat Genotype in Berastagi of Karo District

Optimal planting date is one of the important factors affecting the wheat crop. Improper planting date can lead to a drastic decrease in wheat yield. Therefore, information about the adaptation of wheat plants at planting date at a particular location will benefit farmers in determining how best to utilize the wheat plants in each production system through morphological characters. Then conducted research The Impact of Differences Planting date against Morphology Character of some Wheat Genotypes in Berastagi of Karo district to determine the most appropriate wheat genotypes grown in Berastagi at certain times growing season through morphological characters. This research was conducted at Berastagi with two planting date (planting date I = late February to early June 2012 and planting date II = late October 2012 to early February 2013), using a Randomized Block Design (RBD) non factorial using 12 wheat plant,namely 2 varieties (Selayar / K and Dewata / L) and 10 genotypes that OASIS / SKAUZ / / 4 * BCN (A); HP1744 (B); LAJ3302 / 2 * MO88 (C); RABE / 2 * MO88 (D), H-21 (E), G-21 (F), G-18 (G); MENEMEN (H); BASRIBEY (I); ALIBEY (J). Observational data were tested with analysis of variance and combined analysis.The observed morphological characters were plant height, number of spikelet spike-1, number of grainspike-1 and grain weight spike-1. The results of analysis of variance and combined analysis showed that all parameters were observed give significantly different results for each planting date

Cyan-Emitting Cu(I) Complexes and Their Luminescent Metallopolymers

Copper complexes have shown great versatility and a wide application range across the natural and life sciences, with a particular promise as organic light-emitting diodes. In this work, four novel heteroleptic Cu(I) complexes were designed in order to allow their integration in advanced materials such as metallopolymers. We herein present the synthesis and the electrochemical and photophysical characterisation of these Cu(I) complexes, in combination with ab initio calculations. The complexes present a bright cyan emission (λem ~ 505 nm) in their solid state, both as powder and as blends in a polymer matrix. The successful synthesis of metallopolymers embedding two of the novel complexes is shown. These copolymers were also found to be luminescent and their photophysical properties were compared to those of their polymer blends. The chemical nature of the polymer backbone contributes significantly to the photoluminescence quantum yield, paving a route for the strategic design of novel luminescent Cu(I)-based polymeric materials

TREX-DM: a low background Micromegas-based TPC for low mass WIMP detection

Dark Matter experiments are recently focusing their detection techniques in low-mass WIMPs, which requires the use of light elements and low energy threshold. In this context, we present the TREX-DM experiment, a low background Micromegas-based TPC for low-mass WIMP detection. Its main goal is the operation of an active detection mass $\sim$0.300 kg, with an energy threshold below 0.4 keVee and fully built with previously selected radiopure materials. This article describes the actual setup, the first results of the comissioning in Ar+2\%iC$_4$H$_{10}$ at 1.2 bar and the future updates for a possible physics run at the Canfranc Underground Laboratory in 2016. A first background model is also presented, based on Geant4 simulations and a muon/electron discrimination method. In a conservative scenario, TREX-DM could be sensitive to DAMA/LIBRA and other hints of positive WIMPs signals, with some space for improvement with a neutron/electron discrimination method or the use of other light gases.Comment: Proceedings of the 7th Symposium on Large TPCs for Low-Energy Rare Event Detectio