Design and standalone characterisation of a capacitively coupled HV-CMOS sensor chip for the CLIC vertex detector

The concept of capacitive coupling between sensors and readout chips is under study for the vertex detector at the proposed high-energy CLIC electron positron collider. The CLICpix Capacitively Coupled Pixel Detector (C3PD) is an active High-Voltage CMOS sensor, designed to be capacitively coupled to the CLICpix2 readout chip. The chip is implemented in a commercial $180$ nm HV-CMOS process and contains a matrix of $128\times128$ square pixels with $25$ $\mu$m pitch. First prototypes have been produced with a standard resistivity of $\sim20$ $\Omega$cm for the substrate and tested in standalone mode. The results show a rise time of $\sim20$ ns, charge gain of $190$ mV/ke$^{-}$ and $\sim40$ e$^{-}$ RMS noise for a power consumption of $4.8$ $\mu$W/pixel. The main design aspects, as well as standalone measurement results, are presented.Comment: 13 pages, 13 figures, 2 tables. Work carried out in the framework of the CLICdp collaboratio

Variational Deep Semantic Hashing for Text Documents

As the amount of textual data has been rapidly increasing over the past decade, efficient similarity search methods have become a crucial component of large-scale information retrieval systems. A popular strategy is to represent original data samples by compact binary codes through hashing. A spectrum of machine learning methods have been utilized, but they often lack expressiveness and flexibility in modeling to learn effective representations. The recent advances of deep learning in a wide range of applications has demonstrated its capability to learn robust and powerful feature representations for complex data. Especially, deep generative models naturally combine the expressiveness of probabilistic generative models with the high capacity of deep neural networks, which is very suitable for text modeling. However, little work has leveraged the recent progress in deep learning for text hashing. In this paper, we propose a series of novel deep document generative models for text hashing. The first proposed model is unsupervised while the second one is supervised by utilizing document labels/tags for hashing. The third model further considers document-specific factors that affect the generation of words. The probabilistic generative formulation of the proposed models provides a principled framework for model extension, uncertainty estimation, simulation, and interpretability. Based on variational inference and reparameterization, the proposed models can be interpreted as encoder-decoder deep neural networks and thus they are capable of learning complex nonlinear distributed representations of the original documents. We conduct a comprehensive set of experiments on four public testbeds. The experimental results have demonstrated the effectiveness of the proposed supervised learning models for text hashing.Comment: 11 pages, 4 figure

In-Space Propulsion, Logistics Reduction, and Evaluation of Steam Reformer Kinetics: Problems and Prospects

Human space missions generate waste materials. A 70-kg crewmember creates a waste stream of 1 kg per day, and a four-person crew on a deep space habitat for a 400+ day mission would create over 1600 kg of waste. Converted into methane, the carbon could be used as a fuel for propulsion or power. The NASA Advanced Exploration Systems (AES) Logistics Reduction and Repurposing (LRR) project is investing in space resource utilization with an emphasis on repurposing logistics materials for useful purposes and has selected steam reforming among many different competitive processes as the preferred method for repurposing organic waste into methane. Already demonstrated at the relevant processing rate of 5.4 kg of waste per day, high temperature oxygenated steam consumes waste and produces carbon dioxide, carbon monoxide, and hydrogen which can then be converted into methane catalytically. However, the steam reforming process has not been studied in microgravity. Data are critically needed to understand the mechanisms that allow use of steam reforming in a reduced gravity environment. This paper reviews the relevant literature, identifies gravity-dependent mechanisms within the steam gasification process, and describes an innovative experiment to acquire the crucial kinetic information in a small-scale reactor specifically designed to operate within the requirements of a reduced gravity aircraft flight. The experiment will determine if the steam reformer process is mass-transport limited, and if so, what level of forced convection will be needed to obtain performance comparable to that in 1-g

Green Aerospace Fuels from Nonpetroleum Sources

Efforts to produce green aerospace propellants from nonpetroleum sources are outlined. The paper begins with an overview of feedstock processing and relevant small molecule or C1 chemistry. Gas-to-liquid technologies, notably Fischer-Tropsch (FT) processing of synthesis gas (CO and H2), are being optimized to enhance the fraction of product stream relevant to aviation (and other transportation) fuels at the NASA Glenn Research Center (GRC). Efforts to produce optimized catalysts are described. Given the high cost of space launch, the recycling of human metabolic and plastic wastes to reduce the need to transport consumables to orbit to support the crew of a space station has long been recognized as a high priority. If the much larger costs of transporting consumables to the Moon or beyond are taken into account, the importance of developing waste recycling systems becomes still more imperative. One promising way to transform organic waste products into useful gases is steam reformation; this well-known technology is currently being optimized by a Colorado company for exploration and planetary surface operations. Reduction of terrestrial waste streams while producing energy and/or valuable raw materials is an opportunity being realized by a new generation of visionary entrepreneurs. A technology that has successfully demonstrated production of fuels and related chemicals from waste plastics developed in Northeast Ohio is described. Technologies being developed by a Massachusetts company to remove sulfur impurities are highlighted. Common issues and concerns for nonpetroleum fuel production are emphasized. Energy utilization is a concern for production of fuels whether a terrestrial operation or on the lunar (or Martian) surface; the term green relates to not only mitigating excess carbon release but also to the efficiency of grid-energy usage. For space exploration, energy efficiency can be an essential concern. Other issues of great concern include minimizing impurities in the product stream(s), especially those that potential health risks and/or could degrade operations through catalyst poisoning or equipment damage. The potential impacts on future missions by such concerns are addressed in closing

One-carbon metabolism in cancer

Cells require one-carbon units for nucleotide synthesis, methylation and reductive metabolism, and these pathways support the high proliferative rate of cancer cells. As such, anti-folates, drugs that target one-carbon metabolism, have long been used in the treatment of cancer. Amino acids, such as serine are a major one-carbon source, and cancer cells are particularly susceptible to deprivation of one-carbon units by serine restriction or inhibition of de novo serine synthesis. Recent work has also begun to decipher the specific pathways and sub-cellular compartments that are important for one-carbon metabolism in cancer cells. In this review we summarise the historical understanding of one-carbon metabolism in cancer, describe the recent findings regarding the generation and usage of one-carbon units and explore possible future therapeutics that could exploit the dependency of cancer cells on one-carbon metabolism

Enhanced TiO2 Photocatalytic Processing of Organic Wastes for Green Space Exploration

The effect of transition metal co-catalysts on the photocatalytic properties of TiO2 was investigated. Ruthenium (Ru), palladium, platinum, copper, silver, and gold, were loaded onto TiO2 powders (anatase and mixed-phase P25) and screened for the decomposition of rhodamine B (RhB) under broad-band irradiation. The morphology and estimated chemical composition of photocatalysts were determined by scanning electron microscopy and energy dispersive spectroscopy, respectively. Brunhauer, Emmett and Teller (BET) analysis measured mass-specific surface area(s). X-ray diffraction analysis was performed to confirm the identity of titania phase(s) present. The BET surface area of anatase TiO2/Ru 1% (9.2 sq m/gm) was one of the highest measured of all photocatalysts prepared in our laboratory. Photolyses conducted under air-saturated and nitrogen-saturated conditions revealed photodegradation efficiencies of 85 and 2 percent, respectively, after 60 min compared to 58 percent with no catalyst. The cause of low photocatalytic activity under an inert atmosphere is discussed. TiO2/Ru 1% showed a superior photocatalytic activity relative to P25-TiO2 under broad-band irradiation. A potential deployment of photocatalytic technologies on a mission could be a reactor with modest enhancement in solar intensity brought about by a trough-style reactor, with reactants and catalyst flowing along the axis of the trough and therefore being illuminated for a controlled duration based on the flow rate

Mouse Models of Food Allergy in the Pursuit of Novel Treatment Modalities

The prevalence of IgE-mediated food allergies has increased dramatically in the past three decades, now affecting up to 10% of the US population. IgE-mediated food allergy is an immunologic disease, involving a variety of cells, including B and T cells, mast cells, basophils, ILC2s, and epithelial cells. Mouse models of food allergy mimic the overall immunologic processes known to exist in humans. Due to the limitations of invasive sampling of human tissue and the similarities of the human and mouse immune systems, comprehensive pathogenesis studies of food allergy have been performed in mouse models. Mouse models have been effective in elucidating the roles of non-oral routes of sensitization and identifying key cells and molecules involved in allergic sensitization. Furthermore, the development of novel therapeutic approaches for food allergy has been accelerated through the use of pre-clinical mouse models. Despite the groundbreaking findings stemming from research in mice, there are continued efforts to improve the translational utility of these models. Here, we highlight the achievements in understanding food allergy development and efforts to bring novel treatment approaches into clinical trials

Evolution of Immune Responses in Food Immunotherapy

Food allergies are a growing public health concern affecting approximately 8% of children and 10% of adults in the United States. Several immunotherapy approaches are under active investigation, including oral immunotherapy, epicutaneous immunotherapy, and sublingual immunotherapy. Each of these approaches uses a similar strategy of administering small, increasing amounts of allergen to the allergic subject. Immunologic studies have described changes in the T-cell compartment, serum and salivary immunoglobulin profile, and mast cell and basophil degranulation status in response to allergens. This review highlights the immunologic changes induced by food allergen-specific immunotherapy and discusses future directions in this field

Infrastructure for Detector Research and Development towards the International Linear Collider

The EUDET-project was launched to create an infrastructure for developing and testing new and advanced detector technologies to be used at a future linear collider. The aim was to make possible experimentation and analysis of data for institutes, which otherwise could not be realized due to lack of resources. The infrastructure comprised an analysis and software network, and instrumentation infrastructures for tracking detectors as well as for calorimetry.Comment: 54 pages, 48 picture