Beersheba, Israel

Ben-Gurion University of the Negev is a university in Beersheba, Israel. Wikipedia.

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The invention relates to a catalyst suitable for use in the hydrogenation of carbon dioxide-containing gas, said catalyst comprising spinel phase of the formula [Fe^(2+)(Fe^(3+)_(y)Al^(3+)_(1-y))_(2)O_(4)]. Processes for preparing the catalyst and processes for the hydrogenation of carbon dioxide-containing gas in the presence of the catalyst are also disclosed.

Ben - Gurion University of the Negev | Date: 2015-02-03

The invention is a system and method that enable obtaining ultra-high resolution interference, phase and OCT images at high speed. The system uses neither mechanical moving elements nor any optical/electro optical modulating means for obtaining the OCT images. Two OCT operating modes are available: for ultra-high resolution the system allows either spatial coherence TD-FF-OCT or temporal coherence TD-FF-OCT imaging, whereas for high resolution and ultra-high speed the system allows FD-FF-OCT imaging with full range imaging. In the TD mode, the OCT enface images are obtained in real time. In the FD mode, the 2D complex signal is reconstructed in real time. In both cases the method has the advantage of very high speed imaging with great immunity to noise.

Bar - Ilan University and Ben - Gurion University of the Negev | Date: 2015-04-30

A gain cell includes a write bit line input, a read bit line output, a write trigger input and a read trigger input. The gain cell also includes a write transistor, retention element and read transistor. Each of the transistors includes a respective first diffusion connection, gate connection and second diffusion connection. The write transistor first diffusion connection is connected to the write bit line input and the write transistor gate connection is connected to the write trigger input. The read transistor first diffusion connection being connected to the read bit line output and the second diffusion connection is connected to the read trigger input. The retention element buffers between write transistor and the read transistor during data retention. The retention element also connects or disconnects a write transistor diffusion connection to/from a constant voltage in accordance with a retained data level at the read transistor gate connection.

Ben - Gurion University of the Negev | Date: 2016-12-13

Dislosed is a device for up-conversion of Short Wavelength Infra-Red (SWIR) images into visible images. The device comprises a sub micrometer thickness structure that is composed of several sub-layers, each having a typical thickness of tens to hundreds of nanometers. The device is composed of two main sections one on top of the other: (a) a highly efficient SWIR absorption thin layer and (b) a highly efficient organic light emitted diode (OLED). The generated visible image is emitted from the OLED through a top transparent cathode, which is deposited on the OLED.

Agency: Cordis | Branch: H2020 | Program: MSCA-ITN-ETN | Phase: MSCA-ITN-2016 | Award Amount: 3.83M | Year: 2017

ES-Cat will use directed evolution as a tool to reproduce Natures remarkable ability to generate molecular machines - in particular enzymes that perform at levels near perfection. Instead of seeing rational and combinatorial approaches as alternatives, we combine them in this network to achieve a smarter and more efficient exploration of protein sequence space. By harnessing the forces of Darwinian evolution and design in the laboratory we want to (i) screen large and diverse libraries for proteins with improved and useful functions, (ii) optimize existing proteins for applications in medicine or biotechnology and (iii) provide a better understanding of how existing enzymes evolved and how enzyme mechanisms can be manipulated. This Network brings together leading academic and industrial groups with diverse and complementary skills. The range of methodologies represented in ES-Cat allows an integrated approach combining in silico structural and sequence analysis with experimental high-throughput screening selection methods (phage-, ribozyme and SNAP display, robotic liquid handling, lab-on-a-chip/microfluidics) with subsequent systematic kinetic and biophysical analysis. This integration of methods and disciplines will improve the likelihood of success of directed evolution campaigns, shorten biocatalyst development times, and make protein engineering applicable to a wider range of industrial targets. It will also train the next generation of creative researchers ready to fill roles in tailoring enzymes and other proteins for industrial application in synthetic biology efforts to move towards a bio-based economy, rivaling advances that are being made in the US and allowing the EU economy to harvest its evident socio-economic benefits.

Agency: Cordis | Branch: H2020 | Program: RIA | Phase: LCE-11-2015 | Award Amount: 5.99M | Year: 2016

WASTE2FUELS aims to develop next generation biofuel technologies capable of converting agrofood waste (AFW) streams into high quality biobutanol. Butanol is one of the most promising biofuels due to its superior fuel properties compared to current main biofuels, bioethanol and biodiesel. In addition to its ability to reduce carbon emissions, its higher energy content (almost 30% more than ethanol), its ability to blend with both gasoline and diesel, its lower risk of separation and corrosion, its resistance to water absorption, allowing it to be transported in pipes and carriers used by gasoline, it offers a very exciting advantage for adoption as engines require almost no modifications to use it. The main WASTE2FUELS innovations include: Development of novel pretreatment methods for converting AFW to an appropriate feedstock for biobutanol production thus dramatically enlarging current available biomass for biofuels production Genetically modified microorganisms for enhancing conversion efficiencies of the biobutanol fermentation process Coupled recovery and biofilm reactor systems for enhancing conversion efficiencies of Acetone-Butanol-Ethanol fermentation Development of new routes for biobutanol production via ethanol catalytic conversion Biobutanol engine tests and ecotoxicological assessment of the produced biobutanol Valorisation of the process by-products Development of an integrated model to optimise the waste-to-biofuel conversion and facilitate the industrial scale-up Process fingerprint analysis by environmental and techno-economic assessment Biomass supply chain study and design of a waste management strategy for rural development By valorising 50% of the unavoidable and undervalorised AFW as feedstock for biobutanol production, WASTE2FUELS could divert up to 45 M tonnes of food waste from EU landfills, preventing 18 M tonnes of GHG and saving almost 0.5 billion litres of fossil fuels.

Alcohol addiction ranks among the primary global causes of preventable death and disabilities in human population, but treatment options are very limited. Rational strategies for design and development of novel, evidence based therapies for alcohol addiction are still missing. Within this project, we will utilize a translational approach based on clinical studies and animal experiments to fill this gap. We will provide a novel discovery strategy based on systems biology concepts that uses mathematical and network theoretical models to identify brain sites and functional networks that can be targeted specifically by therapeutic interventions. To build predictive models of the relapse-prone state of brain networks we will use magnetic resonance imaging and neurochemical data from patients and laboratory animals. The mathematical models will be rigorously tested through experimental procedures aimed to guide network dynamics towards increased resilience. We expect to identify hubs that promote relapse-proneness and to predict how aberrant network states could be normalized. Proof of concept experiments in animal will need to demonstrate this possibility by showing directed remodeling of functional brain networks by targeted interventions prescribed by the theoretical framework. Thus, our translational goal will be achieved by a theoretical and experimental framework for making predictions based on fMRI and mathematical modeling, which is verified in animals, and which can be transferred to humans. To achieve this goal we have assembled an interdisciplinary consortium (eight European countries) of world-class expertise in all complementary skills required for the project. If successful this project will positively impact on the development of new therapies for a disorder with largely unmet clinical needs, and thus help to address a serious and widespread health problem in our societies.

Agency: Cordis | Branch: H2020 | Program: MSCA-ITN-ETN | Phase: MSCA-ITN-2016 | Award Amount: 3.87M | Year: 2016

SOCRATES is a PhD training program for 15 young researchers, created to develop the field of Social Robotics with an application focus on Robotics in Eldercare. The research in Social Robotics has a common theme of Interaction Quality, which is a concept for characterization of how a specific mode of interaction is fit for a given task, situation, and user. Interaction Quality often changes, for instance if an older adult gets tired and loses focus when interacting with a robot. Interaction Quality also depends on the robots functionality and design, and will be addressed from a range of perspectives in five research workpackages: Emotion: novel multi-modal methods to perceive human emotions from facial expressions, body motion, auditory and language cues Intention: new techniques to infer human goals and intention from natural language and video analysis Adaptivity: techniques to adapt a robots behaviour to user needs Design: Novel design methods for hardware, interfaces, and safety Acceptance: Procedures for evaluation of user acceptance Additional value and impact is generated by the unique multidisciplinary collaboration between academic disciplines that normally do not work together; computer science, cognitive science, biomechanics, ethics, social psychology, and social science. Intersectoral collaboration between academia, caregivers, business developers, and robot manufacturers will further strengthen novelty and impact by ensuring that relevant needs are addressed, and that research result are both economically and technically feasible. The outcome of SOCRATES will be a new generation of researchers with the ability to interact with scholars from different schools-of-thought in areas that are well within as well as outside of their areas of expertise.

Yagupsky P.,Ben - Gurion University of the Negev
Clinical Microbiology Reviews | Year: 2015

Kingella kingae is a common etiology of pediatric bacteremia and the leading agent of osteomyelitis and septic arthritis in children aged 6 to 36 months. This Gram-negative bacterium is carried asymptomatically in the oropharynx and disseminates by close interpersonal contact. The colonized epithelium is the source of bloodstream invasion and dissemination to distant sites, and certain clones show significant association with bacteremia, osteoar-thritis, or endocarditis. Kingella kingae produces an RTX (repeatin-toxin) toxin with broad-spectrum cytotoxicity that probably facilitates mucosal colonization and persistence of the organism in the bloodstream and deep body tissues. With the exception of patients with endocardial involvement, children with K. kingae diseases often show only mild symptoms and signs, necessitating clinical acumen. The isolation of K. kingae on routine solid media is suboptimal, and detection of the bacterium is significantly improved by inoculating exudates into blood culture bottles and the use of PCR-based assays. The organism is generally susceptible to antibiotics that are administered to young patients with joint and bone infections. β-Lactamase production is clonal, and the local prevalence of β-lactamase-producing strains is variable. If adequately and promptly treated, invasive K. kingae infections with no endocardial involvement usually run a benign clinical course. © 2015, American Society for Microbiology. All Rights Reserved.

Shamir M.,Ben - Gurion University of the Negev
Current Opinion in Neurobiology | Year: 2014

Population coding theory aims to provide quantitative tests for hypotheses concerning the neural code. Over the last two decades theory has focused on analyzing the ways in which various parameters that characterize neuronal responses to external stimuli affect the information content of these responses. This article reviews and provides an intuitive explanation for the major effects of noise correlations and neuronal heterogeneity, and discusses their implications for our ability to investigate the neural code. It is argued that to test neural code hypotheses further, additional constraints are required, including relating trial-to-trial variation in neuronal population responses to behavioral decisions and specifying how information is decoded by downstream networks. © 2014 Elsevier Ltd.

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