On the Transport Properties of a Quark-Hadron Coulomb Lattice in the Cores of Neutron Stars

Already more that 40 years ago, it has been suggested that because of the enormous mass densities in the cores of neutron stars, the hadrons in the centers of neutron stars may undergo a phase transition to deconfined quark matter. In this picture, neutron stars could contain cores made of pure (up, down, strange) quark matter which are surrounded by a mixed phase of quarks and hadrons. More than that, because of the competition between the Coulomb and the surface energies associated with the positively charged regions of nuclear matter and negatively charged regions of quark matter, the mixed phase may develop geometrical structures, similarly to what is expected of the sub-nuclear liquid-gas phase transition. In this paper we restrict ourselves to considering the formation of rare phase blobs in the mixed quark-hadron phase. The influence of rare phase blobs on the thermal and transport properties of neutron star matter is investigated. The total specific heat, $c_V$, thermal conductivity, $\kappa$, and electron-blob Bremsstrahlung neutrino emissivities, $\epsilon_{\nu,\text{BR}}$, of quark-hybrid matter are computed and the results are compared with the associated thermal and transport properties of standard neutron star matter. Our results show that the contribution of rare phase blobs to the specific heat is negligibly small. This is different for the neutrino emissivity from electron-blob Bremsstrahlung scattering, which turns out to be of the same order of magnitude as the total contributions from other Bremsstrahlung processes for temperatures below about $10^8$ K.Comment: minor changes, accepted by Phys. Rev.

Neutron star envelopes and thermal radiation from the magnetic surface

The thermal structure of neutron star envelopes is discussed with emphasis on analytic results. Recent progress on the effect of chemical constitution and high magnetic fields on the opacities and the thermal structure is further reviewed in view of the application to pulsar cooling and magnetars

Optogenetics in silicon: A neural processor for predicting optically active neural networks

We present a reconfigurable neural processor for real-time simulation and prediction of opto-neural behaviour. We combined a detailed Hodgkin-Huxley CA3 neuron integrated with a four-state Channelrhodopsin-2 (ChR2) model into reconfigurable silicon hardware. Our architecture consists of a Field Programmable Gated Array (FPGA) with a custom-built computing data-path, a separate data management system and a memory approach based router. Advancements over previous work include the incorporation of short and long-term calcium and light-dependent ion channels in reconfigurable hardware. Also, the developed processor is computationally efficient, requiring only 0.03 ms processing time per sub-frame for a single neuron and 9.7 ms for a fully connected network of 500 neurons with a given FPGA frequency of 56.7 MHz. It can therefore be utilized for exploration of closed loop processing and tuning of biologically realistic optogenetic circuitry

Effect of Cu and Sn promotion on the catalytic deoxygenation of model and algal lipids to fuel-like hydrocarbons over supported Ni catalysts

The ability of Cu and Sn to promote the performance of a 20% Ni/Al2O3 catalyst in the deoxygenation of lipids to fuel-like hydrocarbons was investigated using model triglyceride and fatty acid feeds, as well as algal lipids. In the semi-batch deoxygenation of tristearin at 260 °C a pronounced promotional effect was observed, a 20% Ni-5% Cu/Al2O3 catalyst affording both higher conversion (97%) and selectivity to C10-C17 alkanes (99%) in comparison with unpromoted 20% Ni/Al2O3 (27% conversion and 87% selectivity to C10-C17). In the same reaction at 350 °C, a 20% Ni-1% Sn/Al2O3 catalyst afforded the best results, giving yields of C10-C17 and C17 of 97% and 55%, respectively, which contrasts with the corresponding values of 87 and 21% obtained over 20% Ni/Al2O3. Equally encouraging results were obtained in the semi-batch deoxygenation of stearic acid at 300 °C, in which the 20% Ni-5% Cu/Al2O3 catalyst afforded the highest yields of C10-C17 and C17. Experiments were also conducted at 260 °C in a fixed bed reactor using triolein − a model unsaturated triglyceride − as the feed. While both 20% Ni/Al2O3 and 20% Ni-5% Cu/Al2O3 achieved quantitative yields of diesel-like hydrocarbons at all reaction times sampled, the Cu-promoted catalyst exhibited higher selectivity to longer chain hydrocarbons, a phenomenon which was also observed in experiments involving algal lipids as the feed. Characterization of fresh and spent catalysts indicates that Cu enhances the reducibility of Ni and suppresses both cracking reactions and coke-induced deactivation

Short-Term Memory Trace in Rapidly Adapting Synapses of Inferior Temporal Cortex

Visual short-term memory tasks depend upon both the inferior temporal cortex (ITC) and the prefrontal cortex (PFC). Activity in some neurons persists after the first (sample) stimulus is shown. This delay-period activity has been proposed as an important mechanism for working memory. In ITC neurons, intervening (nonmatching) stimuli wipe out the delay-period activity; hence, the role of ITC in memory must depend upon a different mechanism. Here, we look for a possible mechanism by contrasting memory effects in two architectonically different parts of ITC: area TE and the perirhinal cortex. We found that a large proportion (80%) of stimulus-selective neurons in area TE of macaque ITCs exhibit a memory effect during the stimulus interval. During a sequential delayed matching-to-sample task (DMS), the noise in the neuronal response to the test image was correlated with the noise in the neuronal response to the sample image. Neurons in perirhinal cortex did not show this correlation. These results led us to hypothesize that area TE contributes to short-term memory by acting as a matched filter. When the sample image appears, each TE neuron captures a static copy of its inputs by rapidly adjusting its synaptic weights to match the strength of their individual inputs. Input signals from subsequent images are multiplied by those synaptic weights, thereby computing a measure of the correlation between the past and present inputs. The total activity in area TE is sufficient to quantify the similarity between the two images. This matched filter theory provides an explanation of what is remembered, where the trace is stored, and how comparison is done across time, all without requiring delay period activity. Simulations of a matched filter model match the experimental results, suggesting that area TE neurons store a synaptic memory trace during short-term visual memory

The modular systems biology approach to investigate the control of apoptosis in Alzheimer's disease neurodegeneration

Apoptosis is a programmed cell death that plays a critical role during the development of the nervous system and in many chronic neurodegenerative diseases, including Alzheimer's disease (AD). This pathology, characterized by a progressive degeneration of cholinergic function resulting in a remarkable cognitive decline, is the most common form of dementia with high social and economic impact. Current therapies of AD are only symptomatic, therefore the need to elucidate the mechanisms underlying the onset and progression of the disease is surely needed in order to develop effective pharmacological therapies. Because of its pivotal role in neuronal cell death, apoptosis has been considered one of the most appealing therapeutic targets, however, due to the complexity of the molecular mechanisms involving the various triggering events and the many signaling cascades leading to cell death, a comprehensive understanding of this process is still lacking. Modular systems biology is a very effective strategy in organizing information about complex biological processes and deriving modular and mathematical models that greatly simplify the identification of key steps of a given process. This review aims at describing the main steps underlying the strategy of modular systems biology and briefly summarizes how this approach has been successfully applied for cell cycle studies. Moreover, after giving an overview of the many molecular mechanisms underlying apoptosis in AD, we present both a modular and a molecular model of neuronal apoptosis that suggest new insights on neuroprotection for this disease

QCD and strongly coupled gauge theories : challenges and perspectives

We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.Peer reviewe