From amines to (form)amides: a simple and successful mechanochemical approach

Two easily accessible routes for preparing an array of formylated and acetylated amines under mechanochemical conditions are presented. The two methodologies exhibit complementary features as they enable the derivatization of aliphatic and aromatic amines

Negative Energy Modes and Gravitational Instability of Interpenetrating Fluids

We study the longitudinal instabilities of two interpenetrating fluids interacting only through gravity. When one of the constituents is of relatively low density, it is possible to have a band of unstable wave numbers well separated from those involved in the usual Jeans instability. If the initial streaming is large enough, and there is no linear instability, the indefinite sign of the free energy has the possible consequence of explosive interactions between positive and negative energy modes in the nonlinear regime. The effect of dissipation on the negative energy modes is also examined

STZ-diabetic rat heart maintains developed tension amplitude by increasing sarcomere length and crossbridge density

New Findings: What is the central question of this study? In the papillary muscle from type I diabetic rats, does diabetes-associated altered ventricular function result from changes of acto-myosin interactions and are these modifications attributable to a possible sarcomere rearrangement? What is the main finding and its importance? For the first time, we showed that type-I diabetes altered sarcomeric ultrastructure, as seen by transmission electron microscopy, consistent with physiological parameters. The diabetic condition induced slower timing parameters, which is compatible with a diastolic dysfunction. At the sarcomeric level, augmented β-myosin heavy chain content and increased sarcomere length and crossbridges' number preserve myocardial stroke and could concur to maintain the ejection fraction. Abstract: We investigated whether diabetes-associated altered ventricular function, in a type I diabetes animal model, results from a modification of acto-myosin interactions, through the in vitro recording of left papillary muscle mechanical parameters and examination of sarcomere morphology by transmission electron microscopy (TEM). Experiments were performed on streptozotocin-induced diabetic and age-matched control female Wistar rats. Mechanical isometric and isotonic indexes and timing parameters were determined. Using Huxley's equations, we calculated mechanics, kinetics and energetics of myosin crossbridges. Sarcomere length and A-band length were measured on TEM images. Type I and III collagen and β-myosin heavy chain (MHC) expression were determined by immunoblotting. No variation in resting and developed tension or maximum extent of shortening was evident between groups, but diabetic rats showed lower maximum shortening velocity and prolonged timing parameters. Compared to controls, diabetics also displayed a higher number of crossbridges with lower unitary force. Moreover, no change in type I and III collagen was associated to diabetes, but pathological rats showed a two-fold enhancement of β-MHC content and longer sarcomeres and A-band, detected by ultrastructural morphometry. Overall, these data address whether a preserved systolic function accompanied by an altered diastolic phase results from a recruitment of super-relaxed myosin heads or the phosphorylation of the regulatory light chain site in myosin. Although the early signs of diabetic cardiomyopathy were well expressed, the striking finding of our study was that, in diabetics, sarcomere modification may be a possible compensatory mechanism that preserves systolic function

How is stimulus processing of the lateral geniculate nucleus derived from its input(s)?

LGN neurons can respond with extreme precision to a variety of temporally varying stimuli [1]. This precision requires non-linear processing of the stimulus and therefore cannot be described by standard linear (or linear-non-linear, LN) models. Rather, in previous work, we have found that precision arises through the interplay of an excitatory receptive field and a similarly tuned – but delayed – suppressive receptive field, allowing for fine time scales in the LGN response to arise in the brief window where excitation exceeds the suppression [2]. However, it is not clear whether such non-linear interaction arises in the retina, at the retinogeniculate synapse itself or involves other secondary LGN inputs. To investigate this, we applied a newly developed a Generalized Non-Linear Modeling (GNLM) framework to data involving the simultaneous recording of LGN neurons and their predominant retinal ganglion cell (RGC) input. This framework uses efficient maximum-likelihood optimization [3], adapted to include nested non-linear terms [2, 4]. Using this novel approach, we simultaneously optimize the shape of postsynaptic currents resulting from RGC stimulation along with other non-linear excitatory and inhibitory elements tuned to the visual stimulus, based on the observed RGC and LGN spike trains alone. We also can directly characterize the non-linear elements in the RGC. We found that while there were subtle non-linear elements in the RGC response, they were amplified in that of the LGN. Consistent with previous reports [5], summation with a threshold explains a large part of the increased sparseness of LGN responses relative to those of the input RGC. However, an additional opposite-sign suppressive term was also present, possibly contributing to the push-pull nature of the LGN response observed in intracellular recordings [6]. In many cases, we also detected additional non-linear excitatory inputs, possibly resulting from other RGC inputs. Interestingly, such additional terms were much more sensitive to contrast than the dominant input, possible resulting in the well-known contrast gain control effects, though present both at the level of the retina and LGN. Thus, the GNLM modeling methods reveal how non-linear computation performed is performed the RG synapse, and allows for more general characterization of non-linear computation throughout the visual pathway.https://doi.org/10.1186/1471-2202-10-S1-P12

Detection of Solar Coronal Mass Ejections from Raw Images with Deep Convolutional Neural Networks

Coronal Mass Ejections (CMEs) are massive releases of plasma from the solar corona. When the charged material is ejected towards the Earth, it can cause geomagnetic storms and severely damage electronic equipment and power grids. Early detection of CMEs is therefore crucial for damage containment. In this paper, we study detection of CMEs from sequential images of the solar corona acquired by a satellite. A low-complexity deep neural network is trained to process the raw images, ideally directly on the satellite, in order to provide early alerts

The Heliospheric Space Weather Center: A novel space weather service

The Heliospheric Space Weather Center project is the result of the synergy between the Aerospace Logistics Technology Engineering Company (ALTEC S.p.A.) and the INAF-Astrophysical Observatory of Torino, both located in Turin, Italy. The main goal of this project is to provide space weather medium and short-term forecast, by combining remote-sensing and in situ open data with novel data analysis technologies, giving to scientists the possibility of designing, implementing, and validating space-weather algorithms using extensive data sets

Towards Autopoietic Computing

A key challenge in modern computing is to develop systems that address complex, dynamic problems in a scalable and efficient way, because the increasing complexity of software makes designing and maintaining efficient and flexible systems increasingly difficult. Biological systems are thought to possess robust, scalable processing paradigms that can automatically manage complex, dynamic problem spaces, possessing several properties that may be useful in computer systems. The biological properties of self-organisation, self-replication, self-management, and scalability are addressed in an interesting way by autopoiesis, a descriptive theory of the cell founded on the concept of a system's circular organisation to define its boundary with its environment. In this paper, therefore, we review the main concepts of autopoiesis and then discuss how they could be related to fundamental concepts and theories of computation. The paper is conceptual in nature and the emphasis is on the review of other people's work in this area as part of a longer-term strategy to develop a formal theory of autopoietic computing.Comment: 10 Pages, 3 figure

Computing the Noncomputable

We explore in the framework of Quantum Computation the notion of computability, which holds a central position in Mathematics and Theoretical Computer Science. A quantum algorithm that exploits the quantum adiabatic processes is considered for the Hilbert's tenth problem, which is equivalent to the Turing halting problem and known to be mathematically noncomputable. Generalised quantum algorithms are also considered for some other mathematical noncomputables in the same and of different noncomputability classes. The key element of all these algorithms is the measurability of both the values of physical observables and of the quantum-mechanical probability distributions for these values. It is argued that computability, and thus the limits of Mathematics, ought to be determined not solely by Mathematics itself but also by physical principles.Comment: Extensively revised and enlarged with: 2 new subsections, 4 new figures, 1 new reference, and a short biography as requested by the journal edito

Towards model-based control of Parkinson's disease

Modern model-based control theory has led to transformative improvements in our ability to track the nonlinear dynamics of systems that we observe, and to engineer control systems of unprecedented efficacy. In parallel with these developments, our ability to build computational models to embody our expanding knowledge of the biophysics of neurons and their networks is maturing at a rapid rate. In the treatment of human dynamical disease, our employment of deep brain stimulators for the treatment of Parkinson’s disease is gaining increasing acceptance. Thus, the confluence of these three developments—control theory, computational neuroscience and deep brain stimulation—offers a unique opportunity to create novel approaches to the treatment of this disease. This paper explores the relevant state of the art of science, medicine and engineering, and proposes a strategy for model-based control of Parkinson’s disease. We present a set of preliminary calculations employing basal ganglia computational models, structured within an unscented Kalman filter for tracking observations and prescribing control. Based upon these findings, we will offer suggestions for future research and development

Designing Research

The aim of this chapter is to set out a process that researchers can follow to design a robust quantitative research study of occupant behavior in buildings. Central to this approach is an emphasis on intellectual clarity around what is being measured and why. To help achieve this clarity, researchers are encouraged to literally draw these relationships out in the form of a concept map capturing the theoretical model of the cause and effect between occupant motivations and energy use. Having captured diagrammatically how the system is thought to work, the next step is to formulate research questions or hypotheses capturing the relationship between variables in the theoretical model, and to start to augment the diagram with the measurands (things that can actually be measured) that are good proxies for each concept. Once these are identified, the diagram can be further augmented with one or more methods of measuring each measurand. The chapter argues that it is necessary to carefully define concepts and their presumed relationships, and to clearly state research questions and identify what the researcher intends to measure before starting data collection. The chapter also explains the ideas of reliability, validity, and uncertainty, and why knowledge about them is essential for any researcher