Image informatics strategies for deciphering neuronal network connectivity

Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

Molecular-Level Switching of Polymer/Nanocrystal Non-Covalent Interactions and Application in Hybrid Solar Cells

Hy brid composites obtained upon blending conjugated polymers and colloidal inorganic semiconductor nanocrystals are regarded as attractive photo-active materials for optoelectronic applications. Here we demonstrate that tailoring nanocrystal surface chemistry permits to exert control on non-covalent bonding and electronic interactions between organic and inorganic components. The pendant moieties of organic ligands at the nanocrystal surface do not merely confer colloidal stability while hindering charge separation and transport, but drastically impact morphology of hybrid composites during formation from blend solutions. The relevance of our approach to photovoltaic applications is demonstrated for composites based on poly(3-hexylthiophene) and Pbs nanocrystals, considered as inadequate before the submission of this manuscript, which enable the fabrication of hybrid solar cells displaying a power conversion efficiency that reaches 3 %. Upon (quasi)steady-state and time-resolved analisys of the photo-induced processes in the nanocomposites and their organic and inorganic components, we ascertained that electron transfer occurs at the hybrid interface yielding long-lived separated charge carriers, whereas interfacial hole transfer appears slow. Here we provide a reliable alternative aiming at gaining control over macroscopic optoelectronic properties of polymer/nanocrystal composites by acting at the molecular-level via ligands' pendant moieties, thus opening new possibilities towards efficient solution-processed hybrid solar cells

Surface-to-Bulk Redox Coupling through Thermally Driven Li Redistribution in Li- and Mn-Rich Layered Cathode Materials.

Li- and Mn-rich (LMR) layered cathode materials have demonstrated impressive capacity and specific energy density thanks to their intertwined redox centers including transition metal cations and oxygen anions. Although tremendous efforts have been devoted to the investigation of the electrochemically driven redox evolution in LMR cathode at ambient temperature, their behavior under a mildly elevated temperature (up to ∼100 °C), with or without electrochemical driving force, remains largely unexplored. Here we show a systematic study of the thermally driven surface-to-bulk redox coupling effect in charged Li1.2Ni0.15Co0.1Mn0.55O2. We for the first time observed a charge transfer between the bulk oxygen anions and the surface transition metal cations under ∼100 °C, which is attributed to the thermally driven redistribution of Li ions. This finding highlights the nonequilibrium state and dynamic nature of the LMR material at deeply delithiated state upon a mild temperature perturbation

The acousto-ultrasonic approach

The nature and underlying rationale of the acousto-ultrasonic approach is reviewed, needed advanced signal analysis and evaluation methods suggested, and application potentials discussed. Acousto-ultrasonics is an NDE technique combining aspects of acoustic emission methodology with ultrasonic simulation of stress waves. This approach uses analysis of simulated stress waves for detecting and mapping variations of mechanical properties. Unlike most NDE, acousto-ultrasonics is less concerned with flaw detection than with the assessment of the collective effects of various flaws and material anomalies. Acousto-ultrasonics has been applied chiefly to laminated and filament-wound fiber reinforced composites. It has been used to assess the significant strength and toughness reducing effects that can be wrought by combinations of essentially minor flaws and diffuse flaw populations. Acousto-ultrasonics assesses integrated defect states and the resultant variations in properties such as tensile, shear, and flexural strengths and fracture resistance. Matrix cure state, porosity, fiber orientation, fiber volume fraction, fiber-matrix bonding, and interlaminar bond quality are underlying factors

Detection of Anomalies in the Quality of Electricity Supply

From the last two decades, power quality is getting much attention. Proper functioning of the equipment depends upon the quality of power supplied. Every year, demand of electric power goes on increasing and the power system network is expanding and becoming more complex. On account of thrust on clean power supply, use of renewable sources has dramatically increased in grid but it simultaneously causes power quality problems. In this work, power quality disturbance detection in wind farm integrated with grid is presented. For disturbance detection, time-time transform has been employed. The disturbance signal for the detection purpose is generated in MATLAB/Simulink environment by using a Simulink model

Complementary Sensory and Associative Microcircuitry in Primary Olfactory Cortex

The three-layered primary olfactory (piriform) cortex is the largest component of the olfactory cortex. Sensory and intracortical inputs converge on principal cells in the anterior piriform cortex (aPC).Wecharacterize organization principles of the sensory and intracortical microcircuitry of layer II and III principal cells in acute slices of rat aPC using laser-scanning photostimulation and fast two-photon population Ca²⁺ imaging. Layer II and III principal cells are set up on a superficial-to-deep vertical axis. We found that the position on this axis correlates with input resistance and bursting behavior. These parameters scale with distinct patterns of incorporation into sensory and associative microcircuits, resulting in a converse gradient of sensory and intracortical inputs. In layer II, sensory circuits dominate superficial cells, whereas incorporation in intracortical circuits increases with depth. Layer III pyramidal cells receive more intracortical inputs than layer II pyramidal cells, but with an asymmetric dorsal offset. This microcircuit organization results in a diverse hybrid feedforward/recurrent network of neurons integrating varying ratios of intracortical and sensory input depending on a cell’s position on the superficial-to-deep vertical axis. Since burstiness of spiking correlates with both the cell’s location on this axis and its incorporation in intracortical microcircuitry, the neuronal output mode may encode a given cell’s involvement in sensory versus associative processing

Airborne LiDAR for DEM generation: some critical issues

Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented