Unravelling the Mechanism of Excited-State Interligand Energy Transfer and the Engineering of Dual Emission in [Ir(CN)(NN)] Complexes.

Fundamental insights into the mechanism of triplet-excited-state interligand energy transfer dynamics and the origin of dual emission for phosphorescent iridium(III) complexes are presented. The complexes [Ir(CN)(NN)] (HCN = 2-phenylpyridine (-), 2-(2,4-difluorophenyl)pyridine (-), 1-benzyl-4-phenyl-1,2,3-triazole (-); NN = 1-benzyl-4-(pyrid-2-yl)-1,2,3-triazole (pytz, ), 1-benzyl-4-(pyrimidin-2-yl)-1,2,3-triazole (pymtz, ), 1-benzyl-4-(pyrazin-2-yl)-1,2,3-triazole (pyztz, )) are phosphorescent in room-temperature fluid solutions from triplet metal-to-ligand charge transfer (MLCT) states admixed with either ligand-centered (LC) (, , and ) or ligand-to-ligand charge transfer (LL'CT) character (, , and -). Particularly striking is the observation that pyrimidine-based complex exhibits dual emission from both MLCT/LC and MLCT/LL'CT states.

Advanced Cataloging of Lysine-63 Polyubiquitin Networks by Genomic, Interactome, and Sensor-Based Proteomic Analyses.

The lack of resolution when studying the many different ubiquitin chain types found in eukaryotic cells has been a major hurdle to our understanding of their specific roles. We currently have very little insight into the cellular and physiological functions of Lys-63 (K63)-linked ubiquitin chains, although they are the second most abundant forms of ubiquitin in plant cells. To overcome this problem, we developed several large-scale approaches to characterize (1) the E2-E3 ubiquitination machinery driving K63-linked ubiquitin chain formation and (2) K63 polyubiquitination targets to provide a comprehensive picture of K63 polyubiquitin networks in Arabidopsis ().

SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks With at Most One Spike per Neuron.

Application of deep convolutional spiking neural networks (SNNs) to artificial intelligence (AI) tasks has recently gained a lot of interest since SNNs are hardware-friendly and energy-efficient. Unlike the non-spiking counterparts, most of the existing SNN simulation frameworks are not practically efficient enough for large-scale AI tasks. In this paper, we introduce SpykeTorch, an open-source high-speed simulation framework based on PyTorch.

The bifunctional transporter-receptor IRT1 at the heart of metal sensing and signalling.

Transporters are at the centre of regulatory modules allowing optimal assimilation, distribution or efflux of substrate molecules. The IRT1 root metal transporter represents a textbook example in which detailed regulatory networks have been shown to integrate several endogenous and exogenous cues at various levels to regulate its expression and to fine tune iron uptake. Here, we summarise recent advances in the dissection of the transcriptional and posttranslational control of IRT1 by its various metals substrates and discuss the emerging role of IRT1 in the direct sensing of non-iron metals flowing through IRT1 to drive its degradation.

Optimal Localist and Distributed Coding of Spatiotemporal Spike Patterns Through STDP and Coincidence Detection.

Repeating spatiotemporal spike patterns exist and carry information. Here we investigated how a single spiking neuron can optimally respond to one given pattern (localist coding), or to either one of several patterns (distributed coding, i.e.

Zapping 500 faces in less than 100 seconds: Evidence for extremely fast and sustained continuous visual search.

A number of studies have shown human subjects' impressive ability to detect faces in individual images, with saccade reaction times starting as fast as 100 ms after stimulus onset. Here, we report evidence that humans can rapidly and continuously saccade towards single faces embedded in different scenes at rates approaching 6 faces/scenes each second (including blinks and eye movement times). These observations are impressive, given that humans usually make no more than 2 to 5 saccades per second when searching a single scene with eye movements.

STDP-based spiking deep convolutional neural networks for object recognition.

Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively shallow architectures, and only one layer was trainable. Another line of research has demonstrated - using rate-based neural networks trained with back-propagation - that having many layers increases the recognition robustness, an approach known as deep learning.

Theoretical illumination of highly original photoreactive MC states and the mechanism of the photochemistry of Ru(ii) tris(bidentate) complexes.

We have identified highly novel photoreactive MC states of ruthenium(ii) 4,4'-bi-1,2,3-triazolyl (btz) complexes of the form [Ru(N^N)(btz)] and have elucidated the mechanism of the highly unusual experimental observations of photochemical ligand dechelation and concomitant ligand rearrangement reactivity to form unusual photoproducts trans-[Ru(N^N)(κ-btz)(κ-btz)(solvent)]. The triplet metal-to-ligand charge-transfer (MLCT) states and classical Jahn-Teller type triplet metal-centred (MC) states of the series of complexes [Ru(N^N)(btz)] (btz = 4,4'-bi-1,2,3-triazolyl; N^N = 2,2'-bipyridyl (bpy), n = 0 (1), 1 (2), 2 (3), 3 (5); N^N = 4-(pyrid-2-yl)-1,2,3-triazole (pytz), n = 1 (4)) have been optimised by density functional theory (DFT) and characterised. There is a gradual and significant destabilisation of the MLCT states as the triazole content of the complexes increases, which occurs with a slight stabilisation of the MC states.

STDP Allows Close-to-Optimal Spatiotemporal Spike Pattern Detection by Single Coincidence Detector Neurons.

Repeating spatiotemporal spike patterns exist and carry information. How this information is extracted by downstream neurons is unclear. Here we theoretically investigate to what extent a single cell could detect a given spike pattern and what the optimal parameters to do so are, in particular the membrane time constant τ.

A Fox stops the Wnt: implications for forebrain development and diseases.

In recent years, much progress has been made in understanding the process by which the brain is organised into specific regions. Much less is known about the way neuronal subtypes are defined inside these areas and how the temporal control of connectivity between neurons is achieved. Our thought processes and behaviours depend upon the development of neuronal circuits located in the most anterior brain area: the telencephalon (forming our cerebral cortex).

Topographical presentation of dental wear as arches in a French mediaeval population.

Unlabelled: The diversity of notation systems for recording dental characteristics and the means used to display them makes comparisons and interdisciplinary collaboration difficult.

Objective: The aim of the present study is to propose the use of a method employed by experts worldwide but which may be new to bioarchaeologists. Since 1971 we have used the International Dental Federation (FDI) system, which provides the location of dental characteristics and the morphotype of each tooth at the same time, thus avoiding the need to specify upper or lower, and right or left to state the tooth position in the dental arch.

Interaction of a plant pseudo-response regulator with a calmodulin-like protein.

Calmodulin (CaM) plays a crucial role in the regulation of diverse cellular processes by modulating the activities of numerous target proteins. Plants possess an extended CaM family including numerous CaM-like proteins (CMLs), most of which appear to be unique to plants. We previously demonstrated a role for CML9 in abiotic stress tolerance and seed germination in Arabidopsis thaliana.