The neural basis of visual material properties in the human brain

Three independent studies with human functional magnetic resonance imaging (fMRI) measurements were designed to investigate the neural basis of visual glossiness processing in the human brain. The first study is to localize brain areas preferentially responding to glossy objects defined by specular reflectance. We found activations related to gloss in the posterior fusiform (pFs) and in area V3B/KO. The second study is to investigate how the visual-induced haptic sensation is achieved in our brain. We found that in secondary somatosensory area (S2) was distinguishable between glossy and rough surfaces, suggesting that visual information about object surfaces may be transformed into tactile information in S2. In the third study we investigate how the brain processes surface gloss information conveyed by disparity of specular reflections on stereo mirror objects and compared it with the processing of specular reflectance. We found that both dorsal and ventral areas were involving in this processing. The result implicates that in this region the processing of stereoscopic gloss information has a pattern of activation that is additional to the representation of specular reflectance. Overall, the three studies contribute to our understanding about the neural basis of visual glossiness and material processing in the human brain

Bi- and tri-dentate imino-based iron and cobalt pre-catalysts for ethylene oligo-/polymerization

Recent progress on the use of iron and cobalt complex pre-catalysts for ethylene reactivity is reviewed. The review is organized in terms of the denticity of the chelate ligands employed, with particular reference to the influence of the ligand frameworks and their substituents on the catalytic performance for ethylene oligomerization/polymerization catalysis. The majority of the systems bear tri-dentate ligation at the iron/cobalt centre, though it is clear that bi-dentate iron/cobalt complex pre-catalysts have also attracted significant attention. Such systems produce in most cases highly linear products ranging from oligomeric α-olefins to high molecular weight polyethylene, and as such are promising candidates for both academic and industrial considerations

Diffusion Model-Augmented Behavioral Cloning

Imitation learning addresses the challenge of learning by observing an expert's demonstrations without access to reward signals from environments. Most existing imitation learning methods that do not require interacting with environments either model the expert distribution as the conditional probability p(a|s) (e.g., behavioral cloning, BC) or the joint probability p(s, a) (e.g., implicit behavioral cloning). Despite its simplicity, modeling the conditional probability with BC usually struggles with generalization. While modeling the joint probability can lead to improved generalization performance, the inference procedure can be time-consuming and it often suffers from manifold overfitting. This work proposes an imitation learning framework that benefits from modeling both the conditional and joint probability of the expert distribution. Our proposed diffusion model-augmented behavioral cloning (DBC) employs a diffusion model trained to model expert behaviors and learns a policy to optimize both the BC loss (conditional) and our proposed diffusion model loss (joint). DBC outperforms baselines in various continuous control tasks in navigation, robot arm manipulation, dexterous manipulation, and locomotion. We design additional experiments to verify the limitations of modeling either the conditional probability or the joint probability of the expert distribution as well as compare different generative models

Look but don't touch: Visual cues to surface structure drive somatosensory cortex.

When planning interactions with nearby objects, our brain uses visual information to estimate shape, material composition, and surface structure before we come into contact with them. Here we analyse brain activations elicited by different types of visual appearance, measuring fMRI responses to objects that are glossy, matte, rough, or textured. In addition to activation in visual areas, we found that fMRI responses are evoked in the secondary somatosensory area (S2) when looking at glossy and rough surfaces. This activity could be reliably discriminated on the basis of tactile-related visual properties (gloss, rough, and matte), but importantly, other visual properties (i.e., coloured texture) did not substantially change fMRI activity. The activity could not be solely due to tactile imagination, as asking explicitly to imagine such surface properties did not lead to the same results. These findings suggest that visual cues to an object's surface properties evoke activity in neural circuits associated with tactile stimulation. This activation may reflect the a-priori probability of the physics of the interaction (i.e., the expectation of upcoming friction) that can be used to plan finger placement and grasp force.This project was supported by the Wellcome Trust (095183/Z/10/Z).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.neuroimage.2015.12.05

Nonnegative Matrix Factorization-Based Spatial-Temporal Clustering for Multiple Sensor Data Streams

Cyber physical systems have grown exponentially and have been attracting a lot of attention over the last few years. To retrieve and mine the useful information from massive amounts of sensor data streams with spatial, temporal, and other multidimensional information has become an active research area. Moreover, recent research has shown that clusters of streams change with a comprehensive spatial-temporal viewpoint in real applications. In this paper, we propose a spatial-temporal clustering algorithm (STClu) based on nonnegative matrix trifactorization by utilizing time-series observational data streams and geospatial relationship for clustering multiple sensor data streams. Instead of directly clustering multiple data streams periodically, STClu incorporates the spatial relationship between two sensors in proximity and integrates the historical information into consideration. Furthermore, we develop an iterative updating optimization algorithm STClu. The effectiveness and efficiency of the algorithm STClu are both demonstrated in experiments on real and synthetic data sets. The results show that the proposed STClu algorithm outperforms existing methods for clustering sensor data streams

Damaged DNA-binding protein 2 (DDB2) protects against UV irradiation in human cells and Drosophila

<p>Abstract</p> <p>Background</p> <p>We observed previously that cisplatin-resistant HeLa cells were cross-resistant to UV light due to accumulation of DDB2, a protein implicated in DNA repair. More recently, we found that cFLIP, which represents an anti-apoptotic protein whose level is induced by DDB2, was implicated in preventing apoptosis induced by death-receptor signaling. In the present study, we investigated whether DDB2 has a protective role against UV irradiation and whether cFLIP is also involved in this process.</p> <p>Methods</p> <p>We explored the role of DDB2 in mediating UV resistance in both human cells and Drosophila. To do so, DDB2 was overexpressed by using a full-length open reading frame cDNA. Conversely, DDB2 and cFLIP were suppressed by using antisense oligonucleotides. Cell survival was measured using a colony forming assay. Apoptosis was monitored by examination of nuclear morphology, as well as by flow cytometry and Western blot analyses. A transcription reporter assay was also used to assess transcription of cFLIP.</p> <p>Results</p> <p>We first observed that the cFLIP protein was upregulated in UV-resistant HeLa cells. In addition, the cFLIP protein could be induced by stable expression of DDB2 in these cells. Notably, the anti-apoptotic effect of DDB2 against UV irradiation was largely attenuated by knockdown of cFLIP with antisense oligonucleotides in HeLa cells. Moreover, overexpression of DDB2 did not protect against UV in VA13 and XP-A cell lines which both lack cFLIP. Interestingly, ectopic expression of human DDB2 in <it>Drosophila </it>dramatically inhibited UV-induced fly death compared to control GFP expression. On the other hand, expression of DDB2 failed to rescue a different type of apoptosis induced by the genes <it>Reaper </it>or <it>eiger</it>.</p> <p>Conclusion</p> <p>Our results show that DDB2 protects against UV stress in a cFLIP-dependent manner. In addition, the protective role of DDB2 against UV irradiation was found to be conserved in divergent living organisms such as human and <it>Drosophila</it>. In addition, UV irradiation may activate a cFLIP-regulated apoptotic pathway in certain cells.</p

Localized States and Quantum Spin Hall Effect in Si-Doped InAs/GaSb Quantum Wells

We study localized in-gap states and quantum spin Hall effect in Si-doped InAs/GaSb quantum wells. We propose a model describing donor and/or acceptor impurities to describe Si dopants. This model shows in-gap bound states and wide conductance plateau with the quantized value $2e^2/h$ in light dopant concentration, consistent with recent experiments by Du et al. We predict a conductance dip structure due to backward scattering in the region where the localization length $\xi$ is comparable with the sample width $L_y$ but much smaller than the sample length $L_x$.Comment: 4+pages main text including 4 figures, supplementary materials with 3 figures are include