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Object recognition is often viewed as a feedforward, bottom-up process in machine learning, but in real neural systems, object recognition is a complicated process which involves the interplay between two signal pathways. One is the parvocellular pathway (P-pathway), which is slow and extracts fine features of objects; the other is the magnocellular pathway (M-pathway), which is fast and extracts coarse features of objects. It has been suggested that the interplay between the two pathways endows the neural system with the capacity of processing visual information rapidly, adaptively, and robustly. However, the underlying computational mechanism remains largely unknown. In this study, we build a two-pathway model to elucidate the computational properties associated with the interactions between two visual pathways. Specifically, we model two visual pathways using two convolution neural networks: one mimics the P-pathway, referred to as FineNet, which is deep, has small-size kernels, and receives detailed visual inputs; the other mimics the M-pathway, referred to as CoarseNet, which is shallow, has large-size kernels, and receives blurred visual inputs. We show that CoarseNet can learn from FineNet through imitation to improve its performance, FineNet can benefit from the feedback of CoarseNet to improve its robustness to noise; and the two pathways interact with each other to achieve rough-to-fine information processing. Using visual backward masking as an example, we further demonstrate that our model can explain visual cognitive behaviors that involve the interplay between two pathways. We hope that this study gives us insight into understanding the interaction principles between two visual pathways. [ABSTRACT FROM AUTHOR]

Categorical relationships between objects are encoded as overlapped neural representations in the brain, where the more similar the objects are, the larger the correlations between their evoked neuronal responses. These representation correlations, however, inevitably incur interference when memories are retrieved. Here, we propose that neural feedback, which is widely observed in the brain but whose function remains largely unknown, contributes to disentangle neural correlations to improve information retrieval. We study a hierarchical neural network storing the hierarchical categorical information of objects, and information retrieval goes from rough-to-fine, aided by the push–pull neural feedback. We elucidate that the push and the pull components of the feedback suppress the interferences due to the representation correlations between objects from different and the same categories, respectively. Our model reproduces the push–pull phenomenon observed in neural data and sheds light on our understanding of the role of feedback in neural information processing. [ABSTRACT FROM AUTHOR]

Spatio-temporal information processing is fundamental in both brain functions and AI applications. Current strategies for spatio-temporal pattern recognition usually involve explicit feature extraction followed by feature aggregation, which requires a large amount of labeled data. In the present study, motivated by the subcortical visual pathway and early stages of the auditory pathway for motion and sound processing, we propose a novel brain-inspired computational model for generic spatio-temporal pattern recognition. The model consists of two modules, a reservoir module and a decision-making module. The former projects complex spatio-temporal patterns into spatially separated neural representations via its recurrent dynamics, the latter reads out neural representations via integrating information over time, and the two modules are linked together using known examples. Using synthetic data, we demonstrate that the model can extract the frequency and order information of temporal inputs. We apply the model to reproduce the looming pattern discrimination behavior as observed in experiments successfully. Furthermore, we apply the model to the gait recognition task, and demonstrate that our model accomplishes the recognition in an event-based manner and outperforms deep learning counterparts when training data is limited. [ABSTRACT FROM AUTHOR]

Recent success in isolating and growing various two-dimensional (2D) materials with intriguing properties has pushed forward the search for new 2D nanostructures with novel properties. Current experimental trial-and-error methods face the fundamental challenges of low efficiency and a lack of clear guidelines. In contrast, based on state-of-the-art first-principles calculations and well-developed structural prediction algorithms, computational simulations can not only predict an increasing number of new 2D materials with desirable properties but also suggest their possible synthesis routes. Among them, many predictions, such as the growth of monolayer boron sheets (borophene), piezoelectricity in molybdenum disulfide (MoS 2 ), ferroelectricity in tin telluride (SnTe), topological defects in transition metal dichalcogenides, Dirac cones in borophene, and high carrier mobility and mobility anisotropy in black phosphorene, have been verified by experiments, showing the accuracy of computational approaches, as well as their power in facilitating experimental exploration in 2D flatland. To date, the rapid expansion in theoretical work has generated a large number of very important results, but the overall picture of recent progress, current challenges, and future opportunities is rarely discussed. Accordingly, this review aims at providing information about current trends and future perspectives for 2D materials research. To achieve this, the review is organized as follows: (1) discussion of structural predictions in 2D materials using borophene as an example; (2) predictions of the electronic, optical, mechanical, and magnetic properties in various 2D materials; (3) discussion of the influence of defects on the structures and properties of 2D materials; and (4) evaluation of current progress in computational simulations and perspectives for future development. [ABSTRACT FROM AUTHOR]

Sulfur shows totally opposite faces in environmental and energy issues. Sulfur containing gases, H 2 S and SO 2 , are dominant air pollutants, while sulfur plays as the clean energy carrier for Li-Sulfur (Li-S) batteries. Herein, through confining the gaseous comproportionation reaction in water, between H 2 S and SO 2 that normally produces uncontrollable aggregates, we develop a completely clean approach to convert the air pollutants into water-dispersed sulfur nanoparticle (WDS). The WDS is contaminant-free, size-controllable, and more promisingly solution processable, and is thus ideal for achieving solution hybridization with other materials for various applications. As a typical example, an aqueously fabricated WDS/carbon nanotube composite delivers the theoretical capacity of sulfur at 0.5 A g −1 , and a capacity of ~750 mAh g −1 even at a high current density of 5.0 A g −1 . In addition to the normal use of sulfur as cathode, a new-concept WDS/carbon interlayer with a low sulfur content has been designed to inhibit the shuttling of polysulfides, greatly improving the cycling performance of the Li-S battery. The proposed approach gives a good example to turning pollutants into clean energy carriers by green chemistry. [ABSTRACT FROM AUTHOR]

Summary A critical step in understanding the neural basis of human cognitive functions is to identify neuronal types in the neocortex. In this study, we performed whole-cell recording from human cortical slices and found a distinct subpopulation of neurons with intrinsic persistent activity that could be triggered by single action potentials (APs) but terminated by bursts of APs. This persistent activity was associated with a depolarizing plateau potential induced by the activation of a persistent Na + current. Single-cell RT-PCR revealed that these neurons were inhibitory interneurons. This type of neuron was found in different cortical regions, including temporal, frontal, occipital, and parietal cortices in human and also in frontal and temporal lobes of nonhuman primate but not in rat cortical tissues, suggesting that it could be unique to primates. The characteristic persistent activity in these inhibitory interneurons may contribute to the regulation of pyramidal cell activity and participate in cortical processing. [ABSTRACT FROM AUTHOR]

Abstract: The feasibility to store hydrogen in calcium-decorated metal organic frameworks (MOFs) is explored by using first-principles electronic structure calculations. We show that substitution of boron atoms into the benzene ring of the MOF linker substantially enhances the Ca binding energy to the linker as well as the H2 binding energy to Ca. The Kubas interaction between H2 molecules and Ca added in the MOF gives rise to a large number of bound H2''s (8H2''s per linker) with the binding energy of 20 kJ/mol, which makes the system suitable for reversible hydrogen storage under ambient conditions. [Copyright &y& Elsevier]

• Four-point bending tests were conducted on a stone matrix asphalt. • Stiffness ratio curve can be fitted well by the Weibull equations. • The damage model was expressed as a power exponential function for dissipated energy. Four-point bending tests under strain-controlled mode were conducted on a stone matrix asphalt. Fatigue properties were evaluated by comparing indexes and fatigue curves at different frequencies, temperatures, and strain levels. The results show the effects of temperature and strain level are more significant than that of frequency. The fatigue life is much longer under the conditions of high temperature or low strain level than those under other conditions. Stiffness ratio curve can be fitted well by the Weibull equations. The damage model expressed as a power exponential function for dissipated energy provides a reliable method for evaluating fatigue damage. [ABSTRACT FROM AUTHOR]

The emerging non-noble metal two-dimensional (2D) catalyst, such as MoS 2 , for the hydrogen evolution reaction (HER) is known to have an inert basal plane unless being converted to a metastable metallic phase or defect engineered. In order to take advantage of the majority of the material in such layered catalysts, fast screening of 2D catalysts with superior basal plane activity is imperative. A local electrochemical measurement method assisted by the e-beam lithography patterning was developed and applied to quantify the activity of basal planes of different layered transition metal dichalcogenides (TMDs) toward HER. This local measurement offers a robust platform to discover active TMDs fast and precisely. The construction of HER volcano plot leads to the discovery of superior basal plane active group VB metal disulfides, especially 3R-NbS 2. Interestingly, the trends found in the volcano plot imply distinctive differences in the mechanism of TMD catalysts compared to their metal counterparts. The intensive hydrogen evolution reaction in-between the basal planes drives self-nanostructuring in morphology of 3R-NbS 2. The increase in the effective surface area, and decrease in the electron-transfer resistance across the substrate and basal plane interface induced by the self-nanostructuring in turn enhances the HER performance of 3R-NbS 2. The 3R-NbS 2 clearly stands out among non-noble metal catalysts for HER. [ABSTRACT FROM AUTHOR]

Bamboo fiber (BF) is a type of plant fiber obtained directly from bamboo plants or from waste bamboo residue, which can be used as an asphalt modifier. Rational planning and regular cutting of bamboo forest will promote its growth, thus improving the effect of carbon sequestration and absorption. The use of bamboo products is now widespread, and the reuse of waste bamboo residue will reduce smoke pollution from incineration. This paper outlines the preparation method and surface treatment of bamboo fiber, its characteristics, preparation parameters, basic and rheological properties and ageing resistance of it modified asphalt and conventional engineering properties of bamboo fiber modified asphalt mixtures. Cost analysis and molecular dynamics (MD) simulation attempts were then carried out. Lignin fiber (LF) and polyester fiber (PF) are chosen for comparative study and suggestions for further research were made. The results showed that BF modified bitumen has significant mechanical and oil absorption properties compared to LF and PF modified bitumen. However, its low temperature properties varied with the type of base asphalt. In addition, for bamboo fiber modified asphalt, BF significantly increased its low-temperature cracking resistance and moisture sensitivity, but limited its high-temperature stability, and its fatigue properties need to be further investigated. It is suggested that future research should also improve the dispersion uniformity and interfacial bonding of asphalt with BF, and deeply analyze the modification mechanism of BF on asphalt through micro tests and MD simulation. Through the analysis of economic and environmental benefits, bamboo fiber asphalt mixture can effectively reduce project cost and improve global warming and human hazards, etc. The application of BF in asphalt pavements can enrich the variety of road fibers, which is of great significance to the society, economy, and environment. • The effects of bamboo fiber (BF), lignin fiber (LF) and polyester fiber (PF) on the performance of asphalt were reviewed. • The effects of BF, LF and PF on the performance of asphalt mixture were summarized. • BF modified asphalt pavement has better economic and environmental benefits. • The future research direction of BF in modified asphalt and mixture was proposed. [ABSTRACT FROM AUTHOR]

[Display omitted] Two-dimensional (2D) materials have many promising applications, but their scalable production remains challenging. Herein, we develop a glue-assisted grinding exfoliation (GAGE) method in which the adhesive polymer acts as a glue to massively produce 2D materials with large lateral sizes, high quality, and high yield. Density functional theory simulation shows that the exfoliation mechanism involves the competition between the binding energy of selected polymers and the 2D materials which is larger than the exfoliation energy of the layered materials. Taking h-BN as an example, the GAGE produces 2D h-BN with an average lateral size of 2.18 μm and thickness of 3.91 nm. The method is also extended to produce various other 2D materials, including graphene, MoS 2 , WS 2 , Bi 2 O 2 Se, mica, vermiculite, and montmorillonite. Two representative applications of thus-produced 2D materials have been demonstrated, including 2D h-BN/polymer composites for insulating thermal conduction and 2D MoS 2 -based electrocatalysts for large-current-density hydrogen evolution, indicating the great potential of massively produced 2D materials. [ABSTRACT FROM AUTHOR]

Waste management has been one of the urgent environmental issues due to the rapid urbanization in China. There is a huge potential to improve the energy recovery efficiency of the current waste treatment system. This study aims to propose an efficient waste management system to reduce the landfill amount and improve the energy recovery rate (ERE) of Municipal Solid Waste (MSW) treatment by considering environment, energy, economic, and policy effects. This study selects Beijing as a case study city and proposes four different MSW treatment scenarios. The landfill reduction amount, energy recovery efficiency, life cycle costs and benefits, and the Greenhouse Gas (GHG) emissions are evaluated. Furthermore, the impact of waste separation policy on the landfill amount, and the proposed internal rate of return (IRR) index are also quantified. The results show that the proposed scenarios can significantly reduce the amount of landfill. Scenario 4 (MBT system) ranks the highest, with a value of 92.69%. From the energy recovery and GHG emissions reduction perspectives, scenario 4 can achieve the highest energy recovery efficiency (65.33%) and the highest GHG emissions reduction (2.09 × 106 tons CO 2 e). From the economic perspective, scenario 3 can achieve the highest benefit with a value of 6.00 × 109 CNY. Such benefits are highly affected by the factors of the treatment capacity, the tipping fee and the power generation efficiency. With the continuous implementation of waste separation policy and waste-to-energy option in China, it is critical to assess the related environmental and economic benefits so that an efficient waste management system can be established. • ERE improvement and landfill amount of waste treatment in China are urgent. • Propose integrated MBT technologies and waste to energy treatment system. • Evaluate Life cycle cost-benefit, tipping fee, GHG, internal rate of return. • Integrated system has the highest ERE and GHG reduction. • Evaluate efficient waste treatment system to reduce landfill amount and improve ERE. [ABSTRACT FROM AUTHOR]

Vanadium carbide with periodic carbon vacancies (□ C -VC) was synthesized for efficient catalyzing N 2 to NH 3. The as-prepared □ C -VC with high density of carbon vacancies and mesoporous structure has displayed superior activity as well as durability towards electrocatalytic nitrogen reduction reaction. Although electrocatalytic nitrogen reduction reaction (NRR) has been considered as an emerging pathway to produce ammonia (NH 3) under ambient conditions owing to its low energy consumption, it still lacks efficient the electrocatalysts to dissociate inert N N bonds. Here, we develop an efficient approach to produce vanadium carbide with abundant periodic carbon vacancies (12.5 at. %) and mesoporous structure as electrocatalysts for NRR via a carbothermic reaction. The typical synthesis protocol involves the use of zinc vanadate decorated vanadium pentoxide nanosheets to homogeneously guide the nucleation and growth of metal organic frameworks (MOFs) on their surface, thus facilitating the in-situ formation of unique vanadium carbide during the subsequent carbothermic reaction. Owing to the optimized substrate-adsorbate binding strength, the intrinsic periodic carbon vacancies of the resultant vanadium carbide could act as coordinatively unsaturated sites to adsorb and activate nitrogen through π-back-donation process, thus promoting the reduction of N 2 to NH 3. As a consequence, a high yield rate and high Faradaic efficiency with good stabilities are achieved for producing NH 3 under ambient conditions. [ABSTRACT FROM AUTHOR]

By-products and waste materials have become the main cause of environment contamination. In this study, Rice Husk Ash (RHA) was used as modifier to improve the high temperature property of asphalt binder. Bio-oil (BO) was selected as viscosity reducer to enhance the low-temperature and anti-fatigue properties of RHA Modified Asphalt (RHA-MA). Physical and rheological indexes were measured to determine the optimal RHA and BO content. The Scanning Electron Micrographs (SEM) and Energy Dispersive Spectrometer (EDS) analysis were adopted to reveal the modification mechanism of RHA and BO. Results show that RHA-MA possessed desirable high-temperature but unsatisfactory low-temperature performance compared with base asphalt and Limestone Filler Mixed Asphalt (LA). However, asphalt binder with 1% RHA and 20% BO (RB-MA) obtained ductility (15 °C) nearly 50% higher and loss modulus approximately 20% lower than those of RHA-MA. Meanwhile, the softening point is 4.2 °C more and G ∗ /Sinδ at all temperatures is higher than those of BO Modified Asphalt (BA). Furthermore, SEM observation illustrates that BO is able to reduce RHA agglomeration and increase the uniformity of RHA-MA mix system, contributing greatly to the excellent comprehensive performance of RB-MA. Consequently, the joint modification of base asphalt with RHA and BO could obtain desirable high temperature, low temperature and anti-fatigue performance. Therefore, it is likely that the development of RB-MA could be helpful to make conventional asphalt qualified for complex service ambient, as well as improve the recycling rate of agricultural waste to reduce environmental pollution and reduce the life cycle cost of asphalt pavement. [ABSTRACT FROM AUTHOR]

Purpose: To examine age-related effects of smoking on lung cancer mortality in a large population-based case-control study that was incorporated into a nationwide retrospective survey of mortality in China. Methods: Two data sets were pooled for this analysis: national mortality survey data and data from a nationwide case-control comparison. These pooled data were used to calculate age-specific lung cancer death rates by smoking status and expected years of lost life expectancy for each smoking-associated death. Results: There was a significant excess of deaths (54% of urban deaths, 51% of rural deaths) at 35 to 69 years of age among male smokers and the average loss of life expectancy per smoking-associated death at these ages was 18.3 years. For women ages 35 to 69 years of age, 29% and 11% excess lung cancer mortality was observed in urban and rural smokers, respectively, with an average loss of life expectancy per smoking-associated death of 21.3 years. Conclusions: Tobacco smoking was associated with a large number of deaths from lung cancer. Utilizing information from a population-based retrospective mortality survey for conducting an analytic epidemiological study of main determinants of disease is feasible and can generate important results. [Copyright &y& Elsevier]

• Provide solutions to alleviate waste oil pollution. • Recommend the optimal dosage of WEO and WCO to recover performance of aged asphalt. • The basic performance of aged asphalt was improved by addition of WEO and WCO. • Regenerant with WEO and WCO enhanced the RAP utilization. This paper studies the effects that varying amounts of waste cooking oil (WCO) and waste engine oil (WEO) have on the rejuvenation effect of aged asphalt, and the road performance of the 7% compound regenerant to different contents of RAP. The basic performance tests demonstrated the regeneration effect of waste oil, while the microscopic test and chemical composition analysis revealed the regeneration mechanism, after which the road performance was then tested using RAP. Moreover, the study outcome demonstrates that adding appropriate waste oil dosage can effectively increase the conventional physical properties. Furthermore, it was revealed that due to the addition of waste oil supplementing the light components of the aged asphalt, the basic performance of asphalt at different aged degrees can be restored to the standard. Meanwhile, the addition of waste oil will not cause other chemical reactions, but excessive waste oil addition will lead to undesirable reduction in the viscosity of the asphalt, so the recommended waste oil dosage is 1%~4%. In the end, subsequent road performance tests showed that the compound regenerant can achieve 45% RAP application. [ABSTRACT FROM AUTHOR]