Temporal attention affects contrast response function by response gain

Orienting attention to a specific point in time has been shown to improve the contrast sensitivity at the attended time point and impair it earlier or later. This phenomenon could be explained by temporal attention increasing the effective contrast of the target presented at the attended time point which leads to changes in contrast psychometric function by contrast gain. Another explanation is that temporal attention multiplicatively amplifies the amplitude of behavioral or neural response to contrast, resulting in alterations in contrast psychometric function by response gain. To explore the underlying mechanism, we adopted a temporal cueing orientation discrimination task using audio pre-cues composed of different frequency components to induce different attentional allocations in the time domain and targets of various contrast intensities to measure contrast psychometric functions. Obtained psychometric functions for contrast sensitivity were fitted for different conditions with discrepant attentional states in time. We found that temporal attention manipulated by cue affected contrast psychometric function by response gain, indicating that multiplying the contrast response of the visual target occurring at the selected point in time by a fixed factor is a crucial way for temporal attention to modulate perceptual processing

Reasonable Scale of Megacity Central Area Based on Multivariate Data and a Traffic Perspective

The central area of a megacity, which features high-intensity development, large population density, and concentrated urban functions, demonstrates the most prominent urban problems. Addressing the urban malaise in megacities necessitates analyzing and demonstrating the reasonable scale of the megacity central area. This study proposes that commuting time is the core controlling factor determining the reasonable scale of the megacity central area. Combining with point of interest data of multi-type land use and the geographic information system data for street administrative division, we identified the current central urban areas of ten cities in China using big data analysis and the clustering method; their current traffic efficiencies were then evaluated based on path navigation data via web maps and mobile phone signaling data verification. Finally, demonstration results were presented through quantitative analysis. Our study shows that the current central areas of the ten megacities cannot satisfy residents’ need for a proper commuting time; considering factors such as technological development and improvement in the level of governance, 13 ‒ 15 km is the upper limit of equivalent radius for the central area of a megacity

What Makes a Good Cabman? Behavioral Patterns Correlated with High-Earning and Low-Earning Taxi Driving

The average hourly income of taxi drivers could be improved by understanding the realized income of taxi drivers and investigating the variables that determine their income. Based on 4.85 million taxi-trajectory GPS records in Shenzhen, China, this study built a multi-layer road index system in order to reveal the behavioral patterns of drivers with varying income levels. On this basis, late-shift drivers were further selected and classified into two categories, namely high-earning and low-earning groups. Each driver within these groups was further classified into three income levels and four categories of factors were defined (i.e., occupied trips and duration, operational region, search speed, and taxi service strategies). The sample-based multinomial logit model was used to reveal the significance of these income-influencing factors. The results indicate significant differences in the drivers’ behavioral habits and experience. For instance, high-earning drivers focused more on improving efficiency using mobility intelligence, while low-earning drivers were more likely to invest in working hours to boost their revenue

What Makes a Good Cabman? Behavioral Patterns Correlated with High-Earning and Low-Earning Taxi Driving

The average hourly income of taxi drivers could be improved by understanding the realized income of taxi drivers and investigating the variables that determine their income. Based on 4.85 million taxi-trajectory GPS records in Shenzhen, China, this study built a multi-layer road index system in order to reveal the behavioral patterns of drivers with varying income levels. On this basis, late-shift drivers were further selected and classified into two categories, namely high-earning and low-earning groups. Each driver within these groups was further classified into three income levels and four categories of factors were defined (i.e., occupied trips and duration, operational region, search speed, and taxi service strategies). The sample-based multinomial logit model was used to reveal the significance of these income-influencing factors. The results indicate significant differences in the drivers’ behavioral habits and experience. For instance, high-earning drivers focused more on improving efficiency using mobility intelligence, while low-earning drivers were more likely to invest in working hours to boost their revenue

Uncovering Factors Affecting Taxi Income from GPS Traces at the Directional Road Segment Level

Nowadays, the market demand for taxis is still intense. However, there exist lots of issues affecting the healthy development of the taxi industry, such as an increasing difficulty in hailing taxis, detouring behavior etc., and especially, the low incomes of taxi drivers. This paper establishes a multi-layer road index (MRI) system of 7862 directional road segments (DRSs), and collects over 194 million occupied GPS points within a week, revealing the factors affecting taxi drivers’ incomes in Shenzhen, China. The income differences has been identified on different DRSs, which accordingly have been categorized into two levels. Four categories of DRS factors, i.e., road attributes, traffic dynamics, points of interest (POIs), and taxi operation strategies, are defined as the impact factors affecting income levels. The selected sample-based binomial logit (SBL) model has been proposed to reveal the significance of these influencing factors. The results indicate that the road segments with different features have different incomes over different time periods. The main factors in income analysis are the factors used to represent taxi operation strategies. Highly rewarding pick-up road segments can be identified, which could contribute to drivers’ income improvements, and can further contribute to the development of the taxi market

Metagenomics Investigation of Agarlytic Genes and Genomes in Mangrove Sediments in China: A Potential Repertory for Carbohydrate-Active Enzymes

Monosaccharides and oligosaccharides produced by agarose degradation exhibit potential in the fields of bioenergy, medicine, and cosmetics. Mangrove sediments (MGSs) provide a special environment to enrich enzymes for agarose degradation. However, representative investigations of the agarlytic genes in MGSs have been rarely reported. In this study, agarlytic genes in MGSs were researched in detail from the aspects of diversity, abundance, activity, and location through deep metagenomics sequencing. Functional genes in MGSs were usually incomplete but were shown as results, which could cause virtually high number of results in previous studies because multiple fragmented sequences could originate from the same genes. In our work, only complete and nonredundant (CNR) genes were analyzed to avoid virtually high amount of the results. The number of CNR agarlytic genes in our datasets was significantly higher than that in the datasets of previous studies. Twenty-one recombinant agarases with agarose-degrading activity were detected using heterologous expression based on numerous complete open-reading frames, which are rarely obtained in metagenomics sequencing of samples with complex microbial communities, such as MGSs. Aga2, which had the highest crude enzyme activity among the 21 recombinant agarases, was further purified and subjected to enzymatic characterization. With its high agarose-degrading activity, resistance to temperature changes and chemical agents, Aga2 could be a suitable option for industrial production. The agarase ratio with signal peptides to that without signal peptides in our MGS datasets was lower than that of other reported agarases. Six draft genomes, namely, Clusters 1–6, were recovered from the datasets. The taxonomic annotation of these genomes revealed that Clusters 1, 3, 5, and 6 were annotated as Desulfuromonas sp., Treponema sp., Ignavibacteriales spp., and Polyangiaceae spp., respectively. Meanwhile, Clusters 2 and 4 were potential new species. All these genomes were first reported and found to have abilities of degrading various important polysaccharides. The metabolic pathway of agarose in Cluster 4 was also speculated. Our results showed the capacity and activity of agarases in the MGS microbiome, and MGSs exert potential as a repertory for mining not only agarlytic genes but also almost all genes of the carbohydrate-active enzyme family

Key Factors, Planning Strategy and Policy for Low-Carbon Transport Development in Developing Cities of China

Exploring key impact factors and their effects on urban residents’ transport carbon dioxide (CO2) emissions is significant for effective low-carbon transport planning. Researchers face the model uncertainty problem to seek a rational and better explanatory model and the key variables in the model set containing various factors after they are arranged and combined. This paper uses the Bayesian Model Averaging method to solve the above problem, explore the key variables, and determine their relative significance and averaging effects. Beijing, Xi’an, and Wuhan are selected as three case cities for their representation of developing Chinese cities. We found that the initial key factor increasing transport emissions is the high dependence on cars, and the second is the geographical location factor that much more suburban residents suffer longer commuting. Developing satellite city rank first for reducing transport emissions due to more local trips with an average short distance, the second is the metro accessibility, and the third is polycentric form. Key planning strategies and policies are proposed: (i) combining policies of car restriction based on vehicle plate number, encouraging clean fuel cars, a carbon tax on oil uses, and rewarding public transit passengers; (ii) fostering subcenters’ strong industries to develop self-contained polycentric structures and satellite cities, and forming employment and life circle within 5 km radius; and (iii) integrating bus and rail transit services in the peripheral areas and suburbs and increasing the integration level of muti-modes transferring in transport hubs. The findings will offer empirical evidence and reference value in developing cities globally

The polymer composite electrolyte with polyethylene oxide-grafted graphene oxide as fillers toward stable highcurrent density lithium metal anodes

Adding inorganic fillers to polymer electrolytes is one of the main means to improve ionic conductivity. However, the filler will aggregate, causing the problem of incompatibility between the electrolyte and the metal lithium negative electrode. According to reports, the flaky structure of graphene oxide (GO) has the characteristics of large specific surface area and stable performance, which has attracted widespread attention as a filler for polymer electrolytes. However, the electrolyte membrane has poor compatibility with lithium negative electrodes when GO as a filler, which is not conducive to the full performance of lithium batteries. In this paper, we grafted polyethylene oxide (PEO) on the surface of GO (the product is referred to as GO@PEO) to improving the dispersibility of the filler and the compatibility of the gel polymer electrolyte (GPE) with lithium metal . It is worth that after GO grafting PEO, the impedance of the interface between GPE and lithium metal is significantly reduced, and the compatibility of the electrolyte with the lithium negative electrode is significantly improved. Assembled into Li/ Li battery, the surface current cycle is stable, up to 1 mA cm ^−2 . GO@PEO further improves the ionic conductivity of the ion conductivity up to 1.6 mS cm ^−1 . Further prepared into LiFePO _4 (LFP)/Li battery, GPE-GO@PEO showed excellent cycle stability and the discharge specific capacity retention rate was 95.6% after 100 cycles. The rate performance of the battery is also significantly improved. At 5C, the discharge specific capacity of the LFP/Li battery remains 40 mAh g ^−1