l-Threonine aldolase (LTA) is an attractive tool in organic chemistry for catalyzing the formation of β-hydroxy-α-amino acids with two chiral centers. The enzyme has a strict selectivity for Cα of ...β-hydroxy-α-amino acids but a moderate selectivity for Cβ , limiting its wide applications in stereospecific carbon–carbon bond synthesis. Here, a combinatorial active-site saturation test/iterative saturation mutagenesis (CAST/ISM) strategy was applied to accelerate directed evolution of LTA in diastereoselectivity. A total of 27 amino acid residues lining the substrate pocket were selected and divided into two groups based on their functional region. In silico screening and site-directed saturation mutagenesis identified six (3 + 3) amino acid residues of them with a significant effect on diastereoselectivity. The ISM strategy was then performed in and between each group to obtain the best combinatorial mutation. As a result, a variant RS1 (Y8H/Y31H/I143R/N305R) was obtained with a dramatically improved preference for the synthesis of l-syn-3-4-(methylsulfonyl)phenylserine. The product with a de value of 99.5% (73.2% conv) was produced in a 20 L reactor, which is promising in the industrial synthesis of aromatic l-syn-β-hydroxy-α-amino acids with LTA. The variant also represented a significant selective improvement to other l-phenylserine derivatives. The de values of 2-NO2-, 4-NO2-, H-, and 4-CH4-substituted l-phenylserine derivatives were more than 99% syn by dynamic control. The insight of the mutant model suggests that the binding pocket of the active center was reshaped.
•A stacking ensemble (SE) method to classy urban functional region is proposed.•The SE method integrates the building and point-of-interest data.•A graph convolutional neural network is proposed to ...extract morphological features.•The SE method achieved classification accuracy of 86.83%.
The automatic classification of urban functional regions is vital for urban planning and governance. The current methods mainly rely on single remote sensing image data or social sensing data. However, these imagery-based methods have the disadvantage of capturing high-level socioeconomic features, whereas the information from social sensing data alone rarely contains the morphological features. To overcome these limitations, it is necessary to combine multisource data for sensing urban functionalities. This study presents an ensemble classification method that combines vector-based buildings and points-of-interest (POIs). For each block, we constructed an improved graph convolutional neural network (GCNN) to extract morphological features from the constituent buildings. The ‘Word2Vec’ model was used to obtain the socioeconomic characteristics of POIs. On this basis, a stacking ensemble model was designed to combine morphological and socioeconomic features for classifying the functionality of each block. The proposed method was trained and tested in Nanshan District, Shenzhen, China. The results showed a classification accuracy of 86.83%, which was 12.2%–16.1% higher than standalone applications based on single-source data. The trained models were also applied to two other districts, namely Futian and Guangming, achieving accuracies of 85.32% and 68.37%, respectively, which were 3.68%–7.79% and 3.69%–8.94% higher than those obtained using single-sourced data. Moreover, the classification accuracies of the proposed method showed improvements of 2.41%–9.76%, compared with the existing multisource data integration method in the three study areas. These results suggest that our ensemble method can effectively integrate features from different data sources and provide an alternative, higher-accuracy solution for classifying urban functional regions.
Recently, urban traffic management has encountered a paradoxical situation which is the empty carrying phenomenon for taxi drivers and the difficulty of taking a taxi for passengers. In this paper, ...through analyzing the quantitative relationship between passengers' getting on and off taxis, we propose a time-location-relationship (TLR) combined taxi service recommendation model to improve taxi drivers' profits, uncover the knowledge of human mobility patterns, and enhance passengers' travel experience. Moreover, the TLR model uses Gaussian process regression and statistical approaches to acquire passenger volume, mean trip distance, and average trip time in functional regions during every period on weekdays and weekends, and allows drivers to pick up more passengers within a short time frame. Finally, we compare our proposed model with the autoregressive integrated moving average model, the back-propagation neural network model, the support vector machine model, and the gradient boost decision tree model by using the real taxi GPS data in Beijing. The experimental results show that our optimizing taxi service recommendation can predict more accurately than others by considering the 3-D properties.
The primary objective of this study was to develop an evaluation method for assessing an urban traffic noise–exposed population and apply it in the main urban area of Guangzhou. The method based on ...points of interest (POIs) and noise map is realized in several steps. First, after regionalizing based on road networks and executing a cluster analysis for regions according to the properties of POIs, the environmental noise functional regions (NFRs) of the urban area are presented. Then, surrounding POIs are used to infer the type of buildings, and according to the attraction of different building types and the whole population of the region, the population distribution at the building level is calculated. Finally, with the help of a noise map, an evaluation method for assessing an urban traffic noise–exposed population is proposed. The method is applied in the main urban area of Guangzhou, and the results reveal the followings. 1) At daytime and nighttime, 23.63% and 30.53% of the population, respectively, experience noise levels that exceed the noise standards. The per capita noise exposure value at daytime and nighttime is 0.9 dB and 2.0 dB, respectively. 2) The percentages of the exposed population of Yuexiu District were 28.89% at daytime and 35.65% at nighttime, which are the largest, followed by the exposed population percentages of Liwan, Haizhu, and Tianhe Districts. 3) From the view of different classes of NFRs, the percentages of the exposed population of Class 1 and Class 4 are larger than the percentages of the exposed population from the other classes, especially at nighttime (48.24% of Class 1 and 40.79% of Class 4). 4) Although there are masses of people affected by traffic noise, a large percentage of them (85%) experience not more than 5 dB of traffic noise superscale.
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•Points of interest (POIs) and noise map were applied to evaluate urban traffic noise–exposed population.•High-density areas with residence-relative POIs suffer more serious exposure to noise.•Except for population, daytime or nighttime and noise functional region (NFR) classes also play important roles in the noise effect on humans.•Road-side areas and nighttime, in particular, should be paid attention.
Urban functional region classification plays an important role in urban planning, resource management and sustainable development. While previous studies have solely focused on delineating regions by ...urban morphology or deriving functional types from human activities, the sufficient depiction and integration of these characteristics are seldom discussed. This paper inherently considers both urban morphology and human activities to classify urban functional regions. Building-based and region-based landscape metrics derived from building-level blocks are delineated to measure urban morphology, while socioeconomic features are extracted from crowdsourced data related to human activities using a topic model and semantic scaling method. These characteristics are then fused by applying random forest to measure different functions. This approach is tested in Futian district, Shenzhen, Guangdong. The result shows an overall classification accuracy of 0.818, approximately 0.15 higher than that utilising only landscape metrics or only socioeconomic features. This result indicates the effectiveness of the delineated characteristics to depict urban landscapes and socioeconomic information and the reliability of integrating these features for urban functional region classification.
•An urban functional region classification approach is presented involving landscape metrics and socioeconomic features.•Building-based and region-based landscape metrics are delineated from building-level blocks.•Socioeconomic features are extracted and semantically scaled from crowdsourced data.•Comparative experiments with landscape metrics or socioeconomic features prove the effectiveness of theproposed approach.
This paper introduces a way to study the reproduction of (the identity of) a region through the concept of perceptual region. Perceptual region-revised here in light of the institutionalization of ...regions theory and thus comprehended as the subjective image of a region in the mind of an individual person-connects certain 'European' and 'American' regional traditions. Investigating the institutions imprinted in perceptual regions exposes on what basis people construct regions and what (re)produces such regions. This case study deals with the perception of the Bohemian-Moravian boundary in the minds of 454 borderland inhabitants, surveyed with questionnaires. Among the revealed institutions of the former administrative regions of Bohemia and Moravia, there are various formal/homogeneous and functional regions as well as their boundaries-they all reproduce the examined regions. Besides demonstrating that regions are multiple realities (where both space and time matter), social constructs, and dynamic processes, the article discusses the interrelationship of the abovementioned region types and highlights perceptual regions as essential for the region's existence. Furthermore, it suggests that focusing on ordinary people's perceptions may develop knowledge not only about the concept of region but also the concepts of the regional identity of people, resistance identity, and regionalism.
Herpesviridae comprise a large family of enveloped DNA viruses all of whom employ orthologs of the same three glycoproteins, gB, gH and gL. Additionally, herpesviruses often employ accessory proteins ...to bind receptors and/or bind the heterodimer gH/gL or even to determine cell tropism. Sorting out how these proteins function has been resolved to a large extent by structural biology coupled with supporting biochemical and biologic evidence. Together with the G protein of vesicular stomatitis virus, gB is a charter member of the Class III fusion proteins. Unlike VSV G, gB only functions when partnered with gH/gL. However, gH/gL does not resemble any known viral fusion protein and there is evidence that its function is to upregulate the fusogenic activity of gB. In the case of herpes simplex virus, gH/gL itself is upregulated into an active state by the conformational change that occurs when gD, the receptor binding protein, binds one of its receptors. In this review we focus primarily on prototypes of the three subfamilies of herpesviruses. We will present our model for how herpes simplex virus (HSV) regulates fusion in series of highly regulated steps. Our model highlights what is known and also provides a framework to address mechanistic questions about fusion by HSV and herpesviruses in general.
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