Deep trip generation with graph neural networks for bike sharing system expansion

Bike sharing is emerging globally as an active, convenient, and sustainable mode of transportation. To plan successful bike-sharing systems (BSSs), many cities start from a small-scale pilot and gradually expand the system to cover more areas. For station-based BSSs, this means planning new stations based on existing ones over time, which requires prediction of the number of trips generated by these new stations across the whole system. Previous studies typically rely on relatively simple regression or machine learning models, which are limited in capturing complex spatial relationships. Despite the growing literature in deep learning methods for travel demand prediction, they are mostly developed for short-term prediction based on time series data, assuming no structural changes to the system. In this study, we focus on the trip generation problem for BSS expansion, and propose a graph neural network (GNN) approach to predicting the station-level demand based on multi-source urban built environment data. Specifically, it constructs multiple localized graphs centered on each target station and uses attention mechanisms to learn the correlation weights between stations. We further illustrate that the proposed approach can be regarded as a generalized spatial regression model, indicating the commonalities between spatial regression and GNNs. The model is evaluated based on realistic experiments using multi-year BSS data from New York City, and the results validate the superior performance of our approach compared to existing methods. We also demonstrate the interpretability of the model for uncovering the effects of built environment features and spatial interactions between stations, which can provide strategic guidance for BSS station location selection and capacity planning

Preparation and characterization of mortar mixes containing organic acid/expanded vermiculite composite PCM

In this paper, capric acid (CA) and palmitic acid (PA) binary PCM/expanded vermiculite (CA-PA/EVM) form stable composite PCM (FS-CPCM) was firstly synthesized by adsorption method. The EVM had the optimal adsorption rate when the mass ratio of CA-PA to EVM was 45:55. The FT-IR results indicated that there was no chemical reaction between binary PCM and EVM. After the thermal cycles for 50 times, the mass loss of the prepared CA-PA/EVM FS-CPCM was 2.8%. However, the latent heat was reduced by 16.10%. Furthermore, thermal energy storage (TES) mortar mixes were prepared by replacing sand aggregates with the fabricated CA-PA/EVM FS-CPCM. The effect of replacing sand aggregates with CA-PA/EVM FS-CPCM on compressive and flexural strength of the mortar mixes was investigated by mechanical experiments. The prepared mortar mixes with CA-PA/EVM FS-CPCMs aggregate exhibited good thermal performance and could be preferentially potential PCM for thermal regulation and energy saving in buildings

Demand, mobility, and constraints: Exploring travel behaviors and mode choices of older adults using a facility-based framework

The steady trend of aging has caused great concern on how cities should better accommodate the social needs of aged population. Older people in general have more leisure time than younger adults but are found highly constrained in daily travel. To examine the imbalance between travel demand and transport supply among older adults, this paper decomposes their daily travel into two categories (visits to non-ubiquitous and ubiquitous facilities) according to major characteristics of travel behaviors using Nanjing Household Travel Survey data. Multinominal logit (MNL) models are applied to exploit the effects of household and personal characteristics, trip characteristics, local supplies, and public transport services on travel mode choices. Results show that (i) travel demand and transport supply are highly unbalanced for most non-ubiquitous facilities, (ii) relative to younger adults, older adults travel further and highly rely on public transport to access non-ubiquitous facilities, (iii) providing more public transit services nearby non-ubiquitous facilities are more reliable to increase the accessibility of older adults than increasing the number of facilities. These results would help policy-makers better understand travel behaviors of older adults and develop strategies to accommodate their travel demand, especially from the perspective of facility network reorganization

Designing interstitial boron‐doped tunnel‐type vanadium dioxide cathode for enhancing zinc ion storage capability

Abstract Chemical doping is a powerful method to intrinsically tailor the electrochemical properties of electrode materials. Here, an interstitial boron‐doped tunnel‐type VO2(B) is constructed via a facile hydrothermal method. Various analysis techniques demonstrate that boron resides in the interstitial site of VO2(B) and such interstitial doping can boost the zinc storage kinetics and structural stability of VO2(B) cathode during cycling. Interestingly, we found that the boron doping level has a saturation limit peculiarity as proved by the quantitative analysis. Notably, the 2 at.% boron‐doped VO2(B) shows enhanced zinc ion storage performance with a high storage capacity of 281.7 mAh g−1 at 0.1 A g−1, excellent rate performance of 142.2 mAh g−1 at 20 A g−1, and long cycle stability up to 1000 cycles with the capacity retention of 133.3 mAh g−1 at 5 A g−1. Additionally, the successful preparation of the boron‐doped tunnel‐type α‐MnO2 further indicates that the interstitial boron doping approach is a general strategy, which supplies a new chance to design other types of functional electrode materials for multivalence batteries

The Discrimination and Characterization of Volatile Organic Compounds in Different Areas of <i>Zanthoxylum bungeanum</i> Pericarps and Leaves by HS-GC-IMS and HS-SPME-GC-MS

The pericarps of Zanthoxylum bungeanum (ZBP) and leaves of Zanthoxylum bungeanum (ZBL) are popular spices in China, and they have pharmacological activities as well. In this experiment, the volatile organic compounds (VOCs) of the pericarps of Zanthoxylum bungeanum in Sichuan (SJ) and its leaves (SJY) and the pericarps of Zanthoxylum bungeanum in Shaanxi (SHJ) and its leaves (SHJY) were analyzed by headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). The fingerprint of HS-GC-IMS and the heat maps of HS-SPME-GC-MS were established. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed. The results showed that a total of 95 components were identified, 62 components identified by HS-SPME-GC-MS and 40 components identified by HS-GC-IMS, of which 7 were the same. The analysis found that SJ and SHJ were obviously distinguished, while SJY and SHJY were not. There were considerably fewer VOCs in the leaves than in the pericarps. In the characterization of the VOCs of ZBL and ZBP, the flavor of ZBP was more acrid and stronger, while the flavor of ZBL was lighter and slightly acrid. Thirteen and eleven differential markers were identified by HS-GC-IMS and HS-SPME-GC-MS, respectively. This is helpful in distinguishing between SHJ and SJ, which contributes to their quality evaluation

Characterization of the key volatile organic components of different parts of fresh and dried perilla frutescens based on headspace-gas chromatography-ion mobility spectrometry and headspace solid phase microextraction-gas chromatography-mass spectrometry

Perilla frutescens was an annual herb considered as one of the “One Root of Medicine and Food”, and it was used widely for food and medical treatment. Its main active ingredients were volatile organic compounds (VOCs), but it was easily affected during drying and storage. The leaves, seeds and stems had shown differences in therapeutic effects, but the underlying reason remained unclear. In the present work, headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC–MS) were utilized to effectively and comprehensively analyze VOCs of fresh and dried P. frutescens between the leaves, stems and seeds. Meanwhile, chemometric analysis was applied to compare and identify characteristic volatile markers. As a result, 60 VOCs were identified by HS-GC-IMS and 115 VOCs were identified by HS-SPME-GC–MS from P. frutescen. 25 potential volatile markers were selected based on a combination model of orthogonal partial least squares discriminant analysis (OPLS-DA) and random forest (RF). The models could be used to analyze the variation between fresh and dried P. frutescens and distinguish the differences in different parts effectively and comprehensively. It was the first research regarding the method development of HS-GC-IMS and HS-SPME-GC–MS that comprehensively analyzes the VOCs characterization of fresh and dried P. frutescens in different parts and the findings obtained would evaluate the quality and provide a reference for further exploration of the edible and medicinal effects of P. frutescens