UrbanFM: Inferring Fine-Grained Urban Flows

Urban flow monitoring systems play important roles in smart city efforts around the world. However, the ubiquitous deployment of monitoring devices, such as CCTVs, induces a long-lasting and enormous cost for maintenance and operation. This suggests the need for a technology that can reduce the number of deployed devices, while preventing the degeneration of data accuracy and granularity. In this paper, we aim to infer the real-time and fine-grained crowd flows throughout a city based on coarse-grained observations. This task is challenging due to two reasons: the spatial correlations between coarse- and fine-grained urban flows, and the complexities of external impacts. To tackle these issues, we develop a method entitled UrbanFM based on deep neural networks. Our model consists of two major parts: 1) an inference network to generate fine-grained flow distributions from coarse-grained inputs by using a feature extraction module and a novel distributional upsampling module; 2) a general fusion subnet to further boost the performance by considering the influences of different external factors. Extensive experiments on two real-world datasets, namely TaxiBJ and HappyValley, validate the effectiveness and efficiency of our method compared to seven baselines, demonstrating the state-of-the-art performance of our approach on the fine-grained urban flow inference problem

Being a morning man has causal effects on the cerebral cortex: a Mendelian randomization study

IntroductionNumerous studies have suggested a connection between circadian rhythm and neurological disorders with cognitive and consciousness impairments in humans, yet little evidence stands for a causal relationship between circadian rhythm and the brain cortex.MethodsThe top 10,000 morningness-related single-nucleotide polymorphisms of the Genome-wide association study (GWAS) summary statistics were used to filter the instrumental variables. GWAS summary statistics from the ENIGMA Consortium were used to assess the causal relationship between morningness and variates like cortical thickness (TH) or surficial area (SA) on the brain cortex. The inverse-variance weighted (IVW) and weighted median (WM) were used as the major estimates whereas MR-Egger, MR Pleiotropy RESidual Sum and Outlier, leave-one-out analysis, and funnel-plot were used for heterogeneity and pleiotropy detecting.ResultsRegionally, morningness decreased SA of the rostral middle frontal gyrus with genomic control (IVW: β = −24.916 mm, 95% CI: −47.342 mm to −2.490 mm, p = 0.029. WM: β = −33.208 mm, 95% CI: −61.933 mm to −4.483 mm, p = 0.023. MR Egger: β < 0) and without genomic control (IVW: β = −24.581 mm, 95% CI: −47.552 mm to −1.609 mm, p = 0.036. WM: β = −32.310 mm, 95% CI: −60.717 mm to −3.902 mm, p = 0.026. MR Egger: β < 0) on a nominal significance, with no heterogeneity or no outliers.Conclusions and implicationsCircadian rhythm causally affects the rostral middle frontal gyrus; this sheds new light on the potential use of MRI in disease diagnosis, revealing the significance of circadian rhythm on the progression of disease, and might also suggest a fresh therapeutic approach for disorders related to the rostral middle frontal gyrus-related

Fine-Grained Urban Flow Inference

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERIN

Cell blebbing upon addition of cryoprotectants: a self-protection mechanism.

In this work, the mechanism of cell bleb formation upon the addition of cryoprotectants (CPAs) was investigated, and the role of cell blebs in protecting cells was determined. The results show that after adding CPAs, the hyperosmotic stress results in the breakage of the cortical cytoskeleton and the detachment of the cell membrane from the cortical cytoskeleton, causing the formation of cell blebs. Multiple blebs decrease the intracellular hydrostatic pressure induced by the extracellular hyperosmotic shock and alleviate the osmotic damage to cells, which reduces the cell mortality rate. In the presence of a low concentration of CPAs, cell blebs can effectively protect cells. In contrast, in the presence of a high concentration of CPAs, the protective effect is limited because of severe disruption in the cortical cytoskeleton. To determine the relationship between blebs and the mortality rate of cells, we defined a bleb index and found that the bleb index of 0.065 can be regarded as a reference value for the safe addition of DMSO to HeLa cells. The bleb index can also explain why the stepwise addition of CPAs is better than the single-step addition of CPAs. Moreover, the mechanism of the autophagy of cells induced by the hyperosmotic stress was studied, and the protective effect associated with the autophagy was compared with the effect of the blebbing. The findings reported here elucidate a self-protection mechanism of cells experiencing the hyperosmotic stress in the presence of CPAs, and they provide significant evidence for cell tolerance in the field of cryopreservation

Learning to generate maps from trajectories

Accurate and updated road network data is vital in many urban applications, such as car-sharing, and logistics. The traditional approach to identifying the road network, ie, field survey, requires a significant amount of time and effort. With the wide usage of GPS embedded devices, a huge amount of trajectory data has been generated by different types of mobile objects, which provides a new opportunity to extract the underlying road network. However, the existing trajectory-based map recovery approaches require many empirical parameters and do not utilize the prior knowledge in existing maps, which over-simplifies or over-complicates the reconstructed road network. To this end, we propose a deep learning-based map generation framework, ie, DeepMG, which learns the structure of the existing road network to overcome the noisy GPS positions. More specifically, DeepMG extracts features from trajectories in both spatial view and transition view and uses a convolutional deep neural network T2RNet to infer road centerlines. After that, a trajectory-based post-processing algorithm is proposed to refine the topological connectivity of the recovered map. Extensive experiments on two real-world trajectory datasets confirm that DeepMG significantly outperforms the state-of-the-art methods.Ministry of Education (MOE)Nanyang Technological UniversityAccepted versionThe research of Cheng Long was supported by the NTU Start-Up Grant and Singapore MOE Tier 1 Grant RG20/19 (S)

Doing in one go : delivery time inference based on couriers' trajectories

The rapid development of e-commerce requires efficient and reliable logistics services. Nowadays, couriers are still the main solution to address the "last mile" problem in logistics. They are usually required to record the accurate delivery time of each parcel manually, which provides vital information for applications like delivery insurances, delivery performance evaluations, and customer available time discovery. Couriers' trajectories generated by their PDAs provide a chance to infer the delivery time automatically to ease the burdens on the couriers. However, directly using the nearest stay point to infer the delivery time is under satisfactory due to two challenges: 1) inaccurate delivery locations, and 2) various stay scenarios. To this end, we propose Delivery Time Inference (DTInf), to automatically infer the delivery time of waybills based on couriers' trajectories. Our solution is composed of three steps: 1) Data Pre-processing, which detects stay points from trajectories, and separates stay points and waybills by delivery trips, 2) Delivery Location Correction, which infers true delivery locations of waybills by mining historical deliveries, and 3) Delivery Event-based Matching, which selects the best-matched stay point for waybills in the same delivery location to infer the delivery time. Extensive experiments and case studies based on large scale real-world waybill and trajectory data from JD Logistics confirm the effectiveness of our approach. Finally, we introduce a system based on DTInf, which is deployed and used internally in JD Logistics.Ministry of Education (MOE)Nanyang Technological UniversityAccepted versionThis work was also supported by the Nanyang Technological University Start-UP Grant from the College of Engineering under Grant M4082302 and by the Ministry of Education, Singapore, under its Academic Research Fund Tier 1 (RG20/19 (S))

Table_1_Being a morning man has causal effects on the cerebral cortex: a Mendelian randomization study.XLSX

IntroductionNumerous studies have suggested a connection between circadian rhythm and neurological disorders with cognitive and consciousness impairments in humans, yet little evidence stands for a causal relationship between circadian rhythm and the brain cortex.MethodsThe top 10,000 morningness-related single-nucleotide polymorphisms of the Genome-wide association study (GWAS) summary statistics were used to filter the instrumental variables. GWAS summary statistics from the ENIGMA Consortium were used to assess the causal relationship between morningness and variates like cortical thickness (TH) or surficial area (SA) on the brain cortex. The inverse-variance weighted (IVW) and weighted median (WM) were used as the major estimates whereas MR-Egger, MR Pleiotropy RESidual Sum and Outlier, leave-one-out analysis, and funnel-plot were used for heterogeneity and pleiotropy detecting.ResultsRegionally, morningness decreased SA of the rostral middle frontal gyrus with genomic control (IVW: β = −24.916 mm, 95% CI: −47.342 mm to −2.490 mm, p = 0.029. WM: β = −33.208 mm, 95% CI: −61.933 mm to −4.483 mm, p = 0.023. MR Egger: β Conclusions and implicationsCircadian rhythm causally affects the rostral middle frontal gyrus; this sheds new light on the potential use of MRI in disease diagnosis, revealing the significance of circadian rhythm on the progression of disease, and might also suggest a fresh therapeutic approach for disorders related to the rostral middle frontal gyrus-related.</p

The autophagy induced by the addition of CPAs.

<p><b>(A)</b> GFP-LC3/HeLa cells were treated with various concentrations of DMSO, and GFP green fluorescence dots appeared in cells. <b>(B)</b> LC3 conversion was determined by western blot in HeLa cells treated with different concentrations of DMSO. <b>(C)</b> Effect of DMSO on the autophagy rate. <b>(D)</b> GFP-LC3 /HeLa cells were inhibited by 3-MA, and then stimulated by 30% DMSO. Shrinkage of cell nuclei is a hallmark of apoptosis. <b>(E)</b> Autophagy reduced the apoptosis in the presence of 30% DMSO. **p<0.01 was considered statistically significant. The experiments were repeated 5 times. The number of cells used was approximately 500.</p