Unsupervised Path Representation Learning with Curriculum Negative Sampling

Path representations are critical in a variety of transportation applications, such as estimating path ranking in path recommendation systems and estimating path travel time in navigation systems. Existing studies often learn task-specific path representations in a supervised manner, which require a large amount of labeled training data and generalize poorly to other tasks. We propose an unsupervised learning framework Path InfoMax (PIM) to learn generic path representations that work for different downstream tasks. We first propose a curriculum negative sampling method, for each input path, to generate a small amount of negative paths, by following the principles of curriculum learning. Next, \emph{PIM} employs mutual information maximization to learn path representations from both a global and a local view. In the global view, PIM distinguishes the representations of the input paths from those of the negative paths. In the local view, \emph{PIM} distinguishes the input path representations from the representations of the nodes that appear only in the negative paths. This enables the learned path representations to encode both global and local information at different scales. Extensive experiments on two downstream tasks, ranking score estimation and travel time estimation, using two road network datasets suggest that PIM significantly outperforms other unsupervised methods and is also able to be used as a pre-training method to enhance supervised path representation learning.Comment: This paper has been accepted by IJCAI-2

High channel count and high precision channel spacing multi-wavelength laser array for future PICs

Multi-wavelength semiconductor laser arrays (MLAs) have wide applications in wavelength multiplexing division (WDM) networks. In spite of their tremendous potential, adoption of the MLA has been hampered by a number of issues, particularly wavelength precision and fabrication cost. In this paper, we report high channel count MLAs in which the wavelengths of each channel can be determined precisely through low-cost standard μm-level photolithography/holographic lithography and the reconstruction-equivalent-chirp (REC) technique. 60-wavelength MLAs with good wavelength spacing uniformity have been demonstrated experimentally, in which nearly 83% lasers are within a wavelength deviation of ±0.20 nm, corresponding to a tolerance of ±0.032 nm in the period pitch. As a result of employing the equivalent phase shift technique, the single longitudinal mode (SLM) yield is nearly 100%, while the theoretical yield of standard DFB lasers is only around 33.3%

Tubeimoside-1 up-regulates p21 expression and induces apoptosis and G2/M phase cell cycle arrest in human bladder cancer T24 cells

Tubeimoside-1 (TBMS1) is a triterpenoid saponin with potent anticancer properties. In this study, for the first, we examined the anti-proliferative effects of TBMS1 in human bladder cancer T24 cells and its ability to induce apoptosis and cell cycle arrest. Our results demonstrated that TBMS1 decreased the cell viability of bladder cancer T24 cells in a dose-dependent manner. Flow cytometric analysis showed that TBMS1 significantly triggered apoptosis in T24 cells and arrested cell cycle at G2/M phase in a dose-dependent manner. Further characterization demonstrated that TBMS1-induced apoptosis is associated with dissipation in mitochondrial membrane potential (??m), down-regulation of Bcl-2, and up-regulation of Bax and p21 in TBMS1-treated T24 cells. These in vitro results suggested that TBMS1 is an effective anti-bladder cancer natural compound that worth further mechanistic and therapeutic studies in human bladder cancer

The Structural, Electronic, and Optical Properties of Ge/Si Quantum Wells: Lasing at a Wavelength of 1550 nm

The realization of a fully integrated group IV electrically driven laser at room temperature is an essential issue to be solved. We introduced a novel group IV side-emitting laser at a wavelength of 1550 nm based on a 3-layer Ge/Si quantum well (QW). By designing this scheme, we showed that the structural, electronic, and optical properties are excited for lasing at 1550 nm. The preliminary results show that the device can produce a good light spot shape convenient for direct coupling with the waveguide and single-mode light emission. The laser luminous power can reach up to 2.32 mW at a wavelength of 1550 nm with a 300-mA current. Moreover, at room temperature (300 K), the laser can maintain maximum light power and an ideal wavelength (1550 nm). Thus, this study provides a novel approach to reliable, efficient electrically pumped silicon-based lasers

Molecular/Nanomechanical Insights into Electrostimulation‐Inhibited Energy Metabolism Mechanisms and Cytoskeleton Damage of Cancer Cells

Abstract Inhibiting energy metabolism of cancer cells is an effective way to treat cancer but remains a great challenge. Herein, electrostimulation (ES) is applied to effectively suppress energy metabolism of cancer cells to induce rapid cell death, and deeply reveal the underlying mechanisms at the molecular and nanomechanical levels by combined use of fluorescence imaging and atomic force microscopy. Cancer cells are found significantly less tolerant to ES than normal cells; and ES causes “domino effect” to induce mitochondrial dysfunction to impede electron transport chain (ETC) and tricarboxylic acid (TCA) cycle pathways, leading to fatal energy‐supply crisis and death of cancer cells. From the perspective of cell mechanics, the Young's modulus decreases and cytoskeleton destruction of MCF‐7 cell membranes caused by F‐actin depolymerization occurs, along with down‐regulation and sporadic distribution of glucose transporter 1 (GLUT1) after ES. Such a double whammy renders ES highly effective and promising for potential clinical cancer treatments

Pose-Guided Part-Based Adaptive Pyramid Features for Occluded Person Reidentification

Reidentifying an occluded person across nonoverlapping cameras is still a challenging task. In this work, we propose a novel pose-guided part-based adaptive pyramid neural network for occluded person reidentification. Firstly, to alleviate the impact of occlusion, we utilize pose landmarks to generate pose-guided attention maps. The attention maps will help the model focus on the nonoccluded regions. Secondly, we use pyramid pooling to extract multiscale features in order to address the scale variation problem. The generated pyramid features are then multiplied by attention maps to achieve pose-guided adaptive pyramid features. Thirdly, we propose a pose-guided body part partition scheme to deal with the alignment problem. Accordingly, the adaptive pyramid features are divided into partitions and fed into individual fully connected layers. In the end, all the part-based matching scores are fused with a weighted sum rule for person reidentification. The effectiveness of our method is clearly validated by the experimental results on two popular occluded and holistic datasets, i.e., Occluded-DukeMTMC and the Market-1501