Redesign of the Restrainer band for a Horse Leg Protective Device Based on a Static Analysis

A horse leg orthosis employing a restrainer band is designed to prevent metacarpo-phalangeal joint (MCPJ) hyperextension of horse forelimb. Current band design by Manta Design Inc. produces inconsistent tensions and inadequately protects the forelimb. The goal was to improve the restrainer band design using a static analysis at MCPJ. Band length, cross-sectional area and stiffness effects were studied to meet the tension specifications from the static analysis. The improved restrainer band achieves an 8.4% MCPJ moment reduction at maximum extension

Photoinduced High-Chern-Number Quantum Anomalous Hall Effect from Higher-Order Topological Insulators

Quantum anomalous Hall (QAH) insulators with high Chern number host multiple dissipationless chiral edge channels, which are of fundamental interest and promising for applications in spintronics and quantum computing. However, only a limited number of high-Chern-number QAH insulators have been reported to date. Here, we propose a dynamic approach for achieving high-Chern-number QAH phases in periodically driven two-dimensional higher-order topological insulators (HOTIs).In particular, we consider two representative kinds of HOTIs which are characterized by a quantized quadruple moment and the second Stiefel-Whitney number, respectively. Using the Floquet formalism for periodically driven systems, we demonstrate that QAH insulators with tunable Chern number up to four can be achieved. Moreover, we show by first-principles calculations that the monolayer graphdiyne, a realistic HOTI, is an ideal material candidate. Our work not only establishes a strategy for designing high-Chern-number QAH insulators in periodically driven HOTIs, but also provides a powerful approach to investigate exotic topological states in nonequilibrium cases.Comment: 6 pages, 3 figure

AIDS Project Worcester: Energy Cost Reduction Approaches

For the past 10-15 years, the HIV/AIDS population in Worcester increases by 15% annually. As a non-profit organization which supplies non- medical services to those affected by HIV/AIDS; AIDS Project Worcester, Inc. (APW) has a demand for greater funding. In order to sustain the client services, lowering operating costs is necessary. Installing a new roof and implementing green technology, like solar panels, are ways to reduce energy costs. We found by implementing 35 kW photovoltaic system, APW is able to save $960 per month, which is 42.3% of their energy bill

BatmanNet: Bi-branch Masked Graph Transformer Autoencoder for Molecular Representation

Although substantial efforts have been made using graph neural networks (GNNs) for AI-driven drug discovery (AIDD), effective molecular representation learning remains an open challenge, especially in the case of insufficient labeled molecules. Recent studies suggest that big GNN models pre-trained by self-supervised learning on unlabeled datasets enable better transfer performance in downstream molecular property prediction tasks. However, they often require large-scale datasets and considerable computational resources, which is time-consuming, computationally expensive, and environmentally unfriendly. To alleviate these limitations, we propose a novel pre-training model for molecular representation learning, Bi-branch Masked Graph Transformer Autoencoder (BatmanNet). BatmanNet features two tailored and complementary graph autoencoders to reconstruct the missing nodes and edges from a masked molecular graph. To our surprise, BatmanNet discovered that the highly masked proportion (60%) of the atoms and bonds achieved the best performance. We further propose an asymmetric graph-based encoder-decoder architecture for either nodes and edges, where a transformer-based encoder only takes the visible subset of nodes or edges, and a lightweight decoder reconstructs the original molecule from the latent representation and mask tokens. With this simple yet effective asymmetrical design, our BatmanNet can learn efficiently even from a much smaller-scale unlabeled molecular dataset to capture the underlying structural and semantic information, overcoming a major limitation of current deep neural networks for molecular representation learning. For instance, using only 250K unlabelled molecules as pre-training data, our BatmanNet with 2.575M parameters achieves a 0.5% improvement on the average AUC compared with the current state-of-the-art method with 100M parameters pre-trained on 11M molecules.Comment: 11 pages, 3 figure

Renal cell carcinoma of different pathological types in bilateral native kidneys of a kidney transplant recipient: A case report and literature review

Patients after kidney transplantation have a much higher risk of developing malignant tumors than the general population. And the native kidney is an organ relatively susceptible to malignant tumors after renal transplantation. However, the simultaneous development of bilateral renal tumors is very rare; especially the bilateral native kidneys harbor different pathological types of renal cell carcinoma (RCC). We report a case of a patient who developed malignant tumors in both native kidneys nearly 19 years after renal transplantation. This patient underwent bilateral laparoscopic radical nephrectomy, and postoperative pathological examination showed clear cell RCC on the left native kidney and papillary RCC on the right one. And the early detection and surgical treatment resulted in a good prognosis. The literature related to the diagnosis and treatment of bilateral RCC after renal transplantation is also reviewed

The Ninth Visual Object Tracking VOT2021 Challenge Results

acceptedVersionPeer reviewe

Experimental Investigation on Flame Characterization and Temperature Profile of Single/Multiple Pool Fire in Cross Wind

An experimental study was carried out to investigate the flame characterization and temperature profile for single and multiple pool fire with the influence of cross wind. There were 13 test cases in total, categorized into circle and rectangle fuel pans, with diameter (or equivalent diameter) ranged from 50 mm to 300 mm. Kerosene was used for the fuel of pool fire. Some K-type thermocouples were arranged around the flame to monitor the flame temperature, while the flame tilt angle was measured based on the photograph of flame for different case. Firstly, it can be found that there are three phases, including preheating, steady burning and extinguishing phase, during the flame evolution. The maximum temperature near the fuel surface is similar to 1040 K, which is higher than that of flame plume (similar to 600 K), in the steady burning phase of circle single pool fire (D=300 mm), while the average burning rate is similar to 1.525 g/s. In addition, the burning rates of all cases were measured and compared with the current predicted method. Typically, the flame morphology of single/multiple pool fire at different cross wind speed (ranging from 0 to 3.5 m/s) was analyzed, and it is found that the results for single pool fire agree with Thomas model and AGA model well, which are not suitable for multiple pool fire. Finally, the temperature profile of different case was measured with various wind speed