Comparison of efficacy and safety of three different drugs combined with radiotherapy in the treatment of patients with advanced pancreatic cancer

Purpose: To investigate the clinical efficacy and safety of three different drugs combined with radiotherapy, viz, apatinib mesylate combined radiotherapy (group A), gemcitabine combined oxaliplatin (group B), and Huachansu capsules combined radiotherapy (group C)] in advanced pancreatic cancer patients. Methods: A total of 174 patients with advanced pancreatic cancer treated in Yantai Qishan Hospital, Yantai, China from June 2015 to December 2016 were randomly and evenly divided into groups A, B, and C. The incidence of adverse reactions during treatment, immune reaction, efficacy, quality of life, and survival were compared among the three groups after four courses of treatment. Results: Compared with groups B and C, the incidence of nausea and vomiting was higher in group A (p < 0.05), but the incidence of other adverse events was not significantly different (p > 0.05). Group A showed higher response rate and disease control rate, higher CD4+, CD4+/CD8+ levels and QOL scores, as well as lower CD8+ level in peripheral blood after treatment than groups B and C (p < 0.05). Group A also exhibited longer median OS and median PFS, and higher 2-year survival than groups B and C (p < 0.05). Conclusion: Among the three different drug treatments combined with radiotherapy, apatinib mesylate combined radiotherapy enhanced efficacy and quality of life, and lengthen the survival time of advanced pancreatic cancer patients. However, additional clinical trials are required to validate these findings

Parsing is All You Need for Accurate Gait Recognition in the Wild

Binary silhouettes and keypoint-based skeletons have dominated human gait recognition studies for decades since they are easy to extract from video frames. Despite their success in gait recognition for in-the-lab environments, they usually fail in real-world scenarios due to their low information entropy for gait representations. To achieve accurate gait recognition in the wild, this paper presents a novel gait representation, named Gait Parsing Sequence (GPS). GPSs are sequences of fine-grained human segmentation, i.e., human parsing, extracted from video frames, so they have much higher information entropy to encode the shapes and dynamics of fine-grained human parts during walking. Moreover, to effectively explore the capability of the GPS representation, we propose a novel human parsing-based gait recognition framework, named ParsingGait. ParsingGait contains a Convolutional Neural Network (CNN)-based backbone and two light-weighted heads. The first head extracts global semantic features from GPSs, while the other one learns mutual information of part-level features through Graph Convolutional Networks to model the detailed dynamics of human walking. Furthermore, due to the lack of suitable datasets, we build the first parsing-based dataset for gait recognition in the wild, named Gait3D-Parsing, by extending the large-scale and challenging Gait3D dataset. Based on Gait3D-Parsing, we comprehensively evaluate our method and existing gait recognition methods. The experimental results show a significant improvement in accuracy brought by the GPS representation and the superiority of ParsingGait. The code and dataset are available at https://gait3d.github.io/gait3d-parsing-hp .Comment: 16 pages, 14 figures, ACM MM 2023 accepted, project page: https://gait3d.github.io/gait3d-parsing-h

A new classification system of lithic-rich tight sandstone and its application to diagnosis high-quality reservoirs

        Lithic-rich tight sandstone is one of the most enrichment lithofacies in the Sulige gas field. Clarifying the enrichment mechanism of high-quality lithic-rich tight sandstone is important to economic and efficient development of the tight gas reservoir. This paper introduces a new classification method, which is based on the origin of particles and interstitial materials and their control on reservoir pores growth. Lithic-rich tight sandstone can be subdivided into three types: sedimentary lithic sandstone, diagenetic lithic sandstone and event-type lithic sandstone. The genetic mechanism of a high-quality reservoir is studied by this new method. Research shows that the sedimentary lithic sandstone has high contents of plastic lithics, strong compaction effects of early diagenesis, large porosity reduction and almost no dissolution-induced porosity. The diagenetic lithic sandstone has high contents of rigid lithics and strong compaction effects. Organic acids promote alteration of a large amount of feldspars into kaolinite, while such sandstones are highly cemented. It is seen with moderate porosity reduction and moderate dissolution-attributed porosity growth. Event-type lithic sandstone also has high contents of rigid debris and strong compaction effects. Synsedimentary volcanic dust materials of subaerial deposition are altered into illite through smectite and illite-smectite mixed-layer clay under the effects of acids, which generate many pores and results in large dissolution-attributed porosity growth. Research shows that the sedimentary lithic sandstone has poor physical properties and is identified as the unfavorable reservoir; the diagenetic lithic sandstone having medium physical properties, as the relatively favorable reservoir; the event-type lithic sandstone having good physical properties, as the favorable reservoir. The research route and results have laid a solid geological foundation for better development of lithic-rich tight sandstone reservoirs.Cited as: Liu, Y., Xian, C., Li, Z., Wang, J., Ren, F. A new classification system of lithic-rich tight sandstone and its application to diagnosis high-quality reservoirs. Advances in Geo-Energy Research, 2020, 4(3): 286-295, doi: 10.46690/ager.2020.03.0

Carbon Stocks across a Fifty Year Chronosequence of Rubber Plantations in Tropical China

Transition from forest to rubber (Hevea brasiliensis Muell. Arg.) plantation has occurred in tropical China for decades. Rubber has been planted on 1 million ha to provide raw materials to the rubber industry. The role of various-aged rubber plantations in carbon (C) sequestration remains unclear. The biomass C accumulation including latex C and C distribution in soil of five different-aged stands (7, 13, 19, 25 and 47 years old) were examined. The total biomass C stock (TBC) and total net primary productivity (NPPtotal), whether with or without latex C, had a close quadratic relationship with stand age. Regardless of stand age, around 68% of the C was stored in aboveground biomass, and NPPlatex contributed to approximately 18% of C sequestration. Soil organic carbon stock in the 100-cm depth remained relatively stable, but it lost about 16.8 Mg ha−1 with stand age. The total ecosystem C stock (TEC) across stands averaged 159.6, 174.4, 229.6, 238.1 and 291.9 Mg ha−1, respectively, of which more than 45% was stored in the soil. However, biomass would become the major C sink rather than soil over a maximal rubber life expectancy. Regression analysis showed that TEC for rubber plantation at 22 years is comparable to a baseline of 230.4 Mg ha−1 for tropical forest in China, and would reach the maximum value at around 54 years. Therefore, rubber plantation can be considered as alternative land use without affecting net forest ecosystem C storage. In addition to the potential C gains, a full set of ecosystem and economic properties have to be quantified in order to assess the trade-offs associated with forest-to-rubber transition

Underwater motions analysis and control of a coupling-tiltable unmanned aerial-aquatic quadrotor

This paper proposes a method for analyzing a series of potential motions in a coupling-tiltable aerial-aquatic quadrotor based on its nonlinear dynamics. Some characteristics and constraints derived by this method are specified as Singular Thrust Tilt Angles (STTAs), utilizing to generate motions including planar motions. A switch-based control scheme addresses issues of control direction uncertainty inherent to the mechanical structure by incorporating a saturated Nussbaum function. A high-fidelity simulation environment incorporating a comprehensive hydrodynamic model is built based on a Hardware-In-The-Loop (HITL) setup with Gazebo and a flight control board. The experiments validate the effectiveness of the absolute and quasi planar motions, which cannot be achieved by conventional quadrotors, and demonstrate stable performance when the pitch or roll angle is activated in the auxiliary control channel.Comment: Unmanned Aerial-Aquatic Vehicl

Adaptive Resource Allocation for Workflow Containerization on Kubernetes

In a cloud-native era, the Kubernetes-based workflow engine enables workflow containerized execution through the inherent abilities of Kubernetes. However, when encountering continuous workflow requests and unexpected resource request spikes, the engine is limited to the current workflow load information for resource allocation, which lacks the agility and predictability of resource allocation, resulting in over and under-provisioning resources. This mechanism seriously hinders workflow execution efficiency and leads to high resource waste. To overcome these drawbacks, we propose an adaptive resource allocation scheme named ARAS for the Kubernetes-based workflow engines. Considering potential future workflow task requests within the current task pod's lifecycle, the ARAS uses a resource scaling strategy to allocate resources in response to high-concurrency workflow scenarios. The ARAS offers resource discovery, resource evaluation, and allocation functionalities and serves as a key component for our tailored workflow engine (KubeAdaptor). By integrating the ARAS into KubeAdaptor for workflow containerized execution, we demonstrate the practical abilities of KubeAdaptor and the advantages of our ARAS. Compared with the baseline algorithm, experimental evaluation under three distinct workflow arrival patterns shows that ARAS gains time-saving of 9.8% to 40.92% in the average total duration of all workflows, time-saving of 26.4% to 79.86% in the average duration of individual workflow, and an increase of 1% to 16% in CPU and memory resource usage rate