127 research outputs found
An Enhanced Erasure Code-Based Security Mechanism for Cloud Storage
Cloud computing offers a wide range of luxuries, such as high performance, rapid elasticity, on-demand self-service, and low cost. However, data security continues to be a significant impediment in the promotion and popularization of cloud computing. To address the problem of data leakage caused by unreliable service providers and external cyber attacks, an enhanced erasure code-based security mechanism is proposed and elaborated in terms of four aspects: data encoding, data transmission, data placement, and data reconstruction, which ensure data security throughout the whole traversing into cloud storage. Based on the mechanism, we implement a secure cloud storage system (SCSS). The key design issues, including data division, construction of generator matrix, data encoding, fragment naming, and data decoding, are also described in detail. Finally, we conduct an analysis of data availability and security and performance evaluation. Experimental results and analysis demonstrate that SCSS achieves high availability, strong security, and excellent performance
Object Detection for Caries or Pit and Fissure Sealing Requirement in Children's First Permanent Molars
Dental caries is one of the most common oral diseases that, if left
untreated, can lead to a variety of oral problems. It mainly occurs inside the
pits and fissures on the occlusal/buccal/palatal surfaces of molars and
children are a high-risk group for pit and fissure caries in permanent molars.
Pit and fissure sealing is one of the most effective methods that is widely
used in prevention of pit and fissure caries. However, current detection of
pits and fissures or caries depends primarily on the experienced dentists,
which ordinary parents do not have, and children may miss the remedial
treatment without timely detection. To address this issue, we present a method
to autodetect caries and pit and fissure sealing requirements using oral photos
taken by smartphones. We use the YOLOv5 and YOLOX models and adopt a tiling
strategy to reduce information loss during image pre-processing. The best
result for YOLOXs model with tiling strategy is 72.3 mAP.5, while the best
result without tiling strategy is 71.2. YOLOv5s6 model with/without tiling
attains 70.9/67.9 mAP.5, respectively. We deploy the pre-trained network to
mobile devices as a WeChat applet, allowing in-home detection by parents or
children guardian
Prompt-enhanced Hierarchical Transformer Elevating Cardiopulmonary Resuscitation Instruction via Temporal Action Segmentation
The vast majority of people who suffer unexpected cardiac arrest are
performed cardiopulmonary resuscitation (CPR) by passersby in a desperate
attempt to restore life, but endeavors turn out to be fruitless on account of
disqualification. Fortunately, many pieces of research manifest that
disciplined training will help to elevate the success rate of resuscitation,
which constantly desires a seamless combination of novel techniques to yield
further advancement. To this end, we collect a custom CPR video dataset in
which trainees make efforts to behave resuscitation on mannequins independently
in adherence to approved guidelines, thereby devising an auxiliary toolbox to
assist supervision and rectification of intermediate potential issues via
modern deep learning methodologies. Our research empirically views this problem
as a temporal action segmentation (TAS) task in computer vision, which aims to
segment an untrimmed video at a frame-wise level. Here, we propose a
Prompt-enhanced hierarchical Transformer (PhiTrans) that integrates three
indispensable modules, including a textual prompt-based Video Features
Extractor (VFE), a transformer-based Action Segmentation Executor (ASE), and a
regression-based Prediction Refinement Calibrator (PRC). The backbone of the
model preferentially derives from applications in three approved public
datasets (GTEA, 50Salads, and Breakfast) collected for TAS tasks, which
accounts for the excavation of the segmentation pipeline on the CPR dataset. In
general, we unprecedentedly probe into a feasible pipeline that genuinely
elevates the CPR instruction qualification via action segmentation in
conjunction with cutting-edge deep learning techniques. Associated experiments
advocate our implementation with multiple metrics surpassing 91.0%.Comment: Transformer for Cardiopulmonary Resuscitatio
Full-length transcriptome sequencing reveals the molecular mechanism of monoterpene and sesquiterpene biosynthesis in Cinnamomum burmannii
Essential oil of Cinnamomum burmannii is rich in monoterpenes and sesquiterpenes and is widely used in cosmetics and medicines. Knowledge about the enzymes that catalyze the formation of monoterpenes and sesquiterpenes in C. burmannii is insufficient. Therefore, anatomy observation of C. burmannii at the four developmental stages (7 days, CBS1; 14 days, CBS2; 21 days, CBS3, and 28 days, CBS4) were conducted to elucidate the origins of essential oil production. Twelve full-length transcriptomes of C. burmannii leaves at the four stages were generated using Oxford Nanopore Technologies. GC-MS analysis revealed 15 monoterpene and sesquiterpenes dramatically increased from CBS1 to CBS4. A weighted correlation network analysis (WGCNA) in association and differentially expressed genes across four developmental stages were performed. A total of 44 differentially expressed genes (DEGs) were involved in terpenoid syntheses during leaf development. Among them, the DEGs of the mevalonate acid (MVA) pathway were predominantly expressed at CBS1, while those of the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway showed increased expression from CBS2 to CBS4. Besides, fourteen genes were associated with monoterpene synthesis and nine with sesquiterpene synthesis. Functions of these DEGs were further predicted with regard to gene expression profile and phylogenetic relationship with those characterized in previous studies. In addition, 922 long noncoding RNAs (lncRNAs) were detected, of which twelve were predicted to regulate monoterpene and sesquiterpene biosynthesis. The present study provided new insights the molecular mechanisms of monoterpenoid and sesquiterpenoid syntheses of C. burmannii
In-Hospital Mortality Risk Model of Gastric Cancer Surgery:Analysis of a Nationwide Institutional-Level Database With 94,277 Chinese Patients
Leaf Temperature and Transpiration of Field Grown Cotton and Soybean under Arid and Humid Conditions
Abstract : Cotton (Gossypium hirsutum L.) and soybean (Glycine max (L.) Merr.) cultivars were grown under arid (Urumqi, Xinjiang, China) and humid (Matsudo, Chiba, Japan) conditions to analyze their abilities to adapt to arid conditions in terms of transpiration, leaf movement and leaf temperature. Under the arid condition, the leaf temperature of the cotton cultivars was higher than that of the soybean cultivar and the air temperature. There was no significant difference in leaf temperature among the cotton and soybean cultivars under the humid condition. The flow rate of stem sap in the cotton cultivars under the arid condition was always higher than that in the soybean cultivar, and was largely affected by vapor pressure deficit (VPD). Under the humid condition, however, the flow rates of stem sap were lower in the cotton cultivars than in the soybean cultivars. These results indicate that cotton can avoid heat stress by the high transpiring ability possibly supported by well-developed root systems, which leads to higher drought resistance under the arid condition. Soybean would adapt to arid conditions by the combination of paraheliotropic leaf movement and reduced transpiration
Leaf Temperature and Transpiration of Field Grown Cotton and Soybean under Arid and Humid Conditions
Growth of High-Yielding Soybeans and its Relation to Air Temperature in Xinjiang, China
The growth and seed yields of 2 Japanese and 3 Chinese cultivars of soybeans cultivated in 2002-2005 using a drip irrigation system in the arid area of Xinjiang, China, were analyzed with respect to growth parameters and air temperature. Seed yield was very high in 2002, 2003 and 2004, but relatively low in 2005. The variation among years in seed yield clearly depended on pod number. The mean leaf area index (LAI) and crop growth rate (CGR) in 2005 was lower than those in the other 3 years. CGR showed significant positive correlations with mean LAI at the early growing stages, and with net assimilation rate (NAR) at the later growing stages. The increasing rate of pod number (IRP) was positively correlated with the mean LAI and CGR at the pod setting period, suggesting that an adequate supply of photosynthates would be required for pod setting. It was concluded that excellent growth in the years with high yields was supported by the large LAI before the pod setting periods and by high NAR and vigorous pod growth at the latter half of the growing season
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