Therblig-embedded value stream mapping method for lean energy machining

To improve energy efficiency, extensive studies have focused on the cutting parameters optimization in the machining process. Actually, non-cutting activities (NCA) occur frequently during machining and this is a promising way to save energy through optimizing NCA without changing the cutting parameters. However, it is difficult for the existing methods to accurately determine and reduce the energy wastes (EW) in NCA. To fill this gap, a novel Therblig-embedded Value Stream Mapping (TVSM) method is proposed to improve the energy transparency and clearly show and reduce the EW in NCA. The Future-State-Map (FSM) of TVSM can be built by minimizing non-cutting activities and Therbligs. By implementing the FSM, time and energy efficiencies can be improved without decreasing the machining quality, which is consistent with the goal of lean energy machining. The method is validated by a machining case study, the results show that the total energy is reduced by 7.65%, and the time efficiency of the value-added activities is improved by 8.12% , and the energy efficiency of value-added activities and Therbligs are raised by 4.95% and 1.58%, respectively. This approach can be applied to reduce the EW of NCA, to support designers to design high energy efficiency machining processes during process planning

A load-balancing mechanism for distributed SDN control plane using response time.

Software-Defined Networking (SDN) has become a popular paradigm for managing large-scale networks including cloud servers and data centers because of its advantages of centralized management and programmability. The issues of scalability and reliability that a single centralized controller suffers makes distributed controller architectures emerge. One key limitation of distributed controllers is the statically configured switch-controller mapping, easily causing uneven load distribution among controllers. Previous works have proposed load-balancing methods with switch migration to address this issue. However, the higher-load controller is always directly considered as the overloaded controller that need to shift its load to other controllers, even if it has no response time delay. The pursuit of absolute load-balancing effect can also result in frequent network delays and service interruptions. Additionally, if there are several overloaded controllers, just one controller with the maximum load can be addressed within a single load-balancing operation, reducing load-balancing efficiency. To address these problems, we propose SMCLBRT, a load-balancing strategy of multiple SDN controllers based on response time, considering the changing features of real-time response times versus controller loads. By selecting the appropriate response time threshold and dealing with multiple overloading controllers simultaneously, it can well solve load-balancing problem in SDN control plane with multiple overloaded controllers. Simulation experiments exhibit the effectiveness of our scheme.N/

Allometry of Bud Dynamic Pattern and Linkage Between Bud Traits and Ecological Stoichiometry of Nitraria tangutorum Under Fertilizer Addition

Affected by the pressure and constraints of available resources, plant growth and development, as well as plant life history strategies, usually vary with environmental conditions. Plant buds play a crucial role in the life history of woody plants. Nitraria tangutorum is a common dominant woody species in desertified areas of northern China and its growth is critical to the desert ecosystem. Revealing the allometry of N. tangutorum aboveground bud fates and the linkage between bud traits and plant nutrient contents and stoichiometric ratios can be useful in understanding plant adaptation strategy. We applied seven nitrogen and phosphorus fertilizer addition treatments to natural N. tangutorum ramets in Ulan Buh Desert in three consecutive years. We surveyed three types of aboveground buds (dormant buds, vegetative buds, and reproductive buds) in each N. tangutorum ramet, then measured the plant carbon (C), nitrogen (N), and phosphorus (P) contents and ratios during three consecutive years. We specified that reserve growth potential (RGP), vegetative growth intensity (VGI) and sexual reproduction effort (SRE) are the three indices of bud dynamic pattern. The results showed that the bud dynamic pattern of N. tangutorum ramets differed significantly among different fertilizer addition treatments and sampling years. The allometry of RGP, VGI, and SRE was obvious, showing size dependence. The allometric growth relationship fluctuated among the sampling years. The linkage between bud traits and plant stoichiometric characteristics of N. tangutorum ramets showed close correlation with plant P content, C:P and N:P ratios, no significant correlation with plant C content, N content and C:N ratio. These results contribute to an improved understanding of the adaptive strategies of woody plants growing in desert ecosystems and provide insights for adoption of effective measures to restore and conserve plant communities in arid and semi-arid regions

Dynamic RACH Partition for Massive Access of Differentiated M2M Services

In machine-to-machine (M2M) networks, a key challenge is to overcome the overload problem caused by random access requests from massive machine-type communication (MTC) devices. When differentiated services coexist, such as delay-sensitive and delay-tolerant services, the problem becomes more complicated and challenging. This is because delay-sensitive services often use more aggressive policies, and thus, delay-tolerant services get much fewer chances to access the network. To conquer the problem, we propose an efficient mechanism for massive access control over differentiated M2M services, including delay-sensitive and delay-tolerant services. Specifically, based on the traffic loads of the two types of services, the proposed scheme dynamically partitions and allocates the random access channel (RACH) resource to each type of services. The RACH partition strategy is thoroughly optimized to increase the access performances of M2M networks. Analyses and simulation demonstrate the effectiveness of our design. The proposed scheme can outperform the baseline access class barring (ACB) scheme, which ignores service types in access control, in terms of access success probability and the average access delay

HS-Diffusion: Learning a Semantic-Guided Diffusion Model for Head Swapping

Image-based head swapping task aims to stitch a source head to another source body flawlessly. This seldom-studied task faces two major challenges: 1) Preserving the head and body from various sources while generating a seamless transition region. 2) No paired head swapping dataset and benchmark so far. In this paper, we propose an image-based head swapping framework (HS-Diffusion) which consists of a semantic-guided latent diffusion model (SG-LDM) and a semantic layout generator. We blend the semantic layouts of source head and source body, and then inpaint the transition region by the semantic layout generator, achieving a coarse-grained head swapping. SG-LDM can further implement fine-grained head swapping with the blended layout as condition by a progressive fusion process, while preserving source head and source body with high-quality reconstruction. To this end, we design a head-cover augmentation strategy for training and a neck alignment trick for geometric realism. Importantly, we construct a new image-based head swapping benchmark and propose two tailor-designed metrics (Mask-FID and Focal-FID). Extensive experiments demonstrate the superiority of our framework. The code will be available: https://github.com/qinghew/HS-Diffusion

Effect of Liuweibuqi capsule, a Chinese patent medicine, on the JAK1/STAT3 pathway and MMP9/TIMP1 in a chronic obstructive pulmonary disease rat model

AbstractObjectiveTo observe effect of Liuweibuqi Capsule, a Traditional Chinese Medicine (TCM), on the janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway and matrix metalloproteinases (MMPs) in a chronic obstructive pulmonary disease (COPD) rat model with lung deficiency in terms of TCM's pattern differentiation.MethodsRats were randomly divided into a normal group, model group, Liuweibuqi group, Jinshuibao group, and spleen aminopeptidase group (n= 10). Aside from the normal group, all rats were exposed to smoke plus lipopolysaccharide tracheal instillation to establish the COPD model with lung deficiency. Models were established after 28 days and then the normal and model groups were given normal saline (0.09 g/kg), Liuweibuqi group was given Liuweibuqi capsule (0.35 g/kg), Jinshuibao group was given Jinshuibao capsules (0.495 g/kg), and the spleen group was given spleen aminopeptidase (0.33 mg/kg), once a day for 30 days. Changes in symptoms, signs, and lung histology were observed. Lung function was measured with a spirometer. Serum cytokines were detected using enzyme-linked immunosorbent assay, and changes in the JAK/STAT pathway, MMP-9, and MMPs inhibitor 1 (TIMP1) were detected by immunohistochemistry, RT-PCR, and western blotting, respectively.ResultsCompared with the normal group, lung tissue was damaged, and lung function was reduced in the model control group. Additionally, the levels of interleukin (IL)-1β, γ interferon (IFN-γ), and IL-6 were higher, while IL-4 and IL-10 were lower in the model control group than those in the normal group. The expressions of JAK1, STAT3, p-STAT3, and MMP-9 mRNA and protein in lung tissue were higher, and TIMP1 mRNA and protein was lower in the model group compared with the normal group. After treatment, compared with the model group, the expression of inflammatory cytokines was lower in each treatment group, and expressions of JAK/STAT pathway, MMPs were lower. Compared with the positive control groups, the Jinshuibao and spleen aminopeptidase groups, lung function was better, and JAK1, STAT3, and p-STAT3 protein were lower and TIMP1 was higher in the Liuweibuqi group.ConclusionLiuweibuqi capsules can improve the symptoms of COPD possibly by regulating the expression of the JAK1/STAT3 pathway and MMP9/TIMP1

Optical and SuperDARN radar observations of duskside shock aurora over Zhongshan Station

We present observations of a duskside shock aurora occurred on 21 April 2001 by the SuperDARN radar at Syowa Station and the all-sky camera at Zhongshan Station (ZHS) in Antarctica when the radar was operated in fast-scan mode covering the ZHS region. With the two independent data sets, we examine ionospheric plasma convection and aurora arising from a sudden impulse (SI) event associated with an interplanetary shock. During the transient shock compression, the aurora was quiescent without any optical emission at the preliminary impulse of the SI. About 7 min later, a new thin auroral arc with brighter emissions and a lifetime of ~14 min expanded westward from the region above ZHS during the main impulse of the SI. SuperDARN radar line-of-sight measurements showed periodical oscillation in the flow direction with ultra-low-frequency waves having a period of ~8 min during the shock compression. We suggest that downward field-aligned current during the preliminary impulse stage of the SI was the main driver of the first plasma flow reversal, and the subsequent new discrete auroral arc may be associated with field-aligned acceleration in the region of the main impulse related upward field-aligned currents. The ground magnetometer observations suggest that the oscillation of the ionospheric convection on the duskside was associated with field line resonance activity

Comparative Evaluation of the LAMP Assay and PCR-Based Assays for the Rapid Detection of Alternaria solani

Early blight (EB), caused by the pathogen Alternaria solani, is a major threat to global potato and tomato production. Early and accurate diagnosis of this disease is therefore important. In this study, we conducted a loop-mediated isothermal amplification (LAMP) assay, as well as conventional polymerase chain reaction (PCR), nested PCR, and quantitative real-time PCR (RT-qPCR) assays to determine which of these techniques was less time consuming, more sensitive, and more accurate. We based our assays on sequence-characterized amplified regions of the histidine kinase gene with an accession number (FJ424058). The LAMP assay provided more rapid and accurate results, amplifying the target pathogen in less than 60 min at 63°C, with 10-fold greater sensitivity than conventional PCR. Nested PCR was 100-fold more sensitive than the LAMP assay and 1000-fold more sensitive than conventional PCR. qPCR was the most sensitive among the assays evaluated, being 10-fold more sensitive than nested PCR for the least detectable genomic DNA concentration (100 fg). The LAMP assay was more sensitive than conventional PCR, but less sensitive than nested PCR and qPCR; however, it was simpler and faster than the other assays evaluated. Despite of the sensitivity, LAMP assay provided higher specificity than qPCR. The LAMP assay amplified A. solani artificially, allowing us to detect naturally infect young potato leaves, which produced early symptoms of EB. The LAMP assay also achieved positive amplification using diluted pure A. solani culture instead of genomic DNA. Hence, this technique has greater potential for developing quick and sensitive visual detection methods than do other conventional PCR strategies for detecting A. solani in infected plants and culture, permitting early prediction of disease and reducing the risk of epidemics

Integrated analysis of lncRNA and mRNA repertoires in Marek’s disease infected spleens identifies genes relevant to resistance

Marek’s disease virus (MDV) is an oncogenic herpesvirus that can cause T-cell lymphomas in chicken. Long noncoding RNA (lncRNA) is strongly associated with various cancers and many other diseases. In chickens, lncRNAs have not been comprehensively identified. Here, we profiled mRNA and lncRNA repertoires in three groups of spleens from MDV-infected and non-infected chickens, including seven tumorous spleens (TS) from MDV-infected chickens, five spleens from the survivors (SS) without lesions after MDV infection, and five spleens from noninfected chickens (NS), to explore the underlying mechanism of host resistance in Marek’s disease (MD).https://doi.org/10.1186/s12864-019-5625-

COVID-19 disease identification network based on weakly supervised feature selection

The coronavirus disease 2019 (COVID-19) outbreak has resulted in countless infections and deaths worldwide, posing increasing challenges for the health care system. The use of artificial intelligence to assist in diagnosis not only had a high accuracy rate but also saved time and effort in the sudden outbreak phase with the lack of doctors and medical equipment. This study aimed to propose a weakly supervised COVID-19 classification network (W-COVNet). This network was divided into three main modules: weakly supervised feature selection module (W-FS), deep learning bilinear feature fusion module (DBFF) and Grad-CAM++ based network visualization module (Grad-Ⅴ). The first module, W-FS, mainly removed redundant background features from computed tomography (CT) images, performed feature selection and retained core feature regions. The second module, DBFF, mainly used two symmetric networks to extract different features and thus obtain rich complementary features. The third module, Grad-Ⅴ, allowed the visualization of lesions in unlabeled images. A fivefold cross-validation experiment showed an average classification accuracy of 85.3%, and a comparison with seven advanced classification models showed that our proposed network had a better performance