88 research outputs found
New isoforms and assembly of glutamine synthetase in the leaf of wheat (Triticum aestivum L.).
Glutamine synthetase (GS; EC 6.3.1.2) plays a crucial role in the assimilation and re-assimilation of ammonia derived from a wide variety of metabolic processes during plant growth and development. Here, three developmentally regulated isoforms of GS holoenzyme in the leaf of wheat (Triticum aestivum L.) seedlings are described using native-PAGE with a transferase activity assay. The isoforms showed different mobilities in gels, with GSII>GSIII>GSI. The cytosolic GSI was composed of three subunits, GS1, GSr1, and GSr2, with the same molecular weight (39.2kDa), but different pI values. GSI appeared at leaf emergence and was active throughout the leaf lifespan. GSII and GSIII, both located in the chloroplast, were each composed of a single 42.1kDa subunit with different pI values. GSII was active mainly in green leaves, while GSIII showed brief but higher activity in green leaves grown under field conditions. LC-MS/MS experiments revealed that GSII and GSIII have the same amino acid sequence, but GSII has more modification sites. With a modified blue native electrophoresis (BNE) technique and in-gel catalytic activity analysis, only two GS isoforms were observed: one cytosolic and one chloroplastic. Mass calibrations on BNE gels showed that the cytosolic GS1 holoenzyme was ~490kDa and likely a dodecamer, and the chloroplastic GS2 holoenzyme was ~240kDa and likely a hexamer. Our experimental data suggest that the activity of GS isoforms in wheat is regulated by subcellular localization, assembly, and modification to achieve their roles during plant development
LipsFormer: Introducing Lipschitz Continuity to Vision Transformers
We present a Lipschitz continuous Transformer, called LipsFormer, to pursue
training stability both theoretically and empirically for Transformer-based
models. In contrast to previous practical tricks that address training
instability by learning rate warmup, layer normalization, attention
formulation, and weight initialization, we show that Lipschitz continuity is a
more essential property to ensure training stability. In LipsFormer, we replace
unstable Transformer component modules with Lipschitz continuous counterparts:
CenterNorm instead of LayerNorm, spectral initialization instead of Xavier
initialization, scaled cosine similarity attention instead of dot-product
attention, and weighted residual shortcut. We prove that these introduced
modules are Lipschitz continuous and derive an upper bound on the Lipschitz
constant of LipsFormer. Our experiments show that LipsFormer allows stable
training of deep Transformer architectures without the need of careful learning
rate tuning such as warmup, yielding a faster convergence and better
generalization. As a result, on the ImageNet 1K dataset, LipsFormer-Swin-Tiny
based on Swin Transformer training for 300 epochs can obtain 82.7\% without any
learning rate warmup. Moreover, LipsFormer-CSwin-Tiny, based on CSwin, training
for 300 epochs achieves a top-1 accuracy of 83.5\% with 4.7G FLOPs and 24M
parameters. The code will be released at
\url{https://github.com/IDEA-Research/LipsFormer}.Comment: To appear in ICLR 2023, our code will be public at
https://github.com/IDEA-Research/LipsForme
An Advanced Adaptive Control of Lower Limb Rehabilitation Robot
Rehabilitation robots play an important role in the rehabilitation field, and effective human-robot interaction contributes to promoting the development of the rehabilitation robots. Though many studies about the human-robot interaction have been carried out, there are still several limitations in the flexibility and stability of the control system. Therefore, we proposed an advanced adaptive control method for lower limb rehabilitation robot. The method was devised with a dual closed loop control strategy based on the surface electromyography (sEMG) and plantar pressure to improve the robustness of the adaptive control for the rehabilitation robots. First, in the outer loop control, an advanced variable impedance controller based on the sEMG and plantar pressure was designed to correct robot's reference trajectory. Then, in the inner loop control, a sliding mode iterative learning controller (SMILC) based on the variable boundary saturation function was designed to achieve the tracking of the reference trajectory. The experiment results showed that, in the designed dual closed loop control strategy, a variable impedance controller can effectively reduce trajectory tracking errors and adaptively modify the reference trajectory synchronizing with the motion intention of patients; the designed sliding mode iterative learning controller can effectively reduce chattering in sliding mode control and excellently achieve the tracking of rehabilitation robot's reference trajectory. This study can improve the performance of the human-robot interaction of the rehabilitation robot system, and expand the application to the rehabilitation field
Screening and the epidemic of thyroid cancer in China:an analysis of national representative inpatient and commercial insurance databases
Observation of Dirac hierarchy in three-dimensional acoustic topological insulators
Dirac cones (DCs) play a pivotal role in various unique phenomena ranging
from massless electrons in graphene to robust surface states in topological
insulators (TIs). Recent studies have theoretically revealed a full Dirac
hierarchy comprising an eightfold bulk DC, a fourfold surface DC, and a twofold
hinge DC, associated with a hierarchy of topological phases including
first-order to third-order three-dimensional (3D) topological insulators, using
the same 3D base lattice. Here, we report the first experimental observation of
the Dirac hierarchy in 3D acoustic TIs. Using acoustic measurements, we
unambiguously reveal that lifting of multifold DCs in each hierarchy can induce
two-dimensional (2D) topological surface states with a fourfold DC in a
first-order 3D TI, one-dimensional (1D) topological hinge states with a twofold
DC in a second-order 3D TI, and zero-dimensional (0D) topological corner states
in a third-order 3D TI. Our work not only expands the fundamental research
scope of Dirac physics, but also opens up a new route for multidimensional
robust wave manipulation
Robust estimation of bacterial cell count from optical density
Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
Roadmap on energy harvesting materials
Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere
Linking subordinate political skill to supervisor dependence and reward recommendations: a moderated mediation model
In this study, we examined the relations of subordinate political skill with supervisor’s dependence on thesubordinate and supervisor reward recommendation, as well as mediating (interaction frequency withsupervisor) and moderating (supervisor political behavior) variables of these relations. Our theoreticalmodel was tested using data collected from employees in a company that specialized in constructionmanagement. Analyses of multisource and lagged data from 53 construction management team supervisorsand 296 subordinates indicated that subordinate political skill was positively related to supervisorreward recommendation via subordinate’s interaction frequency with supervisor. Although interactionfrequency with a supervisor was also positively related to the supervisor’s dependence on the subordinate,the indirect effect of subordinate political skill on dependence was not significant. Further, both therelationship between subordinate political skill and interaction frequency with a supervisor and theindirect relationships between subordinate political skill and supervisor reward recommendation werestronger when supervisors exhibited more political behavior
SACT: A New Model of Covert Communication Based on SDN
Anonymous tracking technology of network watermarking is limited by the deployment of tracking devices in traditional network structure, resulting in poor scalability and reusability. Software Defined Network (SDN) boasts more freedom thanks to its separation of the control plane from the data plane. In this paper, a new anonymous communication tracking model SDN-based Anonymous Communication Tracking (SACT) is proposed, which introduces network watermarking into SDN and combines IP time hidden channel and symbol expansion technology. In addition, we introduce a hopping protection mechanism to improve the anti detection ability of the watermark as well. The experimental results show that in a variety of simulated network environments, SACT achieves excellent detection rate and bit error rate, thus it is sufficient to determine the communication relationship between the two parties. Meanwhile, SACT solves the deployment problem of anonymous tracking and improves the availability and scalability of covert communication
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