Search

In this paper, a long-term workload management problem for multi-server edge computing with server collaboration is studied. In the considered model, mobile users computation-intensive tasks are generated dynamically over the time and offloaded to associated edge servers according to pre-determined subscription agreements. Upon receiving the subscribed workload, each edge server can then decide to whether participate in server collaboration for enabling workload re-allocation (i.e., workload exchange) with other heterogeneously configured edge servers. Unlike most of the existing work, this paper takes into account both competitions and collaborations among strategic edge servers in sharing their computing capacities. To achieve the equilibrium for each edge server in minimizing its expected cost (including energy consumption, delay, transmission, configuration and pricing costs), a joint optimization is formulated for determining i) its amount of workload to undertake, ii) compensation price charged from peers, and iii) computing speed to adopt. To efficiently solve this problem, we propose a novel cooperative queueing game approach, which integrates a convex optimization, a core cost sharing scheme and a mapping rule. Theoretical analyses and extensive simulations are conducted to evaluate the performance of the proposed solution, and demonstrate its superiority over counterparts.

This article aims at this problem of adaptive neural tracking control for state-constrained systems. A general fixed-time stability criterion is first presented, by which an adaptive neural control algorithm is developed. Under the action of the proposed adaptive neural tracking controller, the tracking error converges into a small neighborhood around the origin in fixed time; meanwhile, all system states abide by the corresponding state constraints for all the time. The main difference between the present research and the previous control schemes for state-constrained systems is that this article proposes a novel and feasible approach to ensure that the constructed virtual control signals satisfy the state constraints on the corresponding states viewed as the virtual control inputs. Such an approach guarantees theoretically that all the system states cannot violate their constrained requirements at any time. Finally, two simulation examples provide support to the proposed results.

Neural stem progenitor cell (NSPC) transplantation has been regarded as a promising therapeutic method for spinal cord injury (SCI) repair. However, different NSPCs may have different therapeutic effects, and it is therefore important to identify the optimal NSPC type. In our study, we compared the transcriptomes of human fetal brain-derived NSPCs (BNSPCs), spinal cord-derived NSPCs (SCNSPCs) and H9 embryonic stem-cell derived NSPCs (H9-NSPCs)

The relationship between the leaf nitrogen content (LNC) and hyperspectral remote sensing imagery (HYP) was determined to construct an estimation model of the LNC of drip-irrigated sugar beets, aiming to provide supports for the in-time monitoring of sugar beet growth and nitrogen management in arid areas. In this study, a field hyperspectrometer was used to collect the leaf reflectance at the 350–2500 nm for each treatment on the 65th, 85th, 104th, 124th, and 140th day after emergence, and the LNC and leaf chlorophyll content (CHL) of sugar beets were also determined. The spectral characteristic parameters were selected to construct the vegetation indices. The LNC estimation model using HYP as the independent variable (HYP-LNC), and that using CHL and HYP as the independent variables (HYP-CHL-LNC), were compared. The results shows that the HYP-CHL-LNC models had a better linear relationship and a higher fitting accuracy than the HYP-LNC models.

Noise-induced control imperfection is an important problem in applications of diamond-based nano-scale sensing, where measurement-based strategies are generally utilized to correct low-frequency noises in realtime. However, the spin-state readout requires a long time due to the low photon-detection efficiency. This inevitably introduces a delay in noise-reduction process and limits its performance. Here we introduce the deep learning approach to relax this restriction by predicting the trend of noise and compensating the delay. We experimentally implement feedforward quantum control of nitrogen-vacancy center in diamond to protect its spin coherence and improve the sensing performance against noise. The new approach effectively enhances the decoherence time of the electron spin, which enables exploring more physics from its resonant spectroscopy. A theoretical model is provided to explain the improvement. This scheme could be applied in general sensing schemes and extended to other quantum systems., Comment: 6 pages,5 figures, comments are welcome

This article addresses the finite-time consensus tracking control problem for nonlinear multiagent systems (MASs), in which state variables are unmeasured and nonlinear functions are totally unknown. An observer is designed to estimate state variables and fuzzy-logic systems are employed to approximate nonlinearities. Then, an observer-based adaptive fuzzy consensus tracking controller is developed by using the backstepping technique and constructing a novel barrier Lyapunov function with the consideration of the characteristics of MASs. The proposed control protocol can guarantee that: 1) all signals in the closed-loop system keep bounded and 2) the consensus tracking error converges to a prespecified region of the origin in the prescribed finite time. Compared with the existing observer-based finite/fixed-time control protocols, the settling time and the convergence region in our work can be both preassigned by the designer and not affected by the unknown positive constant, which lies in the Lyapunov derivative inequality. Finally, two comparison simulation examples, including a numerical example and a practical example, check the availability of the designed control scheme.

The genus

Objective. ETS1 and ETS2, the main ETS family of transcription factors, have been found to act as downstream effectors of the RAS/MAPK pathway. This study explores the expression and prognostic values of ETS1 and ETS2 across cancers. We also aimed to explore the significance of ETS1 and ETS2 expression in normal immune cells with relation to tumorigenesis. Methods. The expression of ETS1 and ETS2 was examined in the HPA and GEPIA2 databases. The KM plotter was applied to examine prognostic value of ETS1 and ETS2. Correlation between ETS1/ETS2 and infiltrating immune cells and immune checkpoints was assessed using TIMER2.0. The mutation landscape of ETS1/ETS2 was explored using the cBioPortal. STRING and GEPIA2 were used to screen ETS1/ETS2 binding and correlated genes. Enrichr was applied to perform GO and KEGG enrichment analyses. Results. ETS1 showed enhanced expression in lymphoid tissue, while ETS2 showed low tissue specificity. ETS1 was increased in 12 and decreased in 6 cancers, while ETS2 was increased in 4 and decreased in 13 cancers. Both ETS1 and ETS2 were favorable prognostic markers in LIHC and KIRC, while they showed different prognostic roles in more cancers. ETS1 showed stronger correlation with several infiltrating immune cells and immune checkpoints compared with ETS2. Both ETS1 and ETS2 harbored low mutation ratio. ETS1 interacting and correlated genes were enriched in GO terms in response to cadmium ion and response to oxidative stress, while those of ETS2 were enriched in transcription regulation. Conclusion. ETS1 and ETS2 showed different patterns in expression, prognostic values, correlation with immune infiltrating, and immune checkpoints. ETS1 and ETS2 play distinct roles across cancer.

In this paper, consensus analysis and design are investigated for discrete-time multi-agent systems (MASs) with consecutive packet losses in communication links of directed communication topology. It is assumed that at each transmitted instant, the packet loss is stochastic and described by Bernoulli distribution, but during a given time window, the data could be successfully transmitted to the agent from each of its neighbors. First, we utilize the incidence matrix of a directed spanning tree of the communication topology to construct a linear transformation matrix so that the consensus problem is equivalently transformed into a mean square asymptotic stability problem of a reduced-order system. Second, by using Lyapunov–Krasovskii functional approach, we derive some sufficient conditions of consensus criterion in terms of linear matrix inequalities (LMIs). These conditions express the relationship among the control gain matrix, packet loss rate, and the number of consecutive packet losses. Based on the conditions, gain matrix in the consensus protocol is designed to guarantee the MAS with stochastic packet losses to achieve mean square asymptotic consensus. Moreover, for the special case of undirected communication topology, by using the matrix decomposition method, the variables of LMIs are transformed into the low-order conditions independent of the network size. Finally, some numerical examples are given to show the effectiveness of the proposed method.

AP2/ERF (APETALA2/ethylene-responsive factor) superfamily is one of the largest gene families in plants and has been reported to participate in various biological processes, such as the regulation of biosynthesis of active lignan. However, few studies have investigated the genome-wide role of the AP2/ERF superfamily in Isatis indigotica. This study establishes a complete picture of the AP2/ERF superfamily in I. indigotica and contributes valuable information for further functional characterization of IiAP2/ERF genes and supports further metabolic engineering.To identify the IiAP2/ERF superfamily genes, the AP2/ERF sequences from Arabidopsis thaliana and Brassica rapa were used as query sequences in the basic local alignment search tool. Bioinformatic analyses were conducted to investigate the protein structure, motif composition, chromosome location, phylogenetic relationship, and interaction network of the IiAP2/ERF superfamily genes. The accuracy of omics data was verified by quantitative polymerase chain reaction and heatmap analyses.One hundred and twenty-six putative IiAP2/ERF genes in total were identified from the I. indigotica genome database in this study. By sequence alignment and phylogenetic analysis, the IiAP2/ERF genes were classified into 5 groups including AP2, ERF, DREB (dehydration-responsive element-binding factor), Soloist and RAV (related to abscisic acid insensitive 3/viviparous 1) subfamilies. Among which, 122 members were unevenly distributed across seven chromosomes. Sequence alignment showed that I. indigotica and A. thaliana had 30 pairs of orthologous genes, and we constructed their interaction network. The comprehensive analysis of gene expression pattern in different tissues suggested that these genes may play a significant role in organ growth and development of I. indigotica. Members that may regulate lignan biosynthesis in roots were also preliminarily identified. Ribonucleic acid sequencing analysis revealed that the expression of 76 IiAP2/ERF genes were up- or down-regulated under salt or drought treatment, among which, 33 IiAP2/ERF genes were regulated by both stresses.This study undertook a genome-wide characterization of the AP2/ERF superfamily in I. indigotica, providing valuable information for further functional characterization of IiAP2/ERF genes and discovery of genetic targets for metabolic engineering.

Few researchers have discussed the differences in gender between the age groups of patients who underwent transcatheter aortic valve implantation (TAVI). We searched the National Readmissions Database from 2012 to 2019 to identify adults who underwent TAVI. We studied hospital outcomes and short- to medium-term outcomes by age stratification (18 to 59, 60 to 69, 70 to 79, and 80 to 90 years) after TAVI and categorized by gender. We included 147,481 patients who underwent TAVI, and 54,802 pairs were matched using propensity score matching separately for each age group. Compared with men, women in all age groups had a similar rate of hospital death. Except the 18- to 59-year-old groups, female patients were less likely to undergo permanent pacemaker implantation and transfusion. Records of readmission at 30 days and 6 months were used as the follow-up outcome according to the presence or absence of readmission. Major adverse cardiovascular events (MACEs) were a composite of cardiovascular readmission, all-cause mortality during readmission, and stroke readmission. At the 30-day follow-up visit, there was no difference in the all-cause readmission and MACE between women and men in any group. At the 6-month follow-up visit, women in the 70- to 79-year-old and 80- to 90-year-old groups had a high risk of all-cause readmission. In conclusion, we reported that female patients have similar in-hospital death rates to male patients who underwent TAVI. During the 30-day follow-up visit, the all-cause readmission and MACE were not different in all age groups between men and women. At 6 months, women in the 70- to 79-year-old and 80- to 90-year-old groups had a higher risk of all-cause readmission.

Presented herein is the discovery of the in situ synthesis of pyrazolylborates. They exhibit great adaptive coordination behaviors in aluminum oxo clusters and further provide a platform for the development of trans-chelating scorpionate analogues.

Background: Neuroinflammation and oxidative stress after traumatic brain injury (TBI) can further lead to neuronal apoptosis, which plays a crucial role in the process of neuron death. Curcumin, which is derived from the rhizome of the Curcuma longa plant, has multiple pharmacological effects. Objective: The objective of this study was to investigate whether curcumin treatment has neuroprotective effects after TBI, and to elucidate the underlying mechanism. Methods: A total of 124 mice were randomly divided into 4 groups: Sham group, TBI group, TBI+Vehicle group, and TBI+Curcumin group. The TBI mice model used in this study was constructed with TBI device induced by compressed gas, and 50 mg/kg curcumin was injected intraperitoneally 15 minutes after TBI. Then, the blood-brain barrier permeability, cerebral edema, oxidative stress, inflammation, apoptosis-related protein, and behavioral tests of neurological function were utilized to evaluate the protective effect of curcumin after TBI. Results: Curcumin treatment markedly alleviated post-trauma cerebral edema and blood-brain barrier integrity, and suppressed neuronal apoptosis, reduced mitochondrial injury and the expression of apoptosis-related proteins. Moreover, curcumin also attenuates TBI-induced inflammatory response and oxidative stress in brain tissue and improves cognitive dysfunction after TBI. Conclusion: These data provide substantial evidence that curcumin has neuroprotective effects in animal TBI models, possibly through the inhibition of inflammatory response and oxidative stress.

Aim: Study the influence of calcineurin inhibitors (CNI) and genetic polymorphisms of transporters on enterohepatic circulation (EHC) of mycophenolic acid (MPA) in Chinese adult renal allograft recipients and estimate the effect of various covariates on prediction performance of MPA AUC0-12h. Method: MPA concentrations of 125 Chinese patients were collected 0-12 hours after administration. Genotypes of transporters were determined in 64 patients. The influence of type of CNI and genetic polymorphisms on MPA exposure was studied. Shapley additive explanations method was used to study the impact of sampling times and covariates related to EHC on AUC0-12h. Extreme gradient boosting (XGboost) machine learning-based model was established to predict AUC0-12h. Results: Dn-AUC6-12h was significantly lower in patients co-administered with CsA (P

Effect of grain boundary morphology on ductility dip cracking (DDC) sensitivity of nickel base alloy inconel52 deposited metal was researched by welding thermal simulation method and high temperature tensile test. The sample was hold at 1300 °C for 2S ~ 10s and then stretched at its DDC sensitive temperature 1050 °C at different tensile rates. The DDC sensitivity was compared by reduction of area (VoA) of tensile test sample. The results show that straight grain boundary reduces VoA, precipitates in grain boundaries increases VoA, and VoA increases with the increase of tensile rate. Straight grain boundary causes stress concentration and strain localization at the trigeminal grain boundary, curved grain boundary decreases the maximum Mises stress which make more uniform stress distribution. Precipitates on the grain boundary can play a role of locking the grain boundary migration and disperse the strain concentration at the trigeminal grain boundary. The lower the strain rate, the longer the deformation time, which will lead to decrease of dislocation movement rate. The smaller the critical shear stress of grain boundary sliding, the smaller the deformation resistance, and the full progress of dislocation movement and climbing. Effect of strain rate on DDC needs more research.

Transcutaneous electrical cranial-auricular acupoint stimulation (TECAS) is a novel non-invasive therapy that stimulates acupoints innervated by the trigeminal and auricular vagus nerves. An assessor-blinded, randomized, non-inferiority trial was designed to compare the efficacy of TECAS and escitalopram in mild-to-moderate major depressive disorder.468 participants received 2 TECAS sessions per day at home (n = 233) or approximately 10-13 mg/day escitalopram (n = 235) for 8 weeks plus 4-week follow-up. The primary outcome was clinical response, defined as a baseline-to-endpoint ≥50% reduction in Montgomery-Åsberg Depression Rating Scale (MADRS) score. Secondary outcomes included remission rate, changes in the severity of depression, anxiety, sleep and life quality.The response rate was 66.4% on TECAS and 63.2% on escitalopram with a 3.2% difference (95% confidence interval [CI], -5.9% to 12.9%) in intention-to-treat analysis, and 68.5% versus 66.2% with a 2.3% difference (95% CI, -6.9% to 11.4%) in per-protocol analysis. The lower limit of 95% CI of the differences fell within the prespecified non-inferiority margin of -10% (P ≤ 0.004 for non-inferiority). Most secondary outcomes did not differ between the two groups. TECAS-treated participants who experienced psychological trauma displayed a markedly greater response than those without traumatic experience (81.3% versus 62.1%, P = 0.013). TECAS caused much fewer adverse events than escitalopram.TECAS was comparable to escitalopram in improving depression and related symptoms, with high acceptability, better safety profile, and particular efficacy in reducing trauma-associated depression. It could serve an effective portable therapy for mild-to-moderate depression. This article is protected by copyright. All rights reserved.

Histidine phosphorylation (pHis), occurring on the histidine of substrate proteins, is a hidden phosphoproteome that is poorly characterized in mammals. LHPP (phospholysine phosphohistidine inorganic pyrophosphate phosphatase) is one of the histidine phosphatases and its encoding gene was recently identified as a susceptibility gene for major depressive disorder (MDD). However, little is known about how LHPP or pHis contributes to depression. Here, by using integrative approaches of genetics, behavior and electrophysiology, we observed that LHPP in the medial prefrontal cortex (mPFC) was essential in preventing stress-induced depression-like behaviors. While genetic deletion of LHPP per se failed to affect the mice's depression-like behaviors, it markedly augmented the behaviors upon chronic social defeat stress (CSDS). This augmentation could be recapitulated by the local deletion of LHPP in mPFC. By contrast, overexpressing LHPP in mPFC increased the mice's resilience against CSDS, suggesting a critical role of mPFC LHPP in stress-induced depression. We further found that LHPP deficiency increased the levels of histidine kinases (NME1/2) and global pHis in the cortex, and decreased glutamatergic transmission in mPFC upon CSDS. NME1/2 served as substrates of LHPP, with the Aspartic acid 17 (D17), Threonine 54 (T54), or D214 residue within LHPP being critical for its phosphatase activity. Finally, reintroducing LHPP, but not LHPP phosphatase-dead mutants, into the mPFC of LHPP-deficient mice reversed their behavioral and synaptic deficits upon CSDS. Together, these results demonstrate a critical role of LHPP in regulating stress-related depression and provide novel insight into the pathogenesis of MDD.

To predict mycophenolic acid (MPA) exposure in renal transplant recipients using a deep learning model based on a convolutional neural network with bilateral long short-term memory and attention methods.A total of 172 Chinese renal transplant patients were enrolled in this study. The patients were divided into a training group (n = 138, Ruijin Hospital) and a validation group (n = 34, Zhongshan Hospital). Fourteen days after renal transplantation, rich blood samples were collected 0-12 hours after MPA administration. The plasma concentration of total MPA was measured using an enzyme-multiplied immunoassay technique. A limited sampling strategy based on a convolutional neural network-long short-term memory with attention (CALS) model for the prediction of the area under the concentration curve (AUC) of MPA was established. The established model was verified using the data from the validation group. The model performance was compared with that obtained from multiple linear regression (MLR) and maximum a posteriori (MAP) methods.The MPA AUC 0-12 of the training and validation groups was 54.28 ± 18.42 and 41.25 ± 14.53 µg·ml -1 ·h, respectively. MPA plasma concentration after 2 (C 2 ), 6 (C 6 ), and 8 (C 8 ) hours of administration was the most significant factor for MPA AUC 0-12 . The predictive performance of AUC 0-12 estimated using the CALS model of the validation group was better than the MLR and MAP methods in previous studies (r 2 = 0.71, mean prediction error = 4.79, and mean absolute prediction error = 14.60).The CALS model established in this study was reliable for predicting MPA AUC 0-12 in Chinese renal transplant patients administered mycophenolate mofetil and enteric-coated mycophenolic acid sodium and may have good generalization ability for application in other data sets.

Narrowband-Internet of Things (NB-IoT) is an emerging cellular communication technology designed for low-power wide-area applications. Cell selection determines the channel of user device and hence is an important issue in cellular networks. In this article, we make the first attempt to examine and optimize the cell selection in NB-IoT networks by field measurement. We conduct measurements at 30 different locations which involve five typical application scenarios of NB-IoT. Two kinds of NB-IoT modules and two network operators are also involved in the measurements. We find four potential issues on the cell selection of the User Equipment (UE) through the measurements. We propose an adaptive cell selection approach to optimize the cell selection of UE. The simulation test based on real-world measurement data shows that the cell selected by the adaptive approach can improve the coverage level and reduce the power consumption for UE.