Whole-Process Privacy-Preserving and Sybil-Resilient Consensus for Multiagent Networks.

This article is concerned with the co-design of privacy-preserving and resilient consensus protocol for a class of multiagent networks (MANs), where the information exchanges over communication networks among the agents suffer from eavesdropping and Sybil attacks. First, we introduce a new attack model in which an adversarial agent could launch a Sybil attack, generating a large number of spurious entities in the network, thereby gaining disproportionate influence. In this communication framework, a whole-process privacy-preserving mechanism is designed that is capable of protecting both initial and current states of agents.

A Novel Multi-Feature Fusion Network With Spatial Partitioning Strategy and Cross-Attention for Armband-Based Gesture Recognition.

Effectively integrating the time-space-frequency information of multi-modal signals from armband sensor, including surface electromyogram (sEMG) and accelerometer data, is critical for accurate gesture recognition. Existing approaches often neglect the abundant spatial relationships inherent in multi-channel sEMG signals obtained via armband sensors and face challenges in harnessing the correlations across multiple feature domains. To address this issue, we propose a novel multi-feature fusion network with spatial partitioning strategy and cross-attention (MFN-SPSCA) to improve the accuracy and robustness of gesture recognition.

Gaussian Particle Filtering for Nonlinear Systems With Heavy-Tailed Noises: A Progressive Transform-Based Approach.

The Gaussian particle filter (GPF) is a type of particle filter that employs the Gaussian filter approximation as the proposal distribution. However, the linearization errors are introduced during the calculation of the proposal distribution. In this article, a progressive transform-based GPF (PT-GPF) is proposed to solve this problem.

Fast Attack Detection for Cyber-Physical Systems Using Dynamic Data Encryption.

To defend the cyber-physical system (CPSs) from cyber-attacks, this work proposes an unified intrusion detection mechanism which is capable to fast hunt various types of attacks. Focusing on securing the data transmission, a novel dynamic data encryption scheme is developed and historical system data is used to dynamically update a secret key involved in the encryption. The core idea of the dynamic data encryption scheme is to establish a dynamic relationship between original data, secret key, ciphertext and its decrypted value, and in particular, this dynamic relationship will be destroyed once an attack occurs, which can be used to detect attacks.

Neurodynamics-based distributed model predictive control of a low-speed two-stroke marine main engine power system.

This article studies a steady operation optimization problem of a low-speed two-stroke marine main engine (LTMME) power system including a cooling water subsystem, a fuel oil subsystem and a main engine subsystem with input and state constraints. Firstly, a distributed model with coupling inputs and states is established for the LTMME power system according to laws of thermodynamics and kinetics. Further, an optimization problem of the LTMME power system is formulated to ensure the system to operate steadily, subjected to constraint conditions of the distributed model and the input and state bounds.

Pamiparib in patients with locally advanced or metastatic HER2-negative breast cancer with germline BRCA mutations: a phase II study.

Purpose: To evaluate the efficacy and safety of pamiparib in patients with locally advanced or metastatic human epidermal growth factor receptor 2-negative (HER2-) breast cancer, with deleterious or suspected deleterious germline BRCA1/2 mutations (gBRCA1/2 m).

Methods: In this open-label, phase II, multicenter study in China (NCT03575065), patients with triple-negative breast cancer (TNBC cohort) or hormone receptor-positive (HR+)/HER2- breast cancer (HR+/HER2- cohort) and ≤ 2 prior lines of chemotherapy received pamiparib 60 mg orally twice daily in 28-day, continuous cycles. The primary endpoint was objective response rate (ORR; RECIST v1.

Wavelet Packet Decomposition-Based Multiscale CNN for Fault Diagnosis of Wind Turbine Gearbox.

This article presents an intelligent fault diagnosis method for wind turbine (WT) gearbox by using wavelet packet decomposition (WPD) and deep learning. Specifically, the vibration signals from the gearbox are decomposed using WPD and the decomposed signal components are fed into a hierarchical convolutional neural network (CNN) to extract multiscale features adaptively and classify faults effectively. The presented method combines the multiscale characteristic of WPD with the strong classification capacity of CNNs, and it does not need complex manual feature extraction steps as usually adopted in existing results.

Training Deep Neural Network for Optimal Power Allocation in Islanded Microgrid Systems: A Distributed Learning-Based Approach.

Currently, numerical optimization methods are used to solve distributed optimal power allocation (OPA) problems for islanded microgrid (MG) systems. Most of them are developed based on rigorous mathematical derivation. However, the complexity of such optimization algorithms inevitably creates a gap between theoretical analysis and real-time implementation.

Pamiparib dose escalation in Chinese patients with non-mucinous high-grade ovarian cancer or advanced triple-negative breast cancer.

Background: The recommended phase 2 dose (RP2D) of pamiparib, an investigational PARP1/2 inhibitor, was established as 60 mg twice daily (BID) in a first-in-human (FIH) study (NCT02361723).

Methods: Chinese patients with advanced non-mucinous high-grade ovarian cancer (HGOC) or triple-negative breast cancer (TNBC) whose disease either progressed despite standard therapy, or for which there is no standard therapy were enrolled in the dose-escalation (DE) portion of a phase 1/2 study (NCT03333915). The primary endpoint was safety/tolerability; secondary objectives were pharmacokinetics and antitumor activity.

On design of robust sliding mode observer for nonlinear networked time-delay systems with communication constraints.

For a class of nonlinear discrete-time networked systems with time-delay and communication constraints, this paper is concerned with the design of robust sliding mode observer (SMO), where only one sensor node is allowed to transmit information to remote observer. We focus on the design of SMO to guarantee the exponentially stable of estimation error system and have a desired H disturbance attenuation level in presence of communication constraints. Firstly, a sensor selector is introduced such that only one sensor node is chosen and its measurement can be transmitted to remote SMO at each time instant.

Global DNA Hypomethylation in Epithelial Ovarian Cancer: Passive Demethylation and Association with Genomic Instability.

A hallmark of human cancer is global DNA hypomethylation (GDHO), but the mechanisms accounting for this defect and its pathological consequences have not been investigated in human epithelial ovarian cancer (EOC). In EOC, GDHO was associated with advanced disease and reduced overall and disease-free survival. GDHO (+) EOC tumors displayed a proliferative gene expression signature, including and overexpression.

Secure dimensionality reduction fusion estimation against eavesdroppers in cyber-physical systems.

This paper studies the distributed dimensionality reduction fusion estimation problem for cyber-physical systems with limited bandwidth in presence of eavesdroppers. Since wireless communication is implemented by broadcasting, the eavesdroppers can collude to collect the data through anther communication networks. To protect data privacy, based on the physical processes and local estimation error covariance (EEC) matrix, an insertion method of artificial noise (AN) is developed such that only eavesdroppers' fusion EEC becomes worse.

[Responses of soil microbial biomass C and P to different long-term fertilization treatments in the yellow paddy soil].

To explore the rational fertilization mode to improve the availability of soil phosphorus (P), we analyzed the changes and coupling characteristics of soil carbon (C) and P, microbial biomass C (MBC) and P (MBP) under different fertilization modes with a successive 22-year field experiment in yellow paddy soil. The experiment had 10 treatments, including no fertilization (CK), single application of nitrogen (N), combination of phosphorus and potassium (PK), combination of nitrogen and potassium (NK), combination of nitrogen and phosphorus (NP), combination of nitrogen, phosphorus and potassium (NPK), single application of organic fertilizer (M), and three organic-inorganic fertilizer combinations (1/4M+3/4NP, 0.5MNP, MNPK).

Set-Membership Estimation for Complex Networks Subject to Linear and Nonlinear Bounded Attacks.

This paper is concerned with the set-membership estimation problem for complex networks subject to unknown but bounded attacks. Adversaries are assumed to exist in the nonsecure communication channels from the nodes to the estimators. The transmitted measurements may be modified by an attack function with added noise that is determined by the adversary but unknown to the estimators.

Epigenetic activation of POTE genes in ovarian cancer.

The POTE gene family consists of 14 homologous genes localized to autosomal pericentromeres, and a sub-set of POTEs are cancer-testis antigen (CTA) genes. POTEs are over-expressed in epithelial ovarian cancer (EOC), including the high-grade serous subtype (HGSC), and expression of individual POTEs correlates with chemoresistance and reduced survival in HGSC. The mechanisms driving POTE overexpression in EOC and other cancers is unknown.

Expression of the POTE gene family in human ovarian cancer.

The POTE family includes 14 genes in three phylogenetic groups. We determined POTE mRNA expression in normal tissues, epithelial ovarian and high-grade serous ovarian cancer (EOC, HGSC), and pan-cancer, and determined the relationship of POTE expression to ovarian cancer clinicopathology. Groups 1 & 2 POTEs showed testis-specific expression in normal tissues, consistent with assignment as cancer-testis antigens (CTAs), while Group 3 POTEs were expressed in several normal tissues, indicating they are not CTAs.

Distributed H Estimation in Sensor Networks With Two-Channel Stochastic Attacks.

This paper is concerned with the distributed estimation problem in sensor networks subjected to unknown attacks. Network attacks are considered to exist in two classes of channels: 1) communication channels from the plant to sensors and 2) communication channels among sensors. The status of an attack is viewed as a stochastic phenomenon, and the transmitted information will be affected when the attacker successfully carries out an attack on the related data packet.

[Effect of Denitrification and Phosphorus Removal Microorganisms in Activated Sludge Bulking Caused by Filamentous Bacteria].

Activated sludge bulking or foaming caused by filamentous bacteria is a frequent problem in the operation and management of wastewater treatment plants. To clarify the effect of filamentous bacteria sludge bulking on the functional flora in the biological denitrification and phosphorus removal system, morphological identification and Illumina MiSeq sequencing were applied to investigate the distribution of key micro-flora from the non-bulking period, sludge bulking period, and biological foaming period in five municipal wastewater treatment plants. The results showed that the sludge bulking and biological foaming were caused by when the maximum contents were 6% and 38%, respectively.

[Effect of long-term application of NPK fertilizer on maize yield and yellow soil nutrients sustainability in Guizhou, China].

A long-term fertilization field experiment was conducted to investigate the effect of nitrogen (N), phosphorus (P), and potassium (K) fertilizer on maize relative yield, yield-increasing effect and the changes of nutrients in yellow soil in Guizhou Province. Five fertilizer combinations were evaluated, including balanced fertilization (NPK) and nutrient deficiency treatments (N, NK, NP, and PK). The maize relative yield, contribution efficiency of N, P, K fertilizer application, sustainability index of soil N, P, K nutrients, and other indicators were measured.

Multisensor-Based Periodic Estimation in Sensor Networks With Transmission Constraint and Periodic Mixed Storage.

In this paper, we consider a periodic estimation problem in sensor networks with a shared communication channel. The transmission constraint is inevitable in a single-channel-based sensor network if the sensors are heterogeneous or deployed far away from each other. A novel stochastic competitive transmission strategy is presented to deal with the transmission constraint, such that the sensors communicate with the fusion center (FC) in a strict asynchronous manner.

[Response of Olsen-P to P balance in yellow soil upland of southwestern China under long-term fertilization.].

Based on a long-term fertilization experiment in Guizhou Province, we explored the relationships between the soil available phosphorus (Olsen-P), soil apparent P balance and P application rate in order to quantify the best application rate of P fertilizer in yellow upland soil of southwestern China. Moreover, the response curve of crop yield to soil Olsen-P was fitted by Mitscherlich equation to determine the critical content of Olsen-P for crop yield. The results showed that the long-term application of P fertilizer could significantly increase the content of soil Olsen-P, and the increasing rates of Olsen-P across different treatments could be mainly explained by the application rate of P fertilizer.