This study discusses the robust stability problem of Boolean networks (BNs) with data loss and disturbances, where data loss is appropriately described by random Bernoulli distribution sequences. Firstly, a BN with data loss and disturbances is converted into an algebraic form via the semi-tensor product (STP) technique. Accordingly, the original system is constructed as a probabilistic augmented system, based on which the problem of stability with probability one for the original system becomes a set stability with probability one for the augmented system. Subsequently, certain criteria are proposed for the robust stability of the systems. Moreover, an algorithm is developed to verify the robust set stability of the augmented system based on truth matrices. Finally, the validity of the obtained results is demonstrated by an illustrative example.

Aim: Off-reserve conservation is a major contributor to China biodiversity conservation efforts, biodiversity conservation being achieved within afforestation and low-intensity agriculture in fragmented landscapes. Functional trait is more strongly related to ecological processes than taxonomic diversity and reflects ecosystem functioning and species responses to environmental changes. In this study, we selected five habitats that differ in degree of disturbance to explore the effects of land use on ant community compositions, traits distributions and functional diversity change. We assessed how habitat disturbance affects the ant community compositions and traits distributions and asked if ant functional diversity respond to disturbance at the local scale? Location: Lüchun County, Yunnan Province, southwest China. Methods: Pitfall traps were used to survey ant communities. Additionally, we measured four ant morphological traits (eyes diameter, distance between eyes, femur length of the hind-leg and Weber\'s length) to assess the functional traits distributions and functional diversity. Shade plot of ant relative abundance was used to explore species distribution amongst different habitats. Kernel density plot was used to explore ant traits distribution patterns amongst different habitats. Non-metric multi-dimensional scaling ordination, based on ant Weber\'s length, was used to explore the ant traits compositions amongst different habitats. The fourth corner model was used to evaluate the association between ant traits and environmental variables. The FRic, RaoQ and FEve indices were selected as three complementary measures of the multivariate functional traits space and functional redundancy of different habitats. Results: We collected 14258 ants, representing 89 species, 40 genera and seven subfamilies. Aphaenogasterschurri and Tetramoriumciliatum were the common species of secondary forest; P.sagei, P.pieli, Cardiocondylawroughtonii, Recurvidrisnuwa, Tapinnomamelanocephalum, Monomoriumpharaonis and M.orientale were the common species in plantations; and Iridomyrmexanceps and Cardiocondylanuda were the common species in managed farms. Ants had medium eye diameters, narrow distances between eyes, medium leg lengths and smaller body sizes in greatly-disturbed habitats; and ants had an increasing eye diameter and narrowing of the space between eyes, while the leg length and Weber\'s length became shorter in moderately-disturbed habitats. Ant trait composition, based on Weber\'s length, showed significantly differences amongst five habitats. The fourth corner analysis indicated that ant species traits were significantly correlated with environmental variables. The functional diversity of secondary forest, lac plantation and lac plantation-corn agroforest were higher than those in dryland farm and rice paddy. Functional diversities were significantly negatively correlated with bare ground cover and significantly positively correlated with leaf-litter cover, leaf-litter thickness and plant cover. Main conclusion: Our results indicated that ant traits distribution patterns were affected by land-use changes, followed by anthropogenic disturbance pressures at the local scale. Ant traits compositions in greatly-disturbed habitats also differed from the habitats with less disturbance. It is unfavourable for the survival of the large body-size ants in more open habitats with more anthropogenic disturbance. Compared with secondary forest, dryland farm and rice paddies were less resistant and more vulnerable and lac plantations had approximately functional diversity of ant communities, suggesting that lac plantations might be resistant as secondary forest to species loss.

Acute-on-chronic liver failure (ACLF) is a major cause of liver-related death worldwide, but its key pathological features remain incompletely defined. This study aimed to reveal the molecular basis of hepatitis B virus-related ACLF (HBV-ACLF) by transcriptome sequencing of human liver tissue. A total of 18 human liver tissues from patients with different stages of HBV-related disease were collected for RNA sequencing, and liver tissues from patients and mouse models with ACLF were used for subsequent validation. Specifically, 6,853 differentially expressed genes (DEGs) and 5,038 differentially expressed transcripts were identified in patients with ACLF compared to patients with chronic hepatitis B (CHB) and normal controls (NCs). Investigation of functional by KEGG pathway enrichment analysis revealed prominent immune and metabolic dysregulation at the ACLF stage. We found that the key genes FGF19, ADCY8 and KRT17, which are related to immunometabolic disturbances, were significantly upregulated in the progression of ACLF. The three key genes were validated in human and mouse samples, indicating their prognostic and therapeutic potential in ACLF. In summary, our work reveals that immunometabolic disorder is involved in HBV-ACLF pathogenesis and indicates that FGF19, ADCY8 and KRT17 may be sensitive biomarkers for HBV-related ACLF.

BACKGROUND: Countries seeking to mitigate climate change through forests require suitable modelling approaches to predict carbon (C) budget dynamics in forests and their responses to disturbance and management. The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) is a feasible and comprehensive tool for simulating forest C stock dynamics across broad levels, but discrepancies remain to be addressed in China. Taking Guizhou as the case study, we customised the CBM-CFS3 model according to China\'s context, including the modification of aboveground biomass C stock algorithm, addition of C budget accounting for bamboo forests, economic forests, and shrub forests, improvement of non-forest land belowground slow dead organic matter (DOM) pool initialisation, and other model settings.
RESULTS: The adequate linear relationship between the estimated and measured C densities (R2 = 0.967, P < 0.0001, slope = 0.904) in the model validation demonstrated the high accuracy and reliability of our customised model. We further simulated the spatiotemporal dynamics of forest C stocks and disturbance impacts in Guizhou for the period 1990-2016 using our customised model. Results shows that the total ecosystem C stock and C density, and C stocks in biomass, litter, dead wood, and soil in Guizhou increased continuously and significantly, while the soil C density decreased over the whole period, which could be attributed to deforestation history and climate change. The total ecosystem C stock increased from 1220 Tg C in 1990 to 1684 Tg C in 2016 at a rate of 18 Tg C yr-1, with significant enhancement in most areas, especially in the south and northwest. The total decrease in ecosystem C stock and C expenditure caused by disturbances reached 97.6 Tg C and 120.9 Tg C, respectively, but both represented significant decreasing trends owing to the decline of disturbed forest area during 1990-2016. Regeneration logging, deforestation for agriculture, and harvest logging caused the largest C stock decrease and C expenditure, while afforestation and natural expansion of forest contributed the largest increases in C stock.
CONCLUSIONS: The forests in Guizhou were a net carbon sink under large-scale afforestation throughout the study period; Our customised CBM-CFS3 model can serve as a more effective and accurate method for estimating forest C stock and disturbance impacts in China and further enlightens model customisation to other areas.

Baoji is a typical heavy industrial city in northwest China. Its air quality is greatly impacted by the emission from the factories. Elements in fine particulate matter (PM2.5) that are greatly emitted from anthropogenic sources could pose diverse health impacts on humans. In this study, an online AMMS-100 atmospheric heavy metal analyzer was used to quantify 30 elements in PM2.5 under the weak and strong anthropogenic disturbance scenarios before the city lockdown period (from January 9th to 23rd) and the lockdown period (from January 26th to February 9th) due to the outbreak of COVID-19 in 2020. During the lockdown period, the average total concentration of total quantified elements was 3475.0 ng/m3, which was 28% and 33% lower than that of the week and strong anthropogenic disturbance scenarios during the pre-lockdown period. The greatest reductions were found for the elements of chromium (Cr), titanium (Ti), manganese (Mn), and Zinc (Zn), consistent with the industrial structure of Baoji. The mass concentrations of most elements showed obvious reductions when the government post-alerted the industries to reduce the operations and production. Dust, traffic sources, combustion, non-ferrous metal processing, and Ti-related industrial processing that are the contributors of the elements in the pre-lockdown period were apportioned by the positive matrix factorization (PMF) model. Substantial changes in the quantified elements\' compositions and sources were found in the lockdown period. Health assessment was conducted and characterized by apportioned sources. The highest non-carcinogenic risk (HQ) was seen for Zn, demonstrating the high emissions from the related industrial activities. The concentration level of arsenic (As) exceeded the incremental lifetime carcinogenic risk (ILCR) in the lockdown period. This could be attributed to the traditional firework activities for the celebration of the Chinese New Year within the lockdown period.

This paper is concerned with a theoretical investigation on the robust modified function projective lag synchronization (MFPLS) between two complex networks with nonlinear couplings, different-dimensional nodes, parameter disturbances and external disturbances. Some novel robust hybrid controllers are designed to address such synchronization problems for networks with and without disturbances, in which adaptive updated laws of disturbances are adopted to attenuate the disturbances occurred in networks. By utilizing Lyapunov functional method, synchronization criteria are derived by strict theoretical proof. Compared with existing jobs, the proposed model and synchronization type are more general. Two examples are presented to verify our results.

In this paper, we investigated the finite-time consensus tracking problem for multi-agent systems with external bounded disturbances and input bounded disturbances and unknown velocities. Based on the Lyapunov finite-time theorem, a novel finite-time consensus control is constructed by using the backstepping method. For unknown velocities, the high-gain observer is used to estimate the velocity information. It is proved that the consensus can be achieved in finite time. The consensus shows fast response and strong robustness to various disturbances. Finally, the effectiveness of the results is illustrated by numerical simulations.

The distribution of external phosphorus (P) in the overlying water, pore water, and sediment under different disturbances were investigated and the transformation between internal P forms was analyzed. The results show that physical disturbances can promote the migration of external P from the overlying water to the sediment. In addition, the enhancement was even higher due to the bioturbation of the combined disturbances. Noticeably, the improvement of the P migration in the control was lowest, compared with the three disturbances. This may be attributed to the penetration of dissolved oxygen. Meanwhile, the physical disturbance reduced the average content of (dissolved organic phosphorus) DIP in the pore water by 12.13% (a mean of 6d and 10d), compared with the control. However the reduction was less than that associated with the bioturbation (38.63%) and the combined disturbance (50.79%), respectively. These three disturbances may promote the formation of Fe/Al-P and Ca-P. The formation of Fe/Al-P and Ca-P was largest under the physical disturbance. However, the algal-available phosphorus (AAP) is reduced due to the physical disturbance, suggesting that physical disturbance may promote the transformation of AAP to occluded Fe/Al-P or Ca-P.

In this paper, the H∞ performance and control problems for linear systems with interval state or input delays and disturbances are investigated. In order to exploit more information on the delay range, the quadruple -integral terms and quadratic forms of triple integrals are introduced into the Lyapunov-Krasovskii functional (LKF). Particularly, an improved integral inequality is developed for estimation of the cross terms in triple-integral type, which displays significant improvement over the Wirtinger inequality. As a result, a less conservative H∞ performance criterion is derived without requiring many slack variables. Based on the criterion, the H∞ controller design approaches are obtained. Besides the numerical examples, the applications to the practical systems are also provided to illustrate the effectiveness of the proposed approaches.

Due to the nonlinearity and time variation of a two-axis inertially stabilized platform (ISP) system, the conventional feedback control cannot be utilized directly. To realize the control performance with fast dynamic response and high stabilization precision, the dynamic model of the ISP system is expected to match the ideal model which satisfies the desired control performance. Therefore, a composite control method based on the adaptive radial basis function neural network (RBFNN) feedback control and the extended state observer (ESO), is proposed for ISP. The adaptive RBFNN is proposed to generate the feedback control parameters online. Based on the state error information in the working process, the adaptive RBFNN can be constructed and optimized directly. Therefore, no priori training data is needed for the construction of the RBFNN. Furthermore, a linear second-order ESO is constructed to compensate for the composite disturbance. The asymptotic stability of the proposed control method has been proven by the Lyapunov stability theory. The applicability of the proposed method is validated by a series of simulations and flight tests.