Ageing of the immune system, or immunosenescence, contributes to the morbidity and mortality of the elderly
. To define the contribution of immune system ageing to organism ageing, here we ...selectively deleted Ercc1, which encodes a crucial DNA repair protein
, in mouse haematopoietic cells to increase the burden of endogenous DNA damage and thereby senescence
in the immune system only. We show that Vav-iCre
;Ercc1
mice were healthy into adulthood, then displayed premature onset of immunosenescence characterized by attrition and senescence of specific immune cell populations and impaired immune function, similar to changes that occur during ageing in wild-type mice
. Notably, non-lymphoid organs also showed increased senescence and damage, which suggests that senescent, aged immune cells can promote systemic ageing. The transplantation of splenocytes from Vav-iCre
;Ercc1
or aged wild-type mice into young mice induced senescence in trans, whereas the transplantation of young immune cells attenuated senescence. The treatment of Vav-iCre
;Ercc1
mice with rapamycin reduced markers of senescence in immune cells and improved immune function
. These data demonstrate that an aged, senescent immune system has a causal role in driving systemic ageing and therefore represents a key therapeutic target to extend healthy ageing.
•Relationship between relative natural frequency change curves and mode shapes.•A novel strategy for damage localization and severity estimation based on relative natural frequency changes.•Numerical ...and experimental verification of the proposed method.•Investigation on elimination of temperature effect in damage localization.
Concentrated damage such as cracks is one of the most common types of damage in beams. It is essential to detect such damage early to avoid structural failure. Vibration-based damage detection methods that employ changes in structural dynamic parameters such as natural frequencies have been extensively studied, and it is commonly acknowledged that natural frequencies depicting structural global dynamic properties are incompetent to portray local damage. Differing from extant work, this study presents a concept of relative natural frequency change (RNFC) curves for local damage characterization and especially ascertains the relationship between RNFC curves and mode shapes, leading to an explicit equation of RNFC. With RNFC curves and measured values of RNFCs, a two-step method for localizing and quantifying damage is created: a novel probabilistic damage indicator is developed using Bayesian data fusion for localizing single and multiple damage; moreover, a damage severity factor defined as the stiffness reduction ratio of the damaged element is formulated to quantify damage. The proposed method features localization, quantification, and evolution monitoring of damage, relying solely on natural frequencies. The efficacy of the method is verified numerically and then validated experimentally on cracked beams. The numerical and experimental results demonstrate the capability of the method to localize single and multiple damage and to estimate damage severity. This mechanism of characterizing damage relying solely on natural frequencies provides the foundation for developing practical local damage detection and monitoring technologies for beam-type structures.
AbstractPredisaster damage predictions and postdisaster damage assessments often inadequately capture the intensity and spatial–temporal complexity of natural hazard-caused damage. Accurate ...identification of areas with the greatest need in the wake of a disaster requires assessment of both the hazards and community vulnerabilities. This study evaluated the contribution of eight hazard and vulnerability drivers of structural damage due to Hurricane María in Puerto Rico, including wind, flood, landslide, and vulnerability measures via ensemble decision tree algorithms. Results from the algorithms indicate that vulnerability measures, including a structural vulnerability index and a social vulnerability index, were the leading predictors of damage, followed by wind, flood, and landslide measures. Therefore, it is critical to consider community vulnerabilities in damage pattern analyses and targeted, predisaster mitigation efforts.
Advanced nanodevices require reliable nanocomponents where mechanically-induced irreversible structural damage should be largely prevented. However, a practical methodology to improve the plastic ...reversibility of nanosized metals remains challenging. Here, we propose a grain boundary (GB) engineering protocol to realize controllable plastic reversibility in metallic nanocrystals. Both in situ nanomechanical testing and atomistic simulations demonstrate that custom-designed low-angle GBs with controlled misorientation can endow metallic bicrystals with endurable cyclic deformability via GB migration. Such fully reversible plasticity is predominantly governed by the conservative motion of Shockley partial dislocation pairs, which fundamentally suppress damage accumulation and preserve the structural stability. This reversible deformation is retained in a broad class of face-centred cubic metals with low stacking fault energies when tuning the GB structure, external geometry and loading conditions over a wide range. These findings shed light on practical advances in promoting cyclic deformability of metallic nanomaterials.
During earthquake events, a mainshock may trigger a number of following aftershocks in a short time, which can cause additional damage to structures. This paper investigates the influence of ...aftershocks with different durations on the additional accumulative damage of containment structures considering the post-mainshock damage states. For this purpose, 15 as-recorded mainshock-aftershock records with a broad range of aftershock durations, which are scaled and adjusted to match the target spectrum using wavelet transformation, are considered in this study. The three-dimensional structural model which can capture the strength and stiffness degradation during seismic sequences is established. A normalized ‘damage ratio’ measuring tensile and compressive damage is proposed to quantify the accumulative damage from seismic sequences. The results indicate that aftershocks with longer durations can cause more severe accumulative damage and have a significant effect on the damage pattern. Therefore, to evaluate the safety margin of containment structures accurately, the aftershock and its characteristics of duration should be taken into account when selecting ground motion records for seismic safety assessment of a Nuclear Power Plant.
•The concrete damage plasticity model is used to capture accumulative damage.•Aftershock records are scaled and adjusted to match target spectra using wavelet.•The normalized ‘damage ratio’ are proposed to quantify the accumulative damage.•The post-mainshock damage states of containment buildings are considered.•Aftershock durations amplify the accumulative damage and affect the damage pattern.
•Deep object-based semantic change detection framework (ChangeOS) is proposed.•ChangeOS seamlessly integrates object-based image analysis and deep learning.•City-scale building damage assessment can ...be achieved within one minute.•A global-scale dataset is used to evaluate the effectiveness of ChangeOS.•Two local-scale datasets are used to show its great generalization ability.
Sudden-onset natural and man-made disasters represent a threat to the safety of human life and property. Rapid and accurate building damage assessment using bitemporal high spatial resolution (HSR) remote sensing images can quickly and safely provide us with spatial distribution information and statistics of the damage degree to assist with humanitarian assistance and disaster response. For building damage assessment, strong feature representation and semantic consistency are the keys to obtaining a high accuracy. However, the conventional object-based image analysis (OBIA) framework using a patch-based convolutional neural network (CNN) can guarantee semantic consistency, but with weak feature representation, while the Siamese fully convolutional network approach has strong feature representation capabilities but is semantically inconsistent. In this paper, we propose a deep object-based semantic change detection framework, called ChangeOS, for building damage assessment. To seamlessly integrate OBIA and deep learning, we adopt a deep object localization network to generate accurate building objects, in place of the superpixel segmentation commonly used in the conventional OBIA framework. Furthermore, the deep object localization network and deep damage classification network are integrated into a unified semantic change detection network for end-to-end building damage assessment. This also provides deep object features that can supply an object prior to the deep damage classification network for more consistent semantic feature representation. Object-based post-processing is adopted to further guarantee the semantic consistency of each object. The experimental results obtained on a global scale dataset including 19 natural disaster events and two local scale datasets including the Beirut port explosion event and the Bata military barracks explosion event show that ChangeOS is superior to the currently published methods in speed and accuracy, and has a superior generalization ability for man-made disasters.
The paper presents a general gradient-extended continuum mechanical framework for materials with internal variables based on additional generalized balance equations. The framework is applied to the ...case of anisotropic brittle damage where damage is modeled by a second order damage tensor. Although using a second order damage tensor the proposed efficient formulation being implemented into finite elements uses only one scalar additional nodal degree of freedom. Based on the damage growth criterion a specific form of the elastic strain energy is proposed for initially isotropic materials such that artificial stiffening effects are excluded a priori. Special focus is placed on the numerical implementation at the integration point level: Within the concept of generalized standard materials a regularized dissipation potential is used to cope with different inequality constraints, leading to the introduction of penalty viscosity parameters which are chosen sufficiently large such that the occurring errors remain negligibly small. Furthermore, a novel additional damage hardening is suggested which ensures that the eigenvalues of the damage tensor do not exceed the value one. By means of several numerical examples it is demonstrated that the model delivers mesh-independent results and is able to represent (i) localized damage (fracture) and (ii) diffuse (distributed) damage. Finally, isotropic damage (which can be shown to be a special case of the model) and anisotropic damage are compared considering two numerical examples where the occurrence of either localized or diffuse damage will be shown to be crucial.
•A new damage indicator, Modified Cornwell Indicator (MCI).•MCI performs more efficient then Cornwell Indicator (CI).•MCI is combined with Genetic Algorithm (GA), MCI-GA.•MCI-GA provides more ...accurate and efficient results than other techniques in the literature.
This paper presents a new methodology for damage identification and quantification in two- and three-dimensional structures. The application of the proposed methodology is investigated numerically using Finite Element Method (FEM) and Matlab program. We propose a Modified Cornwell Indicator (MCI) that performs more efficient in damage detection than the standard Cornwell Indicator (CI). Furthermore, MCI is combined with Genetic Algorithm (GA) for further quantification of the detected damage. In GA, MCI, is used as an objective function to compare between measured and calculated indicators. The results of the analysis show that the proposed technique is accurate and efficient, when compared with other techniques in the literature, to estimate the severity of structural damage.
R-loops are three-stranded structures that harbour an RNA-DNA hybrid and frequently form during transcription. R-loop misregulation is associated with DNA damage, transcription elongation defects, ...hyper-recombination and genome instability. In contrast to such 'unscheduled' R-loops, evidence is mounting that cells harness the presence of RNA-DNA hybrids in scheduled, 'regulatory' R-loops to promote DNA transactions, including transcription termination and other steps of gene regulation, telomere stability and DNA repair. R-loops formed by cellular RNAs can regulate histone post-translational modification and may be recognized by dedicated reader proteins. The two-faced nature of R-loops implies that their formation, location and timely removal must be tightly regulated. In this Perspective, we discuss the cellular processes that regulatory R-loops modulate, the regulation of R-loops and the potential differences that may exist between regulatory R-loops and unscheduled R-loops.
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