Damage Assessment Research Articles

Proteomics to Study Parchment Degradation – From Bulk to Spatial Analysis

Abstract Implementing biomolecular techniques in the study of written cultural heritage has led to a steady development of biocodicology and the study of DNA and proteins in parchment in the past years. In this context, matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) has gained increasing attention as a powerful tool to study the ancient writing support. With a particular focus on the main components of parchment – different types of collagens – proteomic applications of the technique are highlighted. The review summarises advances in biocodicological studies focusing on manufacturing aspects and conservation treatments. Herein we further investigated proteomic studies on animal skin to prove the potential of MALDI-MS imaging (MALD-MSI) to broaden our knowledge and take studies on damage assessment and degradation of parchment to another level.

Fiber and matrix-level damage detection and assessments for natural fiber composites

Fiber and matrix-level damage detection and assessments for natural fiber composites

Fatigue damage assessment of a large rail-cum-road steel truss-arch bridge using structural health monitoring dynamic data

Structural health monitoring (SHM) system provides valuable information for the fatigue assessment of existing rail-cum-road bridges. This paper aims to develop an effective fatigue assessment approach for the rail-cum-road bridge, Jiujiang Yangtze River Bridge, by utilising the SHM data, focusing on dynamic modal analysis, finite element model updating and fatigue assessment. First, the traffic load spectrum and modal characteristics of the bridge are investigated from the SHM data. A three-dimensional finite element model is constructed and then updated by using the measured modal data through the proposed regularised model updating method. Then, the updated numerical model is verified with the measured dynamic response data, which can be utilised for calculating stress response at critical structural components of the rail-cum-road bridge. Finally, an improved Corten-Dolan’s model is proposed to analyse the fatigue damage and structural reliability of the critical structural components of the bridge, taking into account the combined effects of train and highway vehicle loads. The results demonstrate that the proposed fatigue assessment method provides more reliable results for the rail-cum-road bridge by considering the combined effect of multi-level traffic loads and the non-linear fatigue damage accumulation. It is concluded that the short H-shaped suspender is identified as the most vulnerable structural member of the rail-cum-road bridge, and the remaining fatigue service life of the typical components of the bridge should meet the design requirement.

Multivariable fragility surfaces for earthquake-induced damage assessment of buildings integrating structural features

Multivariable fragility surfaces for earthquake-induced damage assessment of buildings integrating structural features

Morphological Changes in Allergenic Pollen as a Bioindicator

Since the anther opens and the pollen grains travel in the atmosphere, they can come into contact with solid and gaseous particles, and the exine can become contaminated with various adherent particles. Pollen and solid particles are among the most common triggers of bronchial asthma. Increased allergenicity of pollen grains will be determined by chemical reactions between pollutants and pollen, as well as non-specific modulation of the mechanisms of synthesis of many proteins, lipids and enzymes in response to environmental stress due to urbanization and climate change. This situation seriously complicates the identification of pollen to a taxon during traditional monitoring and further complicates the calculation and interpretation of the results obtained during research and automatic determination. To classify tetramorphic pollen from aerobiological samples and explain the mechanism of the identified changes. Determination of mutagenic contamination and a method for integral assessment of pollen viability and damage under a light microscope. Pollen from aerobiological samples was examined under a scanning electron microscope (Hitachi): a high-power imaging technique that uses electron beams to create detailed images of the ultrastructure of pollen grains. Unidentified, tetramorphic pollen from aerobiological samples from sites with varying degrees of contamination can be conditionally classified into 4 types: 1) shapeless lumps of sporopollenin with various outgrowths, cracks and cavities that arose during pollen ontogenesis; 2) atypical ornamentation of sculpture, such as large tubercles - swellings with a smooth surface; 3) atypical form, but with partially preserved sculpture, where in places species-specific features can be identified and pollen can be identified to a taxon; 4) conglomerates. The study of the vitality (viability) and damage of the cocksfoot pollen under a light microscope from observation points with different anthropogenic loads showed the dependence of these indicators on the level of pollutants: with their increase, viability decreases, although it remains quite high. The data obtained are important for assessing allergenic pollen as a bioindicator of environmental changes. An integrated assessment of the enzymatic activity of pollen and the degree of its damage can be used for the purposes of bioecological monitoring.

Hazard assessment of rice cold damage based on energy balance in paddy field

Cold stress seriously affects rice yield in Northeast China and, as a result of climate change, there are new trends in the characterization of cold damage. Accurate simulation of water temperature in paddy fields and assessment of cold damage hazard can contribute to improving the accuracy of agrometeorological disaster risk assessment in the context of climate change. Hence, in this study, first, we simulated the water temperature of paddy fields based on the paddy field energy-balance model and evaluated the simulation results. Subsequently, a composite cooling-degree-day (CCDD) indicator for rice fields was constructed based on water and air temperatures to characterize cold stress and identify cold damage events. Finally, a cold damage hazard-assessment model was constructed for rice based on the frequency and intensity of cold damage to assess cold damage hazard in Northeast China from 1979 to 2018. The results showed that the root-mean-square error between simulated and observed water temperatures of the rice field energy-balance model was 0.45, which means that the model accurately simulated the water temperature of the rice field on a large spatial scale. In 2004, cold damage to late-maturity rice accounted for 30% of the total study area, which was one of the years with most severe cold damage in late-maturity rice-growing areas thus far in the 21st century. Water temperature affected 76.4% of the area in 2004, and was related to radiation and saturated vapor pressure. The low-hazard areas accounted for more than 20% in 2009–2018, and the high-hazard areas were still higher than 10%, indicating that the threat of cold damage in the northeastern region of China remained severe as the climate has become increasingly warm.

Analysis of concrete damage at anchorage end of the high-speed railway bridge sound barrier under the 400 km/h train-induced wind loads

The sound barrier installed on high-speed railway bridges withstands repeated train-induced wind load, which may lead to concrete damage at its anchorage end. This paper focuses on the assessment of concrete static damage at the sound barrier anchorage end under train-induced wind loads. The nonlinear finite element model of the sound barrier anchorage system is established to analyze the stress distribution, strain distribution and static damage of concrete structure at the anchorage end under 400 km/h train-induced wind loads in respect of different bolt preloads. The simulated results illustrate that both mortar and concrete near bolt holes suffer a certain degree of tensile and compressive damage. The maximum tensile and compressive damage factor values for mortar and concrete are 0.930, 0.643 and 0.892, 0.434 respectively. In addition, the effects of train-induced wind load on the internal force of the sound barrier anchorage take nearly no account, with a maximum of only 0.68 %. The results indicate that bolt preload is the most significant factor for concrete static damage, while the train-induced wind load appears negligible. An appropriate bolt preload can avoid the concrete static damage of the sound barrier anchorage end, and guarantee the structural stability of the sound barrier.

Progressive damage and stiffness degradation assessments of double‐lap CFRP/Ti interference fit bolted joints under quasi‐static tensile load

AbstractMatrix crack propagation and stiffness degradation behaviors of the carbon fiber reinforced polymer/titanium alloy (CFRP/Ti) bolted joint were characterized by a synergistic damage mechanics approach. The parametric study including pre‐tightening torques and interference fit sizes was conducted. The results showed that the joint stiffness degradation exhibited characteristics of local stiffness degradation due to local stress concentration. Stiffness degradation in different plies was caused by matrix crack damage occurring in different directions. The pre‐tightening torque significantly increased the joint stiffness and restrain matrix crack progression, effectively inhibiting the stiffness degradation of the joint. Moreover, the low interference fit level delayed the crack initiation in −45° ply and 45° ply and the crack propagation of the laminate, while promoted the crack initiation in 90° ply. The stiffness degradation of the laminate could be significantly reduced by interference fit.Highlights Matrix crack propagation and stiffness degradation behaviors of the CFRP laminate were characterized by a synergistic damage mechanics method. A FE model of the CFRP/Ti double‐lap interference fit bolted joint was established. Influences of pre‐tightening torques on both matrix crack initiation and propagation were investigated. The optimum interference fit size of the matrix damage strengthening was 0.20%–0.60%.

Inactivated LMBV vaccine with nano‑aluminum adjuvant provided immune protection in largemouth bass (Micropterus Salmoides)

Largemouth bass ranavirus (LMBV) has caused severe economic losses in largemouth bass (Micropterus salmoides) aquaculture. Vaccination is acknowledged as an efficient strategy to prevent viral diseases in fish. In this study, an inactivated virus vaccine with nano‑aluminum adjuvant was successfully developed to protect largemouth bass effectively against LMBV. LMBV was inactivated by formalin and mixed with nano‑aluminum adjuvant under moderate agitation. The nano‑aluminum hydroxide adjuvant showed a cuboidal structure under the scanning transmission electron microscope (STEM), scanning electron microscope (SEM), and transmission electron microscope (TEM), and LMBV antigen-adsorbing rate was 39.49 % superior to those of micro‑aluminum hydroxide and IMS1312 adjuvants. The results from both external and internal damage assessments indicated that the nano‑aluminum vaccine had good safety for Micropterus salmoides. The relative percentage of survival was 80 % with a booster immunization in largemouth bass. The expression levels of immune-related genes such as TNF-α, IFN, and IL-8 were significantly up-regulated in the spleen of fish immunized by nano‑aluminum adjuvant vaccine compared to those in inactivated LMBV and control groups. The neutralizing antibody in nano‑aluminum adjuvant vaccine group showed higher abundance and lasted for a longer period. Lymphocytes from the head kidney of largemouth bass in the nano‑aluminum adjuvant vaccine group showed stronger proliferation activity in vitro post-stimulation with ConA. Moreover, stronger migration of the dendritic cells was induced by the nano‑aluminum adjuvant vaccine. Collectively, our findings suggested that the inactivated LMBV vaccine with nano‑aluminum adjuvant could provide efficient protection for largemouth bass against LMBV infection. The nano‑aluminum adjuvant has potential application with inactivated viral vaccines in fish.

Assessment of damage in Takayasu arteritis in the clinic: an idea whose time has come!

Assessment of damage in Takayasu arteritis in the clinic: an idea whose time has come!

Limit hypersurface state-of-the-art damage assessment approach for a galloping energy harvester, accounting for memory effects

Energy harvesters (i.e., EH) constituting nowadays an essential part of renewable energy engineering; hence, apart from numerical modeling, experimental studies are necessary, constituting reliable input for durable design and structural safety assessments. In the current study, galloping EH’s performance was analyzed, utilizing extensive laboratory wind-tunnel tests, conducted under realistic windspeed conditions. The novel structural multivariate risks assessment methodology, presented in the current study is particularly feasible for multi-dimensional nonlinear EH dynamic systems, that have been either directly Monte Carlo (i.e., MC) numerically simulated or physically measured over a representative temporal lapse, providing piecewise ergodic time series. As shown in this analysis, the suggested multivariate methodology accurately enables accurate predictions of the EH dynamic system’s failure/hazard or damage risks, based on laboratory-measured EH system’s dynamics. Furthermore, nonlinear inter-correlations between various systems’ critical components are not always easily handled by classic risk assessment techniques, when dealing with a high-dimensional system’s raw time series. The primary goal of this study was validation and benchmarking the novel risk assessment methodology, which can extract pertinent information, contained within the EH system’s dynamics, based on lab-recorded time histories. In conclusion, the novel hypersurface methodology presented in this study is generic, providing additional capability to accurately, yet efficiently predict damage/failure risks for a variety of nonlinear EH multidimensional systems. Relatively narrow confidence bands have been reported for the forecasted damage and failure levels, indicating both the robustness of the experimental setup, as well as practical design virtues of the advocated Gaidai hypersurface risks assessment methodology. Note that the presented methodology being mathematically exact does not rely on pre-assumptions and yet it is of general purpose.

Study of the Physiological Characteristics of Drivers Facing Apparent Changes in Highway Tunnel Structures

The increasing frequency of structural damage and reinforcement repairs in long-term highway tunnels necessitates an understanding of their effects on drivers. This study examines drivers’ physiological responses to visible structural changes in highway tunnels. Using a vehicle static in-the-loop platform, we created various models of apparent tunnel structure changes for simulated driving experiments. These experiments enabled a detailed analysis of the effects of such changes on driver safety, utilizing metrics such as eye movements, regions of interest, heart rate, and vehicle speed. The results show that visible alterations in tunnel structures significantly affect drivers’ physiological responses. Structural spalling and fire residues within tunnel structures notably increased drivers’ vigilance and psychological stress, resulting in a 14.7% increase in the average number of fixations, a 26.35% increase in the average duration of fixations, and a 36.05% increase in heart rate variability. Additionally, tunnel spalling tends to cause drivers to accelerate or exceed the speed limit, with maximum speeds reaching 17.87% above the designed speed. In contrast, repairs involving cover arch erection had minimal impact on drivers, with eye movement and heart rate data similar to those in ordinary tunnels. However, reinforcement with steel strips and corrugated steel in tunnels has attracted significant attention, with the area of interest exceeding 50% of the tunnel area, potentially leading to distracted driving. This study clarifies the extent of the influence of visible tunnel structure changes on drivers, providing a reference for damage assessment, reinforcement, and repair measures for long-term operated tunnels.

Deep Learning Method for Post-earthquake Damage Assessment of Frame Structures Based on Time–Frequency Analysis and CGAN

Deep Learning Method for Post-earthquake Damage Assessment of Frame Structures Based on Time–Frequency Analysis and CGAN

Drug supply management at first-level public health facilities: Case of Pyay District, Myanmar.

First-level public health facilities (PHFs) serve as primary providers of essential medicines, necessitating critical attention to drug availability and quality assurance. This study aimed to examine the status of functional areas within the drug supply chain management framework and assess the overall capability maturity at first-level PHFs. The cross-sectional study was conducted among 183 drug store sites from six townships of Pyay District. Only situational analysis was exercised to determine the existing situations. The overall capability maturity was determined according to the definitions of levels of the Capability Maturity Module Tool. 58.47% lacked formal drug supply management training, with 23.5% not undergoing performance reviews. Drug forecasting predominantly relied on a pen-paper system (91.6%) and factors like patient load (87.39%), drug consumption (85.71%), and disease prevalence (64.71%). Store site analysis revealed that 65.03% exhibited marginal capability, lacking standardized drugstores and employing unstandardized procedures. Storage practices varied, with 48.69% storing drugs conveniently and others categorizing them by drug type (32.79%) or using the first-expired-first-out system (40.98%). Approximately 42.69% reported having expired drugs. Concerning transportation costs, 37.16% incurred expenses exceeding 20,000 Kyats per time, with management staff often covering the costs. Waste management methods included burial pits (49.18%), incineration (62.84%), and sharp pits (55.19%). A majority (78.14%) used safety boxes, and 57.38% implemented a color-coded system for waste bins. The logistics management information system was entirely paper-based (100%). On average, assessments of drug quality conditions and physical damages scored 46.51% and 48.20%, respectively. The overall supply chain maturity at first-level public health facilities is at a marginal capability level (36.35%). While some basic drug supply chain management procedures were in place, they were not consistently followed, and many systems remain manual. The findings underscored significant inconsistencies in the management functions of supplied drugs, with poor adherence to Standard Operating Procedure guidelines.

Potential of Non-Contact Dynamic Response Measurements for Predicting Small Size or Hidden Damages in Highly Damped Structures.

Vibration-based structural health monitoring (SHM) is essential for evaluating structural integrity. Traditional methods using contact vibration sensors like accelerometers have limitations in accessibility, coverage, and impact on structural dynamics. Recent digital advancements offer new solutions through high-speed camera-based measurements. This study explores how camera settings (speed and resolution) influence the accuracy of dynamic response measurements for detecting small cracks in damped cantilever beams. Different beam thicknesses affect damping, altering dynamic response parameters such as frequency and amplitude, which are crucial for damage quantification. Experiments were conducted on 3D-printed Acrylonitrile Butadiene Styrene (ABS) cantilever beams with varying crack depth ratios from 0% to 60% of the beam thickness. The study utilised the Canny edge detection technique and Fast Fourier Transform to analyse vibration behaviour captured by cameras at different settings. The results show an optimal set of camera resolutions and frame rates for accurately capturing dynamic responses. Empirical models based on four image resolutions were validated against experimental data, achieving over 98% accuracy for predicting the natural frequency and around 90% for resonance amplitude. The optimal frame rate for measuring natural frequency and amplitude was found to be 2.4 times the beam's natural frequency. The findings provide a method for damage assessment by establishing a relationship between crack depth, beam thickness, and damping ratio.

Comparative analysis of saliency map algorithms in capturing visual priorities for building inspections

This study investigates the efficacy of saliency mapping algorithms in capturing the visual priorities of building inspectors for structural damage assessment. Our work established a ground truth dataset by implementing eye-tracking technology to capture the gaze patterns of building inspectors. Further, it enables a detailed evaluation of the saliency models’ ability to reflect experts' visual attention during inspection tasks. Our comparative analysis assesses the performance of three saliency models— EnDec, DeepGaze, and SALICON— against this ground truth data, using conventional saliency metrics such as Area under the Curve, Similarity, Normalized Scanpath Saliency, Correlation Coefficient, and Kullback-Leibler Divergence. Our findings reveal that while the SALICON model demonstrates a marginally better performance and highlights areas where these models fall short, particularly in accurately reflecting the critical visual properties of inspectors, this insight is crucial for advancing the field. By highlighting these limitations, we have drawn attention to the need for developing more specialized saliency models tailored to the unique demands of building inspection tasks. Thus, the study not only fulfills its objectives of comparative analysis but also contributes to the broader discourse on improving automated structural inspection systems. This study highlights the need to develop specialized computer vision models to address specific building inspection challenges. By identifying strengths and improvement areas, this research contributes valuable insights and highlights the potential and current limitations of applying computer vision techniques to real-world building inspection tasks.

A combined RF–GRNN algorithm for monitoring complex damage of bolted joints with high-level robustness

Bolted joints in aerospace, rail transportation, civil engineering, and other applications are prone to various forms of damage, such as bolt loosening and crack, due to the harsh service environments. The difficulties arising from crosstalk and nonlinear evaluation between composite damage and single damage at bolted joints in practical monitoring environments are particularly pronounced. In response to this challenge, we propose an integrated algorithm, namely the random forest-generalized regression neural network (RF–GRNN) algorithm, characterized by high-level robustness. The proposed algorithm adheres to the core concept of “specificity” and forms a multi-task prediction framework of “classification before regression.” This approach enables efficient damage assessment and mitigates the nonlinear complexity of the prediction model. To evaluate the effectiveness of the RF–GRNN algorithm, its generalization, robustness, and prediction accuracy based on the piezoelectric ultrasonic guided wave principle under 0%–10% noise (the corresponding minimum signal-to-noise ratio was 10.4 dB) interference were investigated. Additionally, we clarify the impact of feature selection and its combination method on the algorithm’s prediction performance, deciphering the intrinsic link between prediction performance and feature distribution. The results demonstrate that the presented algorithm achieves the accurate classification and quantification of multiple bolted structural states, including no damage, crack, loosening, and crack-loosening composite damage. Therefore, the RF–GRNN algorithm is an important attempt to solve the bottleneck present in existing damage monitoring techniques which fail to balance the identification and quantification of multiple damage models.

Mbda-net: a building damage assessment model based on a multi-scale fusion network

Mbda-net: a building damage assessment model based on a multi-scale fusion network

Population dynamics and crop damage assessment of Scarabaeid pests in the North-Western Himalayas

Scarabs are pests of horticultural crops in the north-western Himalayan regions. However, our current understanding falls short in comprehending the factors driving the population flare-ups of these pests. We investigated the pest population dynamic of Melolontha sp. Fabricius (Coleoptera: Scarabaeidae) and Polyphylla sikkimensis Brenske (Coleoptera: Scarabaeidae) by monitoring seven sites using UV traps and damage caused by them in 2017 and 2018. Melolontha furcicauda (Ancey) (Coleoptera: Scarabaeidae) was the most dominant species, followed by Melolontha Cuprescens Blanchard (Coleoptera: Scarabaeidae) and Melolontha indica Hope (Coleoptera: Scarabaeidae) and P. sikkimensis. The activity of species peaked in July. The highest Shannon (1.35–1.36), Simpson (0.73–0.74) and Pielou’s evenness indices (0.97–0.98) were recorded at Badagaon in both years. Scarab species from Badagaon and Janjehli were similar in species richness and abundance while Palampur and Sangla were most dissimilar. Melolontha indica and M. furcicauda preferred rose the most and M. cuprescens preferred apple. Maximum damage rate of potato (42.5–47.5%), cabbage (26.2–28.8%) and kidney beans (18.7–20.0%) by P. sikkimensis was recorded at Badagaon.

Tyrobp deficiency blocks NLRP3-mediated inflammation and pyroptosis to alleviate myocardial ischemia-reperfusion injury through regulating Syk

PurposeThe present study aims to investigate the biological function of Tyrobp in myocardial ischemia-reperfusion injury (MIRI) and to clarify its potential reaction mechanisms. MethodsAC16 cells were induced by oxygen-glucose deprivation/reoxygenation (OGD/R) to simulate the MIRI in vitro. The cell transfection technology was used to downregulate Tyrobp, followed by assessment of cell damage, apoptosis and cytokines production via Cell Counting Kit (CCK)-8 assay, lactate dehydrogenase (LDH) release assay, TUNEL and ELISA assays, respectively. Immunofluorescence assay was performed to assess GSDMD. Corresponding proteins were detected via western blotting, and Co-immunoprecipitation (Co-IP) assay was used to validate proteins interaction. ResultsTyrobp was upregulated in OGD/R-exposed AC16 cells, and Tyrobp deficiency significantly alleviated OGD/R-caused cell viability loss, LDH release and cell apoptosis in AC16 cells. Meanwhile, Tyrobp deficiency inhibited the activation of NLRP3 inflammasome, reduced the production of cytokines and inhibited GSDMD intensity and GSDMD-N expression. Additionally, Tyrobp could interact with Syk and regulate Syk/NF-κB signaling. The rescue experiments showed that the above effects of Tyrobp deficiency on OGD/R-exposed AC16 cells were partly weakened by Syk overexpression. ConclusionTyrobp deficiency alleviated MIRI by inhibiting NLRP3-mediated inflammation and pyroptosis through regulating Syk, providing a novel target for the treatment of MIRI.