Search Results (216)

Establishing a sustainable framework for remediating environmental degradation caused by historical mining operations in the Sierra Minera of Cartagena-La Unión, southeastern Spain, is a critical imperative. When the reclamation requirements of the post-mining district are considered in the context of its critical location, nested among conflicting land uses, the development of practical solutions to restore ecological and cultural functions emerge as a landscape planning challenge. The greenway approach emphasizes the primary ecological and functional corridors that sustain the vitality of the region; therefore, it is essential to preserve and enhance these critical lifelines. This study aimed to design a localized greenway network to support the conservation of key ecological, agricultural, and cultural resources within the area, while simultaneously promoting reclamation activities in degraded zones. The greenway corridor is built upon key elements: conservation areas, post-mining cultural resources, dry riverbeds, and agricultural zones. In the light of greenway approach, planners and land managers can make their decisions more judiciously by considering the priority zones. The protection, leveraging, and reclamation of significant resources can be provided through a multifunctional greenway approach as seen in the case of Cartagena-La Unión Post-Mining District. Full article

Structural health monitoring (SHM) is vital for ensuring structural integrity by continuously evaluating conditions through sensor data. However, sensor anomalies caused by external disturbances can severely compromise the effectiveness of SHM systems. Traditional anomaly detection methods face significant challenges due to reliance on large labeled datasets, difficulties in handling long-term dependencies, and issues stemming from class imbalance. To address these limitations, this study introduces a hierarchical attention Transformer (HAT)-based method specifically designed for sensor anomaly detection in SHM applications. HAT leverages hierarchical temporal modeling with local and global Transformer encoders to effectively capture complex, multi-scale anomaly patterns. Evaluated on a real-world dataset from a large cable-stayed bridge, HAT achieves superior accuracy (96.3%) and robustness even with limited labeled data (20%), significantly outperforming traditional models like CNN, LSTM, and RNN. Additionally, this study visualizes the convergence process of the model, demonstrating its fast convergence and strong generalization capabilities. Thus, the proposed HAT method provides a practical and effective solution for anomaly detection in complex SHM scenarios. Full article

This research aimed to evaluate the impact of using brick waste powder (BWP) and varying lengths of polyester fibers (PFs) on the performance properties of asphalt concrete (AC) mixtures. BWP was utilized as a replacement for traditional limestone powder (LS) filler, while PFs of three lengths (3 mm, 8 mm, and 15 mm) were introduced. The study employed the response surface methodology (RSM) for experimental design and analysis of variance (ANOVA) to identify the influence of BWP and PF on the selected performance indicators. These indicators included bulk density, air voids, voids in the mineral aggregate, voids filled with asphalt, Marshall stability, Marshall flow, Marshall quotient, indirect tensile strength, wet tensile strength, and the tensile strength ratio. The findings demonstrated that BWP improved moisture resistance and the mechanical performance of AC mixes. Moreover, incorporating PF alongside BWP further enhanced these properties, resulting in superior overall performance. Using multi-objective optimization through RSM-based empirical models, the study identified the optimal PF length of 5 mm in combination with BWP for achieving the best AC properties. Validation experiments confirmed the accuracy of the predicted results, with an error margin of less than 8%. The study emphasizes the intriguing prospect of BWP and PF as sustainable alternatives for improving the durability, mechanical characteristics, and cost-efficiency of asphalt pavements. Full article

The urban drainage system is a significant lifeline for ensuring the safe operation of a city. In recent years, defects and diseases in drainage pipes and their ancillary facilities have occurred frequently. Aiming to provide decision-makers with comprehensive benefit evaluation support, we chose to evaluate the security, environmental, social, and economic benefits of urban drainage culverts and pipes (UDCPs). An index system of 14 first-level indicators in four dimensions was established, and the indicators contain 28 influencing factors. The index weight was obtained by combining the analytical hierarchy process and entropy weight method, and the weights assigned to the security, environmental, social, and economic benefits were 0.448, 0.222, 0.202, and 0.128, respectively. The evaluation system was developed on the basis of a geographic information system (GIS), and the topological analysis of the GIS was applied in the calculation. To process the questionnaire results, this study adopted the automatic questionnaire analysis and scoring method combining natural language processing and optical character recognition technology. The method was applied in the study area in southern China, which contains 9 catchment areas and 1356 pipes. The results show that about 5% of the pipelines need to be included in the renewal plan. For UDCP renewal, the findings provide a decision-making tool of the comprehensive analysis for the selection of engineering technologies and the evaluation of the implementation effects. Full article

Fanconi anemia (FA) is a DNA repair deficiency disorder associated with genomic and chromosomal instability and a high cancer risk. In a small percentage of cases, FA is caused by biallelic pathogenic variants (PVs) in the BRCA2/FANCD1 gene, defining the FA-D1 subtype. Experimental and epidemiologic data indicate that the complete absence of BRCA2 is incompatible with viability. Therefore, cells from individuals affected with FA caused by biallelic BRCA2 PVs must have a residual BRCA2 function. This activity may be maintained through hypomorphic missense mutations, translation termination–reinitiation associated with a translational stop mutation, or other non-canonical or uncommon translation initiation and elongation events. In some cases, however, residual BRCA2 function is provided by alternatively or aberrantly spliced BRCA2 transcripts. Here, we review and debate aspects of the contribution of splicing in the 5′ segment to BRCA2 functions in the context of PVs affecting this largely intrinsically disordered protein region, with a focus on recent findings in individuals with FA-D1. In this Perspective, we also discuss some of the broader biological implications and open questions that arise from considering 5′-terminal BRCA2 splicing in light of old and new findings from FA-D1 patients and beyond. Full article

In recent decades, the River Ganges in India has been heavily contaminated with domestic waste and industrial toxins because of cultural activities, a lack of community awareness, an absence of sewage disposal facilities, and rapid population growth. Previous studies have focused separately on either the physical or social factors associated with River Ganges pollution but have not combined these elements in a single study. To fill this research gap, our study assesses the bio-physical and social vulnerability of the River Ganges by using a holistic approach. The following four sampling stations were selected: Rishikesh, Haridwar, Kanpur, and Varanasi. These locations were chosen to test the water quality in bio-physical aspects and to assess the social perceptions of river vulnerability among the residents and visitors. Perceptions of river water quality and likely sources of pollution were gathered via the distribution of over 1000 questionnaires. Data collection took place in the winter and summer of 2022 and 2023. The results showed that river water quality is not suitable for drinking purposes at any of the four cities without conventional treatment, and that the river is unsuitable for bathing at all locations, except upstream of Rishikesh. Nearly 50% of those questioned agreed that the river is polluted, whilst 74% agreed that pollution has increased in recent decades, particularly in the last 10 years. These compelling results are critical for policymakers and decision makers. They highlight the urgent need for novel strategies that address Ganges pollution while fostering community health education and environmental management. By dispelling myths surrounding river quality, this study strengthens the ongoing efforts to restore the Ganges, ensuring that it remains a vital lifeline for present and future generations. Full article

Blind Interference Alignment (BIA) and Sparse Code Multiple Access (SCMA) offer the potential for massive connectivity but face limitations. Our recently proposed Sparsecode-and-BIA-based Multiple Access (SBMA) scheme synergizes their strengths, promising enhanced performance. SBMA leverages flexible user grouping (UG) strategies to effectively manage its unique combination of sparse code constraints and interference alignment requirements, thereby facilitating the fulfillment of diverse Quality of Service (QoS) demands. However, realizing SBMA’s full potential requires efficient joint resource allocation (RA), user scheduling (US), and user grouping (UG). The inherent coupling of these factors within the SBMA framework complicates this task significantly, rendering RA/US solutions designed purely for SCMA or BIA insufficient. This paper addresses this critical open issue. We first formulate the joint RA, US, and UG problems specifically for SBMA systems as an integer optimization task, aiming to maximize the number of users meeting QoS requirements. To tackle this NP-hard problem, we propose an effective algorithm based on Particle Swarm Optimization (PSO), featuring a carefully designed update function tailored specifically for the joint US and UG decisions required in SBMA. Comprehensive simulations demonstrate show that the proposed algorithm significantly outperforms the random-based scheme. Under certain conditions, it serves approximately 280% more users who meet their QoS requirements in high-SNR scenarios. Full article

With growing emphasis on sustainable construction, fiber-reinforced polymer (FRP) bars are increasingly being used as alternatives to steel rebars due to their high strength-to-weight ratio, corrosion resistance, and environmental benefits. This study has investigated the bond behavior between FRP bars and concrete of different strength grades under dynamic loading conditions. To analyze the microscopic properties of FRP bar surfaces, the study employs a variety of techniques, including scanning electron microscopy (SEM), atomic force microscopy (AFM), and non-contact surface profilometry. In addition, X-ray photoelectron spectroscopy (XPS), water contact angle (WCA) measurements, and energy dispersive spectrometry (EDS) are used to further investigate surface characteristics. The results reveal a direct correlation between the resin surface roughness of FRP bars and their wettability characteristics, which in turn influence the cement hydration process. Pull-out tests under different loading rates and concrete strength grades have been conducted to evaluate the bond–slip behavior and failure modes. The results indicate that bond strength increases with increasing concrete strength. Dynamic pull-out tests further reveal that higher loading rates generate heterogeneous stress fields, which limit the deformation of FRP bars and consequently diminish the contribution of mechanical interlock to interfacial bonding. Full article

The Ganga River, a lifeline for millions and a critical freshwater ecosystem, is under threat from escalating plastic pollution driven by widespread usage and inadequate disposal practices. While marine ecosystems have garnered extensive research attention, freshwater systems—particularly in the Global South—remain underexplored, leaving critical gaps in understanding plastic pollution’s sources and pathways. Addressing these gaps, the study documents the prevalence and typology of plastic debris in urban and underexplored rural communities along the Ganga River, India, aiming to suggest mechanisms for a reduction in source-based pollution. A stratified random sampling approach was used to select survey sites and plastic debris was quantified and categorised through transect surveys. A total of 37,730 debris items were retrieved, dominated by packaging debris (52.46%), fragments (23.38%), tobacco-related debris (5.03%), and disposables (single-use plastic cutleries) (4.73%) along the surveyed segments with varying abundance trends. Floodplains displayed litter densities nearly 28 times higher than river shorelines (6.95 items/m² vs. 0.25 items/m²), with minor variations between high- and low-population-density areas (7.14 items/m vs. 6.7 items/m²). No significant difference was found between rural and urban areas (V = 41, p = 0.19), with mean densities of 0.87 items/m² and 0.81 items/m², respectively. Seasonal variations were insignificant (V = 13, p = 0.30), but treatment sites displayed significant variance (Chi² = 10.667, p = 0.004) due to flood impacts. The findings underscore the urgent need for tailored waste management strategies integrating industrial reforms, decentralised governance, and community-driven efforts. Enhanced baseline information and coordinated multi-sectoral efforts, including Extended Producer Responsibility (EPR), are crucial for mitigating plastic pollution and protecting freshwater ecosystems, given rivers’ significant contribution to ocean pollution. Full article

Computer vision is increasingly used for fall safety monitoring, but it struggles in subtle hazard scenarios, causing delays in hazard detection. Therefore, this issue was addressed in this study using transfer learning on pre-trained models that were fine-tuned with target datasets to enhance accuracy. We tested two scenarios—“scaffolding transverse brace installation” and “correct safety lifeline hook-up”—with MobileNet v2, GoogleNet, Inception v3, and ResNet-50. GoogleNet achieved an accuracy of 95.2% in brace installation recognition, while MobileNet v2 and Inception v3 achieved an accuracy of 96% for lifeline hook-up recognition, demonstrating excellent capability in complex hazard detection. Full article

In recent years, effective methods for concrete damage identification and localization have become crucial in the field of structural health monitoring (SHM). This study proposes an approach utilizing piezoelectric sensors to detect and localize damage in concrete structures. The method involves using a network of piezoelectric ceramic sensors to actively excite and receive stress waves within the concrete. By analyzing the differences in wave propagation between healthy and damaged states, internal damage can be identified and localized. The collected data are processed using advanced signal processing techniques, including wavelet analysis and pattern recognition algorithms, to accurately identify the damage’s location and severity. Experimental results demonstrate the high precision of this method. Compared to traditional techniques, this approach offers significant advantages, including faster detection, non-destructive testing, and real-time monitoring. In conclusion, the use of piezoelectric sensors for damage detection and localization provides a promising solution for enhancing the safety and longevity of concrete structures, offering a reliable tool for structural health monitoring in civil engineering applications. Full article

This study examines the differences in performance between orbitally shaken bioreactors (OSBs) and stirred tank bioreactors (STBs) in Chinese Hamster Ovary (CHO) cell perfusion culture in response to the growing market demand for monoclonal antibodies (mAbs). Although OSBs demonstrated higher cell densities, a notable reduction in specific antibody production rates was observed during the mid-to-late phases of the culture compared with STBs. To elucidate the underlying mechanisms, the rheological behaviour of high-density cell suspensions in both reactor types was initially characterised, confirming their adherence to the Sisko fluid model. Computational Fluid Dynamics (CFD) analysis revealed the influence of these rheological properties on the shear stress distribution and mass transfer. This analysis identified the key limiting factors for achieving higher cell densities: mass transfer efficiency in OSBs and shear stress in STBs. Using an Euler–Lagrangian cell-tracking methodology to analyse cellular “lifelines”, it was determined that OSBs exhibited approximately twice the number and frequency of shear stress peak occurrences compared to STBs. This persistent mechanical stimulation likely contributes to the reduced specific antibody production rates observed. This comprehensive investigation not only clarifies the comparative advantages and limitations of different bioreactor types in perfusion culture but also provides a robust theoretical basis and technical guidance for informed reactor selection, optimisation, and scale-up in industrial production environments. Full article

Urban infrastructure, the lifeline of modern society, consists of inherently multidimensional and interdependent systems that extend beyond various engineered facilities, utilities, and networks. The increasing frequency of extreme events, like floods, typhoons, power outages, and technical failures, has heightened the vulnerability of these infrastructures to cascading disasters. Over the past decade, significant attention has been devoted to understanding urban infrastructure cascading disasters. However, most of them have been limited by one-sided and one-dimensional analyses. A more systematic and scientific methodology is needed to comprehensively profile existing research on urban infrastructure cascading disasters to address this gap. This paper uses scientometric methods to investigate the state-of-the-art research in this area over the past decade. A total of 165 publications from 2014 to 2023 were retrieved from the Web of Science database for in-depth analysis. It has revealed a shift in research focus from single infrastructures to complex, interconnected systems with multidimensional dependencies. In addition, the study of disaster-causing factors has evolved from internal infrastructure failures to a focus on cascading disasters caused by extreme events, highlighting a trend of multi-factor coupling. Furthermore, predicting and modeling cascading disasters, improving infrastructure resilience, and information sharing for collaborative emergency responses have emerged as key strategies in responding to disasters. Overall, the insights gained from this study enhance our understanding of the evolution and current challenges in urban infrastructure cascading disasters. Additionally, this study offers valuable perspectives and directions for policymakers addressing extreme events in this critical area. Full article

In the engineering domain, the detection of damage in high-strength bolts is critical for ensuring the safe and reliable operation of equipment. Traditional manual inspection methods are not only inefficient but also susceptible to human error. This paper proposes an automated bolt damage identification method leveraging AIGC (Artificial Intelligence Generated Content) technology and object detection algorithms. Specifically, we introduce the application of AIGC in image generation, focusing on the Stable Diffusion model. Given that the quality of bolt images generated directly by the Stable Diffusion model is suboptimal, we employ the LoRA fine-tuning technique to enhance the model, thereby generating a high-quality dataset of bolt images. This dataset is then used to train the YOLO (You Only Look Once) object detection algorithm, demonstrating significant improvements in both accuracy and recall for bolt damage recognition. Experimental results show that the LoRA fine-tuned Stable Diffusion model significantly enhances the performance of the YOLO algorithm, providing an efficient and accurate solution for automated bolt damage detection. Future work will concentrate on further optimizing the model to improve its robustness and real-time performance, thereby better meeting the demands of practical industrial applications. Full article

Background: Basic healthcare may significantly decrease neonatal morbidity and mortality. Attention to this, particularly in populations where rates of potentially preventable illness and death within the first weeks of life are extremely high, will have a positive impact on global health. Objective: This manuscript presents the development and impact of a quality improvement programme to reduce the evidence–practice gap in care for neonates admitted to the NICU in a public hospital in India. The programme was locally customised for optimal and sustainable results. Method: The backbone of the project was educational exchange of neonatal nurses and physicians between Norway and India. Areas of potential improvement in the care for the neonates were mainly identified by the clinicians and focus areas were subject to dynamic changes over time. In addition, a service centre for lactation counselling and milk banking was established. Progress over the timeframe 2017–2019 was compared with baseline data. Results: The project has shown that after a collaborative effort, there is a significant reduction in mortality from 11% in the year 2016 to 5.5% in the year 2019. The morbidity was reduced, as illustrated by the decrease in the proportion of neonates with culture-proven sepsis. Nutrition improved with consumption of human milk by the NICU-admitted neonates remarkably increasing from one third to more than three forth of their total intake, and weight gain in a subgroup was shown to increase. With the introduction of family participatory care, hours of skin-to-skin contact for the neonates significantly increased. Additional indicators of improved care were also observed. Conclusions: It is feasible to reduce neonatal mortality and morbidity in a low- and middle-income hospitalised population by improving basic care including nutrition relatively inexpensively when utilising human resources. Full article