bluuebunny/crossref_metadata_2025 huggingface dataset:
Transfer Learning-Based Classification of Maxillary Sinus Using Generative Adversarial Networks
Authors: Alhumaid Mohammad , Fayoumi Ayman G.
Published: April 2024

Paranasal sinus pathologies, particularly those affecting the maxillary sinuses, pose significant challenges in diagnosis and treatment due to the complex anatomical structures and diverse disease manifestations. The aim of this study is to investigate the use of deep learning techniques, particularly generative adversarial networks (GANs), in combination with convolutional neural networks (CNNs), for the classification of sinus pathologies in medical imaging data. The dataset is composed of images obtained through computed tomography (CT) scans, covering cases classified into “Moderate”, “Severe”, and “Normal” classes. The lightweight GAN is applied to augment a dataset by creating synthetic images, which are then used to train and test the ResNet-50 and ResNeXt-50 models. The model performance is optimized using random search to perform hyperparameter tuning, and the evaluation is conducted extensively for various metrics like accuracy, precision, recall, and the F1-score. The results demonstrate the effectiveness of the proposed approach in accurately classifying sinus pathologies, with the ResNeXt-50 model achieving superior performance with accuracy: 91.154, precision: 0.917, recall: 0.912, and F1-score: 0.913 compared to ResNet-50. This study highlights the potential of GAN-based data augmentation and deep learning techniques in enhancing the diagnosis of maxillary sinus diseases.
Overcoming the Trade-Off between Methanol Rejection and Proton Conductivity via Facile Synthesis of Crosslinked Sulfonated PEEK Proton Exchange Membranes
Authors: Depuydt Stef , Traub Lucy , Van Eygen Gilles , Kumar Santosh , Held Georg , Van der Bruggen Bart
Published: April 2024

In this work, homogeneous, thin-film proton exchange membranes (PEMs) with superior proton conductivities and high methanol rejection were fabricated via a facile synthesis procedure. Sulfonated polyether ether ketone (sPEEK) was crosslinked via a Friedel–Crafts reaction by α,α′-dichloro-p-xylene, a non-hazardous and hydrophobic compound. PEMs with varying crosslinking and sulfonation degrees were fabricated to overcome the traditional trade-off between methanol rejection and proton conductivity. The sulfonation of PEEK at 60 °C for 24 h resulted in a sulfonation degree of 56%. Those highly sulfonated backbones, in combination with a low membrane thickness (ca. 20 µm), resulted in proton conductivities superior to Nafion 117. Furthermore, X-ray photoelectron spectroscopy proved it was possible to control the crosslinking degree via the crosslinking time and temperature. The PEMs with the highest crosslinking degree showed better methanol rejection compared to the commercial benchmark. The introduction of the crosslinker created hydrophobic membrane sections, which reduced the water and methanol uptake. Subsequently, the membrane became denser due to the crosslinking, hindering the solute permeation. Those two effects led to lower methanol crossovers. This study proved the successful fabrication of PEMs overcoming the trade-off between proton conductivity and methanol rejection, following a facile procedure using low-cost and non-hazardous materials.
Comprehensive Performance Evaluation of Earthquake Search and Rescue Robots Based on Improved FAHP and Radar Chart
Authors: Li Liming , Zhao Zeang
Published: April 2024

To effectively enhance the adaptability of earthquake rescue robots in dynamic environments and complex tasks, there is an urgent need for an evaluation method that quantifies their performance and facilitates the selection of rescue robots with optimal overall capabilities. In this paper, twenty-two evaluation criteria are proposed based on a comprehensive review of existing evaluation criteria for rescue robots across various domains. The evaluation criteria are tested using the test modules developed by the National Earthquake Response support service, obtaining the corresponding values for each criterion. Then, the weights of the criterion layer and comprehensive evaluation index are determined based on the analytical hierarch process and trapezoidal fuzzy number complementary judgment matrix, and a new consistency test method is proposed. The qualitative evaluation and quantitative analysis are effectively combined to overcome the subjective influence of expert decision-making. Additionally, the performance of three earthquake search and rescue robots is comprehensively evaluated and ranked using the improved radar chart method as an empirical example. Finally, the robustness of the ranking results is examined using a weight sensitivity analysis. The results of the sensitivity analysis demonstrate the effectiveness and feasibility of the proposed method, thereby providing valuable insights for developing multi-objective optimization control strategies and structural designs for earthquake search and rescue robots.
Enhancing Insect Sound Classification Using Dual-Tower Network: A Fusion of Temporal and Spectral Feature Perception
Authors: He Hangfei , Chen Junyang , Chen Hongkun , Zeng Borui , Huang Yutong , Zhaopeng Yudan , Chen Xiaoyan
Published: April 2024

In the modern field of biological pest control, especially in the realm of insect population monitoring, deep learning methods have made further advancements. However, due to the small size and elusive nature of insects, visual detection is often impractical. In this context, the recognition of insect sound features becomes crucial. In our study, we introduce a classification module called the “dual-frequency and spectral fusion module (DFSM)”, which enhances the performance of transfer learning models in audio classification tasks. Our approach combines the efficiency of EfficientNet with the hierarchical design of the Dual Towers, drawing inspiration from the way the insect neural system processes sound signals. This enables our model to effectively capture spectral features in insect sounds and form multiscale perceptions through inter-tower skip connections. Through detailed qualitative and quantitative evaluations, as well as comparisons with leading traditional insect sound recognition methods, we demonstrate the advantages of our approach in the field of insect sound classification. Our method achieves an accuracy of 80.26% on InsectSet32, surpassing existing state-of-the-art models by 3 percentage points. Additionally, we conducted generalization experiments using three classic audio datasets. The results indicate that DFSM exhibits strong robustness and wide applicability, with minimal performance variations even when handling different input features.
Digital Twin-Driven Multi-Factor Production Capacity Prediction for Discrete Manufacturing Workshop
Authors: Cai Hu , Wan Jiafu , Chen Baotong
Published: April 2024

Traditional capacity forecasting algorithms lack effective data interaction, leading to a disconnection between the actual plan and production. This paper discusses the multi-factor model based on a discrete manufacturing workshop and proposes a digital twin-driven discrete manufacturing workshop capacity prediction method. Firstly, this paper gives a system framework for production capacity prediction in discrete manufacturing workshops based on digital twins. Then, a mathematical model is described for discrete manufacturing workshop production capacity under multiple disturbance factors. Furthermore, an innovative production capacity prediction method, using the “digital twin + Long-Short-Term Memory Network (LSTM) algorithm”, is presented. Finally, a discrete manufacturing workshop twin platform is deployed using a commemorative disk custom production line as the prototype platform. The verification shows that the proposed method can achieve a prediction accuracy rate of 91.8% for production line capacity. By integrating the optimization feedback function of the digital twin system into the production process control, this paper enables an accurate perception of the current state and future changes in the production system, effectively evaluating the production capacity and delivery date of discrete manufacturing workshops.
High-Temperature Oxidation of the 304/6061 Welding–Brazing Joint and Its Effects on Corrosion Characteristics
Authors: Liu Ruilin , Liu Yunqi , Liu Hongming , Li Yuanxing , Chen Hui , Zhu Zongtao
Published: April 2024

Laser–MIG hybrid welding–brazing was used to weld 304 stainless steel and 6061-T6 aluminum alloy with a thickness of 2 mm. The microstructure, morphology, chemical composition and corrosion behavior of the samples after high-temperature oxidation were investigated. The results reveal that the 304/6061 dissimilar joint had a thicker intermetallic compound layer (7–8 μm) during high-temperature oxidation (HTO) treatment than the sample without HTO treatment (2–3 μm). The oxide film thickness of the 6061 side of the weld joint treated by HTO (2401 nm) increased compared to the samples (181.1 nm) without HTO treatment. Unlike other metals treated by high-temperature oxidation, the high-temperature treatment process in this paper can reduce the corrosion resistance of the base metal and dissimilar joints, and the sequence of the corrosion current density was weld (HTO) >weld>6061 (HTO) >6061>304 (HTO) >304.
High-Functioning Autism and Virtual Reality Applications: A Scoping Review
Authors: Chiappini Mattia , Dei Carla , Micheletti Ettore , Biffi Emilia , Storm Fabio Alexander
Published: April 2024

In recent years, the number of applications of virtual reality (VR) for the Autism spectrum disorder (ASD) population has increased and has become one of the most suitable tools to address the psychological needs of these individuals. The present scoping review aims to provide a literature mapping of experimental studies that have used immersive and semi-immersive VR for assessments or interventions specifically addressing high-functioning autism. A total of 23 papers were included and analyzed following PRISMA guidelines. The identified studies concerned social skills (11 papers), eye gaze and joint attention (3 papers), motor learning (3 papers), job training (2 papers), and other aims or rationales (4 papers). The evidence shows that, despite the intellectual potential of high-functioning ASD individuals, little research has been conducted to provide interventions that offer concrete training to improve their adaptive functioning. In addition, the percentage of individuals below 18 years of age is representative of half of the included studies, so aiming future studies at the early stages of development might be an asset in preparing the next generation of young adults to cope with age-related challenges, as early assessments and interventions are more likely to produce major long-term effects.
The Power of Convening: Towards an Understanding of Artist-Led Collective Practice as a Convener of Place
Authors: Wright John David
Published: April 2024

In recent years, there has been a growing interest in artist-led collectives with high-profile recognition within contemporary art mega festivals, prizes, and biennials. Yet, these amorphous entities and initiatives tend to be framed either through their politically motivated actions or as a critique of the notion of the single author or ‘artist-as-genius’ mythology. This article builds upon this discourse to shift the emphasis onto both interpersonal and socio-political relationships that constitute artist-led collectives in order to explore their complex role in convening and placemaking and what this might mean for both policymaking and research.
Predicting Summer Precipitation Anomalies in the Yunnan–Guizhou Plateau Using Spring Sea-Surface Temperature Anomalies
Authors: Tuo Ya , Qiao Panjie , Liu Wenqi , Li Qingquan
Published: April 2024

By constructing a correlation network between global sea surface temperature anomalies (SSTAs) and summer precipitation anomalies in the Yunnan–Guizhou Plateau, key SST regions influencing summer precipitation anomalies in the Yunnan–Guizhou Plateau were selected. It was found that spring SSTAs in the Bay of Bengal, southwestern Atlantic, and eastern Pacific are crucial for influencing summer precipitation anomalies in the Yunnan–Guizhou Plateau. Setting SSTAs from these three regions as predictor variables 3 months in advance, we constructed multiple linear regression (MLR), ridge regression (RR), and lasso regression (LR) models to predict summer precipitation anomalies over the Yunnan–Guizhou region. The training phase involved data spanning from 1961 to 2005, which aimed to predict precipitation anomalies in the Yunnan–Guizhou Plateau for the period extending from 2006 to 2022. Based on MLR, RR, and LR models, the correlations between predicted values and observed summer precipitation anomalies in Yunnan–Guizhou were 0.48, 0.46, and 0.46, respectively. These values were all higher than the correlation coefficients of the NCC_CSM model’s predicted and observed values. Additionally, its performance in predicting summer precipitation anomalies over the Yunnan–Guizhou region, based on key SST regions, was assessed using performance metrics such as anomaly correlation coefficient (ACC), anomaly sign consistency rate (PC), and trend anomaly comprehensive score (PS score). The average ACC of MLR, RR, and LR models was higher than that of the NCC_CSM model’s predictions. For MLR, RR, LR, and NCC_CSM models, the PCs exceeding 50% of the year were 14, 14, 11, and 10, respectively. Furthermore, the average PS score for predicting summer precipitation anomalies over the Yunnan–Guizhou region using MLR, RR, and LR was approximately 73 points; 8 higher than the average PS score of the NCC_CSM model. Therefore, predicting summer precipitation anomalies over the Yunnan–Guizhou region based on key SST regions is of great significance for improving the prediction skills of precipitation anomalies in this region.
Socioeconomic Impacts of Climate Mitigation Actions in Greece: Quantitative Assessment and Public Perception
Authors: Sarafidis Yannis , Demertzis Nicolas , Georgopoulou Elena , Avrami Lydia , Mirasgedis Sevastianos , Kaminiaris Othon
Published: April 2024

Appropriately designed and implemented climate mitigation actions have multiple co-benefits (yet some trade-offs cannot be excluded) that result in substantial social and economic value beyond their direct impact on reducing energy consumption and GHG emissions. Despite their wider acknowledgement by the research community, decision makers and the public have incomplete information on these multiple effects. This paper has a twofold objective: First, through analytical bottom-up approaches, it assesses, in quantitative terms, the macroeconomic effects and the public health benefits attributed to a variety of mitigation actions under consideration in the context of the Greek Energy and Climate Plan. Second, it investigates, through a social survey, how citizens perceive climate change and value these multiple impacts of mitigation actions, and to what extent they are willing to pay for them and support the adoption of policy measures aiming at the green transition of the Greek economy. We show that mitigation actions bring about significant health benefits, particularly in cities, and generate significant positive macroeconomic effects, particularly if mitigation actions focus on the decarbonization of the building sector and on the exploitation of local renewable sources. We also argue that most people do not realize that climate mitigation actions can have wider benefits for society, such as tackling energy poverty, improving public health, and creating new jobs. Unwillingness to pay tends to be the prominent attitude. People who are more reluctant to cover a part of the cost of environmental protection are less likely to perceive that climate change is one of the main challenges at global and national level and support the adoption of climate mitigation policies. In this context, the national strategy for climate change should focus on effectively informing and engaging the public in climate mitigation strategies, strengthening the public trust in government institutions, promoting mutually acceptable solutions with the local communities, and providing incentives for changing citizens’ behavior towards climate-related actions.
Evolving Narratives in Tourism and Climate Change Research: Trends, Gaps, and Future Directions
Authors: Dube Kaitano
Published: April 2024

This study presents a comprehensive overview of the evolving landscape of tourism and climate change research over the past decade by leveraging bibliometric analysis and a dataset sourced from the Scopus Database. The study scrutinised over 3400 English language articles. The analysis reveals a remarkable surge in publications, signifying the growing recognition of climate change’s multifaceted impact on tourism. However, a noteworthy geographical disparity emerges, with many regions remaining underrepresented in the literature, particularly in Africa and the Middle East. This oversight is concerning, given the vulnerability of these regions to climate change and their burgeoning tourism industries. The study also highlights the pivotal role of influential scholars, funding organisations, and publication outlets in shaping the research landscape. The European Commission and the National Natural Science Foundation of China are major funders. At the same time, journals like Sustainability and the Journal of Sustainable Tourism serve as prominent platforms for disseminating research findings. The analysis uncovers thematic trends, including the growing focus on climate change modelling and its implications for destination planning. However, research gaps persist, notably in sports tourism and climate resilience within the tourism sector. In conclusion, this study offers valuable insights into the current state of tourism and climate change research, pinpointing areas that demand increased attention and inclusivity. It is a valuable resource for scholars, policymakers, and stakeholders working towards a sustainable and resilient future for the global tourism industry in the face of climate change.
Simulation of the Jet Fire Using Atmospheric Dispersion Modeling (ALOHA): A Case Study of Natural Gas Pipeline in Istanbul, Türkiye
Authors: Besiktas Remzi , Baltaci Hakki , Akkoyunlu Bulent Oktay
Published: April 2024

Natural gas is known as a widely used energy source in residential, business and industrial areas. During the transportation of natural gas by pipelines, accidents occur due to various reasons, which can also lead to gas output. These accidents are events that have the potential to pose important risks in terms of life and property safety, particularly in urban areas and surrounding of pipeline routings. In this study, accident scenarios were generated based on a natural gas distribution pipeline fire that occurred in Istanbul (NW Türkiye) on 28 April 2020 and the impact areas of the jet fire were calculated using the ALOHA program. The effects of source release factors (i.e., pipe length and diameter) and atmospheric conditions (i.e., wind speed, cloud cover, air temperature and relative humidity) on the thermal radiation threat distances associated with jet fire were calculated for the current and worst scenarios. As a result, it was found that pipe length and diameter have a significant effect on threat distances. In addition to the role of the synoptic circulation mechanism on the jet fire for the selected episodic event (position of low/high pressure centers), local atmospheric conditions also have an effect on the threat distance. From the modeling analysis, significant impact of wind speed, air temperature and relative humidity values on the threat distances were found. In the worst scenario, if there were strong northeasterly winds reaching 30.9 m per hour at the time of the jet fire, the threat distances would have been 21 m (red), 28 m (orange) and 42 m (yellow). This case shows that if a natural gas jet fire occurs under the influence of strong northeasterly winds (passing over the Black Sea without encountering any topographic obstacles), poisonous gas will be transported to long distances in a short time and will negatively affect social life and economy.
An Improved Deep Learning Approach Considering Spatiotemporal Heterogeneity for PM2.5 Prediction: A Case Study of Xinjiang, China
Authors: Wu Yajing , Xu Zhangyan , Xu Liping , Wei Jianxin
Published: April 2024

Prediction of fine particulate matter with particle size less than 2.5 µm (PM2.5) is an important component of atmospheric pollution warning and control management. In this study, we propose a deep learning model, namely, a spatiotemporal weighted neural network (STWNN), to address the challenge of poor long-term PM2.5 prediction in areas with sparse and uneven stations. The model, which is based on convolutional neural network–bidirectional long short-term memory (CNN–Bi-LSTM) and attention mechanisms and uses a geospatial data-driven approach, considers the spatiotemporal heterogeneity effec It is correct.ts of PM2.5. This approach effectively overcomes instability caused by sparse station data in forecasting daily average PM2.5 concentrations over the next week. The effectiveness of the STWNN model was evaluated using the Xinjiang Uygur Autonomous Region as the study area. Experimental results demonstrate that the STWNN exhibits higher performance (RMSE = 10.29, MAE = 6.4, R2 = 0.96, and IA = 0.81) than other models in overall prediction and seasonal clustering. Furthermore, the SHapley Additive exPlanations (SHAP) method was introduced to calculate the contribution and spatiotemporal variation of feature variables after the STWNN prediction model. The SHAP results indicate that the STWNN has significant potential in improving the performance of long-term PM2.5 prediction at the regional station level. Analyzing spatiotemporal differences in key feature variables that influence PM2.5 provides a scientific foundation for long-term pollution control and supports emergency response planning for heavy pollution events.
An Investigation of a Biomimetic Optical System and an Evaluation Model for the Qualitative Analysis of Laser Interference Visual Levels
Authors: Niu Jin , Xu Xiping , Pan Yue , Duan Zhenhao
Published: April 2024

To objectively quantify the level of visual interference induced by lasers, we developed a biomimetic optical system designed to emulate human vision. This system is based on an optical model of the eye and synthetic imaging principles, allowing it to generate biomimetic optical images that closely mimic human visual perception. Upon exposure to a 532 nm laser, biomimetic optical images were captured under various ambient lighting conditions. By employing a contrast threshold model for human visual target detection and grayscale hierarchy analysis, we devised an evaluation model to quantify the levels of laser-induced visual interference. The bionic images obtained from our experiments, in conjunction with the constructed model, enabled us to assess the degree of laser-induced visual interference. Our results indicate that this system can effectively substitute the human eye when testing laser imaging effects, with the generated bionic images achieving up to 90% concordance with human vision. The proposed evaluation model facilitates the quantitative analysis of laser-induced visual impairment. This apparatus and evaluation model hold significant promise for the precise quantification of laser-induced visual interference levels.
Characterization of PDGF-Induced Subcellular Calcium Regulation through Calcium Channels in Airway Smooth Muscle Cells by FRET Biosensors
Authors: Ouyang Mingxing , Zhou Binqian , Li Chunmei , Deng Linhong
Published: April 2024

The homeostasis of cellular calcium is fundamental for many physiological processes, while the calcium levels remain inhomogeneous within cells. During the onset of asthma, epithelial and inflammatory cells secrete platelet-derived growth factor (PDGF), inducing the proliferation and migration of airway smooth muscle (ASM) to the epidermal layer, narrowing the airway. The regulation of ASM cells by PDGF is closely related to the conduction of calcium signals. In this work, we generated subcellular-targeted FRET biosensors to investigate calcium regulation in the different compartments of ASM cells. A PDGF-induced cytoplasmic calcium [Ca2+]C increase was attributed to both extracellular calcium influx and endoplasmic reticulum (ER) calcium [Ca2+]ER release, which was partially regulated by the PLC-IP3R pathway. Interestingly, the removal of the extracellular calcium influx led to inhibited ER calcium release, likely through inhibitory effects on the calcium-dependent activation of the ER ryanodine receptor. The inhibition of the L-type calcium channel on the plasma membrane or the SERCA pump on the ER resulted in both reduced [Ca2+]C and [Ca2+]ER from PDGF stimulation, while IP3R channel inhibition led to reduced [Ca2+]C only. The inhibited SERCA pump caused an immediate [Ca2+]C increase and [Ca2+]ER decrease, indicating active calcium exchange between the cytosol and ER storage in resting cells. PDGF-induced calcium at the outer mitochondrial membrane sub-region showed a similar regulatory response to cytosolic calcium, not influenced by the inhibition of the mitochondrial calcium uniporter channel. Therefore, our work identifies calcium flow pathways among the extracellular medium, cell cytosol, and ER via regulatory calcium channels. Specifically, extracellular calcium flow has an essential function in fully activating ER calcium release.
Electrogenerated Chemiluminescence Biosensor for Quantization of Matrix Metalloproteinase-3 in Serum via Target-Induced Cleavage of Oligopeptide
Authors: Qian Manping , Zeng Yu , Li Meng , Gao Qiang , Zhang Chengxiao , Qi Honglan
Published: April 2024

A highly sensitive and selective electrogenerated chemiluminescence (ECL) biosensor was developed for the determination of matrix metalloproteinase 3 (MMP-3) in serum via the target-induced cleavage of an oligopeptide. One ECL probe (named as Ir-peptide) was synthesized by covalently linking a new cyclometalated iridium(III) complex ([(3-pba)2Ir(bpy-COOH)](PF6)) (3-pba = 3-(2-pyridyl) benzaldehyde, bpy-COOH = 4′-methyl-2,2′-bipyridine-4-carboxylic acid) with an oligopeptide (CGVPLSLTMGKGGK). An ECL biosensor was fabricated by firstly casting Nafion and gold nanoparticles (AuNPs) on a glassy carbon electrode and then self-assembling both of the ECL probes, 6-mercapto-1-hexanol and zwitterionic peptide, on the electrode surface, from which the AuNPs could be used to amplify the ECL signal and Ir-peptide could serve as an ECL probe to detect the MMP-3. Thanks to the MMP-3-induced cleavage of the oligopeptide contributing to the decrease in ECL intensity and the amplification of the ECL signal using AuNPs, the ECL biosensor could selectively and sensitively quantify MMP-3 in the concentration range of 10–150 ng·mL−1 and with both a limit of quantification (26.7 ng·mL−1) and a limit of detection (8.0 ng·mL−1) via one-step recognition. In addition, the developed ECL biosensor showed good performance in the quantization of MMP-3 in serum samples, with a recovery of 92.6% ± 2.8%–105.6% ± 5.0%. An increased level of MMP-3 was found in the serum of rheumatoid arthritis patients compared with that of healthy people. This work provides a sensitive and selective biosensing method for the detection of MMP-3 in human serum, which is promising in the identification of patients with rheumatoid arthritis.
A Constitutive Model for Stud Connection in Composite Structures
Authors: Qin Xi , Zhao Wei
Published: April 2024

The complexity of finite element analysis for composite structures can be significantly reduced by representing the connector and adjacent concrete as a macroscopic element. Nevertheless, the prevailing macroscopic models for shear connections predominantly employ nonlinear elastic theory. This approach introduces inaccuracies in estimating structural stiffness and load-bearing capabilities, primarily due to its inability to precisely capture the cumulative effects of plastic damage. In response, this study introduces a novel macroscopic elastoplastic model grounded in plasticity theory, aimed at accurately characterizing the nonlinear behavior of stud connections subjected to concurrent shear and tensile forces. This paper meticulously delineates the implementation of the elastoplastic constitutive model using the backward Euler method for numerical integration. It further articulates the derivation of the consistent tangent stiffness, which aligns with the convergence efficiency of the Newton–Raphson iterative approach. The computation of the element stiffness matrix for a two-node element is executed via the governing equation inherent to the finite element method. An exemplar macroelement test conducted in ABAQUS affirms the implicit backward Euler scheme’s stability and consistency across varying tolerances. Validation of the elastoplastic model against empirical test outcomes corroborates its efficacy, demonstrating the model’s precision in predicting the load–displacement behavior of stud connections under the influence of shear and tensile forces.
Barriers to Adopting Advanced Work Packaging (AWP) in Construction
Authors: Rebai Slim , Sepúlveda Italo , AlBalkhy Wassim , Hamdi Olfa , Lafhaj Zoubeir , Alarcón Luis F. , Yim Pascal
Published: April 2024

This study presents a systematic literature review (SLR) of the Advanced Work Packaging (AWP) methodology, focusing on identifying barriers to its adoption. The review encompasses an analysis of 287 documents from 2013 to 2023, including conference articles, doctoral theses, journal articles, master theses, reports, and organizational documents. Following a rigorous selection process, 59 of these documents were identified as pertinent to the investigation. This research employs a dual approach. First, a scientometric analysis to map the collaborative networks of authors and the co-occurrence of keywords, providing a comprehensive picture of the research landscape in AWP. Second, the study delves into the main barriers hindering the adoption of AWP, as revealed through the SLR of the selected documents. The findings offer an overlay network visualization of coauthorship and a network visualization of keyword co-occurrence. The study culminates in a detailed identification of primary AWP barriers, suggestions for future research directions, and potential lines of inquiry within the field. This work contributes to the existing body of knowledge by offering a novel perspective on the challenges associated with AWP implementation and provides a foundation for future scholarly endeavors in this domain.
Simplified Model Study of Autoclaved Aerated Concrete Masonry Flexible Connection Infilled Frames with Basalt Fiber Grating Strips
Authors: Wang Xin , Xiong Lihong , Wang Zhuoxin
Published: April 2024

Infilled walls and frames typically employ closely spaced rigid connection, which, under seismic actions, can lead to adverse effects such as amplified seismic responses, overall torsion, and the formation of weak layers in the structure. Flexible connection isolating the infilled walls from the frames can effectively mitigate the adverse effects of rigid connections. In order to reduce the structural mass and seismic impacts, Autoclaved Aerated Concrete (AAC) masonry flexible connection infilled walls have been widely researched. However, most AAC masonry flexible connection infilled walls require complex process operations for AAC blocks, which is not conducive to practical applications in engineering. Therefore, an AAC flexible connection infilled wall with Basalt Fiber Grating (BFG) strips instead of steel bars, with simplified process operations, has been proposed. Existing finite element models for BFG strip-reinforced AAC masonry flexible connection infilled walls employ solid elements, which are difficult to apply to large-scale structural simulations; moreover, existing simplified models for flexible connection infilled walls cannot simulate out-of-plane loading. In this paper, based on homogenization methods, using simplified elements to simulate components, a simplified model for the BFG strip-reinforced AAC masonry flexible connection infilled frame is proposed. Utilizing this model, stress analyses under both in-plane and out-of-plane loading are conducted and compared with corresponding experimental results. The results indicate that the in-plane simplified model (ISM) fits well with the experimental results in terms of hysteresis curves, with similar relationships between stiffness degradation and strength attenuation. The displacement force curve of the out-of-plane simplified model (OSM) before reaching the peak load is in good agreement with the experimental results. The maximum plastic range of OSM is 5% smaller than the test results, and it can be considered that the plastic ranges of the two are comparable, manifesting the models’ capability to adequately manifest arching behavior. The simplified model enables simulation of out-of-plane loading and provides a new approach for modeling large-scale frame structures with flexible connection infilled wall.
Optimizing the Shading Device Configuration of Kinetic Façades through Daylighting Performance Assessment
Authors: Kim Dong-Hyun , Luong Hieu Trung , Nguyen Trang Thao
Published: April 2024

When designing a façade, it is essential to consider the impact of daylight and how it can be optimized through external movable shading devices. To accurately evaluate the lighting performance of a kinetic facade, it is crucial to consider the operation of these shading devices, as they can significantly impact performance. This study proposes a high-precision methodology that utilizes digital tools and hourly data to examine the effectiveness of dynamic shading device systems in enhancing daylight performance and optimizing shading configurations using the Genetic Optimization algorithm. The study’s results demonstrate that the proposed methodology is accurate and effective, showing that the optimal operation scenario can exceed LEED v4.1 requirements while meeting daylight availability standards. Designers can achieve optimal performance by adjusting each parameter for a lighting energy-conserving kinetic façade. The limitations and applicability of this method are also discussed.
Energy and Economic Advantages of Using Solar Stills for Renewable Energy-Based Multi-Generation of Power and Hydrogen for Residential Buildings
Authors: Bahrami Armida , Soltanifar Fatemeh , Fallahi Pourya , Meschi Sara S. , Sohani Ali
Published: April 2024

The multi-generation systems with simultaneous production of power by renewable energy, in addition to polymer electrolyte membrane electrolyzer and fuel cell (PEMFC-PEMEC) energy storage, have become more and more popular over the past few years. The fresh water provision for PEMECs in such systems is taken into account as one of the main challenges for them, where conventional desalination technologies such as reverse osmosis (RO) and mechanical vapor compression (MVC) impose high electricity consumption and costs. Taking this point into consideration, as a novelty, solar still (ST) desalination is applied as an alternative to RO and MVC for better techno-economic justifiability. The comparison, made for a residential building complex in Hawaii in the US as the case study demonstrated much higher technical and economic benefits when using ST compared with both MVC and RO. The photovoltaic (PV) installed capacity decreased by 11.6 and 7.3 kW compared with MVC and RO, while the size of the electrolyzer declined by 9.44 and 6.13%, and the hydrogen storage tank became 522.1 and 319.3 m3 smaller, respectively. Thanks to the considerable drop in the purchase price of components, the payback period (PBP) dropped by 3.109 years compared with MVC and 2.801 years compared with RO, which is significant. Moreover, the conducted parametric study implied the high technical and economic viability of the system with ST for a wide range of building loads, including high values.
Digital Twin Model and Its Establishment Method for Steel Structure Construction Processes
Authors: Liu Zhansheng , Lin Sen
Published: April 2024

At present, the informatization level in the construction process of steel structures is relatively low. Meanwhile, digital twin technology, with better interactive features, provides a new development direction for the intelligent construction of steel structures. Therefore, this paper introduces the concept of a digital twin into the steel structure construction process, analyzes the connotation and characteristics of the digital twin model, and proposes the digital twin model architecture for steel structure construction processes. Furthermore, a method for establishing a digital twin model for steel structure construction processes is presented, which includes three stages: the acquisition and transmission of physical space data, the construction of a digital twin virtual model, and information exchange in the digital twin model. Based on these concepts, this paper describes a digital twin system architecture for the steel structure construction process from the perspective of data flow in the digital twin model. Finally, with the application of information technology in the steel structure construction process of the university park library project in Xiongan New Area and the reconstruction and expansion project of the Nanchong Gaoping airport, the digital twin model and its establishment method methods are analyzed practically and demonstrated effectively in this study.
Mechanical Properties and Hydration Mechanism of Iron Tailings–Cement-Based Supplementary Cementitious Materials
Authors: Hu Ziyang , Gu Xiaowei , Liu Jianping , Ge Xiaowei , Wang Shenyu , Yin Shiqi
Published: April 2024

The preparation of cement-based supplementary cementitious materials is an important method for the efficient use of iron tailings and the reduction in CO2 emissions. The aim of this study is to improve the reactivity of iron tailings by mixing them with steel slag, slag, and fly ash through orthogonal tests to solve the problem that iron tailings cannot be utilised on a large scale. The compressive strength, hydration products, and microstructure of the iron tailings–cement-based supplementary cementitious materials were investigated using ICP-OES, XRD, TG, FTIR, and SEM. The results revealed that each solid waste raw material played a distinct role in the hydration reaction. In the iron tailings–cement-based supplementary cementitious materials system, steel slag provided Ca2+, OH−, and Si4+ ions, slag provided Ca2+ and Al3+ ions, fly ash contributed a significant amount of Ca2+ and Al3+ ions, and iron tailings offered more nucleation sites and some Si4+ ions for the hydration products. Moreover, there was a synergistic effect among these four materials, promoting the formation of hydration products such as ettringite, C-(A)-S-H gels, and others. When the proportion of IOTs:SS:FA:SL was 9:8:8:2, the highest 7 d compressive strength of cementitious material was 24.8 MPa. When the proportion of IOTs:SS:FA:SL was 9:6:8:4, the highest 28 d compressive strength of cementitious material was 35.0 MPa. This study provides a comprehensive solution for the utilisation of iron tailings and contributes to the high-value green utilisation of solid waste.
The Influence of Myeloid-Derived Suppressor Cell Expansion in Neuroinflammation and Neurodegenerative Diseases
Authors: Tamberi Lorenza , Belloni Alessia , Pugnaloni Armanda , Rippo Maria Rita , Olivieri Fabiola , Procopio Antonio Domenico , Bronte Giuseppe
Published: April 2024

The neuro-immune axis has a crucial function both during physiological and pathological conditions. Among the immune cells, myeloid-derived suppressor cells (MDSCs) exert a pivotal role in regulating the immune response in many pathological conditions, influencing neuroinflammation and neurodegenerative disease progression. In chronic neuroinflammation, MDSCs could lead to exacerbation of the inflammatory state and eventually participate in the impairment of cognitive functions. To have a complete overview of the role of MDSCs in neurodegenerative diseases, research on PubMed for articles using a combination of terms made with Boolean operators was performed. According to the search strategy, 80 papers were retrieved. Among these, 44 papers met the eligibility criteria. The two subtypes of MDSCs, monocytic and polymorphonuclear MDSCs, behave differently in these diseases. The initial MDSC proliferation is fundamental for attenuating inflammation in Alzheimer’s disease (AD), Parkinson’s disease (PD), and multiple sclerosis (MS), but not in amyotrophic lateral sclerosis (ALS), where MDSC expansion leads to exacerbation of the disease. Moreover, the accumulation of MDSC subtypes in distinct organs changes during the disease. The proliferation of MDSC subtypes occurs at different disease stages and can influence the progression of each neurodegenerative disorder differently.
Sex Dependent Disparities in the Central Innate Immune Response after Moderate Spinal Cord Contusion in Rat
Authors: Ghosh Mousumi , Lee Jinyoung , Burke Ashley N. , Strong Thomas A. , Sagen Jacqueline , Pearse Damien D.
Published: April 2024

Subacute spinal cord injury (SCI) displays a complex pathophysiology associated with pro-inflammation and ensuing tissue damage. Microglia, the resident innate immune cells of the CNS, in concert with infiltrating macrophages, are the primary contributors to SCI-induced inflammation. However, subpopulations of activated microglia can also possess immunomodulatory activities that are essential for tissue remodeling and repair, including the production of anti-inflammatory cytokines and growth factors that are vital for SCI recovery. Recently, reports have provided convincing evidence that sex-dependent differences exist in how microglia function during CNS pathologies and the extent to which these cells contribute to neurorepair and endogenous recovery. Herein we employed flow cytometry and immunohistochemical methods to characterize the phenotype and population dynamics of activated innate immune cells within the injured spinal cord of age-matched male and female rats within the first week (7 days) following thoracic SCI contusion. This assessment included the analysis of pro- and anti-inflammatory markers, as well as the expression of critical immunomodulatory kinases, including P38 MAPK, and transcription factors, such as NFκB, which play pivotal roles in injury-induced inflammation. We demonstrate that activated microglia from the injured spinal cord of female rats exhibited a significantly diminutive pro-inflammatory response, but enhanced anti-inflammatory activity compared to males. These changes included lower levels of iNOS and TLR4 expression but increased levels of ARG-1 and CD68 in females after SCI. The altered expression of these markers is indicative of a disparate secretome between the microglia of males and females after SCI and that the female microglia possesses higher phagocytic capabilities (increased CD68). The examination of immunoregulatory kinases and transcription factors revealed that female microglia had higher levels of phosphorylated P38Thr180/Tyr182 MAPK and nuclear NFκB pp50Ser337 but lower amounts of nuclear NFκB pp65Ser536, suggestive of an attenuated pro-inflammatory phenotype in females compared to males after SCI. Collectively, this work provides novel insight into some of the sex disparities that exist in the innate immune response after SCI and indicates that sex is an important variable when designing and testing new therapeutic interventions or interpretating positive or negative responses to an intervention.
Evaluation of the Effect of Particle Size and Biomass-to-Water Ratio on the Hydrothermal Carbonization of Sugarcane Bagasse
Authors: Moreno-Chocontá Leidy Natalia , Lozano-Pérez Alejandra Sophia , Guerrero-Fajardo Carlos Alberto
Published: April 2024

The generation of platform chemicals and hydrochar is of great interest because they reduce dependence on fossil resources and contribute to climate change mitigation by reducing carbon emissions. The main objective of this study was to evaluate the effect of biomass particle size and biomass-to-water ratio in a hydrothermal conversion system for the generation of value-added products obtained from sugarcane bagasse. Biomass characterization was performed using proximal, elemental, and structural analysis; hydrothermal carbonization was carried out at 220 and 260 °C for one hour; and conversion was monitored using pH, conductivity, and IR spectroscopy. Platform chemicals were quantified using HPLC-IR. Hydrochars were characterized by using scanning electron microscopy and energy dispersive spectroscopy. Optimizing biomass particle size and water ratio is crucial for maximizing the yield of platform chemicals and hydrochar. The study’s outcomes revealed that specific combinations, such as a biomass-to-water ratio of 1:50 and a particle size of 212 μm at 220 °C, resulted in a substantial 31.07% yield of platform chemicals on a dry basis. This highlights the critical role these parameters play in influencing the production efficiency of valuable chemicals. Furthermore, variations in biomass particle size and water ratio also affect the characteristics of hydrochar. For instance, utilizing a biomass-to-water ratio of 1:50 and a larger particle size of 600 μm at 260 °C led to the production of hydrochar with higher carbon content and increased porosity. These findings underscore how adjustments in these factors can impact not only chemical yields, but also the properties and quality of the resulting hydrochar.
The Growth Behavior and Mechanisms of Pitting Corrosion on Super 13Cr Martensitic Stainless Steel Surfaces at Different Diameter-to-Depth Ratios
Authors: Yang Zichen , Dong Hui , Han Yan , Zhang Yongjie , Li Pengyu , Feng Yukun
Published: April 2024

This study employs finite element analysis and simulated environmental immersion experiments to methodically investigate the growth behavior of pitting corrosion in stainless steel. It particularly examines how the diameter-to-depth ratio of the pit influences its growth dynamics. The findings underscore substantial variations in growth patterns and corrosion rates corresponding to different diameter-to-depth ratios. Key parameters, including electrolyte current density, potential, Fe2+ and Cl− ion concentrations, and pH values, play a crucial role in the corrosion mechanism. Remarkably, a pronounced increase in the corrosion rate at the pit bottom was observed with the increase in the diameter-to-depth ratio to 1:5. The results of this work provide insight into stainless steel pitting mechanisms, enabling the development of more effective prevention strategies.
Insights into the Ligand Effect in β-CD@Fe3O4 Composites to Activate Peroxymonosulfate for Efficient Degradation of Pharmaceutical Contaminants: A Study Employing Density Functional Theory
Authors: Quan Xi , Lv Pengzhao , Yin Linlin , Zuo Wei , Tian Yu , Zhang Jun
Published: April 2024

This study presents a detailed investigation into the use of β-cyclodextrin (β-CD) encapsulated iron oxide nanoparticle (β-CD@Fe3O4) composites, modified with different ligands, to activate peroxymonosulfate (PMS) for the degradation of pharmaceutical contaminants, namely, diclofenac, carbamazepine, and erythromycin. The focus is on understanding the ligand effect, particularly using citric acid (CIT), polyethyleneimine (PEI), and cetyl trimethyl ammonium bromide (CTAB), on the degradation performance of these composites. Employing density functional theory (DFT) calculations, this work examines the electronic structure and charge distributions of β-CD@Fe3O4 composites, providing insights into their interaction with various pollutants. The study reveals that the β-CD@PEI@Fe3O4 composite demonstrates superior degradation efficiency due to optimal electrostatic interactions, regardless of the pollutant’s hydrophobicity. On the other hand, β-CD@CIT@Fe3O4 shows moderate efficiency, and β-CD@CTAB@Fe3O4 exhibits selective efficiency, particularly for hydrophobic compounds. These findings underscore the significant role of surface chemistry in modulating the activation of PMS and the degradation of contaminants, opening avenues for designing tailored β-CD composites for environmental remediation.