bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on the Factors Affecting the Performance of a Pressure Filtration–Flocculation–Solidification Combined Method for Mud Slurry Treatment
Authors: Han Chao , Xie Hongping , Bai Bin , Liu Dongrui , Huang Yue , Zhang Rongjun
Published: October 2023

A pressure filtration–flocculation–solidification combined treatment possesses great potential for the reutilization of the waste mud slurry generated from diverse construction projects as filling material due to its versatility and high efficiency. However, very limited existing studies have focused on the factors affecting pressure filtration’s efficiency. In this paper, a calculation model for compression filtration is established based on laboratory pressure filtration model tests and one-dimensional large-strain consolidation theory. The influence of various parameters on pressure filtration’s efficiency is analyzed, and favorable values for these parameters are recommended. The results show that an increased initial mud cake thickness significantly increases the dewatering time and reduces the treatment’s efficiency. A lower dewatering time and higher efficiency can be achieved by increasing the filtration pressure, but the efficiency improvements become limited after reaching the critical pressure threshold. For the mud slurry used in this study, the optimal values for the initial mud slurry bag thickness, filtration pressure, and dewatering time are 240 mm, 1.0 MPa, and 30 min, respectively, yielding a final mud cake water content of 58.7% after filtration.
Study on Mechanism of Static Blasting-Induced Hard Rock Fracture Expansion
Authors: Xu Zhijun , Cao Yue , Li Chong , Tai Lianhai , He Sifeng
Published: October 2023

How to deal with hard rock cheaply and safely is a pressing issue in today’s coal mining. Weakening fractures of hard rock have always been a significant concern in China’s coal mine engineering. In this study, mechanical derivation, laboratory experiments, and numerical simulation research methodologies are used to evaluate the fracturing process of the static crushing agent (SCA). From a mechanical standpoint, the mechanism of fracturing hard rock by a crushing agent is investigated. It is assumed that single-hole fracturing is separated into three stages: the microfracture stage, the fissure development stage, and the breaking stage. The swelling and fracturing properties of SCA were quantitatively analyzed. It was found that the swelling pressure of SCA increased with the increase in pore diameter, and the range of the swelling pressure was 43.5 MPa to 75.1 MPa. SCA exhibited a delayed fracture initiation, but the rate of breakage was relatively high. The cracking effect of a single-hole specimen under no peripheral pressure was simulated using PFC2D, and the results were consistent with experimental observations. The internal dynamic effect, crack extension, distribution characteristics, and the development law of double-hole expansion pressure were analyzed for double-hole specimens with different hole diameters, hole spacings, and circumferential pressures. It was observed that the cracking effect was positively correlated with the pore diameter, while the pore spacing and surrounding pressure were negatively correlated. The size of the expansion pressure was negatively correlated with the pore diameter, while the pore spacing and surrounding pressure were positively correlated.
Influence of Interference Fit and Temperature on High-Speed Permanent Magnet Motor
Authors: Zeng Yiming , Yang Shanju , Yang Xinyi , Wang Qi , Zhang Lijun , Hao Jie , Hua Wencan
Published: October 2023

A high-speed permanent magnet motor is the core driving component of a centrifugal air compressor. The power of the centrifugal air compressor is output by the motor. Its safety and reliability are embodied in the stability of the rotor structure, which greatly affects the stability and working efficiency of the centrifugal air compressor. Much research has focused on the material strength, structural characteristics, and fit clearance of a high-speed rotor, whereas few research articles have focused on the influence of interference fit of high-speed and ultra-high-speed permanent magnet motors, and there is also little research on the thermal failure caused by temperature in high-speed motors. In this paper, the influence of the interference fit and temperature of the high-speed permanent magnet motor is studied. Using finite element analysis conducted by Ansys to obtain simulation data, the influencing factors of the strength of the interference are analyzed comprehensively in the centrifugal compressor rotor system. The interference value and rotational speed range are determined via numerical calculation. Under the condition of minimum interference, when the calculated speed reaches 137,628.82 rpm, the structure of the rotor is loose and fails, which is a mechanical failure caused by the relative sliding of the magnet and the sheath. The calculated speed value differs from the simulation result by about 1.2%. The simulation results show that the maximum stress of the structure can be reduced from 1186.1 MPa to 308.42 MPa by adding chamfer to the end covers in interference fit structure. The effects of interference value, rotational speed, temperature, and sheath thickness on the structure are also analyzed. From the perspective of temperature on structural reliability, the failure temperature of the structure decreases when the interference value increases. The lowest failure temperature is 182.3 °C when the interference value is 70 μm. After that, the interference value increases and the failure temperature increases. The reason for this is the interaction between radial stress and contact stress. These results are caused by the interaction between interference fit and temperature, which should be paid attention to when the structure of a high-speed permanent magnet motor is designed.
Parametrical Assessment of Polyacrylamide Polymer Membrane Used for CO2 Post-Combustion Capture
Authors: Alabid Maytham , Dinca Cristian
Published: October 2023

A sensitive analysis of CO2 capture from a coal-fired power plant of 600 MW with membrane technology based on post-combustion process is demonstrated. This study aimed to determine the influence of the membrane materials used (e.g., CO2 permeability was considered at 300, 1000, and 3000 GPU) on coal-fired power plant performance by investigating various parameters, such as the membrane number of stages, membrane surface area, and compressors’ pressure. The membrane surface area required varied from 200,000 to 800,000 m2 to procure no less than 99% purity. The total power plant efficiency was reduced by different values after integrating membrane CO2-capture technology based on the process design; nevertheless, the efficiency is profitable by around 13.5% when three membrane stages were harnessed instead of a two-stage configuration. Consequently, the levelized cost of energy (LCOE) decreased from 157 EUR/MWh (two stages of membrane) to 134 EUR/MWh (three stages of membrane).
Structural Strength Analysis of a Rotary Drum Mower in Transportation Position
Authors: Celik H. Kursat , Akinci Ibrahim , Caglayan Nuri , Rennie Allan E. W.
Published: October 2023

A rotary drum mower is a tractor-mounted harvester used for harvesting green fodder plants in agricultural fields. During transportation, it experiences significant dynamic road reaction forces that can cause deformation and functional failures. This study focuses on analysing the deformation behaviour of the machine during transportation to test the machine’s failure condition. To conduct the strength analysis, a total work cycle scenario reflecting actual load conditions and design challenges was created. Experimental strain-gauge-based stress analysis and advanced computer-aided engineering (CAE) simulation methods were employed. The study successfully conducted experimental stress analysis, 3D solid modelling, and validated finite element analysis (FEA). A comparison between experimental and simulation results showed an average relative difference of 24.25% with a maximum absolute difference of approximately 5 MPa. No functional failure issues were observed during physical experiments. The study also revealed that the mean dynamic loading value, when compared to the static linkage position, was calculated as 3.65 ± 0.40. Overall, this research provides a valuable approach for future studies on complex stress and deformation evaluations of agricultural machinery and equipment.
An Approach for Deployment of Service-Oriented Simulation Run-Time Resources
Authors: Zhang Zekun , Peng Yong , Zhang Miao , Yin Quanjun , Li Qun
Published: October 2023

The requirements for low latency and high stability in large-scale geo-distributed training simulations have made cloud-edge collaborative simulation an emerging trend. However, there is currently limited research on how to deploy simulation run-time resources (SRR), including edge servers, simulation services, and simulation members. On one hand, the deployment schemes of these resources are coupled and have mutual impacts. It is difficult to ensure overall optimum by deploying these resources separately. On the other hand, the pursuit of low latency and high system stability is often challenging to achieve simultaneously because high stability implies low server load, while a small number of simulation services implies high response latency. We formulate this problem as a multi-objective optimization problem for the joint deployment of SRR, considering the complex combinatorial relationship between simulation services. Our objective is to minimize the system time cost and resource usage rate of edge servers under constraints such as server resource capacity and the relationship between edge servers and base stations. To address this problem, we propose a learnable genetic algorithm for SRR deployment (LGASRD) where the population can learn from elites and adaptively select evolution operators performing well. Extensive experiments with different settings based on real-world data sets demonstrate that LGASRD outperforms the baseline policies in terms of optimality, feasibility, and convergence rate, verifying the effectiveness and excellence of LGASRD when deploying SRR.
φ-OTDR Based on Orthogonal Frequency-Division Multiplexing Time Sequence Pulse Modulation
Authors: Li Zhengyang , Zhang Yangan , Yuan Xueguang , Xiao Zhenyu , Zhang Yuan , Huang Yongqing
Published: October 2023

This study introduces an innovative phase-sensitive optical time-domain reflectometer (φ-OTDR) technology based on orthogonal frequency-division multiplexing (OFDM) and nonlinear frequency modulation (NLFM) pulse modulation sequences. The proposed approach addresses the inherent trade-offs among spatial resolution, frequency response range, and sensing distance that conventional φ-OTDR systems encounter. This method optimizes spatial resolution and sensing distance by modulating both the frequency and phase of optical pulses. Moreover, it enhances sidelobe suppression by adjusting the nonlinearity of frequency modulation, reducing interference between adjacent signals, and improving the signal-to-noise ratio (SNR). Additionally, orthogonal frequency-division multiplexing expands the frequency response range. This paper elucidates the fundamental principles and implementation of OFDM-NLFM time-domain pulse modulation techniques and designs, experimentally validates a φ-OTDR system based on this method, and conducts comprehensive testing and analysis of the system’s performance. The experimental results demonstrate that the proposed φ-OTDR system achieves an 11 m spatial resolution and a frequency response range of 1–10 kHz over a 16.3 km optical fiber, utilizing a 65 MHz frequency bandwidth with multiplexed signals across four frequencies. This innovative approach reduces hardware resource consumption, opening up promising prospects for various practical engineering applications in optical fiber sensing technology.
Larviculture of Brycon amazonicus under Different Food and Farming Systems
Authors: Arbeláez-Rojas Gustavo Alberto , Melão Maria da Graça Gama
Published: October 2023

Freshwater fish larviculture techniques still have deficiencies in cultivation and feeding. In this study, we evaluated experimentally different cultivation and feeding systems in the Brycon amazonicus (matrinxã) larviculture. Seven treatments with different live foods were used: T1 = a semi-intensive mesocosm system with green water; T2 = a clear water system containing Artemia sp. as food; T3 = a clear water system containing Dendrocephalus brasiliensis as food; T4 = a clear water system containing a combination of Artemia sp. and D. brasiliensis as food (a proportion of 1:1); T5, T6 and T7 were the same as T2, T3 and T4, respectively, but with a swimming exercise system. During the experiment, the water quality parameters were measured and maintained suitably for the cultures. The highest values of final weight (42.97 ± 2.58 mg) and specific growth rate (31.77 ± 0.60%) were observed in T5 (p < 0.05). Regarding the nutritional composition, the larvae of B. amazonicus that were fed nauplii of D. brasiliensis had a better profile of amino acids and essential fatty acids than those fed other live foods. Therefore, nauplii of D. brasiliensis can be used as an adequately nutritional food for larvae of B. amazonicus.
Numerical Analysis of Various Heat Countermeasures: Effects on Energy Consumption and Indoor Thermal Comfort in Densely Built Wooden House Area
Authors: Liu Shanshan , Levinson Ronnen , Narumi Daisuke
Published: October 2023

Densely built areas with poor thermal insulation suffer from high thermal environmental risks and generally consume high energy in summer. Determining the relationship between density and energy consumption is necessary, particularly when implementing urban heat island (UHI) countermeasures. This study evaluated the effects of density and UHI countermeasures on the energy consumption and indoor thermal comfort of a detached house in a typical densely built wooden house area in Yokohama City, Japan. Three densities and six countermeasures were considered. Annual hourly simulations based on the SCIENCE-Vent thermal environment simulation model yielded the following results: in densely built wooden house areas, the energy consumption and thermal discomfort increased with density. The green roof yielded the largest energy savings in the cooling and heating seasons, demonstrating the highest annual energy savings with 5.7%. Density had little impact on rooftop countermeasures, but the effect of the high-reflectance walls increased with density, and the reduction in annual energy consumption (air conditioning and lighting) is 2.6%, 3.0%, 3.6% in 37%, 47%, and 59% density cases, respectively. The impact of thermal countermeasures on indoor thermal comfort varied according to the thermal control mechanism.
Prediction of Storm Surge Water Level Based on Machine Learning Methods
Authors: Liu Yun , Zhao Qiansheng , Hu Chunchun , Luo Nianxue
Published: October 2023

Storm surge disasters result in severe casualties and economic losses. Accurate prediction of storm surge water level is crucial for disaster assessment, early warning, and effective disaster management. Machine learning methods are relatively more efficient and straightforward compared to numerical simulation approaches. However, most of the current research on storm surge water level prediction based on machine learning methods is primarily focused on point predictions. In this study, we explore the feasibility of spatial water level prediction using the ConvLSTM model. We focus on the coastal area of Guangdong Province and employ MIKE21(2019) software to simulate historical typhoons that have made landfall in the region from 1991 to 2018. We construct two datasets: one for direct water level prediction and the other for indirect water level prediction based on water level changes. Utilizing the ConvLSTM network, we employ it to forecast storm surges on both datasets, effectively capturing both temporal and spatial characteristics and thus ensuring the production of dependable results. When directly predicting water levels, we achieve an MAE (mean absolute error) of 0.026 m and an MSE (mean squared error) of 0.0038 m2. In contrast, the indirect prediction approach yields even more promising results, with an MAE of 0.014 m and an MSE of 0.0007 m2. Compared to traditional numerical simulation methods, the ConvLSTM-based approach is simpler, faster, and able to predict water levels accurately without boundary conditions or topographies. Furthermore, we consider worst-case scenarios by predicting the maximum water increase value using the random forest model. Our results indicate that the random forest model can serve as a valuable reference for forecasting the maximum water increase value of typhoon storm surges, supporting effective emergency responses to disasters.
Investigation on the Perception of Microclimatic Factors by the Elderly in Humid and Hot Areas: The Case of Guangzhou, China
Authors: Lin Chang , Feng Qiao , Huang Jun , Zhong Ruize
Published: October 2023

The problem of population aging in China is becoming increasingly serious. Increasing outdoor space can increase the frequency of outdoor activities for the elderly and effectively improve their quality of life. In this study, we examined the thermal comfort of outdoor activity spaces for older adults in summer using a subjective questionnaire in Guangzhou City, calculated and analyzed the perception and comfort range of microclimatic factors for older adults in hot and humid areas, and explored gender differences. The specific results were as follows: (1) The neutral physiological equivalent temperature (PET) for the overall respondents was 30.4 °C, compared to an acceptable PET of 33.8 °C. The neutral wind speed and acceptable wind speed for the overall respondents were both 0.4 m/s. The neutral relative humidity for the overall respondents was 56.49%, whereas the acceptable relative humidity was 64.94%. (2) Gender differences were observed among older respondents regarding PET and relative humidity, while no significant gender differences were found among older respondents regarding wind speed. (3) Summer thermal sensation voting for older adults in hot and humid areas were mainly centered on “hot” (30.2%), and “not too hot nor cold” (38.7%). The wind sensation voting was centered on “not high or low” (44.6%). Humidity sensation voting was mainly concentrated on “not wet nor dry” (69.4%). This study provides guidance to urban planners and architects to help them create urban environments that are more comfortable and responsive to the needs of the aging population.
Functional Roles of the Conserved Amino Acid Sequence Motif C, the Antiporter Motif, in Membrane Transporters of the Major Facilitator Superfamily
Authors: Varela Manuel F. , Ortiz-Alegria Anely , Lekshmi Manjusha , Stephen Jerusha , Kumar Sanath
Published: October 2023

The biological membrane surrounding all living cells forms a hydrophobic barrier to the passage of biologically important molecules. Integral membrane proteins called transporters circumvent the cellular barrier and transport molecules across the cell membrane. These molecular transporters enable the uptake and exit of molecules for cell growth and homeostasis. One important collection of related transporters is the major facilitator superfamily (MFS). This large group of proteins harbors passive and secondary active transporters. The transporters of the MFS consist of uniporters, symporters, and antiporters, which share similarities in structures, predicted mechanism of transport, and highly conserved amino acid sequence motifs. In particular, the antiporter motif, called motif C, is found primarily in antiporters of the MFS. The antiporter motif’s molecular elements mediate conformational changes and other molecular physiological roles during substrate transport across the membrane. This review article traces the history of the antiporter motif. It summarizes the physiological evidence reported that supports these biological roles.
Factors Affecting the Bioproduction of Resveratrol by Grapevine Cell Cultures under Elicitation
Authors: Vera-Urbina Juan Carlos , Sellés-Marchart Susana , Martínez-Márquez Ascensión , Martínez-Esteso María José , Pedreño María Angeles , Morante-Carriel Jaime , Bru-Martínez Roque
Published: October 2023

Here we present a study of the characterization and optimization of the production of trans-Resveratrol (t-R) in grape (Vitis vinifera cv. Gamay) cell cultures elicited with methyl jasmonate (MeJA) and dimethyl-β-cyclodextrin (DIMEB). The aim of this study was to determine the influence of a number of factors of the grapevine cell culture on t-R production level in 250 mL shaken flasks that would enable the better control of this bioproduction system when it is upscaled to a 2 L stirred bioreactor. The factors included the optimal growth phase for elicitation, the concentration of elicitors and of biomass, the order of addition of elicitors, and the illumination regime and ageing of cells. We found out that the optimal biomass density for the production of t-R was 19% (w/v) with an optimal ratio of 0.5 g DIMEB/g biomass. The most productive concentrations of the elicitors tested were 50 mM DIMEB and 100 µM MeJA, reaching maximum values of 4.18 mg·mL−1 and 16.3 mg·g biomass−1 of t-R concentration and specific production, respectively. We found that the order of elicitor addition matters since, as compared with the simultaneous addition of both elicitors, the addition of MeJA 48 h before DIMEB results in ca. 40% less t-R production, whilst there is no significant difference when MeJA is added 48 h after DIMEB. Upon upscaling, the better conditions tested for t-R production were aeration at 1.7 vol/vol/min without agitation, 24 °C, and 30 g·L−1 sucrose, achieving production rates similar to those obtained in shaken flasks.
Protein Concentration Affects the Food Allergen γ-Conglutin Uptake and Bacteria-Induced Cytokine Production in Dendritic Cells
Authors: Heinzl Giuditta C. , Eriksen Danny Blichfeldt , Johnsen Peter Riber , Scarafoni Alessio , Frøkiær Hanne
Published: October 2023

γ-Conglutin (γ-C) from lupin seeds has been identified as a potent allergen with cross reactivity to peanuts. Here, we investigated how γ-C affected the response in bone marrow-derived dendritic cells (DCs) to bacterial stimuli. γ-C enhanced L. acidophilus NCFM (LaNCFM)-induced IL-12, IL-10, and IL-23 dose-dependently. In contrast, together with E. coli Nissle or LPS, γ-C reduced the production of IL-12 but not of IL-23 and IL-10. Enzyme-hydrolyzed γ-C also enhanced LaNCFM-induced IL-12 and IL-23 production. All preparations induced ROS production in the DCs. The mannose receptor ligands mannan and dextran and the clathrin inhibitor monodansylcadaverine partly inhibited the endocytosis of γ-C. Kunitz trypsin inhibitor and the scavenger receptor ligand polyG also enhanced LaNCFM-induced IL-12, indicating the involvement of receptors other than C-type lectin receptors. The endocytosis of labeled γ-C increased dose-dependently by addition of unlabeled γ-C, which coincided with γ-C’s tendency to aggregate. Taken together, γ-C aggregation affects endocytosis and affects the cytokine production induced by gram-positive and gram-negative bacteria differently. We suggest that γ-C is taken up by the same mechanism as other food proteins but due to aggregation is present in higher concentration in the DCs. This could influence the resulting T-cell response in a microbial stimuli-dependent way.
Identifying the Role of Disulfidptosis in Endometrial Cancer via Machine Learning Methods
Authors: Fu Fei , Lu Xuesong , Zhang Zhushanying , Li Zhi , Xie Qinlan
Published: October 2023

Uterine corpus endometrial carcinoma (UCEC) is the second most common gynecological cancer in the world. With the increased occurrence of UCEC and the stagnation of research in the field, there is a pressing need to identify novel UCEC biomarkers. Disulfidptosis is a novel form of cell death, but its role in UCEC is unclear. We integrate differential analysis and the XGBoost algorithm to determine a disulfidptosis-related characteristic gene (DRCG), namely LRPPRC. By prediction and verification based on online databases, we construct a regulatory network of ceRNA in line with the scientific hypothesis, including a ceRNA regulatory axis and two mRNA-miRNA regulatory axes, i.e., mRNA LRPPRC/miRNA hsa-miR-616-5p/lncRNA TSPEAR-AS2, mRNA LRPPRC/miRNA hsa-miR-4658, and mRNA LRPPRC/miRNA hsa-miR-6783-5p. We use machine learning methods such as GBM to screen out seven disulfidptosis-related characteristic lncRNAs (DRCLs) as predictors, and build a risk prediction model with good prediction ability. SCORE = (1.136*LINC02449) + (−2.173*KIF9-AS1) + (−0.235*ACBD3-AS1) + (1.830*AL354892.3) + (−1.314*AC093677.2) + (0.636*AC113361.1) + (−0.589*CDC37L1-DT). The ROC curve shows that in the training set samples, the AUCs for predicting 1-, 3-, 6-, and 10-year OS are 0.804, 0.724, 0.719, and 0.846, respectively. In the test set samples, the AUCs for predicting 1-, 3-, 6-, and 10-year OS are 0.615, 0.657, 0.687, and 0.702, respectively. In all samples, the AUCs for predicting 1-, 3-, 6-, and 10-year OS are 0.752, 0.706, 0.705, and 0.834, respectively. CP724714 has been screened as a potential therapy option for individuals who have a high risk of developing UCEC. Two subtypes of disulfidptosis-related genes (DRGs) and two subtypes of DRCLs are obtained by NMF method. We find that subtype N1 of DRGs is mainly enriched in various metabolic pathways, and subtype N1 may play a significant role in the process of disulfidptosis. Our study confirms for the first time that disulfidptosis plays a role in UCEC. Our findings help improve the prognosis and treatment of UCEC.
Current Status and Emerging Trends in Colorectal Cancer Screening and Diagnostics
Authors: Beniwal Shreya , Lamo Paula , Kaushik Ajeet , Lorenzo-Villegas Dionisio , Liu Yuguang , MohanaSundaram ArunSundar
Published: October 2023

Colorectal cancer (CRC) is a prevalent and potentially fatal disease categorized based on its high incidences and mortality rates, which raised the need for effective diagnostic strategies for the early detection and management of CRC. While there are several conventional cancer diagnostics available, they have certain limitations that hinder their effectiveness. Significant research efforts are currently being dedicated to elucidating novel methodologies that aim at comprehending the intricate molecular mechanism that underlies CRC. Recently, microfluidic diagnostics have emerged as a pivotal solution, offering non-invasive approaches to real-time monitoring of disease progression and treatment response. Microfluidic devices enable the integration of multiple sample preparation steps into a single platform, which speeds up processing and improves sensitivity. Such advancements in diagnostic technologies hold immense promise for revolutionizing the field of CRC diagnosis and enabling efficient detection and monitoring strategies. This article elucidates several of the latest developments in microfluidic technology for CRC diagnostics. In addition to the advancements in microfluidic technology for CRC diagnostics, the integration of artificial intelligence (AI) holds great promise for further enhancing diagnostic capabilities. Advancements in microfluidic systems and AI-driven approaches can revolutionize colorectal cancer diagnostics, offering accurate, efficient, and personalized strategies to improve patient outcomes and transform cancer management.
Peptide-Coated Bacteriorhodopsin-Based Photoelectric Biosensor for Detecting Rheumatoid Arthritis
Authors: Chen Hsiu-Mei , Tsai Yi-Hsuan , Hsu Chien-Yi , Wang Yong-Yi , Hsieh Cheng-En , Chen Jin-Hua , Chang Yu-Sheng , Lin Ching-Yu
Published: October 2023

An effective early diagnosis is important for rheumatoid arthritis (RA) management. This study reveals a novel RA detection method using bacteriorhodopsin as a photoelectric transducer, a light-driven proton pump in purple membranes (PMs). It was devised by covalently conjugating a PM monolayer-coated electrode with a citrullinated-inter-alpha-trypsin inhibitor heavy chain 3 (ITIH3)542–556 peptide that recognizes the serum RA-associated autoantibodies. The direct serum coating decreased the photocurrents in the biosensor, with the reduction in the photocurrent caused by coating with an RA-patient serum that is significantly larger than that with a healthy-control serum (38.1% vs. 20.2%). The difference in the reduction in the photocurrent between those two serum groups widened after the serum-coated biosensor was further labeled with gold nanoparticle (AuNP)-conjugated anti-IgA (anti-IgA-AuNP) (53.6% vs. 30.6%). Both atomic force microscopic (AFM) and Raman analyses confirmed the sequential peptide, serum, and anti-IgA-AuNP coatings on the PM-coated substrates. The reductions in the photocurrent measured in both the serum and anti-IgA-AuNPs coating steps correlated well with the results using commercial enzyme-linked immunosorbent assay kits (Spearman rho = 0.805 and 0.787, respectively), with both a sensitivity and specificity close to 100% in both steps. It was shown that an RA diagnosis can be performed in either a single- or two-step mode using the developed biosensor.
Alteration of Metabolic Profiles during the Progression of Alzheimer’s Disease
Authors: Yu Wuhan , Chen Lihua , Li Xuebing , Han Tingli , Yang Yang , Hu Cheng , Yu Weihua , Lü Yang
Published: October 2023

(1) Background: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that threatens the population health of older adults. However, the mechanisms of the altered metabolism involved in AD pathology are poorly understood. The aim of the study was to identify the potential biomarkers of AD and discover the metabolomic changes produced during the progression of the disease. (2) Methods: Gas chromatography–mass spectrometry (GC–MS) was used to measure the concentrations of the serum metabolites in a cohort of subjects with AD (n = 88) and a cognitively normal control (CN) group (n = 85). The patients were classified as very mild (n = 25), mild (n = 27), moderate (n = 25), and severe (n = 11). The serum metabolic profiles were analyzed using multivariate and univariate approaches. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied to identify the potential biomarkers of AD. Biofunctional enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes. (3) Results: Our results revealed considerable separation between the AD and CN groups. Six metabolites were identified as potential biomarkers of AD (AUC > 0.85), and the diagnostic model of three metabolites could predict the risk of AD with high accuracy (AUC = 0.984). The metabolic enrichment analysis revealed that carbohydrate metabolism deficiency and the disturbance of amino acid, fatty acid, and lipid metabolism were involved in AD progression. Especially, the pathway analysis highlighted that l−glutamate participated in four crucial nervous system pathways (including the GABAergic synapse, the glutamatergic synapse, retrograde endocannabinoid signaling, and the synaptic vesicle cycle). (4) Conclusions: Carbohydrate metabolism deficiency and amino acid dysregulation, fatty acid, and lipid metabolism disorders were pivotal events in AD progression. Our study may provide novel insights into the role of metabolic disorders in AD pathogenesis and identify new markers for AD diagnosis.
The Combination of a Graph Neural Network Technique and Brain Imaging to Diagnose Neurological Disorders: A Review and Outlook
Authors: Zhang Shuoyan , Yang Jiacheng , Zhang Ying , Zhong Jiayi , Hu Wenjing , Li Chenyang , Jiang Jiehui
Published: October 2023

Neurological disorders (NDs), such as Alzheimer’s disease, have been a threat to human health all over the world. It is of great importance to diagnose ND through combining artificial intelligence technology and brain imaging. A graph neural network (GNN) can model and analyze the brain, imaging from morphology, anatomical structure, function features, and other aspects, thus becoming one of the best deep learning models in the diagnosis of ND. Some researchers have investigated the application of GNN in the medical field, but the scope is broad, and its application to NDs is less frequent and not detailed enough. This review focuses on the research progress of GNNs in the diagnosis of ND. Firstly, we systematically investigated the GNN framework of ND, including graph construction, graph convolution, graph pooling, and graph prediction. Secondly, we investigated common NDs using the GNN diagnostic model in terms of data modality, number of subjects, and diagnostic accuracy. Thirdly, we discussed some research challenges and future research directions. The results of this review may be a valuable contribution to the ongoing intersection of artificial intelligence technology and brain imaging.
COVID-19—Evidence of the Impact of Literacy and Salutogenic Behaviours in Positive Mental Health: A Cross-Sectional Study
Authors: Almeida Cláudia , Novo André , Canut Maria Lluch , Ferré-Grau Carme , Sequeira Carlos
Published: October 2023

Positive mental health is defined as the ability to perceive and interpret the context of a situation and to adapt to it whenever necessary. Considering the pandemic situation, identifying the factors that may have the greatest impact on quality of life and consequently, on positive mental health is paramount. The objective of this study was to assess the impact of health literacy on the adoption of behaviours that promote positive mental health during COVID-19. A descriptive, cross-sectional and correlational study was conducted on a sample of 770 patients using a questionnaire for sociodemographic characterization, the Positive Mental Health Questionnaire and the Mental Health Knowledge Questionnaire. Concerning health-promoting behaviours, those who sleep enough hours, exercise regularly, eat healthy and are more aware of mental health promotion activities, or have greater mental health literacy, have higher positive mental health scores. Thus, having more knowledge of mental health and adopting health-promoting behaviours improve positive mental health.
Effects of Physical Exercise on Cerebral Blood Velocity in Older Adults: A Systematic Review and Meta−Analysis
Authors: Paiva Prudente Tiago , Oliva Henrique Nunes Pereira , Oliva Isabela Oliveira , Mezaiko Eleazar , Monteiro-Junior Renato Sobral
Published: October 2023

As the older population grows, there is an increasing interest in understanding how physical exercise can counteract the changes seen with aging. The benefits of exercise to general health, and especially to the cardiovascular system, have been a topic of discussion for decades. However, there is still a need to elucidate the effects of training programs on the cerebrovascular blood velocity in older people. This systematic review and meta-analysis aimed to investigate the effect of physical exercise on the cerebral blood velocity in older people (PROSPERO CRD42019136305). A search was performed on PubMed, Web of Science, EBSCO, ScienceDirect, and Scopus from the inception of this study to October 2023, retrieving 493 results, of which 26 were included, analyzing more than 1000 participants. An overall moderate risk of bias was found for the studies using the Cochrane risk-of-bias tools for randomized and non-randomized clinical trials. The pooled results of randomized trials showed that older people who underwent physical exercise presented a statistically significant increase in cerebral blood velocity (3.58; 95%CI = 0.51, 6.65; p = 0.02). This result indicates that physical exercise is important to help maintain cerebral health in older adults.
Investigation of the Crack Behavior of CRC Using 4D Computed Tomography, Photogrammetry, and Fiber Optic Sensing
Authors: Giese Josiane , Herbers Max , Liebold Frank , Wagner Franz , Grzesiak Szymon , de Sousa Christoph , Pahn Matthias , Maas Hans-Gerd , Marx Steffen , Curbach Manfred , Beckmann Birgit
Published: October 2023

The highly irregular crack pattern of reinforced concrete has been studied primarily at the surface. The ability to extend image correlation into the interior of structures by using X-ray computed tomography (CT) opens up new possibilities for analyzing the internal mechanics of concrete. In order to enable a complete material characterization, it is necessary to study the crack geometry at the micro level in 3D images over time, i.e., 4D data. This paper presents the results of in situ CT tests that were carried out on carbon-reinforced concrete (CRC) beams subjected to bending load. The main objective of the tests was the experimental analysis of the evolution of individual cracks at different stages of their formation by applying digital volume correlation (DVC) to the 4D image data from the computed tomography. The results obtained from the CT were compared with other measurement techniques, such as distributed fiber optic sensing, clip gauges, and digital image correlation (DIC).
Effects of Concrete Strength and CFRP Cloth Ratio on the Shear Performance of CFRP Cloth Strengthened RC Beams
Authors: Li Dong , Yang Bo , Zhang Jiangxing , Jin Liu , Du Xiuli
Published: October 2023

A three-dimensional meso-scale numerical model, which considers (1) the concrete meso-structures, (2) the bond slip between concrete internal structures and steel bars, and (3) the stripping behavior of carbon fiber reinforced polymer (CFRP) cloth from the surface of the concrete component, is established to investigate the effects of concrete strength and the CFRP cloth ratio on the shear performance of reinforced concrete (RC) beams. On the basis of verifying the rationality of the shear failure model and the feasibility of the CFRP reinforcement simulation method, 30 orthogonally designed numerical models of six kinds of concrete strength and five kinds of CFRP cloth ratios were designed and established. Based on the numerical simulation results, this paper analyzes the damage evolution of the CFRP–concrete interface, the variation trend of CFRP strain along the height direction of beam, the failure mode, and the load-displacement curve. Results show the following: (1) With the increase of concrete strength grade and CFRP cloth ratio, the shear strength of RC beams strengthened with increases in CFRP cloth ratio, the influence range of concrete strength grade is 24–50%, and the influence range of the CFRP cloth ratio is 10–25%; (2) The improvement range decreases, and the improvement range of the concrete strength grade decreases, and the reduction range is about 20%; (3) Based on the simulation results, influences of concrete strength and CFRP cloth ratio on the shear strength of CFRP cloth-strengthened RC beams are quantitatively considered.
The Role of Xanthan Gum in Predicting Durability Properties of Self-Compacting Concrete (SCC) in Mix Designs
Authors: Masoumi Alireza , Farokhzad Reza , Ghasemi Seyed Hooman
Published: October 2023

This study comprehensively investigates the rheological properties of self-compacting concrete (SCC) and their impact on critical parameters, including the migration coefficient, penetration depth of chlorine ions, specific electrical resistance, and compressive strength. A total of 43 mix designs were meticulously examined to explore the relationships between these properties. Quantitative analysis employed a backpropagation neural network model with a single hidden layer to accurately predict the resistant and durable characteristics of self-compacting concrete. The optimal number of neurons in the hidden layer was determined using a fitting component selection method, implemented in MATLAB software(2021b). Additionally, qualitative analysis was conducted using sensitivity analysis and expert opinions to determine the priority of research additives. The main contributions of this paper lie in the exploration of SCC properties, the utilization of a neural network model for accurate prediction, and the prioritization of research additives through sensitivity analysis. The neural network model demonstrated exceptional performance in predicting test results, achieving a high accuracy rate using 14 neurons for predicting parameters such as chlorine penetration depth, compressive strength, migration coefficient, and specific electrical resistance. Sensitivity analysis revealed that xanthan gum emerged as the most influential additive, accounting for 43% of the observed effects, followed by nanomaterials at 35% and micro-silica at 21%.
Dimension Reduction Method-Based Stochastic Wind Field Simulations for Dynamic Reliability Analysis of Communication Towers
Authors: Yan Long , Xu Bohang , Liu Zhangjun
Published: October 2023

The communication tower is a lifeline engineering that ensures the normal operation of wireless communication systems. Extreme wind disasters are inevitable while it is in service. Two dimension-reduction (DR) probabilistic representations based on proper orthogonal decomposition (POD) and wavenumber spectral representation (WSR), say DR-POD and DR-WSR, were thus proposed in this study. In order to determine the least representative sample size that satisfies the engineering accuracy requirements, the simulation error and simulation duration of 10 simulation points distributed along the height direction of the communication tower under different representative sample numbers were compared. Furthermore, for the fluctuating wind field with different numbers of simulation points distributed along the height of the communication tower, the simulation accuracy as well as efficiency of the DR-POD and the DR-WSR were compared. Finally, a high-rise communication tower structure’s wind-induced dynamic response study and wind-resistance reliability analysis were performed utilizing an alliance of the probability density evolution method (PDEM) and two DR probabilistic models, taking 10 load points into account. The structural dynamic analysis illustrates that the reliability of the communication tower structure and the wind-induced dynamic response allying the two DR probabilistic models with the PDEM have outstanding consistency.
Enhancing Buildings’ Energy Resilience by Dynamic Seismic Emergency Inspection and Restoration Scheduling in Multiple Systems
Authors: Zhang Zhenyu , Li Shixian , Chen Aidi , Jin Xin , Lan Junjian , Liu Yuyao , Wei Hsi-Hsien
Published: October 2023

Buildings’ energy resilience in natural disasters is reliant on the support of the functionalities of critical infrastructure that the buildings connect to, such as highway-bridge and electric power systems. Meanwhile, as critical infrastructure systems have increasingly become interconnected and interdependent, they are more susceptible to natural hazards and less able to withstand their effects. Insufficient research has been conducted regarding computational models of effectively representing the interdependencies and interactions involved in the restoration scheduling of post-disaster critical infrastructure systems. To address this research gap, this study proposes integer programs, integrating hybrid genetic algorithms, to explicitly investigate the impact of interactions and interdependencies between electric power systems (EPSs) and highway-bridge systems (HBSs) on the energy-recovery processes of buildings. The objective is to dynamically prioritize the restoration scheduling for EPSs and HBSs while considering inspection and restoration activities. A case study based on the 2008 Wenchuan Earthquake in Sichuan province, China, is employed to validate the efficacy of the proposed method. The results of the analysis reveal that the dynamic model exhibits a substantial 6.4% improvement in building energy resilience at the seven-day mark, compared to the static model. Moreover, the proposed coupled EPS–HBS inspection–restoration joint model outperforms a disjoint EPS inspection–restoration scheduling model, yielding a remarkable 11.4% enhancement in system resilience at the seven-day mark. These findings underscore the significance of considering interdependencies and interactions within critical infrastructure systems to enhance the energy resilience of buildings in earthquake-affected areas.
The Influence of the Microbiome on Urological Malignancies: A Systematic Review
Authors: Porto Joao G. , Arbelaez Maria Camila Suarez , Pena Brandon , Khandekar Archan , Malpani Ankur , Nahar Bruno , Punnen Sanoj , Ritch Chad R. , Gonzalgo Mark L. , Parekh Dipen J. , Marcovich Robert , Shah Hemendra N.
Published: October 2023

The microbiome, once considered peripheral, is emerging as a relevant player in the intricate web of factors contributing to cancer development and progression. These often overlooked microorganisms, in the context of urological malignancies, have been investigated primarily focusing on the gut microbiome, while exploration of urogenital microorganisms remains limited. Considering this, our systematic review delves into the complex role of these understudied actors in various neoplastic conditions, including prostate, bladder, kidney, penile, and testicular cancers. Our analysis found a total of 37 studies (prostate cancer 12, bladder cancer 20, kidney cancer 4, penile/testicular cancer 1), revealing distinct associations specific to each condition and hinting at potential therapeutic avenues and future biomarker discoveries. It becomes evident that further research is imperative to unravel the complexities of this domain and provide a more comprehensive understanding.