bluuebunny/crossref_metadata_2025 huggingface dataset:
An Efficient Systematic Methodology for Noise and Vibration Analysis of a Reconfigurable Dynamic System Using Receptance Coupling Formulation
Authors: Hamedi Behzad , Taheri Saied
Published: November 2024

This study presents a generalized and systematic approach to modeling complex dynamic systems using Frequency-Based Substructuring (FBS). The aim is to develop an efficient method for system identification and subsystem decomposition, enabling the creation of reduced-order models for non-linear dynamic systems that are modular and reconfigurable. The methodology combines receptance (Frequency Response Function, FRF) properties from individual subsystems to predict the overall system’s response. This technique extends existing methods by Jetmundsen and D.D. Klerk and adapts them to subsystems with full degrees of freedom (DoFs), making it suitable for flexible and distributed structures. To demonstrate its effectiveness, the method is applied to vehicle noise and vibration analysis, where subsystems are initially treated as rigid bodies, but are later adapted to flexible characteristics. The results show that this hybrid approach accurately predicts system responses, offering significant advantages for NVH target setting when subsystem FRF matrices are sourced either from testing or numerical simulations. This methodology enhances the capability to model complex dynamic systems with improved precision and reduced computational cost. A comparison with traditional modeling techniques confirms the validity of the approach.
Analysis on Evaluations of Monterey Bay Aquarium Research Institute’s Wave Energy Converter’s Field Data Using WEC-Sim and Gazebo: A Simulation Tool Comparison
Authors: Dizon Chris , Coe Ryan , Hamilton Andrew , Forbush Dominic , Anderson Michael , Brekken Ted , Bacelli Giorgio
Published: November 2024

Although many studies have validated wave energy converter (WEC) numerical models against scaled prototype experimental data, there remains a notable lack of validation using data from full-scale deployed WECs. This paper compares two numerical models of Monterey Bay Aquarium Research Institute’s Wave Energy Converter (MBARI-WEC), a two-body point absorber with an electro-hydraulic power take-off system (PTO). The models are implemented in WEC-Sim/Simscape and Gazebo Simulator. A statistical analysis of the models was performed, and field results were obtained to compare the models’ accuracy in predicting the RMS piston velocity, RMS motor speed, and mean electric power compared to field data for 56 observations across varying sea states. The Gazebo model demonstrated a closer agreement across all three parameters for a majority of the observations. When compared to the field data, the Gazebo and WEC-Sim models exhibited average mean electric power overestimations of 13% and 22%, respectively.
Identification of Elephant Rumbles in Seismic Infrasonic Signals Using Spectrogram-Based Machine Learning
Authors: Vidunath Janitha , Shamal Chamath , Hiroshan Ravindu , Gamlath Udani , Edussooriya Chamira U. S. , Munasinghe Sudath R.
Published: November 2024

This paper presents several machine learning methods and highlights the most effective one for detecting elephant rumbles in infrasonic seismic signals. The design and implementation of electronic circuitry to amplify, filter, and digitize the seismic signals captured through geophones are presented. The process converts seismic rumbles to a spectrogram and the existing methods of spectrogram feature extraction and appropriate machine learning algorithms are compared on their merit for automatic seismic rumble identification. A novel method of denoising the spectrum that leads to enhanced accuracy in identifying seismic rumbles is presented. It is experimentally found that the combination of the Mel-frequency cepstral coefficient (MFCC) feature extraction method and the ridge classifier machine learning algorithm give the highest accuracy of 97% in detecting infrasonic elephant rumbles hidden in seismic signals. The trained machine learning algorithm can run quite efficiently on general-purpose embedded hardware such as a Raspberry Pi, hence the method provides a cost-effective and scalable platform to develop a tool to remotely localize elephants, which would help mitigate the human–elephant conflict.
Safety Aspects of Stationary Battery Energy Storage Systems
Authors: He Minglong , Chartouni Daniel , Landmann Daniel , Colombi Silvio
Published: November 2024

Stationary battery energy storage systems (BESS) have been developed for a variety of uses, facilitating the integration of renewables and the energy transition. Over the last decade, the installed base of BESSs has grown considerably, following an increasing trend in the number of BESS failure incidents. An in-depth analysis of these incidents provides valuable lessons for improving the safety of BESS. This paper discusses multiple safety layers at the cell, module, and rack levels to elucidate the mechanisms of battery thermal runaway and BESS failures. We further provide insights into different safety aspects of BESS, covering the system architecture, system consideration, safety standards, typical quality issues, failure statistics, and root causes. Various mitigation strategies are recommended and summarized. We highlight the importance of multi-disciplinary approaches in knowing, managing, and mitigating the risks associated with BESS. In general, this review paper serves as a guide for understanding the safety of BESS.
Thermal Modeling of Lithium-Ion Battery Under High-Frequency Current Excitation and Comparative Study of Self-Heating Scheme
Authors: Li Hao , Chen Jianan , Ma Yingtao , Liu Weizhi , Tang Lei , Liu Bing
Published: November 2024

High-frequency ripple current excitation reduces the lithium precipitation risk of batteries during self-heating at low temperatures. To study the heat generation behavior of batteries under high-frequency ripple current excitation, this paper establishes a thermal model of LIBs, and different types of LIBs with low-temperature self-heating schemes are studied based on the established thermal model. Under the consideration of contact impedance, this paper tests the heat production of the battery under high-frequency ripple current and establishes an accurate thermal model of a lithium-ion battery under the excitation of high-frequency ripple current, and the absolute value of the maximum relative error between the measurement results and the thermal model is reduced from 181.4% to less than 20.6%, which makes the battery thermal model under high-frequency ripple current excitation more accurate. Then, based on the established thermal model, the calculation method of the minimum heating power required for different batteries under the same low-temperature self-heating conditions is proposed for batteries of different sizes, thermal properties, and internal resistances, and the preferred low-temperature self-heating scheme for different types of batteries is proposed by comparing the current multiplicity required for different high-frequency ripple current self-heating schemes.
The Effect of EEG Biofeedback Training Frequency and Environmental Conditions on Simple and Complex Reaction Times
Authors: Dariusz Skalski , Kostrzewa Maciej , Magdalena Prończuk , Markowski Jarosław , Pilch Jan , Żak Marcin , Maszczyk Adam
Published: November 2024

The objective of this study is to evaluate the impact of EEG biofeedback training under normoxic and normobaric hypoxic conditions on both simple and complex reaction times in judo athletes, and to identify the optimal training frequency and environmental conditions that substantially enhance reaction times in the examined athlete groups. The study comprised 20 male judo athlete members of the Polish national judo team in the middleweight and heavyweight categories. We randomly assigned participants to an experimental group and a control group. We conducted the research over four cycles, varying the frequency of EEG biofeedback sessions and environmental circumstances for both the experimental and control groups. Every research cycle had 15 training sessions. The results showed that the experimental group, following the theta/beta regimen, got significantly faster at complex reactions after a training cycle that included sessions every other day at normal oxygen levels. Following daily training sessions in normoxic circumstances, we noted enhancements in simple reaction speeds. Under normobaric hypoxia conditions, the judo athletes showed deterioration in both simple and complex reaction times. The control group showed no similar changes. Daily EEG training in normoxic settings markedly improved simple reaction time, but EEG-BF training conducted every other day greatly raised complicated reaction time. In contrast, training under normobaric hypoxia settings did not result in enhancements in basic or complicated reaction times following EEG training.
Keypoints-Based Multi-Cue Feature Fusion Network (MF-Net) for Action Recognition of ADHD Children in TOVA Assessment
Authors: Tang Wanyu , Shi Chao , Li Yuanyuan , Tang Zhonglan , Yang Gang , Zhang Jing , He Ling
Published: November 2024

Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder among children and adolescents. Behavioral detection and analysis play a crucial role in ADHD diagnosis and assessment by objectively quantifying hyperactivity and impulsivity symptoms. Existing video-based action recognition algorithms focus on object or interpersonal interactions, they may overlook ADHD-specific behaviors. Current keypoints-based algorithms, although effective in attenuating environmental interference, struggle to accurately model the sudden and irregular movements characteristic of ADHD children. This work proposes a novel keypoints-based system, the Multi-cue Feature Fusion Network (MF-Net), for recognizing actions and behaviors of children with ADHD during the Test of Variables of Attention (TOVA). The system aims to assess ADHD symptoms as described in the DSM-V by extracting features from human body and facial keypoints. For human body keypoints, we introduce the Multi-scale Features and Frame-Attention Adaptive Graph Convolutional Network (MSF-AGCN) to extract irregular and impulsive motion features. For facial keypoints, we transform data into images and employ MobileVitv2 for transfer learning to capture facial and head movement features. Ultimately, a feature fusion module is designed to fuse the features from both branches, yielding the final action category prediction. The system, evaluated on 3801 video samples of ADHD children, achieves 90.6% top-1 accuracy and 97.6% top-2 accuracy across six action categories. Additional validation experiments on public datasets NW-UCLA, NTU-2D, and AFEW-VA verify the network’s performance.
Senescence-like Phenotype After Chronic Exposure to Isoproterenol in Primary Quiescent Immune Cells
Authors: Laumann Michael , Palombo Philipp , Fieres Judy , Thomas Mara , Saretzki Gabriele , Bürkle Alexander , Moreno-Villanueva Maria
Published: November 2024

Chronic stress is associated with a higher risk for carcinogenesis as well as age-related diseases and immune dysfunction. There is evidence showing that psychological stress can contribute to premature immunosenescence. Therefore, the question arose whether chronic exposure to catecholamine could drive immune cells into senescence. Peripheral blood mononuclear cells were isolated from whole blood. After repeated ex vivo treatment with isoproterenol, an epinephrine analog, well-established senescence biomarkers were assessed. We found (i) DNA double-strand break induction, (ii) telomere shortening, (iii) failure to proliferate, (iv) higher senescence-associated β-galactosidase activity, (v) decreases in caspases 3 and 7 activity, and (vi) strong upregulation of the proteoglycan versican accompanied by increased cellular adhesion suggesting the induction of a senescence-like phenotype. These results emphasize the complexity of the effect of isoproterenol on multiple cellular processes and provide insights into the molecular mechanisms of stress leading to immunosenescence.
Novel Antimicrobial and Antitumor Agents Bearing Pyridine-1,2,4-triazole-3-thione-hydrazone Scaffold: Synthesis, Biological Evaluation, and Molecular Docking Investigation
Authors: Šermukšnytė Aida , Stasevych Maryna , Komarovska-Porokhnyavets Olena , Zvarych Viktor , Jakubauskienė Eglė , Kantminienė Kristina , Tumosienė Ingrida
Published: November 2024

A series of target 4-substituted-5-(2-(pyridine-2-ylamino)ethyl)-2,4-dihydro-3H-1,2,4-triazole-3-thiones and their chloro analogs 7–21 were synthesized in a reaction of the selected aldehydes with the corresponding 4-amino-1,2,4-triazole-3-thiones 5 and 6, which were obtained from 3-(pyridin-2-ylamino)propanoic acid (3) or 3-((5-chloropyridin-2-yl)amino)propanoic acid (4), respectively, with thioacetohydrazide. The antibacterial and antifungal activities of the synthesized hydrazones were screened against the bacteria Escherichia coli, Staphylococcus aureus, and Mycobacterium luteum and the fungi Candida tenuis and Aspergillus niger by agar diffusion and serial dilution methods. 4-Amino-5-(2-((5-chloropyridin-2-yl)amino)ethyl)-2,4-dihydro-3H-1,2,4-triazole-3-thione (6) and 4-(benzylideneamino)-5-(2-(pyridin-2-ylamino)ethyl)-2,4-dihydro-3H-1,2,4-triazole-3-thione (7) were identified as exceptionally active (MIC 0.9 µg/mL) against the fungus C. tenuis. 5-Chloropyridine derivatives bearing 4-benzylidene 8, 2-nitrobenzylidene 10, pyridinylmethylene 16, and 4-methylthiobenzylidene 21 moieties showed very high antibacterial activity (MIC 3.9 µg/mL) against the M. luteum strain. The cell viability screening of the synthesized compounds using triple-negative breast cancer MDA-MB-231 and glioblastoma U-87 cell lines by MTT assay identified three active hydrazones, of which 5-(2-(pyridin-2-ylamino)ethyl)-4-((pyridin-3-ylmethylene)amino)-2,4-dihydro-3H-1,2,4-triazole-3-thione (15) had the highest effect on the viability of cells (IC50 value 39.2 ± 1.7 μM against MDA-MD-231). The in silico molecular modeling results suggested that these three most active hydrazones might have influenced the mitogen-activated protein kinase pathway through the inhibition of BRAF and MEK serine–threonine protein kinases. 5-(2-((5-Chloropyridin-2-yl)amino)ethyl)-4-((4-(methylthio)benzylidene)amino)-2,4-dihydro-3H-1,2,4-triazole-3-thione (21) demonstrated the highest affinity among them.
Bone Marrow Stem Cell Population in Single- and Multiple-Level Aspiration
Authors: Che Xiangguo , Kim Hee-June , Jin Xian , Kim Joon-Woo , Park Kyeong-Hyeon , Lim Jeong-Ok , Kyung Hee-Soo , Oh Chang-Wug , Choi Je-Yong
Published: November 2024

Background: Bone marrow aspiration concentrate (BMAC) has garnered increasing interest due to its potential for healing musculoskeletal injuries. While the iliac crest remains a common harvest site, the aspiration technique’s efficacy in offering the highest yield and prevalence of mesenchymal stem cells (MSCs) is controversial. This study aimed to compare two different techniques of bone marrow aspiration over the anterior iliac crest from a single level versus multiple levels. Methods: Anterior iliac crests were selected in seven adult patients (aged between 31 and 59 years old). Aspiration was achieved using an 11-gauge needle (length: 100 mm; diameter: 2.3 mm) specifically manufactured for bone marrow collection (BD, Becton, Franklin Lakes, NJ, USA) connected to a 10 mL syringe. On one side, 4cc of bone marrow was aspirated at a single level to a depth of 7 cm without changing the needle direction. On the other side, over the same portion of the iliac crest, 1 cc of bone marrow was obtained from multiple levels of different depths during needle retrieval, maintaining a distance of 1 cm and changing the tip direction. The samples were blindly sent to the laboratory without indicating whether they came from an single level or multiple levels. Fluorescence-activated cell sorting (FACS) and osteoblast differentiation were analyzed and compared. Results: In the FACS analysis, the single level resulted in a higher population of MSCs that were positive for CD105, CD73, and CD90 and negative for CD34, compared to the multiple-level method. In the process of osteoblast differentiation, it was observed that MSCs exhibited more advanced features of enhanced osteoblastic abilities in the single-level method rather than the multiple-level method. Conclusions: A single-level aspiration technique at the anterior iliac crest may produce a high-quality bone marrow aspirate. This technique may help obtain specific populations of MSCs with the desired characteristics for use in regenerative therapies for musculoskeletal injuries.
Association of IDH1 Mutation and MGMT Promoter Methylation with Clinicopathological Parameters in an Ethnically Diverse Population of Adults with Gliomas in England
Authors: Wanis Hiba A. , Møller Henrik , Ashkan Keyoumars , Davies Elizabeth A.
Published: November 2024

Background: Molecular profiles can predict which patients will respond to current standard treatment and new targeted therapy regimens. Using data from a highly diverse population of approximately three million in Southeast London and Kent, this study aims to evaluate the prevalence of IDH1 mutation and MGMT promoter methylation in the gliomas diagnosed in adult patients and to explore correlations with patients’ demographic and clinicopathological characteristics. Methods: Anonymised data on 749 adult patients diagnosed with a glioma in 2015–2019 at King’s College Hospital were extracted. Univariable and multivariable logistic regressions were used to estimate odds ratios (ORs) for expressing IDH1 mutation and MGMT promoter methylation, based on each patient’s age, sex, ethnicity, histology, tumour location and extent of resection. The Kaplan–Meier method was used to estimate the overall survival functions. Results: A total of 19.5% of cases were IDH1-mutated. Being 39 years and younger (OR 5.48, 95% CI 3.17–9.47), from Asian/Asian British background (OR 3.68, 95% CI 1.05–12.97), having MGMT methylation (OR 15.92, 95% CI 7.30–34.75), an oligodendroglioma diagnosis (OR 7.45, 95% CI 2.90–19.13) and receiving a gross total/total microscopic resection (OR 1.95, 95% CI 1.24–3.08) were each univariately correlated with IDH1 mutation. MGMT methylation association persisted on adjustment (OR 14.13, 95% CI 3.88–51.43). MGMT promoter methylation was seen in 54.3% of gliomas. In the univariate adjusted ORs, being younger than 39 years (OR 2.56, 95% CI 1.48–4.43), female (OR 1.52, 95% CI 1.11–2.08), having IDH1 mutation (OR 15.92, 95% CI 7.30–34.75) and an oligodendroglioma diagnosis (OR 6.20, 95% CI 1.33–28.88) were associated with MGMT methylation. Being female (OR 1.75, 95% CI 1.22–2.51) and having an IDH1 mutation (OR 15.54, 95% CI 4.73–51.05) persisted after adjustment for age, sex, ethnicity, histology, tumour location and extent of resection. IDH1 mutant and MGMT methylated gliomas were associated with frontal lobe location. Survival analysis showed that patients with both IDH1 mutation and MGMT methylation had significantly better survival than those with either molecular marker alone. Over a 3-year period, women with unmethylated MGMT promoters generally had better survival than men with unmethylated MGMT. Conclusion: This study showed that the molecular markers of IDH1 mutation and MGMT promoter methylation were associated with age, sex, Asian/Asian British ethnic group, tumour histology, anatomical location and extent of resection. This study has demonstrated the importance of assessing glioma molecular markers in the clinical setting and the need to stratify patients according to their clinicopathological characteristics.
Genetic Variation in Targets of Antidiabetic Drugs and Amyotrophic Lateral Sclerosis Risk
Authors: Wan Mengxia , Zhang Linjing , Huo Junyan , Fu Yu , Huang Tao , Fan Dongsheng
Published: November 2024

Background: Previous studies have suggested that antidiabetic drug use may be associated with amyotrophic lateral sclerosis. However, these studies are limited by many confounding and reverse causality biases. We aimed to determine whether antidiabetic drug use has causal effects on ALS. Methods: Drug-target Mendelian randomization analysis was conducted to evaluate the association between genetic variation in the targets of antidiabetic drugs and ALS risk. The antidiabetic drugs included sulfonylureas, GLP-1 analogues, thiazolidinediones, insulin/insulin analogues, metformin, and SGLT2 inhibitors. Summary statistics for ALS were retrieved from previous genome-wide association studies comprising 27,205 ALS patients and 55,058 controls. The instrumental variables for these drugs are from previous published articles. Results: Genetic variation in SGLT2 inhibition targets was associated with lower risk of ALS (odds ratio [OR] = 0.32, 95% CI = 0.14–0.74; p = 0.008). We did not find that genetic variation in metformin targets was associated with ALS (OR = 1.61, 95% CI = 0.94–2.73; p = 0.081). Nevertheless, mitochondrial complex I, a target of metformin, was associated with a higher risk of ALS (OR = 1.83, 95% CI = 1.01–3.32; p = 0.047). The analysis showed that genetic variation in sulfonylureas, GLP-1 analogues, thiazolidinediones, insulin or insulin analogues targets was not associated with ALS (all p > 0.05). Conclusions: The complex interaction between hypoglycemic, antioxidation, and anti-inflammatory effects may account for the different results across antidiabetic drug types. These findings provide key evidence to guide the use of antidiabetic drugs and will help to identify novel therapeutic targets in ALS.
Genetic Heterogeneity in Four Probands Reveals HGSNAT, KDM6B, LMNA and WFS1 Related Neurodevelopmental Disorders
Authors: Mudassir Behjat Ul , Mudassir Mujaddid , Williams Jamal B. , Agha Zehra
Published: November 2024

Background: Neurodevelopmental disorders of genetic etiology are a highly diverse set of congenital recurrent complications triggered by irregularities in the basic tenets of brain development. Methods: We present whole exome sequencing analysis and expression characteristics of the probands from four unrelated Pakistani consanguineous families with facial dysmorphism, neurodevelopmental, ophthalmic, auditory, verbal, psychiatric, behavioral, dental, and skeletal manifestations otherwise unexplained by clinical spectrum. Results: Whole exome sequencing identifies a novel, bi-allelic, missense variant in the HGSNAT gene [NM_152419.3: c.1411G > A (p. Glu471Lys) exon 14] for proband family E-1 and a rare, bi-allelic, non-frameshift variant in the KDM6B gene [NM_001348716.2: c.786_791dupACCACC (p. Pro263_Pro264dup) exon 10] for proband family E-2, and a novel, mono-allelic, missense variant in the LMNA gene [NM_170707.4: c. 1328 A > G (p. Glu443Gly) exon 8] for proband family E-3 and an ultra-rare, mono-allelic, missense variant in the WFS1 gene [NM_006005.3: c.2131G > A (p. Asp711Asn) exon 8] for proband family E-4. Protein modelling shows conformation and size modifications in mutated residues causing damage to the conserved domains expressed as neurocognitive pathology. Conclusions: The current study broadens the distinctly cultural and genetically inbred pool of the Pakistani population for harmful mutations, contributing to the ever-expanding phenotypic palette. The greatest aspirations are molecular genetic profiling and personalized treatment for individuals with complex neurological symptoms to improve their life activities.
Revolutionizing Epithelial Differentiability Analysis in Small Airway-on-a-Chip Models Using Label-Free Imaging and Computational Techniques
Authors: Chen Shiue-Luen , Xie Ren-Hao , Chen Chong-You , Yang Jia-Wei , Hsieh Kuan-Yu , Liu Xin-Yi , Xin Jia-Yi , Kung Ching-Kai , Chung Johnson H. Y. , Chen Guan-Yu
Published: November 2024

Organ-on-a-chip (OOC) devices mimic human organs, which can be used for many different applications, including drug development, environmental toxicology, disease models, and physiological assessment. Image data acquisition and analysis from these chips are crucial for advancing research in the field. In this study, we propose a label-free morphology imaging platform compatible with the small airway-on-a-chip system. By integrating deep learning and image recognition techniques, we aim to analyze the differentiability of human small airway epithelial cells (HSAECs). Utilizing cell imaging on day 3 of culture, our approach accurately predicts the differentiability of HSAECs after 4 weeks of incubation. This breakthrough significantly enhances the efficiency and stability of establishing small airway-on-a-chip models. To further enhance our analysis capabilities, we have developed a customized MATLAB program capable of automatically processing ciliated cell beating images and calculating the beating frequency. This program enables continuous monitoring of ciliary beating activity. Additionally, we have introduced an automated fluorescent particle tracking system to evaluate the integrity of mucociliary clearance and validate the accuracy of our deep learning predictions. The integration of deep learning, label-free imaging, and advanced image analysis techniques represents a significant advancement in the fields of drug testing and physiological assessment. This innovative approach offers unprecedented insights into the functioning of the small airway epithelium, empowering researchers with a powerful tool to study respiratory physiology and develop targeted interventions.
What Factors Affect Binocular Summation?
Authors: Yassin Marzouk , Lev Maria , Polat Uri
Published: November 2024

Binocular vision may serve as a good model for research on awareness. Binocular summation (BS) can be defined as the superiority of binocular over monocular visual performance. Early studies of BS found an improvement of a factor of about 1.4 (empirically), leading to models suggesting a quadratic summation of the two monocular inputs (√2). Neural interaction modulates a target’s visibility within the same eye or between eyes (facilitation or suppression). Recent results indicated that at a closely flanked stimulus, BS is characterized by instability; it relies on the specific order in which the stimulus condition is displayed. Otherwise, BS is stable. These results were revealed in experiments where the tested eye was open, whereas the other eye was occluded (mono-optic glasses, blocked presentation); thus, the participants were aware of the tested eye. Therefore, in this study, we repeated the same experiments but utilized stereoscopic glasses (intermixed at random presentation) to control the monocular and binocular vision, thus potentially eliminating awareness of the tested condition. The stimuli consisted of a central vertically oriented Gabor target and high-contrast Gabor flankers positioned in two configurations (orthogonal or collinear) with target–flanker separations of either two or three wavelengths (λ), presented at four different presentation times (40, 80, 120, and 200 ms). The results indicate that when utilizing stereoscopic glasses and mixing the testing conditions, the BS is normal, raising the possibility that awareness may be involved.
Pediatric Fibrous Dysplasia of the Skull Base: Update on Management and Treatment
Authors: Spencer Pierce , Raturi Vidhatri , Watters Amanda , Tubbs R. Shane
Published: November 2024

Background: Fibrous dysplasia (FD) is often difficult for skull base surgeons to address. FD arises due to the abnormal proliferation of fibroblasts, ultimately resulting in immature osseous tissue replacing normal cancellous bone. When the skull base is involved, it can result in cranial nerve compression. FD affecting the optic canal and optic nerve is the most concerning as new onset of vision loss is considered a surgical emergency. The prevalence of FD is approximately 3.6 per 1,000,000. The most severe implications of this disease are neurological deficits due to cranial nerve compression, cosmetic appearance, and high recurrence rates even in the setting of surgical and medical therapy interventions. Methods: A PubMed search of “pediatric fibrous dysplasia management” using MESH Terms was conducted. Articles were excluded for non-English languages, inaccessibility, and events/erratum/letters to the editor. Included articles were in English, as well as encompassed pediatric FD case reports or comprehensive reviews of FD that discussed pediatric presentations. Results: A total of 109 articles were reviewed, and 44 were included in the final review. Most articles were case reports. There is a clear need for guidelines regarding surgical intervention, especially in the pediatric population, where hormonal fluctuation can influence rates of recurrence and bony deformity. Overall, most surgeons recommend close observation with biomarkers and radiographic imaging for asymptomatic patients until at least the age of 16 years old. Conservative methods, such as RANK-L inhibitors, can be utilized to decrease growth with some success, especially in older adolescents. Conclusion: This review is an update on this disease and its presentations, imaging findings, and treatment options. The current literature lacks clear guidance on management, especially in regard to surgical intervention or recurrence monitoring algorithms.
Adaptation and Validation of the Multidimensional Fairness Scale in Chilean University Students
Authors: Cea-Leiva Fredy , Dominguez-Lara Sergio , Salvo-Garrido Sonia
Published: November 2024

The Multidimensional Fairness Scale (MFS) assesses an individual’s experience of fairness across the many contexts of daily life. It has been applied in the USA; however, the psychometric qualities of reliability and validity have not been examined in a Spanish-speaking population or among Chilean university students. A cross-sectional study was conducted on 377 university students to explore these properties. Students from public (46.2%) and private (53.8%) universities participated, with a mean age = 21.5 (SD = 3.3). CFA was performed, showing good goodness-of-fit indices (RMSEA = 0.08; CFI = 0.97; TLI = 0.96) for the model of three related factors (interpersonal, occupational, and societal) and good reliability indices. Although changes were made to the original structure, the tested model was consistent with the theoretical structure of the MFS, which allows its use on the Chilean university population.
Safety Status Prediction Model of Transmission Tower Based on Improved Coati Optimization-Based Support Vector Machine
Authors: Gong Xinxi , Zhu Yaozhong , Wang Yanhai , Li Enyang , Zhang Yuhao , Zhang Zilong
Published: November 2024

Natural calamities have historically impacted operational mountainous power transmission towers, including high winds and ice accumulation, which can result in pole damage or diminished load-bearing capability, compromising their structural integrity. Consequently, developing a safety state prediction model for transmission towers may efficiently monitor and evaluate potential risks, providing early warnings of structural dangers and diminishing the likelihood of bending or collapse incidents. This paper presents a safety state prediction model for transmission towers utilizing improved coati optimization-based SVM (ICOA-SVM). Initially, we optimize the coati optimization algorithm (COA) through inverse refraction learning and Levy flight strategy. Subsequently, we employ the improved coati optimization algorithm (ICOA) to refine the penalty parameters and kernel function of the support vector machine (SVM), thereby developing the safety state prediction model for the transmission tower. A finite element model is created to simulate the dynamic reaction of the transmission tower under varying wind angles and loads; ultimately, wind speed, wind angle, and ice cover thickness are utilized as inputs to the model, with the safe condition of the transmission tower being the output. The predictive outcomes indicate that the proposed ICOA-SVM model exhibits rapid convergence and high prediction accuracy, with a 62.5% reduction in root mean square error, a 59.6% decrease in average relative error, and a 75.0% decline in average absolute error compared to the conventional support vector machine. This work establishes a scientific foundation for the safety monitoring and maintenance of transmission towers, effectively identifying possible dangers and substantially decreasing the likelihood of accidents.
A State-of-the-Art Review and Bibliometric Analysis on the Smart Preservation of Heritages
Authors: Shehata Alaa O. , Noroozinejad Farsangi Ehsan , Mirjalili Seyedali , Yang T. Y.
Published: November 2024

The preservation of heritage buildings is a crucial endeavour for countries worldwide. This study presents a comprehensive bibliometric analysis of the latest trends in smart applications for heritage building preservation within the context of Industry 4.0 and Industry 5.0, covering the period of 2020–2024. A total of 216 peer-reviewed journal articles obtained from the Scopus database were subjected to analysis using RStudio and VOSviewer. The methodology was based on a dual analysis, including surface-level examination and in-depth exploration. Consequently, a new conceptual framework is presented for achieving smart preservation of heritages. It is structured based on two pillars: the physical methods pillar, including smart devices and smart processes, and the digital methods pillar, involving smart technologies and environments. Also, the results revealed that the dominant portion of literature publications (61%) emphasize specific topics such as interoperability, monitoring, data management, and documentation. However, training and community engagement represent an insufficient fraction (2–6%), and more research is needed in the future. This paper concludes by discussing a future innovative vision for policy and industry through urging policymakers to promote interoperability standards; address data security; and fund innovative, low-cost technologies, as well as advocating the industry sectors for public engagement, sustainable preservation, and prioritizing skill development programs and workforce.
Multiple Water and Sand Leakage Model Tests for Shield Tunnels
Authors: Greene Emmet Amonee , Zheng Gang , Cheng Xuesong , Zhaolin Cui
Published: November 2024

Water and sand leakage in shield tunnels has become more of a research interest in recent years. On the other hand, accidents involving underground engineering can take many forms and occur often. These accidents pose a risk to people’s lives as well as their property, and it is imperative that studies on underground engineering catastrophes be conducted without delay. In this paper, a technique for indoor model tests for disaster and erosion in shield tunnels is utilized to investigate the process of crater, water, and sand leakage evolution in shield tunnels. The change in water pressure at the leaking joint is inversely proportional to the magnitude of the water input rate, and the change in soil pressure is inversely proportional to the distance from the leakage joint. Both changes occurred in the same direction. Notably, the soil’s initial effective stress was also considered to maintain compatibility with actual engineering works. The preliminary findings suggest that soil-effective stress may cause erosion resulting in the soil arching effect. Tests with one and two leakage spots were carried out using this foundation. Compared to the scenario where two leakage sites are opened simultaneously, it was discovered that opening the two leakage points one after the other might result in a more extensive erosion area of superposition. The double leakage point test results indicate that the point where leakage occurs first causes another leakage point because the erosion area created when two leakage points are opened successively will be larger than the erosion area created when two leakage points are opened simultaneously. When two leakage points under a tunnel are close to each other, the width and depth of the soil erosion groove under the tunnel caused by the two leakage points leaking one after another are significantly larger than those caused by two leakage points leaking simultaneously and are also substantially larger than a single leakage point. After a leakage disaster occurs in the tunnel, the water and soil pressure near the leakage point will continue to decrease. The closer the leakage point, the greater the reduction. Until the leakage erosion converges, the water and soil pressure will tend to stabilize.
Environmental Impact of Earthquake-Resistant Design: A Sustainable Approach to Structural Response in High Seismic Risk Regions
Authors: Bohorquez Alvaro , Viteri Esteban , Rivera Edgar , Avila Carlos
Published: November 2024

This study evaluates the environmental impact of earthquake-resistant structural design choices in high-risk seismic regions through life cycle assessment. As climate change concerns intensify, understanding the environmental implications of structural design decisions becomes crucial for sustainable construction. Examining a building in Quito, Ecuador, the research compares three structural systems: Optimized Framed System (OFS), Optimized Dual System (ODS), and Equivalent Framed System (EFS). The assessment quantifies emissions through a ‘cradle to gate’ approach, encompassing materials fabrication, transportation, and construction processes. The results demonstrate that the ODS achieves optimal seismic performance equal to the EFS while reducing emissions by 38%, with only 5% higher emissions than the OFS. The findings establish that effective earthquake-resistant design can simultaneously achieve structural resilience and environmental sustainability, providing valuable insights for sustainable structural engineering practices in seismic regions.
Optimising Ventilation Strategies Based on Predicted Mean Vote and Indoor CO2 Concentration: A Case Study of University Teaching Spaces in Cold Region of China
Authors: Yu Jiahui , Wang Hongnan , Sui Yige , Xu Yitong , Chen Yang
Published: November 2024

Background: Educational spaces, which represent a vital setting for students’ learning activities, significantly influence both learning efficiency and physiological health. As university teaching spaces are characterised by high occupancy density and prolonged occupancy, it is vital to address the problem of elevated CO2 concentrations in these spaces. Although effective ventilation design can improve indoor air quality, the relatively short ventilation periods in cold regions of China, driven by winter insulation requirements, often lead to substandard indoor air quality. Purpose: Based on predicted mean vote (PMV), this study explored the effect of natural ventilation on indoor CO2 concentration during the transition season in cold regions and proposed reasonable optimization strategies. Method: Through the method of combination of measurement and simulation, an effective design method of doors and Windows and an intermittent ventilation strategy for improving the indoor environment quality of teaching space in universities in cold regions of China are put forward. Result: The results revealed that indoor CO2 concentrations exceeded the standard limit of 1000 ppm for the majority of the periods studied. Peak indoor CO2 concentrations reached 1970 ppm, 2751 ppm, and 3200 ppm in large-, medium-, and small-sized classrooms, respectively. The duration of exceeding CO2 concentration accounted for the highest proportion of class time, which were 89%, 93%, and 88%, respectively. Furthermore, optimisation of door and window design and ventilation methods was carried out for a representative medium-sized classroom. The simulation results indicated that while maintaining indoor comfort (−0.5 < PMV < 0.5), peak indoor CO2 concentrations during class periods decreased from 2551 ppm to 1149 ppm, and the proportion of time for which CO2 concentrations exceeded standards decreased from 87% to 47%. Conclusions: This study suggests that relevant codes and standards should be refined for the relationship between indoor CO2 concentration and thermal comfort, and that designers should provide suggestions for suitable door and window design and ventilation strategies to improve indoor air quality in educational spaces in cold regions of China.
Sustainability Certifications in Real Estate: Value and Perception
Authors: Marques António , Januário João Fragoso , Cruz Carlos Oliveira
Published: November 2024

This study examines the influence of sustainability certifications on the real estate market, particularly highlighting the advantages they offer compared to uncertified buildings and their recognition within the industry. A survey targeting various industry professionals garnered ninety responses, predominantly from the real estate sector. The survey explored the respondents’ awareness and perceived benefits of sustainability certifications, their priority areas within sustainability, and the relevance of these certifications across different real estate sectors. The analysis also compared the additional costs and operational savings of certified versus uncertified buildings. Among the certifications, LEED and BREEAM were the most recognized. The primary benefits associated with these certifications included enhanced corporate image, improved health and well-being, increased building value, and higher rental yields. We estimated a valuation and rent premium for certified buildings, noting that these premiums were more pronounced among respondents who were younger, had less professional experience, and were from the property sector. The office market was identified as the segment placing the highest importance on sustainability certifications. Additionally, the LiderA evaluation system’s weighting closely aligned with the respondents’ sustainability priorities. This study concludes that while sustainability certifications incur a cost premium, this is outweighed by the appreciation in building value, rental advantages, and operational cost savings.
Optimization of Single-Layer Reticulate Shell Assembly Sequence Using Deep Reinforcement Learning Graph Embedding Method
Authors: Wu Hongyu , Wu Yuching , Zhu Peng , Zhi Peng , Qi Cheng
Published: November 2024

This study explores reinforcement learning algorithms combined with graph embedding methods to optimize the assembly sequence of complex single-layer reticulate shells. To minimize the number of temporary support brackets during installation, the structural assembly process is modeled using the inverse dismantling process. The remaining members of the structure at each iteration step are scored, and the one with the highest score for removal is selected. Next, this study trains an effective intelligent agent to assemble the structure. The proposed method can be used to design several types of latticed shells. The trained intelligent model can complete the assembly sequence design of the mesh shell without requiring any other data except for previous structural information. To verify the feasibility of the novel method, it is compared with the empirical approach used in the traditional assembly sequence design process. The feasibility of the new method is demonstrated. It is indicated that the novel method can obtain the optimal solution accurately and efficiently. In addition, it has more innovative choices for installation sequences than the conventional technique. It has enormous potential and application in the civil engineering field.
Length Optimization of MEP Pipeline Integrated Modular Based on Genetic Algorithm
Authors: Zhao Xuefeng , Yang Qiantai , Yan Gangwen , Fan Xiongtao , Yang Yinghui , Zhang Huizhong , Chen Song
Published: November 2024

This study aims to optimize the length partitioning of modular MEP systems in building construction using a genetic algorithm, addressing challenges such as avoiding fittings (e.g., tees and crosses) and achieving standardized module lengths. To this end, this paper proposes an optimization method utilizing the customization of Revit 2021. The method comprehensively considers factors such as the location of pipe fittings, module length, production, transportation, and installation, achieving a more systematic partitioning of modules. The results show that the optimized partitioning scheme effectively avoids critical pipe fittings, and the optimized module lengths are comparable to those created manually. However, the optimized scheme includes more standardized segments, which is conducive to factory-standardized production. Additionally, cost analysis reveals that production and transportation costs account for a significant proportion of total costs, while lifting costs are relatively low. Furthermore, the presence of modules with non-standard lengths introduces corresponding penalty costs. This paper discusses the advantages and limitations of the proposed method and suggests future directions for further optimizing the algorithm and improving module partitioning. The novelty of this research lies in the integration of a genetic algorithm with BIM software to optimize MEP module partitioning, offering a more efficient and systematic approach to the modular construction process.
Ventilation Optimization Based on Spatial-Temporal Distribution and Removal Efficiency of Patient-Exhaled Pollutants in Hospital Wards During the Post-Epidemic Period
Authors: Chen Min , Wang Qingyu
Published: November 2024

Given the potential risks of unknown and emerging infectious respiratory diseases, prioritizing an appropriate ventilation strategy is crucial for controlling aerosol droplet dispersion and mitigating cross-infection in hospital wards during post-epidemic periods. This study optimizes the layout of supply diffusers and exhaust outlets in a typical two-bed ward, employing a downward-supply and bottom-exhaust airflow pattern. Beyond ventilation, implementing strict infection control protocols is crucial, including regular disinfection of high-touch surfaces. CO2 serves as a surrogate for exhaled gaseous pollutants, and a species transport model is utilized to investigate the airflow field under various configurations of vents. Comparisons of CO2 concentrations at the respiratory planes of patients, accompanying staff (AS), and healthcare workers (HCWs) across nine cases are reported. A discrete phase model (DPM) is employed to simulate the spatial-temporal dispersion characteristics of four different particle sizes (3 μm, 12 μm, 20 μm, and 45 μm) exhaled by the infected patient (Patient 1) over 300 s. Ventilation effectiveness is evaluated using indicators like contaminant removal efficiency (CRE), suspension rate (SR), deposition rate (DER), and removal rate (RR) of aerosol droplets. The results indicate that Case 9 exhibits the highest CRE across all respiratory planes, indicating the most effective removal of gaseous pollutants. Case 2 shows the highest RR at 50.3%, followed by Case 1 with 40.4%. However, in Case 2, a significant portion of aerosol droplets diffuse towards Patient 2, potentially increasing the cross-infection risk. Balancing patient safety with pollutant removal efficacy, Case 1 performs best in the removal of aerosol droplets. The findings offer novel insights for the practical implementation of ventilation strategies in hospital wards, ensuring personnel health and safety during the post-epidemic period.