bluuebunny/crossref_metadata_2025 huggingface dataset:
On Efficiency of Two-Degree-of-Freedom Galloping Energy Harvesters with Two Transducers
Authors: Sarbinowski Filip , Starosta Roman
Published: June 2024

This paper examines the energy efficiency of three variations of the two-degree-of-freedom transverse galloping energy harvester. These variants differ in the number and placement of electromechanical transducers. By utilizing the harmonic balance method, the limit cycles of mathematical models of the devices were determined. Analytical expressions derived from the models were then used to formulate the efficiency of the systems. It was demonstrated that efficiency depends on flow speed and can be comprehensively characterized by the following criteria parameters: peak efficiency, denoting the maximum efficiency of the system, and high-efficiency bandwidth, which describes the range of flow speeds within which the efficiency remains at no less than 90% of peak efficiency. The values of these parameters are heavily reliant on two other parameters: the speed at which the system achieves peak efficiency, referred to as the nominal speed, and also the flow speed at which the system undergoes Hopf bifurcation, namely the critical speed. Comparative analysis revealed that only the device equipped with two electromechanical transducers can potentially outperform a simple one-degree-of-freedom system. For selected parameters, this gain reached nearly 10%.
Investigation into the Time-Dependent Characteristics of Stress and Deformation of Weak Surrounding Rock and Lining Structure in Operational Tunnels: Model Test
Authors: Wang Pai , Ma Xujin , Yang Lei , Sheng Xiangchao , Wang Xiaolong , Lin Chunjin
Published: June 2024

During the long-term operation of tunnels, surrounding rock undergoes creep effects under environmental loads, resulting in changes in the aging evolution model of stress and deformation in surrounding rock and lining, which affects the long-term operational safety of the tunnel. Therefore, using the model test device for time-dependent characteristics of stress and deformation of weak surrounding rock and lining structure in operational tunnels, taking into account the influence of tunnel burial depth and lateral pressure coefficient of surrounding rock, a model test on time-dependent characteristics of stress and deformation in weak surrounding rock and lining structure was conducted, and the stress and deformation time-varying curves at key locations of surrounding rock and lining were obtained. The time characteristics of surrounding rock stress, the contact force between surrounding rock and lining, internal force, and displacement of lining structure were analyzed. Research findings indicate that the stress of surrounding rock, the internal force and displacement of lining structure, and the contact force between surrounding rock and lining all increase and tend to be stable over time under constant load. This implies that the stress and deformation of the surrounding rock and lining structure exhibit time-dependent changes. With changes in burial depth and lateral pressure coefficient, significant variations are observed in the various indicators of stress and deformation in the surrounding rock and lining structure, indicating both time-dependent and long-term characteristics in terms of stress and deformation. The research results provide basic data support for the study of the time-dependent characteristics of stress and deformation between weak surrounding rock and lining structures in operational tunnels and can provide theoretical and technical guidance for the long-term service status discrimination and disaster prevention and control of operational tunnels.
A Simplified Theoretical Method for Estimating the Effect of Capsule Grouting Expansion Technology on Controlling Pile Deformation
Authors: Yu Jianlin , Guo Jin , Zhou Jiajin , Hu Haibo , Gong Xiaonan
Published: June 2024

Deep excavation and shield tunneling processes often induce significant deformation in adjacent existing pile foundations, posing risks to the safety of superstructures. To address this issue, capsule grouting expansion technology has emerged as an efficient and economical technology to actively control pile deformation during such construction activities. This technology has been applied in some engineering projects aimed at safeguarding nearby buildings or facilities. However, theoretical research on capsule grouting expansion technology is limited and lags behind its practical engineering application. This paper proposed a simplified theoretical approach for estimating the effect of capsule grouting expansion technology on the deformation of neighboring pile foundations. Initially, virtual image technology was employed to obtain an analytical solution for the lateral displacement of soil resulting from the expansion of a cylindrical cavity with infinite height. The pile was considered as an Euler–Bernoulli beam on a Winkler foundation, allowing for the calculation of the loading response of the existing pile foundation. Utilizing the two-stage method, the theoretical analytical method of the lateral deformation of the pile shaft caused by capsule expansion was obtained. The reliability of the proposed theoretical method was verified by comparing the measured and calculated results. Further investigation into the controlling effect of the capsule grouting expansion technology on the deformation of the pile foundation was conducted through parametric analyses. These analyses encompass capsule radius, the distance between the capsule and pile foundation, the depth of the capsule, the length of the capsule, and the pile base constraints.
A Comparative Analysis for Optimizing Machine Learning Model Deployment in IoT Devices
Authors: Sayeedi Md. Faiyaz Abdullah , Deepti Jannatul Ferdous , Osmani Anas Mohammad Ishfaqul Muktadir , Rahman Taimur , Islam Safrin Sanzida , Islam Md. Motaharul
Published: June 2024

In the intersection of the Internet of Things (IoT) and Machine Learning (ML), the choice between high-level and low-level programming libraries presents a significant dilemma for developers, impacting not only the efficiency and effectiveness of ML models but also their environmental footprint. We have proposed a comprehensive framework to aid in this decision-making process, underpinned by a detailed comparative analysis of both types of libraries on one of the key IoT ML tasks: image classification. We have introduced a novel algorithm designed to calculate the green footprint of ML model training, factoring in execution time, memory utilization, power consumption, and CPU temperature, addressing the urgent need for sustainable ML practices. Through an empirical evaluation of popular libraries such as PyTorch for high-level and Libtorch for low-level development, we have assessed their performance, development efficiency, and hardware compatibility. The culmination of our research is a decision support system that synthesizes the experimental findings to guide developers toward choices that harmonize model performance with environmental sustainability.
On the Lock-In Phenomena near the Transonic Buffet Onset of a Prescribed Pitching Airfoil
Authors: Wei Lianyi , Zheng Guannan , Lu Weishuang , Zhang Yuchen , Yang Guowei
Published: June 2024

The limit cycle oscillation (LCO) in the transonic buffet on the fixed supercritical airfoil OAT15A under Ma = 0.73, AoA = 3.5° and Re≈3×106, is successfully simulated by means of the Reynolds Stress Model. Further, the buffet lock-in phenomena under prescribed pitch conditions near the buffet onset are also studied by evaluating the modified energy exchange based on the pitching component of the moment coefficients as well as the normalized relative phase map between the pitching component of the moment coefficients and the airfoil’s angular velocity. The zero energy transfer branches in the modified energy map fail to indicate the lock-in boundaries, while the normalized phase map generally outlines the lock-in boundaries for small pitch amplitudes near the buffet onset, which suggests that the lock-in occurs where the moment is in phase with the angular velocity at small pitch amplitudes near the buffet onset. For pitch amplitudes larger than 0.4°, the lock-in onset deviates from the phase shift, possibly due to the fact the instantaneous angle of attack can be lower than the buffet onset where the buffet phenomena may vanish.
Object–Environment Fusion of Visual System for Automatic Pear Picking
Authors: Liu Yuxing , Ying Na , Guo Chunsheng
Published: June 2024

A visual system is a key tool for automatic fruit harvesting. It faces the challenges of varied occlusion and illumination in the field, resulting in difficulties in fruit recognition and picking. At present, there are many studies that lack a comprehensive analysis of the impact of the environment on harvesting. This study proposes an object–environment fusion visual system. It comprises modules for object perception, environment perception, and picking pose estimation. The object perception module aims to identify and locate pears. The environment perception module is deployed to analyze the three-dimensional (3D) information of objects and obstacles. Finally, the picking pose estimation module fuses the information of the objects and environment to calculate the collision-free picking position and orientation. Additionally, specific implementations are employed for each module. It compares three networks to identify pears for object perception. Voxel-based representation is used to simplify point clouds for environmental perception. A sampler and evaluator are applied for picking pose estimation. The S1 and S2 datasets were acquired in a laboratory pear tree model and the orchard of Zhejiang Academy of Agricultural Sciences, respectively, to evaluate the proposed method. In the S2 dataset, the success rate for picking pose estimation reached 87.11% within the distance range of 30∼50 cm. All of the results demonstrate that the proposed method can be applied to visual perception for automatic pear harvesting.
Predictive Modeling of Flight Delays at an Airport Using Machine Learning Methods
Authors: Hatıpoğlu Irmak , Tosun Ömür
Published: June 2024

Flight delays represent a significant challenge in the global aviation industry, resulting in substantial costs and a decline in passenger satisfaction. This study addresses the critical issue of predicting flight delays exceeding 15 min using machine learning techniques. The arrival delays at a Turkish airport are analyzed utilizing a novel dataset derived from airport operations. This research examines a range of machine learning models, including Logistic Regression, Naïve Bayes, Neural Networks, Random Forest, XGBoost, CatBoost, and LightGBM. To address the issue of imbalanced data, additional experiments are conducted using the Synthetic Minority Over-Sampling Technique (SMOTE), in conjunction with the incorporation of meteorological data. This multi-faceted approach ensures robust forecast performance under varying conditions. The SHAP (SHapley Additive exPlanations) method is employed to interpret the relative importance of features within the models. The study is based on a three-year period of flight data obtained from a Turkish airport. The dataset is sufficiently extensive and robust to provide a reliable foundation for analysis. The results indicate that XGBoost is the most proficient model for the dataset, demonstrating its potential to deliver highly accurate predictions with an accuracy of 80%. The impact of weather factors on the predictions is found to be insignificant in comparison to scenarios without weather data in this dataset.
CPF-UNet: A Dual-Path U-Net Structure for Semantic Segmentation of Panoramic Surround-View Images
Authors: Sun Qiqing , Qu Feng
Published: June 2024

In this study, we propose a dual-stream UNet neural network architecture design named CPF-UNet, specifically designed for efficient semantic pixel-level segmentation tasks. This architecture cleverly extends the basic structure of the original UNet, mainly through the addition of a unique attention-guided branch in the encoder part, aiming to enhance the model’s ability to comprehensively capture and deeply fuse contextual information. The uniqueness of CPF-UNet lies in its dual-path mechanism, which differs from the dense connectivity strategy adopted in networks such as UNet++. The dual-path structure in this study can effectively integrate deep and shallow features without relying excessively on dense connections, achieving a balanced processing of image details and overall semantic information. Experiments have shown that CPF-UNet not only slightly surpasses the segmentation accuracy of UNet++, but also significantly reduces the number of model parameters, thereby improving inference efficiency. We conducted a detailed comparative analysis, evaluating the performance of CPF-UNet against existing UNet++ and other corresponding methods on the same benchmark. The results indicate that CPF-UNet achieves a more ideal balance between accuracy and parameter quantity, two key performance indicators.
Impact Assessment of Nematode Infestation on Soybean Crop Production Using Aerial Multispectral Imagery and Machine Learning
Authors: Jjagwe Pius , Chandel Abhilash K. , Langston David B.
Published: June 2024

Accurate and prompt estimation of geospatial soybean yield (SY) is critical for the producers to determine key factors influencing crop growth for improved precision management decisions. This study aims to quantify the impacts of soybean cyst nematode (SCN) infestation on soybean production and the yield of susceptible and resistant seed varieties. Susceptible varieties showed lower yield and crop vigor recovery, and high SCN population (20 to 1080) compared to resistant varieties (SCN populations: 0 to 340). High-resolution (1.3 cm/pixel) aerial multispectral imagery showed the blue band reflectance (r = 0.58) and Green Normalized Difference Vegetation Index (GNDVI, r = −0.6) have the best correlation with the SCN populations. While GDNVI, Green Chlorophyll Index (GCI), and Normalized Difference Red Edge Index (NDRE) were the best differentiators of plant vigor and had the highest correlation with SY (r = 0.59–0.75). Reflectance (REF) and VIs were then used for SY estimation using two statistical and four machine learning (ML) models at 10 different train–test data split ratios (50:50–95:5). The ML models and train–test data split ratio had significant impacts on SY estimation accuracy. Random forest (RF) was the best and consistently performing model (r: 0.84–0.97, rRMSE: 8.72–20%), while a higher train–test split ratio lowered the performances of the ML models. The 95:5 train–test ratio showed the best performance across all the models, which may be a suitable ratio for modeling over smaller or medium-sized datasets. Such insights derived using high spatial resolution data can be utilized to implement precision crop protective operations for enhanced soybean yield and productivity.
Comparison of Emission Properties of Sustainable Aviation Fuels and Conventional Aviation Fuels: A Review
Authors: Song Zehua , Li Zekai , Liu Ziyu
Published: June 2024

In order to achieve the International Air Transport Association’s (IATA) goal of achieving net-zero emissions in the aviation industry by 2050, there has been a growing emphasis globally on the technological development and practical application of sustainable aviation fuels (SAFs). Discrepancies in feedstock and production processes result in differences in composition between SAFs and traditional aviation fuels, ultimately affecting the emission performance of the two types of fuel. This paper discusses the impact of CO2/NOx/SO2/CO/PM/UHC emissions from the aviation industry on the natural environment and human health by comparing the two types of fuel under the same conditions. Fuel combustion is a complex process in the combustor of an engine, which transfers chemical energy into heat energy. The completeness of combustion is related to the fuel properties, including spray, evaporation, and flammability. Therefore, engine performance is not only affected by fuel performance, but also interacts with engine structure and control laws. The CO2 emissions of SAFs differ significantly from traditional aviation fuels from a lifecycle analysis perspective, and most SAFs can reduce CO2 emissions by 41–89%. Compared with traditional aviation fuels, SAFs and blended fuels can significantly reduce SO2 and PM emissions. Pure Fischer–Tropsch hydroprocessed synthesized paraffinic kerosine (FT-SPK) can reduce SO2 and PM emissions by 92% and 70–95% respectively, owing to its extremely low sulfur and aromatic compound content. In contrast, the differences in NOx emissions between the two types of fuel are not significant, as their generation mechanisms largely stem from thermal drive and turbulent flow in the combustor, with emissions performance being correlated to power output and flame temperature profile in engine testing. CO and UHC emissions are related to engine operating conditions and the physical/chemical properties of the SAFs, with no significant upward or downward trend. Therefore, SAFs have significant advantages over conventional aviation fuels in terms of CO2, SO2, and PM emissions, and can effectively reduce the hazards of aviation to the environment and human health.
Robust Online Estimation of State of Health for Lithium-Ion Batteries Based on Capacities under Dynamical Operation Conditions
Authors: Wu Xiaoxuan , Chen Jian , Tang Hu , Xu Ke , Shao Mingding , Long Yu
Published: June 2024

Lithium-ion batteries, as the main energy storage component of electric vehicles (EVs), play a crucial role in ensuring the safe and reliable operation of the battery systems through monitoring their state of health (SOH). However, temperature variations and battery aging have significant impacts on the internal parameters of lithium-ion batteries, and these changes directly correlate with the accuracy of battery SOH estimation. To address these issues, this paper proposes an estimation method for lithium-ion battery SOH that considers the impact of temperature. The method begins with reconstructing a second-order hybrid equivalent circuit model for lithium-ion batteries, through which an adaptive update rate for battery model parameters is designed. On this basis, a nonlinear observer for battery states is introduced by integrating filters to estimate SOH. The proposed method considers the impact of capacity in the design of the parameter adaptive update rate, enabling the capacity to be dynamically adjusted based on the actual state of the batteries. This reduces the cumulative error in the SOC observer and improves the modeling accuracy of battery models. Experimental results demonstrate that the method proposed in this paper exhibits exceptional performance in SOH estimation under different temperature conditions. The mean absolute error for SOH estimation does not exceed 0.5%, and the root mean square error does not exceed 0.2%. This method can significantly improve the estimation accuracy of SOH, providing a more efficient and accurate solution for battery management systems in EVs.
Exploring Lithium-Ion Battery Degradation: A Concise Review of Critical Factors, Impacts, Data-Driven Degradation Estimation Techniques, and Sustainable Directions for Energy Storage Systems
Authors: Rahman Tuhibur , Alharbi Talal
Published: June 2024

Batteries play a crucial role in the domain of energy storage systems and electric vehicles by enabling energy resilience, promoting renewable integration, and driving the advancement of eco-friendly mobility. However, the degradation of batteries over time remains a significant challenge. This paper presents a comprehensive review aimed at investigating the intricate phenomenon of battery degradation within the realm of sustainable energy storage systems and electric vehicles (EVs). This review consolidates current knowledge on the diverse array of factors influencing battery degradation mechanisms, encompassing thermal stresses, cycling patterns, chemical reactions, and environmental conditions. The key degradation factors of lithium-ion batteries such as electrolyte breakdown, cycling, temperature, calendar aging, and depth of discharge are thoroughly discussed. Along with the key degradation factor, the impacts of these factors on lithium-ion batteries including capacity fade, reduction in energy density, increase in internal resistance, and reduction in overall efficiency have also been highlighted throughout the paper. Additionally, the data-driven approaches of battery degradation estimation have taken into consideration. Furthermore, this paper delves into the multifaceted impacts of battery degradation on the performance, longevity, and overall sustainability of energy storage systems and EVs. Finally, the main drawbacks, issues and challenges related to the lifespan of batteries are addressed. Recommendations, best practices, and future directions are also provided to overcome the battery degradation issues towards sustainable energy storage system.
Correlation between Melatonin and Colostral Regulatory T Cells in Giardia lamblia Infection
Authors: de Queiroz Adriele Ataides , França Eduardo Luzía , Gadenz Gabriella Regina Borges , Dalcin Letícia Damas Leão , Fujimori Mahmi , França Danielle Cristina Honorio , Gomes Maria Aparecida , Honorio-França Adenilda Cristina
Published: June 2024

Giardiasis is a parasitic disease caused by Giardia lamblia (G. lamblia) that affects people worldwide. Still, few studies report on the immunoregulatory effects of the biomolecules of colostrum during interactions with G. lamblia. This study aimed to assess the concentrations of melatonin and cortisol hormones, the percentage of Treg cells, and the levels of cytokines IL-10 and TGF-β in colostrum from mothers who tested positive for the parasite. This cross-sectional study analyzed colostrum samples from 25 puerperal. The samples were tested using an ELISA to determine if they were seropositive for G. lamblia and the type of antibody present (IgM and IgG). Based on the results, the samples were divided into three groups: a control group (N = 10) with no reaction to either IgM or IgG, a group seropositive for IgG (IgG+/IgM−; N = 8), and a group seropositive for IgM (IgM+/IgG−; N = 7). The concentrations of melatonin and cortisol were measured using the ELISA method. Additionally, cytokines IL-10 and TGF-β and immunophenotyping were analyzed using flow cytometry. In the group that tested positive for IgM anti-G. lamblia, the concentration of melatonin was lower. However, in the colostrum from mothers who tested positive for IgG anti-G. lamblia, the level of this hormone had increased. The cortisol levels were similar between the groups, regardless of seropositivity. There was a higher percentage of Treg cells in the colostrum from mothers who tested positive for IgM anti-G. lamblia. TGF-β levels also increased in the colostrum of mothers who tested positive for IgM anti-G. lamblia. In the seronegative group for G. lamblia, there was a positive correlation between melatonin concentration and the percentage of Treg cells. These data suggest that the increase in regulatory cells and cytokines and the reduction in melatonin in colostrum from mothers with recent giardia infection may contribute to the evolution and manifestation of the disease.
Bridging the Gap in Cancer Research: Sulfur Metabolism of Leukemic Cells with a Focus on L-Cysteine Metabolism and Hydrogen Sulfide-Producing Enzymes
Authors: Kaleta Konrad , Janik Klaudia , Rydz Leszek , Wróbel Maria , Jurkowska Halina
Published: June 2024

Leukemias are cancers of the blood-forming system, representing a significant challenge in medical science. The development of leukemia cells involves substantial disturbances within the cellular machinery, offering hope in the search for effective selective treatments that could improve the 5-year survival rate. Consequently, the pathophysiological processes within leukemia cells are the focus of critical research. Enzymes such as cystathionine beta-synthase and sulfurtransferases like thiosulfate sulfurtransferase, 3-mercaptopyruvate sulfurtransferase, and cystathionine gamma-lyase play a vital role in cellular sulfur metabolism. These enzymes are essential to maintaining cellular homeostasis, providing robust antioxidant defenses, and supporting cell division. Numerous studies have demonstrated that cancerous processes can alter the expression and activity of these enzymes, uncovering potential vulnerabilities or molecular targets for cancer therapy. Recent laboratory research has indicated that certain leukemia cell lines may exhibit significant changes in the expression patterns of these enzymes. Analysis of the scientific literature and online datasets has confirmed variations in sulfur enzyme function in specific leukemic cell lines compared to normal leukocytes. This comprehensive review collects and analyzes available information on sulfur enzymes in normal and leukemic cell lines, providing valuable insights and identifying new research pathways in this field.
Longitudinal Genome-Wide Association Study of Cognitive Impairment after Subarachnoid Hemorrhage
Authors: Hong Eun Pyo , Lim Seung Hyuk , Youn Dong Hyuk , Han Sung Woo , Jung Harry , Lee Jae Jun , Jeon Jin Pyeong ,   on behalf of the First Korean Stroke Genetics Association Research (The FirstKSGAR) Study
Published: June 2024

Objectives: The occurrence of cognitive deficits after subarachnoid hemorrhage (SAH) is highly possible, leading to vascular dementia. We performed a novel longitudinal genome-wide association study (GWAS) to identify genetic modifications associated with cognitive impairment following SAH in a long-term prospective cohort study. Materials and Methods: This GWAS involved 153 patients with SAH sharing 5,971,372 markers after high-throughput imputation. Genome-wide Cox proportional hazard regression testing was performed to estimate the hazard ratio (HR) and 95% confidence interval (CI). Subsequently, a weighted polygenetic risk score (wPRS) was determined, based on GWAS-driven loci and risk stratification. Results: Cognitive impairment was observed in 65 patients (42.5%) during a mean follow-up of 37.7 ± 12.4 months. Five genome-wide signals, including rs138753053 (PDCD6IP-LOC101928135, HR = 28.33, p = 3.4 × 10−8), rs56823384 (LINC00499, HR = 12.47, p = 2.8 × 10−9), rs145397166 (CASC15, HR = 11.16, p = 1.7 × 10−8), rs10503670 (LPL-SLC18A1, HR = 2.88, p = 4.0 × 10−8), and rs76507772 (IRS2, HR = 5.99, p = 3.5 × 10−8), were significantly associated with cognitive impairment following SAH. In addition, the well-constructed wPRS containing five markers showed nominal ability to predict cognitive impairment (AUROC = 0.745, 95% CI: 0.667–0.824). Tertile stratification showed a higher effectiveness in predicting cognitive impairment, especially in those with haptoglobin 2-1 (HR = 44.59, 95% CI: 8.61–231.08). Conclusions: Our study revealed novel susceptible loci for cognitive impairment, longitudinally measured in patients with SAH. The clinical utility of these loci will be evaluated in further follow-up studies.
Spontaneous Bacterial Peritonitis: A Rare Complication of Pulmonary Arterial Hypertension
Authors: Beckmann Taylor , Pavlatos Nicholas , Kalra Dinesh K.
Published: June 2024

Approximately 3% of all diagnosed cases of ascites are of cardiac etiology. Although more commonly associated with heart failure, pulmonary arterial hypertension is a known but rare cause of cardiac ascites, which has not been associated with spontaneous bacterial peritonitis. We present a case of a 75-year-old male with known pulmonary arterial hypertension and new-onset ascites, the fluid analysis of which was consistent with both cardiac ascites and spontaneous bacterial peritonitis. He was successfully managed with antibiotics, loop diuretics, and mineralocorticoid receptor antagonists.
Recent Advances in Biomolecular Patho-Mechanistic Pathways behind the Development and Progression of Diabetic Neuropathy
Authors: Ratan Yashumati , Rajput Aishwarya , Pareek Ashutosh , Pareek Aaushi , Kaur Ranjeet , Sonia Sonia , Kumar Rahul , Singh Gurjit
Published: June 2024

Diabetic neuropathy (DN) is a neurodegenerative disorder that is primarily characterized by distal sensory loss, reduced mobility, and foot ulcers that may potentially lead to amputation. The multifaceted etiology of DN is linked to a range of inflammatory, vascular, metabolic, and other neurodegenerative factors. Chronic inflammation, endothelial dysfunction, and oxidative stress are the three basic biological changes that contribute to the development of DN. Although our understanding of the intricacies of DN has advanced significantly over the past decade, the distinctive mechanisms underlying the condition are still poorly understood, which may be the reason behind the lack of an effective treatment and cure for DN. The present study delivers a comprehensive understanding and highlights the potential role of the several pathways and molecular mechanisms underlying the etiopathogenesis of DN. Moreover, Schwann cells and satellite glial cells, as integral factors in the pathogenesis of DN, have been enlightened. This work will motivate allied research disciplines to gain a better understanding and analysis of the current state of the biomolecular mechanisms behind the pathogenesis of DN, which will be essential to effectively address every facet of DN, from prevention to treatment.
Characterization of Receptor Binding Affinity for Vascular Endothelial Growth Factor with Interferometric Imaging Sensor
Authors: Lortlar Ünlü Nese , Bakhshpour-Yucel Monireh , Chiodi Elisa , Diken-Gür Sinem , Emre Sinan , Ünlü M. Selim
Published: June 2024

Wet Age-related macular degeneration (AMD) is the leading cause of vision loss in industrialized nations, often resulting in blindness. Biologics, therapeutic agents derived from biological sources, have been effective in AMD, albeit at a high cost. Due to the high cost of AMD treatment, it is critical to determine the binding affinity of biologics to ensure their efficacy and make quantitative comparisons between different drugs. This study evaluates the in vitro VEGF binding affinity of two drugs used for treating wet AMD, monoclonal antibody-based bevacizumab and fusion protein-based aflibercept, performing quantitative binding measurements on an Interferometric Reflectance Imaging Sensor (IRIS) system. Both biologics can inhibit Vascular Endothelial Growth Factor (VEGF). For comparison, the therapeutic molecules were immobilized on to the same support in a microarray format, and their real-time binding interactions with recombinant human VEGF (rhVEGF) were measured using an IRIS. The results indicated that aflibercept exhibited a higher binding affinity to VEGF than bevacizumab, consistent with previous studies using ELISA and SPR. The IRIS system’s innovative and cost-effective features, such as silicon-based semiconductor chips for enhanced signal detection and multiplexed analysis capability, offer new prospects in sensor technologies. These attributes make IRISs a promising tool for future applications in the development of therapeutic agents, specifically biologics.
Copolymer-Coated Gold Nanoparticles: Enhanced Stability and Customizable Functionalization for Biological Assays
Authors: Brambilla Dario , Panico Federica , Zarini Lorenzo , Mussida Alessandro , Ferretti Anna M. , Aslan Mete , Ünlü M. Selim , Chiari Marcella
Published: June 2024

Gold nanoparticles (AuNPs) play a vital role in biotechnology, medicine, and diagnostics due to their unique optical properties. Their conjugation with antibodies, antigens, proteins, or nucleic acids enables precise targeting and enhances biosensing capabilities. Functionalized AuNPs, however, may experience reduced stability, leading to aggregation or loss of functionality, especially in complex biological environments. Additionally, they can show non-specific binding to unintended targets, impairing assay specificity. Within this work, citrate-stabilized and silica-coated AuNPs (GNPs and SiGNPs, respectively) have been coated using N,N-dimethylacrylamide-based copolymers to increase their stability and enable their functionalization with biomolecules. AuNP stability after modification has been assessed by a combination of techniques including spectrophotometric characterization, nanoparticle tracking analysis, transmission electron microscopy and functional microarray tests. Two different copolymers were identified to provide a stable coating of AuNPs while enabling further modification through click chemistry reactions, due to the presence of azide groups in the polymers. Following this experimental design, AuNPs decorated with ssDNA and streptavidin were synthesized and successfully used in a biological assay. In conclusion, a functionalization scheme for AuNPs has been developed that offers ease of modification, often requiring single steps and short incubation time. The obtained functionalized AuNPs offer considerable flexibility, as the functionalization protocol can be personalized to match requirements of multiple assays.
Influence of Critical Parameters on the Extraction of Concentrated C-PE from Thermotolerant Cyanobacteria
Authors: Vergel-Suarez Ariadna H. , García-Martínez Janet B. , López-Barrera German L. , Urbina-Suarez Néstor A. , Barajas-Solano Andrés F.
Published: June 2024

This work aimed to identify the influence of pH, molarity, w/v fraction, extraction time, agitation, and either a sodium (Na2HPO4·7H2O-NaH2PO4·H2O) or potassium buffer (K2HPO4-KH2PO4) used in the extraction of C-phycoerythrin (C-PE) from a thermotolerant strain of Potamosiphon sp. An experimental design (Minimum Run Resolution V Factorial Design) and a Central Composite Design (CCD) were used. According to the statistical results of the first design, the K-PO4 buffer, pH, molarity, and w/v fraction are vital factors that enhance the extractability of C-PE. The construction of a CCD design of the experiments suggests that the potassium phosphate buffer at pH 5.8, longer extraction times (50 min), and minimal extraction speed (1000 rpm) are ideal for maximizing C-PE concentration, while purity is unaffected by the design conditions. This optimization improves extraction yields and maintains the desired bright purple color of the phycobiliprotein.
The Correlation between the MBTI-Based Personality Analysis of Anime Characters and Their Popularity
Authors: Tang Ruiyang , Yang Penghao , Miyauchi Ryoga , Inoue Yuki
Published: June 2024

Anime has become a global phenomenon due to its diverse cultural representations, relatable characters, and unique storytelling. However, there is limited research on the relationship between character personality and popularity. The aim of this study is to understand the relevance of the characters’ personalities to the audience’s evaluation of various characters. This study analyzed the correlation between the MBTI personality evaluations of characters in anime and their popularity, based on the data of the personality of each animation character reviewed by audiences. In this study, 885 characters from 200 anime aimed at a male audience were selected as a sample for research. The results showed that personality traits such as introversion, intuition, and thinking had an impact on the popularity of female characters but not male characters. The overall results were influenced by the larger sample size of female characters. By addressing this question, the study can contribute to the design of a character’s personality and overall success in anime.
Estimation of Chemical and Mineral Composition, Structural Features, and Pre-Firing Technological Properties of Waste Coal Heaps for Ceramic Production
Authors: Yavruyan Khungianos , Kotlyar Vladimir
Published: June 2024

The relevance of the investigation and creation of a new non-traditional raw material base for wall ceramics for the south of Russia is shown in connection with the decreasing availability of traditional raw materials—loams. Characterizations of the mineral and chemical constituent rock formations of the rocks composing the dumps of coal waste heaps and enrichment plants are given. A serious constraint for the industrial development of coal wastes is the requirement for a great variety of mineral constituents. The chemical and mineralogical compositions and the pre-firing ceramic properties of the waste coal heaps are studied and presented in detail. It is mentioned that fine and thin materials contain coal in an increased amount; due to this, they cannot be considered as the main raw material for the production of wall ceramics. The materials of the medium-sized grain group (2.0–5.0 mm, sifting) can contain up to 2–3% of coal and are most often represented by a mixture of mudstones, siltstones, and sandstones, with the predominance of one or another type of rock. The granulometric composition and the content of large-grained inclusions, molding moisture, plasticity, cohesiveness, desiccation properties, and air shrinkage were studied and determined. It is concluded that the middle group of waste coal heaps in particular are of the greatest interest as a basic raw material for the production of wall ceramic products.
Analyzing Critical Influencing Factors of the Maturity of Smart Construction Site Applications
Authors: Liu Jianzhao , Zhang Shuolin , Hou Yonghui , Xiahou Xiaer , Li Qiming
Published: June 2024

The burgeoning application of advanced information technology in the construction industry has led to the widespread adoption of smart construction sites (SCSs) in recent years. As a novel concept, smart construction site application maturity (SCS-AM) aims to identify the pivotal factors impeding the current progression of SCSs and foster the metamorphosis of the construction sector. Through a meticulous review of the existing literature, this study delineates 14 fundamental factors influencing SCS-AM. Employing both Exploratory Factor Analysis (EFA) and confirmatory factor analysis (CFA), alongside the acquisition of 217 valid questionnaires, practitioners’ perceptions regarding these factors within the smart construction domain were examined. This study initially categorized the 14 factors into four dimensions by utilizing the EFA method: technological innovation and integration (TII), project management and implementation (PMI), collaboration mechanism and information sharing (CMIS), and standardization and compliance (SC). Subsequently, a first-order CFA was employed to elucidate the correlations between the observed variables and latent factors, while a second-order CFA was employed to delve into the interplay among the first-order factors and their collective influence on SCS-AM. The results underscore the paramount impact of standardization and compliance (SC) and technological innovation and integration (TII) on SCS-AM. By meticulously analyzing the key influencing factors, this study offers theoretical underpinnings for bolstering SCS-AM, thereby providing stakeholders such as governments and construction enterprises with strategic insights for future development endeavors.
Intelligent Systems Integrating BIM and VR for Urban Subway Microenvironmental Health Risks Management
Authors: Chen Qiwen , Li Chenhui , Xu Xiaoxiao , Mao Peng , Xiong Lilin
Published: June 2024

With the rapid development and construction of urban subways, various risks associated with human health and wellbeing within subway microenvironments have seriously increased. However, only a few intelligent systems have been validated as suitable for facilitating the management of subway environments. Field tests can be time-consuming and inefficient, and questionnaires often lack true intuitiveness for participants. Therefore, to enhance subway environment management, this study proposed intelligent systems that integrate building information modeling (BIM) and virtual reality (VR) for managing health risks in urban subway microenvironments. The systems were developed using Revit 2021, Navisworks 2020, Unity 2019, MYSQL 8.0, and Visual Studio 2019. Additionally, they were applied in scenarios for environmental assessment and passenger coping capability enhancement, differentiated into an expert visual-based health risk assessment system and a gamified simulation system for passenger risk prevention. The feasibility of the approach was validated with the case of Xinzhuang subway station of Line 3 in Nanjing, China. The findings revealed that the assessment system enabled experts to have a better and straight understanding of subway microenvironmental health risks and the gamification simulation system significantly enhanced the passengers’ coping capacity. The integration of BIM and VR, with its design features such as visibility, optimization, and simulation, compensated for BIM’s lack of providing an immersive experience for systems. The intelligent systems introduced in this study present novel models for environmental assessment and passenger training, catering to both subway operators and researchers. The innovative systems serve as a cornerstone in guaranteeing the health and safety of public transportation operations.
New Trends in Catalytic Reaction for High-Temperature and Low-Emission Combustion Technologies
Authors: Dai Baiqian , Wu Xiaojiang , Zhang Lian
Published: June 2024

With the continuous rise in global energy demand and the increasing awareness of environmental protection, high-temperature low-emission combustion technology has become a research hotspot in the field of combustion science [...]
Regulation of Precise DNA Repair by Nuclear Actin Polymerization: A Chance for Improving Gene Therapy?
Authors: He Xiubin , Brakebusch Cord
Published: June 2024

Although more difficult to detect than in the cytoplasm, it is now clear that actin polymerization occurs in the nucleus and that it plays a role in the specific processes of the nucleus such as transcription, replication, and DNA repair. A number of studies suggest that nuclear actin polymerization is promoting precise DNA repair by homologous recombination, which could potentially be of help for precise genome editing and gene therapy. This review summarizes the findings and describes the challenges and chances in the field.
Respectful Children’s Shoes: A Systematic Review
Authors: Alfageme-García Pilar , Hidalgo-Ruiz Sonia , Rico-Martín Sergio , Calderón-García Julián Fernando , Jimenez-Cano Víctor Manuel , Morán-Cortés Juan Francisco , Basilio-Fernández Belinda
Published: June 2024

Background: Child footwear, both in pathologies and in normal situations, can affect the foot in various ways depending on its characteristics. Below, some features of child footwear are described, and how they can influence the foot, including suitable size, shape and design, flexibility, and transpirable material; inadequate footwear includes situations with flat foot, equine foot, and hammer toes. It is important to highlight that each child is unique and may have different footwear needs. In case of specific pathologies or concerns, it is recommended to consult a specialist in podology or foot medicine for personalized assessment and recommendations. Methods: The present systematic review was conducted in accordance with the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Results: Children’s footwear must adapt to all stages of children’s growth, starting from when they begin to walk, to promote the correct evolution of their musculoskeletal system. For up to six months, they do not need to wear shoes; socks and similar clothing are enough to warm your feet like a second skin. The flexibility of respectful footwear is essential between six months and three or four years. From that age onwards, the soles can be somewhat thicker, and the buttress can have a certain firmness, but the shoes should remain flexible. Conclusions: Eco-friendly footwear, which typically comes from small businesses and factories, is sometimes described as “ergonomic footwear”. However, there is some reluctance towards this term. When choosing this type of footwear for children, it is important to not just look at the label; rather, one should verify that it meets all the necessary characteristics to be considered respectful.
Neuroimaging of Vermiform Giant Arachnoid Granulations in Children
Authors: Guevara Tirado Oswaldo A. , Mertiri Livja , Kralik Stephen F. , Desai Nilesh K. , Huisman Thierry A. G. M. , Lequin Maarten H. , Tran Huy (Brandon) D.
Published: June 2024

Arachnoid granulations (AGs) are generally benign structures within the subarachnoid space that extend into the dural sinuses and calvarial bone. They can present in a variety of sizes but are termed ‘giant’ arachnoid granulations (GAGs) when they are larger than 1 cm in diameter or take up a significant portion of the dural sinus’ lumen. Vermiform giant arachnoid granulations are a specific type of GAG that are known for their worm-like appearance. Specifically, these vermiform GAGs can be challenging to diagnose as they can mimic other pathologies like dural sinus thrombosis, sinus cavernomas, or brain tumors. In this case series, we present two cases of vermiform giant arachnoid granulations, discuss their imaging characteristics and highlight the diagnostic challenges to improve identification and prevent misdiagnoses.
Predictors of Readmission in Young Adults with First-Episode Psychosis: A Multicentric Retrospective Study with a 12-Month Follow-Up
Authors: Besana Filippo , Civardi Serena Chiara , Mazzoni Filippo , Carnevale Miacca Giovanni , Arienti Vincenzo , Rocchetti Matteo , Politi Pierluigi , Martiadis Vassilis , Brondino Natascia , Olivola Miriam
Published: June 2024

Background: A significant number of young individuals are readmitted one or more times shortly after their first episode of psychosis. Readmission may represent a marker of psychopathological vulnerability. Our primary aim was to evaluate the impact of clinical and socio-demographic variables on readmission at 12-month follow-up. Secondly, our goal was to determine whether the use of Long-Acting Injection (LAI) antipsychotics provides notable benefits compared to oral medications in preventing subsequent readmissions. Subjects and methods: 80 patients hospitalised for the first time with a diagnosis of psychotic disorder (ICD-10 criteria) were retrospectively assessed through clinical records. The mean age was 21.7 years. Patients were predominantly male (n = 62, 77.5%), and 55 subjects had at least 8 years of education. 50% of the sample was “NEET” (not in education, employment, or training). Results: 35 patients (43.8%) were discharged with a LAI antipsychotic, while 45 (56.2%) recieved oral antipsychotic therapy. Substance use (p = 0.04) and oral antipsychotics at discharge (p = 0.003) were significantly associated with readmission at 1 year. We did not find any significant predictors of being discharged with LAI therapy. Conclusion: Our findings underlined the importance of identifying patients at risk of readmission in order to prevent future rehospitalization and promote appropriate prevention strategies. LAIs should be considered as a first-choice treatment for patients hospitalised for FEP since they proved to be effective in preventing relapse.