bluuebunny/crossref_metadata_2025 huggingface dataset:
Transient Dynamic Response of Generally Shaped Arches under Interval Uncertainties
Authors: Nie Zhihua , Fu Chao , Yang Yongfeng , Zhao Jiepeng
Published: July 2024

This paper endeavors to investigate the characteristics of the transient dynamic response of a generally shaped arch when influenced by uncertain parameters while being subjected to specific external excitation. The equations of motion of the generally shaped arches are derived by the differential quadrature (DQ) method, and the deterministic dynamic responses are calculated using the Newmark-β method. By employing the Chebyshev inclusive function, an interval method based on a non-intrusive polynomial surrogate model is developed, and the uncertain dynamic responses are reckoned by enabling numerical simulations. The results of the proposed interval method are compared with those obtained from the scanning method for validation. The effects of various shapes and rise span ratios on the dynamic responses are investigated through a parametric study. The results suggest that the degree of fluctuation in the uncertain dynamic behavior is influenced by the type of parameter. Additionally, the responses of each shaped arch decrease with the increase in the rise span ratios, and with the same rise span ratio, the deterministic responses and corresponding uncertain responses are also affected by the shape of the arch, and they are considered to be at a minimum when the arch shape is parabolic. This study will enhance understanding of the dynamic properties of arches with uncertainties and provide some basis for the assessment and health monitoring of arch structures.
Heat Transfer Performance and Operation Scheme of the Deeply Buried Pipe Energy Pile Group
Authors: Tian Yuhan , Chen Zhi , Yuan Jianghuai , Mao Anqi
Published: July 2024

This paper describes a study on the heat transfer properties of the deeply buried pipeline energy pile group, which is an efficient and convenient geothermal development technology. Through in situ experiments and a simulation algorithm, the research investigated the heat transmission characteristics of the deeply buried pipe energy pile group and optimized different intermittent operation schemes. The findings suggest that prolonged operation of the pile cluster intensifies heat buildup within the pile foundation, thereby adversely affecting the system’s overall heat exchange efficiency. Employing an intermittent operating mode can alleviate this heat accumulation phenomenon, thereby promoting sustained heat exchange performance of the piles over time. To evaluate the comprehensive thermal interaction and energy efficiency ratio of the energy pile heat exchange system, various intermittent operation strategies were compared in the study. Among them, the intermittent operational scheme with a ratio of n = 5 was found to be optimal, with the total average heat transfer rate of the pile set only 0.51% lower than that of the continuous operational mode, but the overall energy efficiency ratio improved by 19.6%. The intermittent operational mode proposed in this study can achieve the goal of saving energy and efficiently extracting geothermal resources, providing theoretical guidance for the extraction and utilization of subsurface geothermal power by energy piles.
Analysis and Experimental Study on the Stability of Large-Span Caverns’ Surrounding Rock Based on the Progressive Collapse Mechanism
Authors: Chen Huanxia , Fan Junqi , Xu Jingmao
Published: July 2024

The collapse failure of rock surrounding caverns involves a progressive collapse process. Based on the nonlinear Hoek–Brown failure criterion and the upper limit theorem, the whole process curve of the progressive collapse of the surrounding rock of a large-span cavern is outlined in this paper. The progressive collapse process of the surrounding rock of the large-span cavern is experimentally studied using an independently developed visualized large-span-cavern geomechanical model test device with variable angles. The results show that, through theoretical calculation and model tests, the surrounding rock at the top of the large-span cavern undergoes three collapses. Under the condition of rock mass and the shape of the cavern, the larger the span of the cavern, the more times the surrounding rock collapses; with the increase in surrounding rock pressure, the first collapse occurs in the middle part of the arch roof. When the overlying load reaches a certain level, the arch foot becomes the weakest part, and the rock undergoes shear failure along the arch foot, gradually extending upwards, accompanied by multiple collapses, forming a progressive collapse process. The theoretical calculation results of this paper are basically consistent with the scope of the model test, and the research results can provide a basis for the construction and support design of the large-span cavern.
A Placement Method of the 5G Edge Nodes Based on the Hotspot Distribution of Mobile Users
Authors: Gui Ruowei , Zhang Xingjun , Gui Xiaolin , Han Jinsong
Published: July 2024

Due to the emergence of various new applications, such as short videos and online games, higher requirements of their computing and storage capacity are demanded of mobile networks. The traditional cloud computing paradigm has the shortcomings of large latency and high bandwidth demand of the core network. Therefore, how to mine the hotspot distribution of these applications and reasonably configure 5G edge nodes to reduce latency and core network bandwidth are facing great challenges. To address these issues, we designed a placement method for the 5G edge nodes based on mobile hotspots. In this method, we first cluster all locations from the user trajectories to obtain the cluster areas. Further, we extract the features, such as the number of users and duration time in all cluster areas, and extract the hotspots from all cluster areas based on the features of each cluster. Then, we introduce the base station’s high load utilization rate and the core network’s bandwidth reduction rate as the optimization parameters to construct the mathematical model of multi-objective optimization. Finally, we formalize the model into a 0–1 integer programming problem and design a greedy algorithm to solve this model. We also complete a series of experiments to evaluate our proposed methods using the GeoLife dataset. The experimental results show that the high load utilization rate can be increased up to 7.69%, and the bandwidth reduction rate of the core network can be improved up to 6.34%.
Spatio-Temporal Variations in Soil Erosion and Its Driving Forces in the Loess Plateau from 2000 to 2050 Based on the RUSLE Model
Authors: Min Jie , Liu Xiaohuang , Li Hongyu , Wang Ran , Luo Xinping
Published: July 2024

Assessing the spatio-temporal variability and driving forces of soil erosion on the Loess Plateau is critical for ecological and environmental management. In this paper, the Revised Universal Soil Loss Equation (RUSLE) model, the patch-generating land use simulation, and the Geographical Detector are used to investigate the spatio-temporal variations of the Loess Plateau’s soil erosion from 2000 to 2050. The results showed that: (1) The primary categories of soil erosion from 2000 to 2020 were moderate, mild, and slight, and the average level of soil erosion exhibited a decreasing and then an increasing tendency during the last 20 years. (2) Soil erosion was directly impacted by changes in land use, with cropland and forest being the primary land use and land cover changes in the study region. Cropland and construction land being turned into woodland between 2000 and 2020 resulted in a significant decrease in the severity of soil erosion. Projected soil erosion is expected to increase significantly between 2020 and 2050 due to arable land being converted into construction land. (3) The key variables impacting the spatial distribution of soil erosion were LUCC (Land-Use and Land-Cover Change), NDVI (Normalized Difference Vegetation Index), and slope, and the interplay of these variables may increase their ability to explain soil erosion. Grasslands with an NDVI ranging from 0.9 to 1, rain ranging from 0.805 to 0.854 m, a slope above 35°, and a terrain elevation ranging from 1595 to 2559 m were identified as having a high risk of soil erosion. Soil erosion prevention and management efforts should focus on the ecological restoration of upland areas in the future.
Possible Development of Efficient Local Energy Community on the Example of the City of Žilina in Slovakia
Authors: Durcansky Peter , Zvada Branislav , Nosek Radovan
Published: July 2024

Reducing the energy demand in the housing sector is one of the current topics in the EU. Slovakia, as an EU member, is also trying to lower the dependence on the import of energy raw materials used for heating. While new buildings reflect the technical requirements of applicable standards, buildings built in the past usually do not meet any technical requirements. The basis of efficient operation is not only satisfactory building structures, but also technological equipment of the buildings. The heating system is often in an unsatisfactory state, and an outdated heat source disproportionately reduces the overall efficiency of energy conversion. Complex restoration is, therefore, in most cases, necessary and often financially costly. The presented article analyzes the current state of housing stock in the example of a selected city district. In the next step, the current state and energy consumption are identified. Subsequently, needed retrofit measures are identified and the possibilities of renewal are analyzed. The use of RES in buildings is proposed, while selected city districts could create an independent energy community. The main goal of this article is to show the necessary steps to achieve efficient energy use and, using the example of a Zilina City district, show the possible benefits of such community creation in Slovakia. The article also discusses the correlation between the number of sunny days and possible energy generation in winter months.
Chewing Bite Wafers versus Conventional Analgesic Drugs to Relieve Self-Reported Pain Associated with Fixed Orthodontic Appliances: A Systematic Review and Meta-Analysis
Authors: Jabr Luay , Altuhafy Maryam , Barmak Abdul Basir , Rossouw Paul Emile , Michelogiannakis Dimitrios
Published: July 2024

(1) Objectives: To estimate the impact of chewing bite wafers in reducing pain associated with fixed orthodontic treatment (OT) compared with conventional analgesic drugs (CADs) (Ibuprofen or Acetaminophen). (2) Materials and methods: Unrestricted and manual searching was achieved up to November 2023 and PRISMA guidelines were followed. Randomized controlled trials (RCTs) were included. Meta-analyses were conducted using a random-effects model. The available evidence quality was considered using the GRADE approach. (3) Results: Seven RCTs were included. Five RCTs used the Visual Analog Scale for self-reported pain assessment, while two RCTs used the Numeric Rating Scale. Four RCTs had a high RoB, and three RCTs had a moderate RoB. Separate meta-analyses were performed by pooling quantitative data from two RCTs that compared self-reported orthodontic pain between the bite wafer and Ibuprofen groups and three RCTs that compared the bite wafer and Acetaminophen groups for the different timepoints after orthodontic treatment. None of the timepoints individually indicated a significant difference in pain scores between the bite wafer and control groups, except on day 3, indicating significantly lower pain scores in the bite wafer versus the Acetaminophen groups. The overall level of evidence was very low. (4) Conclusions: Chewing bite wafers is possibly a useful option for CADs to relieve pain during early fixed OT.
A Reduced-Dimension Weighted Explicit Finite Difference Method Based on the Proper Orthogonal Decomposition Technique for the Space-Fractional Diffusion Equation
Authors: Ren Xuehui , Li Hong
Published: July 2024

A kind of reduced-dimension method based on a weighted explicit finite difference scheme and the proper orthogonal decomposition (POD) technique for diffusion equations with Riemann–Liouville fractional derivatives in space are discussed. The constructed approximation method written in matrix form can not only ensure a sufficient accuracy order but also reduce the degrees of freedom, decrease storage requirements, and accelerate the computation rate. Uniqueness, stabilization, and error estimation are demonstrated by matrix analysis. The procedural steps of the POD algorithm, which reduces dimensionality, are outlined. Numerical simulations to assess the viability and effectiveness of the reduced-dimension weighted explicit finite difference method are given. A comparison between the reduced-dimension method and the classical weighted explicit finite difference scheme is presented, including the error in the L2 norm, the accuracy order, and the CPU time.
Multimodal Quanvolutional and Convolutional Neural Networks for Multi-Class Image Classification
Authors: Gordienko Yuri , Trochun Yevhenii , Stirenko Sergii
Published: July 2024

By utilizing hybrid quantum–classical neural networks (HNNs), this research aims to enhance the efficiency of image classification tasks. HNNs allow us to utilize quantum computing to solve machine learning problems, which can be highly power-efficient and provide significant computation speedup compared to classical operations. This is particularly relevant in sustainable applications where reducing computational resources and energy consumption is crucial. This study explores the feasibility of a novel architecture by leveraging quantum devices as the first layer of the neural network, which proved to be useful for scaling HNNs’ training process. Understanding the role of quanvolutional operations and how they interact with classical neural networks can lead to optimized model architectures that are more efficient and effective for image classification tasks. This research investigates the performance of HNNs across different datasets, including CIFAR100 and Satellite Images of Hurricane Damage by evaluating the performance of HNNs on these datasets in comparison with the performance of reference classical models. By evaluating the scalability of HNNs on diverse datasets, the study provides insights into their applicability across various real-world scenarios, which is essential for building sustainable machine learning solutions that can adapt to different environments. Leveraging transfer learning techniques with pre-trained models such as ResNet, EfficientNet, and VGG16 demonstrates the potential for HNNs to benefit from existing knowledge in classical neural networks. This approach can significantly reduce the computational cost of training HNNs from scratch while still achieving competitive performance. The feasibility study conducted in this research assesses the practicality and viability of deploying HNNs for real-world image classification tasks. By comparing the performance of HNNs with classical reference models like ResNet, EfficientNet, and VGG-16, this study provides evidence of the potential advantages of HNNs in certain scenarios. Overall, the findings of this research contribute to advancing sustainable applications of machine learning by proposing novel techniques, optimizing model architectures, and demonstrating the feasibility of adopting HNNs for real-world image classification problems. These insights can inform the development of more efficient and environmentally friendly machine learning solutions.
Sensory Characterization and Acceptance of Amazonian Robustas Coffee Brews by Consumers Using a Home-Use Test
Authors: Viencz Thayna , Portela Claudimara da Silva , Rocha Rodrigo Barros , Alves Enrique Anastácio , Ramalho André Rostand , Dias Rafael Carlos Eloy , Benassi Marta de Toledo
Published: July 2024

This study evaluated consumers’ perceptions of beverages obtained from the intervarietal hybrids of Coffea canephora, Conilon and Robusta, produced in the Western Amazon, through a home-use test with 127 participants. An acceptance test and a Check-All-That-Apply procedure were applied. Two clones, BRS 2314 and BRS 2357, were studied (both in natural and fermented versions) and their roasted coffee composition was also evaluated. All beverages were described as having a mild aroma, roasted flavor, and slightly sour taste; consumers noticed both the effect of the fermentation process and genetics. Natural coffees had greater sensory acceptance than fermented ones. Natural coffees were most associated with a slightly bitter taste, and were well accepted by almost half of the participants, mainly women. Fermented coffees were both associated with fermented flavor, but also presented specific characteristics. BRS 2314F was most associated with a fruity flavor and slightly bitter taste and was well accepted by younger consumers with higher levels of education. BRS 2357F was most associated with tobacco flavor and bitter taste and was well accepted by older consumers with a lower education level and a higher coffee consumption frequency. The positive acceptance of C. canephora intervarietal hybrid beverages allowed us to confirm its material market potential.
Hip Exoskeleton for Cycling Assistance
Authors: Grimmer Martin , Zhao Guoping
Published: July 2024

Cycling stands as one of the most widely embraced leisure activities and serves purposes such as exercise, rehabilitation, and commuting. This study aimed to assess the feasibility of assisting three unimpaired participants (age: 34.0 ± 7.9 years, height: 1.86 ± 0.02 m, weight: 75.7 ± 12.7 kg) using the GuroX hip exoskeleton, originally designed for walking assistance, during cycling against a resistance of 1 W/kg. The performance evaluation employed a sweep protocol that manipulated the timing of the exoskeleton’s peak extension and flexion torque in addition to human-in-the-loop optimization to enhance these timings based on metabolic cost. Our findings indicate that with a peak assistance torque of approximately 10.3 Nm for extension and flexion, the GuroX substantially reduced the net metabolic cost of cycling by 31.4 ± 8.1% and 26.4 ± 14.1% compared to transparent and without exoskeleton conditions, respectively. This demonstrates the significant potential of a hip exoskeleton developed for walking assistance to profoundly benefit cycling. Additionally, customizing the assistance strategy proves beneficial in maximizing assistance. While we attribute the average motor power to be a major contributor to the reduced cycling effort, participant feedback suggests that user comfort and synchronization between the user and exoskeleton may have played integral roles. Further research should validate our initial findings by employing a larger participant pool in real-world conditions. Incorporating a more diverse set of parameters for the human-in-the-loop optimization could enhance individualized assistance strategies.
Effects of Acute Mental Stress on Choroidal Thickness
Authors: Lin Jiechun , Han Yingxiang , Liu Meng , Wang Xiaofei
Published: July 2024

Purpose: Previous studies have indicated an association between education and myopia, suggesting that numerous stress events during the educational process may influence eye health. This study aimed to investigate the impact of mental stress induced by mental arithmetic (MA) on choroidal thickness (CT). Methods: This study included 33 participants aged between 19 and 29 years. Swept-source optical coherence tomography (SS-OCT) was used to capture images of the posterior segment of the left eye during baseline and MA to assess changes in the CT. After denoising and compensation, the baseline images and MA images that had been rigidly registered and resampled to the baseline images were segmented using a deep learning-based method. Based on the segmentation results, the CT within the regions of 1 mm and 3 mm diameter centered at the lowest point of the fovea was calculated. Results: Significant increases were observed in both CT1mm and CT3mm during MA, with mean changes of 2.742 ± 7.098 μm (p = 0.034) and 3.326 ± 6.143 μm (p < 0.001), respectively. Conclusions: Thickening of the choroid has been observed during acute mental stress. We speculate that long-term or chronic mental stress could have a potential adverse impact on myopia progression.
An Experimental and Clinical Study of Flap Monitoring with an Analysis of the Clinical Course of the Flap Using an Infrared Thermal Camera
Authors: Kim Hyun , Kwak Si Hyun , Byeon Je Yeon , Lee Da Woon , Kim Jun Hyuk , Lim Soomin , Choi Hwan Jun
Published: July 2024

Flap surgery is a common method used to cover defects following tumor ablation, trauma, or infection. However, insufficient vascularity in the transferred flap can lead to flap necrosis and failure. Proper postoperative monitoring is essential to prevent these complications. Recently, research has explored the use of infrared thermal imaging in plastic surgery, leading to its clinical application. This study comprises two separate parts: an in vivo experimental study and a clinical study. In this study, 28 rats underwent reverse McFarlane flap surgery, and their flaps were analyzed using a FLIR thermal imaging camera seven days post-surgery. Additionally, thermal images of flaps were taken on postoperative days 0, 1, 2, 3, and 7 in 22 patients. This study focused on temperature differences between normal skin and the perforator compared to the average flap temperature. Results showed that the temperature difference was higher in the necrosis group and increased over time in cases of total necrosis. A lower perforator temperature compared to the flap’s average indicated vascular compromise, potentially leading to flap failure. The FLIR camera, being contact-free and convenient, shows promise for understanding and inferring the clinical progression of flaps in postoperative monitoring.
Multi-Shared-Task Self-Supervised CNN-LSTM for Monitoring Free-Body Movement UPDRS-III Using Wearable Sensors
Authors: Shuqair Mustafa , Jimenez-Shahed Joohi , Ghoraani Behnaz
Published: July 2024

The Unified Parkinson’s Disease Rating Scale (UPDRS) is used to recognize patients with Parkinson’s disease (PD) and rate its severity. The rating is crucial for disease progression monitoring and treatment adjustment. This study aims to advance the capabilities of PD management by developing an innovative framework that integrates deep learning with wearable sensor technology to enhance the precision of UPDRS assessments. We introduce a series of deep learning models to estimate UPDRS Part III scores, utilizing motion data from wearable sensors. Our approach leverages a novel Multi-shared-task Self-supervised Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) framework that processes raw gyroscope signals and their spectrogram representations. This technique aims to refine the estimation accuracy of PD severity during naturalistic human activities. Utilizing 526 min of data from 24 PD patients engaged in everyday activities, our methodology demonstrates a strong correlation of 0.89 between estimated and clinically assessed UPDRS-III scores. This model outperforms the benchmark set by single and multichannel CNN, LSTM, and CNN-LSTM models and establishes a new standard in UPDRS-III score estimation for free-body movements compared to recent state-of-the-art methods. These results signify a substantial step forward in bioengineering applications for PD monitoring, providing a robust framework for reliable and continuous assessment of PD symptoms in daily living settings.
Predicting Aneurysmal Degeneration in Uncomplicated Residual Type B Aortic Dissection
Authors: Forneris Arianna , Fatehi Hassanabad Ali , Appoo Jehangir , Di Martino Elena
Published: July 2024

The formation of an aneurysm in the false lumen (FL) is a long-term complication in a significant percentage of type B aortic dissection (AD) patients. The ability to predict which patients are likely to progress to aneurysm formation is key to justifying the risks of interventional therapy. The investigation of patient-specific hemodynamics has the potential to enable a patient-tailored approach to improve prognosis by guiding disease management for type B dissection. CFD-derived hemodynamic descriptors and geometric features were used to retrospectively assess individual aortas for a population of residual type B AD patients and analyze correlations with known outcomes (i.e., rapid aortic growth, death). The results highlight great variability in flow patterns and hemodynamic descriptors. A rapid aortic expansion was found to be associated with a larger FL. Time-averaged wall shear stress at the tear region emerged as a possible indicator of the dynamics of flow exchange between lumens and its effect on the evolution of individual aortas. High FL flow rate and tortuosity were associated with adverse outcomes suggesting a role as indicators of risk. AD induces complex changes in vessel geometry and hemodynamics. The reported findings emphasize the need for a patient-tailored approach when evaluating uncomplicated type B AD patients and show the potential of CFD-derived hemodynamics to complement anatomical assessment and help disease management.
Intuitionistic Fuzzy Biofeedback Control of Implanted Dual-Sensor Cardiac Pacemakers
Authors: Alshahrani Hussain , Alshahrani Amnah , Karar Mohamed Esmail , Ramadan Ebrahim A.
Published: July 2024

Cardiac pacemakers are used for handling bradycardia, which is a cardiac rhythm of usually less than 60 beats per minute. Therapeutic dual-sensor pacemakers aim to preserve or restore the normal electromechanical activity of the cardiac muscle. In this article, a novel intelligent controller has been developed for implanted dual-sensor cardiac pacemakers. The developed controller is mainly based on intuitionistic fuzzy logic (IFL). The main advantage of the developed IFL controller is its ability to merge the qualitative expert knowledge of cardiologists in the proposed design of controlled pacemakers. Additionally, the implication of non-membership functions with the uncertainty term plays a key role in the developed fuzzy controller for improving the performance of a cardiac pacemaker over other fuzzy control schemes in previous studies. Moreover, the proposed pacemaker control system is efficient for managing all health-status conditions and constraints during the different daily activities of cardiac patients. Consequently, the healthcare of patients with implanted dual-sensor pacemakers can be efficiently improved intuitively.
Pan-Evo: The Evolution of Information and Biology’s Part in This
Authors: Sherwin William B.
Published: July 2024

Many people wonder whether biology, including humans, will benefit or experience harm from new developments in information such as artificial intelligence (AI). Here, it is proposed that biological and non-biological information might be components of a unified process, ‘Panevolution’ or ‘Pan-Evo’, based on four basic operations—innovation, transmission, adaptation, and movement. Pan-Evo contains many types of variable objects, from molecules to ecosystems. Biological innovation includes mutations and behavioural changes; non-biological innovation includes naturally occurring physical innovations and innovation in software. Replication is commonplace in and outside biology, including autocatalytic chemicals and autonomous software replication. Adaptation includes biological selection, autocatalytic chemicals, and ‘evolutionary programming’, which is used in AI. The extension of biological speciation to non-biological information creates a concept called ‘Panspeciation’. Panevolution might benefit or harm biology, but the harm might be minimal if AI and humans behave intelligently because humans and the machines in which an AI resides might split into vastly different environments that suit them. That is a possible example of Panspeciation and would be the first speciation event involving humans for thousands of years. This event will not be particularly hostile to humans if humans learn to evaluate information and cooperate better to minimise both human stupidity and artificial simulated stupidity (ASS—a failure of AI).
Sarcoidosis versus Granulomatous and Lymphocytic Interstitial Lung Disease in Common Variable Immunodeficiency: A Comparative Review
Authors: Buso Helena , Discardi Claudia , Bez Patrick , Muscianisi Francesco , Ceccato Jessica , Milito Cinzia , Firinu Davide , Landini Nicholas , Jones Mark G. , Felice Carla , Rattazzi Marcello , Scarpa Riccardo , Cinetto Francesco
Published: July 2024

Sarcoidosis and Granulomatous and Lymphocytic Interstitial Lung Diseases (GLILD) are two rare entities primarily characterised by the development of Interstitial Lung Disease (ILD) in the context of systemic immune dysregulation. These two conditions partially share the immunological background and pathologic findings, with granuloma as the main common feature. In this narrative review, we performed a careful comparison between sarcoidosis and GLILD, with an overview of their main similarities and differences, starting from a clinical perspective and ending with a deeper look at the immunopathogenesis and possible target therapies. Sarcoidosis occurs in immunocompetent individuals, whereas GLILD occurs in patients affected by common variable immunodeficiency (CVID). Moreover, peculiar extrapulmonary manifestations and radiological and histological features may help distinguish the two diseases. Despite that, common pathogenetic pathways have been suggested and both these disorders can cause progressive impairment of lung function and variable systemic granulomatous and non-granulomatous complications, leading to significant morbidity, reduced quality of life, and survival. Due to the rarity of these conditions and the extreme clinical variability, there are still many open questions concerning their pathogenesis, natural history, and optimal management. However, if studied in parallel, these two entities might benefit from each other, leading to a better understanding of their pathogenesis and to more tailored treatment approaches.
Targeted Delivery of Nanoparticles to Blood Vessels for the Treatment of Atherosclerosis
Authors: Zong Qiushuo , He Chengyi , Long Binbin , Huang Qingyun , Chen Yunfei , Li Yiqing , Dang Yiping , Cai Chuanqi
Published: July 2024

Atherosclerosis is a common form of cardiovascular disease, which is one of the most prevalent causes of death worldwide, particularly among older individuals. Surgery is the mainstay of treatment for severe stenotic lesions, though the rate of restenosis remains relatively high. Current medication therapy for atherosclerosis has limited efficacy in reversing the formation of atherosclerotic plaques. The search for new drug treatment options is imminent. Some potent medications have shown surprising therapeutic benefits in inhibiting inflammation and endothelial proliferation in plaques. Unfortunately, their use is restricted due to notable dose-dependent systemic side effects or degradation. Nevertheless, with advances in nanotechnology, an increasing number of nano-related medical applications are emerging, such as nano-drug delivery, nano-imaging, nanorobots, and so forth, which allow for restrictions on the use of novel atherosclerotic drugs to be lifted. This paper reviews new perspectives on the targeted delivery of nanoparticles to blood vessels for the treatment of atherosclerosis in both systemic and local drug delivery. In systemic drug delivery, nanoparticles inhibit drug degradation and reduce systemic toxicity through passive and active pathways. To further enhance the precise release of drugs, the localized delivery of nanoparticles can also be accomplished through blood vessel wall injection or using endovascular interventional devices coated with nanoparticles. Overall, nanotechnology holds boundless potential for the diagnosis and treatment of atherosclerotic diseases in the future.
Gene Therapy of Thromboangiitis Obliterans with Growth Factor Plasmid (VEGF165) and Autologous Bone Marrow Cells
Authors: Barć Piotr , Lubieniecki Paweł , Antkiewicz Maciej , Kupczyńska Diana , Barć Jan , Frączkowska-Sioma Katarzyna , Dawiskiba Tomasz , Dorobisz Tadeusz , Sekula Wojciech , Czuwara Błażej , Małodobra-Mazur Małgorzata , Baczyńska Dagmara , Witkiewicz Wojciech , Skóra Jan Paweł , Janczak Dariusz
Published: July 2024

Background: We performed gene therapy for critical limb ischemia in thromboangiitis obliterans (TAO) by the intramuscular administration of plasmids of the vascular endothelial growth factor gene (VEGF 165) with or without bone marrow-derived stem cells. Methods: The 21 patients were randomly assigned to three groups: A—with dual therapy, cells and plasmid; B—plasmid only; and C—control group, where patients received intramuscular injections of saline. Serum VEGF levels, the ankle–brachial index (ABI), transcutaneous oxygen pressure (TcPO2), and the rest pain measured by the visual analog scale (VAS) were determined sequentially before treatment, and then 1 and 3 months after treatment. Results: In the treatment groups, serum VEGF levels increased by 4 weeks and returned to baseline values after 3 months. ABI after 12 weeks increased by an average of 0.18 in group A, and 0.09 in group B and group C. TcPO2 increased by an average of 17.3 mmHg in group A, 14.1 mmHg in group B, and 10.7 mmHg in group C. The largest pain decrease was observed in group A and averaged 5.43 less pain intensity. Conclusions: Gene therapy using the VEGF plasmid along with or without bone marrow-derived mononuclear cells administered intramuscularly into an ischemic limb in TAO is a safe and effective therapy.
Prognostic Influence of Galectin-1 in Gastric Adenocarcinoma
Authors: Díaz del Arco Cristina , Estrada Muñoz Lourdes , Cerón Nieto María de los Ángeles , Molina Roldán Elena , Fernández Aceñero María Jesús , García Gómez de las Heras Soledad
Published: July 2024

Galectin-1 (Gal-1), a member of the human lectin family, has garnered attention for its association with aggressive behavior in human tumors, prompting research into the development of targeted drugs. This study aims to assess the staining pattern and prognostic significance of Gal-1 immunohistochemical expression in a homogeneous cohort of Western patients with gastric cancer (GC). A total of 149 cases were included and tissue microarrays were constructed. Stromal Gal-1 expression was observed to some extent in most tumors, displaying a cytoplasmic pattern. Cases with stromal Gal-1 overexpression showed significantly more necrosis, lymphovascular invasion, advanced pTNM stages, recurrences, and cancer-related deaths. Epithelial Gal-1 expression was present in 63.8% of the cases, primarily exhibiting a cytoplasmic pattern, and its overexpression was significantly associated with lymphovascular invasion, peritumoral lymphocytic infiltration, and tumor-related death. Kaplan/Meier curves for cancer-specific survival (CSS) revealed a significantly worse prognosis for patients with tumors exhibiting stromal or epithelial Gal-1 overexpression. Furthermore, stromal Gal-1 expression stratified stage III patients into distinct prognostic subgroups. In a multivariable analysis, increased stromal Gal-1 expression emerged as an independent prognostic factor for CSS. These findings underscore the prognostic relevance of Gal-1 and suggest its potential as a target for drug development in Western patients with GC.
Machine Learning for Predicting Chronic Renal Disease Progression in COVID-19 Patients with Acute Renal Injury: A Feasibility Study
Authors: Gracida-Osorno Carlos , Molina-Salinas Gloria María , Góngora-Hernández Roxana , Brito-Loeza Carlos , Uc-Cachón Andrés Humberto , Paniagua-Sierra José Ramón
Published: July 2024

This study aimed to determine the feasibility of applying machine-learning methods to assess the progression of chronic kidney disease (CKD) in patients with coronavirus disease (COVID-19) and acute renal injury (AKI). The study was conducted on patients aged 18 years or older who were diagnosed with COVID-19 and AKI between April 2020 and March 2021, and admitted to a second-level hospital in Mérida, Yucatán, México. Of the admitted patients, 47.92% died and 52.06% were discharged. Among the discharged patients, 176 developed AKI during hospitalization, and 131 agreed to participate in the study. The study’s results indicated that the area under the receiver operating characteristic curve (AUC-ROC) for the four models was 0.826 for the support vector machine (SVM), 0.828 for the random forest, 0.840 for the logistic regression, and 0.841 for the boosting model. Variable selection methods were utilized to enhance the performance of the classifier, with the SVM model demonstrating the best overall performance, achieving a classification rate of 99.8% ± 0.1 in the training set and 98.43% ± 1.79 in the validation set in AUC-ROC values. These findings have the potential to aid in the early detection and management of CKD, a complication of AKI resulting from COVID-19. Further research is required to confirm these results.
Lutetium-177-Prostate-Specific Membrane Antigen Radioligand Therapy: What Is the Value of Post-Therapeutic Imaging?
Authors: Zhang-Yin Jules
Published: July 2024

Lutetium-177 (Lu-177)-labelled radioligand therapies (RLT) targeting prostate-specific membrane antigen (PSMA) present a promising treatment for patients with progressive metastasized castration-resistant prostate cancer (mCRPC). Personalized dosimetry, facilitated by post-therapeutic imaging, offers the potential to enhance treatment efficacy by customizing radiation doses to individual patient needs, thereby maximizing therapeutic benefits while minimizing toxicity to healthy tissues. However, implementing personalized dosimetry is resource-intensive, requiring multiple single-photon emission-computed tomography (SPECT)/CT scans and posing significant logistical challenges for both healthcare facilities and patients. Despite these challenges, personalized dosimetry can lead to optimized radiation delivery, improved safety, and better management of complex cases. Nevertheless, the financial and resource burdens complicate its adoption in routine clinical practice. While the European Association of Nuclear Medicine (EANM) supports personalized dosimetry, standardization is lacking due to these practical constraints. Further research and streamlined methodologies are essential to balance the benefits and feasibility of personalized dosimetry, potentially improving treatment outcomes for mCRPC patients.
The Effects of Acute and Chronic Alcohol Administration and Withdrawal on Bone Microstructure, Mechanical Strength, and Remodeling Protein Expression and Their Relation to an Antioxidant and FGF23 In Vivo
Authors: Syed Hashim Syed Alhafiz , Naina Mohamed Isa , Mohamed Norazlina
Published: July 2024

Alcohol’s detrimental effects on bone health are well established, yet some literature suggests moderate consumption may offer benefits. With alcohol use on the rise, we investigate the impact of acute and chronic alcohol administration, along with withdrawal, on male Wistar rat femurs. We observed a transient cortical thickness increase with acute alcohol (AA) compared to chronic exposure (CA) but no significant changes in trabecular parameters or mechanical properties. High osteocalcin and osteopontin expression levels were noted in AA, alongside elevated RANKL expression. Conversely, CA showed low TRAP levels. FGF23 expression significantly increased during alcohol withdrawal (AW), while GPX decreased after chronic exposure but rose during withdrawal. Although mechanical strength changes were insignificant, biochemical shifts suggest alcohol exposure promotes bone resorption, reduces antioxidant protection, and potentially hampers active vitamin D and phosphate reabsorption via FGF23 upregulation.
Effects of Incorporating Ionic Crosslinking on 3D Printing of Biomass–Fungi Composite Materials
Authors: Rahman Al Mazedur , Akib Yeasir Mohammad , Bedsole Caleb Oliver , Pei Zhijian , Shaw Brian D. , Ufodike Chukwuzubelu Okenwa , Castell-Perez Elena
Published: July 2024

Biomass–fungi composite materials primarily consist of biomass particles (sourced from agricultural residues) and a network of fungal hyphae that bind the biomass particles together. These materials have potential applications across diverse industries, such as packaging, furniture, and construction. 3D printing offers a new approach to manufacturing parts using biomass–fungi composite materials, as an alternative to traditional molding-based methods. However, there are challenges in producing parts with desired quality (for example, geometric accuracy after printing and height shrinkage several days after printing) by using 3D printing-based methods. This paper introduces an innovative approach to enhance part quality by incorporating ionic crosslinking into the 3D printing-based methods. While ionic crosslinking has been explored in hydrogel-based bioprinting, its application in biomass–fungi composite materials has not been reported. Using sodium alginate (SA) as the hydrogel and calcium chloride as the crosslinking agent, this paper investigates their effects on quality (geometric accuracy and height shrinkage) of 3D printed samples and physiochemical characteristics (rheological, chemical, and texture properties) of biomass–fungi composite materials. Results show that increasing SA concentration led to significant improvements in both geometric accuracy and height shrinkage of 3D printed samples. Moreover, crosslinking exposure significantly enhanced hardness of the biomass–fungi mixture samples prepared for texture profile analysis, while the inclusion of SA notably improved cohesiveness and springiness of the biomass–fungi mixture samples. Furthermore, Fourier transform infrared spectroscopy confirms the occurrence of ionic crosslinking within 3D printed samples. Results from this study can be used as a reference for developing new biomass–fungi mixtures for 3D printing in the future.
Vehicle Behavior Discovery and Three-Dimensional Object Detection and Tracking Based on Spatio-Temporal Dependency Knowledge and Artificial Fish Swarm Algorithm
Authors: Chen Yixin , Li Qingnan
Published: July 2024

In complex traffic environments, 3D target tracking and detection are often occluded by various stationary and moving objects. When the target is occluded, its apparent characteristics change, resulting in a decrease in the accuracy of tracking and detection. In order to solve this problem, we propose to learn the vehicle behavior from the driving data, predict and calibrate the vehicle trajectory, and finally use the artificial fish swarm algorithm to optimize the tracking results. The experiments show that compared with the CenterTrack method, the proposed method improves the key indicators of MOTA (Multi-Object Tracking Accuracy) in 3D object detection and tracking on the nuScenes dataset, and the frame rate is 26 fps.
A Decomposition-Based Multi-Objective Flying Foxes Optimization Algorithm and Its Applications
Authors: Zhang Chen , Song Ziyun , Yang Yufei , Zhang Changsheng , Guo Ying
Published: July 2024

The flying foxes optimization (FFO) algorithm stimulated by the strategy used by flying foxes for subsistence in heat wave environments has shown good performance in the single-objective domain. Aiming to explore the effectiveness and benefits of the subsistence strategy used by flying foxes in solving optimization challenges involving multiple objectives, this research proposes a decomposition-based multi-objective flying foxes optimization algorithm (MOEA/D-FFO). It exhibits a great population management strategy, which mainly includes the following features. (1) In order to improve the exploration effectiveness of the flying fox population, a new offspring generation mechanism is introduced to improve the efficiency of exploration of peripheral space by flying fox populations. (2) A new population updating approach is proposed to adjust the neighbor matrices to the corresponding flying fox individuals using the new offspring, with the aim of enhancing the rate of convergence in the population. Through comparison experiments with classical algorithms (MOEA/D, NSGA-II, IBEA) and cutting-edge algorithms (MOEA/D-DYTS, MOEA/D-UR), MOEA/D-FFO achieves more than 11 best results. In addition, the experimental results under different population sizes show that the proposed algorithm is highly adaptable and has good application prospects in optimization problems for engineering applications.
Profiling of Organosulfur Compounds in Onions: A Comparative Study between LC-HRMS and DTD-GC-MS
Authors: González-de-Peredo Ana V. , Maroto Alicia , Barbero Gerardo F. , Memboeuf Antony
Published: July 2024

Onions are known not only for their culinary importance but also for their nutritional and health-promoting properties. Both properties are closely linked to their content of organosulfur compounds, which account for up to 5% of the dry weight of an onion. Given the importance of these compounds, suitable analytical methods are required for their study. Two techniques should be highlighted in this context: gas chromatography coupled to mass spectrometry (GC-MS), and liquid chromatography coupled to mass spectrometry (LC-MS). In this study, eight different onion varieties were analyzed using two distinct analytical techniques: direct thermal desorption–gas chromatography–mass spectrometry (DTD-GC-MS) and high-resolution mass spectrometry (HRMS) on an LC-ESI-QqTOF instrument. Each method identified different organosulfur compounds, with LC-HRMS targeting 15 non-volatile compounds, such as cysteine sulfoxides, and GC-MS targeting 18 volatiles, such as disulfides and trisulfides. The results obtained were studied using Pearson correlations and principal component analysis. No precise correlation was found between the initial organosulfur compounds in onions and their hydrolysates. Consequently, although GC is one of the most employed techniques in the scientific literature, the use of LC-HRMS or a combination of both techniques may offer a more comprehensive and accurate description of the metabolomic profile of onions.
Object Exploration and Manipulation in Infants at Typical vs. Elevated Likelihood for ASD: A Review
Authors: Focaroli Valentina , Taffoni Fabrizio , Velardi Andrea , Caravale Barbara , Keller Flavio
Published: July 2024

The present review considers the growing body of literature on fine motor skills in infants at elevated genetic likelihood (EL) for autism spectrum disorder (ASD). This area of study aims to identify crucial motor markers associated with the disorder, facilitating earlier and more accurate identification of ASD, using various experimental methodologies, including standardized assessments, observational measures, and technological tools. The reviewed evidence revealed distinct developmental trajectories in EL infants, marked by differences in fine motor skills and exploratory behaviors compared to typically developing infants. We discuss the developmental trajectory of fine motor skills in infants and their predictive value for later ASD diagnosis, highlighting the significance of fine motor skills as early indicators of ASD risk in infants and emphasizing the need for further research to elucidate their predictive value and underlying mechanisms.