bluuebunny/crossref_metadata_2025 huggingface dataset:
Protective Role of Sulforaphane against Physiological Toxicity of Triphenyltin in Common Carp (Cyprinus carpio haematopterus)
Authors: Wang Bingke , Zhang Chunnuan , Ma Jianshuang , Wang Yanhui , Zhang Ling , Yang Xingli , Jia Tao , Zhang Kaisong , Zhang Qin
Published: September 2024

This experiment mainly explored the protective role of sulforaphane (SFN) against physiological toxicity of triphenyltin (TPT) in Cyprinus carpio haematopterus. In total, 320 Fish (56.90 ± 0.40 g) were randomly divided into four groups with four replicates each. The control group was fed the basal diet, the TPT group (TPT) was exposed to 10 ng L−1 TPT on the basis of the control group, the SFN + TPT group (TPT + SFN) was fed a diet supplemented with 10 mg kg−1 SFN on the TPT group, and the SFN group (SFN) was fed a diet supplemented with 10 mg kg−1 SFN. After 56 days of breeding trials, the results showed that TPT exposure resulted in a remarkable decrease (p < 0.05) in final weight, weight gain rate (WGR), specific growth rate (SGR), and condition factor (CF), but an increase (p < 0.05) in feed conversion ratio (FCR) and hepatosomatic index (HSI) of fish. TPT treatment decreased (p < 0.05) the amounts of hematocrit (Hct) and hemoglobin (Hb), plasma complement component 3 (C3) and C4 contents, alternative complement pathway (ACH50), acid phosphatase (ACP) and lysozyme (LZM) activities, liver glutathione (GSH) content, catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPX) activities, interleukin 10 (IL-10), and SOD mRNA expressions, but increased (p < 0.05) plasma alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities, liver malonaldehyde (MDA) content, tumor Cyclooxygenase 2 (COX2), and necrosis factor α (TNFα), IL-1β, and MDA mRNA expressions. A histological analysis of the liver showed that a higher occurrence rates of the hepatocyte hypertrophy, nuclear disappearance and hepatocyte vacuolization was observed in the hepatocytes of fish exposed to TPT, and it was accompanied by the dilation of hepatic sinusoids. In addition, the toxicity induced by TPT was significantly improved in the groups that were treated with SFN, and SFN was able to improve growth performance and immunity, alleviate TPT-induced changes in inflammatory factors, ameliorate oxidative stress, and increase the activity of antioxidant enzymes (p < 0.05). The addition of SFN also alleviated liver damage caused by TPT and protected the structural integrity of the liver. Overall, these findings suggest that TPT inhibited the growth, immunity, and antioxidant capacity of Cyprinus carpio haematopteru. Dietary SFN could be beneficial for growth promotion, immunity, antioxidant capacity, and protection of liver structural integrity. Therefore, SFN is a prospective feed supplement for ameliorating the damage caused to fish by TPT contamination.
Effect of Curcumin Intake on Skeletal Muscle Oxygen Saturation Parameters in Older Participants
Authors: Ramos-Junior Olavo João Frederico , Pinheiro Vivian dos Santos , Souza Tatiane Gomes dos Santos de , Alvares Thiago Silveira
Published: September 2024

Introduction: Aging is associated with increased reactive oxygen species (ROS) and reduced bioavailability of nitric oxide (NO). Curcumin has been shown to increase NO bioavailability due to its ability to neutralize ROS, preventing oxidative stress. The present study aimed to investigate the effect of curcumin intake on skeletal muscle oxygen parameters and exercise tolerance in response to exercise in older people. Changes in circulating levels of NO metabolites were also investigated. Methods: Older subjects consumed 10 g of turmeric root extract from Curcuma longa L. (containing 95.33% of the total curcuminoids) or placebo in a randomized, double-blind, crossover study. A time of 2 h after ingestion, the participants performed one set of rhythmic handgrip exercise until the limit of tolerance, followed by 5 min of recovery. During exercise and exercise recovery, skeletal muscle oxygen saturation parameters were recorded. Results: During exercise, the amplitude of deoxyhemoglobin was greater after curcumin intake compared to placebo (CUR: 13.11 ± 9.52 vs. PLA: 10.22 ± 8.39 μM, p = 0.030). Furthermore, a faster skeletal muscle oxygen resaturation during exercise recovery was observed after curcumin compared to placebo (CUR: 1.01 ± 0.65 vs. PLA: 0.32 ± 0.20%.s−1, p = 0.004). These results were associated with significant changes in plasma nitrite (CUR: 6.82 ± 11.68 vs. PLA: −4.94 ± 17.28%, p = 0.028). There was no statistical difference in the total hemoglobin, exercise time until fatigue, and plasma nitrate between groups. Conclusions: The present study suggests that curcumin improves muscle oxygenation status at the capillary level in older adults by possibly improving muscle oxygen extraction and/or delivery, with no effect on exercise tolerance.
Application of Thermal Batteries in Greenhouses
Authors: Mousavi Ajarostaghi Seyed Soheil , Amiri Leyla , Poncet Sébastien
Published: September 2024

One of the key issues confronting modern greenhouses is the need to supply the necessary energy in an environmentally friendly manner to facilitate heating and cooling processes within greenhouses. Solar radiation entering the greenhouse during the day can sometimes be more than the energy demand of the greenhouse. In contrast, there are cases where the greenhouse must dissipate a significant amount of heat, absorbed over a long period, either naturally or forcibly, during the cooling process. Moreover, the system’s efficiency could be enhanced if there is a mechanism capable of capturing heat expelled during greenhouse cooling and redistributing it on demand. Employing thermal energy storage is critical for maintaining stable temperatures, assuring energy efficiency, encouraging sustainability, and enabling year-round production. This technique ensures a safe environment for crops and eliminates temperature fluctuations inside the greenhouse. Nocturnal thermal energy storage, storing thermal energy during the daytime for later use at night, is essential to managing a contemporary greenhouse because it promotes consistent crop growth, sustainability, and profitability, particularly in areas with severe winters and significant day-to-night temperature variations. This work reviews various types of thermal energy storage systems employed in previous works focusing on greenhouse applications by researchers and categorizes them based on efficient factors.
Transformer-Based High-Speed Train Axle Temperature Monitoring and Alarm System for Enhanced Safety and Performance
Authors: Li Wanyi , Xie Kun , Zou Jinbai , Huang Kai , Mu Fan , Chen Liyu
Published: September 2024

As the fleet of high-speed rail vehicles expands, ensuring train safety is of the utmost importance, emphasizing the critical need to enhance the precision of axel temperature warning systems. Yet, the limited availability of data on the unique features of high thermal axis temperature conditions in railway systems hinders the optimal performance of intelligent algorithms in alarm detection models. To address these challenges, this study introduces a novel dynamic principal component analysis preprocessing technique for tolerance temperature data to effectively manage missing data and outliers. Furthermore, a customized generative adversarial network is devised to generate distinct data related to high thermal axis temperature, focusing on optimizing the network’s objective functions and distinctions to bolster the efficiency and diversity of the generated data. Finally, an integrated model with an optimized transformer module is established to accurately classify alarm levels, provide a comprehensive solution to pressing train safety issues, and, in a timely manner, notify drivers and maintenance departments (DEPOs) of high-temperature warnings.
A Methodology Based on Deep Learning for Contact Detection in Radar Images
Authors: Gonzales Martínez Rosa , Moreno Valentín , Rotta Saavedra Pedro , Chinguel Arrese César , Fraga Anabel
Published: September 2024

Ship detection, a crucial task, relies on the traditional CFAR (Constant False Alarm Rate) algorithm. However, this algorithm is not without its limitations. Noise and clutter in radar images introduce significant variability, hampering the detection of objects on the sea surface. The algorithm’s theoretically Constant False Alarm Rates are not upheld in practice, particularly when conditions change abruptly, such as with Beaufort wind strength. Moreover, the high computational cost of signal processing adversely affects the detection process’s efficiency. In previous work, a four-stage methodology was designed: The first preprocessing stage consisted of image enhancement by applying convolutions. Labeling and training were performed in the second stage using the Faster R-CNN architecture. In the third stage, model tuning was accomplished by adjusting the weight initialization and optimizer hyperparameters. Finally, object filtering was performed to retrieve only persistent objects. This work focuses on designing a specific methodology for ship detection in the Peruvian coast using commercial radar images. We introduce two key improvements: automatic cropping and a labeling interface. Using artificial intelligence techniques in automatic cropping leads to more precise edge extraction, improving the accuracy of object cropping. On the other hand, the developed labeling interface facilitates a comparative analysis of persistence in three consecutive rounds, significantly reducing the labeling times. These enhancements increase the labeling efficiency and enhance the learning of the detection model. A dataset consisting of 60 radar images is used for the experiments. Two classes of objects are considered, and cross-validation is applied in the training and validation models. The results yield a value of 0.0372 for the cost function, a recovery rate of 94.5%, and an accuracy rate of 95.1%, respectively. This work demonstrates that the proposed methodology can generate a high-performance model for contact detection in commercial radar images.
Interruption Cost Estimation for Value-Based Reliability Investment in Emerging Smart Grid Resources
Authors: Bhattarai Shandesh , Karki Rajesh
Published: September 2024

Growing uncertainty in supply and demand in power systems causes significant challenges in maintaining supply reliability at affordable costs. Power grids are expected to undergo substantial transformations to address these challenges with upgrades and integration of emerging smart technologies that require significant investment costs. A value-based reliability assessment of these grid technologies is necessary to justify the worth of these investments. A key parameter required in such an assessment is the cost of power interruptions originating from transmission system failures. The interruption cost data available in published reports and past surveys relate to generation inadequacy since generation facilities comprise the most capital-intensive investment of an electric utility. Customer interruptions due to a lack of generation mainly occur due to generation failures during the peak demand period, whereas interruptions due to transmission component failures can occur at other periods with specific probabilities. This paper presents a methodology to estimate the cost of outages originating from transmission asset failures, which proposes a sector period model for each customer sector to obtain associated demand-normalized interruption costs. The proposed method can also be used to decide investment in grid resiliency enhancement against extreme weather that mainly impacts the grid network facilities.
Authentication of a Painting Attributed to the Rembrandt School
Authors: Sandu Ion , Drobota Vasile , Drob Ana , Sandu Andrei Victor , Vasilache Viorica , Iurcovschi Cosmin Tudor , Sandu Ioan Gabriel
Published: September 2024

This paper presents the archaeometric and chemometric authentication of a Renaissance-style oil painting on linen canvas, with plaster and barium sulphate-based primer preparation and bone glue as binder. By optical microscopy (OM), stereomicroscopy (SOM), scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX) and attenuated total reflectance–Fourier transform infrared spectroscopy (ATR-FTIR), a series of archaeometric characteristics were identified: the grain size of the chemical components of the paint layers, the 3D porosity distribution of the pigments, the degree of penetration between the paint layers and the varnish and between the varnish and the oxidatively anchored dirt, and the typology of the craquelure (craquelure network arrangement and morphology). By correlating the results obtained, it was possible to estimate the period of the painting as 1660 ± 3 years.
Assessment of the Impact of Heat-Compression Therapy Time on Muscle Biomechanical Properties and Forearm Tissue Perfusion in MMA Fighters—A Pilot Study
Authors: Kużdżał Adrian , Muracki Jarosław , Makar Piotr , Roczniok Robert , Studnicki Rafał , Pożarowszczyk-Kuczko Beata , Kawczyński Adam , Trybulski Robert
Published: September 2024

Background: The study aimed to evaluate the immediate effect of Heat-Compression-Therapy with Game Ready equipment (GR-HCT) on biomechanical properties at different treatment times. Reducing the duration of stimulation through HCT can help optimize recovery processes in sports. Methods: Twenty male MMA fighters (26.5 ± 4.5 years, BMI 24.75 ± 3.0, training experience: 10.3 ± 5.0 years) performed two experimental sessions: (a) 5 min heat-compression therapy (HCT) stimulation (GR-HCT-5); and (b) 10 min heat-compression therapy (GR-HCT-10). All registered parameters, tissue perfusion (PU), tissue temperature (°C), muscle tone (T-Hz) stiffness (S—N/m), elasticity (E—arb), pressure pain threshold (PPT—N/cm) and isometric muscle strength (Fmax—kgf), were measured at rest (r—2 min before GR-HCT stimulation) and 1 min after GR-HCT (p-post) for the flexor carpi radialis muscle (MFCR) and the brachioradialis muscle (MBR). Results: The Friedman’s test for MBR revealed significant differences between GR-HCT5min vs. GR-HCT10min for PU (p < 0.0001), S (p = 0.008), and for MBR and MFCR for °C (p < 0.0001). The pairwise comparisons for PU, S, and °C showed significant differences between rest vs. post values for 5 min as well as between rest vs. post values for 10 min. Further, there was a significant interaction effect (5 min-10 min × Rest-Post p < 0.0001) for PU for MFCR. The post hoc comparison for the interaction effect showed significantly higher PU for post- compared to premeasurement in 5 min PU and 10 min PU (p < 0.001). Further, there was a significant main effect of condition for Fmax both for MFCR and MBR (5 min vs. 10 min p < 0.001); The post hoc comparison for the main effect of condition showed a significantly higher Fmax for post- compared to premeasurement in 5 min and 10 min (p < 0.001). Further, there was a significant main effect of condition for pressure pain threshold [N/cm] both for MFCR and MBR and for T for MBR time of measurement rest vs. post (p < 0.001; p = 0.006; p < 0.001, respectively). The post hoc comparison for the interaction effect showed a significantly lower PPT for post vs. rest in 5 min (p < 0.001 only for MFCR) and in 10 min (p < 0.001). The delta values for PU (post-rest) and ΔTemp °C showed significant differences between the 5 min and 10 min conditions (MFCR; p < 0.0001); (MBR p < 0.001) and (MFCR p < 0.0001); (MBR p < 0.001). Conclusion: Our results show that GR-HCT significantly affects recovery of muscle biomechanical parameters, pain threshold, strength, tissue perfusion, and temperature. Our findings show that a 5 min effect can be sufficient when compared to a 10 min one which is a clue for designing effective recovery protocols.
Investigating the Use of Differential Scanning Calorimetry in the Prediction of Part Properties in the High-Speed Sintering Process
Authors: Brown Ryan , Holden Alfred , Majewski Candice
Published: September 2024

High-speed sintering (HSS) is an additive manufacturing (AM) technique with high potential for end-use products. Previous research has identified differential scanning calorimetry (DSC) as being a viable method for evaluating the mechanical performance of parts manufactured using the (similar) laser sintering (LS) process through the determination of the degree of particle melt (DPM). This research expands this to demonstrate the applicability of DPM measurement to the HSS process, demonstrating a clear linear correlation between tensile properties and DPM. The DPM increased from 64.9% to 75.8% as sinter speed was reduced from 180 mm/s to 140 mm/s (a slower speed providing a higher energy input), with the ultimate tensile strength approximately doubling over this range. High coefficients of determination (>0.9) indicate that the DPM is a strong indicator of tensile properties, demonstrating the potential for DPM measurements as quality assessment tools for the HSS process.
Seismic Design and Analysis of a Cold-Formed Steel Exoskeleton for the Retrofit of an RC Multi-Story Residential Building
Authors: Meglio Emilia , Formisano Antonio
Published: September 2024

The awareness of the vulnerability of existing structures under both seismic and energy perspectives highlights the need for integrated retrofit solutions that combine structural and thermal enhancements. From this perspective, this study explored the efficacy of the Resisto 5.9 Tube system, which is a seismic retrofit solution for masonry and reinforced concrete (RC) structures that also improves the energy performance by integrating a thermal coat integrated within its basic steel framework. This research involved application to a RC building of a design procedure specifically developed for this system that was aimed at facilitating its adoption by designers involved in seismic retrofitting analysis. After designing the system components, nonlinear static analyses were performed using finite element software to compare the building’s seismic performance before and after the application of the Resisto 5.9 Tube. The results demonstrate a significant increase in the seismic safety coefficient ζE from 0.26 to 0.42, which proved the potential of this intervention to enhance the seismic safety of existing RC buildings.
Numerical Modeling of Plasticity in Metal Matrix Fiber Composites
Authors: Lvov Gennadiy , Tănase Maria
Published: September 2024

This paper presents micromechanical analyses of an orthogonally reinforced composite with new constitutive equations of kinematic plastic hardening. The homogenization of plastic properties was performed through a numerical analysis of a representative volume using the finite element method. A modification of Prager’s theory was used to construct physical relations for an equivalent orthotropic material. In the proposed version of the theory, a special tensor for back stresses is introduced, which takes into account the difference in the rate of hardening for different types of plastic deformation. For boron–aluminum orthogonally reinforced composite with known mechanical properties of fibers and matrix, all material parameters of the theory were determined, deformation diagrams were constructed, and the equation for a plasticity surface in a six-dimensional stress space was obtained. The advantage of the developed method of numerical homogenization is that it only requires a minimal amount of experimental data. The efficiency of micromechanical analysis makes it possible to optimally design metal matrix composites with the required plastic properties.
Research on a High-Precision Interventional Pressure Measurement Catheter with a Compact Structure for In Vivo Pressure Monitoring
Authors: Wang Bo , Jiang Senran , Cui Yao , Li Zhonghua , Wang Fuji , Liu Qiang , Yang Xing
Published: September 2024

This paper proposes a high-precision interventional pressure measurement catheter with a compact structure for in vivo pressure monitoring. This catheter uses a minimally invasive testing method, and the proposed compact structure reduces pressure loss caused by fluid movement inside the catheter, ensuring accuracy in dynamically varying pressure measurements. The paper conducts a theoretical analysis of the pressure transmission process inside the catheter, fabricates a prototype, and establishes both dynamic and static pressure testing systems. Through experimental research on the effects of the catheter’s dimensions on the accuracy of dynamically varying pressure measurements, it demonstrates that the compact pressure measurement catheter can effectively enhance the precision of dynamically varying pressure measurements. The catheter offers high precision, small size, and simple manufacturing processes. It holds promising applications in fields such as in-body pressure measurement and microfluidic system monitoring.
DeepESN Neural Networks for Industrial Predictive Maintenance through Anomaly Detection from Production Energy Data
Authors: Bonci Andrea , Fredianelli Luca , Kermenov Renat , Longarini Lorenzo , Longhi Sauro , Pompei Geremia , Prist Mariorosario , Verdini Carlo
Published: September 2024

Optimizing energy consumption is an important aspect of industrial competitiveness, as it directly impacts operational efficiency, cost reduction, and sustainability goals. In this context, anomaly detection (AD) becomes a valuable methodology, as it supports maintenance activities in the manufacturing sector, allowing for early intervention to prevent energy waste and maintain optimal performance. Here, an AD-based method is proposed and studied to support energy-saving predictive maintenance of production lines using time series acquired directly from the field. This paper proposes a deep echo state network (DeepESN)-based method for anomaly detection by analyzing energy consumption data sets from production lines. Compared with traditional prediction methods, such as recurrent neural networks with long short-term memory (LSTM), although both models show similar time series trends, the DeepESN-based method studied here appears to have some advantages, such as timelier error detection and higher prediction accuracy. In addition, the DeepESN-based method has been shown to be more accurate in predicting the occurrence of failure. The proposed solution has been extensively tested in a real-world pilot case consisting of an automated metal filter production line equipped with industrial smart meters to acquire energy data during production phases; the time series, composed of 88 variables associated with energy parameters, was then processed using the techniques introduced earlier. The results show that our method enables earlier error detection and achieves higher prediction accuracy when running on an edge device.
MD-TransUNet: An Image Segmentation Network for Car Front Face Design
Authors: Ouyang Jinyan , Shi Hongru , Su Jianning , Zhang Shutao , Zhou Aimin
Published: September 2024

To enhance the segmentation accuracy of car front face elements such as headlights and grilles for car front face design, and to improve the superiority and efficiency of solutions in automotive partial modification design, this paper introduces MD-TransUNet, a semantic segmentation network based on the TransUNet model. MD-TransUNet integrates multi-scale attention gates and dynamic-channel graph convolution networks to enhance image restoration across various design drawings. To improve accuracy and detail retention in segmenting automotive front face elements, dynamic-channel graph convolution networks model global channel relationships between contextual sequences, thereby enhancing the Transformer’s channel encoding capabilities. Additionally, a multi-scale attention-based decoder structure is employed to restore feature map dimensions, mitigating the loss of detail in the local feature encoding by the Transformer. Experimental results demonstrate that the MSAG module significantly enhances the model’s ability to capture details, while the DCGCN module improves the segmentation accuracy of the shapes and edges of headlights and grilles. The MD-TransUNet model outperforms existing models on the automotive front face dataset, achieving mF-score, mIoU, and OA metrics of 95.81%, 92.08%, and 98.86%, respectively. Consequently, the MD-TransUNet model increases the precision of automotive front face element segmentation and achieves a more advanced and efficient approach to partial modification design.
Impacts of Electrolyzed Water Treatments on Bioactive Compounds and Microbial and Visual Quality of Minimally Processed ‘Granny Smith’ Apples
Authors: Nyamende Nandi E. , Sigge Gunnar , Belay Zinash A. , Mpahleni Buhle , Caleb Oluwafemi J.
Published: September 2024

Ready-to-eat fresh-cut apples deteriorate rapidly in visual quality due to browning, leading to consumer rejection and food waste. In addition, minimal processing induces tissue damage and releases organic substrates, which could accelerate microbial growth. The present study evaluated the impacts of alkaline and acidic electrolyzed water (AIEW and AEW) on natural microbial load and bioactive compounds on fresh-cut ‘Granny Smith’ apples. Minimally processed apples were dipped for 10 min in AEW and AIEW solutions (200 mg L−1), packed in PET containers with lids, and stored for 9 days at 2 °C. Overall, fresh-cut ‘Granny Smith’ apples treated with AEW significantly (p < 0.05) maintained higher total phenolics (99.4 ± 4.3 mg GAE L−1) and antioxidant capacity (79.5 ± 6.5 mg VitCE L−1) compared to the non-treated control samples (42.9 ± 5.1 mg GAE L−1, 31.9 ± 8.1 mg GAE L−1, respectively). Similarly, pretreatment with AIEW maintained the highest total flavonol content (55.71 ± 1.5 mg QE L−1) compared to the AEW-treated samples and control (p < 0.05). AEW pretreatment led to a 2 Log and a 1 Log decline in total aerobic mesophilic bacteria and yeasts and moulds, respectively. The best visual quality and highest visual score was maintained by AEW and followed by AIEW. This study further demonstrated the effectiveness of electrolyzed water treatments in minimizing browning and enhancing bioactive compounds in fresh-cut ‘Granny Smith’ apples.
Evaluation of Biodentine Tricalcium Silicate-Based Cement after Chlorhexidine Irrigation
Authors: Dąbrowska Katarzyna , Palatyńska-Ulatowska Aleksandra , Klimek Leszek
Published: September 2024

The effectiveness of biocements applied in specialistic endodontic procedures can be influenced by multiple factors, including the postplacement chemical action of the irrigating solution. This in vitro study aimed to assess the impact of 2% chlorhexidine digluconate on the surface structure and chemical composition of Biodentine as a perforation repair cement. A total of 54 Biodentine specimens were prepared with strict adherence to the manufacturer’s instructions and irrigated with 2% chlorhexidine with or without ultrasonic activation. The material specimens were divided into three setting-time-based groups: group A—rinsed after 12 min of setting, group B—after 45 min, and group C—after 24 h. The control group was not subjected to any irrigation protocol. The evaluation of the microappearance of biocement surface was performed with the aid of a scanning electron microscope (SEM). The chemical composition of Biodentine was analyzed with the energy dispersive spectroscopy (EDS) method. The SEM images of the specimens in group B and C revealed a heterogeneous and layered surface morphology. The EDS results are comparable between pairs of cement specimens in both groups: after 5 min and 20 min CHX irrigation as well as after 5 min and 20 min ultrasonically activated CHX irrigation. To conclude, the 12 min Biodentine setting time is not recommended when used in perforation closure. Irrigation protocol involving 2% chlorhexidine visibly affected the tested material surface. The EDS results did not confirm any significant changes in Biodentine chemical composition. Further research is required to analyze the influence of the observed changes on the outcome of the endodontic treatment.
Designed Segregation: Racial Space and Social Reform in San Juan’s Casa de Beneficencia
Authors: Niell Paul Barrett
Published: September 2024

In the 1840s, San Juan, Puerto Rico witnessed the construction of an institutional building dedicated to “beneficencia” (social welfare)—the Casa de Beneficencia. This facility sheltered a diverse population, including orphaned children, women, the mentally ill, and the unhoused. An early plan of the architectural complex by Spanish engineer Santiago Cortijo reveals a design emphasizing bilateral symmetry, clear spatial organization, and functionality for housing residents, shaping their daily routines and assigning them work tasks. Notably, Cortijo’s plan divided wards not only by gender and age but also by race, with separate spaces designated for “blancas/os” (whites) and “gentes de color” (people of color). This article examines the social delineations of Cortijo’s plan and explores the implications of a building that functioned as a nineteenth-century institution dedicated to reformist ideas of social welfare within San Juan’s colonial context, paying close attention to its embedded racial and gendered order.
Capital Asset Pricing Model and Ordered Weighted Average Operator for Selecting Investment Portfolios
Authors: Uzeta-Obregon Cristhian R. , Garcia-Gastelum Tanya S. , Alvarez Pavel A. , Mellado-Cid Cristhian , Blanco-Mesa Fabio , Leon-Castro Ernesto
Published: September 2024

The main objective of this article is to present the formulation of a Capital Asset Pricing Model ordered weighted average CAPMOWAand its extensions, called CAPM-induced OWA (CAPMIOWA), CAPM Bonferroni OWA (CAPMBon-OWA), and CAPM Bonferroni-induced OWA CAPMBon-IOWA. A step-by-step process for applying this new proposal in a real case of formulating investment portfolios is generated. These methods show several scenarios, considering the attitude, preferences, and relationship of each argument, when underestimation or overestimation of the information by the decision maker may influence the decision-making process regarding portfolio investments. Finally, the complexity of the method and the incorporation of soft information into the modeling process lead to generating a greater number of scenarios and reflect the attitudes and preferences of decision makers.
On the Torsional Energy of Deformed Curves and Knots
Authors: Rančić Svetozar R. , Velimirović Ljubica S. , Najdanović Marija S.
Published: September 2024

This paper deals with the study of torsional energy (total squared torsion) at infinitesimal bending of curves and knots in three dimensional Euclidean space. During bending, the curve is subject to change, and its properties are changed. The effect that deformation has on the curve is measured by variations. Here, we observe the infinitesimal bending of the second order and variations of the first and the second order that occur in this occasion. The subjects of study are curves and knots, in particular torus knots. We analyze various examples both analytically and graphically, using our own calculation and visualization software tool.
A Review on Design Parameters for the Full-Cell Lithium-Ion Batteries
Authors: Ghani Faizan , An Kunsik , Lee Dongjin
Published: September 2024

The lithium-ion battery (LIB) is a promising energy storage system that has dominated the energy market due to its low cost, high specific capacity, and energy density, while still meeting the energy consumption requirements of current appliances. The simple design of LIBs in various formats—such as coin cells, pouch cells, cylindrical cells, etc.—along with the latest scientific findings, trends, data collection, and effective research methods, has been summarized previously. These papers addressed individual design parameters as well as provided a general overview of LIBs. They also included characterization techniques, selection of new electrodes and electrolytes, their properties, analysis of electrochemical reaction mechanisms, and reviews of recent research findings. Additionally, some articles on computer simulations and mathematical modeling have examined the design of full-cell LIBs for power grid and electric vehicle applications. To fully understand LIB operation, a simple and concise report on design parameters and modification strategies is essential. This literature aims to summarize the design parameters that are often overlooked in academic research for the development of full-cell LIBs.
Stepwise Corrected Attention Registration Network for Preoperative and Follow-Up Magnetic Resonance Imaging of Glioma Patients
Authors: Feng Yuefei , Zheng Yao , Huang Dong , Wei Jie , Liu Tianci , Wang Yinyan , Liu Yang
Published: September 2024

The registration of preoperative and follow-up brain MRI, which is crucial in illustrating patients’ responses to treatments and providing guidance for postoperative therapy, presents significant challenges. These challenges stem from the considerable deformation of brain tissue and the areas of non-correspondence due to surgical intervention and postoperative changes. We propose a stepwise corrected attention registration network grounded in convolutional neural networks (CNNs). This methodology leverages preoperative and follow-up MRI scans as fixed images and moving images, respectively, and employs a multi-level registration strategy that establishes a precise and holistic correspondence between images, from coarse to fine. Furthermore, our model introduces a corrected attention module into the multi-level registration network that can generate an attention map at the local level through the deformation fields of the upper-level registration network and pathological areas of preoperative images segmented by a mature algorithm in BraTS, serving to strengthen the registration accuracy of non-correspondence areas. A comparison between our scheme and the leading approach identified in the MICCAI’s BraTS-Reg challenge indicates a 7.5% enhancement in the target registration error (TRE) metric and improved visualization of non-correspondence areas. These results illustrate the better performance of our stepwise corrected attention registration network in not only enhancing the registration accuracy but also achieving a more logical representation of non-correspondence areas. Thus, this work contributes significantly to the optimization of the registration of brain MRI between preoperative and follow-up scans.
Between Two Worlds: Investigating the Intersection of Human Expertise and Machine Learning in the Case of Coronary Artery Disease Diagnosis
Authors: Apostolopoulos Ioannis D. , Papandrianos Nikolaos I. , Apostolopoulos Dimitrios J. , Papageorgiou Elpiniki
Published: September 2024

Coronary artery disease (CAD) presents a significant global health burden, with early and accurate diagnostics crucial for effective management and treatment strategies. This study evaluates the efficacy of human evaluators compared to a Random Forest (RF) machine learning model in predicting CAD risk. It investigates the impact of incorporating human clinical judgments into the RF model’s predictive capabilities. We recruited 606 patients from the Department of Nuclear Medicine at the University Hospital of Patras, Greece, from 16 February 2018 to 28 February 2022. Clinical data inputs included age, sex, comprehensive cardiovascular history (including prior myocardial infarction and revascularisation), CAD predisposing factors (such as hypertension, dyslipidemia, smoking, diabetes, and peripheral arteriopathy), baseline ECG abnormalities, and symptomatic descriptions ranging from asymptomatic states to angina-like symptoms and dyspnea on exertion. The diagnostic accuracies of human evaluators and the RF model (when trained with datasets inclusive of human judges’ assessments) were comparable at 79% and 80.17%, respectively. However, the performance of the RF model notably declined to 73.76% when human clinical judgments were excluded from its training dataset. These results highlight a potential synergistic relationship between human expertise and advanced algorithmic predictions, suggesting a hybrid approach as a promising direction for enhancing CAD diagnostics.
The Use of Mesenchymal Stem/Stromal Cell-Derived Extracellular Vesicles in the Treatment of Osteoarthritis: Insights from Preclinical Studies
Authors: Jones Mitch , Jones Elena , Kouroupis Dimitrios
Published: September 2024

Osteoarthritis (OA) is a prominent cause of disability, and has severe social and economic ramifications across the globe. The main driver of OA’s pervasiveness is the fact that no current medical interventions exist to reverse or even attenuate the degeneration of cartilage within the articular joint. Crucial for cell-to-cell communication, extracellular vesicles (EVs) contribute to OA progression through the delivery of bioactive molecules in the inflammatory microenvironment. By repurposing this acellular means of signal transmission, therapeutic drugs may be administered to degenerated cartilage tissue in the hopes of encouraging regeneration. Positive outcomes are apparent in in vivo studies on this subject; however, for this therapy to prove itself in the clinical world, efforts towards standardizing the characterization, application, biological contents, and dosage are essential.
Pediatric Intensive Care Unit Length of Stay Prediction by Machine Learning
Authors: Ganatra Hammad A. , Latifi Samir Q. , Baloglu Orkun
Published: September 2024

Purpose: To develop and validate machine learning models for predicting the length of stay (LOS) in the Pediatric Intensive Care Unit (PICU) using data from the Virtual Pediatric Systems (VPS) database. Methods: A retrospective study was conducted utilizing machine learning (ML) algorithms to analyze and predict PICU LOS based on historical patient data from the VPS database. The study included data from over 100 North American PICUs spanning the years 2015–2020. After excluding entries with missing variables and those indicating recovery from cardiac surgery, the dataset comprised 123,354 patient encounters. Various ML models, including Support Vector Machine, Stochastic Gradient Descent Classifier, K-Nearest Neighbors, Decision Tree, Gradient Boosting, CatBoost, and Recurrent Neural Networks (RNNs), were evaluated for their accuracy in predicting PICU LOS at thresholds of 24 h, 36 h, 48 h, 72 h, 5 days, and 7 days. Results: Gradient Boosting, CatBoost, and RNN models demonstrated the highest accuracy, particularly at the 36 h and 48 h thresholds, with accuracy rates between 70 and 73%. These results far outperform traditional statistical and existing prediction methods that report accuracy of only around 50%, which is effectively unusable in the practical setting. These models also exhibited balanced performance between sensitivity (up to 74%) and specificity (up to 82%) at these thresholds. Conclusions: ML models, particularly Gradient Boosting, CatBoost, and RNNs, show moderate effectiveness in predicting PICU LOS with accuracy slightly over 70%, outperforming previously reported human predictions. This suggests potential utility in enhancing resource and staffing management in PICUs. However, further improvements through training on specialized databases can potentially achieve better accuracy and clinical applicability.
Untargeted Metabolomic Profiling of Extracellular Vesicles Isolated from Human Seminal Plasma
Authors: Panner Selvam Manesh Kumar , Chandra Partha K. , Bakhtiary Zahra , Busija David W. , Sikka Suresh C.
Published: September 2024

Seminal extracellular vesicles (SemEVs) are repositories of biomolecules, including metabolites involved in the regulation of sperm function. The correlation between the metabolite profile of SemEVs and semen parameters, along with their role in regulating sperm function, is an unexplored area. This preliminary study evaluated the metabolomic content of SemEVs. Semen samples were obtained from 18 healthy men, and SemEVs were extracted from seminal plasma using the size exclusion chromatography qEV Gen 2–35 nm column coupled with an automatic fraction collector. The physical characterization of SemEVs was carried out with the ZetaView PMX-430-Z QUATT laser system. EV protein markers were detected using Western blot. In addition, these SemEVs were used for metabolomic profiling and functional bioinformatic analysis. The mean concentration of isolated SemEVs was 1.7 ± 1.1 × 1011/mL of seminal plasma, whereas SemEVs size and zeta potential were 129.5 ± 5.5 nm and −40.03 ± 3.99 mV, respectively. Western blot analysis confirmed the presence of EV specific markers such as CD81, ALIX, and TSG101. A total of 107 metabolites were identified using this untargeted metabolomic approach in SemEVs. Bioinformatics analysis further revealed that metabolites associated with tyrosine metabolism were highly enriched in these SemEVs. Ingenuity Pathway Analysis (IPA) also indicated that these metabolites present in SemEVs were involved in the regulation of the free radical scavenging pathway. Furthermore, our metabolomic results suggest that these SemEV-associated metabolites may play a pivotal role in the maintenance of seminal plasma redox homeostasis.
Assessment and Monitoring of the Wound Micro-Environment in Chronic Wounds Using Standardized Wound Swabbing for Individualized Diagnostics and Targeted Interventions
Authors: Rembe Julian-Dario , Garabet Waseem , Lackmann Jan-Wilm , Alizadehrahrouei Sadaf , Augustin Matthias , Dissemond Joachim , Ibing Wiebke , Köhrer Karl , Pfeffer Klaus , Rommerskirchen Anna , Scharf Sebastian Alexander , Wienemann Tobias , Wachtmeister Thorsten , Schelzig Hubert , Stuermer Ewa Klara
Published: September 2024

Background/Objectives: Patient-specific diagnostic and therapeutic approaches are important in the care of people with chronic wounds. The heterogeneity of underlying disease profiles and the diversity of the wound micro-environment make generalized approaches difficult. While high-throughput molecular diagnostic methods are increasingly widespread and available, the analysis of objective biomolecular disease patterns has not found its way into everyday wound management. The aim of this study is to evaluate the use of wound swab samples for the analysis of biomarkers and disease patterns in people with chronic wounds. Methods: A sample cohort from the multicenter “Wound-BIOME” project was analyzed. The project aims to comprehensively investigate the local micro-environment of chronic wounds of various entities, healing tendencies and regeneration stages at the biomolecular level. A sample collection and handling protocol suitable for everyday use was tested and evaluated regarding feasibility for multiplex immunoassay, proteomics, small RNA sequencing (miRNA) and metagenome analyses (microbiomics). Results: It could be shown that standard wound swabs are well-suited for the analysis of the complex wound micro-environment using various high-throughput methods. Despite the sample heterogeneity, the quality was adequate to analyze biomolecular patterns. Conclusions: Initial analyses of protein signatures, microbial wound communities and miRNA patterns show promising results for future individualized diagnostics and targeted interventions.
Soluble Glycoprotein VI Levels Assessed Locally within the Extra- and Intracerebral Circulation in Hyper-Acute Thromboembolic Stroke: A Pilot Study
Authors: Starke Andreas , Kollikowski Alexander M. , Vogt Vivian , Stoll Guido , Nieswandt Bernhard , Pham Mirko , Stegner David , Schuhmann Michael K.
Published: September 2024

Background: Severe acute ischemic stroke (AIS) is mainly caused by thromboembolism originating from symptomatic carotid artery (ICA) stenosis or in the heart due to atrial fibrillation. Glycoprotein VI (GPVI), a principal platelet receptor, facilitates platelet adherence and thrombus formation at sites of vascular injury such as symptomatic ICA stenosis. The shedding of GPVI from the platelet surface releases soluble GPVI (sGPVI) into the circulation. Here, we aimed to determine whether sGPVI can serve as a local biomarker to differentiate between local atherosclerotic and systemic cardiac thromboembolism in AIS. Methods: We conducted a cohort study involving 105 patients undergoing emergency endovascular thrombectomy (EVT) for anterior circulation stroke. First, sGPVI concentrations were measured in systemic arterial plasma samples collected at the ipsilateral ICA level, including groups with significantly (≥50%) stenotic and non-stenotic arteries. A second sample, taken from the intracerebral pial circulation, was used to assess GPVI shedding locally within the ischemic brain. Results: Our analysis revealed no significant increase in systemic sGPVI levels in patients with symptomatic ≥ 50% ICA stenosis (3.2 [95% CI 1.5–5.0] ng/mL; n = 33) compared with stroke patients without significant ICA stenosis (3.2 [95% CI 2.3–4.2] ng/mL; n = 72). Additionally, pial blood samples, reflecting intravascular molecular conditions during collateral flow, showed similar sGPVI levels when compared to the systemic ICA samples in both groups. Conclusions: Our findings indicate that GPVI is not locally cleaved and shed into the bloodstream in significant amounts during hyper-acute ischemic stroke, neither at the level of symptomatic ICA nor intracranially during collateral blood supply. Therefore, sGPVI does not appear to be suitable as a local stroke biomarker despite strong evidence of a major role for GPVI-signaling in stroke pathophysiology.
Harnessing CRISPR/Cas Systems for DNA and RNA Detection: Principles, Techniques, and Challenges
Authors: Son Heyjin
Published: September 2024

The emergence of CRISPR/Cas systems has revolutionized the field of molecular diagnostics with their high specificity and sensitivity. This review provides a comprehensive overview of the principles and recent advancements in harnessing CRISPR/Cas systems for detecting DNA and RNA. Beginning with an exploration of the molecular mechanisms of key Cas proteins underpinning CRISPR/Cas systems, the review navigates the detection of both pathogenic and non-pathogenic nucleic acids, emphasizing the pivotal role of CRISPR in identifying diverse genetic materials. The discussion extends to the integration of CRISPR/Cas systems with various signal-readout techniques, including fluorescence, electrochemical, and colorimetric, as well as imaging and biosensing methods, highlighting their advantages and limitations in practical applications. Furthermore, a critical analysis of challenges in the field, such as target amplification, multiplexing, and quantitative detection, underscores areas requiring further refinement. Finally, the review concludes with insights into the future directions of CRISPR-based nucleic acid detection, emphasizing the potential of these systems to continue driving innovation in diagnostics, with broad implications for research, clinical practice, and biotechnology.