bluuebunny/crossref_metadata_2025 huggingface dataset:
Microseism Detection Method in Coal Mine Based on Spatiotemporal Characteristics and Support Vector Regression Algorithm
Authors: Gao Hong , Mu Chaomin , Sun Hui
Published: September 2023

In view of the inconsistency of guided wave energy in distributed acoustic sensing coal mine maps and the difficulty in distinguishing the vibration levels of coal mines, which leads to the poor sensitivity and accuracy of microseism detection, a coal mine microseism detection method based on time–space characteristics and a support vector regression algorithm is proposed to ensure the safety of coal mine operations. The spatiotemporal sliding window was used to collect the coal mine data in real-time, and the continuous attribute discretization algorithm based on entropy was used to discretize the coal mine data, then the data were mapped to different state spaces to build a Markov chain; by calculating the state transition probability matrix and the cross-state probability transition matrix, respectively, the temporal and spatial characteristics of the coal mine microseisms at the target node were extracted. The extracted spatiotemporal characteristics of the coal mine microseisms were used as the input to the particle-swarm-optimization-improved support vector regression model, and the regression solution results of the coal mine microseism detection signals were output. The error penalty factor and kernel function parameters were improved, and the particle swarm optimization algorithm was introduced to optimize the detection results of microseisms in coal mines. The experimental results showed that this method can accurately and detect in real-time the microseisms in coal mines in the mining area, can effectively control the rate of missing detections in the detection process, and can ensure the stability of the overall detection operation. When the inertia weight was set at 0.9 and the number of particles was 45, this method had the highest sensitivity and the best-detection accuracy for microseisms in coal mines.
Dynamic Effect of the Earth Fissure Sites in the Yuncheng Basin, China
Authors: Cao Ge , Deng Yahong , Chang Jiang , Xuan You , He Nainan , Mu Huandong
Published: September 2023

Earth fissures are widely distributed worldwide, and the Fenwei Basin in China is one of the regions with the most significant number and scale of fissures in the world. The Yuncheng Basin is an important constituent basin of the Fenwei Basin in China, where earth fissures are densely developed and cause severe damage. In particular, the impact of earth fissures on the seismic response of the site is still unknown and is an urgent problem that needs to be solved. Based on microtremor tests, three types of typical earth fissure sites in the Yuncheng Basin were selected for field testing. Through spectrum analysis, the dynamic response characteristics of the earth fissure sites were determined. The results show that the dynamic response of the site is significantly affected by the earth fissures. The dynamic response strength of the site is the largest on both sides of the earth fissures, and it decreases and gradually stabilizes with increasing distance from the fissures. The influence range of the earth fissures on the hanging side is slightly longer than the heading side.
Encoder–Decoder Structure Fusing Depth Information for Outdoor Semantic Segmentation
Authors: Chen Songnan , Tang Mengxia , Dong Ruifang , Kan Jiangming
Published: September 2023

The semantic segmentation of outdoor images is the cornerstone of scene understanding and plays a crucial role in the autonomous navigation of robots. Although RGB–D images can provide additional depth information for improving the performance of semantic segmentation tasks, current state–of–the–art methods directly use ground truth depth maps for depth information fusion, which relies on highly developed and expensive depth sensors. Aiming to solve such a problem, we proposed a self–calibrated RGB-D image semantic segmentation neural network model based on an improved residual network without relying on depth sensors, which utilizes multi-modal information from depth maps predicted with depth estimation models and RGB image fusion for image semantic segmentation to enhance the understanding of a scene. First, we designed a novel convolution neural network (CNN) with an encoding and decoding structure as our semantic segmentation model. The encoder was constructed using IResNet to extract the semantic features of the RGB image and the predicted depth map and then effectively fuse them with the self–calibration fusion structure. The decoder restored the resolution of the output features with a series of successive upsampling structures. Second, we presented a feature pyramid attention mechanism to extract the fused information at multiple scales and obtain features with rich semantic information. The experimental results using the publicly available Cityscapes dataset and collected forest scene images show that our model trained with the estimated depth information can achieve comparable performance to the ground truth depth map in improving the accuracy of the semantic segmentation task and even outperforming some competitive methods.
ESL: A High-Performance Skiplist with Express Lane
Authors: Na Yedam , Koo Bonmoo , Park Taeyoon , Park Jonghyeok , Kim Wook-Hee
Published: September 2023

With the increasing capacity and cost-efficiency of DRAM in multi-core environments, in-memory databases have emerged as fundamental solutions for delivering high performance. The index structure is a crucial component of the in-memory database, which, leveraging fast access to DRAM, plays an important role in the performance improvement and scalability of in-memory databases. A skiplist is one of the most widely used in-memory index structures and it has been adopted by popular databases. However, skiplists suffer from poor performance due to their structural limitations. In this work, we propose ESL, a high-performance and scalable skiplist. ESL efficiently enhances the performance of traverse operations by optimizing index levels for the CPU cache. With CPU cache-optimized index levels, we synergistically leverage a combination of exponential and linear searches. In addition, ESL reduces synchronization overhead by updating the index levels asynchronously, while tolerating inconsistencies. In our YCSB evaluation, ESL improves throughput by up to 2.8× over other skiplists in high-level evaluations. ESL also shows lower tail latency than other skiplists by up to 35×. Also, ESL consistently shows higher throughput in our real-world workload evaluation.
Contributions to the Process of Calibrating Corn Seeds Using a Calibrator with Cylindrical Sieves
Authors: Găgeanu Iuliana , Gheorghe Gabriel , Persu Cătălin , Vlăduț Nicolae-Valentin , Cujbescu Dan , Matache Mihai Gabriel , Voicea Iulian , Ion George-Cătălin , Tăbărașu Ana-Maria , Boruz Sorin Petruț , Popa Lorena-Diana
Published: September 2023

This paper presents theoretical and experimental research on the process of calibrating corn seeds using a specialized equipment with cylindrical sieves, studying the influence of process parameters and corn seed particularities on the quality of the calibration work. The research took into consideration corn seed characteristics, namely, their dimensions (length, width, and thickness) and weight, determining the influence of process parameters—the contact point between the seed and the cylindrical sieve, the influence of the length of the sieve, and the sieve’s revolution speed on the separation process. The experiments for determining the influence of these parameters on the calibration process were conducted on a calibrating equipment with cylindrical sieves using three different corn hybrids. It was noticed from the experiments that, overall, the revolution speed had the most important effect on the calibration process, with sieve length also affecting the process, but to a lesser degree. Seed calibration efficiency was best at the smallest revolution speed (33 rot/min) and decreased when the revolution speed increased up to 49 rot/min for all corn hybrids tested. The number of calibrated seeds decreased in the second part of the cylindrical sieve. Seed thickness influenced the process, in the respect that seeds smaller than 4.8 mm passed through the first third of the sieve and those with a thickness between 4.8 and 5 mm passed through the other two thirds of the sieve length.
Mining on Students’ Execution Logs and Repairing Compilation Errors Based on Deep Learning
Authors: Shi Ruoyan , Hu Jianpeng , Lin Bo
Published: September 2023

Automatic program repair techniques based on deep neural networks have attracted widespread attention from researchers due to the high degree of automation and generality. However, there is a scarcity of high-quality labeled datasets available for training program repair models. This study proposes a method of mining reasonable program repair examples from student program execution logs. Additionally, we introduce the Rookie Simulator (RS), which simulates the error patterns commonly made by novice programmers and generates a large number of program repair sample pairs. To address the issue of low repair rates for infrequent and complex error patterns in compilation errors, the study proposes the attention-enhanced capsule network for program repair (ACNPR), a program repair model that integrates compiler feedback information and utilizes capsule networks to capture complex semantic features. Experimental evaluations were conducted using publicly available datasets, including the DeepFix, TEGCER, and a real course dataset named SUES-COJ mined in this study. The results indicate that our method consistently outperforms current state-of-the-art models in terms of full repair rates.
Conversion between Number Systems in Membrane Computing
Authors: Nan Hai , Jiang Jiqiao , Zhang Jie , Liu Ran , Wang Aijuan
Published: September 2023

The number system is the representation method of numbers, and number system conversion is the most basic function of a computing system. The decimal system is the most commonly used number system; however, it may not necessarily be the most suitable number system in a computing system. This paper investigates the conversion methods between different number systems and designs corresponding cells, such as P systems, to implement them. The P systems we designed include Π10_2 and Π2_10 to implement conversion between decimal and binary, Π10_m and Πm_10 to implement conversion between decimal and m-base. The operation process of each P system was explained through examples, and their feasibility and effectiveness were verified through simulation software, UPSimulator.
Parapharyngeal Fat Tissue Accumulation and Its Association with Carotid Intima-Media Thickness in Discordant Twin Pairs
Authors: Jokkel Zsofia , Szily Marcell , Piroska Marton , Szabó Helga , Hernyes Anita , Szabó Gergely , Kalina Ildikó , Maurovich-Horvat Pál , Tarnoki David Laszlo , Tarnoki Adam Domonkos
Published: September 2023

Background: Recurrent upper airway obstruction during sleep is a common feature of obstructive sleep apnea (OSA). Risk factors for the development of OSA include obesity, male gender and smoking. In addition, anatomical factors contribute to the development of the disease; however, the heritability of the anatomical structures that determine upper airway narrowing is poorly understood. In this study, we aimed to investigate the background of anatomical structures associated with upper airway narrowing in discordant monozygotic (MZ) twin pairs. Methods: 33 adult MZ twin pairs (median age and Q1-Q3: 50 (42–56) years) from the Hungarian Twin Registry underwent head and neck MR (Philips Ingenia 1.5 T). T1- and T2-weighted images in sagittal, coronal and axial planes were used to measure cephalometric, soft tissue and adipose tissue structures. In addition, the twin pairs underwent carotid and femoral ultrasound scans (Samsung RS85) and full-body composition measurements (OMRON BF500). The analysis of discordant MZ twins for anatomical markers in relation to clinical background, blood test, vascular ultrasound and body composition results was performed using a paired permutation test. Results: We found a significant association between parapharyngeal adipose tissue area and body weight, waist circumference and metabolism (p < 0.05). Submental adipose tissue thickness showed an association with lower body muscle percentage (<0.05). Carotid intima-media thickness showed a negative association with parapharyngeal adipose tissue, tongue volume and submental adipose tissue thickness (<0.05). Conclusions: Our study found a significant association between anatomical structures potentially involved in upper airway narrowing and obesity-related markers such as weight, BMI, hip and waist circumference, and whole body composition analysis results (body fat percentage, visceral fat percentage, muscle percentage). This study may help to better understand the background of anatomical structures potentially involved in upper airway narrowing and the possible development of obstructive sleep apnea.
Effects of Intermittent Hypoxic Training on Aerobic Capacity and Second Ventilatory Threshold in Untrained Men
Authors: Maciejczyk Marcin , Palka Tomasz , Wiecek Magdalena , Szymura Jadwiga , Kusmierczyk Justyna , Bawelski Marek , Masel Sebastian , Szygula Zbigniew
Published: September 2023

The aim of study was to evaluate the effects of interval training performed in hypoxia on aerobic capacity and second ventilatory threshold in young, untrained men. Participants (n = 48) were randomly divided into a control group and two groups performing the same interval training (three times a week for 4 weeks) in normoxia (200 m asl) (NT) and in hypoxia (IHT) (3000 m asl, FIO2 = 14.4%). In the incremental test, maximal oxygen uptake (VO2max) was measured and the first (VT1) and second (VT2) ventilatory thresholds and the maximal power output (Pmax) were determined for each participant. The training workloads of the efforts corresponded to the workload at VT2 (effort) and VT1 (active recovery). Training in both normoxia and hypoxia significantly increased absolute VO2max (p = 0.02, ES = 0.51 and p = 0.002, ES = 0.47, respectively). In comparison to NT, only IHT significantly (p < 0.001; ES = 0.80) improved Pmax, as well as power at VT2 (p = 0.02; ES = 0.78). The applied IHT was effective in improving Pmax and power at VT2, which was not observed after training in normoxia.
Influence of Grinding Degree and Screw Rotation Speed on Sunflower Oil Pressing Process
Authors: Abdilova Galiya , Sergibayeva Zhadra , Orynbekov Duman , Shamenov Merey , Zhumadilova Gulmira , Bakiyeva Anara , Mukashev Nurbolat , Bayadilova Assyl , Dukenbayev Damir
Published: September 2023

Sunflower is a major agricultural oilseed crop, and the Republic of Kazakhstan has been steadily strengthening its position as a producer of oilseeds. In this study, an oil pressing machine with two processes, including grinding sunflower seeds and pressing the obtained cake to separate the oil, is constructed. The experiment investigated the impact of different grinding degrees (hole diameters of plates of 5 mm, 4 mm, 3 mm, and 2 mm) and screw rotation speeds (ranging from 30 rpm to 250 rpm) on oil pressing efficiency. The study used sunflower seeds with an oil content of 45–47% and moisture of 7–9%. The results showed that increasing the grinding degree and screw rotation speed led to higher oil yield. The optimal condition was a grinding degree of 4 mm and a screw rotation speed of 60 rpm, resulting in the highest oil yield of 15.6 g/s. Additionally, the residual oil content of the seed cake decreased significantly as pressure increased during pressing, particularly with 4 mm grinding. Power consumption increased with higher screw rotation speeds and finer grinding degrees, indicating the influence of grinding components on energy demand. The cake density increased with higher screw rotation speeds and finer grinding degrees, highlighting the impact of grinding mechanisms on cake compactness. Moreover, the temperature of the cake rose with increased screw rotation speed and the presence of grinding sieves. These findings provide valuable insights into optimizing the sunflower oil pressing process, highlighting the importance of selecting appropriate grinding degrees and screw rotation speeds to maximize oil yield and pressing efficiency.
Improving Dimensionality Reduction Projections for Data Visualization
Authors: Rafieian Bardia , Hermosilla Pedro , Vázquez Pere-Pau
Published: September 2023

In data science and visualization, dimensionality reduction techniques have been extensively employed for exploring large datasets. These techniques involve the transformation of high-dimensional data into reduced versions, typically in 2D, with the aim of preserving significant properties from the original data. Many dimensionality reduction algorithms exist, and nonlinear approaches such as the t-SNE (t-Distributed Stochastic Neighbor Embedding) and UMAP (Uniform Manifold Approximation and Projection) have gained popularity in the field of information visualization. In this paper, we introduce a simple yet powerful manipulation for vector datasets that modifies their values based on weight frequencies. This technique significantly improves the results of the dimensionality reduction algorithms across various scenarios. To demonstrate the efficacy of our methodology, we conduct an analysis on a collection of well-known labeled datasets. The results demonstrate improved clustering performance when attempting to classify the data in the reduced space. Our proposal presents a comprehensive and adaptable approach to enhance the outcomes of dimensionality reduction for visual data exploration.
Modeling of RC Moment Frame Retrofit with Mortar Walls Reinforced with Steel Wire Mesh
Authors: Herrera Melisa , Sosa Diego , Díaz Sigifredo , Thangjitham Jessica
Published: September 2023

Current construction codes require detailed analyses for structural retrofitting, which must consider performance during seismic events. Therefore, the computational models used to evaluate existing infrastructure require nonlinear structural analysis and damage estimates. For structural retrofitting, nonlinear computational modeling must represent the connectivity between existing and new elements. This study proposes recommendations on structural modeling based on fiber elements to represent reinforced concrete (RC) moment frames retrofitted with mortar walls reinforced with steel wire mesh. For this purpose, capacity curves of moment frames retrofitted with mortar walls were calculated by hand with the Bernoulli–Euler beam theory, moment–curvature analyses, and a plastic hinge model. Then, these capacity curves were used to calibrate the connectivity and constraint conditions in fiber models between the existing frame and the new wall required to capture the performance of the retrofitted structure. The study found that, for a single wall connected with top and bottom frame border elements, the capacity curves from fiber models underestimate stiffness, maximum strength, and residual strength. These estimation issues are reduced by including intermediate connectivity nodes between the top and bottom frame where rigid link constraints connect the existing frame with the new wall.
Optimization of the Production Management of an Upholstery Manufacturing Process Using Lean Tools: A Case Study
Authors: Santos Eva , Lima Tânia M. , Gaspar Pedro D.
Published: September 2023

This study aims to address the challenge of implementing Lean philosophy in Small and Medium Enterprises (SMEs) and fill the research gap regarding Lean application in vehicle seat upholstery maintenance/repairing processes. The Lean tools applied in a case study of an upholstery industry of vehicle seats were as follows: Value Stream Mapping, Spaghetti Diagram, Gemba, 5S, Standardized Work, Kaizen, Kanban, and Poka-Yoke tools. A Decision Support Method using Excel Microsoft 365 was developed for improved stock control. A GUT Matrix was formulated to prioritize improvement opportunities, aiding prompt decision-making. This systematic approach enabled the company to address critical areas requiring swift attention. The results of Lean tools implementation led to a process waste minimization around 47%, and the process Lead Time decreased by approximately 26%, resulting in a 33% production increase. Thus, the Lean tools integration leads to substantial waste reduction, shorter process time, and increased production. The Decision Support Method enabled the company to efficiently monitor and manage its stock levels, thereby enhancing inventory management practices. This case study outlines the successful optimization of an upholstery production process in an SME by effectively applying Lean tools, highlighting its feasibility and benefits.
Study on the Optimization of Pile Length of Micropiles in Soil Landslides
Authors: Cheng Hui , Sui Guochen , Wang Guanglu , Deng Junfeng , Wei Huan , Xu Rui , He Youshan , Yang Wei
Published: September 2023

This study summarizes the engineering design and calculation methods of micropiles and proposes a pile length optimization model based on numerical simulation software. Based on the proposed micropile calculation method and optimization method, a specific analysis of a project example was carried out, and a series of calculations, such as micropile design calculation and pile length optimization for the project, was completed. The results show that the miniature pile length optimization model based on numerical simulation finite difference method improves the previous method by automating the optimization process through fast modeling, automatic creation of optimization commands, and output and analysis of optimization results, and realizes the optimization of pile length using numerical simulation, which improves the efficiency of the optimization of the pile length under the premise of guaranteeing accuracy, and achieves the unity of both efficiency and accuracy. The feasibility of this optimization process is proved by engineering examples. The engineering practicability of the micropile design calculation method and optimization method proposed in this study is proved through practice. It provides a reference value for the initial fast and flexible management of small landslides.
Exploring the Potential of Sensing for Breast Cancer Detection
Authors: Chowdhury Nure Alam , Wang Lulu , Gu Linxia , Kaya Mehmet
Published: September 2023

Breast cancer is a generalized global problem. Biomarkers are the active substances that have been considered as the signature of the existence and evolution of cancer. Early screening of different biomarkers associated with breast cancer can help doctors to design a treatment plan. However, each screening technique for breast cancer has some limitations. In most cases, a single technique can detect a single biomarker at a specific time. In this study, we address different types of biomarkers associated with breast cancer. This review article presents a detailed picture of different techniques and each technique’s associated mechanism, sensitivity, limit of detection, and linear range for breast cancer detection at early stages. The limitations of existing approaches require researchers to modify and develop new methods to identify cancer biomarkers at early stages.
Engineering Supply Chain Transportation Indexes through Big Data Analytics and Deep Learning
Authors: Sakas Damianos P. , Giannakopoulos Nikolaos T. , Terzi Marina C. , Kanellos Nikos
Published: September 2023

Deep learning has experienced an increased demand for its capabilities to categorize and optimize operations and provide higher-accuracy information. For this purpose, the implication of deep learning procedures has been described as a vital tool for the optimization of supply chain firms’ transportation operations, among others. Concerning the indexes of transportation operations of supply chain firms, it has been found that the contribution of big data analytics could be crucial to their optimization. Due to big data analytics’ variety and availability, supply chain firms should investigate their impact on their key transportation indexes in their effort to comprehend the variation of the referred indexes. The authors proceeded with the gathering of the required big data analytics from the most established supply chain firms’ websites, based on their (ROPA), revenue growth, and inventory turn values, and performed correlation and linear regression analyses to extract valuable insights for the next stages of the research. Then, these insights, in the form of statistical coefficients, were inserted into the development of a Hybrid Model (Agent-Based and System Dynamics modeling), with the application of the feedforward neural network (FNN) method for the estimation of specific agents’ behavioral analytical metrics, to produce accurate simulations of the selected key performance transportation indexes of supply chain firms. An increase in the number of website visitors to supply chain firms leads to a 60% enhancement of their key transportation performance indexes, mostly related to transportation expenditure. Moreover, it has been found that increased supply chain firms’ website visibility tends to decrease all of the selected transportation performance indexes (TPIs) by an average amount of 87.7%. The implications of the research outcomes highlight the role of increased website visibility and search engine ranking as a cost-efficient means for reducing specific transportation costs (Freight Expenditure, Inferred Rates, and Truckload Line Haul), thus achieving enhanced operational efficiency and transportation capacity.
A Study on the Design and Control of the Overhead Hoist Railway-Based Transportation System
Authors: Truong Thuy Duy , Nguyen Xuan Tuan , Vu Tuan Anh , Khuu Nguyen Huu Loc , Le Quoc Dien , Vu Tran Thanh Cong , Tran Hoa Binh , Vo Tuong Quan
Published: September 2023

Overhead hoist transportation systems (OHTS) have been the subject of worldwide research and development in recent years. The majority of these systems are utilized in semi-automated or fully automated factories. This article proposes a new solution for OTHS based on the concept of the modulation of mobile units that can move on a railway structure from one point to another. The OHTS mentioned in this article is a group of shuttles that can operate independently but which also have the ability to cooperate together to complete the desired tasks. By using the space below the ceiling, this system can operate without affecting the original design of the factories. There are many potential fields of application for picking-up and delivering, such as the medical field, the food and beverage fields, automotive and electrical appliances, etc. Moreover, by applying Dijkstra’s algorithm in the controller design, the transportation speed among the stations in the whole system can be improved. The real prototype of the whole system, including three shuttles, is also manufactured to explore and assess the design and operation of the proposed system and its controller.
The Medieval Chants for Ste Foy Considered through the Prism of Their Nocturnal Performance
Authors: Parkes Henry
Published: September 2023

The medieval cult of Ste Foy inspired several sets of liturgical chants, or historiae, including at least two that were probably made for use at Conques in the early eleventh century. Whilst it is widely understood that historia chants belonged within the liturgy of the Divine Office, this article explores the significance of two lesser-known parameters in their performance: their use during the nocturnal hours, above all during the lengthy service known as the Night Office, and their use alongside various modes of sensory augmentation that were employed on major feast days. By exploring these parameters as they might have applied to the medieval Abbey of Conques in the context of Ste Foy’s feast—using sources from Fleury and Saint-Bénigne, Dijon, wherever local evidence is lacking—the article draws attention to the ways in which historiae intersected with non-verbal modes of creativity within the performative frame of the Office liturgy. Ultimately, it argues for a more consciously multidisciplinary approach to this historically ‘musical’ genre.
Modular Open-Core System for Collection and Near Real-Time Processing of High-Resolution Data from Wearable Sensors
Authors: Temple Dorota S. , Hegarty-Craver Meghan , Gaur Pooja , Boyce Matthew D. , Holt Jonathan R. , Preble Edward A. , Eckhoff Randall P. , Davis-Wilson Hope , Walls Howard J. , Dausch David E. , Blackston Matthew A.
Published: September 2023

Wearable devices, such as smartwatches integrating heart rate and activity sensors, have the potential to transform health monitoring by enabling continuous, near real-time data collection and analytics. In this paper, we present a novel modular architecture for collecting and end-to-end processing of high-resolution signals from wearable sensors. The system obtains minimally processed data directly from the smartwatch and further processes and analyzes the data stream without transmitting it to the device vendor cloud. The standalone operation is made possible by a software stack that provides data cleaning, extraction of physiological metrics, and standardization of the metrics to enable person-to-person and rest-to-activity comparisons. To illustrate the operation of the system, we present examples of datasets from volunteers wearing Garmin Fenix smartwatches for several weeks in free-living conditions. As collected, the datasets contain time series of each interbeat interval and the respiration rate, blood oxygen saturation, and step count every 1 min. From the high-resolution datasets, we extract heart rate variability metrics, which are a source of information about the heart’s response to external stressors. These biomarkers can be used for the early detection of a range of diseases and the assessment of physical and mental performance of the individual. The data collection and analytics system has the potential to broaden the use of smartwatches in continuous near to real-time monitoring of health and well-being.
Biomechanics of the JCT and SC Inner Wall Endothelial Cells with Their Basement Membrane Using 3D Serial Block-Face Scanning Electron Microscopy
Authors: Karimi Alireza , Razaghi Reza , Kelley Mary J. , Acott Ted S. , Gong Haiyan
Published: September 2023

Background: More than ~70% of the aqueous humor exits the eye through the conventional aqueous outflow pathway that is comprised of the trabecular meshwork (TM), juxtacanalicular tissue (JCT), the inner wall endothelium of Schlemm’s canal (SC). The flow resistance in the JCT and SC inner wall basement membrane is thought to play an important role in the regulation of the intraocular pressure (IOP) in the eye, but current imaging techniques do not provide enough information about the mechanics of these tissues or the aqueous humor in this area. Methods: A normal human eye was perfusion-fixed and a radial wedge of the TM tissue from a high-flow region was dissected. The tissues were then sliced and imaged using serial block-face scanning electron microscopy. Slices from these images were selected and segmented to create a 3D finite element model of the JCT and SC cells with an inner wall basement membrane. The aqueous humor was used to replace the intertrabecular spaces, pores, and giant vacuoles, and fluid–structure interaction was employed to couple the motion of the tissues with the aqueous humor. Results: Higher tensile stresses (0.8-kPa) and strains (25%) were observed in the basement membrane beneath giant vacuoles with open pores. The volumetric average wall shear stress was higher in SC than in JCT/SC. As the aqueous humor approached the inner wall basement membrane of SC, the velocity of the flow decreased, resulting in the formation of small eddies immediately after the flow left the inner wall. Conclusions: Improved modeling of SC and JCT can enhance our understanding of outflow resistance and funneling. Serial block-face scanning electron microscopy with fluid–structure interaction can achieve this, and the observed micro-segmental flow patterns in ex vivo perfused human eyes suggest a hypothetical mechanism.
Interaction between Autophagy and Senescence in Pancreatic Beta Cells
Authors: Hela Francesko , Aguayo-Mazzucato Cristina
Published: September 2023

Aging leads to an increase in cellular stress due to the fragility of the organism and the inability to cope with it. In this setting, there is a higher chance of developing different cardiometabolic diseases like diabetes. Cellular senescence and autophagy, both hallmarks of aging and stress-coping mechanisms, have gained increased attention for their role in the pathophysiology of diabetes. Studies show that impairing senescence dampens and even prevents diabetes while the role of autophagy is more contradictory, implying a context- and disease-stage-dependent effect. Reports show conflicting data about the effect of autophagy on senescence while the knowledge about this interaction in beta cells remains scarce. Elucidating this interaction between autophagy and senescence in pancreatic beta cells will lead to an identification of their respective roles and the extent of the effect each mechanism has on beta cells and open new horizons for developing novel therapeutic agents. To help illuminate this relationship we will review the latest findings of cellular senescence and autophagy with a special emphasis on pancreatic beta cells and diabetes.
Isolation of Polyphenols from Two Waste Streams of Clingstone Peach Canneries Utilizing the Cloud Point Extraction Method
Authors: Giovanoudis Ioannis , Athanasiadis Vassilis , Chatzimitakos Theodoros , Kalompatsios Dimitrios , Bozinou Eleni , Gortzi Olga , Nanos George , Lalas Stavros
Published: September 2023

This study aimed to assess the feasibility of employing cloud point extraction (CPE) as an efficient way of extracting polyphenols from peach waste (PW). Four distinct food-grade surfactants (Genapol X-080, PEG 8000, Tween 80, and lecithin) were evaluated at concentrations ranging from 2–10% w/v to determine the efficiency of the technique in two separate PW streams [i.e., lye peeling waste stream (LPWS) and total wastewater stream (TWS)]. Low amounts (2% w/v) of surfactants in a single-step CPE were found to result in less than ~61% polyphenol recovery in LPWS and less than ~69% polyphenol recovery in the TWS, necessitating additional extraction steps. In both PW streams, the single-step polyphenol recovery was improved by 25–67% utilizing a higher amount of surfactants (5–10% w/w), leading to a statistically significant figure (p < 0.05). The CPE procedure was conducted under optimal conditions, including a temperature of 65 °C, a sodium chloride concentration of 3% w/v, a pH level of 3.5, and a surfactant concentration of 5% w/v. The polyphenol recovery was efficient when the CPE procedure was conducted twice. Tween 80 proved to be the most efficient surfactant among the four tested surfactants, achieving recoveries above 98% in both PW streams. Under optimum extraction conditions, the total polyphenol content and antiradical activity of PW extracts were evaluated. The results showed statistically significant differences (p < 0.05) between the two PW streams, with the LPWS having approximately 12 times higher polyphenol content and being more potent, achieving ~64% antiradical activity. Using the LPWS instead of the TWS is a more cost-effective and feasible option for the industry. In addition, the considerable volume of the TWS makes it challenging to handle and demands a correspondingly major amount of surfactant. Considering that Tween 80 is a low-toxicity surfactant and that the CPE method is simple, fast, cost-effective, highly accurate, and selective, the extracted polyphenols from two PW streams could be exploited as natural antioxidants to be used directly in the food industry. These findings could have major implications for the manufacturing of sustainable and naturally-derived food additives.
Evaluation of Cartilage Integrity following Administration of Oral and Intraarticular Nifedipine in a Murine Model of Osteoarthritis
Authors: Aleksiuk Viktorija , Baleisis Justinas , Kirdaite Gailute , Uzieliene Ilona , Denkovskij Jaroslav , Bernotas Paulius , Ivaskiene Tatjana , Mobasheri Ali , Bernotiene Eiva
Published: September 2023

Osteoarthritis (OA) ranks as the prevailing type of arthritis on a global scale, for which no effective treatments are currently available. Arterial hypertension is a common comorbidity in OA patients, and antihypertensive drugs, such as nifedipine (NIF), may affect the course of OA progression. The aim of this preclinical study was to determine the effect of nifedipine on healthy and OA cartilage, depending on its route of administration. In this study, we used the destabilization of medial meniscus to develop a mouse model of OA. Nifedipine was applied per os or intraarticularly (i.a.) for 8 weeks to both mice with OA and healthy animals. Serum biomarker concentrations were evaluated using the Luminex platform and alterations in the knee cartilage were graded according to OARSI histological scores and investigated immunohistochemically. Nifedipine treatment per os and i.a. exerted protective effects, as assessed by the OARSI histological scores. However, long-term nifedipine i.a. injections induced the deterioration of healthy cartilage. Lubricin, cartilage intermediate layer matrix protein (CILP), collagen type VI (COLVI), CILP, and Ki67 were upregulated by the nifedipine treatment. Serum biomarkers MMP-3, thrombospondin-4, and leptin were upregulated in the healthy groups treated with nifedipine, while only the levels of MMP-3 were significantly higher in the OA group treated with nifedipine per os compared to the untreated group. In conclusion, this study highlights the differential effects of nifedipine on cartilage integrity, depending on the route of administration and cartilage condition.
C-Reactive Protein: The Quintessential Marker of Systemic Inflammation in Coronary Artery Disease—Advancing toward Precision Medicine
Authors: Amezcua-Castillo Emanuel , González-Pacheco Héctor , Sáenz-San Martín Arturo , Méndez-Ocampo Pablo , Gutierrez-Moctezuma Iván , Massó Felipe , Sierra-Lara Daniel , Springall Rashidi , Rodríguez Emma , Arias-Mendoza Alexandra , Amezcua-Guerra Luis M.
Published: September 2023

Atherosclerotic cardiovascular disease (CVD) remains the leading cause of mortality worldwide. While conventional risk factors have been studied and managed, CVD continues to pose a global threat. Risk scoring systems based on these factors have been developed to predict acute coronary syndromes and guide therapeutic interventions. However, traditional risk algorithms may not fully capture the complexities of individual patients. Recent research highlights the role of inflammation, particularly chronic low-grade inflammation, in the pathogenesis of coronary artery disease (CAD). C-reactive protein (CRP) is an inflammatory molecule that has demonstrated value as a predictive marker for cardiovascular risk assessment, both independently and in conjunction with other parameters. It has been incorporated into risk assessment algorithms, enhancing risk prediction and guiding therapeutic decisions. Pharmacological interventions with anti-inflammatory properties, such as statins, glucagon-like peptide-1 agonists, and interleukin-1 inhibitors, have shown promising effects in reducing both cardiovascular risks and CRP levels. This manuscript provides a comprehensive review of CRP as a marker of systemic inflammation in CAD. By exploring the current knowledge surrounding CRP and its implications for risk prediction and therapeutic interventions, this review contributes to the advancement of personalized cardiology and the optimization of patient care.
Neovascular Progression and Retinal Dysfunction in the Laser-Induced Choroidal Neovascularization Mouse Model
Authors: Salas Anna , Badia Anna , Fontrodona Laura , Zapata Miguel , García-Arumí José , Duarri Anna
Published: September 2023

The mouse model of laser-induced choroidal neovascularization (LI-CNV) has been widely used to study neovascular age-related macular degeneration; however, it still lacks a comprehensive characterization. Here, CNV was induced in the eyes of 12-week-old C57BL/6J male mice by argon laser irradiation. We studied the CNV lesion progression of an LI-CNV mouse cohort by using multimodal imaging (color fundus, optical coherence tomography (OCT), and fluorescence angiography, focal electroretinography features for 14 days, and related cytokines, angiogenic factors, and reactive gliosis for 5 days. CNV lesions involving the rupture of the Bruch’s membrane were confirmed using funduscopy and OCT after laser photocoagulation. During the initial stage, from the CNV induction until day 7, CNV lesions presented leakage observed by using fluorescence angiography and a typical hyperreflective area with cell infiltration, subretinal leakage, and degeneration of photoreceptors observed through OCT. This correlated with decreased retinal responses to light. Moreover, inflammatory and angiogenic markers were reduced to basal levels in the first 5 days of CNV progression. In contrast, reactive gliosis and the VEGF expression in retinal sections were sustained, with infiltration of endothelial cells in the subretinal space. In the second stage, between days 7 and 14 post-induction, we observed stabilization of the CNV lesions, a hyperfluorescent area corresponding to the formation of fibrosis, and a partial rescue of retinal function. These findings suggest that the LI-CNV lesion development goes through an acute phase during the first seven days following induction, and then the CNV lesion stabilizes. According to these results, this model is suitable for screening anti-inflammatory and anti-angiogenic drugs in the early stages of LI-CNV. At the same time, it is more convenient for screening anti-fibrotic compounds in the later stages.
A Brain Region-Dependent Alteration in the Expression of Vasopressin, Corticotropin-Releasing Factor, and Their Receptors Might Be in the Background of Kisspeptin-13-Induced Hypothalamic-Pituitary-Adrenal Axis Activation and Anxiety in Rats
Authors: Csabafi Krisztina , Ibos Katalin Eszter , Bodnár Éva , Filkor Kata , Szakács Júlia , Bagosi Zsolt
Published: September 2023

Previously, we reported that intracerebroventricularly administered kisspeptin-13 (KP-13) induces anxiety-like behavior and activates the hypothalamic-pituitary-adrenal (HPA) axis in rats. In the present study, we aimed to shed light on the mediation of KP-13′s stress-evoking actions. The relative gene expressions of the corticotropin-releasing factor (Crf, Crfr1, and Crfr2) and arginine vasopressin (Avp, Avpr1a, and Avpr1b) systems were measured in the amygdala and hippocampus of male Wistar rats after icv KP-13 treatment. CRF and AVP protein content were also determined. A different set of animals received CRF or V1 receptor antagonist pretreatment before the KP-13 challenge, after which either an open-field test or plasma corticosterone levels measurement was performed. In the amygdala, KP-13 induced an upregulation of Avp and Avpr1b expression, and a downregulation of Crf. In the hippocampus, the mRNA level of Crf increased and the level of Avpr1a decreased. A significant rise in AVP protein content was also detected in the amygdala. KP-13 also evoked anxiety-like behavior in the open field test, which the V1 receptor blocker antagonized. Both CRF and V1 receptor blockers reduced the KP-13-evoked rise in the plasma corticosterone level. This suggests that KP-13 alters the AVP and CRF signaling and that might be responsible for its effect on the HPA axis and anxiety-like behavior.
A Novel Classification of Endometriosis Based on Clusters of Comorbidities
Authors: Sarria-Santamera Antonio , Yemenkhan Yerden , Terzic Milan , Ortega Miguel A. , Asunsolo del Barco Angel
Published: September 2023

Endometriosis is a heterogeneous, complex, and still challenging disease, due to its epidemiological, etiological and pathogenic, diagnostic, therapeutic, and prognosis characteristics. The classification of endometriosis is contentious, and existing therapies show significant variability in their effectiveness. This study aims to capture and describe clusters of women with endometriosis based on their comorbidity. With data extracted from electronic records of primary care, this study performs a hierarchical clustering with the Ward method of women with endometriosis with a subsequent analysis of the distribution of comorbidities. Data were available for 4055 women with endometriosis, and six clusters of women were identified: cluster 1 (less comorbidity), cluster 2 (anxiety and musculoskeletal disorders), cluster 3 (type 1 allergy or immediate hypersensitivity); cluster 4 (multiple morbidities); cluster 5 (anemia and infertility); and cluster 6 (headache and migraine). Clustering aggregates similar units into similar clusters, partitioning dissimilar objects into other clusters at a progressively finer granularity—in this case, groups of women with similarities in their comorbidities. Clusters may provide a deeper insight into the multidimensionality of endometriosis and may represent diverse “endometriosis trajectories” which may be associated with specific molecular and biochemical mechanisms. Comorbidity-based clusters may be important to the scientific study of endometriosis, contributing to the clarification of its clinical complexity and variability. An awareness of those comorbidities may help elucidate the etiopathogenesis and facilitate the accurate earlier diagnosis and initiation of treatments targeted toward particular subgroups.
Novel Noninvasive Paraclinical Study Method for Investigation of Liver Diseases
Authors: Gyorfi Nina , Gal Adrian Robert , Fincsur Andras , Kalmar-Nagy Karoly , Mintal Kitti , Hormay Edina , Miseta Attila , Tornoczky Tamas , Nemeth Anita Katalin , Bogner Peter , Kiss Tamas , Helyes Zsuzsanna , Sari Zoltan , Klincsik Mihaly , Tadic Vladimir , Lenard Laszlo , Vereczkei Andras , Karadi Zoltan , Vizvari Zoltan , Toth Attila
Published: September 2023

Based on a prior university patent, the authors developed a novel type of bioimpedance-based test method to noninvasively detect nonalcoholic fatty liver disease (NAFLD). The development of a new potential NAFLD diagnostic procedure may help to understand the underlying mechanisms between NAFLD and severe liver diseases with a painless and easy-to-use paraclinical examination method, including the additional function to detect even the earlier stages of liver disease. The aim of this study is to present new results and the experiences gathered in relation to NAFLD progress during animal model and human clinical trials.