bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental and Numerical Study of the Effect of Rock Dissolution on Absolute Permeability of Limestone Sub-Samples
Authors: Akasheva Zhibek K. , Assilbekov Bakytzhan K. , Bolysbek Darezhat A. , Iskakov Berik , Uzbekaliyev Kenbai Sh. , Issayev Gani I.
Published: December 2023

Permeability is a key transport property of porous materials, and its accurate evaluation is relevant when studying applied tasks, such as CO2 injection into reservoirs and investigating groundwater quality. This study examines the dependence of permeability on total and connected porosity, hydraulic tortuosity, specific surface area, and mean pore radius based on the data of 408 cubic sub-volumes extracted from heterogeneous and naturally fractured cylindrical carbonate samples, before and after injection of HCl solutions. These parameters were computed using pore-scale modeling of fluid flow. Our results show that permeability correlates well with porosity and mean pore radius, with correlation coefficients of R2≈0.65−0.79 for heterogeneous samples. It was found that the presence of natural fractures significantly influenced the relationship between permeability and other parameters. The relationship between permeability k, tortuosity τ, and specific surface area S is described by the power laws k~τ−α and k~S−β, with coefficients α and β substantially exceeding those in the Kozeny–Carman equation. It was also found that there is a parabolic relationship between connected and total porosities, both before and after rock dissolution with R2≈0.96−0.99. This allowed for an estimation of percolation threshold porosity in accordance with the literature data.
Fabric Defect Detection Method Using SA-Pix2pix Network and Transfer Learning
Authors: Hu Feng , Gong Jie , Fu Han , Liu Wenliang
Published: December 2023

This paper proposes a fabric defect detection algorithm based on the SA-Pix2pix network and transfer learning to address the issue of insufficient accuracy in detecting complex pattern fabric defects in scenarios with limited sample data. Its primary contribution lies in treating defects as disruptions to the fabric’s texture. It leverages a generative adversarial network to reconstruct defective images, restoring them to images of normal fabric texture. Subsequently, the reconstituted images are subjected to dissimilarity calculations against defective images, leading to image segmentation for the purpose of defect detection. This approach addresses the issues of poor defect image reconstruction accuracy due to the limited ability of remote dependency modeling within the generator’s convolutional neural network. It also tackles deficiencies in the generative adversarial network’s loss function in handling image details. To enhance the structure and loss function of the generative adversarial network, it introduces self-attention mechanisms, L1 loss, and an improved structural loss, thus mitigating the problems of low defect image reconstruction accuracy and insufficient image detail handling by the network. To counteract the issue of declining model training accuracy in the face of sparse complex fabric defect samples, a channel-wise domain transfer learning approach is introduced. This approach constrains the training of the target network through feature distribution, thereby overcoming the problem of target network overfitting caused by limited sample data. The study employs three methods to experimentally compare and investigate five distinct complex pattern fabric defects. The results demonstrate that, when compared to two other defect detection methods, the approach advocated in this paper exhibits superior detection accuracy in scenarios with limited sample data.
Numerical Investigation on the Buckling Load Capacity of Novel Compound Cross-Sections Used in Crane Construction
Authors: Ladinek Markus , Klapper Georg , Lang Robert
Published: December 2023

Although a crane is exposed to a wide range of loads, there is a growing need for a lighter, more slender design. As a result, double girder cranes are becoming single girder cranes, aiming to make the steel structure as light as possible. The optimization potential of the classic design as a hollow-box girder is approaching its end. In order to meet today’s requirements, a new design was developed, which combines beams with curved panels into a new cross-section to be used as the crane’s main girder. Compound cross-sections pose a challenge for the mechanical engineer as there are usually no comparative data available and designing using numerical methods is complex. For this reason, a scaled model was abstracted for which a load determination will be carried out in 2024. This article deals with the finite element calculations for the design of the test specimen. A global numerical analysis was used to determine the buckling load, and several imperfection patterns were investigated. The results revealed that the buckling loads are similar to each other. This finding may lead to the conclusion that the most damaging imperfection pattern has yet to be found, which supports the need for an accompanying series of tests.
Development of Grouting Test System for Rough Fissure Rock Body and Research on Slurry Diffusion Law
Authors: Li Guosheng , Li Zhenhua , Du Feng , Cao Zhengzheng , Wang Wenqiang
Published: December 2023

The surface roughness of grout in fractured rock masses has a significant impact on the diffusion characteristics of grout, especially in millimeter-scale fractures. In this study, a self-constructed experimental system for grouting in rough fractured rock masses was used to conduct grout diffusion tests with varying fracture roughness, fracture aperture, and grouting pressure. A theoretical model was developed to account for the combined effects of fracture roughness, aperture, and grouting pressure on grout diffusion, and its validity was verified. The results showed that the theoretical calculations and experimental results had an error rate of around 12%, indicating the high reliability of the theory. Fracture aperture, grouting pressure, and fracture roughness all exhibited nonlinear relationships with the grout pressure distribution. With increasing diffusion distance, the grout pressure decreased, and the rate of decrease gradually slowed down. Fracture roughness and aperture had a relatively small impact on grout pressure, while grouting pressure had a significant influence on grout pressure distribution. The difference in grout pressure between the initial and final stages of diffusion was small, whereas in the middle stage of diffusion, the difference was more pronounced. This research provides a valuable reference for the selection of grouting techniques in the roadway surrounding rock projects.
Multi-Stage Operation Optimization of PV-Rich Low-Voltage Distribution Networks
Authors: Dubravac Marina , Žnidarec Matej , Fekete Krešimir , Topić Danijel
Published: December 2023

The high expansion of a variable and intermittent nature of distributed generation, such as photovoltaics (PV), can cause technical issues in existing distribution networks (DN). In addition to producing electrical energy, PVs are inverter-based sources, and can help conventional control mechanisms in mitigating technical issues. This paper proposes a multi-stage optimal power flow (OPF)-based mixed-integer non-linear programming (MINLP) model for improving an operation state in LV PV-rich DN. A conventional control mechanism such as on load tap changer (OLTC) is used in the first stage to mitigate overvoltage caused by PVs. The second stage is related to reducing losses in DN using reactive power capabilities from PVs, which defines the optimization problem as a fully centralized observed from the distribution system operator’s (DSO) point of view. The optimization problem is realized under the co-simulation approach in which the power system analyzer and computational intelligence (CI) optimization method interact through an interface. This approach allows keeping the original MINLP model without approximations and using any computational intelligence method. OpenDSS is used as a power system analyzer, while particle swarm optimization (PSO) is used as a CI optimization method in this paper. Detailed case studies are performed and analyzed over a single-day period. To study validation and feasibility, the proposed model is evaluated on the IEEE LV European distribution feeder. The obtained results suggest that a combination of conventional control mechanisms (OLTC) and inverter-based sources (PVs) represent a promising solution for DSO and can serve as an alternative control method in active distribution networks.
Advancing Aircraft Safety through CAx-Enhanced Digitalization and Thermal Stress Testing Methodologies: A Comprehensive Approach
Authors: Korba Peter , Šváb Patrik , Vereš Michal , Hudák Pavol
Published: December 2023

Safety is of utmost importance in air transport, and the quality and durability of aircraft construction materials play a significant role in ensuring overall safety. The right technology and methodology for designing, simulating, and testing aircraft components can simplify the process, digitize components, and utilize non-destructive testing methods to increase safety. This article focuses on the digitization, creation of a 3D model, and testing of a small jet engine, MPM-20. Using a 3D scanner and position markers, the authors created a 3D digital model of the engine and adjusted it to the desired state using computer-aided technologies (CAx). Thermo-spectral analysis was then performed on the real object using a thermal camera and associated software. It was found that the engine’s structural integrity was not compromised by excessive thermal load in the specified spatial points. The methodology used can be applied to a wide range of aircraft components, improving their digitization, modification, and stress-testing.
Commercially Biochar Applied for Tartrazine Removal from Aqueous Solutions
Authors: Soran Maria-Loredana , Bocșa Mariana , Pintea Stelian , Stegarescu Adina , Lung Ildiko , Opriş Ocsana
Published: December 2023

Biochar gained attention due to its definite physico-chemical characteristics and because it is a cost-effective and efficient adsorbent. In this paper, commercial biochar was tested for the removal of tartrazine from aqueous solutions. Thus, the optimum experimental conditions were determined for several parameters (pH, temperature, initial concentration of tartrazine, biochar dose, and contact time). The concentration of tartrazine residues was determined using UV-Vis spectrophotometry. The best experimental results were obtained at 1 mg L−1 concentration of tartrazine, pH 2, 30 °C, 18 min, and 0.9 g L−1 adsorbent dose. The maximum removal efficiency of tartrazine obtained in optimum conditions was 90.18%. The experimental data were analyzed by the isotherm and kinetic models. The isotherm and kinetics of tartrazine removal on biochar follow the Langmuir isotherm and pseudo-second-order kinetics, respectively. According to the Langmuir isotherm model, the biochar showed a maximum adsorption capacity of 3.28 mg g−1. In addition, biochar demonstrated a good reuse potential and therefore can be used for the removal of tartrazine from aqueous solutions.
Mapping of Deep Neural Network Accelerators on Wireless Multistage Interconnection NoCs
Authors: Aydi Yassine , Mnejja Sirine , Mohammed Faraqid Q. , Abid Mohamed
Published: December 2023

In the last few decades, the concept of Wireless Network-on-chip (WiNoC) has emerged as a promising alternative for Multiprocessor Systems on Chip (MPSOC) to achieve reliable and scalable communication. Worth recalling in this regard is that our research team has already designed, verified and evaluated Multistage Interconnection Networks (MIN) in this field. With respect to the present work, we consider proceeding with further exploring our thoughts on this research area. Firstly, we propose the design and performance evaluation of a hybrid (wireless/wired) MIN, analysing how this augmented network can potentially improve not only the average delay, but also energy consumption. Secondly, we continue with examining the implementation of our advanced DELTA-based MIN architecture on Deep Neural Network (DNN) accelerators, while accounting for its potential regularity and scalability in simultaneously maintaining an effective power efficiency and lower latency throughout the DNN operating process. In this context, several metrics have been evaluated in regard to three DNN application cases through implementation of their main respective modules.
Multi-Physics Field Computation for Microwave Heating of Multi-Mobile Components Based on Transformation Optics and Implicit Function
Authors: Chen Haoming , Gu Hao , Zhu Huacheng , Yang Yang
Published: December 2023

This paper proposed a method based on transformation optics, implicit function, and level set methods to solve the challenge of multi-physics simulation of a microwave heating cavity with two different motion modes. A 3D computation model with a rotating turntable, a lifting support rod, and a sample is proposed as a detailed demonstration. Based on the theory of transformation optics, the rotating turntable is surrounded by two circles with a time-varying, inhomogeneous and anisotropy medium, and the electric field in the moving region is rotated by controlling the two mediums. The implicit function and level set methods compute the lifting motion by setting the properties of the lifting region as a function of space and time. The correctness of the proposed method is verified by comparing the proposed method’s results with the discrete position’s results, and then its accuracy is further verified by experiment. Subsequently, compared with the implicit function and level set methods only, the proposed method is more accurate. Finally, the effects of lifting motion, rotating motion and lifting motion (i.e., spiral motion) on microwave heating uniformity and heating efficiency were analyzed, respectively.
Structure Design Improvement and Stiffness Reinforcement of a Machine Tool through Topology Optimization Based on Machining Characteristics
Authors: Lin Shen-Yung , Chang Chun-Ho
Published: December 2023

Machining characteristics were applied to topology optimization for machine tool structure design improvement in this study, and the goals of lightweight and high rigidity of the structure were achieved. Firstly, an ultrasonic-assisted grinding experiment was carried out on zirconia to investigate the surface roughness, surface morphology, grinding vibration, and forces. Then, the topology optimization analysis was conducted for structure design improvement, in which the magnitude of the grinding vibration was utilized as the reference for selecting the topology subsystems and the grinding force was used as the boundary conditions of the static analysis in the topology optimization. Hence, columns, bases, and saddles were redesigned for structure stiffness improvement, and the variations in the effective stress, natural frequency, weight, and stiffness of the whole machine tool were compared accordingly. The results showed that the deduced topological shape (model) can make the natural frequency and stiffness of the whole machine tool tend to be stable and convergent with a weight retention rate more than 75% as the design constraint. The subsystem structures with larger effective stress distributions were designated for stiffness improvement in the design. At the same time, the topological shape (model) was also employed in the design for weight reduction, focusing on minimizing redundant materials within the structure. In contrast to the consistency of the modal shapes before and after topological analysis, the sequential number of the modal mode of the machine tool model after topological analysis was advanced by two modes relative to those of the original situation, which means the original machine tool may be out of its inherently resonant frequency range. Also, the natural frequencies corresponding to each mode had an increasing tendency, and the maximum increase was 110.28%. Furthermore, the stiffness of the machine tool also increased significantly, with a maximum of 355.97%, leading to minor changes of the machine tool’s weight. These results confirm that the topology optimization based on machining characteristics proposed in this study for structure redesign improvement and stiffness enhancement is effective and feasible.
Intelligent Compaction Measurement Value in Variability Control of Subgrade Compaction Quality
Authors: Wang Zhiwen , Qian Jinsong , Ling Jianming
Published: December 2023

Intelligent compaction (IC) is an innovative and modified technology used for quality control in subgrade digital construction. However, current intelligent compaction measurement values (ICMVs) cannot provide accurate measurement of the filling layer when the strength of the underlying layer is relatively high. Experimental field tests conducted in the cut to fill subgrade were performed to collect and analyze the variability of ICMV called the vibration modulus (Evib). Furthermore, a new ICMV called the modulus of vibration compaction (Evc) that could remove the interference of the underlying layer and reveal the actual compaction state of filling layer is presented based on the theoretical analysis and numerical simulation method. It was also extracted to study the variability of the filling layer’s compaction state. The results of the above research indicate the influence of the underlying layer’s stiffness on overall compaction quality is remarkable. It was found that it is more likely to achieve the variability control of the compaction state of the filling layer by a new ICMV called Evc. The measured data, improved approaches, and associated conclusions that are presented provide valuable information for researchers and employees considering the use of IC technology.
Regenerative Cooling Comparison of LOX/LCH4 and LOX/LC3H8 Rocket Engines Using the One-Dimensional Regenerative Cooling Modelling Tool ODREC
Authors: Kose Yigithan Mehmet , Celik Murat
Published: December 2023

Due to the extreme temperatures inside the combustion chambers of liquid propellant rocket engines, the walls of the combustion chamber and the nozzle are cooled by either the fuel or the oxidizer in what is known as regenerative cooling. This study presents an indigenous computational tool developed for the analysis of heat transfer in regenerative cooling of such rocket engines. The developed tool incorporates a one-dimensional (1-D) combustion analysis to calculate the thermophysical properties of the combustion gas. Basic engine properties were calculated and used to generate a thrust chamber profile based on a bell-shaped nozzle. The hot gas side was analyzed using 1-D isentropic flow assumptions, along with heat transfer correlations. The coolant side was evaluated using the hydraulic analysis in the axial direction and the heat transfer analysis in the radial direction. Thermophysical properties and the phase of the coolant were determined using the given property tables and the instantaneous state of the coolant. This flexible and computationally less demanding tool was used to analyze two small-scale engines utilizing liquid hydrocarbon fuels, which are used in modern rocket propulsion. The wall cooling analyses of a liquid oxygen (LOX)/liquid methane (LCH4) engine and a liquid oxygen (LOX)/liquid propane (LC3H8) engine are presented. Fuel and oxidizer were used separately as coolants for both engines, and both of them experienced phase change. Results reveal the advantage of the high mass flow rate of the oxidizer in cooling performance. In addition, the results of this study show that the cooling of the LOX/LC3H8 engine is somewhat more challenging compared to the LOX/LCH4 engine.
Simultaneous Validity and Intra-Test Reliability of Joint Angle Measurement through Novel Multi-RGB Sensor-Based Three-Joint-Continuous-Motion Analysis: A Pilot Study
Authors: Ahn Junghoon , Choi Hongtaek , Lee Heehwa , Kim Suhng Wook , Lee Jinyoung , Kim Hyeong-Dong
Published: December 2023

The use of motion-analysis devices that can measure the progress of rehabilitation exercises for nerve paralysis is increasing because of the need to confirm the effectiveness of treatment for sports injuries. This study developed a new motion-analysis device that can be easily handled compared with the existing VICON motion-analysis device. Motion analysis of the human body (specifically, hip flexion, knee flexion, and trunk rotation) performed simultaneously with the new device and the existing VICON device was compared. Five healthy young men voluntarily participated in this study. Various joint angles were captured using a marker-less multi-view image-based motion-analysis system and a VICON motion capture system with markers during lower-extremity work. Intra-class correlation coefficient (ICC) analysis was used to examine simultaneous- and angular-limit validity and the intra-joint reliability of multi-point image-based motion-analysis systems. Simultaneous validity analysis showed that the highest ICCs for hip flexion, knee flexion, and trunk rotation were 0.924–0.998, 0.842–0.989 or higher, and 0.795–0.962, respectively. We confirmed that this new marker-less motion-analysis system has high accuracy and reliability in measuring joint kinematics in the lower extremities during rehabilitation and in monitoring the performance of athletes in training facilities.
Modeling and Visualizing the Dynamic Spread of Epidemic Diseases—The COVID-19 Case
Authors: Zachilas Loukas , Benos Christos
Published: December 2023

Our aim is to provide an insight into the procedures and the dynamics that lead the spread of contagious diseases through populations. Our simulation tool can increase our understanding of the spatial parameters that affect the diffusion of a virus. SIR models are based on the hypothesis that populations are “well mixed”. Our model constitutes an attempt to focus on the effects of the specific distribution of the initially infected individuals through the population and provide insights, considering the stochasticity of the transmission process. For this purpose, we represent the population using a square lattice of nodes. Each node represents an individual that may or may not carry the virus. Nodes that carry the virus can only transfer it to susceptible neighboring nodes. This important revision of the common SIR model provides a very realistic property: the same number of initially infected individuals can lead to multiple paths, depending on their initial distribution in the lattice. This property creates better predictions and probable scenarios to construct a probability function and appropriate confidence intervals. Finally, this structure permits realistic visualizations of the results to understand the procedure of contagion and spread of a disease and the effects of any measures applied, especially mobility restrictions, among countries and regions.
Testing Alpha-1 Antitrypsin Deficiency in Black Populations
Authors: Lafortune Pascale , Zahid Kanza , Ploszaj Magdalena , Awadalla Emilio , Carroll Tomás P. , Geraghty Patrick
Published: December 2023

Alpha-1 antitrypsin (AAT) deficiency (AATD) is an under-recognized hereditary disorder and a significant cause of chronic obstructive pulmonary disease (COPD), a disease that contributes to global mortality. AAT is encoded by the SERPINA1 gene, and severe mutation variants of this gene increase the risk of developing COPD. AATD is more frequently screened for in non-Hispanic White populations. However, AATD is also observed in other ethnic groups and very few studies have documented the mutation frequency in these other ethnic populations. Here, we review the current literature on AATD and allele frequency primarily in Black populations and discuss the possible clinical outcomes of low screening rates in a population that experiences poor health outcomes and whether the low frequency of AATD is related to a lack of screening in this population or a truly low frequency of mutations causing AATD. This review also outlines the harmful SERPINA1 variants, the current epidemiology knowledge of AATD, health inequity in Black populations, AATD prevalence in Black populations, the clinical implications of low screening of AATD in this population, and the possible dangers of not diagnosing or treating AATD.
Comment on Patsaki et al. Benefits from Incorporating Virtual Reality in Pulmonary Rehabilitation of COPD Patients: A Systematic Review and Meta-Analysis. Adv. Respir. Med. 2023, 91, 324–336
Authors: Salimi Mostafa
Published: December 2023

I am writing this comment regarding the review article by Patsaki et al. titled “Benefits from Incorporating Virtual Reality in Pulmonary Rehabilitation of COPD Patients: A Systematic Review and Meta-Analysis” [...]
Performing Yuánfèn: An Exploration of Untranslatable Words in the Lacunae Project
Authors: Piazzoli Erika , Corderi Novoa Modesto , Hogan Zoe
Published: December 2023

In this paper, we discuss a collaborative research project called Lacunae: Embodying the Untranslatable. The issue of untranslatability has been a much-discussed topic in translation studies, with recent debate linking it to performability. Although untranslatability has received some attention lately, the debate has been largely theoretical, confined to a textual conception of translation. In the study discussed in this article, we explored an applied approach to (un)translatability, working with/through the body in space, positing the body as the vehicle for deciphering the untranslatable. We draw on an embodied way of knowing as a phenomenological framework to construct knowledge as lived experience. The study aimed to investigate the lexical, intercultural, and aesthetic potential of performing untranslatability by exploring a series of untranslatable words through research-based theatre. The data generation process involved a retreat where nine researchers/artists/practitioners addressed the research question through practices like process drama, Butoh, physical theatre, improvisation, and visual arts on mixed media. In this paper, first, we introduce the theoretical framework and context of the study. Next, we illustrate the methodology, data analysis, and findings, with reference to one untranslatable word from the Chinese language, yuánfèn 缘分, loosely translated as ‘serendipity in relationships and life events’. We contemplate the practice in this workshop through a philosophical, pedagogical, and research-based lens. Finally, we contemplate future iterations of this project, reflecting on how performing yuánfèn could inform theatre-based research on migration and identity in education.
Interval Type-3 Fuzzy Inference System Design for Medical Classification Using Genetic Algorithms
Authors: Melin Patricia , Sánchez Daniela , Castillo Oscar
Published: December 2023

An essential aspect of healthcare is receiving an appropriate and opportune disease diagnosis. In recent years, there has been enormous progress in combining artificial intelligence to help professionals perform these tasks. The design of interval Type-3 fuzzy inference systems (IT3FIS) for medical classification is proposed in this work. This work proposed a genetic algorithm (GA) for the IT3FIS design where the fuzzy inputs correspond to attributes relational to a particular disease. This optimization allows us to find some main fuzzy inference systems (FIS) parameters, such as membership function (MF) parameters and the fuzzy if-then rules. As a comparison against the proposed method, the results achieved in this work are compared with Type-1 fuzzy inference systems (T1FIS), Interval Type-2 fuzzy inference systems (IT2FIS), and General Type-2 fuzzy inference systems (GT2FIS) using medical datasets such as Haberman’s Survival, Cryotherapy, Immunotherapy, PIMA Indian Diabetes, Indian Liver, and Breast Cancer Coimbra dataset, which achieved 75.30, 87.13, 82.04, 77.76, 71.86, and 71.06, respectively. Also, cross-validation tests were performed. Instances established as design sets are used to design the fuzzy inference systems, the optimization technique seeks to reduce the classification error using this set, and finally, the testing set allows the validation of the real performance of the FIS.
Insight into Bioactive Compounds, Antioxidant and Anti-Diabetic Properties of Rosehip (Rosa canina L.)-Based Tisanes with Addition of Hibiscus Flowers (Hibiscus sabdariffa L.) and Saffron (Crocus sativus L.)
Authors: Vasić Dušan , Katanić Stanković Jelena S. , Urošević Tijana , Kozarski Maja , Naumovski Nenad , Khan Haroon , Popović-Djordjević Jelena
Published: December 2023

Tisane is a fruit or herbal infusion, commonly referred to as herbal tea. These products are consumed as part of a balanced diet, which is closely related to the trend of a healthier lifestyle. In this work, tisanes prepared from rosehip (R), and herbal mixtures containing rosehip/hibiscus flowers (R/H) and rosehip/hibiscus flowers/saffron (R/H/S) were studied. Rosehip was dried by the convective drying method at 40, 50 and 60 °C. Total phenolic content (TPC), total flavonoid content (TFC), total flavonol content (TFlC), total anthocyanin content (TAC), antioxidant properties (DPPH∙ and ABTS∙+ assays) and in vitro inhibitory potential toward α-amylase of tisanes were examined. The highest TPC (based on dry weight (dw)) was measured in tisane obtained from rosehip dried at 60 °C (37.84 mg GAE/g dw). Tisanes prepared from a R/H/S mixture had the highest values of TFC (4.66–6.13 mg QUE/g dw), TFlC (2.67–3.98 mg QUE/g dw) and TAC (1.35–2.27 mg Cy 3-glc/g dw). The highest DPPH∙ scavenging activity (53.42 mg TE/g dw) was measured in rosehip (dried at 60 °C) tisane, whereas tisane prepared from a rosehip (dried at 60 °C)/hibiscus mixture expressed the best ABTS∙+ scavenging activity (107.44 mg TE/g dw). All tisane samples expressed high inhibitory potential toward α-amylase, with the highest activity of 85.03% and 89.90%, measured for tisanes prepared from rosehip/hibiscus flowers mixture (rosehip dried at 50 and 60 °C, respectively).
Preliminary Evaluation of Minor Cereals as Non-Traditional Brewing Raw Materials
Authors: Nocente Francesca , Galassi Elena , Taddei Federica , Natale Chiara , Gazza Laura
Published: December 2023

Recently, “minor” cereals have been gaining interest due to their distinctive characteristics, not only in terms of nutritional and health potential, but also because of their hardiness. To date, the use of several of these cereals for the production, both at artisan and industrial level, of foods such as pasta and bakery products has already been well established, whereas their investigation for the production of malt and beer has been more limited. In this work, a preliminary analysis of the malting aptitude of einkorn, tritordeum, food-grade sorghum and teff was evaluated. Grain quality parameters that influence the processes of malting and transformation into alcoholic beverages were evaluated, i.e., thousand-kernel weight, test weight, total protein and starch content, falling number, germination capacity, germination energy and amylase activity. Grain analyses showed, on average, satisfactory values for alcoholic fermented beverage production in all the cereal species examined (mainly in tritordeum), whereas the amylase activity of the malts produced was lower than that revealed in barley malt. Fermented drinks derived from these minor cereals, therefore, could be interesting for the light and gluten-free beer markets.
Predicting the Potential Distribution of Haloxylon ammodendron under Climate Change Scenarios Using Machine Learning of a Maximum Entropy Model
Authors: Xiao Fengjin , Liu Qiufeng , Qin Yun
Published: December 2023

Haloxylon ammodendron (H. ammodendron) is a second-class protected plant of national significance in China that is known for its growth in desert and semidesert regions, where it serves as a desert ecosystem guardian by playing a substantial role in maintaining ecosystem structure and function. The changing global climate has substantially altered the growth conditions for H. ammodendron. This study focuses on identifying the key variables influencing the distribution of H. ammodendron and determining their potential impact on future distribution. We employed the Maxent model to evaluate the current climate suitability for H. ammodendron distribution and to project its future changes across various shared socioeconomic pathway (SSP) scenarios. Our findings indicate that precipitation during the warmest quarter and precipitation during the wettest month are the most influential variables affecting the potentially suitable habitats of H. ammodendron. The highly suitable habitat area for H. ammodendron currently covers approximately 489,800 km2. The Maxent model forecasts an expansion of highly suitable H. ammodendron habitat under all future SSP scenarios, with the extent of unsuitable areas increasing with greater global warming. The increased highly suitable habitats range from 40% (SSP585) to 80% (SSP126) by the 2070s (2060–2080). Furthermore, our results indicate a continued expansion of desertification areas due to global warming, highlighting the significant role of H. ammodendron in maintaining desert ecosystem stability. This study offers valuable insights into biodiversity preservation and ecological protection in the context of future climate change scenarios.
Lipopolysaccharide Stimulates A549 Cell Migration through p-Tyr 42 RhoA and Phospholipase D1 Activity
Authors: Mahmud Shohel , Hamza Amir , Lee Yoon-Beom , Min Jung-Ki , Islam Rokibul , Dogsom Oyungerel , Park Jae-Bong
Published: December 2023

Cell migration is a crucial contributor to metastasis, a critical process associated with the mortality of cancer patients. The initiation of metastasis is triggered by epithelial–mesenchymal transition (EMT), along with the changes in the expression of EMT marker proteins. Inflammation plays a significant role in carcinogenesis and metastasis. Lipopolysaccharide (LPS), a typical inflammatory agent, promoted the generation of superoxide through the activation of p-Tyr42 RhoA, Rho-dependent kinase 2 (ROCK2), and the phosphorylation of p47phox. In addition, p-Tyr42 RhoA activated phospholipase D1 (PLD1), with PLD1 and phosphatidic acid (PA) being involved in superoxide production. PA also regulated the expression of EMT proteins. Consequently, we have identified MHY9 (Myosin IIA, NMIIA) as a PA-binding protein in response to LPS. MYH9 also contributed to cell migration and the alteration in the expression of EMT marker proteins. Co-immunoprecipitation revealed the formation of a complex involving p-Tyr42 RhoA, PLD1, and MYH9. These proteins were found to be distributed in both the cytosol and nucleus. In addition, we have found that p-Tyr42 RhoA PLD1 and MYH9 associate with the ZEB1 promoter. The suppression of ZEB1 mRNA levels was achieved through the knockdown of RhoA, PLD1, and MYH9 using si-RNAs. Taken together, we propose that p-Tyr42 RhoA and PLD1, responsible for producing PA, and PA-bound MYH9 are involved in the regulation of ZEB1 expression, thereby promoting cell migration.
Pathogenic Mechanisms and Therapeutic Approaches in Obesity-Related Knee Osteoarthritis
Authors: Shumnalieva Russka , Kotov Georgi , Ermencheva Plamena , Monov Simeon
Published: December 2023

The knee is the joint most frequently involved in osteoarthritis, a common joint disorder in the adult population that is associated with significant chronic joint pain, reduced mobility and quality of life. Recent studies have established an association between obesity and the development of knee osteoarthritis that goes beyond the increased mechanical load on the knees as weight-bearing joints. This link is based on the maintenance of a chronic low-grade inflammation, altered secretion of adipokines by the adipose tissue and development of sarcopenia. Major adipokines involved in the pathogenesis of obesity-related knee osteoarthritis include adiponectin, which appears to have a protective effect, as well as leptin, resistin and visfatin, which are associated with higher pain scores and more severe structural damage. Joint pain in knee osteoarthritis may be both nociceptive and neuropathic and is the result of complex mechanisms driven by nerve growth factor, calcitonin gene-related peptide and pro-inflammatory cytokines. The role of endogenous cannabinoids and gut microbiota in common mechanisms between obesity and knee pain has recently been studied. The aim of the present review is to highlight major pathogenic mechanisms in obesity-related knee osteoarthritis with special attention on pain and to comment on possible therapeutic approaches.
Automated Identification of Cutaneous Leishmaniasis Lesions Using Deep-Learning-Based Artificial Intelligence
Authors: Leal José Fabrício de Carvalho , Barroso Daniel Holanda , Trindade Natália Santos , Miranda Vinícius Lima de , Gurgel-Gonçalves Rodrigo
Published: December 2023

The polymorphism of cutaneous leishmaniasis (CL) complicates diagnosis in health care services because lesions may be confused with other dermatoses such as sporotrichosis, paracocidiocomycosis, and venous insufficiency. Automated identification of skin diseases based on deep learning (DL) has been applied to assist diagnosis. In this study, we evaluated the performance of AlexNet, a DL algorithm, to identify pictures of CL lesions in patients from Midwest Brazil. We used a set of 2458 pictures (up to 10 of each lesion) obtained from patients treated between 2015 and 2022 in the Leishmaniasis Clinic at the University Hospital of Brasilia. We divided the picture database into training (80%), internal validation (10%), and testing sets (10%), and trained and tested AlexNet to identify pictures of CL lesions. We performed three simulations and trained AlexNet to differentiate CL from 26 other dermatoses (e.g., chromomycosis, ecthyma, venous insufficiency). We obtained an average accuracy of 95.04% (Confidence Interval 95%: 93.81–96.04), indicating an excellent performance of AlexNet in identifying pictures of CL lesions. We conclude that automated CL identification using AlexNet has the potential to assist clinicians in diagnosing skin lesions. These results contribute to the development of a mobile application to assist in the diagnosis of CL in health care services.
Cellular Components of the Tumor Environment in Gliomas—What Do We Know Today?
Authors: Nafe Reinhold , Hattingen Elke
Published: December 2023

A generation ago, the molecular properties of tumor cells were the focus of scientific interest in oncology research. Since then, it has become increasingly apparent that the tumor environment (TEM), whose major components are non-neoplastic cell types, is also of utmost importance for our understanding of tumor growth, maintenance and resistance. In this review, we present the current knowledge concerning all cellular components within the TEM in gliomas, focusing on their molecular properties, expression patterns and influence on the biological behavior of gliomas. Insight into the TEM of gliomas has expanded considerably in recent years, including many aspects that previously received only marginal attention, such as the phenomenon of phagocytosis of glioma cells by macrophages and the role of the thyroid-stimulating hormone on glioma growth. We also discuss other topics such as the migration of lymphocytes into the tumor, phenotypic similarities between chemoresistant glioma cells and stem cells, and new clinical approaches with immunotherapies involving the cells of TEM.
Association of STAT4 Gene Polymorphisms (rs10181656, rs7574865, rs7601754, rs10168266) and Serum STAT4 Levels in Age-Related Macular Degeneration
Authors: Blekeris Tomas , Gedvilaite Greta , Kaikaryte Kriste , Kriauciuniene Loresa , Zaliuniene Dalia , Liutkevciene Rasa
Published: December 2023

Age-related macular degeneration (AMD) is a progressive degenerative disease that affects the central part of the retina: the macula. AMD is the most common cause of central vision loss in industrialized countries. Increasing attention is being paid to the study of genetic factors that may influence the manifestation of AMD. STAT4 protein is involved in the pathogenesis of numerous inflammatory processes, so we decided to investigate the association between STAT4 gene polymorphisms (rs10181656, rs7574865, rs7601754, and rs10168266) and age-related macular degeneration. Purpose: To investigate the association between STAT4 (rs10181656, rs7574865, rs7601754, and rs10168266) gene polymorphisms and STAT4 serum levels in patients with age-related macular degeneration. Methods and participants: The study included 150 individuals with early AMD, 150 individuals with exudative AMD, and 200 healthy subjects. DNA was extracted from peripheral blood leukocytes using the DNA salting-out method, and the genotyping was performed using a real-time polymerase chain reaction (RT-PCR) method. STAT4 serum levels were evaluated using the ELISA method. Statistical analysis was performed using “IBM SPSS “Statistics 29.0” software”. Results: The study revealed no statistically significant differences in the distribution of genotypes and alleles for the STAT4 polymorphisms (rs10181656, rs7574865, rs7601754, and rs10168266) between patients with AMD and the control group. Similarly, a gender-based analysis did not yield any significant differences in the genotype or allele frequencies. Age group comparisons also showed no statistically significant variations in the presence of these STAT4 polymorphisms between AMD patients and the control group. However, notably, individuals with exudative AMD displayed lower levels of serum STAT4 in comparison to the control group (median (IQR): 0.118 (0.042) vs. 0.262 (0.385), p = 0.005). Conclusion: Investigating STAT4 gene polymorphisms (rs10181656, rs7574865, rs7601754, and rs10168266) did not reveal a significant association with AMD. However, further analysis demonstrated intriguing findings regarding serum STAT4 levels. Exudative AMD patients with at least one G allele of the STAT4 rs10181656 exhibited significantly lower serum STAT4 levels than the control group subjects (p = 0.011). Similarly, those with at least one T allele of STAT4 rs10168266 had lower serum STAT4 levels compared to the control group subjects (p = 0.039). These results suggest a potential link between specific STAT4 genotypes and serum STAT4 levels in exudative AMD patients, shedding light on a novel aspect of the disease.
Aptasensors Based on Non-Enzymatic Peroxidase Mimics: Current Progress and Challenges
Authors: Davydova Anna S. , Vorobyeva Mariya A.
Published: December 2023

Immunoassays based on antibodies as recognizing elements and enzymes as signal-generating modules are extensively used now in clinical lab diagnostics, food, and environmental analyses. However, the application of natural enzymes and antibodies has some drawbacks, such as relatively high manufacturing costs, thermal instability, and lot-to-lot variations that lower the reproducibility of results. Oligonucleotide aptamers are able to specifically bind their targets with high affinity and selectivity, so they represent a prospective alternative to protein antibodies for analyte recognition. Their main advantages include thermal stability and long shelf life, cost-efficient chemical synthesis, and negligible batch-to-batch variations. At the same time, a wide variety of non-protein peroxidase mimics are now available that show strong potential to replace protein enzymes. Here, we review and analyze non-protein biosensors that represent a nexus of these two concepts: aptamer-based sensors (aptasensors) with optical detection (colorimetric, luminescent, or fluorescent) based on different peroxidase mimics, such as DNAzymes, nanoparticles, or metal-organic frameworks.
Emotional Bias among Individuals at Risk for Seasonal Affective Disorder—An EEG Study during Remission in Summer
Authors: Theódórsdóttir Dagný , Höller Yvonne
Published: December 2023

Emotional bias in attention and memory is well researched in depression. Patients with depression prioritize processing of negative information over positive input. While there is evidence that emotional bias exists in seasonal affective disorder (SAD) during winter, it is unclear whether such altered cognition exists also during summer. Moreover, it is unclear whether such bias affects attention, memory, or both. In this study, we investigated 110 individuals in summer, 34 of whom reported suffering from low mood during winter, according to the seasonal pattern assessment questionnaire. While the electroencephalogram was recorded, participants learned 60 emotional pictures and subsequently were asked to recognize them in an old/new task. There were no clear group differences in behavioral measures, and no brain response differences in frontal alpha power during learning. During recognition, at 100–300 ms post stimulus individuals with higher seasonality scores exhibited larger alpha power in response to negative as compared to neutral stimuli, while individuals with low seasonality scores exhibited larger alpha power in response to positive as compared to neutral stimuli. While we cannot draw conclusions whether this is an effect of attention or memory, the finding suggests that early cognitive processes are altered already during summer in individuals with increased likelihood to experience SAD during winter. Our data provide evidence for an all-year-round cognitive vulnerability in this population.
Frequency, Characteristics, and Correlates of Cognitive Complaints in a Cohort of Individuals with Post-Acute Sequelae of COVID-19
Authors: Muschel Cayla , Lynch Sean T. , Dornbush Rhea , Klepacz Lidia , Shahar Sivan , Ferrando Stephen J.
Published: December 2023

Background: Cognitive complaints are among the most frequent symptoms of post-acute sequelae of COVID-19 (PASC). This study aimed to investigate the frequency, characteristics, and clinical correlates of cognitive complaints (CC) in PASC, particularly in relation to objective neuropsychological (NP) performance. Methods: Seventy-four participants underwent psychiatric, medical, and NP testing approximately 7 months after acute COVID-19. The Patient Assessment of Own Functioning Inventory (PAOFI) was used to characterize the frequency and severity of CC in domains of memory, language, and cognitive/executive function. The associations of CC with sociodemographic, medical, psychiatric, and NP variables were assessed utilizing correlational analysis, logistic regression, and pairwise comparisons of those categorized as having CC vs. not having CC. Results: Taken together, approximately one-third of the study participants had clinically significant CC. Memory difficulty was the most frequent CC, although all categories were frequently endorsed. Memory and cognitive/executive complaints correlated with NP tests in these and multiple other NP domains. CC were more likely to be under-reported in those with diminished NP performance than over-reported in those without diminished performance. Acute COVID-19 symptom severity, elevated depressive symptoms, and NP tests of diminished attention and psychomotor processing speed were independent predictors of CC in logistic regression. Conclusions: Cognitive complaints after acute COVID-19 should be taken seriously, as they are likely to reflect diminished NP performance, as well as medical, psychiatric, and functional burdens. However, patients with PASC may not accurately identify or characterize objective cognitive difficulties, so programs offering comprehensive care for patients with PASC should offer formal neuropsychological testing.