bluuebunny/crossref_metadata_2025 huggingface dataset:
Axial Stiffness Augmentation by Adding Superconductor Bulks or Limiting Permanent Magnet Rings to a Horizontal Axis Zero-Field Cooled High-Tc Radial Passive Superconducting Bearing
Authors: Arsénio Costa António J. , Fernandes João F. P. , Costa Branco Paulo J.
Published: May 2024

This paper analyzes the viability of different solutions to passively augment the axial stiffness of a horizontal axis radial levitation passive magnetic bearing (PMB) with a previously studied topology. The zero-field cooling (ZFC) of high-temperature superconductor (HTS) bulks promotes higher magnetic impulsion and levitation forces and lower electromagnetic losses than those with field-cooling (FC) but, on the other hand, the guiding stability is much lower than those with FC. Because of stability reasons, FC was adopted in most superconducting maglev systems. The trend of this research group has been to develop a horizontal axis HTS ZFC radial levitation PMB presenting notable levitation forces with reduced electromagnetic losses, defined by a topology that creates guiding stability. Previous work has shown that optimizing the bearing geometry to maximize magnetic guidance forces might not be enough to guarantee the axial stiffness required for many applications. First, the extent to which guidance forces are augmented by increasing the number of HTS bulks in the stator is evaluated. Then, the axial stiffness augmentation by passively adding two limiting permanent magnet (PM) rings is evaluated. The results show that the axial stiffness is highly augmented by adding limiting PM rings with no significant additional investment. This change enables the use of the studied ZFC superconducting PMB in high-precision axial stability applications, such as precision gyroscopes, horizontal axis propellers, and turbines.
Crater Triangle Matching Algorithm Based on Fused Geometric and Regional Features
Authors: Jin Mingda , Shao Wei
Published: May 2024

Craters are regarded as significant navigation landmarks during the descent and landing process in small body exploration missions for their universality. Recognizing and matching craters is a crucial prerequisite for visual and LIDAR-based navigation tasks. Compared to traditional algorithms, deep learning-based crater detection algorithms can achieve a higher recognition rate. However, matching crater detection results under various image transformations still poses challenges. To address the problem, a composite feature-matching algorithm that combines geometric descriptors and region descriptors (extracting normalized region pixel gradient features as feature vectors) is proposed. First, the geometric configuration map is constructed based on the crater detection results. Then, geometric descriptors and region descriptors are established within each feature primitive of the map. Subsequently, taking the salience of geometric features into consideration, composite feature descriptors with scale, rotation, and illumination invariance are generated through fusion geometric and region descriptors. Finally, descriptor matching is accomplished by computing the relative distances between descriptors and adhering to the nearest neighbor principle. Experimental results show that the composite feature descriptor proposed in this paper has better matching performance than only using shape descriptors or region descriptors, and can achieve a more than 90% correct matching rate, which can provide technical support for the small body visual navigation task.
The Residue Chemistry Transformation Linked to the Fungi Keystone Taxa during Different Residue Tissues Incorporation into Mollisols in Northeast China
Authors: Zhang Qilin , Li Xiujun , Chen Guoshuang , Luo Nana , Sun Jing , Ngozi Ezemaduka Anastasia , Lu Xinrui
Published: May 2024

Managing carbon input from crop straw in cropland ecosystems could increase soil organic carbon (SOC) sequestration to achieve C neutrality and mitigate climate change. The complexity of the chemical structures of crop residue largely affects SOC sequestration. Fungi communities play an important role in the degradation of crop residues. However, the relationship between the fungal community composition and the chemical structures of crop residues remains unclear and requires further investigation. Therefore, a 120-day incubation experiment was conducted in Mollisols in Northeast China to investigate the decomposition processes and dynamics of maize straw stem (ST), leaf (LE) and sheath (SH) residues using 13C-NMR spectroscopy. Additionally, the microbiomes associated with these residues were analyzed through high-throughput sequencing to explore their relationship. Our results showed that the alkyl C contents in all treatments exhibited increases ranging from 15.1% to 49.1%, while the O-alkyl C contents decreased, ranging from 0.02% to 11.2%, with the incubation time. The A/OA ratios of ST, LE and SH treatments were increased by 23.7%, 43.4% and 49.3% with incubation time, respectively. During the early stages of straw decomposition, Ascomycota dominated, and in the later stage, Basidiomycota were predominant. The class of Sordariomycetes played a key role in the chemistry transformation of straw tissues during decomposition. The keystone taxa abundances, Fusarium_kyushuense, and Striatibotrys_eucylindrospora, showed strong negative correlations with di-O-alkyl C and carbonyl-C content and positive correlations with the β-glucosidase and peroxidase enzyme activity, respectively. In conclusion, our study demonstrated that the keystone taxa play a significant role in regulating the chemical structures of straw tissues, providing a better understanding of the influence of residue quality on SOC sequestration.
Effective Biotic Elicitors for Augmentation of Secondary Metabolite Production in Medicinal Plants
Authors: Jain Divya , Bisht Shiwali , Parvez Anwar , Singh Kuldeep , Bhaskar Pranav , Koubouris Georgios
Published: May 2024

Plants are an essential component of our daily diet, and their nutritional value has been thoroughly studied for many years. The ability of plants to adapt to changing environmental conditions through signaling systems is an essential component of their survival. Plants undergo an array of physiological alterations to respond to stress from biotic sources. Secondary compounds frequently accumulate in crops that are sensitive to stress, particularly those with several eliciting agents or signaling molecules. Plants contain various types of bioactive compounds, including phytosterols, alkaloids, glycosides, and polyphenols, which make them valuable for the food and pharmaceutical industries. The increased production of secondary metabolites via elicitation has opened up a new field of study with the potential to provide substantial financial gains for the pharmaceutical and nutraceutical industries. These elicitors are pharmacological compounds that activate specific transcription factors and up-regulate genes to activate metabolic pathways. Thus, the current review discusses the mechanism of biotic elicitation and various elicitation techniques using biotic (proteins, carbohydrates, rhizobacteria, fungi, and hormones) elicitors that may increase the yield of secondary metabolites, particularly in medicinal plants, which is advantageous to the agrochemical and therapeutic industries.
Integration of Image and Sensor Data for Improved Disease Detection in Peach Trees Using Deep Learning Techniques
Authors: Chen Kuiheng , Lang Jingjing , Li Jiayun , Chen Du , Wang Xuaner , Zhou Junyu , Liu Xuan , Song Yihong , Dong Min
Published: May 2024

An innovative framework for peach tree disease recognition and segmentation is proposed in this paper, with the aim of significantly enhancing model performance in complex agricultural settings through deep learning techniques and data fusion strategies. The core innovations include a tiny feature attention mechanism backbone network, an aligned-head module, a Transformer-based semantic segmentation network, and a specially designed alignment loss function. The integration of these technologies not only optimizes the model’s ability to capture subtle disease features but also improves the efficiency of integrating sensor and image data, further enhancing the accuracy of the segmentation tasks. Experimental results demonstrate the superiority of this framework. For disease detection, the proposed method achieved a precision of 94%, a recall of 92%, and an accuracy of 92%, surpassing classical models like AlexNet, GoogLeNet, VGGNet, ResNet, and EfficientNet. In lesion segmentation tasks, the proposed method achieved a precision of 95%, a recall of 90%, and an mIoU of 94%, significantly outperforming models such as SegNet, UNet, and UNet++. The introduction of the aligned-head module and alignment loss function provides an effective solution for processing images lacking sensor data, significantly enhancing the model’s capability to process real agricultural image data. Through detailed ablation experiments, the study further validates the critical role of the aligned-head module and alignment loss function in enhancing model performance, particularly in the attention-head ablation experiment where the aligned-head configuration surpassed other configurations across all metrics, highlighting its key role in the overall framework. These experiments not only showcase the theoretical effectiveness of the proposed method but also confirm its practical value in agricultural disease management practices.
Influence of Organic Humic Fertilizer “Tumat” on the Productivity of Sugar Beet
Authors: Suleimenov Beibut , Kaisanova Gulmira , Suleimenova Mariya , Tanirbergenov Samat
Published: May 2024

The production of sugar beet in the Republic of Kazakhstan is insufficient to meet the domestic sugar needs of the population. This shortfall is attributed to the natural and climatic conditions, the high cost of production, and the low use of mineral fertilizers. The objective of the study is to investigate the impact of the organic humic fertilizer “Tumat” on the growth, development, yield, and sugar content of sugar beet in the conditions of irrigated light chestnut soils in Southeast Kazakhstan. Scientific research confirms the effectiveness of using the organic humic fertilizer Tumat for cultivating sugar beets. This fertilizer is highly bioavailable and contains a balanced mix of essential macronutrients and micronutrients, polyunsaturated fatty acids, and other biologically active substances. Foliar feeding of sugar beets enriches the soil with exchangeable potassium, mobile phosphorus, and easily hydrolyzable nitrogen during the plant’s vegetative period. Using the Tumat fertilizer enhances plant germination rates by 6.0–16.0%, stimulates growth and development, accelerates the ripening of sugar beets, and increases the yield of tubers by 10.5–15.2%, sugar content by 0.4–0.7%, and sugar output by 13.6–20.8%. An organic humic fertilizer, is recommended as an environmentally safe and effective agricultural product that boosts the productivity and quality of sugar beets, as well as soil fertility.
Impact of Key Agronomic Traits on Economic Yield Traits in Anhui Rice (Oryza sativa L. spp. japonica)
Authors: Ren Yi , Xu Ending , Zhang Peijiang , Zhan Xinchun , He Qingyuan , Zou Yu
Published: May 2024

Nitrogen (N) application rates and planting density are key factors affecting grain yield and quality. In this experiment, four varieties, Huijing 753 (HJ 753), Huijing 855 (HJ 855), Huijing 866 (HJ 866), and Dangjing 8 (DJ 8), were used to investigate their effects on the yield and quality of japonica rice in Anhui, which has a lower soil N supply capacity. The current study set four levels of N application N1, N2, N3, and N4 (120, 180, 240, and 300) kg ha−1 and three planting densities D1, D2, and D3 (high-density: 45 × 104; medium-density: 37.5 × 104; low-density: 32.2 × 104) hills ha−1 for a total of 12 treatments. The effects of N application and planting density on rice yield, composition, processing quality, appearance quality, and cooking quality were analyzed. The results showed that with the increase in N application rates and planting density, the effective panicle number per plant and grain number per panicle of each rice variety increased, while HJ 753, HJ 855, and HJ 866 reached the highest yield under the N3D1 treatment and then gradually declined, and DJ 8 had the highest yield in the N4D1 treatment. In addition, the processing quality of various varieties can be improved by increasing the N application rate and planting density, but the appearance quality will deteriorate, the amylose content will also decrease, and gel consistency will also be lower. Therefore, under medium-planting density conditions, N at a rate of 240 kg ha−1 was the best for HJ 753, HJ 855, and HJ 866, and using 300 kg ha−1 for DJ 8 resulted in high grain yields and superior rice grain quality. In the next step, physiological, biochemical, and genotypic analyses of these three japonica rice varieties were carried out to provide a scientific basis and technical support for accelerating the breeding of high-yield japonica rice varieties.
Meropenem/Vaborbactam—A Mechanistic Review for Insight into Future Development of Combinational Therapies
Authors: Hillyer Trae , Shin Woo Shik
Published: May 2024

Beta-lactam antibiotics have been a major climacteric in medicine for being the first bactericidal compound available for clinical use. They have continually been prescribed since their development in the 1940s, and their application has saved an immeasurable number of lives. With such immense use, the rise in antibiotic resistance has truncated the clinical efficacy of these compounds. Nevertheless, the synergism of combinational antibiotic therapy has allowed these drugs to burgeon once again. Here, the development of meropenem with vaborbactam—a recently FDA-approved beta-lactam combinational therapy—is reviewed in terms of structure rationale, activity gamut, pharmacodynamic/pharmacokinetic properties, and toxicity to provide insight into the future development of analogous therapies.
Catalase, Glutathione Peroxidase, and Peroxiredoxin 2 in Erythrocyte Cytosol and Membrane in Hereditary Spherocytosis, Sickle Cell Disease, and β-Thalassemia
Authors: Melo Daniela , Ferreira Fátima , Teles Maria José , Porto Graça , Coimbra Susana , Rocha Susana , Santos-Silva Alice
Published: May 2024

Catalase (CAT), glutathione peroxidase (GPx), and peroxiredoxin 2 (Prx2) can counteract the deleterious effects of oxidative stress (OS). Their binding to the red blood cell (RBC) membrane has been reported in non-immune hemolytic anemias (NIHAs). Our aim was to evaluate the relationships between CAT, GPx, and Prx2, focusing on their role at the RBC membrane, in hereditary spherocytosis (HS), sickle cell disease (SCD), β-thalassemia (β-thal), and healthy individuals. The studies were performed in plasma and in the RBC cytosol and membrane, evaluating OS biomarkers and the enzymatic activities and/or the amounts of CAT, GPx, and Prx2. The binding of the enzymes to the membrane appears to be the primary protective mechanism against oxidative membrane injuries in healthy RBCs. In HS (unsplenectomized) and β-thal, translocation from the cytosol to the membrane of CAT and Prx2, respectively, was observed, probably to counteract lipid peroxidation. RBCs from splenectomized HS patients showed the highest membrane-bound hemoglobin, CAT, and GPx amounts in the membrane. SCD patients presented the lowest amount of enzyme linkage, possibly due to structural changes induced by sickle hemoglobin. The OS-induced changes and antioxidant response were different between the studied NIHAs and may contribute to the different clinical patterns in these patients.
Enhancing Human Key Point Identification: A Comparative Study of the High-Resolution VICON Dataset and COCO Dataset Using BPNET
Authors: Lee Yunju , Lama Bibash , Joo Sunghwan , Kwon Jaerock
Published: May 2024

Accurately identifying human key points is crucial for various applications, including activity recognition, pose estimation, and gait analysis. This study introduces a high-resolution dataset formed via the VICON motion capture system and three diverse 2D cameras. It facilitates the training of neural networks to estimate 2D key joint positions from images and videos. The study involved 25 healthy adults (17 males, 8 females), executing normal gait for 2 to 3 s. The VICON system captured 3D ground truth data, while the three 2D cameras collected images from different perspectives (0°, 45°, and 135°). The dataset was used to train the Body Pose Network (BPNET), a popular neural network model developed by NVIDIA TAO. Additionally, a comparison entails another BPNET model trained on the COCO 2017 dataset, featuring over 118,000 annotated images. Notably, the proposed dataset exhibited a higher level of accuracy (14.5%) than COCO 2017, despite comprising one-fourth of the image count (23,741 annotated image). This substantial reduction in data size translates to improvements in computational efficiency during model training. Furthermore, the unique dataset’s emphasis on gait and precise prediction of key joint positions during normal gait movements distinguish it from existing alternatives. This study has implications ranging from gait-based person identification, and non-invasive concussion detection through sports temporal analysis, to pathologic gait pattern identification.
Study on the Alkali–Sulfur Co-Activation and Mechanical Properties of Low-Carbon Cementitious Composite Materials Based on Electrolytic Manganese Residue, Carbide Slag, and Granulated Blast-Furnace Slag
Authors: Liang Jianbo , Liu Rongjin , Jing Daiyan , Lu Fuhua , Zhao Yanrong , Xie Zhihan , Huang Wanyu , Chen Tingchao
Published: May 2024

Industrial solid waste is characterized by complex mineral phases and various components. Low-carbon cementitious materials can be prepared through precise regulation based on the material composition and properties of various industrial solid wastes. In this study, electrolytic manganese residue (EMR), carbide slag (CS), and granulated blast-furnace slag (GBFS) were used as alternatives to cement to prepare multicomponent solid waste cementitious materials. The effects of the proportions of EMR and CS on the cementitious activity of GBFS and the activation mechanism of alkali and sulfur were studied. The results showed that with increasing EMR content, the strength first increased and then decreased. At a GBFS content of 20%, CS content of 2%, and EMR content of 8%, the compressive strength was highest, reaching 45.5 MPa after 28 days of curing, mainly because the OH− in CS and SO42− in EMR synergistically stimulated the active components in GBFS. Hydrated products such as ettringite and hydrated calcium silicate (C–S–H gel) were generated and interlaced with each other to improve the densification of the mortar. Overall, the proposed system provides an avenue to reduce or replace the production of cement clinker and achieve the high-value-added utilization of industrial solid waste.
Atom Exchange Radical Cyclization: A Sustainable Synthetic Approach towards New Functionalized Targets
Authors: Anderlini Biagio , Severini Andrea , Ferrari Camilla , Fontanesi Claudio , Ascari Vittorio , Braidi Niccolò , Roncaglia Fabrizio
Published: May 2024

In this study, we demonstrate the direct preparation of dihalo-γ-lactams featuring two distinct halogens from dichloroamides using a novel atom exchange radical cyclization (AERC) procedure. This method integrates the established atom transfer radical cyclization (ATRC) with halogen exchange in solution. The technique operates under mild conditions and requires small amounts of metallic copper, serving as both a supplemental activator and reducing agent.
Efficient Parallel FDTD Method Based on Non-Uniform Conformal Mesh
Authors: Liu Kaihui , Huang Tao , Zheng Liang , Jin Xiaolin , Lin Guanjie , Huang Luo , Cai Wenjing , Gong Dapeng , Fang Chunwang
Published: May 2024

The finite-difference time-domain (FDTD) method is a versatile electromagnetic simulation technique, widely used for solving various broadband problems. However, when dealing with complex structures and large dimensions, especially when applying perfectly matched layer (PML) absorbing boundaries, tremendous computational burdens will occur. To reduce the computational time and memory, this paper presents a Message Passing Interface (MPI) parallel scheme based on non-uniform conformal FDTD, which is suitable for convolutional perfectly matched layer (CPML) absorbing boundaries, and adopts a domain decomposition approach, dividing the entire computational domain into several subdomains. More importantly, only one magnetic field exchange is required during the iterations, and the electric field update is divided into internal and external parts, facilitating the synchronous communication of magnetic fields between adjacent subdomains and internal electric field updates. Finally, unmanned helicopters, helical antennas, 100-period folded waveguides, and 16 × 16 phased array antennas are designed to verify the accuracy and efficiency of the algorithm. Moreover, we conducted parallel tests on a supercomputing platform, showing its satisfactory reduction in computational time and excellent parallel efficiency.
Study on Evaluation and Prediction for Shale Gas PDC Bit in Luzhou Block Sichuan Based on BP Neural Network and Bit Structure
Authors: Chen Ye , Sang Yu , Wang Xudong , Ye Xiaoke , Shi Huaizhong , Wu Pengcheng , Li Xinlong , Xiong Chao
Published: May 2024

Deep and ultra-deep shale gas resources have great potential, but well drilling faces many challenges. The Polycrystalline Diamond Compact (PDC) bit has become the primary rock-breaking instrument for oil and gas drilling. Reasonable bit structure designs can promote rock-breaking efficiency and extend service life. In this study, reverse modeling technology is used to analyze the structural characteristics of PDC bits collected in the field, and the influence of the structural characteristics of the bit at a specific interval on the rate of penetration (ROP) and drill footage is investigated using the Spearman rank correlation coefficient method. The number of blades, cutting angle of the cutters, crown rotation radius, internal cone angle, and diameter of the cutters are discovered to be the main structural characteristics that affect the ROP and footage of the bits, and the degree of influence varies depending on the formation conditions. The number of blades, crown rotation radius, inner cone angle, and cutting angle of the cutters have a significant impact on the ROP, whereas blade thickness, gauge length, gauge width, nozzle equivalent diameter have a significant impact on the bit footage. In addition, a back propagation (BP) neural network is utilized to build a prediction model of bit footage and ROP over a certain interval based on the structural characteristics of the bit. The goodness of fit of the model is greater than 85%, and its accuracy is high. Based on the usage of the bit, the evaluation and prediction of the bit can provide a reference for the structural design and optimization of the bit in a specific interval, guide the bit selection work, rationally plan the drilling operation, and reduce the drilling cost.
Design and Validation of New Methodology for Hydraulic Passage Integration in Carbon Composite Mechanisms
Authors: Sleiman Maya , Khalil Khaled , Olaru Adrian , AlFayad Samer
Published: May 2024

Humanoid robots have rapidly become the focus of research in recent years, with the most impressive humanoids being hydraulically actuated. This is due to the capacity of hydraulic actuation to provide simultaneous high forces with dynamic motion. The scarcity of hydraulic robots is mainly due to the difficulty in managing hydraulic pipes. These decrease the robot’s social acceptance and safety and are the main source of leaks. Recently, there has been a new trend in hydraulically actuated robots that involves creating internal oil passages within the robotic parts to eliminate the need for external flexible tubes. Developing these parts using carbon composite materials provides an additional advantage of ensuring lightweight yet robust robotic parts. However, assembling hydraulically integrated parts is challenging due to the leakproof requirement and the high pressures involved. This article proposes a new, reliable, and effective method that ensures a strong, leakproof assembly. A mathematical model with 11 parameters describing the assembly zone and accounting for geometric parameters, material characteristic parameters, and porosity has been developed. A numerical model was conducted to evaluate the effect of these parameters on the state of the assembly. Experimental validation was conducted to evaluate the assembly force. A satisfactory convergence between the mathematical model and the experimental results was observed with a maximum deviation of 20%.
Conditioning Theory for ML-Weighted Pseudoinverse and ML-Weighted Least Squares Problem
Authors: Samar Mahvish , Zhu Xinzhong , Xu Huiying
Published: May 2024

The conditioning theory of the ML-weighted least squares and ML-weighted pseudoinverse problems is explored in this article. We begin by introducing three types of condition numbers for the ML-weighted pseudoinverse problem: normwise, mixed, and componentwise, along with their explicit expressions. Utilizing the derivative of the ML-weighted pseudoinverse problem, we then provide explicit condition number expressions for the solution of the ML-weighted least squares problem. To ensure reliable estimation of these condition numbers, we employ the small-sample statistical condition estimation method for all three algorithms. The article concludes with numerical examples that highlight the results obtained.
Exercise, mTOR Activation, and Potential Impacts on the Liver in Rodents
Authors: Onaka Giuliano Moreto , Carvalho Marianna Rabelo de , Onaka Patricia Kubalaki , Barbosa Claudiane Maria , Martinez Paula Felippe , Oliveira-Junior Silvio Assis de
Published: May 2024

The literature offers a consensus on the association between exercise training (ET) protocols based on the adequate parameters of intensity and frequency, and several adaptive alterations in the liver. Indeed, regular ET can reverse glucose and lipid metabolism disorders, especially from aerobic modalities, which can decrease intrahepatic fat formation. In terms of molecular mechanisms, the regulation of hepatic fat formation would be directly related to the modulation of the mechanistic target of rapamycin (mTOR), which would be stimulated by insulin signaling and Akt activation, from the following three different primary signaling pathways: (I) growth factor, (II) energy/ATP-sensitive, and (III) amino acid-sensitive signaling pathways, respectively. Hyperactivation of the Akt/mTORC1 pathway induces lipogenesis by regulating the action of sterol regulatory element binding protein-1 (SREBP-1). Exercise training interventions have been associated with multiple metabolic and tissue benefits. However, it is worth highlighting that the mTOR signaling in the liver in response to exercise interventions remains unclear. Hepatic adaptive alterations seem to be most outstanding when sustained by chronic interventions or high-intensity exercise protocols.
Habitat Enrichment Causes Changes in Fish Behavioural Characteristics: A Case Study of Sparus latus
Authors: Guo Yu , Chen Zhanlong , Qin Chuanxin , Yu Gang , Zhang Jia
Published: May 2024

To better understand the habitat preferences and behavioural ecology of Sparus latus, we performed an experiment using box-shaped reefs as habitat enrichment materials, allowing us to determine the behavioural strategies and drivers involved in the response to different enrichment structures. The results showed that the first contact time of S. latus was negatively correlated (Pearson’s correlation, p < 0.005) with the distribution rate in the artificial reef area. Enrichment structures affected the habitat preferences of S. latus, and there was a significant difference in the average distribution rate between the control and treatment groups (Adonis, p < 0.001). The opening ratio (Adonis, R2 = 0.36) explained the distribution difference of S. latus better than the opening shape (Adonis, R2 = 0.12). In the absence of an enrichment structure, S. latus remained more active during the daytime, exhibiting poor clustering, while in the presence of an enrichment structure, S. latus exhibited clustered movement at night. The opening ratio was negatively correlated with the average interindividual distance (Spearman’s correlation, p < 0.01) and showed a significant positive correlation with the average distribution rate in the reef area (Spearman’s correlation, p < 0.001), indicating that the reef opening ratio significantly affected the reef-tropism and clustering behaviours of S. latus. The light intensity was negatively correlated with the average distance moved, and the average speed (Spearman’s correlation, p < 0.05) was significantly positively correlated with the reef first contact time (Spearman’s correlation, p < 0.001), indicating that the light intensity affected the exploration and activity patterns of S. latus. These results provide a research basis for analysing the pattern and process of fish proliferation induced by artificial reef habitats.
Deformation Characteristics and Energy Evolution Rules of Siltstone under Stepwise Cyclic Loading and Unloading
Authors: Miao Shengjun , Shang Xiangfan , Wang Hui , Liang Mingchun , Yang Pengjin , Liu Chunkang
Published: May 2024

Uniaxial step cyclic loading and unloading tests on siltstone were conducted to investigate the mechanisms and evolution characteristics of rock deformation, including elastic, viscoelastic, and plastic aspects. This study proposes a method for separating dissipated energy into damage energy, which is used for particle slippage and structural fractures, and plastic energy, which remains in cracks that do not open after unloading. Additionally, elastic energy is divided into particle elastic energy, released by particle rebound, and crack elastic energy, released by the reopening of compacted cracks. The results indicate that as the stress amplitude increases, the damage energy consumption, plastic energy consumption, particle elastic energy, and crack elastic energy increase. At peak stress, significant expansion and penetration of cracks within the rock sample occur, leading to a sharp increase in damage energy consumption and a dramatic decrease in the rock sample’s mechanical properties, with the particle elastic energy dropping quickly. Plastic energy dissipation relates solely to cracks that do not reopen during unloading, with minimal change after reaching peak stress. The calculated damage variables, based on damage energy consumption, align with the deformation and energy characteristics of the rock, providing a reasonable description of the damage development process of the rock under cyclic loading and unloading.
Magnetic Iron Oxide Nanomaterials for Lipase Immobilization: Promising Industrial Catalysts for Biodiesel Production
Authors: Hajareh Haghighi Farid , Binaymotlagh Roya , Palocci Cleofe , Chronopoulou Laura
Published: May 2024

Biodiesel is a mixture of fatty acid alkyl esters (FAAEs) mainly produced via transesterification reactions among triglycerides and short-chain alcohols catalyzed by chemical catalysts (e.g., KOH, NaOH). Lipase-assisted enzymatic transesterification has been proposed to overcome the drawbacks of chemical synthesis, such as high energy consumption, expensive separation of the catalyst from the reaction mixture and production of large amounts of wastewater during product separation and purification. However, one of the main drawbacks of this process is the enzyme cost. In recent years, nano-immobilized lipases have received extensive attention in the design of robust industrial biocatalysts for biodiesel production. To improve lipase catalytic efficiency, magnetic nanoparticles (MNPs) have attracted growing interest as versatile lipase carriers, owing to their unique properties, such as high surface-to-volume ratio and high enzyme loading capacity, low cost and inertness against chemical and microbial degradation, biocompatibility and eco-friendliness, standard synthetic methods for large-scale production and, most importantly, magnetic properties, which provide the possibility for the immobilized lipase to be easily separated at the end of the process by applying an external magnetic field. For the preparation of such effective magnetic nano-supports, various surface functionalization approaches have been developed to immobilize a broad range of industrially important lipases. Immobilization generally improves lipase chemical-thermal stability in a wide pH and temperature range and may also modify its catalytic performance. Additionally, different lipases can be co-immobilized onto the same nano-carrier, which is a highly effective strategy to enhance biodiesel yield, specifically for those feedstocks containing heterogeneous free fatty acids (FFAs). This review will present an update on the use of magnetic iron oxide nanostructures (MNPs) for lipase immobilization to catalyze transesterification reactions for biodiesel production. The following aspects will be covered: (1) common organic modifiers for magnetic nanoparticle support and (2) recent studies on modified MNPs-lipase catalysts for biodiesel production. Aspects concerning immobilization procedures and surface functionalization of the nano-supports will be highlighted. Additionally, the main features that characterize these nano-biocatalysts, such as enzymatic activity, reusability, resistance to heat and pH, will be discussed. Perspectives and key considerations for optimizing biodiesel production in terms of sustainability are also provided for future studies.
Normal and Dysregulated Sphingolipid Metabolism: Contributions to Podocyte Injury and Beyond
Authors: Tolerico Matthew , Merscher Sandra , Fornoni Alessia
Published: May 2024

Podocyte health is vital for maintaining proper glomerular filtration in the kidney. Interdigitating foot processes from podocytes form slit diaphragms which regulate the filtration of molecules through size and charge selectivity. The abundance of lipid rafts, which are ordered membrane domains rich in cholesterol and sphingolipids, near the slit diaphragm highlights the importance of lipid metabolism in podocyte health. Emerging research shows the importance of sphingolipid metabolism to podocyte health through structural and signaling roles. Dysregulation in sphingolipid metabolism has been shown to cause podocyte injury and drive glomerular disease progression. In this review, we discuss the structure and metabolism of sphingolipids, as well as their role in proper podocyte function and how alterations in sphingolipid metabolism contributes to podocyte injury and drives glomerular disease progression.
BACH2: The Future of Induced T-Regulatory Cell Therapies
Authors: Zwick Daniel , Vo Mai Tram , Shim Young Jun , Reijonen Helena , Do Jeong-su
Published: May 2024

BACH2 (BTB Domain and CNC Homolog 2) is a transcription factor that serves as a central regulator of immune cell differentiation and function, particularly in T and B lymphocytes. A picture is emerging that BACH2 may function as a master regulator of cell fate that is exquisitely sensitive to cell activation status. In particular, BACH2 plays a key role in stabilizing the phenotype and suppressive function of transforming growth factor-beta (TGF-β)-derived human forkhead box protein P3 (FOXP3)+ inducible regulatory T cells (iTregs), a cell type that holds great clinical potential as a cell therapeutic for diverse inflammatory conditions. As such, BACH2 potentially could be targeted to overcome the instability of the iTreg phenotype and suppressive function that has hampered their clinical application. In this review, we focus on the role of BACH2 in T cell fate and iTreg function and stability. We suggest approaches to modulate BACH2 function that may lead to more stable and efficacious Treg cell therapies.
MR Relaxometry for Discriminating Malignant Ovarian Cystic Tumors: A Prospective Multicenter Cohort Study
Authors: Kawahara Naoki , Kobayashi Hiroshi , Maehana Tomoka , Iwai Kana , Yamada Yuki , Kawaguchi Ryuji , Takahama Junko , Marugami Nagaaki , Nishi Hirotaka , Sakai Yosuke , Takano Hirokuni , Seki Toshiyuki , Yokosu Kota , Hirata Yukihiro , Yoshida Koyo , Ujihira Takafumi , Kimura Fuminori
Published: May 2024

Background: Endometriosis-associated ovarian cancer (EAOC) is a well-known type of cancer that arises from ovarian endometrioma (OE). OE contains iron-rich fluid in its cysts due to repeated hemorrhages in the ovaries. However, distinguishing between benign and malignant tumors can be challenging. We conducted a retrospective study on magnetic resonance (MR) relaxometry of cyst fluid to distinguish EAOC from OE and reported that this method showed good accuracy. The purpose of this study is to evaluate the accuracy of a non-invasive method in re-evaluating pre-surgical diagnosis of malignancy by a prospective multicenter cohort study. Methods: After the standard diagnosis process, the R2 values were obtained using a 3T system. Data on the patients were then collected through the Case Report Form (CRF). Between December 2018 and March 2023, six hospitals enrolled 109 patients. Out of these, 81 patients met the criteria required for the study. Results: The R2 values calculated using MR relaxometry showed good discriminating ability with a cut-off of 15.74 (sensitivity 80.6%, specificity 75.0%, AUC = 0.750, p < 0.001) when considering atypical or borderline tumors as EAOC. When atypical and borderline cases were grouped as OE, EAOC could be distinguished with a cut-off of 16.87 (sensitivity 87.0%, specificity 61.1%). Conclusions: MR relaxometry has proven to be an effective tool for discriminating EAOC from OE. Regular use of this method is expected to provide significant insights for clinical practice.
Automated Classification of Physiologic, Glaucomatous, and Glaucoma-Suspected Optic Discs Using Machine Learning
Authors: Diener Raphael , Renz Alexander W. , Eckhard Florian , Segbert Helmar , Eter Nicole , Malcherek Arnim , Biermann Julia
Published: May 2024

In order to generate a machine learning algorithm (MLA) that can support ophthalmologists with the diagnosis of glaucoma, a carefully selected dataset that is based on clinically confirmed glaucoma patients as well as borderline cases (e.g., patients with suspected glaucoma) is required. The clinical annotation of datasets is usually performed at the expense of the data volume, which results in poorer algorithm performance. This study aimed to evaluate the application of an MLA for the automated classification of physiological optic discs (PODs), glaucomatous optic discs (GODs), and glaucoma-suspected optic discs (GSODs). Annotation of the data to the three groups was based on the diagnosis made in clinical practice by a glaucoma specialist. Color fundus photographs and 14 types of metadata (including visual field testing, retinal nerve fiber layer thickness, and cup–disc ratio) of 1168 eyes from 584 patients (POD = 321, GOD = 336, GSOD = 310) were used for the study. Machine learning (ML) was performed in the first step with the color fundus photographs only and in the second step with the images and metadata. Sensitivity, specificity, and accuracy of the classification of GSOD vs. GOD and POD vs. GOD were evaluated. Classification of GOD vs. GSOD and GOD vs. POD performed in the first step had AUCs of 0.84 and 0.88, respectively. By combining the images and metadata, the AUCs increased to 0.92 and 0.99, respectively. By combining images and metadata, excellent performance of the MLA can be achieved despite having only a small amount of data, thus supporting ophthalmologists with glaucoma diagnosis.
Associations of Brain Arteriovenous Malformation-Related Factors with Epileptic Seizure Presentations
Authors: Mukhtarova Kymbat , Nurimanov Chingiz , Zholdybayeva Elena , Makhambetov Yerbol , Akshulakov Serik
Published: May 2024

Background: Arteriovenous malformations (AVMs) are abnormal tangles of arteries and veins that connect directly without an intervening capillary bed. Epileptic seizures are the second most common symptom in patients with brain AVMs, occurring in 30 to 50% of cases. However, the exact mechanism of epileptic seizure development in AVMs remains unclear. In this study, we aimed to investigate the factors associated with epileptic seizures in patients with brain arteriovenous malformation (AVMs) in Kazakhstan. Methods: A case–control study was conducted, which included 163 patients diagnosed with brain AVMs. Demographic and clinical data were collected and analyzed, and multivariate logistic regression was built to assess the factors associated with seizures in brain AVMs. Results: from this rupture of vessels OR = 0.36 95% CI (0.14–0.91, a medium-to-high Spetzler-Martin score (III–V) OR = 6.16 (2.14–17.69) and OR = 3.05 (1.08–8.68), respectively), location in brain cortex (frontal lobe OR = 6.16 (2.04–18.54), parietal lobe OR = 9.37 (3.26–26.91), temporal lobe OR = 4.57 (1.56–13.36), occipital lobe OR = 0.27 (0.08–0.91), and the presence of hemiparesis OR = 0.12 (0.02–0.66) in adverse outcomes were statistically significantly associated with the presence of epileptic seizures in brain arteriovenous malformations patients. Conclusions: To conclude, this contributed to model factors associated with brain arteriovenous malformations that are linked to epileptic seizures.
Laboratory Tests, Bacterial Resistance, and Treatment Options in Adult Patients Hospitalized with a Suspected Urinary Tract Infection
Authors: Froom Paul , Shimoni Zvi
Published: May 2024

Patients treated for systemic urinary tract infections commonly have nonspecific presentations, and the specificity of the results of the urinalysis and urine cultures is low. In the following narrative review, we will describe the widespread misuse of urine testing, and consider how to limit testing, the disutility of urine cultures, and the use of antibiotics in hospitalized adult patients. Automated dipstick testing is more precise and sensitive than the microscopic urinalysis which will result in false negative test results if ordered to confirm a positive dipstick test result. There is evidence that canceling urine cultures if the dipstick is negative (negative leukocyte esterase, and nitrite) is safe and helps prevent the overuse of urine cultures. Because of the side effects of introducing a urine catheter, for patients who cannot provide a urine sample, empiric antibiotic treatment should be considered as an alternative to culturing the urine if a trial of withholding antibiotic therapy is not an option. Treatment options that will decrease both narrower and wider spectrum antibiotic use include a period of watching and waiting before antibiotic therapy and empiric treatment with antibiotics that have resistance rates > 10%. Further studies are warranted to show the option that maximizes patient comfort and safety.
Performance of Artificial Intelligence Models Designed for Automated Estimation of Age Using Dento-Maxillofacial Radiographs—A Systematic Review
Authors: Khanagar Sanjeev B. , Albalawi Farraj , Alshehri Aram , Awawdeh Mohammed , Iyer Kiran , Alsomaie Barrak , Aldhebaib Ali , Singh Oinam Gokulchandra , Alfadley Abdulmohsen
Published: May 2024

Automatic age estimation has garnered significant interest among researchers because of its potential practical uses. The current systematic review was undertaken to critically appraise developments and performance of AI models designed for automated estimation using dento-maxillofacial radiographic images. In order to ensure consistency in their approach, the researchers followed the diagnostic test accuracy guidelines outlined in PRISMA-DTA for this systematic review. They conducted an electronic search across various databases such as PubMed, Scopus, Embase, Cochrane, Web of Science, Google Scholar, and the Saudi Digital Library to identify relevant articles published between the years 2000 and 2024. A total of 26 articles that satisfied the inclusion criteria were subjected to a risk of bias assessment using QUADAS-2, which revealed a flawless risk of bias in both arms for the patient-selection domain. Additionally, the certainty of evidence was evaluated using the GRADE approach. AI technology has primarily been utilized for automated age estimation through tooth development stages, tooth and bone parameters, bone age measurements, and pulp–tooth ratio. The AI models employed in the studies achieved a remarkably high precision of 99.05% and accuracy of 99.98% in the age estimation for models using tooth development stages and bone age measurements, respectively. The application of AI as an additional diagnostic tool within the realm of age estimation demonstrates significant promise.
Effect of Al Content on Microstructure and Properties of AlxCr0.2NbTiV Refractory High-Entropy Alloys
Authors: Li Rongbin , Li Qianqian , Zhang Zhixi , Zhang Rulin , Xing Yue , Han Doudou
Published: May 2024

High-temperature creep refers to the slow and continuous plastic deformation of materials under the effects of high temperatures and mechanical stress over extended periods, which can lead to the degradation or even failure of the components’ functionality. AlxCr0.2NbTiV (x = 0.2, 0.5, or 0.8) refractory high-entropy alloys were fabricated by arc melting. The effects of Al content on the microstructure of AlxCr0.2NbTiV alloys were studied using X-ray diffraction, scanning electron microscopy, and electron backscatter diffraction. The microhardness, compression properties, and nanoindentation creep properties of AlxCr0.2NbTiV alloys were also tested. The results show that the AlxCr0.2NbTiV series exhibits a BCC single-phase structure. As the Al content increases, the lattice constant of the alloys gradually decreases, and the intensity of the (110) crystal plane diffraction peak increases. Adding aluminum enhances the effect of solution strengthening; however, due to grain coarsening, the microhardness and room temperature compressive strength of the alloy are only slightly improved. Additionally, because the effect of solution strengthening is diminished at high temperatures, the compressive strength of the alloy at 1000 °C is significantly reduced. The creep mechanism of the alloys is predominantly governed by dislocation creep. Moreover, increasing the Al content helps to reduce the sensitivity of the alloy to the loading rate during the creep process. At a loading rate of 2.5 mN/s, the Al0.8Cr0.2NbTiV alloy exhibits the lowest creep strain rate sensitivity index (m), which is 0.0758.
Ising Paradigm in Isobaric Ensembles
Authors: Cerdeiriña Claudio A. , Troncoso Jacobo
Published: May 2024

We review recent work on Ising-like models with “compressible cells” of fluctuating volume that, as such, are naturally treated in NpT and μpT ensembles. Besides volumetric phenomena, local entropic effects crucially underlie the models. We focus on “compressible cell gases” (CCG), namely, lattice gases with fluctuating cell volumes, and “compressible cell liquids” (CCL) with singly occupied cells and fluctuating cell volumes. CCGs contemplate singular diameters and “Yang–Yang features” predicted by the “complete scaling” formulation of asymmetric fluid criticality, with a specific version incorporating “ice-like” hydrogen bonding further describing the “singularity-free scenario” for the low-temperature unusual thermodynamics of supercooled water. In turn, suitable CCL variants constitute adequate prototypes of water-like liquid–liquid criticality and the freezing transition of a system of hard spheres. On incorporating vacant cells to such two-state CCL variants, one obtains three-state, BEG-like models providing a satisfactory description of water’s “second-critical-point scenario” and the whole phase behavior of a simple substance like argon. Future challenges comprise water’s crystal–fluid phase behavior and metastable states.