Search Results (13,659)

Background/Objectives: The effect of sodium butyrate (NaB), β-glucan (βG) and vitamins in the diet on gut microbiome, cortisol level, lysozyme activity and growth parameters of juvenile hybrid sturgeon (Acipenser gueldenstaedtii♀ × Acipenser baerii♂) was determined. Methods: Sturgeon hybrids (n = 144) were divided into three groups with enriched feeding (mg/kg of feed): FQV1 (50 NaB; 20 βG; const. vitamins), FQV2 (150 NaB; 20 βG; const. vitamins), FQV3 (50 NaB; 60 βG; const. vitamins) and control (not supplemented), each group in triplicate, 12 fish in each repetition. Rearing was carried out for 30 days in controlled conditions. Gut microbiome was characterized using Next Generation Sequencing (NGS) of DNA samples isolated from intestinal content. Cortisol level was determined using the ELISA test. Lysozyme activity was measured by turbidimetric test. Results: Based on data obtained from NGS, it was determined that the FQV1 group is characterized by the highest values of diversity indices (Shannon, Simpson and Chao-1) and the largest number of ASVs (Amplicon Sequence Variants). The highest abundance of probiotic bacteria (Lactobacillus, Lactococcus) was determined in the FQV1 group. The highest cortisol concentration was determined in the control (33.26 ng/mL), while the lowest was in FQV3 (27.75 ng/mL). The highest lysozyme activity was observed in FQV1 (154.64 U/mL), and the lowest in FQV2 (104.39 U/mL) and control (121.37 U/mL) (p < 0.05). FQV2 was characterized by significantly more favorable values of breeding indicators (p < 0.05). Conclusions: The obtained results prove that an appropriate composition of NaB, βG and vitamins can be used in the commercial breeding of juvenile hybrid sturgeons. Full article

Background: Busulfan is an FDA-approved alkylating drug used in the chemotherapy of advanced acute myeloid leukemia. The precise mechanisms by which Busulfan kills spermatogonia stem cells (SSCs) are not yet completely understood. Methods: Using a murine model, we evaluated Busulfan-induced apoptosis and DNA damage signaling between testis and ovary tissues. We executed RT-qPCR, analyzed single-nuclei RNA sequencing data and performed in situ hybridization for the localization of the gene expression in the tissues. Results: The results indicate that, in contrast to female germ cells, haploid male germ cells undergo significant apoptosis following Busulfan chemotherapy. Moreover, a gene enrichment analysis revealed that reactive oxygen species may activate the inflammatory response in part through the TNF-α/NF-κB signaling pathway. Interestingly, in the testis, the mRNA levels of TNF-α and TAF7 (TATA box-binding protein-associated factor 7) are downregulated, and testosterone levels suppressed. Mechanistically, the promoter of TNF-α has a conserved motif for binding TAF7, which is necessary for its transcriptional activation and may require further in-depth study. We next analyzed the tumorigenic function of TAF7 and revealed that it is highly overexpressed in several types of human cancers, particularly testicular germ cell tumors, and associated with poor patient survival. Therefore, we executed in situ hybridization and single-nuclei RNA sequencing, finding that less TAF7 mRNA is present in SSCs after chemotherapy. Conclusions: Thus, our data indicate a possible function of TAF7 in the regulation of SSCs and spermatogenesis following downregulation by Busulfan. These findings may account for the therapeutic effects of Busulfan and underlie its potential impact on cancer chemotherapy prognosis. Full article

According to the different excitation methods, automotive eddy current retarders (ECRs) can be divided into electrically excited retarders (EERs) and permanent magnet excited retarders (PMERs), and EERs and PMERs have certain complementarity in control and braking characteristics. Therefore, based on literature research, this article proposes a hybrid excitation rotary electromagnetic retarder (HERER) and conducts numerical simulation analysis and experimental research on the braking performance of the HERER. Firstly, the structure and working principle of the HERER are introduced. Secondly, based on the principles of electromagnetics, an equivalent magnetic circuit analysis model of the HERER is established. Then, a finite element analysis model of the HERER is established using Jmag 14 electromagnetic simulation software, and the braking performance of the HERER under different current and speed conditions is studied. Finally, bench tests are conducted on the air loss torque and eddy current braking performance of the HERER. The effectiveness of the finite element analysis model and equivalent magnetic circuit model of the HERER is verified. Full article

In this paper, we present an optimization planning method for enhancing power quality in integrated energy systems in large-building microgrids by adjusting the sizing and deployment of hybrid energy storage systems. These integrated energy systems incorporate wind and solar power, natural gas supply, and interactions with electric vehicles and the main power grid. In the optimization planning method developed, the objectives of cost-effective and low-carbon operation, the lifecycle cost of hybrid energy storage, power quality improvements, and renewable energy utilization are targeted and coordinated by using utility fusion theory. Our planning method addresses multiple energy forms—cooling, heating, electricity, natural gas, and renewable energies—which are integrated through a combined cooling, heating, and power system and a natural gas turbine. The hybrid energy storage system incorporates batteries and compressed-air energy storage systems to handle fast and slow variations in power demand, respectively. A sensitivity matrix between the output power of the energy sources and the voltage is modeled by using the power flow method in DistFlow, reflecting the improvements in power quality and the respective constraints. The method proposed is validated by simulating various typical scenarios on the modified IEEE 13-node distribution network topology. The novelty of this paper lies in its focus on the application of integrated energy systems within large buildings and its approach to hybrid energy storage system planning in multiple dimensions, including making co-location and capacity sizing decisions. Other innovative aspects include the coordination of hybrid energy storage combinations, simultaneous siting and sizing decisions, lifecycle cost calculations, and optimization for power quality enhancement. As part of these design considerations, microgrid-related technologies are integrated with cutting-edge nearly zero-energy building designs, representing a pioneering attempt within this field. Our results indicate that this multi-objective, multi-dimensional, utility fusion-based optimization method for hybrid energy storage significantly enhances the economic efficiency and quality of the operation of integrated energy systems in large-building microgrids in building-level energy distribution planning. Full article

Background/Objectives: Giant splenic artery aneurysms (SAAs) and pseudoaneurysms (SAPs) represent rare conditions, characterized by a diameter greater than or equal to 5 cm. The risk of rupture is increased compared to common SAAs and SAPs, necessitating urgent treatments to prevent it. Methods: This systematic review was conducted through a comprehensive search involving the PubMed, Google Scholar, and Scopus databases. A total of 82 patients and 65 articles were included in the analysis. For each patient, we investigated age, sex, symptoms, comorbidities, the presence of a true or a false aneurysm, the dimensional criteria used to define dilations as giant aneurysms or pseudoaneurysms, the dimension of the two greatest diameters, imaging studies, surgical treatment, post-operative length of stay (LOS), and post-operative follow-up. Results: The results revealed a similar incidence in both genders (43 males vs. 39 females) with a median age of 55.79 years. The most frequently described symptom was pain (59.76%). Thirteen cases were false aneurysms and 69 were true aneurysms. The mean greatest diameter was 9.90 cm. The CT scan was the most utilized imaging study (80.49%). Open, endovascular, and hybrid surgery were performed in 47, 26, and 9 patients, respectively, with complication rates of 14.89%, 23.08%, and 22.22% occurring for each treatment. The post-operative LOS was 12.29 days, 2.36 days, and 5 days, respectively. The median follow-up was 17.28 months overall. No recanalization was observed after endovascular procedures during the follow-up period. Conclusions: The dimensional criterion to define SAAs and SAPs as giant was most frequently that at least one diameter was ≥ 5 cm. The CT scan was the most frequently utilized radiological study to diagnose giant SAAs and SAPs. Finally, endovascular procedures, open surgeries, and hybrid treatments presented similar post-operative complication rates. The post-operative LOS was lower for the endovascular group, and the follow-up period did not show aneurysm recanalization in any patients. Full article

Cell-free millimeter wave (mmWave) multiple-input multiple-output (MIMO) can effectively overcome the shadow fading effect and provide macro gain to boost the throughput of communication networks. Nevertheless, the majority of the existing studies have overlooked the user-centric characteristics and practical fronthaul capacity limitations. To solve these practical problems, we introduce a resource allocation scheme using statistical channel state information (CSI) for uplink user-centric cell-free mmWave MIMO system. The hybrid beamforming (HBF) architecture is deployed at each access point (AP), while the central processing unit (CPU) only combines the received signals by the large-scale fading decoding (LSFD) method. We further frame the issue of maximizing sum-rate subject to the fronthaul capacity constraint and minimum rate constraint. Based on the alternating optimization (AO) and fractional programming method, we present an algorithm aimed at optimizing the users’ transmit power for the power allocation (PA) subproblem. Then, an algorithm relying on the majorization–minimization (MM) method is given for the HBF subproblem, which jointly optimizes the HBF and the LSFD coefficients. Full article

Zenker’s Diverticulum (ZD) is the most common hypopharyngeal diverticulum; however, it is often underdiagnosed. It results from the herniation of the mucosa and submucosa through Killian’s Triangle. Dysphagia is the primary symptom, occurring in 80–90% of cases. The primary goal of treatment is to transect the cricopharyngeal muscle (CM) and connect the ZD cavity to the esophageal lumen. Traditional treatments include surgical open transcervical diverticulectomy and CM septomyotomy, using rigid or flexible endoscopes. However, surgery is burdened by technical difficulties and not negligible rates of adverse events (AEs). For this reason, endoscopic techniques for ZD treatment have gained traction in recent years. Flexible endoscopic septum division (FESD), introduced nearly 20 years ago, involves a full-thickness incision of the diverticular septum. The advent of third-space endoscopy has led to the application of these techniques to ZD treatment as well. Zenker-POEM (Z-POEM) and, subsequently, Per Oral Endoscopic Septomyotomy (POES) have been developed. Hybrid techniques, such as Peroral Endoscopic Diverticulotomy (POED) and tunneling-free methods, represent additional ZD treatment options. This review outlines the armamentarium of ZD endoscopic management, summarizing the characteristics of these techniques, their benefits and limitations, and highlighting future research directions. Full article

The primary objective of this paper is to identify the critical components of the acoustic field for a piston-type pressure reducing valve (PRV) with a high pressure reduction ratio, as well as to predict unfavorable noise both experimentally and numerically. The numerical calculations were conducted using a hybrid approach that combines computational fluid dynamics (CFD) and computational aeroacoustics (CAA). Flow-induced pressure fluctuation from unsteady turbulent flow extracted by the throttling cone, the valve body and the baffle in the low-pressure chamber were considered as individual dipole acoustic sources during calculation of the internal acoustic field. The results indicated that the selected three dipole acoustic sources always played a vital role in the response of the acoustic field, and none of them could be ignored. In comparison, the throttling cone had the most salient contribution to acoustic field distribution, the valve body took second place, and the baffle had the least salient contribution. The radiated noise of interest was predicted using the indirect boundary element method (IBEM), incorporating all three components as dipole acoustic sources simultaneously; the numerical noise values showed strong validation against the experimental data. Furthermore, the distribution of sound pressure levels, as well as directional and planar field points, is also presented. This paper provides new insights into the role of each component in flow-induced noise, and offers technical support for noise reduction design and optimization of pressure reducing valves. Full article

Agricultural productivity is one of the critical factors towards ensuring food security across the globe. However, some of the main crops, such as potato, tomato, and mango, are usually infested by leaf diseases, which considerably lower yield and quality. The traditional practice of diagnosing disease through visual inspection is labor-intensive, time-consuming, and can lead to numerous errors. To address these challenges, this study evokes the AgirLeafNet model, a deep learning-based solution with a hybrid of NASNetMobile for feature extraction and Few-Shot Learning (FSL) for classification. The Excess Green Index (ExG) is a novel approach that is a specified vegetation index that can further the ability of the model to distinguish and detect vegetative properties even in scenarios with minimal labeled data, demonstrating the tremendous potential for this application. AgirLeafNet demonstrates outstanding accuracy, with 100% accuracy for potato detection, 92% for tomato, and 99.8% for mango leaves, producing incredibly accurate results compared to the models already in use, as described in the literature. By demonstrating the viability of a deep learning/IoT system architecture, this study goes beyond the current state of multi-crop disease detection. It provides practical, effective, and efficient deep-learning solutions for sustainable agricultural production systems. The innovation of the model emphasizes its multi-crop capability, precision in results, and the suggested use of ExG to generate additional robust disease detection methods for new findings. The AgirLeafNet model is setting an entirely new standard for future research endeavors. Full article

The polar motion (PM, including two parameters PMx and PMy) ultra-short-term prediction (1–10 days) is demanded in the real-time navigation of satellites and spacecrafts. Improving the PMx and PMy ultra-short-term predictions accuracies are a key to optimize the performance of these related applications. Currently, the least squares (LS)+autoregressive (AR) hybrid method is regarded as one of the most capable approaches for ultra-short-term predictions of PMx and PMy. The Kalman filter has proven to be effective in improving the ultra-short-term prediction performance of the LS+AR hybrid method, but the PMx and PMy ultra-short-term predictions accuracies are still not able to satisfy some related applications. In order to improve the performance of PM ultra-short-term prediction, it is worth exploring the combinations of existing methods. Throughout the existing predicted methods, the LS+multivariate autoregressive (MAR) hybrid method by using the Kalman filter has the potential to improve the accuracy of PM ultra-short-term prediction. In addition, a PM prediction performance analysis of the LS+MAR hybrid method by using the Kalman filter, namely the LS+MAR+Kalman hybrid method, is still missing. In this contribution, we proposed the LS+MAR+Kalman hybrid method for PM ultra-short-term prediction. The data sets for PM predictions, which range from 1 to 10 days, have been tested based on the International Earth Rotation and Reference Systems Service Earth Orientation Parameter (IERS EOP) 14 C04 series to assess the performance of the LS+MAR+Kalman hybrid model. The experimental results illustrated that the LS+MAR+Kalman hybrid method can effectively execute PMy ultra-short-term predictions. The improvement of PMy prediction accuracy can rise up to 12.69% for 10-day predictions, and the improvement of ultra-short-term predictions is 7.64% on average. Full article

The rise of social media has transformed the landscape of news dissemination, presenting new challenges in combating the spread of fake news. This study addresses the automated detection of misinformation within written content, a task that has prompted extensive research efforts across various methodologies. We evaluate existing benchmarks, introduce a novel hybrid word embedding model, and implement a web framework for text classification. Our approach integrates traditional frequency–inverse document frequency (TF–IDF) methods with sophisticated feature extraction techniques, considering linguistic, psychological, morphological, and grammatical aspects of the text. Through a series of experiments on diverse datasets, applying transfer and incremental learning techniques, we demonstrate the effectiveness of our hybrid model in surpassing benchmarks and outperforming alternative experimental setups. Furthermore, our findings emphasize the importance of dataset alignment and balance in transfer learning, as well as the utility of incremental learning in maintaining high detection performance while reducing runtime. This research offers promising avenues for further advancements in fake news detection methodologies, with implications for future research and development in this critical domain. Full article

Hybrid turbine blade protection systems, which combine thermal barrier coatings (TBCs) and cooling mechanisms, are essential for safeguarding turbine blades in advanced gas turbine applications. However, conventional furnace evaluation methods are inadequate for accurately simulating the complex thermal conditions experienced by TBCs in these environments. Initial testing revealed substantial degradation of TBCs when subjected to high temperatures without the necessary cooling support. To address this limitation, the furnace setup was modified to incorporate a cooling air system. This system channeled 400 °C air to the back surface of the TBC while subjecting the front to 1400 °C furnace air, effectively replicating the thermal gradient encountered in hybrid protection systems. The modified furnace setup demonstrated a remarkable improvement in the performance of yttria-stabilized zirconia TBCs. By cooling the back surface of the TBC, the metal substrate temperature decreased, thereby improving the thermal gradient on the coating and its durability. The thermal gradient achieved by the modified furnace was verified to simulate accurately the conditions experienced by TBCs in advanced gas turbines. The conventional furnace setup, lacking a cooling mechanism, overestimated the heat transfer on the TBCs, leading to inaccurate results. The modified furnace, with its integrated cooling system, more accurately simulated the conditions experienced by TBCs in real-world advanced gas turbine applications and more reliably assessed their performance. Full article

Background: Homozygous cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) loss is one of the parameters that support the designation of meningiomas as Central Nervous System (CNS) WHO grade 3 tumors. Evaluation of CDKN2A/B by sequencing or Fluorescence in situ hybridization (FISH) is costly and not always readily accessible. An immunohistochemistry (IHC)-based marker for the evaluation of CDKN2A/B loss would provide faster results at a lower cost. Methods: This retrospective study included patients diagnosed with meningioma at our institution between 2016 and 2019. Archival tumor tissue was used for analysis. MTAP immunohistochemistry (IHC) was performed at various dilutions (1:1200, 1:400, 1:200, 1:100) using two different antibodies, and p16 IHC was conducted simultaneously. These analyses were carried out at two different institutions. To determine the sensitivity and specificity of MTAP and p16 as surrogate markers for CDKN2A/B loss, CDKN2A FISH was utilized as the gold standard. Results: Overall, 46/49 tumors showed strong MTAP staining (94%) at institution 1, and 44/49 (90%) showed either faint positive or positive results at institution 2. One grade 3 meningioma that demonstrated homozygous CDKN2A loss by FISH also showed loss of MTAP expression by IHC. One grade 2 meningioma showed regional CDKN2A loss by FISH and variable MTAP expression under different IHC conditions. MTAP expression evaluation was superior at a dilution of 1:100 with the Abnova Anti-MTAP Monoclonal antibody. Conclusions: P16 expression was variable and did not correlate with either MTAP expression or CDKN2A FISH results. MTAP IHC is a promising surrogate marker for the evaluation of CDKN2A status in meningiomas. Full article

To detect moving weak targets in the dual function radar communication (DFRC) system of an orthogonal frequency division multiplexing (OFDM) waveform, a modified hybrid integration method is addressed in this paper. A high-speed aircraft can cause range walk (RW) and Doppler walk (DW), rendering traditional detection methods ineffective. To overcome RW and DW, this paper proposes an integration approach combining DFRC and OFDM. The proposed approach consists of two primary components: intra-frame coherent integration and hybrid multi-inter-frame integration. After the echo signal is re-fragmented into multiple subfragments, the first step involves integrating energy across fixed situations within intra-frames for each subcarrier. Subsequently, coherent integration is performed across the subfragments, followed by the application of a Radon transform (RT) to generate frames based on the properties derived from the coherent integration output. This paper provides detailed expressions and analyses for various performance metrics of our proposed method, including the communication bit error ratio (BER), responses of coherent and non-coherent outputs, and probability of detection. Simulation results demonstrate the effectiveness of our strategy. Full article

The reliability of electric vehicles (EVs) is crucial for the performance and safety of modern transportation systems. Electric motors are the driving force in EVs, and their maintenance is critical for efficient EV performance. The conventional fault detection methods for motors often struggle with accurately capturing complex spatiotemporal vibration patterns. This paper proposes a recurrent convolutional neural network (RCNN) for effective defect detection in motors, taking advantage of the advances in deep learning techniques. The proposed approach applies long short-term memory (LSTM) layers to capture the temporal dynamics essential for fault detection and convolutional neural network layers to mine local features from the segmented vibration data. This hybrid method helps the model to learn complicated representations and correlations within the data, leading to improved fault detection. Model development and testing are conducted using a sizable dataset that includes various kinds of motor defects under differing operational scenarios. The results demonstrate that, in terms of fault detection accuracy, the proposed RCNN-based strategy performs better than the traditional fault detection techniques. The performance of the model is assessed under varying vibration data noise levels to further guarantee its effectiveness in practical applications. Full article