Browse Articles

Multi-scale convolutional transformer network for motor imagery brain-computer interface

Abstract Brain-computer interface (BCI) systems allow users to communicate with external devices by translating neural signals into real-time commands. Convolutional neural networks (CNNs) have been effectively utilized for decoding motor imagery electroencephalography (MI-EEG) signals in BCIs. However, traditional CNN-based methods face challenges such as individual variability in EEG signals and the limited receptive fields of CNNs. This study presents the Multi-Scale Convolutional Transformer (MSCFormer) model that integrates multiple CNN branches for multi-scale feature extraction and a Transformer module to capture global dependencies, followed by a fully connected layer for classification. The multi-branch multi-scale CNN structure effectively addresses individual variability in EEG signals, enhancing the model’s generalization capabilities, while the Transformer encoder strengthens global feature integration and improves decoding performance. Extensive experiments on the BCI IV-2a and IV-2b datasets show that MSCFormer achieves average accuracies of 82.95% (BCI IV-2a) and 88.00% (BCI IV-2b), with kappa values of 0.7726 and 0.7599 in five-fold cross-validation, surpassing several state-of-the-art methods. These results highlight MSCFormer’s robustness and accuracy, underscoring its potential in EEG-based BCI applications. The code has been released in https://github.com/snailpt/MSCFormer.

Fault analysis on deep groove ball bearing using ResNet50 and AlexNet50 algorithms

Abstract Deep Groove Ball Bearings (DGBBs) serve multipurpose and are used for the propeller shaft movement and applications based on revolving. They have great applications in industry related to axial and radial loads. The major risk factors are faults in bearings. Data analyzed for faults in the DGBBs help us conclude that there are 4 types of bearing faults. For instance, Excluding HB- Healthy Bearing, there are CF- Case Fault, BF- Ball Fault, IRF- Inner Ring Fault, and ORF- Outer Ring Fault. The input parameters are represented by using 14 features in the evaluation. Next, a feature ranking method is established to classify the bearing fault and contribution of each of the features is used as input conditions. It displays the involvement value for each of the 14 parameters. Automatic fault classification has been done by Artificial Neural Networks (ANN). Training on various algorithms is performed, noting and storing the probability of correct prediction for comparison. The probability of correct predictions decreases as the number of samples representing faults increases. A high efficiency of around 97.9% has been achieved for the Resnet50 algorithm. The classifier learner achieved an accuracy of 97% using the neural network, followed by the decision tree and discriminant analysis.

Cystatin 6 (CST6) and Legumain (LGMN) are potential mediators in the pathogenesis of preeclampsia

Abstract Preeclampsia results from placental insufficiency and causes maternal endothelial dysfunction and multi-organ damage. Our in-silico analysis identified Cystatin 6 (CST6), a cysteine protease inhibitor, as located on the placental surface where it might be released into maternal circulation. This study aimed to characterise CST6 and one of its high affinity targets, Legumain (LGMN), in preeclampsia and assess its biomarker potential by measuring levels in maternal circulation. Placental CST6 mRNA expression was significantly increased in 78 pregnancies complicated by early-onset preeclampsia (delivering at < 34 weeks’ gestation) relative to 30 gestation matched controls (P < 0.0001). LGMN mRNA expression was significantly decreased (P = 0.0309). Circulating CST6 was increased in 35 pregnancies complicated by early-onset preeclampsia (< 34 weeks’ gestation) relative to 27 gestation matched controls (P = 0.0261), and LGMN levels remained unchanged. At 36 weeks’ gestation, circulating CST6 was significantly increased (P = 0.001), while LGMN was significantly decreased (P = 0.0135) in 21 pregnancies preceding diagnosis of preeclampsia at term, compared to 184 pregnancies that did not develop preeclampsia. Human trophoblast stem cells (hTSC) were differentiated into syncytiotrophoblast or extravillous trophoblast (EVT) to evaluate CST6 and LGMN expression in these trophoblast lineages. CST6 and LGMN mRNA expression were significantly increased across 96 h after syncytiotrophoblast (P = 0.0066 and P = 0.0010 respectively) and EVT differentiation (P = 0.0618 and P = 0.0016 respectively), with the highest expression in syncytiotrophoblast. Computational analysis of two publicly available single-cell and single-nuclei RNA sequencing datasets correlated with the expression pattern observed in vitro. When syncytiotrophoblast cells were exposed to hypoxia (1% O2 vs. 8% O2), CST6 expression significantly increased (P = 0.0079), whilst LGMN expression was unchanged. The vascular endothelium may serve as an additional source of circulating CST6 and LGMN in preeclampsia.  Induction of dysfunction in endothelial cells by TNFα, caused reduced CST6 expression (P = 0.0036), whilst LGMN expression remained unchanged. Administering recombinant CST6 to endothelial cells enhanced markers of endothelial dysfunction and LGMN expression in the presence of TNFα. These findings indicate an inverse relationship between CST6 and LGMN in the placenta and maternal circulation in preeclampsia. We suggest elevated circulating levels of CST6 may be induced by placental hypoxia. This study provides novel insight into the dysregulation of CST6 and LGMN in preeclampsia and introduces their potential roles in human pregnancy and associated pathology.

Simulating high-speed solar wind streams from coronal holes using an L5-L1 configuration of Lagrangian points

Abstract Coronal holes (CHs) are known to be sources of high-speed solar wind streams (HSSs), yet the physical mechanisms linking CH position and characteristics to solar wind (SW) behaviour remain unclear. Our results reveal that the latitude of CHs, especially smaller ones, combined with the heliographic latitude of the solar disk’s central point (B0 angle), plays a critical role in driving discrepancies in SW velocity across the heliosphere. To investigate this, we use archival data from STEREO-B, STEREO-A, and Earth to simulate an L5-L1 configuration, where L5 is a vantage point approximately $$60^\circ$$ behind Earth in its orbit (as proposed for the Vigil mission), and L1 is between Earth and the Sun where SW measurements are typically taken. We use these insights to develop a predictive algorithm for HSSs, beginning with an analysis of the separation angle and distances between L5 and L1. We then introduce a predictive indicator and empirical criteria based on CH properties and the B0 angle to adjust for changes in SW velocity at L1. Our results show that the L5 viewpoint demonstrates the capability to significantly improve the accuracy and lead times of HSS predictions, enhancing our understanding of the CH-HSS relationship and potentially improving space weather forecasting.

LLM-based intelligent Q&A system for railway locomotive maintenance standardization

Juvenile social isolation in Sprague Dawley rats does not have a lasting impact on social behavior in adulthood

Publisher Correction: Analyzing bacterial networks and interactions in skin and gills of Sparus aurata with microalgae-based additive feeding

Deduction of full factorial design of HPLC technique for the simultaneous analysis of meloxicam and esomeprazole in their laboratory prepared tablets

Abstract A reversed phase HPLC method with UV detection was designed for the first time for the simultaneous estimation of meloxicam and esomeprazole in their combined tablet dosage forms. Full factorial design was used for rapid optimization of the proposed method. Chromatographic separation was reached using isocratic elution on C18 column. The mobile phase was a mixture of methanol: acetonitrile: 0.05 M potassium dihydrogen phosphate buffer at pH 5, adjusted using phosphoric acid and/or NaOH when needed. The flow rate was 1 mL/min and the injection volume was 20 µL. The detection wavelength was 230 nm. The working ranges of the method were 5.0-100.0 and 10.0–100.0 µg/mL, LOD values were 0.8 and 1.8 µg/mL and LOQ values were 2.6 and 5.5 µg/mL for meloxicam and esomeprazole, respectively. The proposed method was successfully applied to their combined tablet dosage forms with acceptable % recoveries (100.4 − 100.7%) obtained. Four methods were used to evaluate the greenness of the proposed method, suggesting the acceptability of the greenness of the proposed method.

Genomic characterization of Leishmania (V.) braziliensis associated with antimony therapeutic failure and variable in vitro tolerance to amphotericin B

Hybrid adaptive ant lion optimization with traditional controllers for driving and controlling switched reluctance motors to enhance performance

Research on the dynamic characteristics and disaster mechanism of anti-slide short pile-supported slopes

A deep learning approach for blood glucose monitoring and hypoglycemia prediction in glycogen storage disease

Validation of a novel CT perfusion software compared to RAPID in stroke patients receiving endovascular therapy

MiR- 150 deletion promotes lung tumor growth by upregulating P-STAT3 and ROS in MDSCs

Curcumin reduces pain after spinal cord injury in rats by decreasing oxidative stress and increasing GABAA receptor and GAD65 levels

Host ZAP activity correlates with the levels of CpG suppression in primate lentiviruses

Zinc-finger antiviral protein (ZAP) is thought to drive the suppression of CpG dinucleotides in many viruses to mimic the composition of their host genomes. However, in vivo evidence is sparse. Here, we investigated the reasons for unusually high CpG levels in SIVmus and SIVmon from mustached and mona monkeys, descendants of one of the precursors of HIV-1. We show that SIVmus is not resistant to ZAP inhibition. Instead, these Cercopithecus monkey hosts differ from other primate species by a splice site mutation and express the poorly active extralarge XL rather than the highly active L isoform of ZAP. Similarly, higher CpG levels in endogenous prosimian lentiviruses were associated with low activity of the corresponding host lemur ZAPs. In addition, lemur genes also show lower CpG suppression than other primates. Thus, the antiviral activity of ZAP not only affects suppression of CpG dinucleotides in viral transcripts but possibly also host genomes.

Assessment of lncRNA biomarkers based on NETs for prognosis and therapeutic response in ovarian cancer

Two phases of aseismic afterslip following the March 2021 Damasi, Greece, normal faulting earthquakes retrieved from InSAR measurements

Sporadic detection of vaccine-derived poliovirus type 2 using next-generation sequencing in Canadian wastewater in August of 2022

Abstract In July 2022, an unvaccinated young adult living in Rockland County, New York became paralyzed due to a vaccine-derived poliovirus type 2 (VDPV2) infection that was internationally transmitted. Wastewater surveillance in New York State uncovered VDPV2 in neighboring counties, showing silent community spread. These communities have strong epidemiological links to some vaccine-hesitant communities in Canada, spurring the need to monitor these populations for potential poliovirus importation. At the time, Canada did not have an established poliovirus wastewater method. We initiated this study to apply molecular methods to detect poliovirus in these communities and establish poliovirus wastewater surveillance capabilities in Canada. We sequence confirmed one poliovirus detection on August 30th, 2022 using both viral isolation and direct detection methods. Subsequent retrospective and prospective sampling was initiated, resulting in another sequence confirmed detection of VDPV2 in an overlapping catchment area collected on August 27th, 2022. Both VDPV2 detections were genetically linked to the New York clinical case. No clinical cases of poliomyelitis were detected in Canada during this study. The sporadic detection of VDPV2 in Canadian wastewater supports a travel-related shedding event without community transmission. Furthermore, we show that a direct detection method is sensitive to sequence confirm poliovirus in wastewater samples.

Brain-guided convolutional neural networks reveal task-specific representations in scene processing