Search Results (1,102)

Linear latent variable models such as principal component analysis (PCA), independent component analysis (ICA), canonical correlation analysis (CCA), and factor analysis (FA) identify latent directions (or loadings) either ordered or unordered. These data are then projected onto the latent directions to obtain their projected representations (or scores). For example, PCA solvers usually rank principal directions by explaining the most variance to the least variance. In contrast, ICA solvers usually return independent directions unordered and often with single sources spread across multiple directions as multiple sub-sources, severely diminishing their usability and interpretability. This paper proposes a general framework to enhance latent space representations to improve the interpretability of linear latent spaces. Although the concepts in this paper are programming language agnostic, the framework is written in Python. This framework simplifies the process of clustering and ranking of latent vectors to enhance latent information per latent vector and the interpretation of latent vectors. Several innovative enhancements are incorporated, including latent ranking (LR), latent scaling (LS), latent clustering (LC), and latent condensing (LCON). LR ranks latent directions according to a specified scalar metric. LS scales latent directions according to a specified metric. LC automatically clusters latent directions into a specified number of clusters. Lastly, LCON automatically determines the appropriate number of clusters to condense the latent directions for a given metric to enable optimal latent discovery. Additional functionality of the framework includes single-channel and multi-channel data sources and data pre-processing strategies such as Hankelisation to seamlessly expand the applicability of linear latent variable models (LLVMs) to a wider variety of data. The effectiveness of LR, LS, LC, and LCON is shown in two foundational problems crafted with two applied latent variable models, namely, PCA and ICA. Full article

This paper proposes a highly secure image encryption technique based on chaotic synchronization. Firstly, through the design of a synchronization controller, we ensure that the master–slave chaotic extremum-coded random number generators (ECRNGs) embedded in separated transmitters and receivers are fully synchronized to provide synchronized dynamic random sequences for image encryption applications. Next, combining these synchronized chaotic sequences with the AES encryption algorithm, we propose an image segmentation and multi-encryption method to enhance the security of encrypted images and realize a secure image transmission system. Notably, in the design of the synchronization controller, the transient time before complete synchronization between the master and slave ECRNGs is effectively controlled by specifying the eigenvalues of the matrix in the synchronization error dynamics. Research results in this paper also show that complete synchronization of ECRNGs can be achieved within a single sampling time, which significantly contributes to the time efficiency of the image transmission system. As for the image encryption technique, we propose the method of image segmentation and use the synchronized dynamic random sequences generated by the ECRNGs to produce the keys and initialization vectors (IVs) required for AES-CBC image encryption, greatly enhancing the security of the encrypted images. To highlight the contribution of the proposed segmented image encryption, statistical analyses are conducted on the encrypted images, including histogram analysis (HA), information entropy (IE), correlation coefficient analysis (CCA), number of pixels change rate (NPCR), and unified average changing intensity (UACI), and compared with existing literature. The comparative results fully demonstrate that the proposed encryption method significantly enhances image encryption performance. Finally, under the network transmission control protocol (TCP), the synchronization of ECRNGs, dynamic keys, and IVs is implemented as well as segmented image encryption and transmission, and a highly secure image transmission system is realized to validate the practicality and feasibility of our design. Full article

Objectives: An excessive and abrupt increase in cerebral blood flow may cause blood vessel damage, leading to stroke. Therefore, appropriate methods to immediately regulate blood flow velocity are important. Through an analysis of 31 healthy adults, we therefore investigated whether stimulating the common carotid artery (CCA) using transcutaneous electrical nerve stimulation (TENS) could modulate blood flow velocity in the CCA. Methods: Three stimulation intensities (below-threshold, threshold, and above-threshold) were applied in a random order. Blood velocity changes were examined by the measurement of peak systolic velocity (PSV) with Doppler ultrasound before, during, and after TENS stimulation. To evaluate arterial stiffness, pulse wave velocity (PWV) was calculated using CCA diameter, and blood pressure was measured before and after stimulation. Results: PSV changes in the below-threshold level were significant (p = 0.028). The PSV after below-threshold stimulation was significantly decreased by 2.23% compared to that before stimulation (p = 0.031). PWV showed no significant differences; however, a nonsignificant increase was observed immediately after stimulation only in the above-threshold condition. Above-threshold stimulation can increase vascular tone by activating the sympathetic nerve, possibly triggering vasoconstriction. Conclusions: A decrease in blood flow velocity may not be expected upon the above-threshold stimulation. In contrast, the below-threshold stimulation immediately reduces blood flow velocity, without significantly affecting hemodynamic function, such as arterial flexibility. Therefore, this short-term and low electrical stimulation technique can help to lower vascular resistance and prevent vascular damage from rapid blood flow velocity. Full article

Background/Objectives: This study compares the power of the radiofrequency (RF) signal reflected from the media layer (media power) of the common carotid artery (CCA) and the CCA stiffness between individuals with and without type 2 diabetes mellitus (T2DM). It also evaluates the associations of CCA media power with plasma glucose and lipid levels, as well as carotid stiffness. Methods: A total of 540 individuals, 115 with and 425 without T2DM (273 males, mean age = 64 ± 8 years) were studied using RF-based tracking of the right CCA. The following parameters were measured: CCA media thickness, luminal diameter, wall tensile stress (WTS), local pulse wave velocity (PWV), and media power. Results: Compared to the non-diabetic individuals, the T2DM patients had significantly higher CCA media thickness (652 ± 122 vs. 721 ± 138 microns, p < 0.005), luminal diameter (6.12 ± 0.78 vs. 6.86 ± 0.96 mm, p < 0.0005), media power (36.1 ± 4.8 vs. 39.3 ± 4.6, p < 0.0001), and PWV (7.65 ± 1.32 vs. 8.40 ± 1.89 m/s; p < 0.01), but comparable WTS (32.7 ± 10.4 vs. 33.1 ± 10.7 kPa; p = 0.25). In the entire population, CCA media power was independently associated with male sex, pulse pressure, current smoking, and T2DM; when T2DM was not included in the model, triglycerides emerged as an independent determinant of media power. The CCA PWV was independently associated with age, pulse pressure, media power, and T2DM. Conclusions: Our findings suggest the presence of structural changes in the arterial media of T2DM patients, leading to carotid stiffening and remodeling, aiming to preserve WTS. T2DM-related changes in arterial wall composition may be driven by high plasma triglyceride levels, which have previously been associated with both arterial stiffening and the incidence of CV events. Full article

Cholangiocarcinoma (CCA) is a rare and aggressive malignancy originating from the bile ducts, with poor prognosis and limited treatment options. Traditional therapies, such as surgery, chemotherapy, and radiation, have shown limited efficacy, especially in advanced cases. Recent advancements in immunotherapy, particularly T cell-based therapies like chimeric antigen receptor T (CAR T) cells, tumor-infiltrating lymphocytes (TILs), and T cell receptor (TCR)-based therapies, have opened new avenues for improving outcomes in CCA. This review provides a comprehensive overview of the current state of T cell therapies for CCA, focusing on CAR T cell therapy. It highlights key challenges, including the complex tumor microenvironment and immune evasion mechanisms, and the progress made in preclinical and clinical trials. The review also discusses ongoing clinical trials targeting specific CCA antigens, such as MUC1, EGFR, and CD133, and the evolving role of precision immunotherapy in enhancing treatment outcomes. Despite significant progress, further research is needed to optimize these therapies for solid tumors like CCA. By summarizing the most recent clinical results and future directions, this review underscores the promising potential of T cell therapies in revolutionizing CCA treatment. Full article

Identifying the key climate variables affecting optical saturation values (OSVs) in forest aboveground biomass (AGB) estimation using optical remote sensing is crucial for analyzing OSV changes. This can improve AGB estimation accuracy by addressing the uncertainties associated with optical saturation. In this study, Pinus yunnanensis forests and Landsat 8 OLI imagery from Yunnan were used as case studies to explain this issue. The spherical model was applied to determine the OSVs using specific spectral bands (Blue, Green, Red, Near-Infrared (NIR), and Short-Wave Infrared Band 2 (SWIR2)) derived from Landsat 8 OLI imagery. Canonical correlation analysis (CCA) uncovered the intricate relationships between climatic variables and OSV variations. The results reveal the following: (1) All Landsat 8 OLI spectral bands showed a negative correlation with the Pinus yunnanensis forest AGB, with OSVs ranging from 104.42 t/ha to 209.11 t/ha, peaking in the southwestern region and declining to the lowest levels in the southeastern region. (2) CCA effectively explained 93.2% of the OSV variations, identifying annual mean temperature (AMT) as the most influential climatic factor. Additionally, the mean temperature of the wettest quarter (MTQ) and annual precipitation (ANP) were significant secondary determinants, with higher OSV values observed in warmer, more humid areas. These findings offer important insights into climate-driven OSV variations, reducing uncertainty in forest AGB estimation and enhancing the precision of AGB estimations in future research. Full article

We have previously shown that the overexpression of acetyl-CoA carboxylase 1 (ACC1) was associated with the poor prognosis of cholangiocarcinoma (CCA) patients, and suppression of its expression in CCA cell lines deteriorated cell growth. The present study explored the mechanism by which ACC1 inhibition affects global protein acetylation, using genetic knockdown and pharmacological inhibition with an ACC1 inhibitor ND-646 as models. Both ACC1 knockdown and ACC1-inhibitor-treated cells displayed the hyperacetylation of proteins, accompanied by impaired growth and migration. The immunoprecipitation of hyperacetylated proteins using the anti-acetylated lysine antibody, followed by tandem mass spectrometry, identified three potential verification candidates, namely POTE ankyrin domain family member E, peroxisomal biogenesis factor 1, and heat shock protein 90 beta (HSP90B). HSP90 acetylation was the candidate selected for the verification of protein acetylation. To establish the effects of protein hyperacetylation, treatment with suberoylanilide hydroxamic acid (SAHA), a lysine deacetylase inhibitor, was conducted, and this served as an independent model. Decreased tumor growth but increased acetylated protein levels were observed in ACC1-KD xenograft tumors. Hyperacetylated-alleviated cell growth and migration were consistently observed in the SAHA-treated models. The molecular linkage between protein hyperacetylation and the AKT/GSK3β/Snail pathway was demonstrated. This study highlighted the importance of protein acetylation in CCA progression, suggesting that ACC1 and KDAC are potential targets for CCA treatment. Full article

Background: The epithelial malignant tumor known as cholangiocarcinoma (CCA) is most commonly found in Southeast Asia, particularly in northeastern Thailand. Previous research has indicated that the overexpression of acyl-CoA synthetase long-chain family member 4 (ACSL4), solute carrier family 7 member 11 (SLC7A11), and ChaC glutathione-specific γ-glutamylcyclotransferase (CHAC1) as ferroptosis-related proteins is associated with poorer prognosis in several cancers. The role of these three proteins in CCA is still unclear. The present study aimed to investigate the expression levels of ACSL4, SLC7A11, and CHAC1, all potential ferroptosis biomarkers, in CCA. Methods: The ACSL4, SLC7A11, and CHAC1 protein expression levels in 137 CCA tissues were examined using immunohistochemistry, while 61 CCA serum samples were evaluated using indirect ELISA. The associations between the expression levels of ACSL4, SLC7A11, and CHAC1 and patient clinicopathological data were evaluated to determine the clinical significance of these proteins. Results: The expression levels of ACSL4, SLC7A11, and CHAC1 were assessed in CCA tissues. A significant association was observed between high ACSL4 levels and extrahepatic CCA, tumor growth type, and elevated alanine transferase (ALT). There was also a positive association between elevated SLC7A11 levels and tumor growth type. Additionally, the upregulation of CHAC1 was significantly associated with a shorter survival time in patients. High levels of ACSL4 and SLC7A11 in CCA sera were both significantly associated with advanced tumor stages and abnormal liver function test results, indicating that they could be used as a reliable prognostic biomarker panel in patients with CCA. Conclusions: The results of the present study demonstrated that the upregulation of ACSL4, SLC7A11, and CHAC1 could be used as a valuable biomarker panel for predicting prognosis parameters in CCA. Furthermore, ACSL4 and SLC7A11 could potentially serve as complementary markers for improving the accuracy of prognosis prediction when CCA sera is used. These less invasive biomarkers could facilitate effective treatment planning. Full article

The Indonesian Throughflow (ITF) is significantly modulated by Indo-Pacific climate forcing, especially the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). However, when ENSO and IOD occur concurrently, they tend to play different roles in the ITF volume transport. By employing an improved Constructed Circulation Analogue (CCA) method, the relative contributions of these climate events to the ITF inflow and outflow transport in the upper and lower layers were quantified. The results indicate that during co-occurring El Niño and positive IOD events, ENSO is the dominant influence, with ratio values of 5.5:1 (3.5:1) in the upper layer and 1.7:1 (1.6:1) in the lower layer of the inflow (outflow). Conversely, during co-occurring La Niña and negative IOD events, the IOD predominates, with ratio values of 1:6 (1:6.5) in the upper layer and 1:4 (1:3) in the lower layer of the inflow (outflow). The mechanisms underlying these variations in the upper and lower layers can be explained by the differences in sea level anomaly (SLA) and wave propagation, respectively. This study provides a new insight into distinct roles of climate forcing on the ITF volume transport during the simultaneous occurrence of multiple climate modes. Full article

From the late Carboniferous to the early Permian, multiple pulses of glaciation and deglaciation have been caused by the LPIA. The Pennsylvanian period experienced phases of recovery, proliferation, and decline, ultimately forming a reef system distinctly different from that of the Mississippian period. During the late Bashkirian to Moscovian, the metazoan reef experienced a limited resurgence, with reef predominantly formed by chaetetid developing in the United States, northern China, and Japan. During the Kasimovian to Gzhelian, the phylloid algal reef dominated the global reef systems. In the late Pennsylvanian, bioconstruction cases and paleoenvironmental proxies in southern Guizhou Province were studied to investigate the composition, recovery, and evolutionary processes of the bioconstructions as well as their response to environmental variations during this period. Several bioconstructions have been reported in the Lumazhai section of Houchang Town, Guizhou Province, southern China, from the Moscovian to the Gzhelian. The upper Carboniferous strata are well-preserved and continuously exposed. The continuous strata, abundant fossils, and diverse bioconstructions provide excellent research materials for exploring the mutual constraints between organisms and their environment. This study identified ten microfacies, whose vertical evolution indicated significant changes in the depositional environment related to relative sea-level fluctuations. Skeletal grains are widely present in these facies. Among them, foraminifera, algae, bryozoans, crinoids, and Tubiphytes are the most common and exhibit distinct distribution characteristics in various environments. Quantitative statistics, CCA and theoretical ecospace have been utilized to examine and interpret environmental impact factors. Quantitative analysis of their relative abundance and distribution patterns provides insights into the complex interactions between organisms and environmental factors. The relative abundances of different organisms and factors controlling their bioconstructions are influenced by relative sea-level changes. CCA analysis reveal that hydrodynamic conditions are the primary influencing factor. Variation trends in average tiering and motility reveal the characteristics of biological communities during environmental changes in phylloid algae and microbial bioconstructions. These bioconstructions are not directly correlated with changes in environmental factors, and the biological communities in phylloid algae mounds and biostromes exhibit similar organism compositions and ecological niches across different environments. Full article

For over forty years, TCP has been the main protocol for transporting data on the Internet. To improve congestion control algorithms (CCAs), delay bounding algorithms such as Vegas, FAST, BBR, PCC, and Copa have been developed. However, despite being designed to ensure fairness between data flows, these CCAs can still lead to unfairness and, in some cases, even cause data flow starvation in WiFi networks under certain conditions. We propose a new CCA switching solution that works with existing TCP and WiFi standards. This solution is offline and uses Deep Reinforcement Learning (DRL) trained on features such as noncongestive delay variations to predict and prevent extreme unfairness and starvation. Our DRL-driven approach allows for dynamic and efficient CCA switching. We have tested our design preliminarily in realistic datasets, ensuring that they support both fairness and efficiency over WiFi networks, which requires further investigation and extensive evaluation before online deployment. Full article

The transportation of coal-based solid waste filling slurry (CSWFS) through pipelines for underground goaf injection is essential for enhancing mine safety and promoting green, low-carbon coal mining. To address the issue of pipeline blockage caused by the suspension sensitivity of CSWFS during long-distance transportation, this study proposes the addition of the suspending agent hydroxypropyl methyl cellulose (HPMC) to transform the filling slurry into a stable suspending slurry. The mechanism by which the suspending agent modifies the rheological property of CSWFS was elucidated and verified. Firstly, an evaluation index system for the suspending state of CSWFS based on the “experimental test and theoretical calculation” was established. The values for layering degree, bleeding rate time-loss, and the corresponding average time-loss rate over 0 to 120 min of A1–A5 CSWFS were recorded as 24 mm–2 mm, 3.0–0.2%, 252.4–54.2%, and 149.6–14.6%, respectively. The concentration gradient evaluation result, C/C_A = 0.91 (≥0.8), confirmed that the suspending agent maintained a stable suspending state over time for CSWFS. Secondly, it was demonstrated that the suspending agent HPMC modified the rheological property of A1–A5 CSWFS by increasing its plastic viscosity, which strengthened the viscous resistance to particle settling, thereby transforming a semi-stable slurry into a stable one. Additionally, the formation of a spatial suspending network by the suspending agent ensures that no pipeline blockage accidents occured in practical engineering applications. Furthermore, the XRD and SEM tests were utilized to verify the microstructure of the top (T) and bottom (B) samples in A4 block. It was concluded that the type of hydration products, occurrence forms, lapping compactness, and microstructural development were consistent, ultimately forming a high-strength, dense, hardened filling block. Finally, numerical simulation confirmed that the addition of suspending agent in A4 slurry formed a comprehensive spatial suspending network and a well-structured, unified system. This is one effective approach which could contribute to addressing the technical issue of pipeline blockage during long-distance pipeline transportation. Full article

Long-term live cell imaging requires sophisticated and fully automated commercial-stage incubators equipped with specified inverted microscopes to regulate temperature, CO₂ content, and humidity. In this study, we present a CO₂-free on-stage incubator specifically designed for use across various cell culture platforms, enabling live cell imaging applications. A simple and transparent incubator was fabricated from acrylic sheets to be easily placed on the stages of most inverted microscopes. We successfully performed live-cell imaging of cholangiocarcinoma (CCA) cells and HeLa cell dynamics in both 2D and 3D microenvironments over three days. We also analyzed directed cell migration under high serum induction within a microfluidic device. Interesting phenomena such as “whole-colony migration”, “novel type of collective cell migration” and “colony formation during cell and colony migration” are reported here for the first time, to the best of our knowledge. These phenomena may improve our understanding of the nature of cell migration and cancer metastasis. Full article

Most existing intelligent editing tools for music and video rely on the cross-modal matching technology of the affective consistency or the similarity of feature representations. However, these methods are not fully applicable to complex audiovisual matching scenarios, resulting in low matching accuracy and suboptimal audience perceptual effects due to ambiguous matching rules and associated factors. To address these limitations, this paper focuses on both the similarity and integration of affective distribution for the artistic audiovisual works of movie and television video and music. Based on the rich emotional perception elements, we propose a hybrid matching model based on feature canonical correlation analysis (CCA) and fine-grained affective similarity. The model refines KCCA fusion features by analyzing both matched and unmatched music–video pairs. Subsequently, the model employs XGBoost to predict relevance and to compute similarity by considering fine-grained affective semantic distance as well as affective factor distance. Ultimately, the matching prediction values are obtained through weight allocation. Experimental results on a self-built dataset demonstrate that the proposed affective matching model balances feature parameters and affective semantic cognitions, yielding relatively high prediction accuracy and better subjective experience of audiovisual association. This paper is crucial for exploring the affective association mechanisms of audiovisual objects from a sensory perspective and improving related intelligent tools, thereby offering a novel technical approach to retrieval and matching in music–video editing. Full article

Background: Diabetes contributes to a spectrum of complications encompassing microvascular and macrovascular disorders. This study aimed to explore the correlation between distal sensorimotor polyneuropathy (DSPN) severity and heightened carotid atherosclerosis among individuals with type 2 diabetes mellitus (T2DM). Method: Participants underwent comprehensive assessments including nerve conduction studies (NCS), Toronto Clinical Neuropathy Score (TCNS) evaluations, assessment of cardiometabolic risk factors, and carotid sonography studies covering dynamic and morphological parameters. The resistance index (RI), pulsatility index (PI), peak systolic velocity (PSV), and end-diastolic velocity (EDV) in both the common carotid artery (CCA) and internal carotid artery (ICA), carotid intima-media thickness (IMT), and carotid plaque score (CPS) were also measured. Peripheral nerve function severity was assessed using composite amplitude scores (CAS) derived from NCS. Results: Individuals with DSPN exhibited lower EDV in the CCA and ICA (p < 0.0001 and p = 0.002), higher PI and RI in both CCA and ICA (all p < 0.0001), and higher CPS (p = 0.002). They also demonstrated a higher prevalence of retinopathy as an underlying condition, higher index HbA1c, and reduced estimated glomerular filtration rate (eGFR) (all p < 0.0001). Multiple linear regression analysis revealed significant associations where eGFR, ICA-PI, index HbA1c, waist circumference, and age were correlated with CAS. Meanwhile, diabetes duration, waist circumference, age, and index HbA1c showed significant associations with TCNS. Conclusions: Our study suggests that individuals with T2DM who exhibit more severe carotid atherosclerosis may not only be at increased risk of developing DSPN but also may experience greater severity of DSPN. PI in both the CCA and ICA, along with the CPS, serve as surrogate biomarkers for DSPN severity. Full article