Miracle-dz/UniFAR-FTUs huggingface dataset:
Bottom Current Modification of Turbidite Lobe Complexes

Submarine lobes form at the distal end of sediment gravity flow systems and are globally important sinks for sediment, anthropogenic pollutants and organic carbon, as well as forming hydrocarbon and CO2 reservoirs. Deep-marine, near bed or bottom currents can modify gravity flow pathways and sediment distribution by directly interacting with the flow or by modifying seafloor morphology. Deciphering the nature of gravity- and bottom currents interaction, particularly in ancient systems, remains a challenge due to the lack of integrated datasets and the necessary oceanographic framework. Here we analyse high-resolution 3D seismic reflection and core data from the Upper Cretaceous interval offshore Tanzania to reveal the interaction of turbidite lobes with fine-grained sediment waves and contourite drift deposits. Contourite drift morphology governs the large-scale confinement style and shape of lobes that range from frontally confined and crescent shaped, to laterally confined and elongated, to semi-confined lobes. Core data reveals massive to cross-laminated high density turbidites in the lobe axis position that show no direct interaction between gravity flows and contour currents. Lobe off-axis and fringe deposits consist of parallel- and ripple-laminated, low density turbidites, which are inter-bedded with bioturbated, muddy siltstones that represent the toes of contourite drifts. Starved ripples, and streaks of up to fine-grained sandstone above individual turbidite beds indicate reworking by bottom currents. This facies distribution reflects the temporal interaction of quasi-steady bottom currents and turbidity currents that interact with the topography and build lobes over short periods of time. Frontally confined turbidity currents form lobes in a fill-and-spill fashion, in which the confinement of turbidity currents causes rapid deposition and obscures any bottom current signal. Lateral confinement causes increased turbidity current runout length, and promotes the development of lobe fringes with a high proportion of bottom current reworked sands. During times when sediment gravity flows are subordinate, contourites accumulate on top of the lobe, confining the next flow and thus modifying the overall stacking pattern of the lobe complex. Although sediment volumes of these bottom current modified lobe complexes are comparable to other deep-marine systems, bottom currents considerably influence facies distribution and deposit architecture.
Research on Energy Management of a Virtual Power Plant Based on the Improved Cooperative Particle Swarm Optimization Algorithm

Energy management of virtual power plants (VPPs) directly affects operators’ operating profits and is also related to users’ comfort and economy. In order to provide a reasonable scheme for scheduling each unit of the VPP and to improve the operating profits of the VPP, this study focuses on the optimization of VPP energy management under the premise of ensuring the comfort of flexible load users. First, flexible loads are divided into time-shiftable load (TL), power-variable load (PL), and interruptible load (IL), and their accurate power consumption models are established, respectively. Then, aiming at maximizing the operation profits of a VPP operator, an optimization model of VPP energy management considering user comfort is proposed. Finally, the improved cooperative particle swarm optimization (ICPSO) algorithm is applied to solve the proposed VPP energy management optimization model, and the optimal scheduling scheme of VPP energy management is obtained. Taking a VPP in the coastal area of China as an example, results show that the optimization model proposed in this article has the advantages of good economy and higher user comfort. Meanwhile, the ICPSO algorithm has the characteristics of faster optimization speed and higher accuracy when solving the problem with multiple variables.
A Guide to Left Bundle Branch Area Pacing Using Stylet-Driven Pacing Leads

Left bundle branch area pacing (LBBAP) has emerged as a novel pacing modality which aims to capture the left bundle branch area and avoids the detrimental effects of right ventricular pacing. Current approaches for LBBAP have been developed using lumen-less pacing leads (LLL). Expanding the tools and leads for LBBAP might contribute to a wider adoption of this technique. Standard stylet-driven pacing leads (SDL) differ from current LLL as they are characterized by a wider lead body diameter, are stylet-supported and often have a non-isodiametric extendable helix design. Although LBBAP can be performed safely with SDL, the implant technique of LBBAP differs compared to LLL. In the current overview we describe in detail how different types of SDL can be used to target a deep septal position and provide a practical guide on how to achieve LBBAP using SDL.
Insight Into the Effects of Clinical Repetitive Transcranial Magnetic Stimulation on the Brain From Positron Emission Tomography and Magnetic Resonance Imaging Studies: A Narrative Review

Repetitive transcranial magnetic stimulation (rTMS) has been proposed as a therapeutic tool to alleviate symptoms for neurological and psychiatric diseases such as chronic pain, stroke, Parkinson’s disease, major depressive disorder, and others. Although the therapeutic potential of rTMS has been widely explored, the neurological basis of its effects is still not fully understood. Fortunately, the continuous development of imaging techniques has advanced our understanding of rTMS neurobiological underpinnings on the healthy and diseased brain. The objective of the current work is to summarize relevant findings from positron emission tomography (PET) and magnetic resonance imaging (MRI) techniques evaluating rTMS effects. We included studies that investigated the modulation of neurotransmission (evaluated with PET and magnetic resonance spectroscopy), brain activity (evaluated with PET), resting-state connectivity (evaluated with resting-state functional MRI), and microstructure (diffusion tensor imaging). Overall, results from imaging studies suggest that the effects of rTMS are complex and involve multiple neurotransmission systems, regions, and networks. The effects of stimulation seem to not only be dependent in the frequency used, but also in the participants characteristics such as disease progression. In patient populations, pre-stimulation evaluation was reported to predict responsiveness to stimulation, while post-stimulation neuroimaging measurements showed to be correlated with symptomatic improvement. These studies demonstrate the complexity of rTMS effects and highlight the relevance of imaging techniques.
Unspecific CTL Killing Is Enhanced by High Glucose via TNF-Related Apoptosis-Inducing Ligand

TNF-related apoptosis inducing ligand (TRAIL) is expressed on cytotoxic T lymphocytes (CTLs) and TRAIL is linked to progression of diabetes. However, the impact of high glucose on TRAIL expression and its related killing function in CTLs still remains largely elusive. Here, we report that TRAIL is substantially up-regulated in CTLs in environments with high glucose (HG) both in vitro and in vivo. Non-mitochondrial reactive oxygen species, NFκB and PI3K/Akt are essential in HG-induced TRAIL upregulation in CTLs. TRAILhigh CTLs induce apoptosis of pancreatic beta cell line 1.4E7. Treatment with metformin and vitamin D reduces HG-enhanced expression of TRAIL in CTLs and coherently protects 1.4E7 cells from TRAIL-mediated apoptosis. Our work suggests that HG-induced TRAILhigh CTLs might contribute to the destruction of pancreatic beta cells in a hyperglycemia condition.
The Role of m6A Regulator-Mediated Methylation Modification and Tumor Microenvironment Infiltration in Glioblastoma Multiforme

N6-methyladenosine (m6A) RNA methylation is an emerging epigenetic modification in recent years and epigenetic regulation of the immune response has been demonstrated, but the potential role of m6A modification in GBM tumor microenvironment (TME) cell infiltration and stemness remain unknown. The m6A modification patterns of 310 GBM samples were comprehensively evaluated based on 21 m6A regulators, and we systematically correlated these modification patterns with TME cell infiltration characteristics and stemness characteristics. Construction of m6Ascore to quantify the m6A modification patterns of individual GBM samples using a principal component analysis algorithm. We identified two distinct patterns of m6A modification. The infiltration characteristics of TME cells in these two patterns were highly consistent with the immunophenotype of the GBM, including the immune activation differentiation pattern and the immune desert dedifferentiation pattern. We also identified two modes of regulation of immunity and stemness by m6A methylation. Stromal activation and lack of effective immune infiltration were observed in the high m6Ascore subtype. Pan-cancer analysis results illustrate a significant correlation between m6AScore and tumor clinical outcome, immune infiltration, and stemness. Our work reveals that m6A modifications play an important role in the development of TME and stemness diversity and complexity. Patients with a low m6AScore showed significant therapeutic advantages and clinical benefits. Assessing the m6A modification pattern of individual tumors will help enhance our knowledge of TME infiltration and stemness characteristics, contribute to the development of immunotherapeutic strategies.
Elevated Myoglobin in Patients With Primary Aldosteronism: A Cross-Sectional Study

Objectives Primary aldosteronism (PA) is characterized by the autonomous excessive production of aldosterone in the adrenal cortex. Aldosterone is associated with damages to heart muscle and skeletal muscle. The purpose of this study was to evaluate serum levels of muscle injury markers and their associated factors in patients with primary aldosteronism. Methods We retrospectively enrolled subjects with PA and essential hypertension (EH) who had completed testing for serum high sensitivity troponin T (hs-TnT), creatine kinase isoenzyme MB (CK-MB) and myoglobin from the database of the Chongqing Primary Aldosteronism Study (CONPASS). Univariate and multivariate linear regression analyses were performed to analyze the influencing factors of myocardial injury markers. Results In total, 278 patients with PA and 445 patients with EH were enrolled in this study. Compared with EH patients, serum concentrations of hs-TnT [7.0 (4.0–12.0) vs. 6.0 (3.0–11.0) ng/L; p=0.005] and myoglobin [24.2 (21.0–38.1) vs. 21.8 (21.0–31.9) μg/L; p=0.023] were significantly higher among PA patients, while no significant difference of CK-MB was found between two groups [1.4 (1.0–2.0) vs. 1.3 (0.9–1.9) μg/L; p=0.154]. Univariate linear regression analysis showed that myoglobin was negatively correlated with serum potassium (β=-0.31; p<0.01) and positively correlated with plasma aldosterone concentration (β=0.40; p<0.01) in the PA group, while no significant correlation was found between hs-TnT and biochemical parameters. After adjusting for multiple confounders, myoglobin was negatively correlated with serum potassium (β=-0.15; p<0.05) and positively correlated with plasma aldosterone concentration (β=0.34; p<0.01) in the PA group. Conclusions The serum level of myoglobin was significantly increased in PA patients, and myoglobin was independently correlated with plasma aldosterone concentration.
Moving in Semantic Space in Prodromal and Very Early Alzheimer's Disease: An Item-Level Characterization of the Semantic Fluency Task

The semantic fluency task is a widely used clinical tool in the diagnostic process of Alzheimer's disease. The task requires efficient mapping of the semantic space to produce as many items as possible within a semantic category. We examined whether healthy volunteers (n = 42) and patients with early Alzheimer's disease (24 diagnosed with amnestic Mild Cognitive Impairment and 18 with early Alzheimer's dementia) take advantage of and travel in the semantic space differently. With focus on the animal fluency task, we sought to emulate the detailed structure of the multidimensional semantic space by utilizing word2vec-method from the natural language processing domain. To render the resulting multidimensional semantic space visually comprehensible, we applied a dimensionality reduction algorithm (t-SNE), which enabled a straightforward division of the semantic space into sub-categories. Moving in semantic space was quantified with the number of items created, sub-categories visited, and switches and returns to these sub-categories. Multinomial logistic regression models were used to predict the diagnostic group with these independent variables. We found that returning to a sub-category provided additional information, besides the number of words produced in the task, to differentiate patients with Alzheimer's dementia from both amnestic Mild Cognitive Impairment patients and healthy controls. The results suggest that the frequency of returning to a sub-category may serve as an additional aid for clinicians in diagnosing early Alzheimer's disease. Moreover, our results imply that the combination of word2vec and subsequent t-SNE-visualization may offer a valuable tool for examining the semantic space and its sub-categories.
Population Genomics of Microbial Biostalactites: Non-recombinogenic Genome Islands and Microdiversification by Transposons

Intrapopulation genetic variability in prokaryotes is receiving increasing attention thanks to improving sequencing methods; however, the ability to distinguish intrapopulation variability from species clusters or initial stages of gene flow barrier development remains insufficient. To overcome this limitation, we took advantage of the lifestyle of Ferrovum myxofaciens, a species that may represent 99% of prokaryotic microbiome of biostalactites growing at acid mine drainage springs. We gained four complete and one draft metagenome-assembled F. myxofaciens genomes using Oxford Nanopore and Illumina sequencing and mapped the reads from each sample on the reference genomes to assess the intrapopulation variability. We observed two phenomena associated with intrapopulation variability: hypervariable regions affected by mobilome expansion called “scrapyards,” and variability in gene disruptions caused by transposons within each population. Both phenomena were previously described in prokaryotes. However, we present here for the first time scrapyard regression and the development of a new one. Nearly complete loss of intrapopulation short sequence variability in the old scrapyard and high variability in the new one suggest that localized gene flow suppression is necessary for scrapyard formation. Concerning the variable gene disruptions, up to 9 out of 41 occurrences per sample were located in highly conserved diguanylate cyclases/phosphodiesterases. We propose that microdiversification of life strategies may be an adaptive outcome of random diguanylate cyclase elimination. The mine biostalactites thus proved as a unique model system for describing genomic intrapopulation processes, as they offer easily sampleable units enriched in a single microbial species.
Women have higher levels of CoQ10 than men when supplemented with a single dose of CoQ10 with monoglycerides omega-3 or rice oil and followed for 48 h: a crossover randomised triple blind controlled study

Abstract Coenzyme Q10 (CoQ10), a lipid involved in ATP synthesis, exhibits very limited oral absorption, and its endogenous production decreases with ageing and with the occurrence of oxidative stress. Our group previously showed that monoglycerides omega-3 (MAG-OM3) increase OM3 plasma concentrations. Since CoQ10 is liposoluble, we hypothesised that its 48 h pharmacokinetics is higher when provided with MAG-OM3 compared to CoQ10 alone (in powder form) or added to rice oil (a neutral triacylglycerol oil). A randomised triple-blind crossover study was performed with fifteen men and fifteen women consuming the three supplements providing 200 mg of CoQ10 in a random order. Blood samples were collected before (t = 0) and 1, 3, 5, 6, 7, 8, 10, 11, 24 and 48 h after the supplement intake. Plasma total CoQ10 concentrations were analysed on ultrahigh-performance liquid chromatography coupled to a tandem mass spectrometer (UPLC-MS/MS). Participants were 26⋅1 ± 4⋅8 years old. When CoQ10 was provided with rice or MAG-OM3 oils, the 48 h area under the curve (AUC 0–48 h) was approximately two times higher compared to when provided without an oil. The delta max concentration (ΔCmax) of plasma CoQ10 was, respectively, 2 (MAG-OM3) and 2⋅5 (rice oil) times higher compared to CoQ10 alone. There was a significant sex by treatment interaction (P = 0⋅0250) for the AUC 0–6 h supporting that in postprandial, men and women do not respond the same way to the different supplement. Women had a higher CoQ10 concentration 48 h after the single-dose intake compared to men. We conclude that CoQ10 supplements must be provided with lipids, and their kinetics is different between men and women.
A High Speed Economical Industrial Control System “Programmable Controller for Industrial Automation” (PCIA)

This paper describes the high speed and the cost effective of the general purpose industrial control system named as Programmable controller for industrial automation (PCIA). It is a replacement of expensive controllers/ PLCs that are used in industries for automation purpose. PCIA is real-time power efficient and reliable controller with a facility of data acquisition and monitoring on its touch screen using interfacing module. This control system can automate any type of industrial machinery and processes. The core element of PCIA is programmable AVR (Advance Virtual RISC) microcontroller which controls each and every action of Programmable controller for industrial automation. It compromises of nine different modules CPU, HMI, digital input, digital output, analog input, analog output, thermocouple module and power supply modules. The software of PCIA is written in C language. Special circuitries are used in power supply and other modules are also used to protect the system from different industrial noises.
Covid-19 Prediction Modeling Using Bidirectional Gated Recurrent Unit Network Model

: Artificial Neural Networks (ANN) are Non-linear models can solve many complex and sophisticated real world problems. Deep Learning (DL) based forecasting mechanism has a significant role to enhance the future course of action in numerous domains. A variant Recurrent Neural Networks are being effectively applied to handle the problems concerned with prediction. In this paper, a Bidirectional Gated Recurrent Unit (BGRU) Neural Network model has been proposed to predict the total number of Confirmed, Deaths and Cured cases on SARS-CoV-2 (COVID-19) pandemic. Our model performance is determined by Mean Absolute Percentage Error (MAPE), R 2 score, R 2Adjusted score and Root Mean Square Error (RMSE). Finally, the BGRU is contrasted with
Application of a triangular saw guide in cranial tibial wedge osteotomy in ten cats

A traumatic etiology of mechanical injury, trophic and degenerative changes are common etiopathogenesis of cranial cruciate ligament injury in cats. The aim of the study was to assess the usage of the authors own design triangular saw guide for surgery of the cranial tibial wedge osteotomy in feline patients. Cranial tibial wedge osteotomy procedures were performed in 10 cats of both genders. The appliance of a triangular saw guide and modified technique ensures meticulous orthogonal incision in the course of the cranial tibial wedge osteotomy and enables achieving a levelling of the tibial plateau precisely, reducing cortical damage and significantly decreasing the surgical time. It provides an adequate environment for bone union within three months post operatively.
A Model-Based Clustering via Mixture of Bayesian Hierarchical Models with Covariate Adjustment for Detecting Differentially Expressed Genes from Paired Design

The causes of many complex human diseases are still largely unknown. Genetics plays an important role in uncovering the molecular mechanisms of complex human diseases. A key step to characterize the genetics of a complex human disease is to unbiasedly identify disease-associated gene transcripts in whole-genome scale. Confounding factors could cause false positives. Paired design, such as measuring gene expression before and after treatment for the same subject, can reduce the effect of known confounding factors. Model-based clustering, such as mixtures of Bayesian hierarchical models, has been proposed to detect gene transcripts differentially expressed between paired samples. However, not all known confounding factors can be controlled in a paired/match design. To the best of our knowledge, no clustering methods have the capacity to adjust for the effects of covariates yet. In this article, we proposed a novel mixture of Bayesian hierarchical models with covariate adjustment in identifying differentially expressed transcripts using high-throughput whole-genome data from paired design. Both simulation study and real data analysis show the good performance of the proposed method
Applying ensemble machine learning models to predict individual response to a digitally delivered worry postponement intervention.

OBJECTIVE Generalized anxiety disorder (GAD) is a prevalent mental health disorder that often goes untreated. A core aspect of GAD is worry, which is associated with negative health outcomes, accentuating a need for simple treatments for worry. The present study leveraged pretreatment individual differences to predict personalized treatment response to a digital intervention. METHODS Linear mixed-effect models were used to model changes in daytime and nighttime worry duration and frequency for 163 participants who completed a six-day worry postponement intervention. Ensemble-based machine learning regression and classification models were implemented to predict changes in worry across the intervention. Model feature importance was derived using SHapley Additive exPlanation (SHAP). RESULTS Moderate predictive performance was obtained for predicting changes in daytime worry duration (test r2 = 0.221, AUC = 0.77) and nighttime worry frequency (test r2 = 0.164, AUC = 0.72), while poor predictive performance was obtained for nighttime worry duration and daytime worry frequency. Baseline levels of worry and subjective health complaints were most important in driving model predictions. LIMITATIONS A complete-case analysis was leveraged to analyze the present data, which was collected from participants that were Dutch and majority female. CONCLUSIONS This study suggests that treatment response to a digital intervention for GAD can be accurately predicted using baseline characteristics. Particularly, this worry postponement intervention may be most beneficial for individuals with high baseline worry but fewer subjective health complaints. The present findings highlight the complexities of and need for further research into daily worry dynamics and the personalizable utility of digital interventions.