Miracle-dz/UniFAR-FTUs huggingface dataset:
On the nonlinear evolution of a pair of oblique Tollmien–Schlichting waves in boundary layers

This paper is concerned with the nonlinear interaction and development of a pair of oblique Tollmien–Schlichting waves which travel with equal but opposite angles to the free stream in a boundary layer. Our approach is based on high-Reynolds-number asymptotic methods. The so-called ‘upper-branch’ scaling is adopted so that there exists a well-defined critical layer, i.e. a thin region surrounding the level at which the basic flow velocity equals the phase velocity of the waves. We show that following the initial linear growth, the disturbance evolves through several distinct nonlinear stages. In the first of these, nonlinearity only affects the phase angle of the amplitude of the disturbance, causing rapid wavelength shortening, while the modulus of the amplitude still grows exponentially as in the linear regime. The second stage starts when the wavelength shortening produces a back reaction on the development of the modulus. The phase angle and the modulus then evolve on different spatial scales, and are governed by two coupled nonlinear equations. The solution to these equations develops a singularity at a finite distance downstream. As a result, the disturbance enters the third stage in which it evolves over a faster spatial scale, and the critical layer becomes both non-equilibrium and viscous in nature, in contrast to the two previous stages, where the critical layer is in equilibrium and purely viscosity dominated. In this stage, the development is governed by an amplitude equation with the same nonlinear term as that derived by Wu, Lee & Cowley (1993) for the interaction between a pair of Rayleigh waves. The solution develops a new singularity, leading to the fourth stage where the flow is governed by the fully nonlinear three-dimensional inviscid triple-deck equations. It is suggested that the stages of evolution revealed here may characterize the so-called ‘oblique breakdown’ in a boundary layer. A discussion of the extension of the analysis to include the resonant-triad interaction is given.
Pulmonary Nodule Segmentation Framework Based on Fine-Tuned and Pretrained Deep Neural Network Using CT Images

Deep learning is one of the most rapidly growing and emerging technologies in pulmonary nodule segmentation. However, the different shape, size, and location of the nodules make it extremely difficult to segment correctly. The purpose of this study is to obtain a fast and accurate segmentation algorithm with less number of stages. A fine-tuned dual skip connection-based segmentation framework is proposed that integrates pretrained residual neural network (ResNet) 152 with the U-Net architecture, namely, ResiU-Net. Nine different pretrained and fine-tuned encoder backbones, such as ResNet18, ResNet 34, ResNet 50, ResNet 101, ResNet 152, SEResNet18, SE-ResNet34, ResNext 101, and ResNext 50 are compared and the proposed ResiU-Net approach gives the best results. Also, the fine-tuned ResiU-Net performs better than nontuned ResiU-Net. 1224 computed tomography patient images with different nodule shapes and sizes are selected. The proposed method achieves 97.44% F score, 95.02% intersection over union score, 94.87% dice score, 0.34% binary cross-entropy loss, and 0.7585 combined dice coefficient and binary focal loss. The proposed ResiU-Net outperforms the state-of-the-art methods and reports the best evaluation metrics. The time taken by the model to train is 43 min. Hence, the proposed model is a fast and accurate segmentation approach.
Three-dimensional separation induced by a convected disturbance

A three-dimensional inviscid velocity distribution is selected to mimic the flow produced at the wall by a three-dimensional vortex convected above an infinite wall. The main interest is in determining the viscous response of the boundary layer on the wall to the imposed pressure distribution. It is demonstrated that complex effects occur in the boundary layer (including the formation of zones of apparent recirculation) that eventually lead to separation. Solutions are obtained in both a conventional Eulerian frame of reference and with a three-dimensional Lagrangian method. The separation takes the form of a sharply focused eruptive tongue of fluid in a manner consistent with modern asymptotic theories of three-dimensional separation, which indicate the boundary-layer solution will develop a singularity in the absence of interaction with the external flow. The unsteady separation structure is similar to that in two dimensions when viewed in the appropriate direction. The possible relevance of the results to the dynamics of turbulent boundary layers is described.
The Critical Role of Acyl Hydrocarbon Receptor on the Combined Benefits of Postbiotic Propionate on Active Vitamin D3-Orchestrated Innate Immunity in Salmonella Colitis

Our recent study observed the combined beneficial effects of postbiotic butyrate on active vitamin D3-orchestrated innate immunity to Salmonella Colitis. There is increasing interest in the role of acyl hydrocarbon receptor (AhR) on colitis and innate immunity. Therefore, we investigated the involvement of AhR in the effects. Salmonella colitis model is conducted with 6–8 w/o male C57BL/6 mice: Streptomycin (20 mg/mouse p.o.)-pretreated C57BL/6 mice were mock infected with sterile PBS or infected orally with 1 × 108 CFU of an S. typhimurium wild-type strain SL1344 for 48 h. Before and after the colitis induction, mice were oral gavage with active vitamin D3 0.2 μg/25 g mice (VD3) and/or postbiotics propionate (PP), in the absence of the presence of intraperitoneal injection of AhR inhibitor for 4 and 7 days, respectively. We observed AhR inhibitor counteracted the synergistic effects of PP and VD3 on reducing the severity of Salmonella colitis and body weight loss in C57BL/6 mice, reducing the cecal inflammatory but enhancing antimicrobial peptide mRNAs expression, and reducing the bacterial translocation in liver/spleen, compared to single treatment. It suggests the involvement of AhR on the synergistic effects of postbiotics PP and VD3 on the antibacterial and anti-inflammatory responses in Salmonella colitis and the potential biological treatment of Salmonella colitis.
OL-SLAM: A Robust and Versatile System of Object Localization and SLAM

This paper proposes a real-time, versatile Simultaneous Localization and Mapping (SLAM) and object localization system, which fuses measurements from LiDAR, camera, Inertial Measurement Unit (IMU), and Global Positioning System (GPS). Our system can locate itself in an unknown environment and build a scene map based on which we can also track and obtain the global location of objects of interest. Precisely, our SLAM subsystem consists of the following four parts: LiDAR-inertial odometry, Visual-inertial odometry, GPS-inertial odometry, and global pose graph optimization. The target-tracking and positioning subsystem is developed based on YOLOv4. Benefiting from the use of GPS sensor in the SLAM system, we can obtain the global positioning information of the target; therefore, it can be highly useful in military operations, rescue and disaster relief, and other scenarios.
Observations of Gravity Wave Refraction and Its Causes and Consequences

Horizontal gravity wave (GW) refraction was observed around the Andes and Drake Passage during the SouthTRAC campaign. GWs interact with the background wind through refraction and dissipation. This interaction helps to drive midatmospheric circulations and slows down the polar vortex by taking GW momentum flux (GWMF) from one location to another. The SouthTRAC campaign was composed to gain improved understanding of the propagation and dissipation of GWs. This study uses observational data from this campaign collected by the German High Altitude Long Range research aircraft on 12 September 2019. During the campaign a minor sudden stratospheric warming in the southern hemisphere occurred, which heavily influenced GW propagation and refraction and thus also the location and amount of GWMF deposition. Observations include measurements from below the aircraft by Gimballed Limb Observer for Radiance Imaging of the Atmosphere and above the aircraft by Airborne Lidar for the Middle Atmosphere. Refraction is identified in two different GW packets as low as ≈4 km and as high as 58 km. One GW packet of orographic origin and one of nonorographic origin is used to investigate refraction. Observations are supplemented by the Gravity‐wave Regional Or Global Ray Tracer, a simplified mountain wave model, ERA5 data and high‐resolution (3 km) WRF data. Contrary to some previous studies we find that refraction makes a noteworthy contribution in the amount and the location of GWMF deposition. This case study highlights the importance of refraction and provides compelling arguments that models should account for this.
Self-esteem, Interpersonal Communication Competence, and Media and Technology Usage as Predictors of Loneliness Among University Students

Loneliness is a common concern among university students, as these individuals experience many of the risk factors associated with loneliness. This experience of loneliness tends to lead to numerous consequences such as negative self-evaluations, anxiety, and depression, which in turn lead to impaired concentration and a decline in academic motivation and performance. The overarching aims of this study were to identify the predictor variable(s) or combination of predictor variables, namely self-esteem, interpersonal communication competence, and media and technology usage, that explain a significant percentage of the variance in loneliness amongst undergraduate university students, as well as to investigate whether differences exist in loneliness with regards to gender, ethnicity, and generational status. The sample consisted of 1,191 South African undergraduate university students between the ages of 18 and 30. This study was non-experimental in nature and a correlational research design was used. The results indicated that the combination of the independent (predictor) variables accounted for 51.9% of the variance in the Loneliness scores of the sample. Interpersonal Communication Competence and Self-esteem served as statistically and practically significant individual predictor variables of the students’ loneliness. Male students and first-generation students tend to be lonelier than female students and non-first-generation students, respectively.
Study of cell classification with a diffraction imaging flow cytometer method

With a diffraction imaging flow cytometer, we have acquired and analyzed the diffraction imaging data from 5 types of cultured cells. A gray level co-occurrence matrix (GLCM) algorithm was applied to extract the interference fringe related textures from the diffraction image data. Six GLCM parameters were chosen and imported into a support vector machine algorithm for automated classification of about 20 cells for each of the 5 cell types. We found that the GLCM based algorithm has the capacity for rapid processing of diffraction images and yield feature parameters for subsequent cell classification except the T- and B-lymphocytes.
Influence of Channel Selection and Subject’s Age on the Performance of the Single Channel EEG-Based Automatic Sleep Staging Algorithms

The electroencephalogram (EEG) signal is a key parameter used to identify the different sleep stages present in an overnight sleep recording. Sleep staging is crucial in the diagnosis of several sleep disorders; however, the manual annotation of the EEG signal is a costly and time-consuming process. Automatic sleep staging algorithms offer a practical and cost-effective alternative to manual sleep staging. However, due to the limited availability of EEG sleep datasets, the reliability of existing sleep staging algorithms is questionable. Furthermore, most reported experimental results have been obtained using adult EEG signals; the effectiveness of these algorithms using pediatric EEGs is unknown. In this paper, we conduct an intensive study of two state-of-the-art single-channel EEG-based sleep staging algorithms, namely DeepSleepNet and AttnSleep, using a recently released large-scale sleep dataset collected from 3984 patients, most of whom are children. The paper studies how the performance of these sleep staging algorithms varies when applied on different EEG channels and across different age groups. Furthermore, all results were analyzed within individual sleep stages to understand how each stage is affected by the choice of EEG channel and the participants’ age. The study concluded that the selection of the channel is crucial for the accuracy of the single-channel EEG-based automatic sleep staging methods. For instance, channels O1-M2 and O2-M1 performed consistently worse than other channels for both algorithms and through all age groups. The study also revealed the challenges in the automatic sleep staging of newborns and infants (1–52 weeks).
Microarray Profiling of Differentially Expressed Genes in Coronary Artery Bypass Grafts of High-Risk Patients with Postoperative Cognitive Dysfunctions

Postoperative cognitive dysfunction (POCD) is cognitive decline after surgery. The authors hypothesized that gene-level changes could be involved in the pathogenesis of POCD. The present study evaluated the incidence of POCD and its associated differentially expressed genes. This was a prospective cohort study conducted on high-risk coronary artery bypass graft patients aged 40 to 75 years. POCD classification was based on a one standard deviation decline in the postoperative scores compared to the preoperative scores. The differentially expressed genes were identified using microarray analysis and validated using quantitative RT-PCR. Forty-six patients were recruited and completed the study. The incidence of POCD was identified using a set of neurocognitive assessments and found to be at 17% in these high-risk CABG patients. Six samples were selected for the gene expression analyses (3 non-POCD and 3 POCD samples). The findings showed five differentially expressed genes in the POCD group compared to the non-POCD group. The upregulated gene was ERFE, whereas the downregulated genes were KIR2DS2, KIR2DS3, KIR3DL2, and LIM2. According to the results, the gene expression profiles of POCD can be used to find potential proteins for POCD diagnostic and predictive biomarkers. Understanding the molecular mechanism of POCD development will further lead to early detection and intervention to reduce the severity of POCD, and hence, reduce the mortality and morbidity rate due to the condition.
DALAN: A Course Recommender for Freshmen Students using a Multiple Regression Model

It is challenging for the institution to provide students with ideas about courses or programs to pursue. This study aims to propose a tool that employs multiple regression to forecast incoming college students’ courses at Notre Dame of Midsayap College. The proponents developed a prediction model based on the identified predictors and Cumulative Semestral Grade Point Average of all College of Information Technology and Engineering students from the first semester of S.Y. 2013-2014 to S.Y. 2015-2016, using the ex post facto method. The necessary variables were Entrance Exam results, High School Grade Point Average, and Cumulative Semestral Grade Point Average. Also, Pearson’s R correlation was used to determine the relationship between EE and HSGPA to CSGPA. Conclusively, this study supported the notion that EE and HSGPA considerably impact CSGPA. Additionally, the developed predictive model was considered appropriate for course recommendation.
Molecular Mechanism for Hepatic Glycerolipid Partitioning of n-6/n-3 Fatty Acid Ratio in an Obese Animal Biomodels

The n-6/n-3 metabolic pathway associated with hepatic glycerolipid portioning plays a key role in preventing obesity. In this nutrition metabolism study, we used in vivo monitoring techniques with 40 obese male Sprague-Dawley strain rats attached with jugular-vein cannula after obesity was induced by a high-fat diet to determine the molecular mechanism associated with hepatic glycerolipid partitioning involving the n-6/n-3 metabolic pathway. Rats were randomly assigned to four groups (10 animals per group), including one control group (CON, n-6/n-3 of 71:1) and three treatment groups (n-6/n-3 of 4:1, 15:1 and 30:1). They were fed with experimental diets for 60 days. Incorporation rates of [14C]-labeling lipid into glycerolipid in the liver were 28.87–37.03% in treatment groups fed with diets containing an n-6/n-3 ratio of 4:1, 15:1 and 30:1, which were significantly (p < 0.05) lower than that in the CON (40.01%). However, 14CO2 emission % of absorbed dose showed the opposite trend. It was significantly (p < 0.05) higher in a treatment groups (n-6/n-3 of 4:1, 15:1 and 30:1, 30.35–45.08%) than in CON (27.71%). Regarding the metabolic distribution of glycerolipid to blood from livers, phospholipid/total glycerolipid (%) was significantly (p < 0.05) lower in CON at 11.04% than in treatment groups at 18.15% to 25.15%. Moreover, 14CO2/[14C]-total glycerolipid (%) was significantly (p < 0.05) higher in treatment groups at 44.16–78.50% than in CON at 39.50%. Metabolic distribution of fatty acyl moieties flux for oxidation and glycerolipid synthesis in the liver were significantly (p < 0.05) better in order of 4:1 > 15:1 > 30:1 than in the CON. Our data demonstrate that n-6/n-3 of 4:1 could help prevent obesity by controlling the mechanism of hepatic partitioning through oxidation and esterification of glycerolipid in an obese animal biomodel.
Underage Youth Continue to Obtain E-Cigarettes from Retail Sources in 2022: Evidence from the Truth Continuous Tracking Survey

(1) Background: This study aims to describe the primary sources of e-cigarettes among young people and to explore how these sources may differ by individual-level characteristics. (2) Methods: Data were obtained from a cross-sectional, continuous tracking survey of participants. The analytic sample includes current e-cigarette users (aged 15–20 years) surveyed from January to August 2022 (N = 1296). Respondents provided information on e-cigarette source of acquisition, device type, and flavors used, as well as sociodemographic and residential characteristics. Chi-square tests were used to determine differences in source of acquisition by age, gender, race/ethnicity, United States (US) census region, urban-rural classification, flavors used, and device type. (3) Results: Although most current e-cigarette users obtained their devices through a social source (56.9%), a considerable proportion obtained e-cigarettes from a retail source (43.1%). The primary retail sources of e-cigarette acquisition were vape shops (22.0%) and gas station/convenience stores (15.9%). Source of e-cigarette acquisition differed by age, gender, US census region, flavors used, and device type, such that a lower proportion of those who were younger, female, residing in the West, and used vape pens had reported obtaining e-cigarettes via retail sources. (4) Conclusions: Results indicate that a significant proportion of youth report obtaining e-cigarettes from retail sources, despite the federal, state, and local policies that prohibit the sale of any tobacco products to those under the age of 21. Comprehensive retail regulations to help restrict tobacco product access are needed to reduce e-cigarette use among young people.
Isolation of Novel Bacterial Strains Pseudomonas extremaustralis CSW01 and Stutzerimonas stutzeri CSW02 from Sewage Sludge for Paracetamol Biodegradation

Paracetamol is one of the most used pharmaceuticals worldwide, but due to its widespread use it is detected in various environmental matrices, such as surface and ground waters, sediments, soils or even plants, where it is introduced mainly from the discharge of wastewater and the use of sewage sludge as fertilizer in agriculture. Its accumulation in certain organisms can induce reproductive, neurotoxic or endocrine disorders, being therefore considered an emerging pollutant. This study reports on the isolation, from sewage sludge produced in wastewater treatment plants (WWTPs), of bacterial strains capable of degrading paracetamol. Up to 17 bacterial strains were isolated, but only two of them, identified as Pseudomonas stutzeri CSW02 and Pseudomonas extremaustralis CSW01, were able to degrade very high concentrations of paracetamol in solution as a sole carbon and energy source, and none of them had been previously described as paracetamol degraders. These bacteria showed the ability to degrade up to 500 mg L−1 of paracetamol in only 6 and 4 h, respectively, much quicker than any other paracetamol-degrader strain described in the literature. The two main paracetamol metabolites, 4-aminophenol and hydroquinone, which present high toxicity, were detected during the degradation process, although they disappeared very quickly for paracetamol concentrations up to 500 mg L−1. The IC50 of paracetamol for the growth of these two isolates was also calculated, indicating that P. extremaustralis CSW01 was more tolerant than S. stutzeri CSW02 to high concentrations of paracetamol and/or its metabolites in solution, and this is the reason for the much lower paracetamol degradation by S. stutzeri CSW02 at 2000–3000 mg L−1. These findings indicate that both bacteria are very promising candidates for their use in paracetamol bioremediation in water and sewage sludge.
Activated Leucocyte Cell Adhesion Molecule (CD166): A Biomarker in Diagnosis and Prognosis of Breast Cancer

The global incidence of breast cancer and associated mortality is rising annually despite advanced diagnostic aids and treatment methods. This is due to the failure and difficulty in detecting the disease at an early stage. Due to an increase in the breast cancer mortality rate, biomarkers associated with early and prompt detection are being extensively studied, owing to their sensitivity, specificity, cost-effectiveness, and minimally invasive or non invasive analysis. Among those carbohydrate antigens, carcinoembryonic antigens, and circulating tumour cells are the most commonly observed serum biomarkers in the detection of cancer. In recent years, extensive research is carried out on cell adhesion molecules and their role in the process of cell adhesion which is essential for the development and homeostasis in multicellular organisms. These cell adhesion molecules accelerate appropriate cell response and intercellular communication. Activated Leucocyte Cell Adhesion Molecule (ALCAM) or Cluster of Differentiation 166 (CD166) is a transmembrane glycoprotein and emerging as a promising biomarker for primary detection of tumour cells with metastatic potential and is also upregulated in breast tumours. This review ascertains the usefulness of the ALCAM as a potential diagnostic and prognostic marker for early detection, classification, and prognosis of breast cancer and also elucidates the role of the various other biomarkers.
Air–Sea Interaction on the Time Scale of 30 to 50 Days

Abstract In this Paper we have examined the fluxes of latent and sensible heat between the ocean and the atmosphere utilizing primarily the observations from the global experiment. The procedure for calculation is based on the Monin-Obukhov similarity theory. The transfer coefficients are stability dependent. Some calculations are also performed utilizing several different datasets. One of these covers the region of Asian monsoon oceans during the Global Experiment. This is a daily sea surface temperature (SST) dataset. A second dataset covers the global oceans for the entire FGGE year. This is a 10-day averaged dataset prepared by the European Centre for Medium Range Weather Forecasts. A third dataset obtained from the Japan Meteorological Agency, covers a 7-year period between 1979 and 1985. This dataset was also averaged over 10-day periods. Both the daily and the 10-day averaged SST data have been used for studies of low frequency oscillations. An equivalence, on the time scale of 30 to 50 days, for t.