Miracle-dz/UniFAR-FTUs huggingface dataset:
Bioinformatics Prediction and Experimental Verification Identify CAB39L as a Diagnostic and Prognostic Biomarker of Kidney Renal Clear Cell Carcinoma

Background and Objectives: Calcium-binding protein 39-like (CAB39L) has been reported to be downregulated and possessed diagnostic and prognostic values in several types of cancer. However, the clinical value and mechanism of CAB39L in kidney renal clear cell carcinoma (KIRC) remain unclear. Materials and Methods: Bioinformatics analysis was conducted using different databases including TCGA, UALCAN, GEPIA, LinkedOmics, STRING, and TIMER. One-way variance analysis and t-test were chosen to investigate the statistical differences of CAB39L expression in KIRC tissues with different clinical characteristics. The receiver operating characteristic (ROC) curve was chosen to assess the discriminatory capacity of CAB39L. Kaplan–Meier curves were employed for assessing the influence of CAB39L on the progression-free survival (PFS), disease-specific survival (DSS), and overall survival (OS) of KIRC patients. The independent prognostic significance of clinical parameters for OS such as CAB39L expression in KIRC patients was estimated by Cox analysis. A series of in vitro functional experiments and Western blot (WB) and immunohistochemistry (IHC) were used to validate the relative protein expression and function of CAB39L. Results: The mRNA and protein levels of CAB39L were relatively downregulated in KIRC samples. Meanwhile, hypermethylation of the CAB39L promoter region was possibly associated with its low expression in KIRC. The ROC curve showed that the mRNA expression of CAB39L had a strong diagnostic value for both early and late KIRC. Kaplan–Meier survival curves indicated that a higher mRNA level of CAB39L predicted good PFS, DSS, and OS. The mRNA expression of CAB39L was an independent prognostic factor (hazard ratio = 0.6, p = 0.034) identified by multivariate Cox regression analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis exhibited that CAB39L was mainly associated with substance and energy metabolism. Finally, overexpression of CAB39L impaired the proliferation and metastasis of KIRC cells in vitro. Conclusions: CAB39L possesses prognostic and diagnostic capacity in KIRC.
Metabolizable energy equivalence of guanidinoacetic acid in corn soybean meal-based broiler diets

- In this study, we evaluated how guanidinoacetic acid (GAA) addition in diets with various metabolizable energy (ME) contents affects the performance of broiler chickens. We also estimated the equivalence of GAA in ME. We distributed 1,280 one-day-old broilers in a completely randomized design with eight treatments, eight replicates, and twenty birds per experimental unit. Treatments were based on ME levels (2,775-2,875-2,975 kcal/kg; 2,850-2,950-3,050 kcal/kg; 2,925-3,025-3,125 kcal/kg; or 3,000-3,100-3,200 kcal/kg, from 1 to 7, 8 to 21, and 22 to 42 days of age) and the inclusion of GAA (0 or 600 mg/kg). Supplementation of GAA increased weight gain in broilers at an energy level of 2,908 kcal/kg and improved feed conversion ratio (FCR) at energy levels of 2,908 and 2,983 kcal/kg. There was a linear reduction in feed intake and an improvement in FCR of broilers with increasing levels of energy in diets, with and without GAA addition. Solving the equivalence equation, by applying each of the weighted average energy levels studied. indicates the GAA equivalence of 133, 103, 74, and 44 kcal/kg of diet. In conclusion, GAA supplementation improves broilers’ efficiency of energy use; the average ME equivalence of 600 mg/kg of GAA is 88.5 kcal/kg
Decision region analysis to deconstruct the subgroup influence on AI/ML predictions

Assessing the generalizability of deep learning algorithms based on the size and diversity of the training data is not trivial. This study uses the mapping of samples in the image data space to the decision regions in the prediction space to understand how different subgroups in the data impact the neural network learning process and affect model generalizability. Using vicinal distribution-based linear interpolation, a plane of the decision region space spanned by the random ‘triplet’ of three images can be constructed. Analyzing these decision regions for many random triplets can provide insight into the relationships between distinct subgroups. In this study, a contrastive self-supervised approach is used to develop a ‘base’ classification model trained on a large chest x-ray (CXR) dataset. The base model is fine-tuned on COVID-19 CXR data to predict image acquisition technology (computed radiography (CR) or digital radiography (DX) and patient sex (male (M) or female (F)). Decision region analysis shows that the model’s image acquisition technology decision space is dominated by CR, regardless of the acquisition technology for the base images. Similarly, the Female class dominates the decision space. This study shows that decision region analysis has the potential to provide insights into subgroup diversity, sources of imbalances in the data, and model generalizability.
Comparison of Selected Meshless Methods for Analysis of Steady, Fully-Developed, Laminar Flow of an Incompressible Newtonian Fluid in Internally Finned Tubes

Fluid flow in internally finned tubes is a very important problem from a practical point of view. In the literature there are many different numerical methods which were used for analysis this problem. However to the best knowledge of the authors of the present paper there are no so many papers in which meshless methods were applied for this purpose. The main advantages of these methods are: easy implementation, semi-analytical form of the approximate solution and no need for mesh generation. In the paper these meshless methods are compared in application for analysis of incompressible, fully-developed, Newtonian fluid flow in an internally finned tube.
A U.S. Isolate of Theileria orientalis Ikeda Is Not Transstadially Transmitted to Cattle by Rhipicephalus microplus

Theileria orientalis Ikeda has caused an epidemic of bovine anemia and abortion across several U.S. states. This apicomplexan hemoparasite is transmitted by Haemaphysalis longicornis ticks; however, it is unknown if other North American ticks are competent vectors. Since the disease movement is largely determined by the host tick range(s), the prediction of the T. orientalis spread among U.S. cattle populations requires determination of additional competent tick vectors. Although Rhipicephalus microplus has mostly been eradicated from the U.S., outbreaks in populations occur frequently, and the U.S. remains at risk for reintroduction. Since R. microplus is a vector of Theileria equi and T. orientalis DNA has been detected in R. microplus, the goal of this study was to determine whether R. microplus is a competent vector of T. orientalis. Larval R. microplus were applied to a splenectomized, T. orientalis Ikeda-infected calf for parasite acquisition, removed as molted adults, and applied to two T. orientalis naïve, splenectomized calves for transmission. After 60 days, the naïve calves remained negative for T. orientalis by PCR and cytology. Additionally, T. orientalis was not detected in the salivary glands or larval progeny of acquisition-fed adults. These data suggest that R. microplus is not a competent vector of the U.S. T. orientalis Ikeda isolate.
Johnson Counter-Based Multiphase Generation for VCO-Based ADC for Direct Digitization of Low Amplitude Sensor Signals

Voltage-controlled oscillator (VCO)-based analog-to-digital converter (ADC) have been used for the direct digitization of sensor signals. This article proposes a Johnson counter (JC) based multiphase generation for VCO-based ADC for direct digitization of low amplitude sensor signals. The proposed approach reduces the flicker noise of the VCO, thereby giving better signal-to-noise (SNR) ratio. A prototype design is implemented at a printed circuit board (PCB) level using discrete components achieving a signal-to noise + distortion ratio (SNDR) SNDR of 59.2 dB over a 5 kHz bandwidth for $200 \text {mV}_{\text {pp},\text {diff}}$ input signal using an eight-phase JC-based VCO ADC sampled at 2.5 MHz. The proposed design also achieves a dynamic range of 64 dB for 5-kHz bandwidth and is therefore ideal for many sensor interface applications.
A Fast Algorithm of Wavelet Transform Based on Arithmetic Fourier Transform

The multiplicity of computing Discrete Fourier Transform using the Arithmetic Fourier Transform are just only o(N). Based on this feature, a fast algorithm for computing Discrete Wavelet Transform is presented after analyzing the principle of Mallat Algorithm and the construction character of the Discrete Fourier Transform . The theoretical derivation and the analysis of computer simulation results are also given.
Accurate and Swift Approach to As-Built Mapping in TBM-Excavated Tunnels

AbstractThis paper offers a new method for mapping as-built tunnels excavated by tunnel-boring machines (TBMs) that is conveniently applicable and cost-effective. The presented procedure can algorithmically be explained as follows: (1) surveying some points on the edge of each segment using a reflectorless total station in an arbitrarily initial coordinate system, (2) shifting the measured coordinates to a location as close as the origin of the initial frame, (3) fitting a plane to the shifted coordinates of the measuring points, (4) deriving the direction angles between the normal vector and the axes of the coordinate system, (5) rotating the shifted coordinates around the third and first axes of the frame, (6) fitting a circle to the transformed coordinates to determine the position of its origin, and (7) transforming the derived coordinates of the circle origin into the initial coordinate system. The capability and reliability of the method have been indicated by means of simulated data sets. The metho.
Extracellular Vesicles and Their Zeta Potential as Future Markers Associated with Nutrition and Molecular Biomarkers in Breast Cancer

A nutritional intervention promotes the loss of body and visceral fat while maintaining muscle mass in breast cancer patients. Extracellular vesicles (EVs) and their characteristics can be potential biomarkers of disease. Here, we explore the changes in the Zeta potential of EVs; the content of miRNA-30, miRNA-145, and miRNA-155; and their association with body composition and biomarkers of metabolic risk in breast cancer patients, before and 6 months after a nutritional intervention. Clinicopathological data (HER2neu, estrogen receptor, and Ki67), anthropometric and body composition data, and plasma samples were available from a previous study. Plasma EVs were isolated and characterized in 16 patients. The expression of miRNA-30, miRNA-145, and miRNA-155 was analyzed. The Zeta potential was associated with HER2neu (β = 2.1; p = 0.00), Ki67 (β = −1.39; p = 0.007), estrogen positive (β = 1.57; p = 0.01), weight (β = −0.09; p = 0.00), and visceral fat (β = 0.004; p = 0.00). miRNA-30 was associated with LDL (β = −0.012; p = 0.01) and HDL (β = −0.02; p = 0.05). miRNA-155 was associated with visceral fat (β = −0.0007; p = 0.05) and Ki67 (β = −0.47; p = 0.04). Our results reveal significant associations between the expression of miRNA-30 and miRNA-155 and the Zeta potential of the EVs with biomarkers of metabolic risk and disease prognosis in women with breast cancer; particularly, the Zeta potential of EVs can be a new biomarker sensitive to changes in the nutritional status and breast cancer progression.
A study of the turbulence within a spiralling vortex filament using proper orthogonal decomposition

The stability and turbulence characteristics of a vortex filament emanating from a single-bladed rotor in hover are investigated using proper orthogonal decomposition (POD). The rotor is operated at a tip chord Reynolds number and tip Mach number of 218 000 and 0.23, respectively, and with a blade loading of $C_{T}/{\it\sigma}=0.066$ . In-plane components of the velocity field (normal to the axis of the vortex filament) are captured by way of two-dimensional particle image velocimetry with corrections for vortex wander being performed using the ${\it\Gamma}_{1}$ method. The first POD mode alone is found to encompass nearly 75 % of the energy for all vortex ages studied and is determined using a grid of sufficient resolution to avoid numerical integration errors in the decomposition. The findings reveal an equal balance between the axisymmetric and helical modes during vortex roll-up, which immediately transitions to helical mode dominance at all other vortex ages. This helical mode is one of the modes of the elliptic instability. The spatial eigenfunctions of the first few Fourier-azimuthal modes associated with the most energetic POD mode is shown to be sensitive to the choice of the wander correction technique used. Higher Fourier-azimuthal modes are observed in the outer portions of the vortex and appeared not to be affected by the choice of the wander correction technique used.
Champs de Markov pour le traitement d'images catadioptriques

Les images produites par les capteurs catadioptriques presentent des distorsions importantes qui empechent l’utilisation systematique de traitements conventionnels. Ainsi les champs de Markov dont l’utilite n’est plus a demontrer en traitement d’images perspectives, ne sont pas utilisables directement sur les images omnidirectionnelles. Dans cet article, nous proposons une adaptation des Champs de Markov aux images catadioptriques. La methode consiste alors a redefinir la notion de voisinage en utilisant le theoreme de l’equivalence des capteurs catadioptriques centraux. Nous montrons l’interet de cette adaptation dans le cas de la segmentation supervisee en niveau de gris et de la detection de mouvement.
Mitigation of salt stress and stimulation of growth by salicylic acid and calcium chloride seed priming in two barley species

Abstract The main objective of the current study is to underline the effects of salicylic acid or calcium chloride seed priming on plant growth, water content, chlorophyll content and photosynthetic activity of two barley species Hordeum marinum and Hordeum vulgare exposed to salinity (0, 100 and 200 mM NaCl). Results revealed that salinity decreased shoot and root growth, transpiration rate, chlorophyll concentration, stomata conductivity and water content in plants obtained from unprimed seeds. This reduction was dependent on the saline concentration used. However, Hordeum marinum species showed tolerance by maintaining tissue hydration, growth, photosynthetic assimilation and chlorophyll biosynthesis in stressed plants compared to controls. Moreover, priming seeds with salicylic acid or calcium chloride significantly improved all the above parameters under different salt treatments, suggesting that the effectiveness of this approach mainly depends on the priming agent applied and may vary with species and stress intensity applied.
Knowledge and Attitudes of Women toward the Influenza Vaccination during Pregnancy in Amman, Jordan

Objectives: The study aimed to assess the level of knowledge and attitudes of Jordanian women regarding influenza and its vaccine during pregnancy. Methods: A cross-sectional study was conducted on 384 Jordanian women who had had a full-term delivery during the last 12 months. Data were collected with an interviewer-administrated questionnaire at five governmental comprehensive healthcare centers in Amman governorate. Results: Most participants had moderate knowledge (78.1%) (average score of 6.08 ± 1.38 out of 10). Women were either positive (51.0%) or neutral (47.9%) towards the influenza vaccination during pregnancy (average score of 52.43 ± 6.29 out of 75). Further, the vaccination rate during the women’s latest pregnancy was 2.1%. A significant positive relationship was found between the knowledge and attitudes of participants (p=0.001). Conclusion: The vaccination rate was low among women during pregnancy. The study’s results suggest that a greater awareness of the flu vaccine would help build positive attitudes towards its uptake during pregnancy. In this sense, antenatal care healthcare providers, such as gynecologists and midwives, should communicate strong health education messages about the flu vaccine as a preventative measure against influenza complications during pregnancy.
The Role of Health Behaviors in Quality of Life: A Longitudinal Study of Patients with Colorectal Cancer

Colorectal cancer (CRC) is the third most common malignancy and the second most common cancer-related cause of death worldwide. CRC incidence depends, in part, on the health behaviors that make up an individual’s lifestyle. We aimed to assess the influence of health behaviors and quality of life (QoL) among patients with CRC receiving surgical treatment. In this single-center questionnaire study, 151 patients were surveyed 1 week before and 6 months after colorectal procedures (laparoscopic hemicolectomy, low rectal anterior resection, abdominoperineal resection, and others). This study demonstrated a significant decrease in alcohol consumption and physical activity following the execution of colorectal procedures. No statistically significant changes were observed in smoking or the consumption of healthy food. Global QoL did not change significantly; however, a decrease in physical and role-related functioning was observed. Significant improvements in emotional functioning were also observed. A detailed analysis showed that physical and social functioning were related to smoking, the consumption of healthy food, physical activity, and additional therapies. Emotional functioning was related to smoking, the consumption of healthy food, and complementary treatments. Six months following an operation, it was also dependent on alcohol intake. Physical functioning was the area that decreased the most in the six months after colorectal tumor surgery compared to the period before surgery. Health behaviors such as cessation of smoking, engagement in physical activity, and the consumption of healthy food contributed to a higher quality of life among patients prior to resecting colorectal cancer and six months after the procedure. Patients who received adjuvant/neoadjuvant therapy had a lower quality of life than patients who did not receive this type of therapy. The kind of surgery (laparoscopic hemicolectomy, lower anterior rectum resection, or abdominoperineal rectum resection) was not related to QoL six months after surgery.
Robust adaptive control : Improved e - modification using a non-quadratic lyapunov function

In adaptive control schemes, adaptive laws are modified to obtain robust adaptive control schemes. The adaptive laws with e - modification have been well known over a decade; this e -modification was developed based on Lyapunov stability theory, using a Quadratic Lyapunov Function (QLF). In contrast to such development, using a Non-Quadratic Lyapunov Function (NQLF), this paper presents a new adaptive laws with improved e - modification. This paper also presents simulation results, supporting the arguments.
Representation of topography by partial steps using the immersed boundary method in a vector vorticity equation model (VVM)

In this study, representation of surface topography in the vector vorticity equation model (VVM) is updated with a partial step approach using the immersed boundary method. Compared with the full step approach, the partial step approach provides additional topography forcing to represent micro mountains while preserving the same grid structure through interpolating from adjacent grid points. It maintains the characteristics of dynamics and physics of VVM and improves the representation of gentle slope topography without increasing vertical resolution. This approach produces reasonable results on the simulation of classical mountain waves with coarse vertical resolution. Additional experiments are performed to verify our approach including density driven flow using a cold bubble and 3‐D orographic precipitation over a ridge. The results show that vorticity fields in the partial step approach have a smoother response to the gentle slopes due to the improvement in the topography representation.
Estimation in moderately misspecified models

Suppose data are fitted to some parametric model f(y, 8), but that the true model happens to be f(y,O,/), with an additional/ parameter, and where f(y,O,/o) = f(y,8). When a parameter J.L is to be estimated, one can use p,(Bwide, ::Ywide) based on likelihood estimation in the wider model, or p,(Bnarr, /O) based on likelihood estimation of 8 alone in the narrow model. Including 1 in the model means less bias but larger sampling variability. Two basic questions are addressed in this article. (i) Just how much misspecification can the narrow model tolerate? In the context of a large-sample moderate misspecification framework we find a surprisingly simple, sharp, and general answer, in the form of an explicit criterion for when narrow estimation is more precise than wide estimation. There is effectively a 'tolerance radius' around a given narrow model. The theory is illustrated by computing this tolerance radius in a selection of interesting examples, that also demonstrate the degree of robustness of important standard methods against moderate incorrectness of the model under which they are optimal. (ii) Are there other estimators that work well both under narrow and wide circumstances? We discuss several possibilities and propose some new procedures. All methods are compared in a broad performance study. This comparison can be carried out rather generally and rather simply due to a drastic reduction to a particular standard problem.
Melanoma Clinical Decision Support System: An Artificial Intelligence-Based Tool to Diagnose and Predict Disease Outcome in Early-Stage Melanoma Patients

Simple Summary Early diagnosis and accurate prognosis is essential to personalize treatment and improve the survival of melanoma patients. We report here a new tool that can improve the early diagnosis of melanoma through the use of epiluminescence dermatoscopy and deep learning image analysis. By employing artificial intelligence algorithms to analyze simple serological and histopathological biomarkers, the risk of metastasis and the disease-free interval of melanoma patients can be accurately predicted. This low-cost Melanoma Clinical Decision Support System represents an effective tool to help clinicians manage melanoma patients. Abstract This study set out to assess the performance of an artificial intelligence (AI) algorithm based on clinical data and dermatoscopic imaging for the early diagnosis of melanoma, and its capacity to define the metastatic progression of melanoma through serological and histopathological biomarkers, enabling dermatologists to make more informed decisions about patient management. Integrated analysis of demographic data, images of the skin lesions, and serum and histopathological markers were analyzed in a group of 196 patients with melanoma. The interleukins (ILs) IL-4, IL-6, IL-10, and IL-17A as well as IFNγ (interferon), GM-CSF (granulocyte and macrophage colony-stimulating factor), TGFβ (transforming growth factor), and the protein DCD (dermcidin) were quantified in the serum of melanoma patients at the time of diagnosis, and the expression of the RKIP, PIRIN, BCL2, BCL3, MITF, and ANXA5 proteins was detected by immunohistochemistry (IHC) in melanoma biopsies. An AI algorithm was used to improve the early diagnosis of melanoma and to predict the risk of metastasis and of disease-free survival. Two models were obtained to predict metastasis (including “all patients” or only patients “at early stages of melanoma”), and a series of attributes were seen to predict the progression of metastasis: Breslow thickness, infiltrating BCL-2 expressing lymphocytes, and IL-4 and IL-6 serum levels. Importantly, a decrease in serum GM-CSF seems to be a marker of poor prognosis in patients with early-stage melanomas.