Miracle-dz/UniFAR-FTUs huggingface dataset:
Symbolic regression based genetic approximations of the Colebrook equation for flow friction

Widely used in hydraulics, the Colebrook equation for flow friction relates implicitly to the input parameters; the Reynolds number, Re and the relative roughness of an inner pipe surface, ε/D with an unknown output parameter; the flow friction factor, λ; λ = f (λ, Re, ε/D). In this paper, a few explicit approximations to the Colebrook equation; λ ≈ f (Re, ε/D), are generated using the ability of artificial intelligence to make inner patterns to connect input and output parameters in an explicit way not knowing their nature or the physical law that connects them, but only knowing raw numbers, {Re, ε/D}→{λ}. The fact that the used genetic programming tool does not know the structure of the Colebrook equation, which is based on computationally expensive logarithmic law, is used to obtain a better structure of the approximations, which is less demanding for calculation but also enough accurate. All generated approximations have low computational cost because they contain a limited number of logarithmic forms used for normalization of input parameters or for acceleration, but they are also sufficiently accurate. The relative error regarding the friction factor λ, in in the best case is up to 0.13% with only two logarithmic forms used. As the second logarithm can be accurately approximated by the Padé approximation, practically the same error is obtained also using only one logarithm.
Correcting Length Bias in Neural Machine Translation

We study two problems in neural machine translation (NMT). First, in beam search, whereas a wider beam should in principle help translation, it often hurts NMT. Second, NMT has a tendency to produce translations that are too short. Here, we argue that these problems are closely related and both rooted in label bias. We show that correcting the brevity problem almost eliminates the beam problem; we compare some commonly-used methods for doing this, finding that a simple per-word reward works well; and we introduce a simple and quick way to tune this reward using the perceptron algorithm.
Bioinformatics Analysis Identifies p53 as a Candidate Prognostic Biomarker for Neuropathic Pain

Neuropathic pain (NP) is a type of chronic pain that is different from the common type of pain. The mechanisms of NP are still poorly understood. Exploring the key genes and neurobiological changes in NP could provide important diagnostic and treatment tools for clinicians. GSE24982 is an mRNA-seq dataset that we downloaded from the Gene Expression Omnibus database to identify key genes in NP. Differentially expressed genes (DEGs) were identified using the BRB-ArrayTools software and R. Functional and pathway enrichment analyses of the DEGs were performed using Metascape. A protein–protein interaction network was created and visualized using Cytoscape. A total of 123 upregulated DEGs were obtained. Among these genes, p53 was the node with the highest degree; hence, we validated it experimentally using a chronic constriction injury mouse model. Our results showed that overexpression of the p53 gene, and the subsequent increase in caspase-3 expression, in dorsal root ganglion neurons led to increased apoptotic changes in these neurons. p53 may therefore be partly responsible for the development of chronic constriction injury-induced NP.
Efficacy and safety of BORTEZOMIB treatment for refractory acute antibody‐mediated rejection—a pilot study

A novel therapeutic approach to refractory acute antibody‐mediated rejection (AMR) in kidney transplant recipients was applied in 23 patients based on administration of Bortezomib, intravenous corticosteroids, plasmapheresis and Rituximab. Application of Bortezomib regimen led to diminishing of donor‐specific antibodies (DSA) to HLA‐B (P = 0.004) and HLA‐DR (P = 0.0005), but not to HLA‐A (P = 0.106) and HLA‐DQ antigens (P = 0.18). Patients with good clinical response to treatment had significantly better allograft survival than recipients with continuing deterioration of graft function (P = 0.019). Graft survival after therapy of refractory AMR was significantly worse than survival after first transplantation and was comparable with outcomes after retransplantation. In conclusion, therapy with Bortezomib was well tolerated and effective in decreasing the levels of HLA‐B and ‐DR antibodies, however, was not successful in depleting HLA‐A and ‐DQ DSA.
Inflammation and atrial fibrillation: A comprehensive review

Atrial fibrillation (AF) has different underlying substrates. Atrial remodeling involves electrophysiological and structural abnormalities that promote the development and perpetuation of AF. Experimental and clinical data indicate that inflammation is implicated in the pathophysiology of atrial remodeling. The mechanistic links between atrial remodeling and inflammation are complex while diverse underlying diseases and conditions may affect these pathways. Inflammatory markers have also been associated with AF development, recurrence, perpetuation, total AF burden as well as with thromboembolic complications. The development of specific anti‐inflammatory interventions in this setting seems to be challenging and complicated. Several agents with pleiotropic properties, including anti‐inflammatory, have been tested in experimental and clinical settings with variable results. This updated review provides a concise overview of all available data regarding the role of inflammation in AF including the predictive role of inflammatory markers. Also, current knowledge and future directions on anti‐inflammatory strategies are critically discussed.
Light correlated color temperature and task switching performance in preschool-age children: Preliminary insights

Data from a growing number of experimental studies show that exposure to higher correlated color temperature (CCT) ambient light, containing more blue light, can positively impact alertness and cognitive performance in older children and adults. To date, few if any studies have examined whether light exposure influences cognitive task performance in preschool-age children, who are in the midst of rapid developmental changes in attention and executive function skills. In this study, healthy children aged 4.5–5.5 years (n = 20; 11 females) completed measures of sustained attention and task switching twice while being exposed to LED light set to either 3500K (a lower CCT) or 5000K (a higher CCT). A control group (n = 18; 10 females) completed the tasks twice under only the 3500K lighting condition. Although the lighting condition did not impact performance on the sustained attention task, exposure to the higher CCT light lead to greater improvement in preschool-age children’s task switching performance (F(1,36) = 4.41, p = 0.04). Children in the control group showed a 6.5% increase in task switching accuracy between time points, whereas those in the experimental group improved by 15.2%. Our primary finding–that exposure to light at a higher correlated color temperature leads to greater improvement in task switching performance–indicates that the relationship between the spectral power distribution of light and executive function abilities is present early in cognitive development. These data have implications for designing learning environments and suggest that light may be an important contextual factor in the lives of young children in both the home and the classroom.
Gaussian Mixture Generative Adversarial Networks for Diverse Datasets, and the Unsupervised Clustering of Images

Generative Adversarial Networks (GANs) have been shown to produce realistically looking synthetic images with remarkable success, yet their performance seems less impressive when the training set is highly diverse. In order to provide a better fit to the target data distribution when the dataset includes many different classes, we propose a variant of the basic GAN model, called Gaussian Mixture GAN (GM-GAN), where the probability distribution over the latent space is a mixture of Gaussians. We also propose a supervised variant which is capable of conditional sample synthesis. In order to evaluate the model's performance, we propose a new scoring method which separately takes into account two (typically conflicting) measures - diversity vs. quality of the generated data. Through a series of empirical experiments, using both synthetic and real-world datasets, we quantitatively show that GM-GANs outperform baselines, both when evaluated using the commonly used Inception Score, and when evaluated using our own alternative scoring method. In addition, we qualitatively demonstrate how the \textit{unsupervised} variant of GM-GAN tends to map latent vectors sampled from different Gaussians in the latent space to samples of different classes in the data space. We show how this phenomenon can be exploited for the task of unsupervised clustering, and provide quantitative evaluation showing the superiority of our method for the unsupervised clustering of image datasets. Finally, we demonstrate a feature which further sets our model apart from other GAN models: the option to control the quality-diversity trade-off by altering, post-training, the probability distribution of the latent space. This allows one to sample higher quality and lower diversity samples, or vice versa, according to one's needs.
Personality traits affect the influences of intensity perception and emotional responses on hedonic rating and preference rank toward basic taste solutions

This study aimed at determining, based on independent predictors of taste intensity and emotional response, whether individual personality traits could affect prediction models of overall liking and preference rank toward basic taste solutions. Sixty‐seven participants rated taste intensities (TI) of four basic‐taste solutions at both low and high concentrations, and of plain water. Emotional responses toward each sample were measured using a self‐reported emotion questionnaire (SE), facial expressions (FE), and/or autonomic nervous system responses (ANS). Participants rated overall liking of the samples and ranked their preferences. Based on the results of a hierarchical cluster analysis of five personality traits measured using the Big Five Inventory, participants were classified into two clusters: cluster N (high neuroticism) and cluster E (high extraversion). Results showed that the SE measure for both clusters N and E was better than the TI, FE, and ANS measures in explaining variances of overall liking or preference rank. A measurement of effect size found that using FE and/or taste intensity measures, along with self‐reported emotion measure, could enhance model predictability of overall liking or preference rank toward taste samples for cluster N, while the contribution to the prediction model for cluster E was minimal. ANS measures showed little contribution to the prediction model of overall liking for either cluster. In conclusion, this study shows that personality traits, in particular traits of extraversion and neuroticism, affect not only optimum measures of emotional responses, but also modulate predicting overall liking and preference rank toward basic taste solutions.
Burning mouth syndrome in postmenopausal women with self-reported sleep problems

ABSTRACT Objective The aim of this study was to investigate possible relationships among hematologic factors, psychological dimensions, the presence of self-reported sleep problems, and clinical characteristics in patients with burning mouth syndrome (BMS). Methods Twenty-five postmenopausal female patients with primary BMS (aged 55.2 ± 9.6 years) were included. All participants underwent clinical and psychological evaluations and blood sampling. The patients were subdivided according to the absence or presence of the self-reported sleep problems. Results Pain intensity of BMS patients with sleep problems was significantly higher than those without sleep problems, and the severity of oral complaints was correlated with the presence of depression, anxiety, hostility, phobia, and psychosis. Estradiol levels were significantly lower, and FSH and LH levels were higher in BMS patients with sleep problems than those without sleep problems. Discussion BMS patients with sleep problems may suffer inharmonious psychoneuroendocrinological interactions that might worsen oral BMS symptoms.
TXNIP regulates AKT‐mediated cellular senescence by direct interaction under glucose‐mediated metabolic stress

Aging is associated with an inevitable and universal loss of cell homeostasis and restricts an organism's lifespan by an increased susceptibility to diseases and tissue degeneration. The glucose uptake associated with producing energy for cell survival is one of the major causes of ROS production under physiological conditions. However, the overall mechanisms by which glucose uptake results in cellular senescence remain mysterious. In this study, we found that TXNIP deficiency accelerated the senescent phenotypes of MEF cells under high glucose condition. TXNIP‐/‐ MEF cells showed greater induced glucose uptake and ROS levels than wild‐type cells, and N‐acetylcysteine (NAC) treatment rescued the cellular senescence of TXNIP‐/‐ MEF cells. Interestingly, TXNIP‐/‐ MEF cells showed continuous activation of AKT during long‐term subculture, and AKT signaling inhibition completely blocked the cellular senescence of TXNIP‐/‐ MEF cells. In addition, we found that TXNIP interacted with AKT via the PH domain of AKT, and their interaction was increased by high glucose or H2O2 treatment. The inhibition of AKT activity by TXNIP was confirmed using western blotting and an in vitro kinase assay. TXNIP deficiency in type 1 diabetes mice (Akita) efficiently decreased the blood glucose levels and finally increased mouse survival. However, in normal mice, TXNIP deficiency induced metabolic aging of mice and cellular senescence of kidney cells by inducing AKT activity and aging‐associated gene expression. Altogether, these results suggest that TXNIP regulates cellular senescence by inhibiting AKT pathways via a direct interaction under conditions of glucose‐derived metabolic stress.
A study of integer sorting on multicores

Integer sorting on multicores and GPUs can be realized by a variety of approaches that include variants of distribution-based methods such as radix-sort, comparison-oriented algorithms such as deterministic regular sampling and random sampling parallel sorting, and network-based algorithms such as Batcher’s bitonic sorting algorithm. In this work we present an experimental study of integer sorting on multicore processors. We have implemented serial and parallel radix-sort for various radixes, deterministic regular oversampling, and random oversampling parallel sorting, including new variants of ours, and also some previously little explored or unexplored variants of bitonic-sort and odd-even transposition sort. The study uses multithreading and multiprocessing parallel programming libraries with the same C language code working under Open MPI, MulticoreBSP, and BSPlib. We first provide some general high-level observations on the performance of these implementations. If we can conclude anything is that accurate prediction of performance by taking into consideration architecture dependent features such as the structure and characteristics of multiple memory hierarchies is difficult and more often than not untenable. To some degree this is affected by the overhead imposed by the high-level library used in the programming effort. Another objective is to model the performance of these algorithms and their implementations under the MBSP (Multi-memory BSP) model. Despite the limitations mentioned above, we can still draw some reliable conclusions and reason about the performance of these implementations using the MBSP model, thus making MBSP useful and usable.
Augmented Pla2g4c/Ptgs2/Hpgds axis in bronchial smooth muscle tissues of experimental asthma

Rationale Augmented smooth muscle contractility of the airways is one of the causes of airway hyperresponsiveness in asthmatics. However, the mechanism of the altered properties of airway smooth muscle cells is not well understood. Objectives To identify differentially expressed genes (DEGs) related to the bronchial smooth muscle (BSM) hyper-contractility in a murine asthma model. Methods The ovalbumin (OA)-sensitized mice were repeatedly challenged with aerosolized OA to induce asthmatic reaction. Transcriptomic profiles were generated by microarray analysis of BSM tissues from the OA-challenged and control animals, and KEGG (Kyoto Encyclopedia of Genes and Genomes) Pathway Analysis was applied. Measurements and main results Tension study showed a BSM hyperresponsiveness to acetylcholine (ACh) in the OA-challenged mice. A total of 770 genes were differentially expressed between the OA-challenged and control animals. Pathway analysis showed a significant change in arachidonic acid (AA) metabolism pathway in BSM tissues of the OA-challenged mice. Validation of DEGs by quantitative RT-PCR showed a significant increase in PLA2 group 4c (Pla2g4c)/COX-2 (Ptgs2)/PGD2 synthase 2 (Hpgds) axis. PGD2 level in bronchoalveolar fluids of the OA-challenged mice was significantly increased. A 24-h incubation of BSM tissues with PGD2 caused a hyperresponsiveness to ACh in naive control mice. Conclusions AA metabolism is shifted towards PGD2 production in BSM tissues of asthma. Increased PGD2 level in the airways might be a cause of the BSM hyperresponsiveness in asthma.
Order-level fern plastome phylogenomics: new insights from Hymenophyllales.

PREMISE OF THE STUDY Filmy ferns (Hymenophyllales) are a highly specialized lineage, having mesophyll one-cell layer thick and inhabiting particularly shaded and humid environments. The phylogenetic placement of Hymenophyllales has been inconclusive, and while over 87 whole fern plastomes have been published, none was from Hymenophyllales. To better understand the evolutionary history of filmy ferns, we sequenced the first complete plastome for this order. METHODS We compiled a phylogenomic plastome data set encompassing all 11 fern orders, and reconstructed phylogenies using different data types (nucleotides, codons, and amino acids) and partition schemes (codon positions and loci). To infer the evolution of fern plastome organization, we coded plastome features, including inversions, inverted repeat boundary shifts, gene losses, and tRNA anticodon sequences as characters, and reconstructed the ancestral states for these characters. KEY RESULTS We discovered a suite of novel, Hymenophyllales-specific plastome structures that likely resulted from repeated expansions and contractions of the inverted repeat regions. Our phylogenetic analyses reveal that Hymenophyllales is highly supported as either sister to Gleicheniales or to Gleicheniales + the remaining non-Osmundales leptosporangiates, depending on the data type and partition scheme. CONCLUSIONS Although our analyses could not confidently resolve the phylogenetic position of Hymenophyalles, the results here highlight the danger of drawing conclusions from "all-in" phylogenomic data set without exploring potential inconsistencies in the data. Finally, our first order-level reconstruction of fern plastome structural evolution provides a useful framework for future plastome research.
A comparison of 8‐mm and open‐irrigated gold‐tip catheters for typical atrial flutter ablation: Data from a prospective multicenter registry

Cavotricuspid isthmus (CTI) radiofrequency (RF) catheter ablation is the standard treatment for patients suffering from CTI‐dependent atrial flutter (AFL). The aim of this study was to compare the use in clinical practice of 8‐mm gold‐tip catheter (8mmRFC) and open‐irrigated gold‐tip catheter (irrRFC) for RF typical AFL ablation.
Catheter ablation of ventricular tachycardia in nonischemic cardiomyopathy

The number of patients with nonischemic cardiomyopathy (NICM) undergoing catheter ablation of ventricular tachycardia (VT) has increased by the years, however, there are no randomized studies of VT ablation in this population. Many studies have reported more mixed or inferior outcome after the ablation in patients with NICM as compared to in those with ischemic cardiomyopathy (ICM)—likely because of the heterogeneous VT substrates in each etiology. While, various ablation strategies for substrate modification in the setting of ICM, including low voltage area ablation, late potential abolition, and local abnormal ventricular activity elimination, have been well established, it is still unknown which ablation strategy is effective for prevention of recurrence VTs in NICM patients. Therefore, this review will highlight the recent progress made in VT ablation in patients with NICM.
Expedition 381 methods

L.C. McNeill, D.J. Shillington, G.D. O. Carter, J.D. Everest, E. Le Ber, R.E. Ll. Collier, A. Cvetkoska, G. De Gelder, P. Diz, M. -L. Doan, M. Ford, R.L. Gawthorpe, M. Geraga, J. Gillespie, R. Hemelsdaël, E. Herrero-Bervera, M. Ismaiel, L. Janikian, K. Kouli, S. Li, M.L. Machlus, M. Maffione, C. Mahoney, G. Michas, C. Miller, C.W. Nixon, S.A. Oflaz, A.P. Omale, K. Panagiotopoulos, S. Pechlivanidou, M.P. Phillips, S. Sauer, J. Seguin, S. Sergiou, and N.V. Zakharova2
Adding It Up

Manipulatives are a common tool in mathematics teaching and learning, including for students with disabilities. The most common manipulatives are concrete manipulatives, yet app-based manipulatives are a viable age-appropriate option for secondary students with disabilities. Through an adapted alternating treatment design with three middle school students—two with mild intellectual disability and one with a learning disability, researchers explored the impact of virtual and concrete manipulatives on students’ accuracy, independence, and task completion time for solving addition of fractions with unlike denominators. Students were equally successful in terms of accuracy and differences with independence were minimal. When comparing the two manipulative types, the results were idiosyncratic; two students were more independent with the concrete manipulative and one with the app-based manipulative. Implications for research regarding mathematics instruction and use of concrete and app-based manipulatives are discussed.
Converting loss‐on‐ignition to organic carbon content in arable topsoil: pitfalls and proposed procedure

Assessments of changes in soil organic carbon (SOC) stocks depend heavily on reliable values of SOC content obtained by automated high‐temperature C analysers. However, historical as well as current research often relies on indirect SOC estimates such as loss‐on‐ignition (LOI). In this study, we revisit the conversion of LOI to SOC using soil from two long‐term agricultural field experiments and one arable field with different contents of SOC, clay and particles <20 μm (Fines20). Clay‐, silt‐ and sand‐sized fractions were isolated from the arable soil. Samples were analysed for texture, LOI (500°C for 4 hours) and SOC by dry combustion. For a topsoil with 2 g C and 30 g clay 100 g−1 soil, converting LOI to SOC by the conventional factor 0.58 overestimated the SOC stock by 45 Mg C ha−1. The error increased with increasing contents of clay and Fines20. Converting LOI to SOC by a regression model underestimated the SOC stock by 5 Mg C ha−1 at small clay and Fines20 contents and overestimated the SOC stock by 8 Mg C ha−1 at large contents. This was due to losses of structural water from clay minerals. The best model to convert LOI to SOC incorporated clay content. Evaluating this model against an independent dataset gave a root mean square error and mean error of 0.295 and 0.125 g C 100 g−1, respectively. To avoid misleading accounts of SOC stocks in agricultural soils, we recommend re‐analysis of archived soil samples for SOC using high‐temperature dry combustion methods. Where archived samples are not available, accounting for clay content improves conversion of LOI to SOC considerably. The use of the conventional conversion factor 0.58 is antiquated and provides misleading estimates of SOC stocks.