Miracle-dz/UniFAR-FTUs huggingface dataset:
Nuclear Protein 1 Expression Is Associated with PPARG in Bladder Transitional Cell Carcinoma

Background The Nuclear protein 1 gene was first discovered in acute pancreatitis and functions as an oncogene in cancer progression and drug resistance. However, the role of Nuclear protein 1 in bladder transitional cell carcinoma (BTCC) is still unclear. Methods The Cancer Genome Atlas database and immunohistochemical analysis were adopted to evaluate Nuclear protein 1 expression in BTCC. We applied lentivirus-mediated small-interfering RNA to down-regulate the expression of Nuclear protein 1 in BTCC cell lines. We further performed an Affymetrix microarray and Gene Set Enrichment Analysis (GSEA) to assess the genes and signaling pathways related to Nuclear protein 1. Results We found that Nuclear protein 1 expression was up-regulated in BTCC and positively related to the degree of BTCC malignancy. Compared with Caucasian patients with BTCC, Nuclear protein 1 expression was attenuated in Asian patients. The Affymetrix microarray showed that lipopolysaccharide was the upstream regulatory factor of Nuclear protein 1 in BTCC. The GSEA indicated that Nuclear protein 1 expression was associated with signaling pathways in cancer, peroxisome proliferator-activated receptor (PPAR) pathways, and RNA degradation. The expression of Nuclear protein 1 was negatively correlated with PPARG (R = −0.290, P < 0.001), but not with PPARA (R = 0.047, P = 0.344) and PPARD (R = −0.055, P = 0.260). Conclusions The study findings indicate that Nuclear protein 1 is positively associated with the malignancy degree of BTCC and that Nuclear protein 1 expression is negatively correlated with PPARG.
Oscillation Criteria for Second Order Linear Differential Equations

By using the form of Ricattis equation and combining it with the technique of integral averages, oscillation criteria for second order differential equations (r(t)x′)′+p(t)x′+q(t)x= 0 are obtained. The results are generalizations and improvements of earlier results.
DCI-PGCN: Dual-Channel Interaction Portable Graph Convolutional Network for Landslide Detection

Landslide, a kind of destructive natural disaster, often occurs in the mountainous areas of China. Landslide information instant collection plays an important role in taking appropriate remedial measures and personnel evacuation. In recent years, the use of convolutional neural network (CNN) for landslide regional detection achieved good performance; however, most CNN-based methods had no regard for the internal connection of the cover materials in the disaster occurrence area. Moreover, the information revealed by the internal deformation features was ignored, and the same surface object in the image presents different features under different illumination, environment, and resolution, which makes it difficult to extract the structural features of landslide images. In this article, we propose a novel graph convolutional network for landslide detection, inspired by attention mechanism’s ability to focus on selective information supplemented with both different channels. The global maximum node connection strategy with positive and negative connectivity makes the graph convolution network (GCN) more portable, which is used as the basic unit of graph feature propagation to construct a multilayer residual connection module. In order to learn interactively and spread graph information, channel dimension is added to make the boundary of features between classes more discriminative. Extensive experiments on Sichuan Province and Bijie landslide datasets show that our proposed method outperforms other detection models and achieves high precision and accuracy. In addition, we also carried out landslide detection for Zhaotong of Yunnan Province on GF-2 original images to prove the effectiveness and applicability of the algorithm.
An Efficient and Compact Equalizer Based on Forward-Flyback Conversion for Large-Scale Energy Storage Systems

An effective battery equalizer is of great significance to eliminate inconsistencies and improve the performance of large-scale battery packs. Nevertheless, the existing balancing circuits have various problems, such as slow balancing speed, high cost, bulky size, and complex control. Therefore, this article designs an efficient and compact transformer-based equalizer, which works at forward-flyback conversion. Distinguished from the conventional transformer-based equalizers, the proposed equalizer requires only one MOSFET and one transformer winding equipped with each cell. Two complementary pulse width modulation (PWM) signals can control all MOSFETs used in the proposed equalizer. The equalizer can automatically equalize all cells without the need for additional voltage sensing and demagnetization circuits, reducing the cost and volume. It can directly transfer energy between any two adjacent modules, improving the equalization efficiency and speed. An experimental prototype of eight series-connected cells was set up. The experimental results and systematic comparison with the existing balancing topologies show that the proposed equalizer is appropriate for balancing large-scale energy storage systems (ESSs). The energy delivery efficiency among cells can be as high as 93.15% over various loading conditions.
Immune-Related Long Non-Coding RNA Signatures for Tongue Squamous Cell Carcinoma

Background: Tongue squamous cell carcinoma (TSCC) represents one of the major subsets of head and neck cancer, which is characterized by unfavorable prognosis, frequent lymph node metastasis, and high mortality rate. The molecular events regulating tongue tumorigenesis remain elusive. In this study, we aimed to identify and evaluate immune-related long non-coding RNAs (lncRNAs) as prognostic biomarkers in TSCC. Methods: The lncRNA expression data for TSCC were obtained from The Cancer Genome Atlas (TCGA) and the immune-related genes were downloaded from the Immunology Database and Analysis Portal (ImmPort). Pearson correlation analysis was performed to identify immune-related lncRNAs. The TCGA TSCC patient cohort was randomly divided into training and testing cohorts. In the training cohort, univariate and multivariate Cox regression analyses were used to determining key immune-related lncRNAs, which were then validated through Cox regression analysis, principal component analysis (PCA), and receiver operating characteristic (ROC) analysis in the testing cohort. Results: Six immune-related signature lncRNAs (MIR4713HG, AC104088.1, LINC00534, NAALADL2-AS2, AC083967.1, FNDC1-IT1) were found to have prognostic value in TSCC. Multivariate and univariate cox regression analyses showed that the risk score based on our six-lncRNA model, when compared to other clinicopathological factors (age, gender, stage, N, T), was an important indicator of survival rate. In addition, Kaplan–Meier survival analysis demonstrated significantly higher overall survival in the low-risk patient group than the high-risk patient group within both training and testing cohorts. The ROC analysis indicated that the AUCs for 5-year overall survival were 0.790, 0.691, and 0.721, respectively, for training, testing, and entire cohorts. Finally, PCA analysis demonstrated that the high-risk and low-risk patient groups presented significant deviation regarding their immune status. Conclusions: A prognostic model based on six immune-related signature lncRNAs was established. This six-lncRNA prognostic model has clinical significance and may be helpful in the development of personalized immunotherapy strategies.
Numerical simulation of shallow water equations and related models

This thesis is devoted to the numerical approximation of the shallow water equations and of some related models. In the first part, we analyze the mathematical properties and the applications of the staggered grid scheme. The robustness of this scheme is validated on various applications such as the rotating shallow water equations for geostrophic flows model and viscous shallow water equations. In the second part, we consider some related models. Firstly focusing on the coupling between the Exner equation and the shallow water equations, modelling bedload sediment transport, we observe in a particular case the numerical convergence of the scheme to the exact solution, as well as a good agreement with the experimental data in the dam-break with erodible bottom test. Secondly, we present a numerical scheme based on the finite volume collocated scheme (HLLC) in order to approximate the Richard-Gavrilyuk model. This model is an extension of the shallow water model, fit for modelling the shear shallow water flows. Some numerical tests provide a validation of the scheme
Economics of deficit irrigation utilizing soil moisture probes in the western corn belt

Abstract Effective irrigation management is critical for future food supplies and the prosperity of producers engaged in irrigation production. Through a deficit irrigation field experiment, we determine the financial impact on producers caused by changing irrigation costs, corn prices, extreme weather events, and restricting irrigation levels. Results suggest that the optimal economic strategy within our constrained optimization model is to fully irrigate, with the economic impact highly dependent on commodity prices, restriction level, and irrigation costs. The greatest economic losses caused by irrigation restrictions come from decreases in yield. Some simulations resulted in negative profits, indicating that a switch to alternative crops requiring less irrigation may be warranted.
The local fractional bootstrap

We introduce a bootstrap procedure for high‐frequency statistics of Brownian semistationary processes. More specifically, we focus on a hypothesis test on the roughness of sample paths of Brownian semistationary processes, which uses an estimator based on a ratio of realized power variations. Our new resampling method, the local fractional bootstrap, relies on simulating an auxiliary fractional Brownian motion that mimics the fine properties of high‐frequency differences of the Brownian semistationary process under the null hypothesis. We prove the first‐order validity of the bootstrap method, and in simulations, we observe that the bootstrap‐based hypothesis test provides considerable finite‐sample improvements over an existing test that is based on a central limit theorem. This is important when studying the roughness properties of time series data. We illustrate this by applying the bootstrap method to two empirical data sets: We assess the roughness of a time series of high‐frequency asset prices and we test the validity of Kolmogorov's scaling law in atmospheric turbulence data.
The Leg Sensilla of Insects from Different Habitats—Comparison of Strictly Aquatic and Riparian Bugs (Corixidae, Ochteridae, Gelastocoridae: Nepomorpha: Insecta: Heteroptera)

Simple Summary Insects of the Nepomorpha infraorder live in various environments—some are associated strictly with water and some are mostly terrestrial. In this study, we examined specimens from the aquatic Corixidae and two riparian families—Ochteridae and Gelastocoridae. Apart from the differences in general leg morphology (legs adapted for swimming in Corixidae and for walking in Ochteroidea), there were eight types of sensilla found on the legs. From those, mechanosensilla displayed the most observed variability. The leg sensilla of Nepomorpha had not been studied until now. Abstract The aim of this study was to analyze morphological types and arrangement of the leg sensilla of Corixidae, Ochteridae and Gelastocoridae, in relation to their various habitats. The leg sensilla of four species of Corixidae, six of Gelastocoridae and two of Ochteridae were studied. Eight main types of sensilla with six subtypes of sensilla trichodea and four subtypes of sensilla chaetica were found and described. The greatest variability was observed among mechanoreceptive sensilla. The study showed differences in the shape of the legs between strictly aquatic and terrestrial taxa. It is the first attempt to describe leg sensilla among nepomorphan taxa.
Automatic generation of paragraph templates using a Textual Energy approach: - Applications in Literary Text production

In this paper, we present the results of preliminary experiments using the Textual Energy measure to be used in Automatic Text Generation tasks (ATG). Textual Energy calculates the similarity among the sentences of a document, using intuitive ideas coming from Mechanical statistical like the associative memories and the energy of a system. Using this approach we intend to generate a set of selected sentences having a semantic and structural coherence. In our experiment, the number of selected sentences was manually determined. In particular, the experiments were performed using sets of 4 sentences. Then, the selected sentences can be employed for paragraph generation using Canned Text-like techniques. We have performed an important number of experiments, and we found interesting results that we present in this paper. These results allow us to conclude that it is possible to generate a set of sentences, as paragraphs-like, through methods, avoiding as much as possible undesirable phenomena, such hallucination, which have been recently found in ATG models based on Deep learning Neural Networks.
Validity and Reliability of the activPAL4TM for Measurement of Body Postures and Stepping Activity in 6–12-Year-Old Children

A link between inappropriate physical behaviour patterns (low physical activity and high sedentary behaviour) and poor health outcomes has been observed. To provide evidence to quantify this link, it is important to have valid and reliable assessment tools. This study aimed to assess the validity and reliability of the activPAL4TM monitor for distinguishing postures and measuring stepping activity of 6–12-year-old children. Thirteen children (8.5 ± 1.8 years) engaged in pre-determined standardised (12 min) and non-standardised (6 min) activities. Agreement, specificity and positive predictive value were assessed between the activPAL4TM and direct observation (DO) (nearest 0.1 s). Between-activPAL4TM (inter-device) and between-observer (inter-rater) reliability were determined. Detection of sitting and stepping time and forward purposeful step count were all within 5% of DO. Standing time was slightly overestimated (+10%) and fast walking/jogging steps underestimated (−20%). For non-standardised activities, activPAL4TM step count matched most closely to combined backward and forward purposeful steps; however, agreement varied widely. The activPAL4TM demonstrated high levels of reliability (ICC(1, 1) > 0.976), which were higher in some instances than could be achieved through direct observation (ICC(2, 1) > 0.851 for non-standardised activities). Overall, the activPAL4TM recorded standardised activities well. However, further work is required to establish the exact nature of steps counted by the activPAL4TM.
Mathematical Modelling Of Ocean Waves

This study is concerned about finding simple solution techniques to determine the wave-wave interactions of four progressive waves travelling with four different wavenumbers and frequencies in a deep ocean. It has been demonstrated by many previous researchers including Phillips [6] and Hasselmann et.al [I] that this set of four waves, called a quadruplet, could exchange energy if they interact nonlinearly such that the resonance conditions are satisfied. In this paper, however, we shall be concerned with the approximate solutions of the nonlinear transfer action functions which satisfy a set of first order ordinary differential equations using the JONS WAP spectrum as the initial input condition. We will demonstrate three simple methods to compute the nonlinear transfer action functions within an infinitesimal interaction phase-space element Ak. The solutions by two analytical methods namely, Picard's iteration and Bernoulli's integrating factor methods are compared with those obtained by the fourth order Runge-Kutta numerical scheme. The comparison shows favourable agreement. In this paper, the complete solution of the nonlinear source function Sni has been avoided.
Dietary Supplements Containing Oat Beta-Glucan and/or Green Coffee (Poly)phenols Showed Limited Effect in Modulating Cardiometabolic Risk Biomarkers in Overweight/Obese Patients without a Lifestyle Intervention

Obesity has reached pandemic proportions and has become a major health concern worldwide. Therefore, it is necessary to find new strategies against this condition and its associated comorbidities. Green coffee polyphenols (GCP) and oat beta-glucans (BGs) have proven their hypolipidaemic and hypoglycaemic effects. This study aimed to examine the effects of the long-term consumption of supplements containing GCP, BG or the novel GCP/BG combination on lipid and glucose metabolism biomarkers in overweight/obese subjects who maintained their dietary habits and physical activity, hence addressing the difficulty that this population faces in adapting to lifestyle changes. A randomised, crossover, blind trial was carried out in 29 volunteers who consumed either GCP (300 mg), BG (2.5 g) or GCP/BG (300 mg + 2.5 g) twice a day for 8 weeks. Blood samples were collected, and blood pressure and body composition were measured at the beginning and end of each intervention. Total cholesterol, triglycerides, high-density lipoprotein (HDL-C), low-density lipoprotein (LDL-C), very low-density lipoprotein (VLDL-C) cholesterol, glycated haemoglobin, fasting glucose, insulin, aspartate transaminase, alanine transaminase and different hormones and adipokines were analysed. Only VLDL-C (p = 0.01) and diastolic blood pressure (p = 0.027) decreased after the intervention, especially with the BG supplement. There were no other significant changes in the analysed biomarkers. In conclusion, the regular intake of GCP, BG and GCP/BG without lifestyle changes is not an efficient strategy to improve lipid and glucose homeostasis in overweight/obese subjects.
Soil nutrients cause threefold increase in pathogen and herbivore impacts on grassland plant biomass

A combination of theory and experiments predicts that increasing soil nutrients will modify herbivore and microbial impacts on ecosystem carbon cycling. However, few studies of herbivores and soil nutrients have measured both ecosystem carbon fluxes and carbon pools. Even more rare are studies manipulating microbes and nutrients that look at ecosystem carbon cycling responses. We added nutrients to a long‐term, experiment manipulating foliar fungi, soil fungi, mammalian herbivores and arthropods in a low fertility grassland. We measured gross primary production (GPP), ecosystem respiration (ER), net ecosystem exchange (NEE) and plant biomass throughout the growing season to determine how nutrients modify consumer impacts on ecosystem carbon cycling. Nutrient addition increased above‐ground biomass and GPP, but not ER, resulting in an increase in ecosystem carbon uptake rate. Reducing foliar fungi and arthropods increased plant biomass. Nutrients amplified consumer effects on plant biomass, such that arthropods and foliar fungi had a threefold larger impact on above‐ground biomass in fertilized plots. Synthesis. Our work demonstrates that throughout the growing season soil resources modify carbon uptake rates as well as animal and fungal impacts on plant biomass production. Taken together, ongoing nutrient pollution may increase ecosystem carbon uptake and drive fungi and herbivores to have larger impacts on plant biomass production.
The computational complexity of the circuit value and network stability problems

This dissertation investigates the computational complexity of the Circuit Value problem and a new problem, Network Stability, when fanout is limited. In the Circuit Value problem, the task is to determine the output of an acyclic circuit of boolean gates. The Network Stability problem asks whether it is possible to assign values to the edges of a (possibly cyclic) network of boolean gates in a manner consistent with a given input assignment. Fanout is limited in a nontrivial way by allowing gates to have many outputs and then placing conditions on the different outputs produced by any single gate of the circuit or network. The fanout-limited versions of Circuit Value and Network Stability define new classes of problems between the standard Logarithmic-space and Polynomial-time complexity classes. The simplest of the new classes CC, contains natural complete problems, including Circuit Value for Comparator Circuits and the Stable Matching (Stable Marriage and Stable Roommates) problems. One offshoot of this research is a fruitful new approach to the Stable Matching problems. Several positive results emerge when fanout is appropriately limited, including a parallel algorithm for Circuit Value, a linear-time sequential algorithm for Network Stability, a characterization of the networks that lack consistent assignments of values to edges, and equivalence of Circuit Value and Network Stability under logarithmic-depth reductions.
Rosuvastatin Synergistically Enhances the Antinociceptive Efficacy of Duloxetine in Paclitaxel-Induced Neuropathic Pain in Mice

Paclitaxel, a widely used cancer chemotherapeutic agent, has high incidence of neurotoxicity associated with the production of neuropathic pain, for which only duloxetine has shown significant but moderate analgesic effect. Since statins, classically used to reduce hypercholesterolemia, have shown antinociceptive effect in preclinical studies on neuropathic pain, we studied whether the antinociceptive efficacy of duloxetine could be synergistically potentiated by rosuvastatin in a model of paclitaxel-induced neuropathy in mice. The astrocytic and microglial responses in the spinal cord of paclitaxel-treated mice were also assessed by measuring GFAP and CD11b proteins, respectively. Paclitaxel treatment did not impair motor coordination and balance in rotarod testing. Rosuvastatin, duloxetine, and the rosuvastatin/duloxetine combination (combined at equieffective doses) dose-dependently decreased mechanical allodynia (ED30, von Frey testing) and thermal hyperalgesia (ED50, hot plate testing) in paclitaxel-treated mice. Isobolographic analysis showed a superadditive interaction for rosuvastatin and duloxetine, as both the ED30 and ED50 for the rosuvastatin/duloxetine combination contained only a quarter of each drug compared to the individual drugs. The rosuvastatin/duloxetine combination reversed paclitaxel-induced GFAP overexpression, indicating that such effects might depend in part on astrocyte inactivation. Results suggest that statins could be useful in synergistically enhancing the efficacy of duloxetine in some chemotherapy-induced neuropathic conditions.
Postpartum Hemorrhage and Tranexamic Acid: A Literature Review

This review aims to explore the postpartum hemorrhage (PPH) burden and the efficacy of prophylactic tranexamic acid (TXA) in PPH and recent indications of TXA. A comprehensive review of the literature was conducted using a combination of Medical Subject Headings keywords including “Postpartum haemorrhage,” “Tranexamic acid,” and “Cesarean section. ” PPH has been explored for epidemiology, risk factors, and pathophysiology in the first part of the article. Recent indications of TXA, obstetric indications, and the role of TXA as prophylaxis for PPH are discussed in the second part of this article. TXA has many indications apart from obstetric indications and shows a significant effect in controlling bleeding. Furthermore, TXA is more efficient in preventing PPH if administered during the final stage of labor and is a valuable option for managing obstetric bleeding.