Miracle-dz/UniFAR-FTUs huggingface dataset:
Infrared properties of forced magnetohydrodynamic turbulence

The dynamical renormalisation group (RG) is implemented to study the large-scale properties of incompressible conducting fluid stirred by random forces and currents. In contrast with Navier-Stokes turbulence, invariance properties and dimensional constraints do not always prescribe the renormalisation of the couplings. In dimensions d>dc approximately=2.8, the system displays two non-trivial regimes: a kinetic regime where the renormalisation of the transport coefficients is due to the kinetic small scales, and a magnetic regime where it is due to the magnetic small scales. The results for the magnetic regime are not identical with predictions from the direct interaction approximation; this is due to vertex renormalisation of the Lorentz force. In dimensions 2<or=d<or=dc, with sufficiently strong external currents, there is no stable fixed point: runaway of the figurative point occurs, making the RG approach self-defeating. In two dimensions, with weak forces and currents, the absolute equilibrium results of Fyfe and Montgomery (1976) are recovered.
Multiplicative-interaction logit models for i×j×2 three-way tables

Multiplicative-interaction (M-I) logit models are proposed for three-way IxJx2 contingency tables where the third variable constitutes a binary response. Models are derived by assigning unknown scores to the categories and forming product interactions from them. Asymptotic results under special sampling constraints are derived for maximum likelihood estimates and the goodness-of-fit statistics. The class of models proposed in this paper are found to be useful when no obvious scores are available. An example is included.
Spinal Metastasis Causing Dropped Head Syndrome in the Chiropractic Office: A Case Report

Dropped head syndrome is a rare disorder involving an inability to hold the head upright. It may be caused by a variety of neuromuscular disorders and occasionally by pathological vertebral fractures. A 79-year-old man presented to a chiropractor with a two-year history of gradual-onset chin-on-chest posture and increased thoracic kyphosis, which had failed to respond to physical therapy. The chiropractor ordered whole spine computed tomography which revealed extensive mixed lytic and sclerotic changes and multiple thoracic compression fractures suggestive of metastasis. The chiropractor promptly referred the patient to an oncologist, who performed a biopsy confirming prostate adenocarcinoma. The patient’s health deteriorated, and he expired three weeks later. This case highlights that chiropractors should be aware that patients may present to their office with symptoms related to undiagnosed cancer, such as spinal deformity and dropped head syndrome. Chiropractors should order advanced imaging when patients have red flag signs or symptoms (e.g., older age, progressive symptoms despite care) and refer to an oncologist when clinical features or testing are suggestive of metastasis.
Advancing Stroke Research on Cerebral Thrombi with Omic Technologies

Cerebrovascular diseases represent a leading cause of disability, morbidity, and death worldwide. In the last decade, the advances in endovascular procedures have not only improved acute ischemic stroke care but also conceded a thorough analysis of patients’ thrombi. Although early anatomopathological and immunohistochemical analyses have provided valuable insights into thrombus composition and its correlation with radiological features, response to reperfusion therapies, and stroke etiology, these results have been inconclusive so far. Recent studies applied single- or multi-omic approaches—such as proteomics, metabolomics, transcriptomics, or a combination of these—to investigate clot composition and stroke mechanisms, showing high predictive power. Particularly, one pilot studies showed that combined deep phenotyping of stroke thrombi may be superior to classic clinical predictors in defining stroke mechanisms. Small sample sizes, varying methodologies, and lack of adjustments for potential confounders still represent roadblocks to generalizing these findings. However, these techniques hold the potential to better investigate stroke-related thrombogenesis and select secondary prevention strategies, and to prompt the discovery of novel biomarkers and therapeutic targets. In this review, we summarize the most recent findings, overview current strengths and limitations, and present future perspectives in the field.
CRISPR-Cas9-Mediated Mutation of Methyltransferase METTL4 Results in Embryonic Defects in Silkworm Bombyx mori

DNA N6-methyladenine (6mA) has recently been found to play regulatory roles in gene expression that links to various biological processes in eukaryotic species. The functional identification of 6mA methyltransferase will be important for understanding the underlying molecular mechanism of epigenetic 6mA methylation. It has been reported that the methyltransferase METTL4 can catalyze the methylation of 6mA; however, the function of METTL4 remains largely unknown. In this study, we aim to investigate the role of the Bombyx mori homolog METTL4 (BmMETTL4) in silkworm, a lepidopteran model insect. By using CRISPR-Cas9 system, we somatically mutated BmMETTL4 in silkworm individuates and found that disruption of BmMETTL4 caused the developmental defect of late silkworm embryo and subsequent lethality. We performed RNA-Seq and identified that there were 3192 differentially expressed genes in BmMETTL4 mutant including 1743 up-regulated and 1449 down-regulated. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that genes involved in molecular structure, chitin binding, and serine hydrolase activity were significantly affected by BmMETTL4 mutation. We further found that the expression of cuticular protein genes and collagens were clearly decreased while collagenases were highly increased, which had great contributions to the abnormal embryo and decreased hatchability of silkworm. Taken together, these results demonstrated a critical role of 6mA methyltransferase BmMETTL4 in regulating embryonic development of silkworm.
Double‐trace deformations and SL(2,Z) action on three‐dimensional CFTs

I discuss the connection between certain double‐trace deformations of three‐dimensional CFTs and a natural \documentclass{article}\pagestyle{empty}\usepackage{amssymb}\begin{document}$SL(2,\mathbb{Z})$\end{document} action on their two‐point functions that involve higher‐spin currents. I argue that this connection is a salient feature of the holography of Higher‐Spin gauge theories on AdS4.
Bayesian computation for the superposition of nonhomogeneous poisson processes

Bayesian inference for the superposition of nonhomogeneous Poisson processes is studied. A Markov‐chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, a latent variable is introduced that indicates which component of the superposition model gives rise to the failure. This data‐augmentation approach facilitates specification of the transitional kernel in the Markov chain. Moreover, new Bayesian tests are developed for the full superposition model against simpler submodels. Model determination by a predictive likelihood approach is studied. A numerical example based on a real data set is given.
Research on Multi-Sensor Fusion SLAM Algorithm Based on Improved Gmapping

Simultaneous Localization and Mapping (SLAM) is the core technology of the intelligent robot system, and it is also the basis for its autonomous movement. In recent years, it has been found that SLAM using a single sensor has certain limitations, such as Inertial Measurement Unit (IMU) noise and serious drift, and 2D radar can only detect environmental information on the same horizontal plane. In this regard, this paper constructs a multi-sensor back-end fusion SLAM algorithm that combines vision, laser, encoder and IMU information. Experiments have proved that compared with using a single sensor, the application of a multi-sensor fusion system makes the edges of the constructed map clearer and the noise reduced. Aiming at the problem of increased calculation caused by particle degradation and too many particles, this paper improves the Gmappping algorithm, and uses the combination of selective resampling and Kullback-Leibler Distance (KLD) sampling to complete resampling. It has been proved by experiments that compared with the original algorithm of Gmapping, the application of the improved algorithm increases the particle convergence speed by 39.85% in the process of indoor mapping. Aiming at the problems that the traditional loop detection algorithm is easily affected by environmental factors, resulting in low detection accuracy, and the loop detection algorithm based on deep convolutional neural network has a large amount of calculation and takes a long time to detect. The main research of this paper is to apply a deep learning-based loop detection algorithm on the multi-sensor fusion framework, and use the combination of high-dimensional and low-dimensional features of the image for loop detection. This paper uses different algorithms to conduct comparative experiments on the dataset CityCentre. The experimental results show that compared with the traditional algorithms Bag of Words (BoW), AlexNet algorithm, VGG19 algorithm, and ResNet32 algorithm, the accuracy of the algorithm proposed in this paper has increased by 31.26%, 14.21%, 3.05%, and 1.56%, respectively. In addition, the comparison experiment results of SLAM mapping with the original Real-Time Appearance-Based Mapping (RTAB-MAP) algorithm prove that the loop closure detection algorithm based on deep learning proposed in this paper can enable the system to better build a globally consistent map, including more environmental information.
Fast converging inverse lithography algorithm incorporating image gradient descent methods

In this paper, we develop an image-gradient-based algorithm to simultaneously optimize various cost functions for inverse mask design. The algorithm employs an iterative approach which evaluates the gradient decent of the resist image, aerial image, and the aerial image contrast with a pre-assigned step length. Moreover, an independent iteration step is inserted among iterations for binary mask conversion. We show that the proposed algorithm allows fast convergence while achieving high aerial image contrast. The impacts of each cost function on the pattern fidelity and convergence are also discussed.
Spatial autocorrelation, model selection and hypothesis testing in geographical ecology: Implications for testing metabolic theory in New World amphibians

In this paper, we stressed that avoiding significance tests under an alternative model selection framework does not mean that spatial autocorrelation no longer matters, since Akaike information criterion (AIC) is sensitive to the presence of spatial autocorrelation. We exemplify our discussion by analysing species richness patterns of American amphibians, in the context of metabolic theory, to understand how the presence of spatial autocorrelation in data affects data analysis under alternative frameworks of hypothesis testing and model selection. In general, temperature was found to be an important predictor of species richness in both frameworks, although particular predictions of metabolic theory were not fully satisfied when taking spatial autocorrelation into account.
Optimum Design of High-Temperature Steam Generator for Hydrogen Production Enhancement

In this study, an optimal design was proposed for the pressure drop of a high-temperature steam generator to enhance hydrogen production in a solid oxide electrolyzer cell (SOEC). The high-temperature steam generator (HTSG) was analyzed under experimental conditions of a steam temperature of 773 K, steam inlet pressure of 300–600 kPa, and steam flow rate of 10–35 kg/h. The pressure drop characteristics of the HTSG were analyzed under various variable conditions via a computational fluid dynamics simulation. The pressure drop according to the variable change was ranged from a minimum of 54 kPa (inlet nozzle angle: 25°) to a maximum of 309 kPa (body ratio: 0.63), and the valid range was 28,700 < Re < 306,600 . The hydrogen production capacity that can be produced utilizing the optimally designed HTSG was predicted to be up to 35.7 tons annually. In addition, CO2 emissions during hydrogen production under optimal conditions are 9.92 ton-CO2/ton-hydrogen, which can be reduced by up to 86.8% compared to the conventional high-temperature and high-pressure (HTHP) steam, thereby enhancing hydrogen production and energy harvesting.
Generating Admissible Heuristics by Criticizing Solutions to Relaxed Models

CUCS-119-85 This paper examines one paradigm used to develop admissible heuristics: problem relaxation [10, 11,32]. This consists of three steps: simplify (or relax) a problem, solve the simplified problem, and use that solution as advice to guide the search for a solution to the original problem. We introduce an extension to this methodology which exploits the simplicity of relaxed models. By criticizing the feasibility of a relaxed solution, we arrive at a closer approximation of the solution to the original problem. This solution-criticism process recovers some of the information lost by relaxation. and yields more powerful admissible heuristics than by relaxation alone. We apply our methodology to the TravelingSalesman problem and the N Puzzle. For the Traveling-Salesman Problem, it yields the well known. admissible minimum spanning tree heuristic. For the Eight and Fifteen Puzzles (in general the N puzzle), it yields a new heuristic which performs significantly better than all previously known heuristics.
Low-drive-voltage MQW electroabsorption modulator for optical short-pulse generation

This paper reports on InGaAsP-InGaAsP tensile strained MQW electroabsorption (EA) modulators with a high modulation efficiency of 35 GHz/V that generate optical short pulses. We studied and optimized the multiple-quantum-well (MQW) structural parameters, barrier height, and well number, thickness, and strain in the absorption layer to ensure high attenuation efficiency and generate low duty cycle pulses. Low TE/TM polarization sensitivity was obtained by controlling strain. Stable, nearly transform-limited optical pulse trains with a narrow pulsewidth of 3.6 ps are generated by applying a 20-GHz sinusoidal modulation voltage (6 V/sub pp/) to the EA modulator. This achieves a very small pulse duty cycle of 7.2%.
A Systematic Literature Review on Multimodal Machine Learning: Applications, Challenges, Gaps and Future Directions

Multimodal machine learning (MML) is a tempting multidisciplinary research area where heterogeneous data from multiple modalities and machine learning (ML) are combined to solve critical problems. Usually, research works use data from a single modality, such as images, audio, text, and signals. However, real-world issues have become critical now, and handling them using multiple modalities of data instead of a single modality can significantly impact finding solutions. ML algorithms play an essential role in tuning parameters in developing MML models. This paper reviews recent advancements in the challenges of MML, namely: representation, translation, alignment, fusion and co-learning, and presents the gaps and challenges. A systematic literature review (SLR) was applied to define the progress and trends on those challenges in the MML domain. In total, 1032 articles were examined in this review to extract features like source, domain, application, modality, etc. This research article will help researchers understand the constant state of MML and navigate the selection of future research directions.
Medium-Term Risk of Recurrent Pelvic Organ Prolapse within 2-Year Follow-Up after Laparoscopic Sacrocolpopexy

Objective: The present study was performed to determine the risk of recurrent pelvic organ prolapse (POP) within 2 years after laparoscopic sacrocolpopexy (LSC) in patients with uterovaginal prolapse. Materials and Methods: A retrospective comparative study was performed in a population of 204 patients over a 2-year follow-up period following LSC with concomitant supracervical hysterectomy or uterine preservation at a single urological clinic between 2015 and 2019. The primary outcome was surgical failure following LSC in cases of POP, focusing on failures occurring before the 2nd year of follow-up. Logistic regression analysis was used to determine the odds ratios (ORs) for surgical failure. Results: The primary outcome, surgical failure in cases of POP, occurred 2 years after the initial surgery in 19 of the 204 patients (9.3%) (95% confidence interval [CI], 5.7% – 14.2%). Surgical failure was most common in the anterior compartment (n = 10, 4.9%), and further surgery was performed in seven of the patients with surgical failure (3.4%). The poor primary outcome was predicted by lysis of adhesions (OR, 7.5, 95% CI, 1.6–33.8, P = 0.008) and preoperative POP stage IV (OR, 3.5; 95% CI, 1.1–10.8, P = 0.03) on multivariable logistic regression analysis. Conclusion: The overall rate of surgical failure following LSC in our cohort was 9.3% over the 2-year follow-up period after surgery, and preoperative prolapse stage IV was associated with a higher risk of recurrence.
Loss of SENP3 mediated the formation of nasal polyps in nasal mucosal inflammation by increasing alternative activated macrophage

Small ubiquitin–like modifier (SUMO)‐specific protease (SENP)3 is a protease molecule that responds to reactive oxygen species (ROS) with high sensitivity. However, the role of ROS and SENP3 in the formation of nasal polyps (NPs) remains unclear. This study aimed to explore how SENP3 influenced the outcome of chronic rhinosinusitis (CRS) by altering macrophage function, that is, the formation of NPs.
Follicular lymphoma: an update on biology and optimal therapy

Abstract Follicular lymphoma (FL) is a mature B-cell neoplasm with a mostly indolent course. Genetic hallmark characteristics are Bcl-2 overexpression based on a t(14;18) translocation and additional secondary genetic and epigenetic aberrations. Standard treatment for early-stage patients has curative intent and usually consists of radiotherapy with or without rituximab. In the advanced stage, the main therapeutic focus is on prolonged remissions. Therefore, treatment in asymptomatic patients is usually deferred. Symptomatic patients are subject to immunochemotherapy induction followed by antibody maintenance. Importantly, about one in five patients subsequently experiences a more rapid clinical course, achieving only short remissions with multiple relapses (POD24). In those patients, there is still an urgent need for improved therapeutic options. Accordingly, a plethora of targeted and immunotherapeutic options, including immunomodulatory drugs, small molecule inhibitors, monoclonal antibodies as well as bispecific T-cell engager antibodies and CAR-T cell products have been recently evaluated in such relapsed high-risk patients.
Genetic architecture of microhabitat adaptation traits in a pair of sympatric Primulina species

Abstract Exploring the genetic basis of adaptive divergence at fine spatial scales can broaden our basic understanding of evolution and how organisms may adapt to changing environments in the future. Cave-associated microhabitats provide a unique opportunity to gain insight into microgeographic adaptation. We studied the genetic architecture of microhabitat-related divergence in flower phenology and leaf traits between two sister species of Primulina, P. depressa and P. danxiaensis, which live in sympatry but occupy contrasting microhabitats. We identified 40 significant quantitative trait loci (QTLs) associated with the interspecific differences in these microhabitat adaptation traits. Flowering time was controlled by one major-effect and six minor-effect QTLs, while leaf traits were influenced by 9–12 QTLs of small to moderate effect. The genetic architecture of the flowering time and the specific leaf area was genetically independent of other traits. Our results suggest that microhabitat adaptation in sympatric populations of Primulina differs according to different traits, with leaf traits diverging with the accumulation of many small changes and flowering phenology being driven by major effect variance.
Integrated Computational Approaches for Inhibiting Sex Hormone-Binding Globulin in Male Infertility by Screening Potent Phytochemicals

Male infertility is significantly influenced by the plasma-protein sex hormone-binding globulin (SHBG). Male infertility, erectile dysfunction, prostate cancer, and several other male reproductive system diseases are all caused by reduced testosterone bioavailability due to its binding to SHBG. In this study, we have identified 345 phytochemicals from 200 literature reviews that potentially inhibit severe acute respiratory syndrome coronavirus 2. Only a few studies have been done using the SARS-CoV-2 inhibitors to identify the SHBG inhibitor, which is thought to be the main protein responsible for male infertility. In virtual-screening and molecular-docking experiments, cryptomisrine, dorsilurin E, and isoiguesterin were identified as potential SHBG inhibitors with binding affinities of −9.2, −9.0, and −8.8 kcal/mol, respectively. They were also found to have higher binding affinities than the control drug anastrozole (−7.0 kcal/mol). In addition to favorable pharmacological properties, these top three phytochemicals showed no adverse effects in pharmacokinetic evaluations. Several molecular dynamics simulation profiles’ root-mean-square deviation, radius of gyration, root-mean-square fluctuation, hydrogen bonds, and solvent-accessible surface area supported the top three protein–ligand complexes’ better firmness and stability than the control drug throughout the 100 ns simulation period. These combinatorial drug-design approaches indicate that these three phytochemicals could be developed as potential drugs to treat male infertility.
Experimental measurements of the global anisotropic elastic behaviour of dry Hostun sand during triaxial tests, and effect of sample preparation

Experimental measurements have been carried out with a new, accurate, triaxial device (Triaxial StaDy) to determine the quasi-elastic properties of dry Hostun sand. The experimental investigations consist in successively applying very small axial cyclic static loadings (strain single-amplitude cycle, esa ≈ 10–5 m/m) and four types of wave, generated by piezoelectric sensors (compressive and shear waves in the axial and radial directions), at different levels of the stress–strain curve. The use of both static and dynamic results allows for an entire description of the anisotropic elastic compliance tensor at a given stress–strain state to be made. The evolutions of this tensor during triaxial loading and unloading are presented. The isotropic and deviatoric triaxial stress paths considered underline the effects of inherent and induced anisotropy respectively. The different methods used to set the sample involve clearly different kinds of anisotropic elastic behaviour, which are probably indicators of diffe.