Miracle-dz/UniFAR-FTUs huggingface dataset:
Dependence of the Casimir–Polder interaction between an atom and a cavity wall on atomic and material properties

The Casimir–Polder and van der Waals interactions between an atom and a flat cavity wall are investigated under the influence of real conditions including the dynamic polarizability of the atom, actual conductivity of the wall material and nonzero temperature of the wall. The cases of different atoms near metal and dielectric walls are considered. It is shown that to obtain accurate results for the atom–wall interaction at short separations, one should use the complete tabulated optical data for the complex refractive index of the wall material and the accurate dynamic polarizability of an atom. At relatively large separations in the case of a metal wall, one may use the plasma model dielectric function to describe the dielectric properties of the wall material. The obtained results are important for the theoretical interpretation of experiments on quantum reflection and Bose–Einstein condensation.
Role of Herbal Extracts of Catechu from Uncaria gambir in the Treatment of Chronic Diabetic Wounds

Catechu is a dried decoction from twigs with the leaves of Uncaria gambir. Its antioxidant, anti-inflammatory, and antimicrobial activities have been previously reported because of its high catechin and epicatechin content (>21%). It is also one of the components used in traditional Chinese herbal medicine, “Jinchuang Ointment,” which has excellent efficacy in treating chronic diabetic wounds. An in vivo zebrafish embryo platform and an in vitro cell-based tube formation assay were used to measure the angiogenic activity of catechu extracts. Interestingly, for the first time, catechu extracts stimulated angiogenic activity on both platforms. The expression of the IL-8 gene was induced in HMEC1 cells after treatment with catechu extracts for 1 h only. In contrast, the upregulation of FGFR2, FGFR3, NF-κB, STAT3, and vimentin persisted for 24 h. A summary of the possible mechanisms underlying the angiogenic activity of catechu extracts in HMEC1 cells is shown. Unexpectedly, catechu extracts inhibited the migration of HaCaT cells. These results can account for the intense blood flow flux in porcine excisional wound sites in our previous studies, which provides insights into the therapeutic activity of catechu extract in chronic diabetic wounds.
The Saffman–Taylor instability: From the linear to the circular geometry

The Saffman–Taylor fingers are studied in cells that have the form of sectors of a disk. The less viscous fluid can be injected at the apex (divergent flow) or at the periphery (convergent flow). As in the linear geometry, at large velocities, a unique finger tends to occupy a well determined fraction λ of the cell angular width. This fraction is a function of the angle of the cell, being larger than 0.5 in the divergent case and smaller in the convergent case. In both cases these fractions tend linearly toward λ=0.5 when the angle of the cell tends to zero. In support of recent theories, these results show how the selection is changed when the geometry induces an increase or a decrease of the curvature of the profiles. The formation of fingers in the circular geometry is revisited. In a divergent flow, the circular front appears to break into independent parts so that each finger grows as if it were contained in a sector shaped cell. The rate of occupancy of the cell by one of the fluids as a function of the distance to the center is then discussed. Finally, the existence of the mathematical counterpart to the well‐known Saffman–Taylor finger solutions in a nonparallel cell is discussed in the Appendix.
Finite p-Groups and Centralizers of Noncentral Elements

Let G be a finite p-group. If |CG(x): ⟨ x ⟩ | ≤pk for every noncentral element x of G, then G is called a k − 𝒩𝒞 −p-group. In this article, we give a classification of k − 𝒩𝒞 −p-groups, where k = 1, 2 and p > 2.
Human Adenovirus Gene Expression and Replication Is Regulated through Dynamic Changes in Nucleoprotein Structure throughout Infection

Human adenovirus (HAdV) is extremely common and can rapidly spread in confined populations such as daycare centers, hospitals, and retirement homes. Although HAdV usually causes only minor illness in otherwise healthy patients, HAdV can cause significant morbidity and mortality in certain populations, such as the very young, very old, or immunocompromised individuals. During infection, the viral DNA undergoes dramatic changes in nucleoprotein structure that promote the rapid expression of viral genes, replication of the DNA, and generation of thousands of new infectious virions—each process requiring a distinct complement of virus and host-encoded proteins. In this review, we summarize our current understanding of the nucleoprotein structure of HAdV DNA during the various phases of infection, the cellular proteins implicated in mediating these changes, and the role of epigenetics in HAdV gene expression and replication.
Robust Analysis of Generalized Linear Mixed Models

The method of maximum likelihood (ML) is widely used for analyzing generalized linear mixed models (GLMM's). A full maximum likelihood analysis requires numerical integration techniques for calculation of the log-likelihood, and to avoid the computational problems involving irreducibly high-dimensional integrals, several maximum likelihood algorithms have been proposed in the literature to estimate the model parameters by approximating the log-likelihood function. Although these likelihood algorithms are useful for fitting the GLMM's efficiently under strict model assumptions, they can be highly influenced by the presence of unusual data points. In this article, the author develops a technique for finding robust maximum likelihood (RML) estimates of the model parameters in GLMM's, which appears to be useful in downweighting the influential data points when estimating the parameters. The asymptotic properties of the robust estimators are investigated under some regularity conditions. Small simulations are carried out to study the behavior of the robust estimates in the presence of outliers, and these estimates are also compared to the ordinary classical estimates. To avoid the computational problems involving high-dimensional integrals, the author proposes a robust Monte Carlo Newton–Raphson (RMCNR) algorithm for fitting GLMM's. The proposed robust method is illustrated in an analysis of data from a clinical experiment described in a biometrical journal.
An electropalatographic description of Putonghua fricatives and affricates

AbstractLingual-palatal contact patterns for the Putonghua fricatives and affricates (/s/,/s/,/c/,/z/,/ts/,/tsh/,/ts/,/tsh/,/tz/,/tzh/) are described, using electropalatography. The alveolar, and alveolo–palatal placement of the fricatives and affricates is confirmed by visual inspection of the EPG traces, and by the Centre of Gravity Indices. The placement of the plosive component of the affricate is governed by the fricative component. The Putonghua /s/ resembles the English /s/ and the Cantonese /s/ resembles the Putonghua /c/. These data can be used as a template for speech therapy for Putonghua speakers with speech disorders.
Taking a ‘Toll’ on Skin: A novel TLR9-deficient Model of Cutaneous Lupus

Endosomal Toll-like receptors (TLRs), TLR7 and TLR9 have been implicated in the pathogenesis of systemic lupus erythematosus (SLE). However, their role in cutaneous lupus (CL) is not well established, in part due to lack of appropriate mouse models for CL. We developed a novel murine model of CL that depends on T cell recognition of an ovalbumin (OVA) peptide on MHC class II+ cells and closely mimics human CL. These mice develop epidermal hyperplasia associated with mononuclear interface dermatitis and IgG deposition at the dermal-epidermal border within 4 weeks of administration of “pseudo-alloantigen” (OVA)-specific DO11 T cells. Importantly, cutaneous disease is entirely dependent on expression of TLR7 and the loss of TLR9. TLR9KO recipients have fewer DO11 Tregs, more germinal center B cells and more plasma cells than TLR9-sufficient recipients. They make autoantibodies specific for Ro52, a common self-reactivity in human CL. Additional clinical manifestations include extensive accumulation of IFNγ-producing DO11 T cells, elevated class II expression by keratinocytes (KC) and epidermal dendritic cells and extensive KC death. Preliminary data point to a mechanistic role of FasL in KC death that presumably drives skin lesions in this model. Intriguingly, radiation chimeras identify a critical role for radio-resistant TLR9KO cells in the development of cutaneous lesions in this model, suggesting a role for KC or Langerhans cell expression of TLR9 in constraining the development of CL. Our model thus provides a novel, rapid and reproducible system for investigating the opposing roles of TLR9 in CL and SLE. Findings from this study will have important applications in designing TLR-targeting molecules as therapeutic agents for CL.
Minimal positive 2-spanning sets of vectors

Let (vl, . . ., v,) be a sequence in an m-dimensional vector space V over an ordered field such that, for each i, {vj:j # i) positively spans V. It is shown that if (vl, . . ., v,,) is minimal with this property, then f4m if m 5 and all cases are determined in which n = 4m, m < 4. An application to convex polytopes is given.
Origin of defect emission identified by polarized luminescence from aligned ZnO nanorods

It is found that both of the band-edge and defect emission from aligned ZnO nanorods are strongly polarized, and the intensities vary with the polarization angle by the relation of a square cosine function. The intensity of the UV emission has its maximum along the c axis of a ZnO crystal. However, the intensity of the green emission is minimum in this direction. Namely, the two intensity curves are 90° out of phase. This unique characteristic of the polarization provides useful information to identify the fact that the green emission mostly occurs on the surface defects of the nanorods. This result is consistent with the currently accepted model that the green emission arises from the recombination between holes trapped at the surface defects and electrons trapped at the oxygen vacancy.
An alternative subspace approach to EEG dipole source localization

In the present study, we investigate a new approach to electroencephalography (EEG) three-dimensional (3D) dipole source localization by using a non-recursive subspace algorithm called FINES. In estimating source dipole locations, the present approach employs projections onto a subspace spanned by a small set of particular vectors (FINES vector set) in the estimated noise-only subspace instead of the entire estimated noise-only subspace in the case of classic MUSIC. The subspace spanned by this vector set is, in the sense of principal angle, closest to the subspace spanned by the array manifold associated with a particular brain region. By incorporating knowledge of the array manifold in identifying FINES vector sets in the estimated noise-only subspace for different brain regions, the present approach is able to estimate sources with enhanced accuracy and spatial resolution, thus enhancing the capability of resolving closely spaced sources and reducing estimation errors. The present computer simulations show, in EEG 3D dipole source localization, that compared to classic MUSIC, FINES has (1) better resolvability of two closely spaced dipolar sources and (2) better estimation accuracy of source locations. In comparison with RAP-MUSIC, FINES' performance is also better for the cases studied when the noise level is high and/or correlations among dipole sources exist.
Lithium Separation from Geothermal Brine to Develop Critical Energy Resources Using High-Pressure Nanofiltration Technology: Characterization and Optimization

There is a shift from internal combustion engines to electric vehicles (EVs), with the primary goal of reducing CO2 emissions from road transport. Battery technology is at the heart of this transition as it is vital to hybrid and fully electric vehicles’ performance, affordability, and reliability. However, it is not abundant in nature. Lithium has many uses, one of which is heat transfer applications; synthesized as an alloying agent for batteries, glass, and ceramics, it therefore has a high demand on the global market. Lithium can be attained by extraction from other natural resources in igneous rocks, in the waters of mineral springs, and geothermal brine. During the research, geothermal brine was used because, from the technological point of view, geothermal brine contains higher lithium content than other resources such as seawater. The nanofiltration separation process was operated using various solutions of pH 5, 7, and 10 at high pressures. The varying pressures are 11, 13, and 15 bar. The nanofiltration method was used as the separation process. High pressure of inert nitrogen gas was used to supply the driving force to separate lithium from other ions and elements in the sample. The research results supported the selected parameters where higher pressure and pH provided more significant lithium recovery but were limited by concentration polarization. The optimal operating conditions for lithium recovery in this research were obtained at a pH of 10 under a pressure of 15 bar, with the highest lithium recovery reaching more than 75%.
Large DM AO systems: synthetic IM or calibration on sky?

Several designs of future Adaptive Optics (AO) systems propose to use a large Deformable Mirror (DM), regarding the size as well as the number of actuators. Most of the time, there is no focal plane upstream the DM. Therefore, the classical way of calibrating the interaction matrix on an artificial source cannot be applied. Furthermore, the requirements in terms of calibration error budget are tight and the high order modes of such DMs are stiff and hence they achieve only a small stroke. This is why novel ways to determine the system Interaction Matrix (IM) have to be investigated. Several paths have been studied. One solution would be to simulate a synthetic IM. However, calibration on sky is also an option. Different techniques were simulated, tested and optimized on real AO systems. The results are presented in this paper.
Cardiac Magnetic Resonance Image Segmentation Method Based on Multi-Scale Feature Fusion and Sequence Relationship Learning

Accurate segmentation of the left atrial structure using magnetic resonance images provides an important basis for the diagnosis of atrial fibrillation (AF) and its treatment using robotic surgery. In this study, an image segmentation method based on sequence relationship learning and multi-scale feature fusion is proposed for 3D to 2D sequence conversion in cardiac magnetic resonance images and the varying scales of left atrial structures within different slices. Firstly, a convolutional neural network layer with an attention module was designed to extract and fuse contextual information at different scales in the image, to strengthen the target features using the correlation between features in different regions within the image, and to improve the network’s ability to distinguish the left atrial structure. Secondly, a recurrent neural network layer oriented to two-dimensional images was designed to capture the correlation of left atrial structures in adjacent slices by simulating the continuous relationship between sequential image slices. Finally, a combined loss function was constructed to reduce the effect of positive and negative sample imbalance and improve model stability. The Dice, IoU, and Hausdorff distance values reached 90.73%, 89.37%, and 4.803 mm, respectively, based on the LASC2013 (left atrial segmentation challenge in 2013) dataset; the corresponding values reached 92.05%, 89.41% and 9.056 mm, respectively, based on the ASC2018 (atrial segmentation challenge at 2018) dataset.
A PASSIVE DIAGNOSTIC EXPERIMENT WITH ERGODIC PROPERTIES

Abstract During the elaboration of vibration condition monitoring procedures for critical machinery one has to apply the so-called passive diagnostic experiment. To model such an experiment, either as a set of units, or as one unit several stages of operation and or repair cycles, one can consider the respective machines as energy processors. With the theory of the ergodic equivalence of observation, it can be concluded that both considerations lead to the same results, taking into account the possible realisations of the logistic vector. Using the simulation, it is possible to show that the symptom models used in vibration condition monitoring, for condition recognition and prediction, can be in most cases limited to Weibull and Frechet models.
Selfish-Aware and Learning-Aided Computation Offloading for Edge–Cloud Collaboration Network

Mobile-edge computing (MEC) raises the problem of selfish user devices that utilize less computing resources than expected to execute offloading tasks or maliciously discard computation tasks. However, most of the existing work either focused on the task offloading or concentrated on the trust mechanism in MEC systems. By jointly considering the two challenges, in this article, we propose a selfish-aware and learning-aided computation offloading scheme for edge–cloud collaboration network. Specifically, we first design a selfishness evaluation mechanism to evaluate the selfishness of the user devices based on the historical interaction records of the edge–cloud collaboration network. Then, we construct the task offloading model which introduces the selfishness evaluation mechanism to suppress the selfish user devices. On this basis, we further formalize the selfish-aware task offloading as an optimization problem of the weighted sum of time latency and energy consumption. Thereafter, we take one step further formalizing the optimization problem as a Markov decision process (MDP) and design a task offloading algorithm based on deep reinforcement learning (DRL) to find the optimized task offloading decision. The simulation results demonstrate that our work can decrease the time latency and energy consumption as well as suppress the selfish user devices.
Alfalfa Xeno-miR168b Target CPT1A to Regulate Milk Fat Synthesis in Bovine Mammary Epithelial Cells

It was shown that microRNAs (miRNAs) play an important role in the synthesis of milk fat; thus, this manuscript evaluated whether exogenous miRNA (xeno-miRNAs) from alfalfa could influence the milk fat content in dairy cows. At first, mtr-miR168b was screened from dairy cow milk and blood. Then, EdU staining, flow cytometry, Oil Red O staining, qRT-PCR, and WB were applied to explore the effect of xeno-miR168b on the proliferation, apoptosis, and lipid metabolism of bovine mammary epithelial cells (BMECs). Finally, in order to clarify the pathway that regulated the lipid metabolism of BMECs using xeno-miR168b, a double-luciferase reporter assay was used to verify the target gene related to milk fat. These results showed that overexpression of xeno-miR168b inhibited cell proliferation but promoted apoptosis, which also decreased the expression of several lipid metabolism genes, including PPARγ, SCD1, C/EBPβ, and SREBP1, significantly inhibited lipid droplet formation, and reduced triglyceride content in BMECs. Furthermore, the targeting relationship between CPT1A and xeno-miR168b was determined and it was confirmed that CPT1A silencing reduced the expression of lipid metabolism genes and inhibited fat accumulation in BMECs. These findings identified xeno-miR168b from alfalfa as a cross-kingdom regulatory element that could influence milk fat content in dairy cows by modulating CPT1A expression.
THE RELATIONSHIPS BETWEEN MORPHOLOGICAL TYPE AND QUANTITATIVE MEASURES IN THE CLUSTER ENVIRONMENT

The relationships between morphological types in both the Hubble-Sandage system and the RDDO system and quantitative measurements of the integrated properties are investigated for a sample of cluster spirals. The parameters measured are integrated color, integrated H I content, position in the color-gas content relation, and 20% velocity width. It is found that there are significant differences between these parameters in the mean as a function of morphological type as well as large scatter within morphological class and conspicuous overlap between various types. It is also shown that the same differences are a strong function of visually estimated disk-to-bulge ratio (D/B). It is suggested that analysis of the physical properties of a spiral galaxy be based on quantitative measurements, rather than on the morphological type of that galaxy.
Associations between Primary Healthcare Experiences and Glycemic Control Status in Patients with Diabetes: Results from the Greater Bay Area Study, China

Primary healthcare (PHC) plays an important role in diabetes management; community health centers (CHCs) serve as the main providers of PHC. However, few studies have discussed the association between the service quality of PHC and the effects of diabetes management. In this study, we explored the associations between experiences of PHC in CHCs and glycemic control status in patients with diabetes mellitus. This study was conducted in six CHCs in the Greater Bay Area of China. In total, 418 patients with diabetes mellitus (44% males and 56% females) were recruited between August and October 2019. We evaluated their PHC experiences using the Primary Care Assessment Tool (PCAT) developed by Johns Hopkins and assessed their glycemic control status by measuring their fasting plasma glucose levels. Binary logistic regression analyses were conducted to assess the associations between the patients’ PHC experiences and glycemic control status, adjusting for covariates. The patients with good glycemic control had significantly higher total and dimensional PCAT scores compared with those with poor glycemic control (p < 0.05). Higher PCAT scores were significantly associated with a greater adjusted odds ratios (aORs) of good glycemic control for total and dimensional PCAT scores. For example, compared to those with poor glycemic control, the aORs for those with good glycemic control was 8.82 (95% CI = 4.38–17.76) per total PCAT score increasing. Especially, the aORs for those with good glycemic control were 3.92 (95% CI = 2.38–6.44) and 4.73 (95% CI = 2.73–8.20) per dimensional PCAT score of family-centeredness and community orientation increasing, respectively. Better PHC experiences were associated with better diabetes management. In particular, family-centered and community-oriented CHCs may help improve diabetes management in China and other low- and middle-income countries.
Individual theta-band cortical entrainment to speech in quiet predicts word-in-noise comprehension

Abstract Speech elicits brain activity time-locked to its amplitude envelope. The resulting speech-brain synchrony (SBS) is thought to be crucial to speech parsing and comprehension. It has been shown that higher speech-brain coherence is associated with increased speech intelligibility. However, studies depending on the experimental manipulation of speech stimuli do not allow conclusion about the causality of the observed tracking. Here, we investigate whether individual differences in the intrinsic propensity to track the speech envelope when listening to speech-in-quiet is predictive of individual differences in speech-recognition-in-noise, in an independent task. We evaluated the cerebral tracking of speech in source-localized magnetoencephalography, at timescales corresponding to the phrases, words, syllables and phonemes. We found that individual differences in syllabic tracking in right superior temporal gyrus and in left middle temporal gyrus (MTG) were positively associated with recognition accuracy in an independent words-in-noise task. Furthermore, directed connectivity analysis showed that this relationship is partially mediated by top-down connectivity from premotor cortex—associated with speech processing and active sensing in the auditory domain—to left MTG. Thus, the extent of SBS—even during clear speech—reflects an active mechanism of the speech processing system that may confer resilience to noise.