Miracle-dz/UniFAR-FTUs huggingface dataset:
Power Transformation Toward a Linear Regression Quantile

In this article we consider the linear quantile regression model with a power transformation on the dependent variable. Like the classical Box–Cox transformation approach, it extends the applicability of linear models without resorting to nonparametric smoothing, but transformations on the quantile models are more natural due to the equivariance property of the quantiles under monotone transformations. We propose an estimation procedure and establish its consistency and asymptotic normality under some regularity conditions. The objective function employed in the estimation can also be used to check inadequacy of a power-transformed linear quantile regression model and to obtain inference on the transformation parameter. The proposed approach is shown to be valuable through illustrative examples.
Double Dilation ≠ Double Mixing (extended abstract)

Density operators are one of the key ingredients of quantum theory. They can be constructed in two ways: via a convex sum of 'doubled kets' (i.e. mixing), and by tracing out part of a 'doubled' two-system ket (i.e. dilation). Both constructions can be iterated, yielding new mathematical species that have already found applications outside physics. However, as we show in this paper, the iterated constructions no longer yield the same mathematical species. Hence, the constructions 'mixing' and 'dilation' themselves are by no means equivalent. Concretely, when applying the Choi-Jamiolkowski isomorphism to the second iteration, dilation produces arbitrary symmetric bipartite states, while mixing only yields the disentangled ones. All results are proven using diagrams, and hence they hold not only for quantum theory, but also for a much more general class of process theories.
Anarchy Is What It Is Made Up Of: Reappraising Kenneth Waltz’s Grand Concept Through a Marxian Lens

In this article, I attempt to critically assess Kenneth Waltz’s deployment of the idea of anarchy to erect a ‘scientific theory of international politics’. First, I argue that the formation of a concept requires comprehension of the object from the standpoint of historical development, not a narrow reading of it. Second, I subject the thinner abstractions of self-help, balance of power and bandwagoning to the test of history. Third, I argue about mainstream international relations’ disdain for revolutions. I would posit that revolutions are fine templates which store rich agential history of structural transformation, a theme subject to much chagrin by realists of all hues, particularly neorealists. In doing so, I take the Bolshevik Revolution of 1917 as my benchmark. I elucidate that through the occlusion of first and second images, man and state, in the favour of third image, that is, structural anarchy, Waltz tends to ignore the role of agency as a conscious collective which could be best captured by the Bolshevik Revolution. In doing so, I rely on Perry Anderson’s three modes of agency in history. As a corrective to Waltz’s theorization, I make a strong case for class transcending both man and state as an organic category with immense potential of becoming a level of analysis which both acts upon the structure and refracts through it. I finally conclude by saying that anarchy was a condition and not a ‘social relation’ of any sort which could claim to constitute the ‘international’.
Analysis of the influence of car front wheel kingpin caster angle on steering trajectory based on bicycle model

The front wheel kingpin caster angle of cars is the inclination angle between the axis of the kingpin and the vertical line of the ground. It is one of the key points of the technical testing that affects the safety performance of automobiles, and it is also one of the key topics of today's research. Some researchers found that the front wheel kingpin caster angle has a certain influence on the car driving. However, there is still a research gap on its influence on the trajectory of the car when turning. Therefore, based on the establishment of the bicycle model, this paper analyzes the trajectory of the car return to alignment and explores the influence of front wheel kingpin caster angle on the steering stability under the condition that there is no human intervention in the car and the car's torque is solely used to bring the car back into alignment. The research found that the front wheel kingpin caster angle has a positive effect on the time and the rate of the car returning to alignment by affecting the aligning torque. When the front wheel kingpin caster angle increases, the trajectory line changes from a curve to a straight line more quickly after the turn is over. Because of this result, the research suggests that the car's front wheel kingpin caster angle can be appropriately increased to enhance the car’s rate of returning to alignment, thereby improving the steering stability of the car.
The symplectic approach of gauged linear $\sigma$-model

Witten's Gauged Linear $\sigma$-Model (GLSM) unifies the Gromov-Witten theory and the Landau-Ginzburg theory, and provides a global perspective on mirror symmetry. In this article, we summarize a mathematically rigorous construction of the GLSM in the geometric phase using methods from symplectic geometry.
Reverse orbifold construction and uniqueness of holomorphic vertex operator algebras

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Average information REML: An efficient algorithm for variance parameter estimation in linear mixed models

A strategy of using an average information matrix is shown to be computationally convenient and efficient for estimating variance components by restricted maximum likelihood (REML) in the mixed linear model. Three applications are described. The motivation for the algorithm was the estimation of variance components in the analysis of wheat variety means from 1,071 experiments representing 10 years and 60 locations in New South Wales. We also apply the algorithm to the analysis of designed experiments by incomplete block analysis and spatial analysis of field experiments.
Soft Computing Approach to Design a Triple-Band Slotted Microstrip Patch Antenna

The design process of antenna structures that meet up-to-date requirements takes a long time and brings a high computational load. In this paper, an approach based on Soft Computing (SC) techniques was used to shorten the design time and to achieve an antenna structure that yields performance characteristics as close as possible to the desired values. In order to obtain a microstrip patch antenna with the targeted characteristics and the best accuracy in a faster way, a Support Vector Machine (SVM)-based regression model was employed. A triple-band microstrip antenna with desired resonance frequencies and gain values was designed by using the Support Vector Regression (SVR) model by introducing multiple slots and arc-truncation to the patch antenna. Simulation results of the High-Frequency Structural Simulator (HFSS) and measurements of implementation of the designed antenna are given. Performance characteristics of the obtained antenna are also compared with those given in the literature, which have triple-band properties. In addition, the antenna was redesigned using the optimization tool in HFSS for comparison. The accuracy of the results and required time for design were compared for both the SVR model approach and the HFSS optimization tool.
Dynamics of Filamentous Viruses in Polyelectrolyte Solutions

: The structure and dynamics of polyelectrolytes differ from those of neutral polymers. How these differences affect the transport of anisotropic particles remains incompletely understood. Here, we investigate the transport of semiflexible M13 bacteriophage (phage) in aqueous semidilute solutions of sodium polystyrenesulfonate (PSS) with various ionic strengths using fluorescence microscopy. We tune the characteristic length scales of the PSS using two molecular weights of 68 and 2200 kDa and by varying the ionic strength of the solutions from 10 − 6 to 10 − 1 M. Phage exhibit diffusive dynamics across all polymer concentrations. For 2200 kDa PSS solutions, the phage dynamics monotonically deviate from the bulk prediction as polymer concentration increases and exhibit non-Gaussian distributions of displacements. Existing scaling theories can approximately collapse dynamics as a function of phage hydrodynamic radius to polymer size ratio R h / ξ onto a master curve across polymer concentrations and ionic strengths. This partial collapse, however, does not follow the prediction for diffusion of isotropic particles in flexible Gaussian chains, suggesting the presence of multiple diffusive modes due to the anisotropic structure of the phage and the confining length scales set by the structure and dynamics of charged polymers.
Advances in the Preparation of Nanofiber Dressings by Electrospinning for Promoting Diabetic Wound Healing

Chronic diabetic wounds are one of the main complications of diabetes, manifested by persistent inflammation, decreased epithelialization motility, and impaired wound healing. This will not only lead to the repeated hospitalization of patients, but also bear expensive hospitalization costs. In severe cases, it can lead to amputation, sepsis or death. Electrospun nanofibers membranes have the characteristics of high porosity, high specific surface area, and easy functionalization of structure, so they can be used as a safe and effective platform in the treatment of diabetic wounds and have great application potential. This article briefly reviewed the pathogenesis of chronic diabetic wounds and the types of dressings commonly used, and then reviewed the development of electrospinning technology in recent years and the advantages of electrospun nanofibers in the treatment of diabetic wounds. Finally, the reports of different types of nanofiber dressings on diabetic wounds are summarized, and the method of using multi-drug combination therapy in diabetic wounds is emphasized, which provides new ideas for the effective treatment of diabetic wounds.
Miniaturized Dual-Mode Star-Shaped Bandpass Filter with Spurious Suppression

Abstract A compact dual-mode resonator bandpass filter with harmonic suppression is presented. The filter is composed of a perturbed star-shaped resonator and defected ground structure units. The spurious suppression of the bandpass filter could be realized by controlling the dimension of the defected ground structure, which provides a low-pass characteristic. The star-shaped resonator offers a 37% size reduction compared to a conventional ring resonator operating at 2.5 GHz. Measured results agree well with the simulation ones.
Equilibrium paradigm for field-reversed configurations and application to experiments

Fresh insights on field-reversed configurations (FRCs) are incorporated in a new paradigm for equilibria. In particular four new or unappreciated properties are accounted for: an empirically based scrape-off layer thickness; a new, more accurate axial force balance relation; viscous force regularity at the O-point; and the broken-surface effect. The new paradigm corrects glaring defects of previous models (rigid rotor, Hill’s vortex). Further, the new paradigm is simple enough to be easily used as an interpretive tool despite the limited data suite in most experiments. It is applied to the newly enhanced FRC data compendium, a database of 69 records from 15 facilities. Several important observations and corrections on the previous understanding of FRCs follow, three of which stand out. (1) The traditional axial force balance (“average-β” relation) gives an inaccurate scaling with the separatrix-to-wall radius ratio. (2) The improved equilibrium paradigm yields separatrix particle transport rates of 3–5 m2.
Smith ideals of operadic algebras in monoidal model categories

Building upon Hovey's work on Smith ideals for monoids, we develop a homotopy theory of Smith ideals for general operads in a symmetric monoidal category. For a sufficiently nice stable monoidal model category and an operad satisfying a cofibrancy condition, we show that there is a Quillen equivalence between a model structure on Smith ideals and a model structure on algebra maps induced by the cokernel and the kernel. For symmetric spectra this applies to the commutative operad and all Sigma-cofibrant operads. For chain complexes over a field of characteristic zero and the stable module category, this Quillen equivalence holds for all operads.
miR-96-5p regulates myocardial infarction-induced cardiac fibrosis via Smad7/Smad3 pathway

Fibrotic remodelling contributes to heart failure in myocardial infarction. MicroRNAs (miRNAs) play a crucial role in myocardial fibrosis. However, current antifibrotic therapeutic strategies using miRNAs are far from effective. In this study, we aim to investigate the effect of miR-96-5p on cardiac fibrosis. Our work reveals a significant upregulation of miR-96-5p level in the ventricular tissues of myocardial infarction mice, as well as in neonatal rat cardiac fibroblasts stimulated with TGF-β or Ang II as shown by qPCR assay. In myocardial infarction mice, miR-96-5p knockdown using antagomir alleviates the aggravated cardiac fibrosis and exacerbated myocardial function caused by myocardial infarction surgery as shown by the echocardiography and Masson’s staining analysis. In contrast, immunofluorescence staining results reveal that miR-96-5p overexpression in neonatal rat cardiac fibroblasts contributes to an increase in the expressions of fibrosis-associated genes and promotes the proliferation and differentiation of cardiac fibroblasts. Conversely, miR-96-5p downregulation using inhibitor presents adverse consequences. Furthermore, Smad7 expression is downregulated in fibrotic cardiac tissues, and the Smad7 gene is identified as a direct target of miR-96-5p by dual luciferase assay. Indeed, Smad7 knockdown weakens the anti-fibrotic effect of the miR-96-5p inhibitor on cardiac fibroblasts. Moreover, Smad3 phosphorylation is elevated in fibrotic cardiac tissues, and interestingly, the Smad3 inhibitor suppresses the profibrotic effect of the miR-96-5p mimic. Taken together, our findings demonstrate that the Smad7/Smad3 signaling pathway mediates the profibrotic effect of miR-96-5p in cardiac fibrosis.
THE EFFECTIVE CONE OF MODULI SPACES OF SHEAVES ON A SMOOTH QUADRIC SURFACE

Let $\unicode[STIX]{x1D709}$ be a stable Chern character on $\mathbb{P}^{1}\times \mathbb{P}^{1}$ , and let $M(\unicode[STIX]{x1D709})$ be the moduli space of Gieseker semistable sheaves on $\mathbb{P}^{1}\times \mathbb{P}^{1}$ with Chern character $\unicode[STIX]{x1D709}$ . In this paper, we provide an approach to computing the effective cone of $M(\unicode[STIX]{x1D709})$ . We find Brill–Noether divisors spanning extremal rays of the effective cone using resolutions of the general elements of $M(\unicode[STIX]{x1D709})$ which are found using the machinery of exceptional bundles. We use this approach to provide many examples of extremal rays in these effective cones. In particular, we completely compute the effective cone of the first fifteen Hilbert schemes of points on $\mathbb{P}^{1}\times \mathbb{P}^{1}$ .
Machine learning optical proximity correction with generative adversarial networks

Abstract. Background Algorithmic breakthroughs in machine learning (ML) have allowed increasingly more applications developed for computational lithography, gradually shifting focus from hotspot detection to inverse lithography and optical proximity correction (OPC). We proposed a pixelated mask synthesis method utilizing deep-learning techniques, to generate after-development-inspection (ADI) contour and mask feature generation. Aim Conventional OPC correction consists of two parts, the simulation model which predicts the expected contour signal, and the correction script that modifies the actual layout. With practicality in mind, we collected modeling wafer data from scratch, then implemented ML models to reproduce conventional OPC actions, mask to contour prediction, and design to mask correction. Approach Two generative adversarial networks (GANs) were constructed, a pix2pix model was first trained to learn the correspondences between mask image and paired ADI contour image collected on wafer. The second model is embedded into machine learning mask correction (ML-OPC) framework, output mask is optimized through minimizing pixel difference between design target and simulated contour. Results Two different magnification SEM image datasets were collected and studied, with the higher magnification showing better simulator pixel accuracy. Supervised training of the correction model provided a quick prototype mask synthesis generator, and combination of unsupervised training allowed mask pattern synthetization from any given design layout. Conclusions The experimental results demonstrated that our ML-OPC framework was able to mimic conventional OPC model in producing exquisite mask patterns and contours. This ML-OPC framework could be implemented across full chip layout.
EFFECTIVENESS OF B3 WASTE MANAGEMENT OF CORONAVIRUS DISEASE 2019 (COVID-19) SELF-QUARANTINE

Patients who self-quarantine were carried out to break the chain from the spread of the COVID-19 virus, but a new problem arose: solid medical B3 waste originating from these patients. If this B3 medical waste is not managed properly, it can potentially transmit and be contaminated by infectious substances. Management of infectious waste from self-quarantine patients was minimal because most people did not know about it, and there was a lack of infrastructure from the government. Therefore the researchers were interested in researching the management of B3 waste, substantial B3 waste, from people who carried out Covid-19 self-quarantine. This study aimed to determine the community's effectiveness in managing solid medical B3 waste from COVID-19 self-quarantine activities. Using the snowball sampling method and cross-sectional design, the results showed that there was a significant relationship between Attitude (P Value = 0.000), Knowledge (P value = 0.006), Age (P Value = 0.019), Gender (P value = 0.000), Occupation (P value = 0.000) and Education (P value = 0.04) on community behavior in managing B3 medical waste during the Covid-19 self-quarantine period. Management of Solid B3 Medical Waste from self-quarantine has not been effective since its application is still low, and local drop boxes were not available as temporary shelters for B3 waste.
Effect of Nurse-Led Intervention on Headache Pain, Anxiety, and Fatigue Levels among Patients with Brain Tumors

Headache pain, anxiety, and Fatigue are recognized as one of the most common and distressing adverse effects among patients with brain tumors. Aim was to evaluate the effect of the nurse-led intervention on headache pain, anxiety, and fatigue level among patients with brain tumors. Subjects and method: Design: A quasi-experimental research design was used to fulfill the aim of this study. Setting: the research was conducted in the neurosurgery department at Mansoura University Hospital. Subjects : A purposive sample of 50 adult patients was included. Four tools were used: Tool (I) a structured interview questionnaire (II) a numerical pain rating scale, (III) a State-Trait Anxiety Inventory, and Tool (IV) a Fatigue assessment scale. Results : The current study revealed that there was a highly statistically significant difference and reductions in headache pain mean scores post-nurse-led intervention at (P= <0.05). Also, the study demonstrated that there was a highly statistically significant difference in anxiety scores post-nurse-led intervention with (P= <0.001). Highly statistically significant differences and reductions were detected between fatigue mean scores pre and post-nurse-led intervention with (P= <0.001) . Conclusion: The nurse-led intervention had a positive effect on headache pain, anxiety, and fatigue level among patients with brain tumors. Recommendations: The nurse-led intervention regarding brain tumors should be conducted, discussed, and integrated into the rehabilitation programs. Nurse-led intervention, Pain level, Patients with brain tumors.
Analysis of factors affecting riders injury severity in E-bike-motor vehicle collision accidents based on CIDAS data

To analyze influencing factors of rider injury severity in E-bike-motor vehicle collision accidents, we have analyzed 1,246 accidents in the China In-depth Accident Study (CIDAS) dataset using the Light Gradient Boosting Machine (LightGBM) model, which is used to further explore primary factors affecting the injury of riders. Experimental results show that severity of injury is highly correlated with traffic environment, characteristics of electric vehicles and riders. Meanwhile, we find that the throwing distance of riders has an obvious threshold effect on death, and accidents occurred outside urban areas are more likely to lead to death of riders. Finally, suggestions are made for the causes of accident injuries. This research is beneficial to the understanding of complex nonlinear relationships between accident injuries and influencing factors. The experimental results and analysis provide more guidelines to investigate injury prevention measures.