Miracle-dz/UniFAR-FTUs huggingface dataset:
EVOLUTION OF TRANSIENT LOW-MASS X-RAY BINARIES TO REDBACK MILLISECOND PULSARS

Redback millisecond pulsars (MSPs; hereafter redbacks) are a subpopulation of eclipsing MSPs in close binaries. The formation processes of these systems are not clear. The three pulsars showing transitions between rotation- and accretion-powered states belong to both redbacks and transient low-mass X-ray binaries (LMXBs), suggesting a possible evolutionary link between them. Through binary evolution calculations, we show that the accretion disks in almost all LMXBs are subject to the thermal-viscous instability during certain evolutionary stages, and the parameter space for the disk instability covers the distribution of known redbacks in the orbital period—companion mass plane. We accordingly suggest that the abrupt reduction of the mass accretion rate during quiescence of transient LMXBs provides a plausible way to switch on the pulsar activity, leading to the formation of redbacks, if the neutron star has been spun up to be an energetic MSP. We investigate the evolution of redbacks, taking into account the evaporation feedback, and discuss its possible influence on the formation of black widow MSPs.
Modified Multipath Transmission Control Protocol Using Logarithmic Increase Under Long-Term Evolution and Wi-Fi Networks

Multipath transmission control protocol (MPTCP) has been proposed for devices with multiple network interfaces. This idea seems to be impossible for user implementation at the beginning of its proposal. However, the emergence of smartphones with multiple network access allows this idea to be implemented. This paper provides both theoretical and empirical throughput analysis of MPTCP under long term evolution (LTE) and Wi-Fi networks. First, a new modified congestion control is presented as an enhancement of standard TCP Reno using logarithmic function. Second, the existing MPTCP approaches like linked increase algorithm (LIA) and balanced LIA (BALIA) are discussed briefly. Finally, the experimental results under long term evolution (LTE) and Wi-Fi under software defined wireless networking (SDWN) are given along with the analysis. The experimental result shows that the proposed congestion control achieves higher average congestion window size. The BALIA MPTCP is shown to have higher throughput than that of the LIA MPTCP.
Brain Vessel Segmentation Using Deep Learning—A Review

This article provides a comprehensive review of deep learning-based blood vessel segmentation of the brain. Cerebrovascular disease develops when blood arteries in the brain are compromised, resulting in severe brain injuries such as ischemic stroke, brain hemorrhages, and many more. Early detection enables patients to obtain more effective treatment before becoming critically unwell. Due to the superior efficiency and accuracy compared to manual segmentation and other computer-assisted diagnosis procedures, deep learning algorithms have been extensively deployed in brain vascular segmentation. This study examined current articles on deep learning-based brain vascular segmentation, which examined the proposed methodologies, particularly the network architectures, and determined the model trend. We evaluated challenges and crucial factors associated with the application of deep learning to brain vascular segmentation, as well as future research prospects. This paper will assist researchers in developing more sophisticated and robust models in the future to develop deep learning solutions.
Neoadjuvant PD-1 blockade plus chemotherapy induces a high pathological complete response rate and anti-tumor immune subsets in clinical stage III gastric cancer

ABSTRACT First-line PD-1 blockade plus chemotherapy significantly improves the survival benefits in late-stage gastric cancer (GC) patients. However, the pathological response rate and effects on the immune microenvironment of neoadjuvant PD-1 blockade plus chemotherapy in patients with cTNM-stage III GC remain to be elucidated. Patients with cTNM-stage III GC who underwent neoadjuvant PD-1 blockade plus chemotherapy and surgery were enrolled. Four in vivo models bearing GC were jointly established to investigate the specific roles of chemotherapy and PD-1 blockade for GC treatment. The tumor immune microenvironment was analyzed by hematoxylin and eosin (H&E) and IHC staining, multicolor flow cytometry and immunofluorescence. A total of 75 patients with cTNM-stage III (cT2-4N1-3M0) gastric cancer who received neoadjuvant PD-1 blockade plus chemotherapy (SOX/XELOX) were included in this study. After treatment, 21 (28.0%) and 57 (76.0%) patients achieved pathological complete response (pCR) and post-therapy pathological downstaging. Subgroup analyses revealed that patients with CPS >1 (32.6% vs 8.3%) and dMMR (35.7% vs 25.4%) subtype had better efficacy. Additionally, the resected specimens showed more anti-tumor immune infiltration indicating a response to neoadjuvant PD-1 blockade plus chemotherapy. Multicolor immunofluorescence and in vivo experiments on mouse models revealed that elevated M1/M2 ratio of macrophages, CD8 + T cells and plasma cells indicated effective response to treatment. Furthermore, neoadjuvant PD-1 blockade plus chemotherapy neither delayed surgery nor increased postoperative complication rate. The analyses indicate neoadjuvant PD-1 blockade plus chemotherapy is a promising therapeutic strategy in patients with cTNM-stage III GC with an encouraging pCR rate.
On the radius of habitable planets

Context. The conditions that a planet must fulfill to be habitable are not precisely known. However, it is comparatively easier to define conditions under which a planet is very likely not habitable. Finding such conditions is important as it can help select, in an ensemble of potentially observable planets, which ones should be observed in greater detail for characterization studies. Aims: Assuming, as in the Earth, that the presence of a C-cycle is a necessary condition for long-term habitability, we derive, as a function of the planetary mass, a radius above which a planet is likely not habitable. We compute the maximum radius a planet can have to fulfill two constraints: surface conditions compatible with the existence of liquid water, and no ice layer at the bottom of a putative global ocean. We demonstrate that, above a given radius, these two constraints cannot be met. Methods: We compute internal structure models of planets, using a five-layer model (core, inner mantle, outer mantle, ocean, and atmosphere), for different masses and composition of the planets (in particular, the Fe/Si ratio of the planet). Results: Our results show that for planets in the super-Earth mass range (1-12 M⊕), the maximum that a planet, with a composition similar to that of the Earth, can have varies between 1.7 and 2.2 R⊕. This radius is reduced when considering planets with higher Fe/Si ratios and taking radiation into account when computing the gas envelope structure. Conclusions: These results can be used to infer, from radius and mass determinations using high-precision transit observations like those that will soon be performed by the CHaracterizing ExOPlanet Satellite (CHEOPS), which planets are very likely not habitable, and therefore which ones should be considered as best targets for further habitability studies.
Adaptive state observation of linear time‐varying systems with delayed measurements and unknown parameters

In this article, we address the problem of adaptive state observation of linear time‐varying systems with delayed measurements and unknown parameters. Our new developments extend the results reported in our recently works. The case with known parameters has been studied by many researchers. However in this article we show that the generalized parameter estimation‐based observer design provides a very simple solution for the unknown parameter case. Moreover, when this observer design technique is combined with the dynamic regressor extension and mixing estimation procedure the estimated state and parameters converge in fixed‐time imposing extremely weak excitation assumptions.
Formalization of two Puzzles Involving Knowledge

This paper describes a formal system and uses it to express the puzzle of the three wise men and the puzzle of Mr. S and Mr. P. Four innovations in the axiomatization of knowledge were required: the ability to express joint knowledge of several people, the ability to express the initial non-knowledge, the ability to describe knowing what rather than merely knowing that, and the ability to express the change which occurs when someone learns something. Our axioms are written in first order logic and use Kripke-style possible worlds directly rather than modal operators or imitations thereof. We intend to use functions imitating modal operators and taking ``propositions'' and ``individual concepts'' as operands, but we haven't yet solved the problem of how to treat learning in such a formalism.
Ordered sets : proceedings of the NATO Advanced Study Institute held at Banff, Canada, August 28 to September 12, 1981

I. Structure and Arithmetic of Ordered Sets. - Arithmetic of ordered sets. - Exponentiation and duality. - The retract construction. - II. Linear Extensions. - Linear extensions of ordered sets. - Dimension theory for ordered sets. - Linear extensions of partial orders and the FKG inequality. - III. Set Theory and Recursion. - Order types of real numbers and other uncountable orderings. - On the cofinality of partially ordered sets. - Infinite ordered sets, a recursive perspective. - IV. Lattice Theory. - The role of order in lattice theory. - Some order theoretic questions about free lattices and free modular lattices. - An introduction to the theory of continuous lattices. - Ordered sets in geometry. - (Appendix: A lattice characterization of affine n-space). - Restructuring lattice theory: an approach based on hierarchies of concepts. - V. Enumeration. - Extremal problems in partially ordered sets. - Enumeration in classes of ordered structures. - The Mobius function of a partially ordered set. - An introduction to Cohen-Macaulay partially ordered sets. - VI. Applications of Ordered Sets to Computer Sciences. - Ordered sets and linear programming. - Machine scheduling with precedence constraints. - Some ordered sets in computer science. - VII. Applications of Ordered Sets to Social Sciences. - Ordered sets and social sciences. - Some social science applications of ordered sets. - VIII. Problem Sessions. - Order types. - Combinatorics. - Linear extensions of finite ordered sets. - Scheduling and sorting. - Graphs and enumeration. - Social science and operations research. - Recursion and game theory. - Order-preserving maps. - Lattices. - Miscellaneous. - IX. A Bibliography.
On Input Design for System Identification : Input Design Using Markov Chains

When system identification methods are used to construct mathematical models of real systems, it is important to collect data that reveal useful information about the systems dynamics. Experimental data are always corrupted by noise and this causes uncertainty in the model estimate. Therefore, design of input signals that guarantee a certain model accuracy is an important issue in system identification.This thesis studies input design problems for system identification where time domain constraints have to be considered. A finite Markov chain is used to model the input of the system. This allows to directly include input amplitude constraints into the input model, by properly choosing the state space of the Markov chain. The state space is defined so that the model generates a binary signal. The probability distribution of the Markov chain is shaped in order to minimize an objective function defined in the input design problem.Two identification issues are considered in this thesis: parameter estimation and NMP zeros estimation of linear systems. Stochastic approximation is needed to minimize the objective function in the parameter estimation problem, while an adaptive algorithm is used to consistently estimate NMP zeros.One of the main advantages of this approach is that the input signal can be easily generated by extracting samples from the designed optimal distribution. No spectral factorization techniques or realization algorithms are required to generate the input signal.Numerical examples show how these models can improve system identification with respect to other input realization techniques.
The Analysis of Groups

Exercise 0 Let f, g, h be functions on a group G and let x, y ∈ G. (i) Verify that f ∗(g∗h) = (f ∗g)∗h holds (as soon as all these sums are absolutely convergent). (ii) Compute δx ∗ δy, δx ∗ f and f ∗ δx. (iii) Find a formula for (f ∗ g)∨, where for any function h we write h∨(x) := h(x−1). (iv) Let 1 ≤ p ≤ ∞ and suppose f ∈ `(G), g ∈ `(G). Verify ‖g ∗ f‖p ≤ ‖f‖p · ‖g‖1. Deduce ‖f ∗ g‖p ≤ ‖f‖p · ‖g‖1. (You might want to separate the case p =∞.) (v) For f ∈ `(G), write Σf := ∑ x∈G f(x). Assuming f, g ∈ `(G), prove Σ(f ∗ g) = ΣfΣg. Deduce that f, g ∈ Prob(G) implies f ∗ g ∈ Prob(G).
THE VELOCITY FUNCTION OF DARK MATTER HALOS AT R = 20 kpc: REMARKABLY LITTLE EVOLUTION SINCE z ≈ 4

We investigate the evolution in the dark matter halo circular velocity function, measured at a fixed physical radius of 20 kpc (v20), which is likely to be a good proxy for galaxy circular velocity, in the Millennium-II simulation. We find that the v20 function evolves remarkably little since z ≈ 4. We analyze the histories of the main progenitors of halos, and we find that the dark matter distribution within the central 20 kpc of massive halos has been in place since early times. This provides evidence for the inside-out growth of halos. The constancy of the central circular velocity of halos may offer a natural explanation for the observational finding that the galaxy circular velocity is an excellent predictor of various galaxy properties. Our results also indicate that we can expect a significant number of galaxies with high circular velocities already at z = 4 (more than one per 106 h−3 Mpc3 with circular velocities in excess of 450 km s−1, and more than one per 104.5 h−3 Mpc3 with circular velocities in excess of 350 km s−1). Finally, adding baryonic mass and using a simple model for halo adiabatic contraction, we find remarkable agreement with the velocity-dispersion functions inferred observationally by Bezanson et al. up to z ≈ 1 and down to about 220 km s−1.
The Experiences of Practice Educator Facilitators and Academics Supporting Adult Nursing Students Completing a Paid Placement During the COVID-19

The first phase of the COVID-19 global pandemic had a significant impact on nursing students studying in the United Kingdom, heralding changes to every aspect of their lives. Practice Education Facilitators (PEFs) and academics had to respond quickly and work in close collaboration with their wider system partners, Health Education England (HEE) and the Department of Health (DH). Changes in emergency measures implemented by the Nursing and Midwifery Council (NMC) provided nursing students in their final six months of study with the opportunity of completing a paid placement. The objectives of this study were to explore the experiences of academics and PEFs supporting the nursing students and to identify examples of good practice. A phenomenological approach was used seeking to understand the lived experience of PEFs and academics within one case study site. A purposeful sample of ten participants was chosen using semi-structured interviews and focus groups to collect the data via a virtual platform. The results highlighted three themes: communication, innovative learning opportunities and the importance of support mechanisms. PEFs and academics reported how they had increased their competence and confidence in using virtual platforms. They suggested that changes they implemented during the pandemic to support staff and students would become embedded in their future practice. This study provides insights into how PEFs and academics transformed their practice to support students and clinicians during the COVID-19 pandemic. Having robust virtual platforms for the development of continuing learning opportunities and enhanced communication approaches across health and academic environments was essential to this success.
Evaluation of the Effects of R-CHOP Chemotherapy on Brain Glucose Metabolism in Patients with Diffuse Large B Cell Lymphoma: A Baseline, Interim, and End-of-Treatment PET/CT Study

Background: To investigate the effect of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) chemotherapy on brain glucose metabolism in patients with diffuse large B cell lymphoma (DLBCL). Methods: Seventy-two patients with newly diagnosed DLBCL underwent FDG PET/CT brain and whole-body scans at baseline (PET0), in the interim of chemotherapy (PET2), and at the end (PET6) of chemotherapy. All three brain scans of each patient were analyzed using statistical parametric mapping software. Results: Compared with the PET0 scan, the PET2 and PET6 scans revealed a significantly higher glucose metabolism throughout the whole brain, with the PET6 scan revealing a higher metabolism than the PET2 scan. Patients with a complete response (CR) displayed decreased glucose metabolism in the lingual gyrus and increased glucose metabolism in the pons after chemotherapy compared with the findings in patients with partial responses or progressive disease. Conclusions: Brain glucose metabolism was affected by R-CHOP treatment throughout the entire chemotherapy protocol.
An exploration of primary caregivers’ knowledge of dyslexia, awareness of the problems, and supports for elementary school children in Nigeria

Abstract Dyslexia is a lifelong disability that affects learning and social interaction in people of all ages, genders, and races all over the world. Yet, little is known about this condition in low- and middle-income countries. This study aims to investigate primary caregivers’ knowledge of dyslexia, their awareness of problems, and their support for elementary school children in Owerri Municipal, Nigeria. A qualitative descriptive design was utilized in this investigation, and 18 participants were invited to a single in-depth semi-structured interview. Thematic analysis was utilized in analyzing the data. Three themes and nine sub-themes emerged from the study. The result shows that participants lacked adequate knowledge of dyslexia, were aware of the effects of the condition and had adopted a variety of management and coping strategies. Participants’ support for children with dyslexia was found to be inadequate. The findings of this study have the potential to influence special education policy and programs in Nigeria, especially in the aspects of promoting social inclusion and the protection of the rights of students with special needs. The study recommends relooking at the National policy for special needs education in Nigeria to establish a more equitable and inclusive educational system.
Continuous opinion dynamics of multidimensional allocation problems under bounded confidence: More dimensions lead to better chances for consensus

We study multidimensional continuous opinion dynamics, where opinions are nonnegative vectors which components sum up to one. Examples of such opinions are budgets or other allocation vectors which display a distribution of a fixed amount of ressource to n projects. We use the opinion dynamics models of Deffuant-Weisbuch and Hegselmann-Krause, which both extend naturally to more dimensional opinions. They both rely on bounded confidence of the agents and differ in their communication regime. We show detailed simulation results regarding $n=2,. ,8$ and the bound of confidence $\eps$. Number, location and size of opinion clusters in the stabilized opinion profiles are of interest. Known differences of both models repeat under higher opinion dimensions: Higher number of clusters and more minor clusters in the Deffuant-Weisbuch model, meta-stable states in the Hegselmann-Krause model. But surprisingly, higher dimensions lead to better chances for a vast majority consensus even for lower bounds of confidence. On the other hand, the number of minority clusters rises with n, too.
Smart and Multi-Functional Magnetic Nanoparticles for Cancer Treatment Applications: Clinical Challenges and Future Prospects

Iron oxide nanoparticle (IONPs) have become a subject of interest in various biomedical fields due to their magnetism and biocompatibility. They can be utilized as heat mediators in magnetic hyperthermia (MHT) or as contrast media in magnetic resonance imaging (MRI), and ultrasound (US). In addition, their high drug-loading capacity enabled them to be therapeutic agent transporters for malignancy treatment. Hence, smartening them allows for an intelligent controlled drug release (CDR) and targeted drug delivery (TDD). Smart magnetic nanoparticles (SMNPs) can overcome the impediments faced by classical chemo-treatment strategies, since they can be navigated and release drug via external or internal stimuli. Recently, they have been synchronized with other modalities, e.g., MRI, MHT, US, and for dual/multimodal theranostic applications in a single platform. Herein, we provide an overview of the attributes of MNPs for cancer theranostic application, fabrication procedures, surface coatings, targeting approaches, and recent advancement of SMNPs. Even though MNPs feature numerous privileges over chemotherapy agents, obstacles remain in clinical usage. This review in particular covers the clinical predicaments faced by SMNPs and future research scopes in the field of SMNPs for cancer theranostics.
Electromagnetic shift arising from the Heisenberg-Euler dipole

We show that photons may be redshifted or blueshifted when interacting with the field of an overcritical dipole, which incorporates the one-loop QED corrections coming from vacuum polarization. Using the effective metric, it follows that such effect depends on the polarization of the photon. The shifts, plotted against the azimuthal angle for various values of the magnetic field, may show an intensity comparable to the gravitational redshift for a magnetar. To obtain these results, we have corrected previous literature.
Two‐invariant modular implicit plasticity solver framework for geomechanical simulators

A modular, computationally efficient integration framework for two‐invariant‐based elastoplastic constitutive models is proposed. It is designed to allow a range of constitutive models to be incorporated with minimal programming effort. The development is intended for efficient numerical schemes in large‐scale geomechanical simulations. The modular format consists of four components: isotropic elastic relation, isotropic yield criterion, two‐invariant smooth flow potential plastic flow rule and isotropic hardening law. Linear and non‐linear bulk elasticity are considered. For the non‐linear case, a numerical assessment of the accuracy of bulk elasticity integration schemes is presented, where pure Euler and semi‐analytical integrators are compared. The deviatoric component of the elastic law considers both the constant shear modulus and constant Poisson's ratio models. The combination of the classic Terzaghi compaction law with different bulk elasticity models may lead to a physical inconsistency, which is removed by a straightforward modification of the hardening law. When used in conjunction with the proposed bulk elasticity models, it results in a family of compaction laws that significantly reshape the normal compaction line – a fact that seems to have been overlooked in the literature. The main contributions concerning the plasticity integrator are: a novel integration scheme that considers the variation of specific volume within each step; and a condensed system comprising two scalar return‐mapping equations. A Modified Cam‐Clay (MCC) model is used in the assessments. A comparison with an existing, well‐known algorithm is also provided and, in spite of its modularity/generality, the proposed scheme is shown to yield significant computational gains.