Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecuaci´ on De Gross-Pitaevskii Usando El Esquema Crank-Nicholson Gross-Pitaevskii Equation Using The Crank-Nicholson Scheme

We present the application of finite difference method to solve the Gross-Pitaevskii equation in one dimension and timedependent. The solution method used is called Crank-Nicholson, which is inherently stable, and also explicitly unitary. It is Explore the dynamics of the equation only taking into account the nonlinear term.
IMAGE COMPRESSION BASED ON BIORTHOGONAL WAVELET TRANSFORM

A common approach to the color image compression was started by transform the red, green, and blue or (RGB) color model to a desire color model, then applying compression techniques, and finally retransform the results into RGB model. In this paper, a low complexity and efficient coding scheme based on Biorthogonal tab3/5 wavelet filter is proposed. The proposed system consists of the color transform YCbCr, followed by Wavelet (Tab3/5) transform, uniform quantization using Pyramid Quantization, modified Bit map Slicing coding method, and finally Huffman coding to produce the final bit stream. The efficiency performance of the suggested image encoding methods has been evaluated by making comparisons between them and corresponding compression results obtained by applying the compression standard JPEG and JPEG2000.
Nonstandard Set Theory

Infinitely small and infinitely large quantities were systematically introduced into mathematics with the invention of calculus by Newton and Leibniz. The use of such quantities, however, was accompanied by logical contradictions, which mathematicians of the seventeenth and eighteenth centuries were unable to resolve. Although the method of infinitesimals generally yielded correct results, no one ever succeeded in formulating a precise, noncontradictory set of rules governing these objects; and infinitesimal quantities were gradually displaced (at least, in pure mathematics) by the familiar e-d calculus. A mathematically sound model of infinitely small and infinitely large objects became possible only after advances in mathematical logic in the twentieth century. Nonstandard Analysis, developed by A. Robinson in 1960, not only provided foundations for the calculus of infinitesimals in the classical spirit but also enabled mathematicians to use "nonstandard" objects in ways that could not be attempted on the basis of vague, intuitive understanding alone. Since then, interesting applications were found in various branches of mathematics, mathematical physics, and economics. Robinson's exposition in [10] and its subsequent simplifications unfortunately involve the cumbersome apparatus of mathematical logic. Our aim here is to present methods of Nonstandard Analysis at a level of formalism customary in other branches of mathematics. We view nonstandard objects as ideal, imaginary elements adjoined to the universe of the standard mathematics and formulate a few simple and reasonably intuitive principles governing their behavior. We then show, on examples selected to illustrate a variety of nonstandard constructions, how nonstandard mathematics can be developed from these principles. The basic framework for Nonstandard Analysis is presented in ? 1-3; this system was introduced in [3], where its relative consistency with respect to the Zermelo-Fraenkel set theory is shown. We examine the real line and some concepts of general topology from our point of view in ? 4-5; these results can be found in Robinson [10] and Luxemburg [7], [8]. Section 6 is devoted to nonstandard measure theory; our approach is basically that of Loeb [6] (except that we construct Loeb's extension in Theorem 3 of ? 6 directly, rather than using Caratheodory's Theorem), with some ideas coming from Anderson [1]. The final ? 7, part I, contains a more formal description of the logical foundations, and parts II and III discuss the relationship between our approach and the classical one based on higher-order nonstandard models, as well as some other axiomatizations of Nonstandard Analysis.
Arresting the surface oxidation kinetics of bilayer 1T′-MoTe2 by sulphur passivation

MoTe2 garnered much attention among 2D materials due to stable polymorphs with distinctive structural and electronic properties. Among the polymorphs, 1T′-MoTe2 in bulk form is type—II Weyl semimetal while, in monolayer form is a quantum spin Hall insulator. Thus, it is suitable for a wide variety of applications. Nevertheless, 1T′-MoTe2 degrades within a few hours when exposed to the atmosphere and causes hindrances in device fabrication. Here the degradation kinetics of CVD-synthesized 1T′-MoTe2 was investigated using Raman spectroscopy, XPS, and microscopic characterizations. The degradation rate of as-grown 1T′-MoTe2 obtained was 9.2 × 10−3 min−1. Further, we prevented the degradation of 1T′-MoTe2 by introducing a thin coating of S that encapsulates the flakes. 1T′-MoTe2 flakes showed stability for several days when covered using sulphur, indicating 25 times enhanced structural stability.
Correlated event-by-event fluctuations of flow harmonics in Pb-Pb collisions at √sNN=2.76 TeV

Adam , J , Brucken , E J , Chang , B , Kim , D J , Mieskolainen , M M , Orava , R , Rak , J , Räsänen , S S , Saarinen , S , Slupecki , M , Snellman , T W , Trzaska , W H , Vargyas , M , Viinikainen , J & The ALICE Collaboration 2016 , ' Correlated Event-by-Event Fluctuations of Flow Harmonics in Pb-Pb Collisions at root S-NN=2.76 TeV ' Physical Review Letters , vol. 117 , no. 18 , 182301 . https://doi.org/10.1103/PhysRevLett.117. 182301
Optimization of Chondrocyte Viability in Partially Decellularized Tracheal Grafts

Objective. Advancements in tissue-engineered tracheal replacement (TETR) show promise for the use of partially decellularized tracheal grafts (PDTG) to address critical gaps in airway management and reconstruction. In this study, aiming to leverage the immunoprivileged nature of cartilage to preserve tracheal biomechanics, we optimize PDTG for retention of native chondrocytes. Study Design. Comparison in vivo murine study. Setting. Research Institute affiliated with Tertiary Pediatric Hospital. Methods. PDTG were created per a shortened decellularization protocol using sodium dodecyl sulfate, then biobanked via cryopreservation technique. Decellularization efficiency was characterized by DNA assay and histology. Viability and apoptosis of chondrocytes in preimplanted PDTG and biobanked native trachea (control) was assessed with live/dead and apoptosis assays. PDTG (N = 5) and native trachea (N = 6) were orthotopically implanted in syngeneic recipients for 1-month. At the endpoint, microcomputed tomography (micro-CT) was employed to interrogate graft patency and radiodensity in vivo. Vascularization and epithelialization were qualitatively analyzed using histology images following explant. Results. PDTG exhibited complete decellularization of all extra-cartilaginous cells and reduced DNA content compared to control. Chondrocyte viability and nonapoptotic cell populations were improved utilizing biobanking and shorter decellularization time. All grafts remained patent. Evaluation of graft radiodensity at 1 month revealed elevation of Hounsfield units in both PDTG and native compared to host, with PDTG showing higher radiodensity than native. PDTG supported complete epithelialization and functional reendothelialization 1-month postimplantation. Conclusion. Optimizing PDTG chondrocyte viability is a key component to successful tracheal replacement. Ongoing research seeks to evaluate the acute and chronic immunogenicity of PDTG.
The Effects of Nature-Based Travel in Virtual Reality: The Role of Spatial Presence and Narrative Engagement

The benefits of nature tourism, or nature-based travel, are plentiful. For example, participation in nature tours has positively impacted environmental attitudes and behaviors. Unfortunately, while psychologically beneficial, nature-based tourism can hurt the environment through a myriad of factors. Therefore, we must continue to explore ways to make the benefits of nature-based travel more sustainable and impactful. Research suggests that nature-based travel in virtual reality (VR) may impart numerous travel benefits, such as improving conservational behavior and interconnectedness with nature. While these early findings are promising, questions remain regarding the theoretical mechanisms underlying the effects of nature-based VR travel. Therefore, this study explores how VR may provide an avenue to make nature tourism more environmentally friendly while simultaneously making people more environmentally connected and conscious. Furthermore, a theoretical framework is posited that combines concepts from the spatial presence and narrative persuasion literature to help explain the effects. To accomplish these goals, an experiment was conducted using a two-condition (VR travel vs. TV control) between-subjects factorial design with random assignment. The participants were 66 college students from a large Midwestern University in the United States. Results indicated that there wasn't a statistically significant difference between the VR travel condition and the television (TV) control condition regarding the environmental outcome variables. However, while the nature-based VR travel experience did not appear to influence the environmental outcome variables directly, it did indirectly affect them through the mediating roles of spatial presence and narrative engagement.
Thinking Beyond COVID-19: How Has the Pandemic Impacted Future Time Horizons?

Older age is reportedly protective against the detrimental psychological impacts of the COVID-19 pandemic, consistent with the theory that reduced future time extension (FTE) leads to prioritization of socioemotional well-being. We investigated whether depression severity and pandemic-related factors (regional severity, threat, social isolation) reduce FTE beyond chronological age and whether these relationships differ between younger and older adults. In May 2020, we recruited 248 adults (younger: 18–43 years, older: 55–80 years) from 13 industrialized nations. Multigroup path analysis found that depression severity was a better predictor of FTE than the reverse association in both age groups, suggesting an affective foreshortening of future time. In both age groups, older age was protective against depression severity, and younger age was associated with heightened vulnerability to the negative impacts of pandemic-related factors. Future research should consider the complex interrelationships between FTE, age, and depression severity and the potential impacts of the broader psychosocial milieu.
Die Kanalkapazität als Grenze für die Digitalsignalübertragung

Le calcul de la capacite du canal de Shannon est considere dans des conditions variees telles que: limitation puissance de pente, puissance moyenne du signal transmis, frequence dependante et independante du canal; bruit blanc et colore. Discussion de point de vue de la transmission numerique
Co-circulation of multiple genotypes of ARV in poultry in Anhui, China

ABSTRACT Poultry production in China has been experiencing a high incidence of broiler arthritis /tenosynovitis caused by avian orthoreovirus (ARV) since 2013. In the spring of 2020 severe arthritis cases from broiler flocks were identified in a large-scale commercial poultry company in Anhui Province, China. Diseased organs from dead birds were sent for diagnosis to our laboratory. ARVs, including seven broiler-isolates and two breeder-isolates, were successfully harvested and sequenced. Interestingly, the genotypes of ARVs isolated from infected chickens were inconsistent between different flocks, or even between different houses on the same flocks. Pathogenicity testing in chicks confirmed that the seven broiler-isolates were pathogenic strains, which could cause arthritis in infected chickens. Subsequently, a total of 89.66% serum samples collected from apparently healthy adult broiler flocks not vaccinated against ARV tested positive for ARV antibodies, suggesting that low and high virulence reovirus strains may be co-circulating in the farm. To this end, we collected dead embryos of unhatched chicken eggs for pathogen tracing, and the two ARV breeder-isolates isolated indicated that vertical transmission from breeders to progeny should not be underestimated for the prevalence of ARV within broiler flocks. The findings have implications for the evidenced-based formulation of prevention and control strategies.
Machine learning in computational histopathology: Challenges and opportunities

Digital histopathological images, high‐resolution images of stained tissue samples, are a vital tool for clinicians to diagnose and stage cancers. The visual analysis of patient state based on these images are an important part of oncology workflow. Although pathology workflows have historically been conducted in laboratories under a microscope, the increasing digitization of histopathological images has led to their analysis on computers in the clinic. The last decade has seen the emergence of machine learning, and deep learning in particular, a powerful set of tools for the analysis of histopathological images. Machine learning models trained on large datasets of digitized histopathology slides have resulted in automated models for prediction and stratification of patient risk. In this review, we provide context for the rise of such models in computational histopathology, highlight the clinical tasks they have found success in automating, discuss the various machine learning techniques that have been applied to this domain, and underscore open problems and opportunities.
The Non Linear Field Theories Of Mechanics

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Multidimensional analysis of immune cells from COVID-19 patients identified cell subsets associated with the severity at hospital admission

Background SARS-CoV-2 emerged as a new coronavirus causing COVID-19, and it has been responsible for more than 760 million cases and 6.8 million deaths worldwide until March 2023. Although infected individuals could be asymptomatic, other patients presented heterogeneity and a wide range of symptoms. Therefore, identifying those infected individuals and being able to classify them according to their expected severity could help target health efforts more effectively. Methodology/Principal findings Therefore, we wanted to develop a machine learning model to predict those who will develop severe disease at the moment of hospital admission. We recruited 75 individuals and analysed innate and adaptive immune system subsets by flow cytometry. Also, we collected clinical and biochemical information. The objective of the study was to leverage machine learning techniques to identify clinical features associated with disease severity progression. Additionally, the study sought to elucidate the specific cellular subsets involved in the disease following the onset of symptoms. Among the several machine learning models tested, we found that the Elastic Net model was the better to predict the severity score according to a modified WHO classification. This model was able to predict the severity score of 72 out of 75 individuals. Besides, all the machine learning models revealed that CD38+ Treg and CD16+ CD56neg HLA-DR+ NK cells were highly correlated with the severity. Conclusions/Significance The Elastic Net model could stratify the uninfected individuals and the COVID-19 patients from asymptomatic to severe COVID-19 patients. On the other hand, these cellular subsets presented here could help to understand better the induction and progression of the symptoms in COVID-19 individuals.
Feasibility of an observational procedure to enhance early identification of autism spectrum disorder in paediatric settings: A mixed-methods study on an Ecuadorian sample

Identification procedures for autism spectrum disorders in paediatric settings include screening and routine clinical surveillance. Screening tools are perceived as challenging, and a preference for direct observation has been reported in Ecuadorian paediatric settings. Augmentative observational procedures could prompt the application of screening tools, increase professionals’ sense of self-efficacy and support referral decision-making. Following the recommendations that identification procedures should be tested in a group of children without autism from local populations, we tested a set of observational tasks on 125 children from 12 to 59 months of age in various socio-economic settings, in semi-experimental conditions and on a group of 33 non-autistic children in a paediatric-setting condition. Results indicated that the social referencing task did not produce the expected response in most children in semi-experimental conditions. Responses to the elicitation of a gesture were significantly influenced by socio-economic status and geographic area. Three other tested tasks (response to name, eye contact, response to joint attention) produced the expected responses in semi-experimental and clinical conditions, suggesting that they could be used in daily routines if fidelity to training is ensured. We discuss the implication of those findings in clinical practice and professional education in an Ecuadorian context. Lay abstract In Ecuador, the low official estimate of the number of persons with autism spectrum disorder suggest that many children are not identified and are not receiving support. Screening tools are short parent-addressed questionnaires used to identify children that may be developing with autism. Their use is recommended, but their application can be perceived as challenging in paediatric routines. Some professionals prefer looking for autism-related behaviours in a child rather than using screening questionnaires. Although a short observation does not replace the use of validated screening questionnaires, tasks to guide the observation of autistic early signs can help professionals decide to screen or refer the family for assessment and early intervention. In this study, we tested observational tasks that could be adapted to the Ecuadorian paediatric contexts.
NARROWING THE GAP: PRECLINICAL TRAUMA WITH POSTINJURY SEPSIS MODEL WITH INCREASED CLINICAL RELEVANCE

ABSTRACT Background: Overall outcomes for trauma patients have improved over time. However, mortality for postinjury sepsis is unchanged. The use of relevant preclinical studies remains necessary to understand mechanistic changes after injury and sepsis at the cellular and molecular level. We hypothesized that a preclinical rodent model of multicompartmental injury with postinjury pneumonia and chronic stress would replicate inflammation and organ injury similar to trauma patients in the intensive care unit. Methods: Male and proestrus female Sprague-Dawley rats (n = 16/group) were subjected to either polytrauma (PT) (lung contusion, hemorrhagic shock, cecectomy, and bifemoral pseudofracture), PT with daily chronic restraint stress (PT/CS), PT with postinjury day one Pseudomonas pneumonia (PT + PNA), PT/CS with pneumonia (PT/CS + PNA) or naive controls. Weight, white blood cell count, plasma toll-like receptor 4 (TLR4), urine norepinephrine (NE), hemoglobin, serum creatinine, and bilateral lung histology were evaluated. Results: PT + PNA and PT/CS + PNA groups lost more weight compared with those without sepsis (PT, PT/CS) and naive rats (P < 0.03). Similarly, both PT + PNA and PT/CS + PNA had increased leukocytosis and plasma TLR4 compared with uninfected counterparts. Urine NE was elevated in PT + PNA and PT/CS + PNA compared with naive (P < 0.03), with PT/CS + PNA exhibiting the highest levels. PT/CS + PNA exhibited worse acute kidney injury with elevated serum creatinine compared with PT/CS (P = 0.008). PT/CS + PNA right and left lung injury scores were worse than PT + PNA (P < 0.01). Conclusions: Sepsis, with postinjury pneumonia, induced significant systemic inflammation, organ dysfunction following polytrauma and chronic stress. Advanced animal models that replicate the critically ill human condition will help overcome the classic limitations of previous experimental models and enhance their translational value.
Delaunay refinement mesh generation of curve-bounded domains

Delaunay refinement is a mesh generation paradigm noted for offering theoretical guarantees regarding the quality of its output. As such, the meshes it produces are a good choice for numerical methods. This thesis studies the practical application of Delaunay refinement mesh generation to geometric domains whose boundaries are curved, in both two and three dimensions. It is subdivided into three manuscripts, each of them addressing a specific problem or a previous limitation of the method. The first manuscript is concerned with the problem in two dimensions. It proposes a technique to sample the boundary with the objective of improving its recoverability. The treatment of small input angles is also improved. The quality guarantees offered by previous algorithms are shown to apply in the presence of curves. The second manuscript presents an algorithm to construct constrained Delaunay tetrahedralizations of domains bounded by piecewise smooth surfaces. The boundary conforming meshes thus obtained are typically coarser than those output by other algorithms. These meshes are a perfect starting point for the experimental study presented in the final manuscript. Therein, Delaunay refinement is shown to eliminate slivers when run using non-standard quality measures, albeit without termination guarantees. The combined results of the last two manuscripts are a major stepping stone towards combining Delaunay refinement mesh generation with CAD modelers. Some algorithms presented in this thesis have already found application in high-order finitevolume methods. These algorithms have the potential to dramatically reduce the computational time needed for numerical simulations.
The trichotomy of HER2 expression confers new insights into the understanding and managing for breast cancer stratified by HER2 status

Human epidermal growth factor receptor 2 (HER2) is a tyrosine kinase receptor that plays a carcinogenic role in breast cancer (BC) through gene amplification, mutation, or overexpression. Traditional methods of HER2 detection were divided into positive (immunohistochemistry (IHC) 3+/fluorescence in situ hybridization (FISH) amplification) and negative (IHC 2+/FISH−, IHC 1+, IHC 0) according to the dichotomy method. Anti‐HER2‐targeted therapies, such as trastuzumab and pertuzumab, have significantly improved the prognosis of HER2‐positive patients. However, up to 75% to 85% of patients remain HER2‐negative. In recent years, with the rapid development of molecular biology, gene detection technology, targeted therapy, and immunotherapy, researchers have actively explored the clinicopathological characteristics, molecular biological characteristics, treatment methods, and HER2 detection methods of HER2‐low/zero breast cancer. With the clinical efficacy of new anti‐HER2 targeted drugs, accurate classification of breast cancer is very important for the treatment choice. Therefore, the following review summarizes the necessity of developing HER2 detection methods, and the clinicopathological and drug treatment characteristics of patients with HER2‐low/zero, to light the dawn of the treatment of breast cancer patients with HER2‐low/zero expression.