Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Histone Deacetylases in Acute Lung Injury—Friend or Foe

Acute lung injury (ALI), caused by intrapulmonary or extrapulmonary factors such as pneumonia, shock, and sepsis, eventually disrupts the alveolar-capillary barrier, resulting in diffuse pulmonary oedema and microatasis, manifested by refractory hypoxemia, and respiratory distress. Not only is ALI highly lethal, but even if a patient survives, there are also multiple sequelae. Currently, there is no better treatment than supportive care, and we urgently need to find new targets to improve ALI. Histone deacetylases (HDACs) are epigenetically important enzymes that, together with histone acetylases (HATs), regulate the acetylation levels of histones and non-histones. While HDAC inhibitors (HDACis) play a therapeutic role in cancer, inflammatory, and neurodegenerative diseases, there is also a large body of evidence suggesting the potential of HDACs as therapeutic targets in ALI. This review explores the unique mechanisms of HDACs in different cell types of ALI, including macrophages, pulmonary vascular endothelial cells (VECs), alveolar epithelial cells (AECs), and neutrophils.
Determinants of goodwill: Empirical study from emerging economies

Goodwill is increasingly receiving the interest of investors, auditors and other users of financial statements, therefore the need for comprehensive information on this topic has grown over time. The aim of this article is to analyze the determinants of goodwill in companies from emerging economy countries. The research is structured in two stages. The first stage of the research consists of a bibliometric analysis of the literature that is focused on the goodwill topic. The second part of the research consists in building an econometric model in order to assess the determinants of goodwill based on data reported by firms in emerging economy countries in 2021, namely the data reported by 21,977 companies from 100 emerging economy countries, structured into 94 industries. The obtained results are represented by the development of an econometric model that shows the implications of net profit, Economic Value Added (EVA), Earnings before Interest, Taxes, Depreciation and Amortization (EBITDA) and of research and development (R&D) expenses on goodwill fluctuations and vice versa. The results of our research highlight the fact that goodwill fluctuation is generated by the fluctuation of net profit, EVA, EBITDA and less by the R&D expenses. This study adds value to the literature by treating the subject differently, analyzing and evaluating the relationship between net profit, EVA, EBITDA, R&D expenses and goodwill.
Fluid dynamics of floating particles

We have developed a numerical package to simulate particle motions in fluid interfaces. The particles are moved in a direct simulation respecting the fundamental equations of motion of fluids and solid particles without the use of models. The fluid–particle motion is resolved by the method of distributed Lagrange multipliers and the interface is moved by the method of level sets. The present work fills a gap since there are no other theoretical methods available to describe the nonlinear fluid dynamics of capillary attraction. Two different cases of constrained motions of floating particles are studied here. In the first case, we study motions of floating spheres under the constraint that the contact angle is fixed by the Young–Dupr´e law; the contact line must move when the contact angle is fixed. In the second case, we study motions of disks (short cylinders) with flat ends in which the contact line is pinned at the sharp edge of the disk; the contact angle must change when the disks move and this angle can change within the limits specified by the Gibbs extension to the Young–Dupré law. The fact that sharp edged particles cling to interfaces independent of particle wettability is not fully appreciated and needs study. The numerical scheme presented here is at present the only one which can move floating particles in direct simulation. We simulate the evolution of single heavier-than-liquid spheres and disks to their equilibrium depth and the evolution to clusters of two and fours spheres and two disks under lateral forces, collectively called capillary attraction. New experiments by Wang, Bai & Joseph on the equilibrium depth of floating disks pinned at the edge are presented and compared with analysis and simulations.
The Kelvin impulse: application to cavitation bubble dynamics

Abstract The Kelvin impulse is a particularly valuable dynamical concept in unsteady fluid mechanics, with Benjamin and Ellis [2] appearing to be the first to have realised its value in cavitation bubble dynamics. The Kelvin impulse corresponds to the apparent inertia of the cavitation bubble and, like the linear momentum of a projectile, may be used to determine aspect It is defined as where ρ is the fluid density, ø is the velocity potential, S is the surface of the cavitation bubble and n is the outward normal to the fluid. Contributions to the Kelvin impulse may come from the presence of nearby boundaries and the ambient velocity and pressure field. With this number of mechanisms contributing to its development, the Kelvin impulse may change sign during the lifetime of the bubble. After collapse of the bubble, it needs to be conserved, usually in the form of a ring vortex. The Kelvin impulse is likely to provide valuable indicators as to the physical properties required of boundaries in order to reduce or eliminate cavitation damage. Comparisons are made against available experimental evidence.
Scientific Practices as Social Knowledge

ABSTRACT Practice-based philosophy of science has gradually arisen in the sociology of scientific knowledge (SSK) and science and technology studies (STS) during the past decades. It studies science as an ensemble of practices and theorising as one of these practices. A recent study has shown how the practice-based approach can be methodologically justified with reference to Peirce and Dewey. In this article, I will explore one consequence of that notion: science, as practice, is necessarily social. I will disambiguate five different senses in which science is social. First, science presupposes language, which is essentially social. Second, practices, including science, are adaptations of the behaviour of an organism to an environment, of which other organisms are a part. Third, practices, including science, are public and hence shareable. Fourth, scientific knowledge can serve as a vehicle of social and moral reform. Fifth, scientific knowledge can be applied to improve the human condition. This fivefold result bears on the problem of realism.
Variables et signaux aléatoires complexes

Les nombres complexes jouent un role important en physique et dans de nombreuses autres sciences d'observation. Les variables et les signaux aleatoires sont egalement un modele mathematique riche d'applications. Nous proposons ici des modeles pour les variables et les signaux aleatoires complexes. Nous montrons comment ces modeles introduisent des signaux utiles (signal analytique) et des concepts nouveaux (circularite). Nous illustrons les proprietes de ces modeles complexes en estimation, traitement d'antenne et separation de sources.
MEGS: A Penalty for Mutually Exclusive Group Sparsity

Penalty functions or regularization terms that promote structured solutions to optimization problems are of great interest in many fields. We introduce MEGS, a nonconvex structured sparsity penalty that promotes mutual exclusivity between components in solutions to optimization problems. This enforces, or promotes, 1-sparsity within arbitrary overlapping groups in a vector. The mutual exclusivity structure is represented by a matrix <inline-formula><tex-math notation="LaTeX">${\bf {S}}$</tex-math></inline-formula>. We discuss the design of <inline-formula><tex-math notation="LaTeX">${\bf {S}}$</tex-math></inline-formula> from engineering principles and show example use cases including the modeling of occlusions in 3D imaging and a total variation variant with uses in image restoration. We also demonstrate synergy between MEGS and other regularizers and propose an algorithm to efficiently solve problems regularized or constrained by MEGS.
Nonlinear dimensionality reduction using probabilistic principal surfaces

This dissertation takes the feature extraction approach to dimensionality reduction by studying nonlinear manifolds for characterizing high-dimensional data. Among various nonlinear dimensionality reduction techniques, the principal curve, which is a nonlinear generalization of principal components, was found to be the most intuitive, interpretable, and theoretically elegant. However, the original principal curve formulation suffers from a number of problems: it is nonparametric, biased, inefficient, and not guaranteed to converge. To address some of these problems, I first develop two new principal curve algorithms—the Hastie-Stuetzle-Banfield-Raftery principal curve, and the probabilistic principal curve. The improved algorithms are then applied to feature extraction and classification of moderate-dimensional data with good results. Next, I develop the probabilistic principal surface (PPS), a general framework for computing principal surfaces of arbitrary dimensionality and topology. In addition, a generalized expectation maximization algorithm with guaranteed convergence is derived for the PPS. Unlike any of the existing principal surface approximation algorithms, the PPS is the only formulation that is self-consistent, parametric, unbiased, efficient, and guaranteed to converge. Empirical properties of the PPS are also studied and shown to be superior to the generative topographical mapping, which is a special case of the PPS. With the groundwork laid for a flexible and powerful manifold formulation, three applications of the PPS are investigated. First, a spherical PPS is proposed for emulating the sparsity and periphery properties of high-dimensional data. It is found to be very effective for visualizing high-dimensional data; providing extra information over linear projection subspace methods such as principal component analysis. Second, a template-based classifier using spherical PPS as reference manifolds is developed and shown to compare favorably against traditional classifiers based on the k-nearest neighbor and Gaussian mixture models. Finally, a practical pattern recognition application of the spherical PPS for simultaneous classification and pose estimation of 3-D objects from 2-D silhouettes, is demonstrated. Results on simulated and real vehicle and aircraft images show the proposed approach to be highly accurate and effective.
Using Image Representation Families for Recognition Based on Symbol Marking of Singular Points

The construction of families of gray-scale image representations is considered, and the general approach to recognition system organization is proposed. An image is represented as a marked graph with ver- tices in singular points. A method of image primary preprocessing, algorithms of searching for singular points, and ways of classifying singular points during image description are developed and implemented.
The effects of age on the severity of problem drinking: Mediating effects of positive alcohol expectancy and neural correlates

Aging is associated with reduction in the severity of alcohol misuse. However, the psychological and neural mechanisms underlying the age‐related changes remain unclear. Here, we tested the hypothesis that age‐related diminution of positive alcohol expectancy (AE) mediated the effects of age on problem drinking and investigated the neural correlates of the mediating effects. Ninety‐six drinkers 21–85 years of age, including social drinkers and those with mild/moderate alcohol use disorder (AUD), were assessed for global positive (GP) AE and problem drinking, each with the Alcohol Expectancy Questionnaire and Alcohol Use Disorders Identification Test (AUDIT), and with brain imaging during alcohol cue exposure. We processed imaging data with published routines; identified the correlates shared between whole‐brain regression against age, GP and AUDIT scores; and performed mediation and path analyses to explore the interrelationships between the clinical and neural variables. The results showed that age was negatively correlated with both GP and AUDIT scores, with GP score completely mediating the correlation between age and AUDIT score. Lower age and higher GP correlated with shared cue responses in bilateral parahippocampal gyrus and left middle occipital cortex (PHG/OC). Further, higher GP and AUDIT scores were associated with shared cue responses in bilateral rostral anterior cingulate cortex and caudate head (ACC/caudate). Path analyses demonstrated models with significant statistical fit and PHG/OC and ACC/caudate each interrelating age to GP and GP to AUDIT scores. These findings confirmed change in positive AE as a psychological mechanism mitigating alcohol misuse as individuals age and highlighted the neural processes of cue‐reactivity interrelating age and alcohol use severity.
Biochemical Characteristics and Potential Biomedical Applications of Hydrolyzed Carrageenans

Seaweed contains a variety of bioactive compounds; the most abundant of them are polysaccharides, which have significant biological and chemical importance. Although algal polysaccharides, especially the sulfated polysaccharides, have great potential in the pharmaceutical, medical and cosmeceutical sectors, the large molecular size often limits their industrial applications. The current study aims to determine the bioactivities of degraded red algal polysaccharides by several in vitro experiments. The molecular weight was determined by size-exclusion chromatography (SEC), and the structure was confirmed by FTIR and NMR. In comparison to the original furcellaran, the furcellaran with lower molecular weight had higher OH scavenging activities. The reduction in molecular weight of the sulfated polysaccharides resulted in a significant decrease in anticoagulant activities. Tyrosinase inhibition improved 2.5 times for hydrolyzed furcellaran. The alamarBlue assay was used to determine the effects of different Mw of furcellaran, κ-carrageenan and ι-carrageenan on the cell viability of RAW264.7, HDF and HaCaT cell lines. It was found that hydrolyzed κ-carrageenan and ι-carrageenan enhanced cell proliferation and improved wound healing, whereas hydrolyzed furcellaran did not affect cell proliferation in any of the cell lines. Nitric oxide (NO) production decreased sequentially as the Mw of the polysaccharides decreased, which indicates that hydrolyzed κ-Carrageenan, ι-carrageenan and furcellaran have the potential to treat inflammatory disease. These findings suggested that the bioactivities of polysaccharides were highly dependent on their Mw, and the hydrolyzed carrageenans could be used in new drug development as well as cosmeceutical applications.
Motorist’s Vestibular Disorientation Syndrome (MVDS)—Proposed Diagnostic Criteria

Motorist’s vestibular disorientation syndrome (MVDS) is a disorder in which patients experience dizziness while driving. MVDS is under-reported in the literature, and in clinical practice, it often goes unrecognized. We identified clinical characteristics of patients with MVDS using data from 24 patients who faced difficulties while driving and were diagnosed with MVDS. Their symptoms, duration of illness, precipitating factors, co-morbidities, history of other neuro-otological disorders, severity of symptoms, and associated anxiety and depression were reviewed. Ocular motor movements were recorded using video-nystagmography. Patients with vestibular disorders that can cause similar symptoms while driving were excluded. The mean age of the patients was 45.7 ± 8.7 years, and most were professional drivers (90.5%). The duration of the illness ranged from eight days to ten years. Most patients presented with disorientation (79.2%) exclusively while driving. The most common triggers for symptoms were higher speeds, i.e., >80 km/h (66.7%), multi-lane roads (58.3%), bends and turns (50%), and looking at other vehicles or signals while driving (41.7%). A history of migraines was reported in 62.5% of the patients, and motion sickness was reported in 50% of the patients. Anxiety was reported in 34.3% of patients, and 15.7% had depression. The video-nystagmography did not show any specific abnormalities. Patients responded to drugs used in prophylactic treatments for migraines such as Amitriptyline, Venlafaxine, Bisoprolol, and Magnesium, and to Pregabalin and Gabapentin. Based on these findings, a classification system and a diagnostic criterion for MVDS were proposed.
Segmenting the target audience for transportation demand management programs: An investigation between mode shift and individual characteristics

Abstract Understanding the characteristics of travelers and situations that are more likely to switch from single occupancy vehicles (SOV) to more sustainable mobility options can help transportation agencies develop better behavior change strategies. Existing mode shift programs, however, rarely identify their target audience, which could make the programs less effective. To investigate the demographics and trip characteristics of those who are more likely to shift from SOV to carpooling, public transit, and micromobility (e.g. walking, biking), a matrix decomposition audience segmentation method is proposed and applied on travel survey data. The results of this research show that for short-distance leisure or social trips, young and middle-income people are more likely to shift to these mobility options from SOV. This study provides a comprehensive and profound understanding of the characteristics of the target audience that can inform policies to create more targeted behavior change strategies to reach their sustainability goals.
Transient dynamics of the field induced force in the isotropic magnetorheological elastomer

The transition dynamics in silicon rubber based isotropic magnetorheological (MR) elastomers in terms of the normal force induced by an external homogeneous magnetic field is experimentally addressed. The primary goal was to evaluate dynamic performances of the MR elastic isotropic composite using a transparently presented measuring system with known characteristics in contrast to few previous studies on the topic. It was found that an increase in the magnetic field leads to an increase in the induced force and a decrease in the response time of the MR elastomer. At the same time, both the use of coarse particles as magnetic filler and a significant reduction in the stiffness of the polymer matrix reduce the response time of the MR elastomer under study. The analysis carried out takes into account the dynamics of the electromagnetic coil and the eddy currents induced in the magnet circuit. The shortest response times obtained for various MR elastomer samples are in the range of 27–72 ms for the maximal used magnetic field with an induction of 230 mT. These times correspond to the fastest previously reported ones for MR elastomers and MR elastomer based systems. In addition, the obtained results indicate the presence of different mechanisms responsible for the measured magnetodeformational effect observed in MR elastomers.
Enhancement of overlay metrology accuracy by multi-wavelength scatterometry with rotated quadrupole illumination

As DRAM technology continues to evolve, advanced nodes shrink the device dimensions and raise the requirements for on-product overlay control to reduce residual error. Increased process complexity also demands tighter accuracy and robustness in metrology control, which necessitates new and innovative metrology enhancements and methods. Scatterometry-based overlay (SCOL®) metrology is a unique overlay metrology architecture that uses angle-resolved pupil imaging for overlay analysis and calculation. KLA’s SCOL metrology system offers wide-spectrum tunable laser and multi-wavelength (MWL) illumination patterns along with custom-designed advanced algorithms that provide multiple measurement conditions to meet unique layer and target requirements. This paper demonstrates improved overlay metrology accuracy and residual error on DRAM FEOL critical layer with SCOL technology. Multiwavelength and rotated quadrupole (RQ) illumination in the metrology tool are utilized to provide significantly improved residuals compared with the traditional single-wavelength (SWL) and on-axis illumination.
What constitutes a community? A co-occurrence exploration of the Costa Rican avifauna

ABSTRACT The concept of a “community” as a form of organization for natural biological systems is both widespread and widely accepted within the ecological and biological sciences. Communities have been defined as groups of organisms that interact in ways that denote interdependence between individuals and taxa (e.g. as defined by “food webs”) but they have also been defined as groups of co-occurring organisms that are assumed to interact by virtue of their shared spatiotemporal existence. The latter definition has been debated and challenged in the literature, with mounting evidence for co-occurrence being more indicative of coincident ecological niches in space and time rather than being evidence of ecological interaction or dependency. Using a dataset of 460 Costa Rican bird species divided into breeding and non-breeding season datasets, we empirically demonstrate the ways in which co-occurrence can create illusory communities based on similar occupied ecological niches and similar patterns of co-occurrence at different times of year. We discuss the importance of discerning coincidental co-occurrence from true ecological interactions that would manifest a true community, and further address the importance of differentiating communities of co-occurrence from communities of demonstrable ecological interaction. While co-occurrence is a necessary aspect of interspecific interactions, we discuss and demonstrate here that such co-occurrence does not make a community, nor should explicit patterns of co-occurrence be seen as evidence for evolutionarily important ecological interactions.
A Stabilized Sequential Quadratic Programming Method for Optimization Problems in Function Spaces

Abstract In this paper, we propose a stabilized sequential quadratic programming (SQP) method for optimization problems in function spaces. A form of the problem considered in this paper can widely formulate many types of applications, such as obstacle problems, optimal control problems, and so on. Moreover, the proposed method is based on the existing stabilized SQP method and can find a point satisfying the Karush-Kuhn-Tucker (KKT) or asymptotic KKT conditions. One of the remarkable points is that we prove its global convergence to such a point under some assumptions without any constraint qualifications. In addition, we guarantee that an arbitrary accumulation point generated by the proposed method satisfies the KKT conditions under several additional assumptions. Finally, we report some numerical experiments to examine the effectiveness of the proposed method.