Miracle-dz/UniFAR-FTUs huggingface dataset:
Proces Svojinske Transformacije U Privredi Srbije I Problem Njegovog Sagledavanja (Ownership Transformation Process in Serbian Economy and the Problem of Its Observations)

English. This paper offers an analysis of the financial results of the 113 and 122 Serbian enterprises that were privatized in 1992 and the first half of 1993, in comparison with those enterprises which did not go through an ownership transformation process. Based on the balances from 1992 and periodical balances from the first half of 1993, a list was formed with 15 accounting and financial indicators for the two mentioned groups of enterprises as well as for a group of the most successful enterprises of the Republic of Serbia according to their profit before tax. The comparison of the financial results of these groups of enterprises was done on the basis of the general results of their balance sheets and income statements, including an insight into the structure of their balances. Comparative analysis was then carried out of their financial results, having divided the groups into sub-groups according to their ownership type and the industries they operate in. The last part of the paper gives an analysis of the general business factors for the industry as a whole as well for the transformed enterprises, considered in total and considered by industry. This analysis is based on the factor analysis of the mentioned indicators. The results of the analysis show that the transformed and non-transformed parts of industry cannot be clearly distinguished, i.e. the transformed ones have not suffered any qualitative changes in doing business, but have only had their form changed instead (workers’ shareholding now being present instead of worker self-management). Serbian. U radu je data analiza finansijskih rezultata poslovanja preduzeca u privredi Srbije privatizovanih tokom 1992. (113) i prve polovine 1993. (122 preduzeca) u odnosu na preduzeca koja nisu izvrsila svojinsku transformaciju. Na osnovu podataka iz zavrsnih racuna za 1992. i periodicnih obracuna za prvo polugodiste 1993. formirana je lista od 15 knjigovodstveno-finansijskih pokazatelja za navedena dva skupa preduzeca i grupu najuspesnijih preduzeca u privredi Republike prema ostvarenoj dobiti pre oporezivanja. Poređenje finansijskih rezultata poslovanja preduzeca iz navedenih skupova, kao i ukupne privrede, vrseno je prema opstim rezultatima iz njihovih bilansa stanja i bilansa uspeha, ukljucujuci uvid u strukturu tih bilansa. Zatim je data uporedna analiza finansijskih rezultata poslovanja, pri cemu su ovi skupovi rasclanjeni na podgrupe po sektorima svojine i po privrednim delatnostima. U poslednjem delu rada data je analiza opstih faktora poslovanja za ukupnu privredu i za transformisana preduzeca, ukupno i rasclanjeno na delatnosti, zasnovana na faktorskoj analizi pomenutih pokazatelja. Rezultati analize pokazuju da se transformisani i netransformisani delovi privrede ne mogu jasno razdvojiti, odnosno da kod transformisanih nije doslo do kvalitativnih promena u poslovanju, vec je promenjena samo forma (radnicko akcionarstvo umesto radnickog samoupravljanja).
Restaurant Dining Environment, Restaurant Formality and Dining Involvement in the Context of Memorable Dining Experiences (Mdes)

ABSTRACT This research study investigates the importance consumers place on four restaurant dining facets (design, ambience, sociability, food and beverage) to ascertain how these elements contribute to memorable dining experience (MDEs). Restaurant formality and restaurant dining involvement were explored as additional influencing factors within the context of MDEs. Data were collected using an online survey administered to a sample of American diners. Through a measurement model approach, all four facets were found to define restaurant dining environment under MDEs. The findings provide meaningful insights to restaurant managers about how the dining environment of a restaurant can influence consumers’ experience in terms of co-creating memorability. These insights are particularly relevant in the post-pandemic era, when the way consumers interact with restaurant environments may change.
Multi-Scale Modelling of Plastic Deformation, Damage and Relaxation in Epoxy Resins

Epoxy resin plasticity and damage was studied from molecular dynamic simulations and interpreted by the help of constitutive modelling. For the latter, we suggested a physically motivated approach that aims at interpolating two well-defined limiting cases; namely, pulling at the vanishing strain rate and very rapid deformation; here, taken as 50% of the speed of sound of the material. In turn, to consider 0.1–10-m/s-scale deformation rates, we employed a simple relaxation model featuring exponential stress decay with a relaxation time of 1.5 ns. As benchmarks, deformation and strain reversal runs were performed by molecular dynamic simulations using two different strain rates. Our analyses show the importance of molecular rearrangements within the epoxy network loops for rationalizing the strain-rate dependence of plasticity and residual stress upon strain reversal. To this end, our constitutive model reasonably reproduced experimental data of elastic and visco-elastic epoxy deformation, along with the maximum stress experienced before fracturing. Moreover, we show the importance of introducing damage elements for mimicking the mechanical behavior of epoxy resins.
Attack Power System State Estimation by Implicitly Learning the Underlying Models

False data injection attacks (FDIAs) are a real and latent threat in modern power systems networks due to the unprecedented integration of data acquisition systems. It is of utmost importance to understand attacking mechanisms to design countermeasures. To successfully deploy a FDIA, most past FDIA strategies need privileged power system information, which is carefully held by the power system operator. Newer approaches circumvent this issue by solely relying on intercepted measurement data, but they lack mathematical warranties of succeeding. This paper exposes power systems’ vulnerability by showing that it is possible to deploy an attack without confidential information and, at the same time, to have a high probability of being successful. We present a scheme that learns (1) the implicit power system measurement distribution and (2) a surrogate of the unknown state estimator model. The proposed framework utilizes a Wasserstein generative adversarial network to learn the measurement distribution and an autoencoder to learn the unknown state estimator model. Additionally, we present a convergence proof that ensures that the proposed framework converges to the power system measurement distribution. The proposed method is demonstrated to be successful via extensive simulation on IEEE 9-, 14-, 57-, 118-, and 300-bus test cases.
Associations between Family Functioning and Symptoms of Attention-Deficit Hyperactivity Disorder (ADHD): A Cross-Sectional Study

Poor family functioning is linked with poor child ADHD symptoms. However, there are many dimensions of family functioning. Thus, this study aims to find the association between each dimension of family functioning and controlled ADHD symptoms in an Asian culture. This cross-sectional study involved caregivers of 113 Thai children with ADHD ages 4–16 years old who visited the Outpatient Department at Maharaj Nakorn Chiang Mai Hospital between October 2017 and March 2018. The caregivers completed the Chulalongkorn Family Inventory and the SNAP-IV Thai version. Logistic regression was used to examine each dimension of family functioning adjusting for potential confounders. In univariate analyses, six of the seven dimensions of family functioning were associated with controlled ADHD symptoms. In multivariate analyses, findings revealed that good family roles (aOR 7.48, 95% CI = 1.56 to 35.85, p = 0.01) and behavior control (aOR 2.56, 95% CI = 1.08 to 6.03, p = 0.03) were associated with controlled ADHD symptoms. In children with ADHD with poor symptom control, the assessment of family functioning could be helpful. Developing a more specific intervention for caregivers that promotes good family roles and behavioral control may be beneficial.
On the definition of word

"On The Definition of Word" develops a consistent and coherent approach to central questions about morphology and its relation to syntax. In sorting out the various senses in which the word "word" is used, it asserts that three concepts which have often been identified with each other are in fact distinct and not coextensive: listemes (linguistic objects permanently stored by the speaker); morphological objects (objects whose shape can be characterized in morphological terms of affixation and compounding); and syntactic atoms (objects that are unanalyzable units with respect to syntax). The first chapter defends the idea that listemes are distinct from the other two notions, and that all one can and should say about them is that they exist. A theory of morphological objects is developed in chapter two. Chapter three defends the claim that the morphological objects are a proper subset of the syntactic atoms, presenting the authors' reconstruction of the important and much-debated Lexical Integrity Hypothesis. A final chapter shows that there are syntactic atoms which are not morphological objects.Anne Marie Di Sciullo is in the Department of Linguistics at the University of Quebec. Edwin Williams is in the Department of Linguistics at the University of Massachusetts. "On The Definition of Word" is Linguistic Inquiry Monograph 14.
Intelligent Matching Method for Heterogeneous Remote Sensing Images Based on Style Transfer

Intelligent matching of heterogeneous remote sensing images is a common basic problem in the field of intelligent remote sensing image processing. Aiming at the difficulty of matching satellite-aerial remote sensing images, this article proposes an intelligent matching method for heterogeneous remote sensing images based on style transfer. First, based on the idea of image style transfer of a generative adversarial networks, this method improves the conversion effect of the model on heterogeneous images by constructing a new generative network loss function and converts satellite images into aerial images. Then, the advanced deep learning-based matching algorithms D2-Net and LoFTR are used to achieve matching between the generated aerial image and the original aerial image. Finally, this transformation relationship is mapped to the corresponding satellite–aerial image pair to obtain the final matching result. The image style transfer experiments and the matching experiments we carry out under different test datasets show that the smooth cycle-consistent generative adversarial networks proposed in this article can effectively reduce the complexity of the algorithm and improve the quality of image generation. In addition, combining it with deep learning-based feature-matching methods can effectively improve the accuracy and robustness of the matching algorithm. Our code and data can be found at: https://gitee.com/AZQZ/intelligent-matching.
Characterization of Phase Separated Planar Lipid Bilayer Membrane by Fluorescence Ratio Imaging and Scanning Probe Microscope

The lipid membrane forms nanodomains (rafts) and shows heterogeneous properties. These nanodomains relate to significant roles in various cell functions, and thus the analysis of the nanodomains in phase-separated lipid membranes is important to clarify the function and role of the nanodomains. However, the lipid membrane possesses small-sized nanodomains and shows a small height difference between the nanodomains and their surroundings at certain lipid compositions. In addition, nanodomain analysis sometimes requires highly sensitive and expensive apparatus, such as a two-photon microscope. These have prevented the analysis by the conventional fluorescence microscope and by the topography of the scanning probe microscope (SPM), even though these are promising methods in macroscale and microscale analysis, respectively. Therefore, this study aimed to overcome these problems in nanodomain analysis. We successfully demonstrated that solvatochromic dye, LipiORDER, could analyze the phase state of the lipid membrane at the macroscale with low magnification lenses. Furthermore, we could prove that the phase mode of SPM was effective in the visualization of specific nanodomains by properties difference as well as topographic images of SPM. Hence, this combination method successfully gave much information on the phase state at the micro/macro scale, and thus this would be applied to the analysis of heterogeneous lipid membranes.
Incorporating multi‐interest into recommendation with graph convolution networks

In recent years, the appearance of graph convolutional networks (GCNs) provides a new idea for graph structure data processing. Because of that, they can learn excellent user and item embedding by using cooperative signals of high‐order neighbors, and the GCNs technique shows great potential in the recommendation. The common problem with the bulk of GCN‐based models is that it appears the situation of performance degradation during the stacking of network layers. The recently proposed IMP‐GCN alleviates this problem to some extent. It aims to avoid the influence of downside information from high‐order propagation on embedding learning. However, we consider that it ignores the multi‐interest factor, in which users may have different interests. In this paper, we present a multi‐interest GCN(MI‐GCN) model for a recommendation, and it conducts high‐order graph convolution operations in three sets of subgraphs. Users with similar interests and the corresponding interaction items belong to the identical subgraph. As for the formation of the subgraph, we adopt two varied clustering methods and the user feature to form a subgraph generation mechanism. This mechanism can generate three groups of differential subgraphs to divide users into multi‐interest groups and make subgraph division more reasonable. We carry out massive experiments on three real‐world datasets, demonstrating the effectiveness of our model. Experimental results confirm that our presented MI‐GCN outperforms the state‐of‐the‐art GCN‐based recommendation models.
Aβ and Tau Interact with Metal Ions, Lipid Membranes and Peptide-Based Amyloid Inhibitors: Are These Common Features Relevant in Alzheimer’s Disease?

In the last two decades, the amyloid hypothesis, i.e., the abnormal accumulation of toxic Aβ assemblies in the brain, has been considered the mainstream concept sustaining research in Alzheimer’s Disease (AD). However, the course of cognitive decline and AD development better correlates with tau accumulation rather than amyloid peptide deposition. Moreover, all clinical trials of amyloid-targeting drug candidates have been unsuccessful, implicitly suggesting that the amyloid hypothesis needs significant amendments. Accumulating evidence supports the existence of a series of potentially dangerous relationships between Aβ oligomeric species and tau protein in AD. However, the molecular determinants underlying pathogenic Aβ/tau cross interactions are not fully understood. Here, we discuss the common features of Aβ and tau molecules, with special emphasis on: (i) the critical role played by metal dyshomeostasis in promoting both Aβ and tau aggregation and oxidative stress, in AD; (ii) the effects of lipid membranes on Aβ and tau (co)-aggregation at the membrane interface; (iii) the potential of small peptide-based inhibitors of Aβ and tau misfolding as therapeutic tools in AD. Although the molecular mechanism underlying the direct Aβ/tau interaction remains largely unknown, the arguments discussed in this review may help reinforcing the current view of a synergistic Aβ/tau molecular crosstalk in AD and stimulate further research to mechanism elucidation and next-generation AD therapeutics.
EMPATIA: A Guide for Communicating the Diagnosis of Neuromuscular Diseases

Introduction: Neuromuscular diseases comprise a heterogeneous group of genetic syndromes that lead to progressive muscle weakness, resulting in functional limitation. There is a gap in the literature regarding the communication of the diagnosis of such diseases, compromising the autonomy of patients and families, besides causing stress on the assistant physician. Objectives: Developing a guide to reduce communication barriers in the diagnosis of neuromuscular diseases. Methodology: Systematic review, after searching the descriptors (“Muscular Diseases” OR “Neuromuscular Diseases”) AND (“Truth Disclosure” OR “Bad news communication” OR “Breaking bad News”) in the Pubmed, Bireme, and Scopus websites, and these results were analyzed through narrative textual synthesis. Results: 16 articles were submitted to the final analysis, giving rise to seven steps to support the communication process. These are Empathy, Message, Prognosis, Reception, Time, Individualization, and Autonomy. Discussion and conclusion: The empathic transmission of the message and the prognosis must accommodate the feelings of the interlocutors with different information needs. In this way, communication planning optimizes the time and individualizes each context, respecting the autonomy of those involved. EMPATIA reflects the bioethical and interdisciplinary analysis of the literature and comes to fill the gap related to the communication of bad news in neuromuscular diseases.
Possible Role of Extracellular Vesicles in Hepatotoxicity of Acetaminophen

We examined proteomic profiles of rat liver extracellular vesicles (EVs) shed following treatment with a sub-toxic dose (500 mg/kg) of the pain reliever drug, acetaminophen (APAP). EVs representing the entire complement of hepatic cells were isolated after perfusion of the intact liver and analyzed with LC-MS/MS. The investigation was focused on revealing the function and cellular origin of identified EVs proteins shed by different parenchymal and non-parenchymal liver cells and their possible role in an early response of this organ to a toxic environment. Comparison of EV proteomic profiles from control and APAP-treated animals revealed significant differences. Alpha-1-macroglobulin and members of the cytochrome P450 superfamily were highly abundant proteins in EVs shed by the normal liver. In contrast, proteins like aminopeptidase N, metalloreductase STEAP4, different surface antigens like CD14 and CD45, and most members of the annexin family were detected only in EVs that were shed by livers of APAP-treated animals. In EVs from treated livers, there was almost a complete disappearance of members of the cytochrome P450 superfamily and a major decrease in other enzymes involved in the detoxification of xenobiotics. Additionally, there were proteins that predominated in non-parenchymal liver cells and in the extracellular matrix, like fibronectin, receptor-type tyrosine-protein phosphatase C, and endothelial type gp91. These differences indicate that even treatment with a sub-toxic concentration of APAP initiates dramatic perturbation in the function of this vital organ.
A New Boosted Proximal Point Algorithm for Minimizing Nonsmooth DC Functions

Abstract Several optimization schemes have been known for convex optimization problems. A significant progress to go beyond convexity was made by considering the class of functions representable as difference of convex functions which constitute the backbone of nonconvex programming and global optimization. In this article, we introduce new algorithm to minimize the difference of a continuously differentiable function and a convex function that accelerate the convergence of the classical proximal point algorithm. We prove that the point computed by proximal point algorithm can be used to define a descent direction for the objective function evaluated at this point. Our algorithms are based on a combination of proximal point algorithm together with a line search step that uses this descent direction. Convergence of the algorithms is proved and the rate of convergence is analyzed under the strong Kurdyka–Łojasiewicz property of the objective function.
Mesenchymal (Stem) Stromal Cells Based as New Therapeutic Alternative in Inflammatory Bowel Disease: Basic Mechanisms, Experimental and Clinical Evidence, and Challenges

Inflammatory bowel diseases (IBD) are an example of chronic diseases affecting 40% of the population, which involved tissue damage and an inflammatory process not satisfactorily controlled with current therapies. Data suggest that mesenchymal stem cells (MSC) may be a therapeutic option for these processes, and especially for IBD, due to their multifactorial approaches such as anti-inflammatory, anti-oxidative stress, anti-apoptotic, anti-fibrotic, regenerative, angiogenic, anti-tumor, or anti-microbial. However, MSC therapy is associated with important limitations as safety issues, handling difficulties for therapeutic purposes, and high economic cost. MSC-derived secretome products (conditioned medium or extracellular vesicles) are therefore a therapeutic option in IBD as they exhibit similar effects to their parent cells and avoid the issues of cell therapy. In this review, we proposed further studies to choose the ideal tissue source of MSC to treat IBD, the implementation of new standardized production strategies, quality controls and the integration of other technologies, such as hydrogels, which may improve the therapeutic effects of derived-MSC secretome products in IBD.
Energy delocalization in strongly disordered systems induced by the long-range many-body interaction

Anderson localization1 in a random system is sensitive to a distance dependence of the excitation transfer amplitude V(r). If V(r) decreases with the distance r slower than 1/r^d in a d-dimensional system then all excitations are delocalized at arbitrarily strong disordering, due to the resonant interaction of far separated quantum states (Fig. 1). At finite temperature T>0 the density of excitations is finite and they can influence each other by means of their interaction. Many body excitations involving simultaneous transitions of several single particle excitations create additional channels for energy delocalization and transport. Here we show that if the interaction of excitations decreases with the distance slower than 1/R^(2d) then excitations are delocalized at finite temperature irrespectively to disordering. This delocalization results in the finite decoherence rate in the ensemble of interacting spins 1/2 representing the model of quantum computer, thus restricting the quantum hardware performance. It also leads to the energy and particle delocalization and transport at finite temperature in various physical systems including doped semiconductors, despite of the full localization of electrons at zero temperature.
Comparative Pathology of Zoonotic Orthopoxviruses

This review provides a brief history of the impacts that a human-specific Orthopoxvirus (OPXV), Variola virus, had on mankind, recalls how critical vaccination was for the eradication of this disease, and discusses the consequences of discontinuing vaccination against OPXV. One of these consequences is the emergence of zoonotic OPXV diseases, including Monkeypox virus (MPXV). The focus of this manuscript is to compare pathology associated with zoonotic OPXV infection in veterinary species and in humans. Efficient recognition of poxvirus lesions and other, more subtle signs of disease in multiple species is critical to prevent further spread of poxvirus infections. Additionally included are a synopsis of the pathology observed in animal models of MPXV infection, the recent spread of MPXV among humans, and a discussion of the potential for this virus to persist in Europe and the Americas.