University of Bucharest
  • Bucharest, District 5, Romania
Recent publications
Background: Nations marked by a Marxist-Leninist ideology have suffered greatly due to a culture of abuse emphasized by the absolute absence of psychology, thus contributing to a diminished ability in recognizing the consequences of traumatic experiences. Objective: To improve the assessment of the presence and severity of posttraumatic stress disorder (PTSD) in such a cultural context, our paper aimed at developing an alternative self-report measure for PTSD - the Post Traumatic Symptom Scale (PTSs), developed by clinicians with wide relevant expertise, based on the natural language people use to describe its subjective experience. This research used multiple samples consistent with the corresponding objectives. Mokken Scale Analysis and the Classical Test Theory were both employed. The proposed scale was tested against five competing PTSD models, whilst also investigating the symptoms' clusters in two different samples by using, to our knowledge, a network analysis approach for the first time. Method: The results indicated excellent psychometric properties regarding internal consistency and temporal reliability, as well as convergent and discriminant validity. The results of MSA showed that the scale fully conforms to the assumptions of the monotone homogeneity model, interpreted as positive evidence for its use in clinical purposes. The factor analyses pointed that the newer models outperformed the standard DSM-5 model, with bifactor models displaying better fit indexes than second-order models. Finally, a distinct pattern of symptom activation in the high-risk group (i.e. first-responders) was found, bringing support for symptoms overlapping between PTSD and affective disorders, thus reinforcing the idea of bridge symptoms which has significant clinical implications. Results: This study presents an alternative sound instrument for measuring PTSD symptomatology focused on how people naturally describe their subjective experiences. Theoretical and practical implications are discussed alongside limitations. Highlights: The construction of PTSs encompasses cultural trauma and one's subjective experience.PTSs was tested against the five major competing models of PTSD.Network analyses suggest different patterns in a student sample vs. a first-responders one, with the accent on the negative alterations in cognitions and mood (NACM) model.
The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.
A natural coupling of a circuit with an electromagnetic device is possible if special boundary conditions, called Electric Circuit Element (ECE), are used for the electromagnetic field formulation. This contribution shows how these ECE boundary conditions can be implemented into the 3D-finite element method for solving coupled full-wave electromagnetic (EM) field-circuit problems in the frequency domain. The frequency response allows the extraction of a reduced order model of the analyzed device, accounting for all the EM field effects. The implementation is based on a weak formulation that uses the electric field strength E strictly inside the domain and a scalar potential V defined solely at the boundary. Edge elements for E are used inside the three-dimensional domain and nodal elements for V are used on its two-dimensional boundary. The weak formulation is described and implemented in the free environment Open Numerical Engineering LABoratory (onelab) . The validation is carried out on 3D examples.
The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.
Quality is a requirement of the 21st century, ranging from education to construction. Hence, this paper aims to treat in a theoretical but especially in an applied manner the set of concepts which lead to the achievement of quality in construction. The article is structured in five sections, followed by the resulting conclusions at the very end. The first section deals with the introductory elements of this article. The second section refers to the definition of the concept of quality in construction. The third section concerns the definition of the concept of planning in construction, as a necessity to reach the quality level required by the Romanian legislation. The fourth section deals with the elements of a database design for a construction project, its stages and the information that is processed. The fifth section refers to the case study that presents the elaboration of the project plan and the logical matrix of a project.
We prove an abstract form of the strong convergence of the Halpern-type and Tikhonov-type proximal point algorithms in CAT(0) spaces. In addition, we derive uniform and computable rates of metastability (in the sense of Tao) for these iterations using proof mining techniques.
To evaluate the prospects of using Baikal endemic sponges as bioindicators of chemical elements pollution, the elemental composition of sponges, water and substrate samples, collected in two areas with different levels of anthropogenic loading of the Baikal Lake, was determined using two analytical techniques. The content of Cl, Ca, V, Zn, As, Se, Ba, Cd, and Cu in the sponges collected in Listvennichny Bay was significantly higher than in Bolshye Koty Bay. The values of the pollution indices point at the slight to moderate pollution of the substrates. According to the bioaccumulation factor values, sponges accumulate mainly Cd, Cu and Br from the substrate, and the main part of the elements from water. The distribution of elements longwise the sponges and their intraspecific variation were evaluated. It was shown that Lubomirskia baikalensis sponges were suitable bioindicators to assess the pollution of Lake Baikal.
Lab-on-a-chip strategies using miniaturized devices enable cells to be cultured in a tridimensional (3D) space that offers a real model mimicking in vivo environment. One may provide architectural configurations relevant for specific tissues to maintain them at adequate temperature, oxygen levels, and pH during the necessary time intervals for observation. Herein, we propose a miniaturized lab-on-chip glass device suitable for simultaneous dosimetry measurements and evaluation of the biological effects of ionizing radiation on cancer cells. For the 3D fabrication of biologically relevant microenvironment, high repetition rate picosecond laser-assisted etching is applied to create microfluidic networks between sealed cell culture chambers in photo-sensitive glasses (PG). To evaluate the radiation dose, we employed collimated X-ray beams to generate free electrons in the PG samples by photoreduction of Ag ions to Ag atoms. A subsequent thermal treatment applied to the PG induced clustering of precipitated Ag atoms to color the exposed area to brown, which allows us to directly evaluate a threshold of the applied X-ray radiation dose applied directly on chip. Based on our glass biochip, we tested the response of human melanoma cancer cells exposed to various X-ray doses. This lab-on-chip platform is a valuable tool to analyze and validate the cellular response to new irradiation strategies as alternatives to conventional radiotherapy methods.
It is difficult to predict and model with an accurate model the floods, that are one of the most destructive risks across the earth's surface. The main objective of this research is to show the prediction power of three ensemble algorithms with respect to flood susceptibility estimation. These algorithms are: Iterative Classifier Optimizer-Alternating Decision Tree-Frequency Ratio (ICO-ADT-FR), Iterative Classifier Optimizer-Deep Learning Neural Network-Frequency Ratio (ICO-DLNN-FR) and Iterative Classifier Optimizer-Multilayer Perceptron-Frequency Ratio (ICO-MLP-FR). The first stage of the manuscript consisted of the collection and processing of the geodatabase needed in the present study. The geodatabase comprises a number of 14 flood predictors and 132 known flood locations. The Correlation-based Feature Selection (CFS) method was used in order to assess the prediction capacity of the 14 predictors in terms of flood susceptibility estimation. The training and validation of the three ensemble models constitute the next stage of the scientific workflow. Several statistical metrics and ROC curve method were involved in the evaluation of the model's performance and accuracy. According to ROC curves all the models achieved high performances since their AUC had values above 0.89. ICO-DLNN-FR proved to be the most accurate model (AUC = 0.959). The outcomes of the study can be used to guide future flood risk management and sustainable land-use planning in the designated area.
Torque teno virus (TTV) is highly prevalent, but little is known about its circulation in humans. Here, we investigated the geographical distribution and phylogeny of TTV in Romania. A fragment of TTV untranslated region B was sequenced in samples from volunteers across the country. Additional sequences from dialyzed patients were also included in the study. Phylogenetic analysis showed that more than 80% of Romanian sequences clustered with isolates assigned to the species Torque teno virus 1 and Torque teno virus 3 (former genogroup 1), and this analysis discriminated between isolates from the North-East and West regions. Further studies assessing the pathogenic potential of TTV isolates should employ analysis based on genomic regions with phylogenetic resolution below the species level.
Purpose To better understand the multidimensional construct of Fear of Cancer Recurrence (FCR) in cancer survivors, the purpose of this study was to highlight key FCR symptoms and their strongest associations with depression and anxiety comorbidities. This approach is critical for developing effective interventions tailored to cancer survivors. We also investigated whether the network changes its symptom connectivity across different diagnostic and treatment subgroups classified as vulnerable or less vulnerable. Methods. We collected data from 234 cancer survivors (women: 78.20%; mean age: 35.58) who had been diagnosed with cancer, were undergoing cancer treatment, or had completed treatment. In addition to cancer-related data that allowed subgrouping, they completed the Fear of Cancer Recurrence Inventory (FCRI) and the Hospital Anxiety and Depression Scale (HADS). The FCRI is a multidimensional construct that captures symptoms on the spectrum of intrusive thoughts, coping skills, and five others. Networks were estimated using the Gaussian graphical model. Results. The main findings suggest that intrusive thoughts were overall the most influential network symptoms. However, coping skills were central to the network and associated with depression only in the vulnerable subgroups. Conclusions. The present study found that intrusive thoughts were core network symptoms, whereas coping skills and their association with depression were significant only for some subgroups. Implications. Future clinical trials and interventions for FCR should specifically target intrusive thoughts and other repetitive thinking patterns. More research should be conducted to understand the unique characteristics of survivors and their interaction with symptomatology to maximize treatment efficacy.
Antimicrobial and anticancer drug resistance represent two of the main global challenges for the public health, requiring immediate practical solutions. In line with this, we need a better understanding of the origins of drug resistance in prokaryotic and eukaryotic cells and the evolutionary processes leading to the occurrence of adaptive phenotypes in response to the selective pressure of therapeutic agents. The purpose of this paper is to present some of the analogies between the antimicrobial and anticancer drug resistance. Antimicrobial and anticancer drugs share common targets and mechanisms of action as well as similar mechanisms of resistance (e.g., increased drug efflux, drug inactivation, target alteration, persister cells' selection, protection of bacterial communities/malignant tissue by an extracellular matrix, etc.). Both individual and collective stress responses triggered by the chemotherapeutic agent involving complex intercellular communication processes, as well as with the surrounding microenvironment, will be considered. The common themes in antimicrobial and anticancer drug resistance recommend the utility of bacterial experimental models for unraveling the mechanisms that facilitate the evolution and adaptation of malignant cells to antineoplastic drugs.
The aim of this study was to examine cross-cultural differences, as operationalized by Schwartz's refined theory of basic values, in burnout levels among psychotherapists from 12 European countries during the coronavirus disease (COVID-19) pandemic. We focused on the multilevel approach to investigate if individual- and country-aggregated level values could explain differences in burnout intensity after controlling for sociodemographic, work-related characteristics and COVID-19-related distress among participants. 2915 psychotherapists from 12 countries (Austria, Bulgaria, Cyprus, Finland, Great Britain, Serbia, Spain, Norway, Poland, Romania, Sweden, and Switzerland) participated in this study. The participants completed the Maslach Burnout Inventory-Human Service Survey, the revised version of the Portrait Values Questionnaire, and a survey questionnaire on sociodemographic, work-related factors and the COVID-19 related distress. In general, the lowest mean level of burnout was noted for Romania, whereas the highest mean burnout intensity was reported for Cyprus. Multilevel analysis revealed that burnout at the individual level was negatively related to self-transcendence and openness-to-change but positively related to self-enhancement and conservation values. However, no significant effects on any values were observed at the country level. Male sex, younger age, being single, and reporting higher COVID-19-related distress were significant burnout correlates. Burnout among psychotherapists may be a transcultural phenomenon, where individual differences among psychotherapists are likely to be more important than differences between the countries of their practice. This finding enriches the discussion on training in psychotherapy in an international context and draws attention to the neglected issue of mental health among psychotherapists in the context of their professional functioning.
Context Deforestation remains one of the most pressing threats to biodiversity. Characterizing the resulting forest loss and fragmentation efficiently from remotely sensed data therefore has strong practical implications. Data are often separately analyzed for spatial fragmentation and disorder, but no existing metric simultaneously quantifies the shapes and arrangement of fragments. Objectives We present a Fractal Fragmentation and Disorder Index ( FFDI ), which advances a previously developed fractal index by merging it with the Rényi information dimension. The FFDI is designed to work across spatial scales, and efficiently reports the fragmentation of images and spatial disorder of those fragments. Methods We validate the FFDI with four sets of synthetic Hierarchically Structured Random Map (HRM) multiscale images, characterized by increasing fragmentation and disorder but decreasing average size over multiple scales. We then apply the FFDI to the Global Land Analysis & Discovery Global Forest Change database satellite imagery of forest cover for 10 distinct regions of the Romanian Carpathian Mountains from 2000-2014. Results The FFDI outperformed the individual use of its two components in resolving spatial patterns of disorder and fragmentation among HRM classes. It offers a clear advantage when compared to the individual use of Fractal Fragmentation Index and the Rényi information dimension, and works in an application to real data. Conclusions This work improves on previous characterizations of landscape patterns. With the FFDI , scientists will be able to better monitor and understand forest fragmentation from satellite imagery. The FFDI will have broad applicability to biological fields where image analysis is used.
The paper discusses the properties of the organic heterostructures with triple-layer ZnO/Ag/ZnO as a replacement for ITO and mixed layer containing arylenevinylene oligomer (based on triphenylamine or carbazole) donor and non-fullerene (perylene diimide) acceptor mixed in the ratio 1:2 and the effect of a buffer layer of PEDOT-PSS intercalated between triple-layer and mixed organic layer. The UV-Vis transmission and photoluminescence properties are investigated in correlation with the surface topography and reveal a good match between the absorption and emission domain which can favor the generation of the charge carriers. The heterostructure with the mixed layer based on triphenylamine oligomer show the widest absorption domain and the photoluminescence spectra of the heterostructures realized with either triphenylamine or carbazole oligomer showed peaks corresponding to radiative decay of the donor and acceptor. The I-V characteristics in dark indicate a slightly non-linear behavior and the current is affected by the charge carriers recombination on the defects presented in the thick mixed layer deposited by Matrix Assisted Pulsed Laser Evaporation. The effect of the PEDOT-PSS buffer layer on the electrical properties of the organic heterostructure with ZnO/Ag/ZnO electrode is also investigated. This article is protected by copyright. All rights reserved.
Given an n-vertex m-edge graph G of clique-width at most k, and a corresponding k-expression, we present algorithms for computing some well-known centrality indices (eccentricity and closeness) that run in O(2O(k)(n+m)1+ϵ)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {O}}(2^{{\mathcal {O}}(k)}(n+m)^{1+\epsilon })$$\end{document} time for any ϵ>0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\epsilon > 0$$\end{document}. Doing so, we can solve various distance problems within the same amount of time, including: the diameter, the center, the Wiener index and the median set. Our run-times match conditional lower bounds of Coudert et al. (SODA’18) under the Strong Exponential-Time Hypothesis. On our way, we get a distance-labeling scheme for n-vertex m-edge graphs of clique-width at most k, using O(klog2n)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {O}}(k\log ^2{n})$$\end{document} bits per vertex and constructible in O~(k(n+m))\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\tilde{\mathcal {O}}(k(n+m))$$\end{document} time from a given k-expression. Doing so, we match the label size obtained by Courcelle and Vanicat (DAM 2016), while we considerably improve the dependency on k in their scheme. As a corollary, we get an O~(kn2)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\tilde{\mathcal {O}}(kn^2)$$\end{document}-time algorithm for computing All-Pairs Shortest-Paths on n-vertex graphs of clique-width at most k, being given a k-expression. This partially answers an open question of Kratsch and Nelles (STACS’20). Our algorithms work for graphs with non-negative vertex-weights, under two different types of distances studied in the literature. For that, we introduce a new type of orthogonal range query as a side contribution of this work, that might be of independent interest.
Topics such as disinformation, misinformation, political polarization, and populism are frequently discussed in the social media literature. The purpose of this article is to investigate how the political emphasis on social media has evolved in the academic publications published in the last decade. Thus, using co-word analysis of the social science articles published between 2012 and 2021, which discuss politically about Facebook or Twitter (N = 3389), this article investigates whether certain major and unexpected political events-such as Donald Trump's presidential victory and the Brexit referendum-have influenced in any way the knowledge field related to social media publications. Thus, the 2017-2021 map brings new and popular words, such as "Covid-19," which is associated in similar clusters with words such as disinformation, fake news, and infodemic. Furthermore, the emergence of the word "Russia" places it in a common cluster with words such as bots, elections, and agenda-setting. Also, the Twitter map, unlike the Facebook one, brings a particular emphasis on Donald Trump's activity, which appears in clusters that are similar to topics that brought him popularity on Twitter, such as: meme, migration, and refugees. Such bibliometric associations should increase policymakers' attention to the potential use of social media as a political tool, along with designing the solutions to limit such intrusions into future political events.
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7,364 members
Octavian D. Pavel
  • Department of Organic Chemistry, Biochemistry and Catalysis
Nicolae Cotfas
  • Faculty of Physics
Florentina Hristea
  • Department of Computer Science
Surugiu Camelia
  • Faculty of Administration and Business
90 Panduri Street, 050663, Bucharest, District 5, Romania
Head of institution
Marian Preda
+40-21- 313 17 60