Alexandru Ioan Cuza University

In social economic researches we often need to measure non-observable, latent variables. For this we use special research instruments, with uni and multi dimensional scales designed for measuring the constructs of interest. Validity and reliability of these scales are crucial and special tests have been developed in this respect. Reliability concerns often arise, due to external factors that can influence the power and significance of such tests. Even for standardized instruments variations are possible, and they could seriously affect research results. The purpose of the present study is to investigate if and how external factors could influence a largely used reliability estimator - Cronbach Alpha. Several scales commonly used in marketing researches were tested, using a bootstrapping technique. Results show that important differences in the values of Cronbach Alpha are possible due to indirect influence from external factors - respondents’ age, gender, level of study, religiousness, rural/urban living, survey type and relevance of the research subject for the participants to the survey.

A progressive reduction of tetragonal distortion, heat of transition, Curie temperature, and relative dielectric constant has been observed on dense ${\mathrm{BaTiO}}_{3}$ ceramics with grain size decreasing from 1200 to $50\phantom{\rule{0.3em}{0ex}}\mathrm{nm}$. The correlations between grain size, extent of tetragonal distortion, and ferroelectric properties strongly support the existence of an intrinsic size effect. From the experimental trends the critical size for disappearance of ferroelectricity has been evaluated to be $10--30\phantom{\rule{0.3em}{0ex}}\mathrm{nm}$. The strong depression of the relative permittivity observed for the nanocrystalline ceramics can be ascribed to the combination of the intrinsic size effect and of the size-dependent ``dilution'' effect of a grain boundary ``dead'' layer.

In higher education institutions, entrepreneurship learning based on successful entrepreneurial role models may promote education for sustainable development. Several theoretical perspectives, such as the human capital theory, the entrepreneurial self-efficacy and self-determination theory, argue that entrepreneurship education is positively correlated with entrepreneurial intentions of students, as it provides adequate know-how and skills and motivates them to develop their entrepreneurial careers. In entrepreneurship education programmes, exposure to successful entrepreneurial models could be a significant factor for stimulating students’ confidence in their ability to start a business and for improving their attitudes towards entrepreneurship. This study aims (i) to identify characteristics viewed by students as being specific to a successful entrepreneur, (ii) to establish the influence of exposure to successful entrepreneurial role models (chosen by students) during entrepreneurship education classes on student entrepreneurial intentions, and (iii) to assess how such exposure influences the attitudes of students towards entrepreneurship. For this purpose, the authors ran a pilot experiment with 30 graduate students enrolled in a Business Creation course using a research methodology that combined qualitative techniques with quantitative measures. Content and statistical analyses were utilised to examine differences in student entrepreneurial intentions and attitudes towards entrepreneurship after being exposed to successful entrepreneurial models. Our study provides evidence that entrepreneurship education based on successful entrepreneurial role models may positively influence the entrepreneurial attitudes and intentions of students and could lead to higher orientation of student perception towards social benefits of entrepreneurship (new jobs) compared to financial ones (high income). However, our findings stress that if educators want to improve the efficiency of education focused on developing entrepreneurial skills, graduate programmes should be designed differently for business and non-business students, since studying successful entrepreneurial stories impacts these two groups differently.

This study explored the correlates of climate anxiety in a diverse range of national contexts. We analysed cross-sectional data gathered in 32 countries (N = 12,246). Our results show that climate anxiety is positively related to rate of exposure to information about climate change impacts, the amount of attention people pay to climate change information, and perceived descriptive norms about emotional responding to climate change. Climate anxiety was also positively linked to pro-environmental behaviours and negatively linked to mental wellbeing. Notably, climate anxiety had a significant inverse association with mental wellbeing in 31 out of 32 countries. In contrast, it had a significant association with pro-environmental behaviour in 24 countries, and with environmental activism in 12 countries. Our findings highlight contextual boundaries to engagement in environmental action as an antidote to climate anxiety, and the broad international significance of considering negative climate-related emotions as a plausible threat to wellbeing.

Combined measurements of Higgs boson production and decay using up to 80

In this study we assess the main determinants of banks’ profitability in EU27 over the period 2004-2011. We split the factors that influence bank profitability in two large groups: bank-specific (internal) factors and industry specific and macroeconomic (external) factors. We consider as proxy for banks profitability the return on average assets (ROAA) and the return on average equity (ROAE). The empirical findings are consistent with the expected results. Credit and liquidity risk, management efficiency, the diversification of business, the market concentration/competition and the economic growth have influence on bank profitability, both on ROAA and ROAE. An interesting and valuable result is the positive influence of competition on bank profitability in EU27.

A global existence and uniqueness result of the solution for multidimensional, time dependent, stochastic differential equations driven by a fractional Brownian motion with Hurst parameter H> 1 2 is proved.It is shown, also, that the solution has finite moments.The result is based on a deterministic existence and uniqueness theorem whose proof uses a contraction principle and a priori estimates.

With the rapid development of processing and storage technologies and the success of the Internet, computing resources have become cheaper, more powerful and more available than ever before. This technological trend has enabled the realization of a new computing model called cloud computing, in which resources are provided as general utilities that can be leased and released by users through the Internet in an on-demand fashion. The organizations are gaining more experience in the cloud and they start to shift more core business functions onto cloud platforms. Because of this fact, we are seeing that cloud adoption is significantly more complex than we imagined initially, particularly in terms of data management, system integration and the management of multiple cloud providers. Cloud computing is of growing interest to companies around the globe, but many are finding greater costs and greater obstacles to the adoption of cloud computing than they anticipated. In this case, is cloud computing still able to deliver all the promises? In this paper we will analyze from a company's point of view the factors that need to be considered by an enterprise when making the decision of using cloud computing. Some of the companies are moving towards cloud computing just because it is the latest trend in information technology. On the other hand, other companies cannot even take into consideration the idea of having their sensitive data outside their premises. Both of these cases represent companies that are just not very well informed. We are not sustaining that cloud computing is a perfect solution for everybody, but adopting it or not should be result of a very well informed analysis. We will analyze the positive and negative aspects of each of the following factors: integration with existing IT infrastructure and existing software, costs, return on investment, performances, security. Also, we will correlate all these factors with the company size and business area in order to identify if or what type of cloud computing solution is suitable for their needs.

The ATLAS inner detector comprises three different sub-detectors: the pixel detector, the silicon strip tracker, and the transition-radiation drift-tube tracker. The Insertable $B$-Layer, a new innermost pixel layer, was installed during the shutdown period in 2014, together with modifications to the layout of the cables and support structures of the existing pixel detector. The material in the inner detector is studied with several methods, using a low-luminosity $\sqrt{s}=13$ TeV $pp$ collision sample corresponding to around $2.0\,\mathrm{nb}^{-1}$ collected in 2015 with the ATLAS experiment at the LHC. In this paper, the material within the innermost barrel region is studied using reconstructed hadronic interaction and photon conversion vertices. For the forward rapidity region, the material is probed by a measurement of the efficiency with which single tracks reconstructed from pixel detector hits alone can be extended with hits on the track in the strip layers. The results of these studies have been taken into account in an improved description of the material in the ATLAS inner detector simulation, resulting in a reduction in the uncertainties associated with the charged-particle reconstruction efficiency determined from simulation.

Abstract Aim The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation‐plot records to the habitats of the EUNIS system, use it to classify a European vegetation‐plot database, and compile statistically‐derived characteristic species combinations and distribution maps for these habitats. Location Europe. Methods We developed the classification expert system EUNIS‐ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set‐theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species‐to‐habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man‐made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert system EUNIS‐ESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment.

: This paper describes the reconstruction of electrons and photons with the ATLAS detector, employed for measurements and searches exploiting the complete LHC Run 2 dataset. An improved energy clustering algorithm is introduced, and its implications for the measurement and identification of prompt electrons and photons are discussed in detail. Corrections and calibrations that affect performance, including energy calibration, identification and isolation efficiencies, and the measurement of the charge of reconstructed electron candidates are determined using up to 81 fb -1 of proton-proton collision data collected at s = 13 TeV between 2015 and 2017.

Light-by-light scattering (γγ → γγ) is a quantum-mechanical process that is forbidden in the classical theory of electrodynamics. This reaction is accessible at the Large Hadron Collider thanks to the large electromagnetic field strengths generated by ultra-relativistic colliding lead ions. Using 480 μb−1 of lead–lead collision data recorded at a centre-of-mass energy per nucleon pair of 5.02 TeV by the ATLAS detector, here we report evidence for light-by-light scattering. A total of 13 candidate events were observed with an expected background of 2.6 ± 0.7 events. After background subtraction and analysis corrections, the fiducial cross-section of the process Pb + Pb (γγ) → Pb(∗) + Pb(∗)γγ, for photon transverse energy ET > 3 GeV, photon absolute pseudorapidity |η| < 2.4, diphoton invariant mass greater than 6 GeV, diphoton transverse momentum lower than 2 GeV and diphoton acoplanarity below 0.01, is measured to be 70 ± 24 (stat.) ± 17 (syst.) nb, which is in agreement with the standard model predictions. Quantum electrodynamics predicts a rare process in which light is scattered by light. The ATLAS Collaboration reports signs of this elusive effect in the collisions of ultra-relativistic lead ions.

With incidence of antimicrobial resistance rising globally, there is a continuous need for development of new antimicrobial molecules. Phenolic compounds having a versatile scaffold that allows for a broad range of chemical additions; they also exhibit potent antimicrobial activities which can be enhanced significantly through functionalization. Synthetic routes such as esterification, phosphorylation, hydroxylation or enzymatic conjugation may increase the antimicrobial activity of compounds and reduce minimal concentrations needed. With potent action mechanisms interfering with bacterial cell wall synthesis, DNA replication or enzyme production, phenolics can target multiple sites in bacteria, leading to a much higher sensitivity of cells towards these natural compounds. The current review summarizes some of the most important knowledge on functionalization of natural phenolic compounds and the effects on their antimicrobial activity.

Proteomics is the field of study that includes the analysis of proteins, from either a basic science prospective or a clinical one. Proteins can be investigated for their abundance, variety of proteoforms due to post-translational modifications (PTMs), and their stable or transient protein-protein interactions. This can be especially beneficial in the clinical setting when studying proteins involved in different diseases and conditions. Here, we aim to describe a bottom-up proteomics workflow from sample preparation to data analysis, including all of its benefits and pitfalls. We also describe potential improvements in this type of proteomics workflow for the future.

Abstract The algorithms used by the ATLAS Collaboration during Run 2 of the Large Hadron Collider to identify jets containing b -hadrons are presented. The performance of the algorithms is evaluated in the simulation and the efficiency with which these algorithms identify jets containing b -hadrons is measured in collision data. The measurement uses a likelihood-based method in a sample highly enriched in $$t{\bar{t}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>t</mml:mi><mml:mover><mml:mrow><mml:mi>t</mml:mi></mml:mrow><mml:mrow><mml:mo>¯</mml:mo></mml:mrow></mml:mover></mml:mrow></mml:math> events. The topology of the $$t \rightarrow W b$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>t</mml:mi><mml:mo>→</mml:mo><mml:mi>W</mml:mi><mml:mi>b</mml:mi></mml:mrow></mml:math> decays is exploited to simultaneously measure both the jet flavour composition of the sample and the efficiency in a transverse momentum range from 20 to 600 GeV. The efficiency measurement is subsequently compared with that predicted by the simulation. The data used in this measurement, corresponding to a total integrated luminosity of 80.5 $$\hbox {fb}^{-1}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mtext>fb</mml:mtext><mml:mrow><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math> , were collected in proton–proton collisions during the years 2015–2017 at a centre-of-mass energy $$\sqrt{s}=$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msqrt><mml:mi>s</mml:mi></mml:msqrt><mml:mo>=</mml:mo></mml:mrow></mml:math> 13 TeV. By simultaneously extracting both the efficiency and jet flavour composition, this measurement significantly improves the precision compared to previous results, with uncertainties ranging from 1 to 8% depending on the jet transverse momentum.

Abstract Research on group identification has shown it to be a surprisingly weak predictor of intentions to take large‐scale social action. The weak links may exist because researchers have not always examined identification with the type of group that is most relevant for predicting action. Our focus in two studies (one in Romania and one in Australia, both Ns = 101) was on opinion‐based groups (i.e. groups formed around shared opinions). We found that social identification with opinion‐based groups was an excellent predictor of political behavioural intentions, particularly when items measuring identity certainty were included. The results provide clear evidence of the role of social identity constructs for predicting commitment to social action and complement analyses of politicised collective identity and crowd behaviour. Copyright © 2006 John Wiley &amp; Sons, Ltd.

The developments of the open-source OpenMolcas chemistry software environment since spring 2020 are described, with a focus on novel functionalities accessible in the stable branch of the package or via interfaces with other packages. These developments span a wide range of topics in computational chemistry and are presented in thematic sections: electronic structure theory, electronic spectroscopy simulations, analytic gradients and molecular structure optimizations, ab initio molecular dynamics, and other new features. This report offers an overview of the chemical phenomena and processes OpenMolcas can address, while showing that OpenMolcas is an attractive platform for state-of-the-art atomistic computer simulations.

Entrepreneurs bring an enormous contribution to a country’s economic growth. Developing individual’s interest into new venture creation represents an important asset, especially for less developed countries where entrepreneurial activities are fundamental in enhancing economic growth. The recent economic crisis turned the attention of European policymakers towards entrepreneurship as a driving force for the creation of new job opportunities, regional/national competitiveness and growth. The aim of this article is to verify what relations are between locus of control, need for achievement and entrepreneurial intention of youth, following a cognitive approach and how much entrepreneurial education consolidates entrepreneurial skills and informs the young that entrepreneurship is a career option. To analyse entrepreneurial intentions, locus of control, need for achievement and entrepreneurial education in the context of Romania, this research used a quantitative design based on the answers to the questionnaire conducted during March 2017 to October 2017 on a sample of 270 students from two important Romanian universities. From the methodological point of view, several hypotheses have been developed and tested using multivariate logistic regression estimates, frequency analysis, internal consistency reliability of the constructs and moderating effects. The results illustrate that locus of control, need for achievement and entrepreneurial education proved to be important determinants for venture creation among young students, both independently and under the action of control variables. Also, respondents’ gender had a significant influence on one’s intention of opening a business in the future, with males being more inclined to become entrepreneurs than females.

This paper describes the implementation and performance of a particle flow algorithm applied to 20.2 fb[Formula: see text] of ATLAS data from 8 TeV proton-proton collisions in Run 1 of the LHC. The algorithm removes calorimeter energy deposits due to charged hadrons from consideration during jet reconstruction, instead using measurements of their momenta from the inner tracker. This improves the accuracy of the charged-hadron measurement, while retaining the calorimeter measurements of neutral-particle energies. The paper places emphasis on how this is achieved, while minimising double-counting of charged-hadron signals between the inner tracker and calorimeter. The performance of particle flow jets, formed from the ensemble of signals from the calorimeter and the inner tracker, is compared to that of jets reconstructed from calorimeter energy deposits alone, demonstrating improvements in resolution and pile-up stability.

Rural areas are exposed to severe environmental pollution issues fed by industrial and agricultural activities combined with poor waste and sanitation management practices, struggling to achieve the United Nations’ Sustainable Development Goals (SDGs) in line with Agenda 2030. Rural communities are examined through a “dual approach” as both contributors and receivers of plastic pollution leakage into the natural environment (through the air–water–soil–biota nexus). Despite the emerging trend of plastic pollution research, in this paper, we identify few studies investigating rural communities. Therefore, proxy analysis of peer-reviewed literature is required to outline the significant gaps related to plastic pollution and plastic waste management issues in rural regions. This work focuses on key stages such as (i) plastic pollution effects on rural communities, (ii) plastic pollution generated by rural communities, (iii) the development of a rural waste management sector in low- and middle-income countries in line with the SDGs, and (iv) circular economy opportunities to reduce plastic pollution in rural areas. We conclude that rural communities must be involved in both future plastic pollution and circular economy research to help decision makers reduce environmental and public health threats, and to catalyze circular initiatives in rural areas around the world, including less developed communities.