Dynamics of Technical Efficiency and Productivity Change under Central Planning: The Romanian Cement Industry 1966-1989

This paper investigates the time-path of efficiency and productivity change in the case of the Romanian cement industry 1966-1989. The analysis is based on different specifications of stochastic frontier models. The efficiency scores and the time paths of efficiency and technical change are found to vary substantially among models. The most important feature of the Romanian cement industry before the revolution in 1989 is a slow rate of productivity progress, and a corresponding catch up in the level of productive efficiency.Productivity change; productive efficiency; stochastic frontiers; time-varying efficiency; panel data; cement industry; Romania;

Dynamics of technical efficiency and productivity change under central planning: The Romainian cement industry 1966 - 1989

This paper investigates the time-path of efficiency and productivity change in the case of the Romanian cement industry 1966-1989. The analysis is based on different specifications of stochastic frontier models. The efficiency scores and the time paths of efficiency and technical change are found to vary substantially among models. The most important feature of the Romanian cement industry before the revolution in 1989 is a slow rate of productivity progress, and a corresponding catch up in the level of productive efficiency

A Collaborative GIS Solution for Public Transport

The recent years brought forward a large number of solutions for automating route finding given the increased availability of geographical data. However, such solutions rarely focus on mass transit or involve the user in submitting information in a collaborative manner to further improve the available dataset and provide additional services. The system presented here intends to fully address these issues by providing a modular, extensible collaborative one-stop-shop for public transport needs based on multi-source collaborative data inputs from both official and user-submitted sources with the usage of a flexible, genetic-algorithms based route-finding application. Implementation wise, the solution is based on an open-ended system of collaborative web-services with front-ends available on mobile, desktop and web platforms. The proposed solution will not only provide users with a powerful technical solution, but will address the theoretical concern by which the increase of available GIS data is solely used for last-mile, map-like solution

Study of Temperature Coefficients for Parameters of Photovoltaic Cells

The temperature is one of the most important factors which affect the performance of the photovoltaic cells and panels along with the irradiance. The current voltage characteristics, I-V, are measured at different temperatures from 25°C to 87°C and at different illumination levels from 400 to 1000 W/m2, because there are locations where the upper limit of the photovoltaic cells working temperature exceeds 80°C. This study reports the influence of the temperature and the irradiance on the important parameters of four commercial photovoltaic cell types: monocrystalline silicon—mSi, polycrystalline silicon—pSi, amorphous silicon—aSi, and multijunction InGaP/InGaAs/Ge (Emcore). The absolute and normalized temperature coefficients are determined and compared with their values from the related literature. The variation of the absolute temperature coefficient function of the irradiance and its significance to accurately determine the important parameters of the photovoltaic cells are also presented. The analysis is made on different types of photovoltaics cells in order to understand the effects of technology on temperature coefficients. The comparison between the open-circuit voltage and short-circuit current was also performed, calculated using the temperature coefficients, determined, and measured, in various conditions. The measurements are realized using the SolarLab system, and the photovoltaic cell parameters are determined and compared using the LabVIEW software created for SolarLab system

Unveiling Vaccine Hesitancy on Twitter: Analyzing Trends and Reasons during the Emergence of COVID-19 Delta and Omicron Variants

Given the high amount of information available on social media, the paper explores the degree of vaccine hesitancy expressed in English tweets posted worldwide during two different one-month periods of time following the announcement regarding the discovery of new and highly contagious variants of COVID-19—Delta and Omicron. A total of 5,305,802 COVID-19 vaccine-related tweets have been extracted and analyzed using a transformer-based language model in order to detect tweets expressing vaccine hesitancy. The reasons behind vaccine hesitancy have been analyzed using a Latent Dirichlet Allocation approach. A comparison in terms of number of tweets and discussion topics is provided between the considered periods with the purpose of observing the differences both in quantity of tweets and the discussed discussion topics. Based on the extracted data, an increase in the proportion of hesitant tweets has been observed, from 4.31% during the period in which the Delta variant occurred to 11.22% in the Omicron case, accompanied by a diminishing in the number of reasons for not taking the vaccine, which calls into question the efficiency of the vaccination information campaigns. Considering the proposed approach, proper real-time monitoring can be conducted to better observe the evolution of the hesitant tweets and the COVID-19 vaccine hesitation reasons, allowing the decision-makers to conduct more appropriate information campaigns that better address the COVID-19 vaccine hesitancy