Techno-economical Analysis of Hybrid PV-WT-Hydrogen FC System for a Residential Building with Low Power Consumption

This paper shows a techno-economical analysis on performance indicators of hybrid solar-wind-hydrogen power generation system which supply with electricity a low - energy building, located in Cluj-Napoca. The case study had the main objectives, as follows: cost estimation, evaluation of energy and environmental performance for a fuel cell integrated into a small-scale hybrid system power generation and estimation of electrolytic hydrogen production based on renewable energy resources available on the proposed site. The results presented in this paper illustrate a case study for location Cluj-Napoca. The wind and solar resource can play an important role in energy needs for periods with "peak load" or intermittent energy supply. However, hydrogen production is dependent directly proportional to the availability of renewable energy resources, but the hydrogen can be considered as a storage medium for these renewable resources. It can be said that this study is a small-scale model analysis, a starting point for a detailed analysis of Romania's potential electrolytic production of hydrogen from renewable resources and supply electricity using fuel cells integrated into hybrid energy systems

How to assess the acceptance of an electronic health record system?

Being able to access a patient’s clinical data in due time is critical to any medical setting. Clinical data is very diverse both in content and in terms of which system produces it. The Electronic Health Record (EHR) aggregates a patient’s clinical data and makes it available across different systems. Considering that user’s resistance is a critical factor in system implementation failure, the understanding of user behavior remains a relevant object of investigation. The purpose of this paper is to outline how we can assess the technology acceptance of an EHR using the Technology Acceptance Model 3 (TAM3) and the Delphi methodology. An assessment model is proposed in which findings are based on the results of a questionnaire answered by health professionals whose activities are supported by the EHR technology. In the case study simulated in this paper, the results obtained showed an average of 3 points and modes of 4 and 5, which translates to a good level of acceptance.The work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019.The work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope DSAIPA/DS/0084/2018

A diallel analysis of a maize donor population response to In vivo maternal haploid induction II: haploid male fertility

Doubled haploid (DH) lines are used in maize breeding to accelerate the breeding cycle and create homogenous inbred lines in as little as two seasons. These pure inbred lines allow breeders to quickly evaluate new cross combinations. There are two important steps in creating DH lines: 1) generation and selection of haploid progeny, and 2) genome doubling to create fertile, diploid inbreds. Colchicine is widely used to artificially double genomes in haploid plants, which is hazardous, expensive, and time consuming. In this study, three public inbred lines A427, A637, and NK778 were found to have substantial haploid male fertility (HMF). A six-parent full diallel between these three HMF lines and three non-HMF lines was created and HMF was scored. Diallel analysis revealed significant GCA estimates of up to 17% for HMF, as well as significant SCA effects of up to 25%. No significant reciprocal effects were found. HMF is promising to be incorporated into elite maize breeding programs to potentially overcome the need of using colchicine treatments for genome doubling. Colchicine aided doubling success rates varying from almost zero to 30%. HMF has an advantage over artificial genome doubling both in terms of increased success rates and decreased costs for DH line production

Am¯ir-i kab¯ir / A

A large amount of social feedback expressed by social signals (e.g. like, +1, rating) are assigned to web resources. These signals are often exploited as additional sources of evidence in search engines. Our objective in this paper is to study the impact of the new social signals, called Facebook reactions (love, haha, angry, wow, sad) in the retrieval. These reactions allow users to express more nuanced emotions compared to classic signals (e.g. like, share). First, we analyze these reactions and show how users use these signals to interact with posts. Second, we evaluate the impact of each such reaction in the retrieval, by comparing them to both the textual model without social features and the first classical signal (like-based model). These social features are modeled as document prior and are integrated into a language model. We conducted a series of experiments on IMDb dataset. Our findings reveal that incorporating social features is a promising approach for improving the retrieval ranking performance

IGeneration's social media usage in retrieving information related to healthcare education: A web-based survey among Italian and Romanian undergraduate medical students

The aim of our study was to assess medical undergraduate student's preferences associated with the value of information/learning methods via social media. An electronic questionnaire was developed and applied to undergraduate medical students from two university centers: Foggia (Italy) and Cluj-Napoca (Romania). 1196 answers were collected, 326 from the Italian university, and 870 from the Romanian university. Students use smartphones to access Facebook, from home, in average 1-3 hours daily. Along with school bibliography and Internet, social media is an active part of the academic life of students. Social media is used to search for information about a specific medical topic or to manage daily student activities. Romanians frequently share information with other colleagues or search for topics related to courses taught at school. The medical students use social media for academic purposes similarly in Italy and Romania

Social Priors to Estimate Relevance of a Resource

International audienceIn this paper we propose an approach that exploits social data associated with a Web resource to measure its a priori relevance. We show how these interaction traces left by the users on the resources, which are in the form of social signals as the number of like and share, can be exploited to quantify social properties such as popularity and reputation. We propose to model these properties as a priori probability that we integrate into language model. We evaluated the effectiveness of our approach on IMDb dataset containing 167438 resources and their social signals collected from several social networks. Our experimental results are statistically significant and show the interest of integrating social properties in a search model to enhance the information retrieval