An Optimized Combination of a Large Grid Connected PV System along with Battery Cells and a Diesel Generator

Environmental, economical and technical benefits of photovoltaic (PV) systems make them to be used in many countries. The main characteristic of PV systems is the fluctuations of their output power. Hence, high penetration of PV systems into electric network could be detrimental to overall system performance. Furthermore, the fluctuations in the output power of PV systems make it difficult to predict their output, and to consider them in generation planning of the units. The main objective of this paper is to propose a hybrid method which can be used to control and reduce the power fluctuations generated from large grid- connected PV systems. The proposed method focuses on using a suitable storage battery along with curtailment of the generated power by operating the PV system below the maximum power point (MPP) and deployment of a diesel generator. These methods are analyzed to investigate the impacts of implementing them on the economical benefits that the PV system owner could gain. To maximize the revenues, an optimization problem is solved

Discovering Pattern Using Automata

Most documents written by humans are not just a collection of words, sentences and paragraphs combined at random. It is believed that there is a pattern hidden behind those piles of characters that represents the author\u27s style of writing. In the previous works and in this thesis, we assumed that the aforementioned belief was a true statement and tried to discover and represent the pattern by automata machines. We used the Alergia algorithm to form an automaton from a prefix-tree-accepter. By testing, we verified that the Alergia algorithm was correctly implemented in our software. Our tests showed that we captured only the patterns of the collections of single sentences in a book. Unfortunately, that is not the full content of a book. Therefore, establishing variable chopping units or a less forceful chopping approach would be a promising approach

Using 360-degree multi-source feedback to evaluate professionalism in surgery departments: an Iranian perspective

Background: Medical professionalism helps physicians adopt a proper and good healing action for the patients based on their particular circumstance. This study was conducted to assess professionalism in surgical residents, using a 360-degree evaluation technique in several teaching hospitals in Tehran, Iran. Methods: This study was conducted on all the second and third year surgery residents from three university teaching hospitals in Tehran. Multi-source feedback questionnaire contained 10 questions on the residents’ professional behavior and was completed by the faculty and staff members (nurses, operation room staff, and medical assistants) as well as other surgery residents, interns and patients to evaluate each resident. Response rates were used to determine feasibility for each of the respondent groups and the mean and standard deviation score for each question was computed to determine the viability of the items. Reliability was assessed using alpha Cronbach coefficient for each respondent group. The correlation between these scores and the residents’ final and OSCE grade was also assessed. Results: The internal consistency reliability for 360-degree rating was 0.889. There was no significant difference in the residents’ score in different hospitals. While male residents obtained higher total score, there was no significant difference between them. The residents, however, obtained lower scores compared to the staff. The highest score was recorded for question 6, suggesting that the residents treated the patients regardless of their socioeconomic status. Conclusion: This study revealed a strong agreement between the results gathered from different respondents, confirming the reliability of the questionnaire and the respondents’ unbiased response. It also revealed that the residents did well in the whole test, showing they were conscientious and learning to become medical professionals

Compare Clinical Competence and Job Satisfaction Among Nurses Working in Both University and Non-University Hospital in Bushehr 2015

Background: Nurses are the biggest component of the health care system in the world and their job satisfaction and clinical competence affect performance and success of the organization. This study aimed to determine and compare the clinical competence and job satisfaction of nurses in both academic and nonacademic hospitals in Bushehr in 2015. Materials & Methods: In this cross-sectional study, 257 nurses were studied in two hospitals of Bushehr city selected by census method. Data was collected by using valid and reliable Nurse Clinical Competence and Job Satisfaction Inventory questionnaires. Data analyzed by using SPSS- 21, and descriptive statistics, t-test, and ANOVA and Pearson correlation coefficient. Statistical significance was set at P< 0.05. Results: Findings showed that there were no significant diffrences between academic hospital nurses' job satisfaction with 126.96±29.34 and non-academic hospital with 128.31±23.26. Also, there were a significant diffrences between total score of nurses' clinical competence in academic hospital 62.18±18.09 and in nonacademic hospital 67.78±17.64. There were a significant and direct association between the clinical competence and job satisfaction of nurses in both hospitals (p≤0.05). Conclusion: Although nurses clinical competence and job satisfaction in both hospitals were assessed at desirable level but both criteria were higher in non-university hospital nurses. It is nessessary that Nurse Manager’s of academic hospitals should pay attention to assessment and improvement of nurse clinical competence and job satisfactio

Comparative Evaluation of RGB-D SLAM Methods for Humanoid Robot Localization and Mapping

In this paper, we conducted a comparative evaluation of three RGB-D SLAM (Simultaneous Localization and Mapping) algorithms: RTAB-Map, ORB-SLAM3, and OpenVSLAM for SURENA-V humanoid robot localization and mapping. Our test involves the robot to follow a full circular pattern, with an Intel RealSense D435 RGB-D camera installed on its head. In assessing localization accuracy, ORB-SLAM3 outperformed the others with an ATE of 0.1073, followed by RTAB-Map at 0.1641 and OpenVSLAM at 0.1847. However, it should be noted that both ORB-SLAM3 and OpenVSLAM faced challenges in maintaining accurate odometry when the robot encountered a wall with limited feature points. Nevertheless, OpenVSLAM demonstrated the ability to detect loop closures and successfully relocalize itself within the map when the robot approached its initial location. The investigation also extended to mapping capabilities, where RTAB-Map excelled by offering diverse mapping outputs, including dense, OctoMap, and occupancy grid maps. In contrast, both ORB-SLAM3 and OpenVSLAM provided only sparse maps.Comment: 6 pages, 11th RSI International Conference on Robotics and Mechatronics (ICRoM 2023

An assessment on potential long-term health effects caused by antibiotic resistance marker genes in genetically modified organisms based on antibiotic usage and resistance patterns in Norway.

Source at https://vkm.no/Usage of antibiotics selects for resistant bacteria, resulting in reduced treatment options, and increased morbidity and mortality from microbial infections. Development of resistance in susceptible bacteria can occur through spontaneous mutation or horizontal gene transfer (HGT). Our current understanding of resistance development in bacterial pathogens is more descriptive than predictive in nature. That is, whereas the acquisition or development of new resistance determinants in bacteria can be retrospectively described relatively easily at the molecular, species and geographical distribution levels, the initial horizontal transfer events, the resistance gene donor, and the environmental location and conditions that produced the first generation of the resistant bacteria remain largely unknown. Without this latter knowledge and without a clear understanding of directional selection and genetic drift in natural bacterial populations, it is impossible to predict accurately further resistance development occurring through HGT. Some of the antibiotic resistance marker (ARM) genes used in the production of genetically modified organisms (GMO) encode resistance to antibiotics in clinical and veterinary use. Thus, concerns have been raised that the large-scale release of such genes in commercialized GMOs may increase the rate of, and broaden the locations where, bacteria horizontally acquire resistance genes

Power Management in a Utility Connected Micro-Grid with Multiple Renewable Energy Sources

As an efficient alternative to fossil fuels, renewable energy sources have attained great attention due to their sustainable, cost-effective, and environmentally friendly characteristic. However, as a deficiency, renewable energy sources have low reliability because of their non-deterministic and stochastic generation pattern. The use of hybrid renewable generation systems along with the storage units can mitigate the reliability problem. Hence, in this paper, a grid connected hybrid micro-grid is presented, which includes wind and photovoltaic resources as the primary power sources and a hydrogen storage system (including fuel cell and electrolyzer) as a backup. A new power management strategy is proposed to perform a proper load sharing among the micro-grid units. Hybrid (distributed/central) control method is applied for the realization of the control objectives such as DC bus voltage regulation, power factor control, synchronous grid connection, and power fluctuation suppression. Distributed controllers have the task of fulfilling local control objectives such as MPPT implementation and storage unit control. On the other hand, the central control unit is mainly responsible for power management in the micro-grid. Performance and effectiveness of the proposed power management strategy for the presented micro-grid are verified using a simulation study

Improving the Effect of Electric Vehicle Charging on Imbalance Index in the Unbalanced Distribution Network Using Demand Response Considering Data Mining Techniques

With the development of electrical network infrastructure and the emergence of concepts such as demand response and using electric vehicles for purposes other than transportation, knowing the behavioral patterns of network technical specifications to manage electrical systems has become very important optimally. One of the critical parameters in the electrical system management is the distribution network imbalance. There are several ways to improve and control network imbalances. One of these ways is to detect the behavior of bus imbalance profiles in the network using data analysis. In the past, data analysis was performed for large environments such as states and countries. However, after the emergence of smart grids, behavioral study and recognition of these patterns in small-scale environments has found a fundamental and essential role in the deep management of these networks. One of the appropriate methods in identifying behavioral patterns is data mining. This paper uses the concepts of hierarchical and k-means clustering methods to identify the behavioral pattern of the imbalance index in an unbalanced distribution network. For this purpose, first, in an unbalanced network without the electric vehicle parking, the imbalance profile for all busses is estimated. Then, by applying the penetration coefficient of 25 and 75 for electric vehicles in the network, charging/discharging effects on the imbalance profile is determined. Then, by determining the target cluster and using demand response, the imbalance index is improved. This method reduces the number of busses competing in demand response programs. Next, using the concept of classification, a decision tree is constructed to minimize metering time

Critical Thinking as an Essential Factor in EFL Teacher Educators’ Professional Development: a Transformative Learning Paradigm

The present qualitative research sought to investigate EFL teacher educators’ experiences and attitudes toward critical thinking and its role in teacher professional development. The adopted design was a case study and the theoretical framework was the theory of transformative learning (Mezirow, 1978). For the data collection purpose, 30 EFL teacher educators participated in in-depth interviews. The  whole procedure of  the data collection was audiotaped for further reference in data analysis. The interviews were transcribed to familiarize with the data and the transcribed interviews were member checked with the participants. The collected data were analyzed through reflective thematic analysis. The data analyzed paved the way for generating three themes: cognition, metacognition, and personal growth/self attainment. The findings of the study comprise a number of implicatios for both theory and practice. One aspect of our contribution is that the notion of critical thinking can be conceived as more than cognitive and metacognitive one; it should be conceptualized as possessing both facets as well as other possible subsets. Beyond that, we suggest that critical thinking should be conjectured as being both a process and a product

Genealogical typing of Neisseria meningitidis

Despite the increasing popularity of multilocus sequence typing (MLST), the most appropriate method for characterizing bacterial variation and facilitating epidemiological investigations remains a matter of debate. Here, we propose that different typing schemes should be compared on the basis of their power to infer clonal relationships and investigate the utility of sequence data for genealogical reconstruction by exploiting new statistical tools and data from 20 housekeeping loci for 93 isolates of the bacterial pathogen Neisseria meningitidis. Our analysis demonstrated that all but one of the hyperinvasive isolates established by multilocus enzyme electrophoresis and MLST were grouped into one of six genealogical lineages, each of which contained substantial variation. Due to the confounding effect of recombination, evolutionary relationships among these lineages remained unclear, even using 20 loci. Analyses of the seven loci in the standard MLST scheme using the same methods reproduced this classification, but were unable to support finer inferences concerning the relationships between the members within each complex