The effectiveness of policymakers' decision-making in times of crisis depends largely on their ability to integrate and make sense of information. The COVID-19 crisis confronts governments with the ...difficult task of making decisions in the interest of public health and safety. Essentially, policymakers have to react to a threat, of which the extent is unknown, and they are making decisions under time constraints in the midst of immense uncertainty. The stakes are high, the issues involved are complex and require the careful balancing of several interests, including (mental) health, the economy, and human rights. These circumstances render policymakers' decision-making processes vulnerable to errors and biases in the processing of information, thereby increasing the chances of faulty decision-making processes with poor outcomes. Prior research has identified three main information-processing failures that can distort group decision-making processes and can lead to negative outcomes: (1) failure to search for and share information, (2) failure to elaborate on and analyze information that is not in line with earlier information and (3) failure to revise and update conclusions and policies in the light of new information. To date, it has not yet been explored how errors and biases underlying these information-processing failures impact decision-making processes in times of crisis. In this narrative review, we outline how groupthink, a narrow focus on the problem of containing the virus, and escalation of commitment may pose real risks to decision-making processes in handling the COVID-19 crisis and may result in widespread societal damages. Hence, it is vital that policymakers take steps to maximize the quality of the decision-making process and increase the chances of positive outcomes as the crisis goes forward. We propose group reflexivity-a deliberate process of discussing team goals, processes, or outcomes-as an antidote to these biases and errors in decision-making. Specifically, we recommend several evidence-based reflexivity tools that could easily be implemented to counter these information-processing errors and improve decision-making processes in uncertain times.
The effectiveness of decision-making teams depends largely on their ability to integrate and make sense of information. Consequently, teams which more often use majority decision-making may make ...better quality decisions, but particularly so when they also have task representations which emphasize the elaboration of information relevant to the decision, in the absence of clear leadership. In the present study we propose that (a) majority decision-making will be more effective when task representations are shared, and that (b) this positive effect will be more pronounced when leadership ambiguity (i.e., team members’ perceptions of the absence of a clear leader) is high. These hypotheses were put to the test using a sample comprising 81 teams competing in a complex business simulation for seven weeks. As predicted, majority decision-making was more effective when task representations were shared, and this positive effect was more pronounced when there was leadership ambiguity. The findings extend and nuance earlier research on decision rules, the role of shared task representations, and leadership clarity.
The use of photovoltaics for electricity generation purposes has recorded one of the largest increases in the field of renewable energies. The energy production of a grid-connected PV system depends ...on various factors. In a wide sense, it is considered that the annual energy provided by a generator is directly proportional to the annual radiation incident on the plane of the generator and to the installed nominal power. However, a range of factors is influencing the expected outcome by reducing the generation of energy.
The aim of this study is to compare the results of four different methods for estimating the annual energy produced by a PV generator: three of them are classical methods and the fourth one is based on an artificial neural network developed by the R&D Group for Solar and Automatic Energy at the University of Jaen.
The results obtained shown that the method based on an artificial neural network provides better results than the alternative classical methods in study, mainly due to the fact that this method takes also into account some second order effects, such as low irradiance, angular and spectral effects.
► It is considered that the annual energy provided by a PV generator is directly proportional to the annual radiation incident on the plane of the generator and to the installed nominal power. ► A range of factors are influencing the expected outcome by reducing the generation of energy (mismatch losses, dirt and dust, Ohmic losses,.). ► The aim of this study is to compare the results of four different methods for estimating the annual energy produced by a PV generator: three of them are classical methods and the fourth one is based on an artificial neural network. ► The results obtained shown that the method based on an artificial neural network provides better results than the alternative classical methods in study. While classical methods have only taken into account temperature losses, the method based in an ANN has taken into account temperature losses, low irradiation losses and spectral and angular losses.
In the photovoltaic field, manufacturers provide ratings for PV modules for conditions referred to as standard test conditions (STC). However, these conditions rarely occur outdoors, so the ...usefulness and applicability of the indoors' characterisation in standard test conditions of PV modules are a controversial issue. Therefore, to carry out photovoltaic engineering well, a suitable characterisation of PV module electrical behaviour (V–I curves) is necessary. The IDEA Research Group from Jaén University has developed a method based on artificial neural networks (ANNs) to electrical characterisation of PV modules. An ANN has been developed which is able to generate V–I curves of Si-crystalline PV modules for any irradiance and module cell temperature. The results show that the proposed ANN introduces a good accurate prediction for Si-crystalline PV modules' performance when compared with the measured values.
The integration of grid-connected photovoltaic (GCPVS) systems into urban buildings is very popular in industrialized countries. Many countries enhance the international collaboration efforts which ...accelerate the development and deployment of photovoltaic solar energy as a significant and sustainable renewable energy option. A previous method, based on artificial neural networks (ANNs), has been developed to electrical characterisation of PV modules. This method was able to generate V–I curves of si-crystalline PV modules for any irradiance and module cell temperature. The results showed that the proposed ANN introduced a good accurate prediction for si-crystalline PV modules performance when compared with the measured values. Now, this method, based on ANNs, is going to be applied to obtain a suitable value of the power provided by a photovoltaic installation. Specifically this method is going to be applied to obtain the power provided by a particular installation, the “Univer generator”, since modules used in these works were the same as the ones used in this photovoltaic generator.
The presence of PV modules made with new technologies and materials is increasing in PV market, in special Thin Film Solar Modules (TFSM). They are ready to make a substantial contribution to the ...world's electricity generation. Although Si wafer-based cells account for the most of increase, technologies of thin film have been those of the major growth in last three years. During 2007 they grew 133%.
On the other hand, manufacturers provide ratings for PV modules for conditions referred to as Standard Test Conditions (STC). However, these conditions rarely occur outdoors, so the usefulness and applicability of the indoors characterisation in standard test conditions of PV modules is a controversial issue. Therefore, to carry out a correct photovoltaic engineering, a suitable characterisation of PV module electrical behaviour is necessary. The IDEA Research Group from Jaén University has developed a method based on artificial neural networks (ANNs) to electrical characterisation of PV modules. An ANN was able to generate
V–
I curves of si-crystalline PV modules for any irradiance and module cell temperature. The results show that the proposed ANN introduces a good accurate prediction for si-crystalline PV modules performance when compared with the measured values. Now, this method is going to be applied for electrical characterisation of PV CIS modules. Finally, a comparative study with other methods, of electrical characterisation, is done.
We sought to develop a low-fidelity simulation-based curriculum for pediatric residents in Rwanda utilizing either rapid cycle deliberate practice (RCDP) or traditional debriefing, and to determine ...whether RCDP leads to greater improvement in simulation-based performance and in resident confidence compared with traditional debriefing.
Pediatric residents at the Centre Hospitalier Universitaire de Kigali (CHUK) were randomly assigned to RCDP or traditional simulation and completed a 6 month-long simulation-based curriculum designed to improve pediatric resuscitation skills. Pre- and post- performance was assessed using a modified version of the Simulation Team Assessment Tool (STAT). Each video-taped simulation was reviewed by two investigators and inter-rater reliability was assessed. Self-confidence in resuscitation, pre- and post-simulation, was assessed by Likert scale survey. Analyses were conducted using parametric and non-parametric testing, ANCOVA and intra-class correlation coefficients (ICC).
There was a 21% increase in pre- to post-test performance in both groups (p < 0.001), but no difference between groups (mean difference - 0.003%; p 0.94). Inter-rater reliability was exceptional with both pre and post ICCs ≥0.95 (p < 0.001). Overall, self-confidence scores improved from pre to post (24.0 vs. 30.0 respectively, p < 0.001), however, the there was no difference between the RCDP and traditional groups.
Completion of a six-month low-fidelity simulation-based curriculum for pediatric residents in Rwanda led to statistically significant improvement in performance on a simulated resuscitation. RCDP and traditional low-fidelity simulation-based instruction may both be valuable tools to improve resuscitation skills in pediatric residents in resource-limited settings.
In 2012, Botswana embarked on an organized public approach to prehospital medicine. One goal of the Ministry of Health (MOH) was to improve provider education regarding patient stabilization and ...resuscitation. Simulation-based instruction is an effective educational strategy particularly for high-risk, low-frequency events. In collaboration with partners in the United States, the team created a short, simulation-based course to teach and update prehospital providers on common field responses in this resource-limited setting. The objective of this study was to evaluate an educational program for Botswanan prehospital providers via written and simulation-based examinations.
We developed a two-day course based on a formal needs assessment and MOH leadership input. The subject matter of the simulation scenarios represented common calls to the prehospital system in Botswana. Didactic lectures and facilitated skills training were conducted by U.S. practitioners who also served as instructors for a rapid-cycle, deliberate practice simulation education model and simulation-based testing scenarios. Three courses, held in three cities in Botswana, were offered to off-duty MOH prehospital providers, and the participants were evaluated using written multiple-choice tests, videotaped traditional simulation scenarios, and self-efficacy surveys.
Collectively, 31 prehospital providers participated in the three courses. The mean scores on the written pretest were 67% (standard deviation SD, 10) and 85% (SD, 7) on the post-test (p < 0.001). The mean scores for the simulation were 42% (SD, 14.2) on the pretest and 75% (SD, 11.3) on the post-test (p < 0.001). Moreover, the intraclass correlation coefficient scores between reviewers were highly correlated at 0.64 for single measures and 0.78 for average measures (p < 0.001 for both). Twenty-one participants (68%) considered the course "extremely useful."
Botswanan prehospital providers who participated in this course significantly improved in both written and simulation-based performance testing. General feedback from the participants indicated that the simulation scenarios were the most useful and enjoyable aspects of the course. These results suggest that this curriculum can be a useful educational tool for teaching and reinforcing prehospital care concepts in Botswana and may be adapted for use in other resource-limited settings.
Applications for sizing Photovoltaic (PV) self-consumption systems have been studied over recent years in order to achieve either an optimization of the cost of energy, the investment cost or any ...economic profitability criteria. However, PV self-consumption systems at the residential or small business level can be designed with the aims of reducing the electricity consumption from the conventional local grid and achieving competitiveness with grid electricity prices. These criteria will provide not only greater environmental benefits, security and independence of the grid but it will make the cost of PV self-consumption electricity competitive with electricity prices from the power grid. In this sense, this paper proposes a method to size the generator for a PV self-consumption system based on cost-competitiveness, maximizing direct self-consumption. The method will be applied for three different households located in the south of Spain using the household daily consumption and generation profiles for a single year. However, the method here illustrated can be applied to other countries. The results obtained suggest that residential direct PV self-consumption systems with an annual global irradiation at the optimal tilt angle higher than 1000 kWh/(m2·year) may be a feasible investment to future owners of these systems.
•A method to size PV generators based on the cost of PV self-consumed electricity has been developed.•The method is based on cost–competitiveness, maximizing direct self-consumption.•Real household load data have been used to illustrate the method.•In Spain PV self-consumption may be cost-competitive for irradiation >1000 kWh/(m2 y).•The method can be also used when considering batteries and Demand side Management.
In order to develop future projects in the field of photovoltaic solar energy, it is essential to accurately know the potential solar resources. There are many methods to estimate the incident solar ...radiation in a certain place. However, most of them are very expensive or do not have the ideal characteristics for good monitoring of a particular photovoltaic installation. For these reasons, an electronic device connected to the internet of things (IoT) is presented in this paper which manages to measure global radiation in photovoltaic applications. The device developed has been patented in the Spanish Patent and Trademark Office. It presents some features that make it very suitable to measure photovoltaic installations with the advantage of being a low cost and very reliable device. The device has been tested to determine global horizontal irradiance obtaining a correlation coefficient R2 = 0.994.
PDF
