Abernathysweeney7548

Since December 2019 the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has produced an outbreak of pulmonary disease which has soon become a global pandemic, known as COronaVIrus Disease-19 (COVID-19). The new coronavirus shares about 82% of its genome with the one which produced the 2003 outbreak (SARS CoV-1). Both coronaviruses also share the same cellular receptor, which is the angiotensin-converting enzyme 2 (ACE2) one. In spite of these similarities, the new coronavirus has expanded more widely, more faster and more lethally than the previous one. Many researchers across the disciplines have used diverse modeling tools to analyze the impact of this pandemic at global and local scales. This includes a wide range of approaches - deterministic, data-driven, stochastic, agent-based, and their combinations - to forecast the progression of the epidemic as well as the effects of non-pharmaceutical interventions to stop or mitigate its impact on the world population. The physical complexities of mone design. Therefore, we compile the most relevant existing literature about modeling strategies against the virus to help modelers to navigate this fast-growing literature. We also keep an eye on future outbreaks, where the modelers can find the most relevant strategies used in an emergency situation as the current one to help in fighting future pandemics.Social media has enhanced integration between marketing and public relations. As such, public relations professionals have had to adapt and grow their knowledge and skillsets to stay relevant and current throughout the evolution of the digital landscape (Gesualdi, 2019). One of the growing areas of focus for public relations professionals has been customer service skills online. This specialization, often referred to as social care or social customer service, has been promoted and discussed heavily in industry circles and publications, but not in academic research. This study focuses on the survey results from 396 employers exploring the social media skills they most prefer university graduates to possess when entering the workforce. The results indicate that public relations and customer service are the social media skills most sought after by employers of university graduates ahead of proficiency in areas such as social media content production, strategy development and analytics. The potential implications of these findings to the public relations profession are examined and future research is also discussed.Dialogic communication has long been viewed as vital for effective organization-public relations. Yet, it is under-theorized whether and how organizations' disaster communication messages may embody dialogic communication principles, and how various dialogic features are associated with different public engagement outcomes on social media. Extending the Organization-Public Dialogic Communication (OPDC) framework to the context of social media-mediated disaster communication, we propose a multi-level framework to assess the dialogic capacity of Facebook messages sent by disaster management organizations during a natural disaster. Three levels of dialogic communication characteristics (i.e., message structure-level, topic-level, and linguistic level) are examined using content analysis and Linguistic Inquiry and Word Count (LIWC). Results identified media richness, correcting, and confirming topics as three consistent predictors of public engagement of all types. CPI-613 Meanwhile, there exhibit greater variations regarding how other topical features and linguistic characteristics are related to public's cognitive, emotional, and behavioral engagement during a disaster.Ant Colony algorithm has been applied to various optimisation problems, however, most of the previous work on scaling and parallelism focuses on Travelling Salesman Problems (TSPs). Although useful for benchmarks and new idea comparison, the algorithmic dynamics do not always transfer to complex real-life problems, where additional meta-data is required during solution construction. This paper explores how the benchmark performance differs from real-world problems in the context of Ant Colony Optimization (ACO) and demonstrate that in order to generalise the findings, the algorithms have to be tested on both standard benchmarks and real-world applications. ACO and its scaling dynamics with two parallel ACO architectures - Independent Ant Colonies (IAC) and Parallel Ants (PA). Results showed that PA was able to reach a higher solution quality in fewer iterations as the number of parallel instances increased. Furthermore, speed performance was measured across three different hardware solutions - 16 core CPU, 68 core Xeon Phi and up to 4 Geforce GPUs. State of the art, ACO vectorisation techniques such as SS-Roulette were implemented using C++ and CUDA. Although excellent for routing simple TSPs, it was concluded that for complex real-world supply chain routing GPUs are not suitable due to meta-data access footprint required. Thus, our work demonstrates that the standard benchmarks are not suitable for generalised conclusions.The Coverage Location Problem (CLP) seeks the best locations for service to minimize the total number of facilities required to meet all demands. This paper studies a new variation of this problem, called the Coverage Location Problem with Overlap Control (CLPOC). This problem models real contexts related to overloaded attendance systems, which require coverage zones with overlaps. Thus, each demand must be covered by a certain number of additional facilities to ensure that demands will be met even when the designated facility is unable to due to some facility issue. This feature is important in public and emergency services. We observe that this number of additional facilities is excessive in some demand points because overlaps among coverage zones occur naturally in CLP. The goal of the CLPOC is to control overlaps to prioritize regions with a high density population or to minimize the number of coverage zones for each demand point. In this paper, we propose a new mathematical model for the CLPOC that controls the overlap between coverage zones. We used a commercial solver to find the optimal solutions for available instances in the literature. The computational tests show that the proposed mathematical model found appropriate solutions in terms of number of demand points with minimum coverage zones and sufficient coverage zones for high demand points.Thermoelectric radiant panel system (TERP), requires no hydronic pipes, pumps and chillers and the size is compact in solid form. In this study, the main results include a new system model of TERP and some new findings on the system dynamic characteristics. The new model integrates finite difference method and state-space matrix, which is an integration of great simulation accuracy, high speed, and easy implementation. The thermal response time (TRT) and its asynchronism are confirmed and a new concept of AM (Asynchronism Magnitude) is defined to measure the degree of TRT asynchronism. Some new observations are obtained (1) Under a certain environment, AM becomes a constant even when different step changes of current are imposed; (2) The TRT asynchronism disappeared at the second stage when environmental condition is step changed. Three new definitions of TRT are proposed and compared. Finally, in order to realize the fast and accurate prediction of TRT for the use of system on-line control or fast evaluation under dynamic state, an artificial neural network-based model is proved to be effective. The dynamic analysis can offer a new paradigm to the evaluation, control and optimization of radiant cooling and other dynamic systems.'Energy efficiency first' is one of the key principles of the Energy Union, mainly due to it being the most cost effective way to reduce emissions, improving energy security, enhancing competitiveness and making energy consumption more affordable for all consumers. In light of the revised EU Energy Efficiency Directive, this paper discusses new developments brought by the EU together with the national case studies of Slovenia and Spain. Given that the paper has a specific focus on the industrial sector, it discusses the selected measures of the Energy Efficiency Directive, such as defined in Articles 7, 8, and 14, which are the most relevant to this sector. The paper also explores the newly issued integrated national energy and climate plans together with national measures and policies that support energy efficiency in industry, including the quantification of achieved and forecast energy savings in these two EU Member States.Improving the energy efficiency is a fundamental way to ensure energy security and sustainable development, and is also the requirement of supply-side structural reform of China's energy. This paper uses the DEA-BCC model to estimate China's energy efficiency at the provincial level, analyzes its regional differences from 2006 to 2016, and applies a panel data model to analyze the influencing factors of energy efficiency. It selects labor, capital stock and total energy consumption as inputs and takes real GDP and comprehensive index of environmental pollution as desirable and undesirable outputs, respectively. The results show that (1) energy efficiency when undesirable output is included is generally lower than when undesirable output is excluded; (2) There is a considerable difference in energy efficiency among provinces, and China's energy efficiency, by and large, shows a trend of declining. The energy efficiency of four major regions demonstrates obvious regional differences coastal region>northeastern region> middle region >western region; (3) The economic development level, technological progress, energy price and urbanization level are positively associated with energy efficiency, while the proportion of secondary industry and the energy consumption structure dominated by coal and oil are negatively correlated with energy efficiency.Studies focusing on 100% renewable energy systems have emerged in recent years; however, existing studies tend to focus only on the power sector using exploratory approaches. This paper therefore undertakes a whole-system approach and explores optimal pathways towards 100% renewable energy by 2050. The analysis is carried out for Ireland, which currently has the highest share of variable renewable electricity on a synchronous power system. Large numbers of scenarios are developed using the Irish TIMES model to address uncertainties. Results show that compared to decarbonization targets, focusing on renewable penetration without considering carbon capture options is significantly less cost effective in carbon mitigation. Alternative assumptions on bioenergy imports and maximum variability in power generation lead to very different energy mixes in bioenergy and electrification levels. All pathways suggest that indigenous bioenergy needs to be fully exploited and the current annual deployment rate of renewable electricity needs a boost. Pathways relying on international bioenergy imports are slightly cheaper and faces less economic and technical challenges. However, given the large future uncertainties, it is recommended that further policy considerations be given to pathways with high electrification levels as they are more robust towards uncertainties.