Mackaybarry9967

demand, is supported by predictions from the simple bioeconomic model, may increase income inequality between fishers and traders. Our findings highlight the real and urgent need to re-think fisheries management models in the context of small-scale fisheries and climate change worldwide to encompass social relationship dynamics.

The online version contains supplementary material available at (10.1007/s10113-021-01747-5).

The online version contains supplementary material available at (10.1007/s10113-021-01747-5).The current situation of COVID-19 highlights the paramount importance of infectious disease surveillance, which necessitates early monitoring for effective response. Policymakers are interested in data insights identifying high-risk areas as well as individuals to be quarantined, especially as the public gets back to their normal routine. We investigate both requirements by the implementation of disease outbreak modeling and exploring its induced dynamic spatial risk in form of risk assessment, along with its real-time integration back into the disease model. This paper implements a contact tracing-based stochastic compartment model as a baseline, to further modify the existing setup to include the spatial risk. This modification of each individual-level contact's intensity to be dependent on its spatial location has been termed as Contextual Contact Tracing. The results highlight that the inclusion of spatial context tends to send more individuals into quarantine which reduces the overall spread of infection. With a simulated example of an induced spatial high-risk, it is highlighted that the new spatio-SIR model can act as a tool to empower the analyst with a capability to explore disease dynamics from a spatial perspective. We conclude that the proposed spatio-SIR tool can be of great help for policymakers to know the consequences of their decision prior to their implementation.Team communication is considered a key factor for team performance. Importantly, voicing concerns and suggestions regarding work-related topics-also termed speaking up-represents an essential part of team communication. Particularly in action teams in high-reliability organizations such as healthcare, military, or aviation, voice is crucial for error prevention. Although research on voice has become more important recently, there are inconsistencies in the literature. This includes methodological issues, such as how voice should be measured in different team contexts, and conceptual issues, such as uncertainty regarding the role of the voice recipient. We tried to address these issues of voice research in action teams in the current literature review. Romglizone We identified 26 quantitative empirical studies that measured voice as a distinct construct. Results showed that only two-thirds of the articles provided a definition for voice. Voice was assessed via behavioral observation or via self-report. Behavioral observation includes two main approaches (i.e., event-focused and language-focused) that are methodologically consistent. In contrast, studies using self-reports showed significant methodological inconsistencies regarding measurement instruments (i.e., self-constructed single items versus validated scales). The contents of instruments that assessed voice via self-report varied considerably. The recipient of voice was poorly operationalized (i.e., discrepancy between definitions and measurements). In sum, our findings provide a comprehensive overview of how voice is treated in action teams. There seems to be no common understanding of what constitutes voice in action teams, which is associated with several conceptual as well as methodological issues. This suggests that a stronger consensus is needed to improve validity and comparability of research findings.Multicriteria decision-making methods are widely spread and used to assist the decision-makers to resolve problems. Many of the methods are simple to deploy (WSA, TOPSIS), which is an advantage and because of the computer boom, there is no problem with calculations. However, more sophisticated methods are evolving. The modelling of preferences is improved (from linear in WSA to Gaussian in PROMETHEE), multilevel decision-making (such as AHP) is extended to modelling of dependencies between individual criteria (ANP). The presented method, two-stage weighted PROMETHEE, combines the advantages of generalized preferential functions in PROMETHEE methods, unambiguous arrangement (PROMETHEE II) and hierarchical approach (AHP). In addition, this paper demonstrates the application of the method to evaluate the order of 14 regions of the Czech Republic in regard to economic indices such as the unemployment rate, economic activity, average age, wages, free working places, income, consumption and investments. Data are taken from the Czech Statistical Office web and include the years 2012-2019. In the first stage, the position of each region is calculated; in the second stage, all years mentioned are considered, including the aspect of the weighted time series. Result visualization is made possible using the Visual PROMETHEE software.Disaster management generally includes the post-disaster stage, which consists of the actions taken in response to the disaster damages. These actions include the employment of emergency plans and assigned resources to (i) rescue affected people immediately, (ii) deliver personnel, medical care and equipment to the disaster area, and (iii) aid to prevent the infrastructural and environmental losses. In the response phase, humanitarian logistics directly influence the efficiency of the relief operation. Ambulances routing problem is defined as employing the optimisation tools to manage the flow of ambulances for finding the best ambulance tours to transport the injured to hospitals. Researchers pointed out the importance of equity and fairness in humanitarian relief services managing the operations of ambulances in the immediate aftermath of a disaster must be done impartially and efficiently to rescue affected people with different priority in accordance with the restrictions. Our research aim is to find the best ambulance tours to transport the patients during a disaster in relief operations while considering fairness and equity to deliver services to patients in balance. The problem is formulated as a new variant of the team orienteering problem with hierarchical objectives to address also the efficiency issue. Due to the limitation of solving the proposed model using a general-purpose solver, we propose a new hybrid algorithm based on a machine learning and neighbourhood search. Based on a new set of realistic benchmark instances, our quantitative analysis proves that our algorithm is capable to largely reduce the solution running time especially when the complexity of the problem increases. Further, a comparison between the fair solution and the system optimum solution is also provided.The perceived dichotomy between analytical and ab initio approaches to theory in attosecond science is often seen as a source of tension and misconceptions. This Topical Review compiles the discussions held during a round-table panel at the 'Quantum Battles in Attoscience' cecam virtual workshop, to explore the sources of tension and attempt to dispel them. We survey the main theoretical tools of attoscience-covering both analytical and numerical methods-and we examine common misconceptions, including the relationship between ab initio approaches and the broader numerical methods, as well as the role of numerical methods in 'analytical' techniques. We also evaluate the relative advantages and disadvantages of analytical as well as numerical and ab initio methods, together with their role in scientific discovery, told through the case studies of two representative attosecond processes non-sequential double ionisation and resonant high-harmonic generation. We present the discussion in the form of a dialogue between two hypothetical theoreticians, a numericist and an analytician, who introduce and challenge the broader opinions expressed in the attoscience community.

What is the nature of tunnelling? This yet unanswered question is as pertinent today as it was at the dawn of quantum mechanics. This article presents a cross section of current perspectives on the interpretation, computational modelling, and numerical investigation of tunnelling processes in attosecond physics as debated in the Quantum Battles in Attoscience virtual workshop 2020.

We investigate twisted electrons with a well-defined orbital angular momentum, which have been ionised via a strong laser field. By formulating a new variant of the well-known strong field approximation, we are able to derive conservation laws for the angular momenta of twisted electrons in the cases of linear and circularly polarised fields. In the case of linear fields, we demonstrate that the orbital angular momentum of the twisted electron is determined by the magnetic quantum number of the initial bound state. The condition for the circular field can be related to the famous ATI peaks, and provides a new interpretation for this fundamental feature of photoelectron spectra. We find the length of the circular pulse to be a vital factor in this selection rule and, employing an effective frequency, we show that the photoelectron OAM emission spectra are sensitive to the parity of the number of laser cycles. This work provides the basic theoretical framework with which to understand the OAM of a photoelectron undergoing strong field ionisation.

We discuss the possibility of performing precise tests of μ / e universality in B → π ℓ + ℓ - decays. We show that in wide regions of the dilepton invariant mass spectrum the ratio between muonic and electronic decay widths can be predicted with high accuracy, both within and beyond the Standard Model. We present numerical expressions which can be used to extract precise information on short-distance dynamics if a deviation from universality is observed in the data.The DEAP-3600 detector searches for the scintillation signal from dark matter particles scattering on a 3.3 tonne liquid argon target. The largest background comes from 39 Ar beta decays and is suppressed using pulse-shape discrimination (PSD). We use two types of PSD estimator the prompt-fraction, which considers the fraction of the scintillation signal in a narrow and a wide time window around the event peak, and the log-likelihood-ratio, which compares the observed photon arrival times to a signal and a background model. We furthermore use two algorithms to determine the number of photons detected at a given time (1) simply dividing the charge of each PMT pulse by the mean single-photoelectron charge, and (2) a likelihood analysis that considers the probability to detect a certain number of photons at a given time, based on a model for the scintillation pulse shape and for afterpulsing in the light detectors. The prompt-fraction performs approximately as well as the log-likelihood-ratio PSD algorithm if the photon detection times are not biased by detector effects. We explain this result using a model for the information carried by scintillation photons as a function of the time when they are detected.