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Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural network (PINN), which was proposed to encode physical laws into neural networks, is a less data-demanding approach for flow field reconstruction. However, when the fluid physics is complex, it is tricky to obtain accurate solutions under the PINN framework. This study aims to propose a physics-based data-driven approach for time-averaged flow field reconstruction which can overcome the hurdles of the above methods.

A multifidelity strategy leveraging PINN and a nonlinear information fusion (NIF) algorithm is proposed. Plentiful low-fidelity data are generated from the predictions of a PINN which is constructed purely using Reynold-averaged Navier–Stokes equations, while sparse high-fidelity data are obtained by field or experimental measurements. The NIF algorithm is performed to elicit a multifidelity model, which blends the nonlinear cross-correlation information between low- and high-fidelity data.

Two experimental cases are used to verify the capability and efficacy of the proposed strategy through comparison with other widely used strategies. It is revealed that the missing flow information within the whole computational domain can be favorably recovered by the proposed multifidelity strategy with use of sparse measurement/experimental data. The elicited multifidelity model inherits the underlying physics inherent in low-fidelity PINN predictions and rectifies the low-fidelity predictions over the whole computational domain. The proposed strategy is much superior to other contrastive strategies in terms of the accuracy of reconstruction.

In this study, a physics-informed data-driven strategy for time-averaged flow field reconstruction is proposed which extends the applicability of the PINN framework. In addition, embedding physical laws when training the multifidelity model leads to less data demand for model development compared to purely data-driven methods for flow field reconstruction.

The purpose of this paper is to test the performance of the control system developed for the helicopter automatic approach and landing on the moving vessel deck, when different values of backlashes are applied to the four control actuators.

The system consists of automatic control algorithm based on the linear quadratic regulator and the vessel motion prediction algorithm based on autoregressive method with parameters calculated using Burg’s method. Necessary navigation data is provided by on-board inertial navigation system/Global Positioning System. Calculated control commands are executed by four electromechanical actuators. Performance of the mission, which is based on selected procedure of approach and landing of the helicopter on the moving vessel deck, is analyzed taking into account different values of backlashes applied to the actuators.

In this paper, a description of the control system dedicated for automatic approach and landing of the helicopter on the moving vessel deck is shown. Necessary information about helicopter dynamic model, control system and vessel motion model is included. Tests showing influence of actuator backlashes on the mission performance are presented.

The developed control methodology can be adapted for selected helicopter and used in prospective development of an automatic flight control system (AFCS) or in a simulator. The system can be used to define in which conditions helicopter can perform safe and successful automatic approach and landing on a moving vessel deck.

In this paper, an integrated control system is presented; influence of the control actuator backlashes on the mission performance is analyzed.

With the outset of automatic detection of information, misinformation, and disinformation, the purpose of this paper is to examine and discuss various conceptions of information, misinformation, and disinformation within philosophy of information.

The examinations are conducted within a Gricean framework in order to account for the communicative aspects of information, misinformation, and disinformation as well as the detection enterprise.

While there often is an exclusive focus on truth and falsity as that which distinguish information from misinformation and disinformation, this paper finds that the distinguishing features are actually intention/intentionality and non-misleadingness/misleadingness – with non-misleadingness/misleadingness as the primary feature. Further, the paper rehearses the argument in favor of a true variety of disinformation and extends this argument to include true misinformation.

The findings are novel and pose a challenge to the possibility of automatic detection of misinformation and disinformation. Especially the notions of true disinformation and true misinformation, as varieties of disinformation and misinformation, which force the true/false dichotomy for information vs mis-/disinformation to collapse.

This study aims to propose an adaptive fractional-order sliding mode controller to solve the problem of train speed tracking control and position interval control under disturbance environment in moving block system, so as to improve the tracking efficiency and collision avoidance performance.

The mathematical model of information interaction between trains is established based on algebraic graph theory, so that the train can obtain the state information of adjacent trains, and then realize the distributed cooperative control of each train. In the controller design, the sliding mode control and fractional calculus are combined to avoid the discontinuous switching phenomenon, so as to suppress the chattering of sliding mode control, and a parameter adaptive law is constructed to approximate the time-varying operating resistance coefficient.

The simulation results show that compared with proportional integral derivative (PID) control and ordinary sliding mode control, the control accuracy of the proposed algorithm in terms of speed is, respectively, improved by 25% and 75%. The error frequency and fluctuation range of the proposed algorithm are reduced in the position error control, the error value tends to 0, and the operation trend tends to be consistent. Therefore, the control method can improve the control accuracy of the system and prove that it has strong immunity.

The algorithm can reduce the influence of external interference in the actual operating environment, realize efficient and stable tracking of trains, and ensure the safety of train control.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

Social enterprises (SEs) face tensions when combining financial and social missions, and this is particularly evident in the scaling process. Although extant research mainly focuses on SEs that integrate their social and financial missions, this study aims to unpack social impact scaling strategies in differentiated hybrid organizations (DHOs) through the case of African SEs.

The study entails an inductive multiple case study approach based on four case SEs: work integration social enterprises (WISEs) and fair trade producer social enterprises (FTPSEs) in Uganda and Kenya. A total of 24 semi-structured interviews were collected together with multiple secondary data sources and then coded and analyzed through the rigorous Gioia et al. (2013) methodology to build a theoretical model.

The results indicate that SEs, as differentiated hybrids, implement four types of social impact scaling strategies toward beneficiaries and benefits (penetration, bundling, spreading and diversification) and unveil different dual mission tensions generated by each scaling strategy. The study also shows mutually reinforcing mechanisms named cross-bracing actions, which are paradoxical actions connected to one another for navigating tensions and ensuring dual mission during scaling.

This study provides evidence of four strategies for scaling social impact, with associated challenges and response mechanisms based on the cross-bracing effect between social and financial missions. Thus, the research provides a clear framework (social impact scaling matrix) for investigating differentiation in hybridity at scaling and provides new directions on how SEs scale their impact, with implications for social entrepreneurship and dual mission management literature.

The model offers a practical tool for decision-makers in SEs, such as managers and social entrepreneurs, providing insights into what scaling pathways to implement (one or multiples) and, more importantly, the implications and possible solutions. Response mechanisms are also useful for tackling specific tensions, thereby contributing to addressing the challenges of vulnerable, marginalized and low-income individuals. The study also offers implications for policymakers, governments and other ecosystem actors such as nongovernmental organizations (NGOs) and social investors.

Despite the growing body of literature on scaling social impact, only a few studies have focused on differentiated hybrids, and no evidence has been provided on how they scale only the social impact (without considering commercial scaling). This study brings a new perspective to paradox theory and hybridity, showing paradoxes come into view at scaling, and documenting how from a differentiation approach to hybridity, DHOs also implemented cross-bracing actions, which are reinforcement mechanisms, thus suggesting connections and synergies among the actions in social and financial mission, where such knowledge is required to better comprehend how SEs can achieve a virtuous cycle of profits and reinvestments in social impact.

Decision-making competence (DMC) of entrepreneurs and managers is a longstanding topic in this increasingly globalized world. These figures operate in conditions not within their own control, and good levels of DMC are often considered to be desirable for the flourishing of business and society. This paper reports an empirical investigation on the DMC of entrepreneurs and managers, in an attempt to inform about their tendencies to incur in risky and costly choices.

Three cognitive biases associated with operational strategies and individual characteristics of entrepreneurs and managers, namely under/overconfidence (UOC, i.e. self-confidence in taking decisions), resistance to sunk costs (RSC, i.e. propensity to take cost investments) and consistency in risk perception (CRP, i.e. how well individuals understand probability rules) were considered . Cognitive biases measures were used in a cross-sectional study on a sample of n = 639 entrepreneurs and n = 512 managers. Data collected via online survey were analyzed using descriptive statistics and inferential statistics to determine differences among entrepreneurs and managers DMC.

Analyses reveal that entrepreneurs exhibit higher levels of UOC compared to managers with a marked presence of UOC among entrepreneurs at younger ages. Conversely, performance regarding RSC improves with higher education levels while age and RSC are positively correlated only for managers, regardless of education. Lastly, entrepreneurs and managers resulted as not being affected by CRP. This study discusses these results to provide initial insights for further avenues of research and practice.

The study offers an innovative, evidence-based viewpoint on how entrepreneurs and managers deal with risky and costly decisions. It offers an initial understanding of the role of UOC, RSC and CRP, that is specific cognitive biases associated with operational strategies and individual characteristics, in the DMC of these working figures. The study forwards avenues of scrutiny of quick-witted entrepreneurs and systematic managers.

While there are several readiness assessments regarding digital transformation (DT) and Industry 4.0 in extant literature, this study aims to contribute to (a) a better understanding of digital readiness in supply chain (SC) aspects and (b) elaborate on differences between small and medium-sized enterprises (SMEs) and large enterprises.

The study is based on 409 companies that participated in the Digital Readiness Check (DRC) in the region of Salzburg (Austria) and Bavaria (Germany) – an online assessment for self-evaluating the digital readiness of companies.

The study's results provide insights for the categories of strategy, employees, initiation of business transactions and SC. These are further differentiated for SMEs and large enterprises.

The study is limited to two regions in Austria and Germany, based on a self-evaluation of companies in a single point of time perspective. For future research, the results of this study should be expanded for different regions. Further, the results could be validated regarding external observations and measuring results at a later point of time.

The DRC may help companies in benchmarking themselves and gaining a better understanding about categories that must be improved, especially regarding SC aspects of DT.

The DRC extends extant literature regarding the differentiation between SMEs and large enterprises as well as focussing on SC aspects of DT.

The critical role of diet in climate change mitigation has raised behavioural approaches to the top of the agenda. In this paper, the authors take a critical look at these behavioural approaches and call for a more dynamic, practice-oriented understanding of long-term changes in sustainable food consumption and supply.

This approach is based on the experiences from a long-term experiment promoting sustainable eating in a workplace lunch restaurant using a series of informational and nudging techniques. In the experiment, the authors found that focussing solely on eating behaviours did not help to capture the multi-level change processes mobilised. The authors therefore propose a more dynamic, practice-oriented methodology for examining long-term changes in sustainable eating. The emprical data of the experiment are based on qualitative and quantitative data, consisting of customer survey, customer and kitchen personnel focus group discussions and monitoring data on the use of food items in the restaurant and their climate impacts.

The results draw attention to a series of practical challenges restaurants face when promoting sustainable eating. Directing analytical attention to tinkering helped to reveal the tensions brought about by labelling and nudging in menu planning and recipe development. The results show how tinkering required attentiveness to customers' wishes in both cases. Nudging offered more freedom for the restaurant to develop menus and recipes. In the case scrutinised, however, nudging customers towards tastier and more satiating vegetarian dishes included the use of dairy. This partly watered down the climate benefits gained from reduced meat consumption.

Rather than looking separately at changes in consumer behaviour and in the supply of food, the authors show how we need analytical concepts that enable the evaluation of their mutual evolution. Tinkering can assist us in this endeavour. Its adaptive, adjustive character, however, calls for caution. The development of praxis in food services and catering requires critical companions from the transdisciplinary research community. Research can provide systematic knowledge on the impacts of labels and nudges on kitchen praxis. However, research itself also needs to tinker and learn from experiments. This necessitates long-term speculative research strategies.

Building on the existing literature and on a series of interviews conducted in very diverse coworking spaces, this article attempts at analyzing coworking by focusing on the historical evolution and heterogeneity of its interpretations, as well as the plurality of its realization in practice and prospective developments.

The theoretical framework adopted is Cultural Historical Activity Theory – a dialectical approach which allows the study of human activities as historically evolving and complex systems which change under the impulse of their inner contradictions. The analysis presented here starts with an overview of the history of the theoretical elaborations and discussions of coworking. The authors then focus on the experiences and interpretations of this phenomenon as conveyed by coworkers and coworking managers in the north of Italy – one of the most active coworking areas in Europe.

Coworking first emerged as a way of promoting forms of work and organization that require simultaneous, multidirectional, and reciprocal work, as understood in contrast to forms that incorporate an established division of labor, demarcated communities, and formal and informal sets of rules. However, with time, coworking has evolved toward novel directions, giving rise to heterogeneous interpretations of it. Inquiry constitutes a deeper investigation of the heterogeneity of coworking. The take-away message here is that the prefix co- in coworking can be interpreted, through a play of words, to evoke multiple positions and views conveying internal contradictions.

The historical overview of coworking shows a strong differentiation and multisided interpretation of this phenomenon along two dimensions of historical development, namely, social and business, and outward and inward. The qualitative analysis of the interviews traces the different lived interpretations and conceptions of coworking. The analysis confirms, on the one hand, the complexity and heterogeneity described in the literature, and on the other hand, it enriches the literature by depicting the contradictory nature of the phenomenon, including how the historical and inner tensions of coworking are dynamically evolving in the concrete experiences reported by the managers and users in the coworking spaces.