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Reinforced concrete (R/C) hyperbolic cooling towers are the largest thin‐shell structures ever constructed. These towers stand more than 150m tall and have wall thicknesses of 0.20‐0.25m. Therefore, these can be classified as thin‐shell structures. Analyses the influences of both the reinforcing ratio and the tensile strength of the concrete on the strength of the R/C cooling tower shells. In the numerical analysis Port Gibson tower is adopted for the numerical model and the finite element method is applied to examine the non‐linear behaviour of the cooling tower shells. From the load displacement curves the initial crack strength and the ultimate strength are determined. Also presents the stress redistribution processes and demonstrates the influences of these problems on the strength of the cooling tower shells.

The purpose of this paper is to examine from the viewpoint of resource utilization the Japanese surgical payment system which was revised in April 2016.

The authors collected data from surgical records in the Teikyo University electronic medical record system from April 1 till September 30, 2016. The authors defined the decision-making unit as a surgeon with the highest academic rank in the surgery. Inputs were defined as the number of medical doctors who assisted surgery, and the time of operation from skin incision to closure. An output was defined as the surgical fee. The authors calculated each surgeon’s efficiency score using output-oriented Charnes–Cooper–Rhodes model of data envelopment analysis. The authors compared the efficiency scores of each surgical specialty using the Kruskal–Wallis and the Steel method.

The authors analyzed 2,558 surgical procedures performed by 109 surgeons. The difference in efficiency scores was significant (p = 0.000). The efficiency score of neurosurgery was significantly greater than obstetrics and gynecology, general surgery, orthopedics, emergency surgery, urology, otolaryngology and plastic surgery (p<0.05).

The authors demonstrated that the surgeons’ efficiency was significantly different among their specialties. This suggests that the Japanese surgical reimbursement scales fail to reflect resource utilization despite the revision in 2016.

This paper investigates the evolving landscape of architectural criticism in the digital era, leveraging the enduring interplay between architecture and media. It specifically examines the role of social media and public awards in improving user engagement with architectural discourse.

A mixed-method approach, incorporating both qualitative and quantitative analyses, is used to discuss three architecture awards. These are chosen for their different evaluation processes and their capacity to offer diverse opportunities for public interaction and engagement.

The study emphasises the potential of social media to democratise architectural criticism, while also addressing challenges such as the prominence of non-critical visual material and the presence of algorithmic biases. The findings underline the importance of providing adequate materials for public evaluation and integrating expert juries to support the assessment process. These elements are essential to fostering informed public participation, bridging the gap between professional expertise and popular engagement, and enabling meaningful architectural discourse on social media.

This paper fills a gap in the academic literature by connecting public architectural awards – a relatively unexplored aspect of architectural culture – with the potential of social media as a platform for architectural criticism.

Flow control has a great potential to contribute to a sustainable society through mitigation of environmental burden. However, the high dimensional and nonlinear nature of fluid flows poses challenges in designing efficient control laws using the control theory. This paper aims to propose a hybrid method (i.e. machine learning and control theory) for feedback control of fluid flows, by which the flow is mapped to the latent space in such a way that the linear control theory can be applied therein.

The authors propose a partially nonlinear linear system extraction autoencoder (pn-LEAE), which consists of convolutional neural networks-based autoencoder (CNN-AE) and a custom layer to extract low-dimensional latent dynamics from fluid velocity field data. This pn-LEAE is designed to extract a linear dynamical system so that the modern control theory can easily be applied, while a nonlinear compression is done with the autoencoder (AE) part so that the latent dynamics conform to that linear system. The key technique is to train this pn-LEAE with the ground truths at two consecutive time instants, whereby the AE part retains its capability as the AE, and the weights in the linear dynamical system are trained simultaneously.

The authors demonstrate the effectiveness of the linear system extracted by the pn-LEAE, as well as the designed control law’s effectiveness for a flow around a circular cylinder at the Reynolds number of Re_D = 100. When the control law derived in the latent space was applied to the direct numerical simulation, the lift fluctuations were suppressed over 50%.

To the best of the authors’ knowledge, this is the first attempt using CNN-AE for linearization of fluid flows involving transient development to design a feedback control law.

The purpose of this paper is to reflect on the development and progression of the International Journal of Pharmaceutical and Healthcare Marketing and include comments on its future direction.

The paper takes the approach of an essay format.

The journal has published key papers in pharmaceutical and healthcare research and continues to develop an interdisciplinary character with contributions from scholarly and practice‐oriented sources.

The paper provides a contemporary appraisal of the status and positioning of the journal.