Abstract
Radiographic canine hip dysplasia (CHD) diagnosis is crucial for breeding selection and disease management, delaying progression and alleviating the associated pain. Radiography is the primary imaging modality for CHD diagnosis, and visual assessment of radiographic features is sometimes used for accurate diagnosis. Specifically, alterations in femoral neck shape are crucial radiographic signs, with existing literature suggesting that dysplastic hips have a greater femoral neck thickness (FNT). In this study we aimed to develop a three-stage deep learning-based system that can automatically identify and quantify a femoral neck thickness index (FNTi) as a key metric to improve CHD diagnosis. Our system trained a keypoint detection model and a segmentation model to determine landmark and boundary coordinates of the femur and acetabulum, respectively. We then executed a series of mathematical operations to calculate the FNTi. The keypoint detection model achieved a mean absolute error (MAE) of 0.013 during training, while the femur segmentation results achieved a dice score (DS) of 0.978. Our three-stage deep learning-based system achieved an intraclass correlation coefficient of 0.86 (95% confidence interval) and showed no significant differences in paired t-test compared to a specialist (p > 0.05). As far as we know, this is the initial study to thoroughly measure FNTi by applying computer vision and deep learning-based approaches, which can provide reliable support in CHD diagnosis. © The Author(s) 2024.

Abstract
Frequency stability in inverter-based renewable energy sources (RES)-dominated, low-inertia, power systems is a timely challenge. This paper employs a systematic approach, utilizing an artificial neural network (ANN) and dynamic simulation, to infer two key frequency stability indicators: nadir and rate of change of frequency (RoCoF). By reformulating the ANN mathematical model, these indicators are then integrated as mixed-integer non-linear constraints into a classical AC security-constrained optimal power flow (AC SCOPF), resulting in the proposed AC-F-SCOPF problem. The results of the proposed AC-F-SCOPF on the IEEE 39-bus system show that the problem identifies accurately the synchronous condensers which must run to ensure the frequency stability.

Abstract
This cross-sectional study addresses Portuguese online shoppers' behavior toward Chinese online retailers, assessing the impact of financial, product, and time-convenience risks and demographic traits on their willingness to buy from those e-stores. The research relies on a survey of 1,432 participants who have shopped online at least once. Approximately half of the sample already buys from Chinese websites; age, financial, and time-convenience risks explain 21.5% of the variance of their purchase intention. On the other hand, participants who buy on Chinese websites present significantly lower values of all risks and the intention to buy from Chinese websites, possibly reflecting a satisfactory transaction experience. Furthermore, a generation gap is evident as younger people feel more confident in dealing intuitively with and solving online issues, giving them the confidence necessary to purchase online from Chinese e-stores - perhaps geographically and ideologically distant - but brought closer by e-expertise (online dexterity).

Abstract
The availability of public services through online platforms has improved the coverage and efficiency of essential services provided to citizens worldwide. These services also promote transparency and foster citizen participation in government processes. However, the increased online presence also exposes sensitive data exchanged between citizens and service providers to a wider range of security threats. Therefore, ensuring the security and trustworthiness of online services is crucial to Electronic Government (EGOV) initiatives' success. Hence, this work assesses the security posture of online platforms hosted in 3068 governmental domain names, across all UN Member States, in three dimensions: support for secure communication protocols; the trustworthiness of their digital certificate chains; and services' exposure to known vulnerabilities. The results indicate that despite its rapid development, the public sector still falls short in adopting international standards and best security practices in services and infrastructure management. This reality poses significant risks to citizens and services across all regions and income levels.

Abstract
Strategic term re-writing and attribute grammars are two powerful programming techniques widely used in language engineering. The former relies on strategies to apply term re-write rules in defining largescale language transformations, while the latter is suitable to express context-dependent language processing algorithms. These two techniques can be expressed and combined via a powerful navigation abstraction: generic zippers. This results in a concise zipper-based embedding offering the expressiveness of both techniques. In addition, we increase the functionalities of strategic programming, enabling the definition of outwards traversals; i.e. outside the starting position. Such elegant embedding has a severe limitation since it recomputes attribute values. This paper presents a proper and efficient embedding of both techniques. First, attribute values are memoized in the zipper data structure, thus avoiding their re-computation. Moreover, strategic zipper based functions are adapted to access such memoized values. We have hosted our memoized zipper-based embedding of strategic attribute grammars both in the Haskell and Python programming languages. Moreover, we benchmarked the libraries supporting both embedding against the state-of-the-art Haskell-based Strafunski and Scala-based Kiama libraries. The first results show that our Haskell Ztrategic library is very competitive against those two well established libraries.

Abstract
This conceptual study explores the alignment between servitization-a shift from selling products to offering services-and circularity principles. The study introduces institutional confluence-a configuration of institutional pressures that enhance business model legitimacy to stakeholders and facilitate operational success- which can serve as a driver aligning servitization with circular principles. Institutional confluence has the capacity to trigger novel business models, shape resources and processes, enhance value capture, and inhibit unsustainable business models. The study develops the concept and underscores the role of institutional confluence in promoting this alignment and subsequent environmental sustainability. The article utilizes illustrative case examples from servitization and circular business models to develop the concept of institutional confluence serving sustainable servitization. The study offers strategic insights for managers and policymakers, emphasizing the need for a holistic approach that integrates servitization and circularity from the outset of business model design. It advocates for policies that leverage regulatory, normative, and mimetic pressures to foster sustainable business practices. The article contributes to the servitization literature by delineating the mechanisms through which institutional forces facilitate or hinder the integration of servitization and circularity, offering directions for future research to explore these dynamics across different contexts and industries.