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Historically, professionals did not consider that people with learning disabilities could make use of psychoanalytic psychotherapy because of limitations of intelligence (Symington, 1981; Symington, 1993; Sternlicht, 1965). Additionally, many believed that people with learning disabilities enjoyed immunity from emotional stress and psychiatric disturbances (Fletcher, 1993). Maladaptive behaviours were perceived as a manifestation of the condition of learning disability and not as a possible sign of psychiatric disorder or emotional problems. However, over the last decade there has been a growing realisation that people with learning disabilities have emotional problems in the same way as others, but are in some ways more vulnerable to developing psychiatric and psychological disturbances. Psychoanalytic practitioners wishing to undertake outcome research have experienced difficulties in finding a measuring device that understands the subtleties of change in the internal psychological structure over time. PORT and DMT (the Percept‐genetic Object Relation Test and the Defence Mechanism Test) are two projective tests that have been extensively validated in Sweden. This paper explores the use of the PORT and DMT outcome measures in the context of Anglo‐Swedish psychotherapy research.

Argues that the dynamic‐explicit approach has in recent years been successfully applied to the solution of various quasi‐static, elastic‐plastic problems, especially in the metal forming area. A condition for the success has, however, been that the problems have been displacement‐driven. The solution of similar force‐driven problems, using this approach, has been shown to be much more complicated and computationally time consuming because of the difficulties in controlling the unphysical dynamic forces. Describes a project aiming to develop a methodology by which a force‐driven problem can be analysed with similar computational effort as a corresponding displacement‐driven one. To this end an adaptive loading procedure has been developed, in which the loading rate is controlled by a prescribed velocity norm. Presents several examples in order to exhibit the merits of the proposed procedure.

The purpose of this paper is to lay a current, research-based foundation for investigation of the concept of innovative price models and its connection to business models.

The design is composed of a structured literature review of articles on price models published in 22 journals during 42 years. This then serves as a base for a subsequent conceptual discussion about the foundation of innovative price models.

The literature review yields only very few results that are loosely scattered across various areas and mostly without any kind of deeper exploration of the concept of price models. The paper therefore goes on to conceptually explore some fundamental conditions that might influence or even determine price models. The final outcome of this exploration is the relation, intention, technology and environment (RITE) framework that is a meta-model for conceptualising innovative price models.

The literature review could include additional journals and areas, and empirical testing of the RITE framework as yet has been limited.

The RITE framework can be used by practitioners as a tool for investigating the potential and usefulness of developing the capability to handle innovative price models.

The RITE framework provides fundamental conditions, which influence, or even determine, how innovative price models are developed and applied.

The purpose of this paper is to examine the role of liaison and diversion services working in the lower courts (also known as Magistrates’ courts) with regard to autism spectrum disorders (ASDs) and their assessment, in particular, the role of pre-sentence and psychiatric reports and interviews.

Current practice is described in the lower courts in the context of current legislation and procedures.

When writing reports, there is a need for expertise to offer an opinion on future risk, disposal and what needs to be in place to support people with ASDs. No assumptions should be made when reporting on the basis of an ASD diagnosis alone and each case must be assessed on its individual merits while ensuring that individual human rights are protected.

There is currently a sparse literature examining ASD in court settings. This paper seeks to clarify the current practice.

Accurate predictions of the steady-state corrosion phase and service life to achieve specific safety limits are crucial for assessing the service of reinforced concrete (RC) structures. Forecasting the service life (SL) of structures is imperative for devising maintenance and repair strategy plans. The optimization of maintenance strategies serves to prolong asset life, mitigate asset failures, minimize repair costs and enhance health and safety standards for society.

The well-known empirical conventional (traditional) approaches and machine learning (ML)-based SL prediction models were presented and compared. A comprehensive parametric study was conducted on existing models, considering real-world conditions as reported in the literature. The analysis of traditional and ML models underscored their respective limitations.

Empirical models have been developed by considering simplified assumptions and relying on factors such as corrosion rate, steel reinforcement diameter and concrete cover depth, utilizing fundamental mathematical formulas. The growth of ML in the structural domain has been identified and highlighted. The ML can capture complex relationships between input and output variables. The performance of ML in corrosion and service life evaluation has been satisfactory. The limitations of ML techniques are discussed, and its open challenges are identified, along with insights into the future direction to develop more accurate and reliable models.

To enhance the traditional modeling of service life, key areas for future research have been highlighted. These include addressing the heterogeneous properties of concrete, the permeability of concrete and incorporating the interaction between temperature and bond-slip effect, which has been overlooked in existing models. Though the performance of the ML model in service life assessment is satisfactory, models overlooked some parameters, such as the material characterization and chemical composition of individual parameters, which play a significant role. As a recommendation, further research should take these factors into account as input parameters and strive to develop models with superior predictive capabilities.

Recent deployment has revealed that ML algorithms can grasp complex relationships among key factors impacting deterioration and offer precise evaluations of remaining SL without relying on traditional models. Incorporation of more comprehensive and diverse data sources toward potential future directions in the RC structural domain can provide valuable insights to decision-makers, guiding their efforts toward the creation of even more resilient, reliable, cost-efficient and eco-friendly RC structures.