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This study aims to examine the scope and contribution of Forensic Clinical Psychology (FCP) advice from the National Crime Agency (NCA) to criminal investigations in the UK to address the gap in current knowledge and research.

The 36 FCP reports reviewed were written between 2017 and 2021. They were analysed using Toulmin’s (1958) application of pertinent arguments to the evaluation process. The potential utility of the reports was analysed in terms of the advice provided.

Most of the reports involved murder and equivocal death. The reports focused primarily on understanding the offender’s psychopathology, actions, motivation and risk to self and others using a practitioner model of case study methodology. Out of the 539 claims, grounds were provided for 99% of the claims, 91% had designated modality, 62% of the claims were potentially verifiable and 57% of the claims were supported by a warrant and/or backing. Most of the reports provided either moderate or high insight into the offence/offender (92%) and potential for new leads (64%).

The advice provided relied heavily on extensive forensic clinical and investigative experience of offenders, guided by theory and research and was often performed under considerable time pressure. Flexibility, impartiality, rigour and resilience are essential prerequisites for this type of work.

To the best of the authors’ knowledge, this study is the first to systematically evaluate forensic clinical psychology reports from the NCA. It shows the pragmatic, dynamic and varied nature of FCP contributions to investigations and its potential utility.

Automatically extracting stance information from natural language texts is a significant research problem with various applications, particularly after the recent explosion of data on the internet via platforms like social media sites. Stance detection system helps determine whether the author agree, against or has a neutral opinion with the given target. Most of the research in stance detection focuses on the English language, while few research was conducted on the Arabic language.

This paper aimed to address stance detection on Arabic tweets by building and comparing different stance detection models using four transformers, namely: Araelectra, MARBERT, AraBERT and Qarib. Using different weights for these transformers, the authors performed extensive experiments fine-tuning the task of stance detection Arabic tweets with the four different transformers.

The results showed that the AraBERT model learned better than the other three models with a 70% F1 score followed by the Qarib model with a 68% F1 score.

A limitation of this study is the imbalanced dataset and the limited availability of annotated datasets of SD in Arabic.

Provide comprehensive overview of the current resources for stance detection in the literature, including datasets and machine learning methods used. Therefore, the authors examined the models to analyze and comprehend the obtained findings in order to make recommendations for the best performance models for the stance detection task.

The study examines the psychometric properties of internal communication satisfaction questionnaire (ICSQ), an instrument originally developed in Croatian. A need for a contemporary instrument validated among a non-English-speaking population of employees who use English as their second language motivated the authors to translate the scale.

ICSQ was validated on a sample of 507 employees of a large Croatian subsidiary of a multinational bank, where English is the official corporate language.

ICSQ displayed satisfactory levels of psychometric properties, retaining the psychometric properties of the original version of the instrument. A confirmatory factor analysis revealed the acceptable model–data fit of the eight-factor model. Additionally, findings supported the reliability and construct validity of the English version of the instrument. Good internal consistencies of all eight internal communication satisfaction (ICS) dimensions and the total ICSQ and an adequate level of scale homogeneity according to the inter-item and inter-total correlations were found.

In order to generalize the study’s results to other business areas and industries, the study should be replicated in other contexts. Additionally, construct validity was tested by applying cross-sectional design, and therefore, no conclusion can be drawn on the causal direction of the relationship. Finally, the discriminant validity of ICSQ was not tested and should be examined in future studies.

The resulting 32-item instrument, in English, can be used for empirical and practical purposes in improving internal communication.

The study confirms that internal communication is a multidimensional construct and should be measured as such.

It is unclear whether information obtained from a one parent can be used to infer the other parent's history of psychopathology. Two hundred and one parental dyads were asked to complete psychiatric interviews. Based on maternal report, non-participating husbands/ fathers had higher rates than participating fathers of psychiatric illness. For fathers who did participate, maternal report did not match direct interview of paternal psychopathology with sensitivities less than 0.40 and positive predictive values of 0.33 to 0.74. Psychopa -thology may be over-represented among fathers who do not participate in research. Mother report of paternal symptoms is not an effective proxy. Alternative methods need to be developed to: i) improve father participation or ii) identify psychiatric status in fathers who do not participate in research projects.

This study aims to develop an experimentally validated three-dimensional numerical model for predicting different flow patterns produced with a gas dynamic virtual nozzle (GDVN).

The physical model is posed in the mixture formulation and copes with the unsteady, incompressible, isothermal, Newtonian, low turbulent two-phase flow. The computational fluid dynamics numerical solution is based on the half-space finite volume discretisation. The geo-reconstruct volume-of-fluid scheme tracks the interphase boundary between the gas and the liquid. To ensure numerical stability in the transition regime and adequately account for turbulent behaviour, the k-ω shear stress transport turbulence model is used. The model is validated by comparison with the experimental measurements on a vertical, downward-positioned GDVN configuration. Three different combinations of air and water volumetric flow rates have been solved numerically in the range of Reynolds numbers for airflow 1,009–2,596 and water 61–133, respectively, at Weber numbers 1.2–6.2.

The half-space symmetry allows the numerical reconstruction of the dripping, jetting and indication of the whipping mode. The kinetic energy transfer from the gas to the liquid is analysed, and locations with locally increased gas kinetic energy are observed. The calculated jet shapes reasonably well match the experimentally obtained high-speed camera videos.

The model is used for the virtual studies of new GDVN nozzle designs and optimisation of their operation.

To the best of the authors’ knowledge, the developed model numerically reconstructs all three GDVN flow regimes for the first time.