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Governments worldwide have been trying to direct more students towards STEM specialty areas, but the number of students majoring in STEM and seeking a STEM career path is not proportional to their efforts. Additionally, the COVID-19 pandemic has brought to the surface the unrealistic expectations and false assumptions held by the general public about STEM fields. These have mainly been shaped by the “T” in the acronym, substituting technology for science. This brief urges for a policy shift in STEM and science education to reveal the true nature of science, emphasizing that science is not about providing definite answers nor granting miraculous solutions but about creating and disseminating knowledge based on the most accurate outcome informed by empirical evidence. Such a policy change will have a dual effect. First, it will ensure students authentically appreciate the nature of science, serve as agents of scientific thinking and reasoning within their communities, and become more oriented towards STEM majors. Secondly, this policy shift will prompt more realistic expectations and valid assumptions about science for the general public, which will help reduce public confusion and uncertainty, specifically at times of pandemics or emergencies.

The purpose of this study is to evaluate the current state of forensic accounting education in the Kingdom of Saudi Arabia (KSA), as well as to identify the desired aims and skills required to practice forensic accounting as a profession. It also seeks to understand the education and skills provided by KSA forensic accounting education programs, the job skills required by professional accountants and the skills required by professional accountants' employers.

The study is exploratory in nature. A convenience base sampling approach was used to select the academicians and practitioners working in KSA. Participants were requested to fill out an electronic questionnaire and rank each statement on a 5-point Likert score. The responses were converted and analyzed using the T-test, to evaluate the inter- and intra-group trends in the data.

The study included 58 responses from practitioners and 30 from academicians. Both groups mentioned that the classroom and the Internet were their primary source of forensic accounting information, especially in professional accounting qualifications. According to the participants, most of the institutions in KSA do not offer forensic accounting courses. Nonetheless, forensic accounting is critical for strengthening the credibility of financial reporting in courtrooms. The study finds subtle inter-group differences regarding the development of an ideal curriculum for forensic accounting, which translates to a bigger difference in curriculum development and practice skills. Both groups were optimistic about the future path of forensic accounting in KSA.

The study reports critical differences between the status of forensic accounting education and the skills required to practice forensic accountancy in KSA.

The role of evidence-based psychological knowledge in cases of juvenile offending is essential to make appropriate decisions relating to youth who violate legal or social norms, as it carries implications for treatment, intervention and practice. Psychological expert opinions therefore need to meet high formal and methodological requirements while maintaining ethical standards. The purpose of this study is to investigate psychological expert opinions in cases of juvenile misbehavior reported to regional courts in Poland. Juvenile court proceedings concern cases of demoralization and/or delinquent offenses. Demoralization is a legal concept described in the Act of June 9, 2022 on juvenile support and resocialization. This concept was not defined; it was only described through examples of behaviors indicating demoralization. These include the following: violations of the principles of community life; evading compulsory education or schooling; use of alcohol, narcotic drugs, psychotropic substances, their precursors, substitutes or new psychoactive substances; and prostitution.

To reach these goals, court records of juvenile cases in six district courts (N = 253) were gathered and analyzed. A semistructured questionnaire was used to examine the cases in which psychologists were appointed and to analyze the procedures used by these experts for assessing adolescents and their families.

Findings revealed that family judges appoint psychologists both in cases of “demoralization” (i.e. status offenses) and in cases of juvenile delinquency. The opinions were delivered by psychologists who were mostly members of diagnostic teams. Results indicate that such opinions generally comply with the minimal standards recommended by the Ministry of Justice, yet a few problems were observed with the determination of levels of demoralization.

The limitations of diagnostic tools used by psychologists are discussed, and recommendations for future practice are provided.

Drug cryptomarkets increase information available to market actors, which should reduce information asymmetry and increase market efficiency. This study aims to determine whether cryptomarket listings accurately represent the advertised substance, weight or number and purity, and whether there are differences in products purchased from the same listing multiple times.

Law enforcement drug purchases – predominantly cocaine, methamphetamine, MDMA and heroin – from Australian cryptomarket vendors (n = 38 in 2016/2017) were chemically analysed and matched with cryptomarket listings (n = 23). Descriptive and comparative analyses were conducted.

Almost all samples contained the advertised substance. In most of these cases, drugs were either supplied as-advertised-weight or number, or overweight or number. All listings that quantified purity overestimated the actual purity. There was no consistent relationship between advertised purity terms and actual purity. Across the six listings purchased from multiple times, repeat purchases from the same listing varied in purity, sometimes drastically, with wide variation detected on listings purchased from only one month apart.

In this data set, cryptomarket listings were mostly accurate, but the system was far from perfect, with purity overestimated. A newer, larger, globally representative sample should be obtained to test the applicability of these findings to currently operating cryptomarkets.

This paper reports on the largest data set of forensic analysis of drug samples obtained from cryptomarkets, where data about advertised drug strength/dose were obtained.

This study aims to using Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy and scanning electron microscope/energy dispersive Xray spectrometer to identify different automotive coatings for forensic purpose.

Two four-layered samples in a hit-and-run case were compared layer by layer with three different methods. FTIR spectroscopy was used to primarily identify the organic and inorganic compositions. Raman spectrum and scanning electron microscope/energy dispersive Xray spectrometer (SEM-EDS) were further used to complement the FTIR results.

Two weak and tiny peaks in one layer found between two samples by FTIR, Raman microscope and SEM-EDS verified the result of differences. The study used the three instruments in combination and found it’s effective in sensing coatings, especially in the inorganic additives.

Using these three instruments in combination is more accurate than individually in multilayered coating analysis for forensic purpose.

The three different instruments all present unique information on the composition, and provided similar and mutually verifiable results on the two samples.

With this method, scientists could identify and discriminate important coating evidences with tiny but characteristic differences.

The present study aims to examine the scope and contribution of behavioural investigative advice (BIA) reports from the National Crime Agency (NCA).

The 77 BIA reports reviewed were written between 2016 and 2021. They were evaluated using Toulmin’s (1958) strategy for structuring pertinent arguments, current compliance with professional standards, the grounds and backing provided for the claims made and the potential utility of the recommendations provided.

Consistent with previous research, most of the reports involved murder and sexual offences. The BIA reports met professional standards with extremely high frequency. The 77 reports contained a total of 1,308 claims of which 99% were based on stated grounds. A warrant and/or backing was provided for 73% of the claims. Most of the claims in the BIA reports involved a behavioural evaluation of the crime scene and offender characteristics. The potential utility of the reports was judged to be 95% for informative behavioural crime scene analysis and 40% for potential new lines of enquiry.

The reports should serve as a model for the work of behavioural investigative advisers internationally.

To the best of the authors’ knowledge, this is the first study to systematically evaluate BIA reports commissioned by the NCA; it adds to previous similar studies by evaluating the largest number of BIA reports ever reviewed, and uniquely provides judgement of overall utility.

The “metaverse” is the new buzzword. With the phenomenal growth of the metaverse comes accounting, taxation and jurisdictional challenges, which business and governments have yet to fully address. This paper aims to highlight and rationalise the lack of regulatory framework and multiplicity of jurisdictions on metaverse transactions. This paper addresses some of the complications with respect to accounting and taxation in virtual environments.

This study relies on secondary data and emerging literature to understand the multiplicity of jurisdiction and complexity of the accounting transactions. The concept of the metaverse is rapidly evolving, and this study uses extant literature to provide the foundation for understanding the key challenges relating to accounting and taxation.

Concepts of revenue recognition and deferment are challenged by the transactions in the metaverse. There are novel applications, underpinned by emerging technologies and blockchain supporting new crypto assets, such as non-fungible tokens and other decentralised finance (DeFi) tools; however, the caveats of anonymity and jurisdictional issues persist. The paper suggests that the industry must adapt to the unique reporting requirements of these assets and develop new standards for evaluating their value for financial reporting purposes. The paper emphasises the need for a case-based approach in the absence of standardised regulations for the accounting industry in the metaverse.

This paper adds original contributions to extant literature of the metaverse and advances ongoing debates into the accounting and taxation issues pertinent to the metaverse and DeFi.

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.

Stalking is considered a public health priority with a range of adverse outcomes. This paper aims to explore existing literature on children and adolescents as perpetrators of stalking, with a focus on rates of stalking and victim and perpetrator characteristics associated with stalking.

A review of research where stalking was engaged in by those 18 years old and younger was conducted, where 17 manuscripts met criteria for review.

This review found a prevalence of young people engaging in stalking of between 5.3% and 36%. Considerations including demographics, typologies, prior relationship characteristics, stalking and pursuit tactics, cyberstalking and a brief consideration of the impact are given.

Literature considering perpetration remains thin, and future research should seek to move towards a widely acceptable definition of stalking, as well as considering effective interventions for early intervention, and to consider the role of mental health services in supporting perpetrators and victims, who may not always be mutually exclusive groups.

This paper extends previous literature reviews; the authors understand this to be original work that contributes to a gap in the literature.

Prisoners with substance use disorder (SUD) are at risk of mental health problems. Given the common co-occurring of psychopathic traits with SUDs, probably because of underlying impulsive traits (Ellingson et al., 2018), this study aims to examine the relation between psychopathy (impulsive antisociality and fearless dominance) and the functioning of incarcerated individuals with SUD. The authors investigated whether impulsivity (motor, nonplanning and attentional) can account for the relationship between one psychopathy facet (impulsive antisociality) and craving and mental health problems.

The authors assessed self-reported impulsivity, psychopathy, craving and mental health problems in 121 male incarcerated individuals with SUD and calculated cross-sectional linear regression analyses and mediation models.

Impulsive antisociality was positively related to all impulsivity facets, craving and mental health problems. Attentional impulsivity mediated the relationship of impulsive antisociality with craving and mental health problems. Fearless dominance was related to lower attentional and nonplanning impulsivity, craving and mental health problems.

Future studies should investigate these relations in longitudinal studies and evaluate tailored approaches, for example, mindfulness interventions.

Interventions to reduce craving and improve mental health might be important for those who display self-centered, antisocial behavior but are less relevant for those with fearless, dominant interpersonal behavior. Addressing attentional impulsivity may be of special interest in this regard.

To the best of the authors’ knowledge, this study was the first to investigate the mediating role of different impulsivity facets for the association of impulsive antisociality with craving and with mental health problems in incarcerated individuals with SUD.