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FASD and Intellectual Disability Equivalence: A Meta‐Analysis of Suggestibility During Forensic Interviews
Full text linkIntellectual disability (ID) equivalence describes conditions in which individuals function cognitively and adaptively at levels comparable to ID without meeting IQ‐based diagnostic criteria. Fetal alcohol spectrum disorder (FASD) is characterised by impaired executive and adaptive functioning despite IQs often above the ID threshold, suggesting functional overlap with ID. This meta‐analytic study is the first to examine whether FASD and ID share vulnerabilities in interrogative suggestibility. Two PRISMA‐guided systematic searches of six databases were undertaken, and identified studies involving FASD or ID. Bayesian random‐effects meta‐analyses were conducted on Gudjonsson Suggestibility Scale–2 outcomes: Yield 1, Yield 2, Shift, and Total Suggestibility. Individuals with FASD showed levels of interrogative suggestibility comparable to, and sometimes exceeding, those with ID across all indices. Effect sizes were large for both groups, with particularly elevated Shift scores in individuals with FASD. Both groups are highly vulnerable to leading questions and interrogative pressure. Individuals with FASD may be especially prone to changing responses following negative feedback, highlighting important forensic interviewing implications
Navigating Identity, Meaning and Belonging: Youth Encounters with Extremism and the Implications for Education
No full textMulti‐Seasonal eDNA Metabarcoding Highlights a Resurgence in Fish Diversity Across a Severely Impacted Estuarine Ecosystem
Full text linkAquatic ecosystems have been in an alarming state of decline for decades. In particular, estuarine ecosystems have experienced long‐term declines in fish diversity due to factors such as habitat degradation, pollution and altered hydrology. Monitoring these systems is often limited by the difficulty and cost of conventional survey methods. In this study, we applied environmental DNA (eDNA) metabarcoding to assess fish diversity in the Mersey Estuary (UK), a historically severely impacted system. Monthly water samples were collected over a year (2023–2024) across saline, brackish, and freshwater zones. Overall, 69 species were detected, surpassing both historical (46 species) and recent (39 species) records. Richness was highest in the upper freshwater zones, and several species were recorded returning to the estuary for the first time since pre‐industrial times (∼1850s). Peak species richness occurred during winter (December–February). Species composition varied monthly and spatially, though not consistently by season. Approximately 15% of detected species were diadromous, with the endangered Atlantic salmon (Salmo salar) being frequently detected during its key spawning period (October–December), for example. The results presented here indicate a resurgence in estuarine fish diversity in the Mersey and highlight eDNA metabarcoding as a rapid, sensitive tool for monitoring both contemporary and historically absent species, supporting conservation and restoration efforts
Self-Constrained Weighted Garrote Ordered Memory Network with Adaptive Distribution Learning for Industrial Soft Sensor
Full text linkChemical processes involve complex operational mechanisms and high-dimensional variables with multiscale dependencies and temporal covariate shifts, posing significant challenges for soft sensing implementation. To address these issues, a self-constrained weighted garrote ordered memory network with adaptive distribution learning is proposed for industrial soft sensor modeling. Specifically, an improved long short-term ordered memory (LSTOM) architecture with a composite hierarchical information update mechanism is designed to capture multiscale dynamic features from industrial time-series data. Meanwhile, an adaptive distribution learning module is embedded into the LSTOM architecture to match high-order feature distributions across different temporal periods via maximally dissimilar segments. With the composite hierarchical update mechanism and embedded adaptive distribution learning, the proposed approach improves generalization in soft sensor modeling under multi-timescale dependencies and temporal covariate shifts. Finally, the shrinkage coefficients of the self-constrained weighted garrote are embedded into the LSTOM’s input weights to eliminate redundant variables and promote structural sparsity. The effectiveness of the proposed approach is validated on a public industrial-scale penicillin fermentation process and a real-world flue gas desulfurization case
Mapping of Clustering, Partners, and Geographic Distribution of Biotech SME Clusters Across the UK: A Case Study
Full text linkThe purpose of this paper is to evaluate which universities spin out biotechnology SMEs, and why some do this successfully while others do not. The research question is: how do institutional, contextual, and geographic factors shape biotechnology spin-out activity among UK universities? A systematic review was carried out, which examined data from the websites of 26 UK universities in 10 geographic regions and 4 industry bodies. To supplement this review, a questionnaire was used to evaluate the factors which encourage universities to spin out. The results show that biotechnology spin-outs tend to be clustered around certain geographical locations. This clustering activity is not deliberate and exists as a by-product of activity. Interestingly, certain universities with good research backgrounds have been shown to produce little to no biotechnology spin-outs. Six themes were noted as drivers for the creation of biotechnology university spin-outs: increased support from universities; funding opportunities; research excellence framework and knowledge exchange framework metrics and impact; geographical location of universities; revenue and profit; a push on technology transfer and intellectual property. The geographical advantage of being near a biotechnology cluster is clear. However, by building a solid research base with an international reputation, a supportive Technology Transfer Office, education for academic staff in entrepreneurial attributes and behaviours, and engaging with biotechnology accelerators, a university can enhance its spin-out success rate even when that university does not have the benefit of geography and a close regional cluster
Examining the Philosophical Underpinnings of Design Science Research (DSR)
Full text linkDesign science research (DSR) has become a popular method in information systems research and has been warmly welcomed in other disciplines as well. The importance of DSR is evident, in terms of its contribution to knowledge, as well as the creation of artefacts to solve problems of common interest. While it has demonstrated a clear methodology for achieving research goals, the philosophical underpinnings are not widely synthesised. There are inconsistencies and voids related to the philosophical aspects of DSR. For example, there is an inconsistent argument among researchers regarding the definition of design science research in the first place. This study analysed six key texts published within the last fifteen years in design science research along with a critical discussion, with the help of the existing literature. Accordingly, the study presents suggestions for the philosophical aspects of DSR. Namely, the definitions related to DSR terms (design, design science, design science research, and research), philosophical aspects (ontology, epistemology, and axiology), and theory development approaches (inductive, deductive, abductive, and retroductive), as well as research strategies were discussed. This is recommended to take as a starting point for a formative discussion of the topic, fine-tuning ideas with a critical eye
HitHire: The future of ethical, fair, and sustainable AI recruitment – A governance framework
Full text linkArtificial Intelligence (AI) is transforming recruitment but remains susceptible to algorithmic bias and environmental inefficiencies. This paper presents HitHire, a pilot fairness- and sustainability-aware AI hiring platform tailored to the Saudi Arabian context and aligned with Vision 2030 goals. HitHire integrates large language models (LLMs), adversarial debiasing, Shapley Additive Explanations (SHAP), and real-time carbon tracking to ensure transparent and equitable candidate ranking. Evaluated on 350 anonymized CVs across four job roles (web development, finance, human resources, and data science) using a 70/20/10 train/test/validation split, HitHire achieves notable improvements in fairness metrics—Statistical Parity Difference (SPD) for gender = 0.0156 and Disparate Impact (DI) for nationality = 1.2387—while maintaining strong predictive performance (F1 = 0.96 compared to a baseline of 0.80). The system achieves over a 40% reduction in operational CO 2 emissions, with inference energy consumption of 0.003 kWh per query. In a three-month pilot study involving 23 HR professionals within a large Saudi organization, 87% of participants rated system trust at 4 out of 5 or higher. These findings contribute to national digital ethics strategies such as the Saudi Green Initiative, which emphasizes carbon neutrality and sustainable innovation
IoT Based Smart Monitoring System for Enhancing Security and Compliance in the Ministry of Commerce: A Case Study in Saudi Arabia
Full text linkThe Internet of Things (IoT) has emerged as a transformative technology connecting physical devices through intelligent networks that enable real-time data exchange, automation, and decision-making. This research presents the design and implementation of an IoT-based smart monitoring system aimed at enhancing security and regulatory compliancewithin the Ministry of Commerce in Saudi Arabia. The proposed solution utilizes motion and pressure sensors integrated with CCTV cameras, GPS modules, and a MongoDB database to automatically detect and record unauthorized reopening of closed commercial establishments. Once a violation is detected, the system generates instant alerts and transmits notifications to the nearest inspector through a mobile application, providing detailed location and timestamp information. This automation minimizes the dependence on manual inspections, reduces operational costs, and improves enforcement efficiency in line with the Kingdom’s Vision 2030 digital transformation goals. The study further discusses the potential business impacts, integration challenges, and key security and ethical considerations related to IoT deployment in public sector environments. Overall, the proposed solution demonstrates how IoT technologies can significantly strengthen compliance monitoring, enhance public safety, and support sustainable digital governance initiatives. Prototype testing of the developed IoT system was conducted in a controlled environment to validate detection accuracy and response time. Results demonstrated reliable operation with average alert latency under five seconds and over 95 percent detection accuracy, confirming the system’s practical feasibility
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