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FAN-F: A Fourier Analysis Network-based Framework for Efficient and Reliable Spectrum Sensing for 5G and Beyond
Get PDFSpectrum sensing plays a major role for dynamic spectrum access in Cognitive Radio Networks as we move towards 6G networks characterized by high-frequency operation, ultralow latency requirements, and dense spectrum usage. Most state-of-the-art spectrum sensing techniques suffer from high computational complexity and degraded performance in low Signal-to-Noise Ratio (SNR) environments. To overcome these shortcomings, we propose a Fourier Analysis Network (FAN)-based spectrum sensing approach that specifically addresses the challenge of low detection probability in low-SNR conditions while significantly reducing computational cost. The proposed FAN-based framework integrates Fourier transform properties within the network layers, allowing it to better model periodic and frequency-localized characteristics of wireless signals, such as those found in 5G and 6G-based waveforms. We have evaluated the proposed approach on three datasets that include 5G-NR, DeepSig, and Radar. The experimental results show that the proposed method achieves an improvement in the detection probability of 32.88% and 91.43% compared to the baseline models KAN-SS and PU-DetNet, respectively, at SNR = -10dB. The proposed scheme also outperforms the baseline models in terms of F1-score, with a reduction of 50.60% in FLOPs
Lifetime cost-effectiveness of first metatarsophalangeal joint fusion using patient reported outcomes from National Foot and Ankle Registry data in the UK
Get PDFBackground: Hallux rigidus is a common and debilitating condition that increasingly impacts UK healthcare resources. First metatarsophalangeal joint (MTPJ) fusion is a widely performed intervention with excellent clinical outcomes; however, its commissioning has faced restrictions in some regions in the UK due to perceived limited value. Robust national cost-effectiveness evidence is needed to guide policy and ensure equitable access to care. Methods: A cost–utility analysis was conducted using British Orthopaedic Foot & Ankle Society (BOFAS) Registry data for patients undergoing primary 1st MTPJ fusion. EuroQol-5 Dimension (EQ-5D-5L) outcomes at baseline and 1 year were utilised to estimate quality-adjusted life year (QALY) gains. A lifetime Markov model over 20 years simulated costs, utilities, and complication pathways from the UK NHS perspective. Costs were derived from national tariffs and discounted at 3.5 % per annum. Incremental cost-effectiveness ratios (ICERs) were calculated relative to conservative management, and deterministic sensitivity analysis tested uncertainty across cost and utility assumptions. Results: Out of 1199 patients, 202 had completed full PROM datasets for cost-utility modelling. EQ-5D-5L improved from 0.53 pre-operatively to 0.77 at one year (p < 0.001), exceeding the MCID by six months and sustained thereafter. The base-case model demonstrated a discounted lifetime QALY gain of 3.331 and cost of £ 4698.15, yielding an ICER of £ 1410.58 per QALY gained. Across all sensitivity scenarios, including increased costs, reduced utility gains, and shortened duration of benefit, the ICER remained well below accepted NICE thresholds (£20,000–£30,000/QALY). In the low-cost scenario, 1st MTPJ fusion became cost-saving (negative ICER) by year 18. Conclusion: 1st MTPJ fusion is a highly cost-effective intervention for hallux rigidus, delivering clinically significant and durable improvements in quality of life at very low cost per QALY gained. This procedure provides greater value for money than many widely commissioned major orthopaedic operations, including hip and knee arthroplasty. Current NHS restrictions on access are not supported by health-economic evidence. These findings reinforce the essential role of 1st MTPJ fusion in value-based foot and ankle surgical care
AI assisted triage of UK patients in mental health care services: a qualitative focus group study of patients’ attitudes
No full textBackground: The referral process between healthcare services can be complex, especially in psychiatry, leading to significant delays and ‘hidden waiting lists’. Digital approaches may be helpful. The CHRONOSIG (CHRONOlogical SIGnature) project aims to improve the referral and triage process by applying machine learning (ML) technology to information in electronic health records. We used a focus group methodology to ascertain the views of patients and participants on using CHRONOSIG and similar digital approaches to support decision making in triaging referrals in difficult to treat depression, and the potential benefits and disadvantages of such an approach. Methods: A lived experience participant focus group (N = 16) was held on 25th September, 2024, with a lived experience chair. Participants were recruited by convenience sampling. Data were analysed thematically and managed using the Framework method, with double coding of transcripts, and reported using COREQ guidelines. Results: Main themes from the analysis were: (i) the complexity of mental health needs assessments; (ii) challenges in the current mental health system; (iii) general challenges of using a computer/artificial intelligence based tool for risk prediction and clinical decision support; (iv) differences and similarities in using a computer-based prediction tool in mental health vs. in physical health; (v) possible benefits and harms; (vi) factors to consider in the future. Conclusions: Patient engagement is a key challenge for digital tools in mental health, but previous studies in digital decision support tools have focussed on clinician feedback. In this study we ascertained the views of lived experience participants in mental healthcare triage and referral in difficult to treat depression. Participants identified delays, errors and confusion in the referral process and expressed positive views on the ability of the CHRONOSIG tool to help to improve waiting times and time spent between services, particularly when used as an addition to a high-quality clinical consultation. In many countries there are shortfalls in mental health care provision with increasing waits in both recorded and unrecorded waiting lists. This study supports a potential route to improve these processes; by more accurately and efficiently identifying the needs of patients and matching these to suitable services and research opportunities
PanForest: predicting genes in genomes using random forests
Get PDFMOTIVATION: The presence or absence of some genes in a genome can influence whether other genes are likely to be present or absent. Understanding these gene co-occurrence and avoidance patterns reveals fundamental principles of genome organization, with applications ranging from evolutionary reconstruction to rational design of synthetic genomes. RESULTS: PanForest, presented here, uses random forest classifiers to predict the presence and absence of genes in genomes from the set of other genes present. Performance statistics output by PanForest reveal how predictable each gene's presence or absence is, based on the presence or absence of other genes in the genome. Further, PanForest produces statistics indicating the importance of each gene in predicting the presence or absence of each other gene. The PanForest software can run serially or in parallel, thereby facilitating the analysis of pangenomes at Network of Life scale.A pangenome of 12 741 accessory genes in 1000 Escherichia coli genomes was analysed in around 5 h using eight processors. To demonstrate PanForest's utility, we present a case study and show that certain genes associated with resistance to antimicrobial drugs reliably predict the presence or absence of other genes associated with resistance to the same drug. Further, we highlight several associations between those genes and others not known to be associated with antimicrobial resistance (AMR), or associated with resistance to other drugs. We envisage PanForest's use in studies from multiple disciplines concerning the dynamics of gene distributions in pangenomes ranging from biomedical science and synthetic biology to molecular ecology. AVAILABILITY AND IMPLEMENTATION: The software if freely available with a full manual and can be found with at www.github.com/alanbeavan/PanForest DOI: https://doi.org/10.5281/zenodo.17865482
Attributional sense‐making of distrust in professional service firms: Working in a coopetitive paradox
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Distrust is an inevitable yet often overlooked feature of relationships in professional service firms (PSFs), where simultaneous demands to collaborate and compete produce a coopetitive paradox shaping everyday organizational life. Drawing on 50 in‐depth qualitative interviews using the critical incident technique, we examine how professionals attribute meaning to the development of distrust in their working relationships. The analysis identifies three recurring loci—readings of character and conduct (internal), signals from structures, processes, and cultures (external), and interactional cues in day‐to‐day exchanges (relational)—which often braid together into compound explanations for distrust that travel and endure. In high pressure, identity‐sensitive PSFs, coopetition heightens this braiding, making small ambiguities easier to read as self‐interest and harder to reverse. The study clarifies how distrust functions as an active, socially embedded process of meaning‐making and why it proves so durable in coopetitive settings.</jats:p
Gender language practices in Greek: Reform, uptake and metapragmatic stancetaking
No full text... language. practices. in. Greek: Reform,. uptake. and. metapragmatic. stancetaking. 1. Introduction. As highlighted in the plethora of research (see among others Hellinger & Bußmann 2001; Pfalzgraf 2024a, and references therein), non-sexist ..
Identification of a genetic risk factor for metformin-induced vitamin B12 deficiency
Get PDFAims/hypothesis: Metformin, a mainstay of treatment for type 2 diabetes, can cause vitamin B12 deficiency. Clinical risk factors have been identified but genetic factors remain undiscovered. Our objective was to identify and validate genetic predisposing factors and establish clinical utility. Methods: Individuals with metformin-induced vitamin B12 deficiency (n=487) and metformin-tolerant control individuals (n=6686) were identified in UK Biobank. Genome-wide association analysis was undertaken using logistic regression. Replication was undertaken in three cohorts: a Scottish cohort; the Diabetes Prevention Program Outcomes Study (DPPOS); and a separate cohort from Liverpool. In the Liverpool cohort, plasma metformin levels were also measured. Results: Analysis identified a genome-wide significant non-synonymous SNP in the cubilin gene (CUBN, rs1801222/p.S253F) associated with metformin-induced vitamin B12 deficiency (additive model; adjusted p=1.86×10−10; OR 1.56 [95% CI 1.36, 1.79] for AG vs GG genotype; OR 2.43 [95% CI 1.85, 3.20] for AA vs GG genotype), which was replicated in both the Scottish and the DPPOS cohorts. Vitamin B12 deficiency occurred in 0.84–1.20% of non-metformin-exposed individuals regardless of rs1801222 genotype. However, a large interaction with metformin use was observed, with vitamin B12 deficiency occurring at 6.02% in GG, 7.96% in GA and 12.84% in AA genotype groups. When followed up from metformin initiation, 10% with the AA genotype were vitamin B12 deficient by 11 years vs 21 years for 10% of the GG group. Conclusions/interpretation: The observed genetic association suggests that the rs180122 genotype should be considered a significant risk factor for metformin-induced vitamin B12 deficiency. While clinical monitoring of serum vitamin B12 levels in patients on metformin is inconsistently done, this finding highlights the potential clinical utility of targeted monitoring for certain subsets of individuals, including those genetically at high risk
Laminin N-terminus α31 regulates corneal epithelial cell adhesion and migration through modifying the organization and proteolytic processing of laminin 332
No full textLaminin N-terminus α31 (LaNt α31) is a netrin-like protein generated by alternative splicing of the laminin α3 gene. While previously shown to regulate vascular permeability in vivo, its role in epithelial tissues remains less defined. Here, we demonstrate that LaNt α31 modulates epithelial cell behavior by altering laminin 332 (LM332) organization and hemidesmosome (HD) maturation. Adenoviral driven overexpression of LaNt α31 in corneal epithelial cells led to premature HD assembly, marked by enhanced recruitment of collagen XVII and BPAG1e to β4 integrin, and reduced cell migration. LaNt α31 expression reorganized LM332 from diffuse arcs into tight clusters and co-localized with LMβ3 during matrix deposition. Notably, phenotypes were rescued by precoated extracellular matrix, indicating a matrix-dependent mechanism. Furthermore, LaNt α31 increased matrix metalloproteinase (MMP) activity and LMα3 proteolytic processing, both essential for its effects, as MMP inhibition reversed LM clustering and HD maturation. These findings identify LaNt α31 as a regulator of epithelial homeostasis through modulation of LM332 architecture and cell–matrix adhesion
Geodemographics and residential differentiation: A methodological review and future directions for learned representations of the social landscape
No full textResidential differentiation reflects the complex patterns by which social groups distribute themselves across urban spaces, fundamentally shaping social, economic, and spatial structures. This paper reviews the methodological development of geodemographic classification, tracing its evolution from early social area analysis and factorial ecology through to contemporary approaches. We critically evaluate this lineage of methods for quantifying residential patterns, and identifying persistent limitations in capturing the non-linear complexities of contemporary urban environments. Building on this review, we explore potential future directions involving learned representations of the social landscape, which may offer alternatives to traditional linear dimensionality reduction techniques. Drawing on recent empirical work applying deep learning to geodemographic classification, we consider how such approaches might address identified limitations while acknowledging that their advantages over established methods remain context-dependent and require further empirical validation. We emphasise that any adoption of these techniques must prioritise transparency and interpretability. The paper concludes by outlining potential directions for future research, including how learned representations might be integrated within existing geodemographic workflows
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