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A Mobile Edge Generation approach
No full textMobile edge generation (MEG) is an emerging technology that allows the network to meet the challenging traffic load expectations posed by the rise of generative artificial intelligence (GAI). A novel MEG model is proposed for deploying GAI models on edge servers (ES) and user equipment (UE) to jointly complete test-to-image generation tasks. In the generaation task, the user uploads the text prompt and the ES and UE will cooperatively generate the image for the user. To enable the data transmission exchange between the ES and the UE, a seed based MEG protocol is employed, where a coded latent feature is created as a generation seed. A pre-trained latent diffusion model (LDM) is invoked to generate the latent feature, and a compression coding technique is proposed for compressing the latent features. The proposed MEG enabled text-to-image generation system is evaluated in terms of image quality and transmission overhead. The numerical results indicate that, compared to the conventional centralized generation-and-downloading scheme, the symbol number of the transmission of MEG is materially reduced. In addition, the proposed compression coding approach can improve the quality of generated images under low signal-to-noise ratio (SNR) conditions.</p
Different measures of working memory decline at different rates across adult ageing, and dual task costs plateau in mid life
No full textWorking memory allows us to store information in mind over brief time periods while engaging in other information-processing activities. As such, this system supports cognitive dual-tasking, that is, remembering information while performing a concurrent processing task. Age-related dual-task deficits have been proposed as a critical feature of lifespan cognitive decline. However, evidence regarding such deficits has been mixed, and knowledge of the conditions under which such deficits appear remains elusive. Moreover, several studies have suggested that different aspects of working memory decline at different rates with age and that age-related change is not necessarily linear. We explored lifespan changes in 539 participants (aged 15-90 years) on several memory, processing, and dual (combined) tasks. We addressed two research questions: (1) Does the magnitude of dual-task costs change across the lifespan? (2) Do different measures of memory, processing, and dual-tasking, all decline at the same rate with age? We found that younger-young adults outperformed all other participants on dual-task measures. However, deficits did not appear to increase from the age of 35 years into older age, suggesting that dual-task ability declined in early adulthood but not thereafter between midlife and older age. Processing performance appeared to decline linearly and more rapidly with age than memory performance. Our finding that for some measures, the largest changes occurred in the transition from early to middle adulthood, provides an interesting contrast to the widely held assumption that cognition declines continuously across the adult lifespan
Depression detection in read and spontaneous speech: a multimodal approach for lesser-resourced languages
No full textThe global prevalence of depression highlights the need for innovative early detection methods. Technological advances have driven novel speech analysis strategies for depression identification, yet existing methods often overlook the nuances between read and spontaneous speech and the variability in real-world data. This research introduces a multimodal approach, employing a hybrid model that combines Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN) for detailed audio analysis and a pre-trained BERT model for textual insights. Using a comprehensive corpus of 228 recordings, which includes 64 cases of depression clinically diagnosed by psychiatrists, this study refines a speech-based detection technique reflective of real-world scenarios. Through decision-level fusion, this methodology achieves an accuracy rate of 94.30% and an F-Score of 94.51%, outperforming existing benchmarks in the detection of depression in both read and spontaneous speech. An in-depth feature correlation analysis reveals that spontaneous speech in depressed individuals exhibits pronounced spectral patterns, particularly in Mel-frequency cepstral coefficients (MFCC) interrelationships, whereas read speech retains a subtle but significant diagnostic value. These findings not only show the effectiveness of the multimodal approach but also highlight its better diagnostic precision in the identification of depression, thus setting a new standard for depression diagnosis. By emphasising the critical role of multimodal data analysis, this research significantly advances mental health diagnostics, offering valuable insights for medical practitioners, scholars, and technologists, and represents a considerable leap forward in achieving more accurate and accessible mental health diagnostics. Our code is publicly available at https://github.com/56kd/MulitmodalDepressionDetection.<br/
Targeting the PREX2/RAC1/PI3Kβ signaling axis confers sensitivity to clinically relevant therapeutic approaches in melanoma
No full textMetastatic melanoma remains a major clinical challenge. Large-scale genomic sequencing of melanoma has identified bona fide activating mutations in RAC1, which are associated with resistance to BRAF-targeting therapies. Targeting the RAC1-GTPase pathway, including the upstream activator PREX2 and the downstream effector PI3Kβ, could be a potential strategy for overcoming therapeutic resistance, limiting melanoma recurrence, and suppressing metastatic progression. Here, we used genetically engineered mouse models and patient-derived BRAFV600E-driven melanoma cell lines to dissect the role of PREX2 in melanomagenesis and response to therapy. While PREX2 was dispensable for the initiation and progression of melanoma, its loss conferred sensitivity to clinically relevant therapeutics targeting the MAPK pathway. Importantly, genetic and pharmacological targeting of PI3Kβ phenocopied PREX2 deficiency, sensitizing model systems to therapy. These data reveal a druggable PREX2/RAC1/PI3Kβ signaling axis in BRAF-mutant melanoma that could be exploited clinically
Sickness absence trajectories among young and early midlife employees with psychological distress: the contributions of social and health-related factors in a longitudinal register linkage study
No full textPsychological distress has been associated with sickness absence (SA), but less is known about whether there are distinct patterns in the development of SA among people with psychological distress. We examined trajectories of short- and long-term SA among employees with psychological distress and how social and health-related factors are associated with them. We used the employer's register data on all-cause short- (≤ 10 working days) and long-term (> 10 working days) SA with a two-year follow-up. We prospectively linked the Helsinki Health Study survey data on 19-39-year-old employees of the City of Helsinki, Finland, in 2017, to the SA data. We included 1060 participants (81% women) who reported experiencing psychological distress, measured by the emotional wellbeing scale of RAND-36. Survey responses of age; gender; education; marital status; social support, procedural and interactional organisational justice, and bullying at work; physical activity; diet; tobacco and alcohol use; prior SA; and the level of psychological distress were included as exposures. Group-based trajectory modelling and multinomial logistic regression were used for the analyses. We identified four short-term SA trajectories: 'low' (n = 379, 36% of participants), 'descending' (n = 212, 20%), 'intermediate' (n = 312, 29%), and 'high' (n = 157, 15%); and two long-term SA trajectories: 'low' (n = 973, 92%) and 'high' (n = 87, 8%). A higher education, fewer prior SA, and lower levels of psychological distress were associated with the 'low' short- and long-term SA trajectories. SA trajectories differ among employees with psychological distress. Early intervention and support are needed among employees with mental health symptoms to prevent future SA.
Application of microarray patches for the transdermal administration of psychedelic drugs in micro-doses
No full textThroughout history, psychedelic compounds have been used for religious, spiritual and recreational purposes. A plethora of studies have reported the use of psychedelic compounds in the treatment of various conditions, such as alcoholism, addictions, depressive state to borderline schizophrenia, personality disorder, among other mental disorders. Psychedelic microdosing, a common technique in recent years, involves the consumption of small doses of psychedelic drugs for therapeutic purposes. This study investigated the potential of hydrogel-forming microarray patches (HF-MAPs) to deliver N,N-dimethyltryptamine (DMT), 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT), and mescaline (MES) in small doses through the skin. To this purpose, HF-MAPs were prepared using poly(vinyl alcohol) (PVA) and poly(vinyl pyrrolidone) (PVP), using citric acid as the crosslinker. Two different reservoirs, containing PVP and PVA as the main components and poly(ethylene)glycol 400 (PEG400) and glycerol as plasticising agents, were used to deliver all the drugs from the HF-MAPs. Franz cells studies in excised neonatal porcine skin demonstrated that the permeation of DMT, 5-MeO-DMT and MES was better from the PEG400 reservoir, showing a permeation of 60.71 %, 59.61 % and 41.85 % respectively. Pharmacokinetic studies in rats showed that HF-MAP technology as a strategy for microdosing psychedelic compounds was also demonstrated with DMT. AUCt0-final for the HF-MAP cohort (7186 ± 1296 ng/mL*h) was significantly greater than the IM cohort (1803 ± 53.25 ng/mL*h) (p = 0.0020), with a relative bioavailability of ∼ 72 %. Considering their pharmacokinetic profile, the frequency of DMT dosing could be reduced with HF-MAP when compared to the IM route.<br/
Using group peer reflection to support learning disability nursing students during placements
No full textNursing students tend to experience high levels of stress and anxiety, particularly in relation to clinical placements, and may require additional support to manage challenging aspects of practice learning. One way of providing additional support to students is to offer group reflection sessions. This article discusses the use of facilitated group peer reflection sessions for learning disability nursing students from Queen’s University Belfast on placements in one trust area in Northern Ireland. The sessions, part of the Connecting Peers in Learning Disability (CoPe-LD) project, had high attendance rates and low logistical and labour requirements. Students gave overwhelmingly positive feedback, explaining that the sessions had supported them with knowledge development and clinical decision-making and had given them a sense of support and safety, which may have helped them to discuss difficulties experienced during their placements