149 research outputs found
Distributed optimal congestion control and channel assignment in wireless mesh networks
Wireless mesh networks have numerous advantages in terms of connectivity as well as reliability. Traditionally the nodes in wireless mesh networks are equipped with single radio, but the limitations are lower throughput and limited use of the available wireless channel. In order to overcome this, the recent advances in wireless mesh networks are based on multi-channel multi-radio approach. Channel assignment is a technique that selects the best channel for a node or to the entire network just to increase the network capacity. To maximize the throughput and the capacity of the network, multiple channels with multiple radios were introduced in these networks. In the proposed system, algorithms are developed to improve throughput, minimise delay, reduce average energy consumption and increase the residual energy for multi radio multi-channel wireless mesh networks. In literature, the existing channel assignment algorithms fail to consider both interflow and intra flow interferences. The limitations are inaccurate bandwidth estimation, throughput degradation under heavy traffic and unwanted energy consumption during low traffic and increase in delay. In order to improve the performance of the network distributed optimal congestion control and channel assignment algorithm (DOCCA) is proposed. In this algorithm, if congestion is identified, the information is given to previous node. According to the congestion level, the node adjusts itself to minimise congestion
Consent-GPT: is it ethical to delegate procedural consent to conversational AI?
Obtaining informed consent from patients prior to a medical or surgical procedure is a fundamental part of safe and ethical clinical practice. Currently, it is routine for a significant part of the consent process to be delegated to members of the clinical team not performing the procedure (eg, junior doctors). However, it is common for consent-taking delegates to lack sufficient time and clinical knowledge to adequately promote patient autonomy and informed decision-making. Such problems might be addressed in a number of ways. One possible solution to this clinical dilemma is through the use of conversational artificial intelligence using large language models (LLMs). There is considerable interest in the potential benefits of such models in medicine. For delegated procedural consent, LLM could improve patients’ access to the relevant procedural information and therefore enhance informed decision-making.
In this paper, we first outline a hypothetical example of delegation of consent to LLMs prior to surgery. We then discuss existing clinical guidelines for consent delegation and some of the ways in which current practice may fail to meet the ethical purposes of informed consent. We outline and discuss the ethical implications of delegating consent to LLMs in medicine concluding that at least in certain clinical situations, the benefits of LLMs potentially far outweigh those of current practices
How do psychiatrists address delusions in first meetings in acute care? A qualitative study
Licensed under the Creative Commons Attribution Licens
A Simple Approach to the Synthesis of Hexagonal-Shaped Silver Nanoplates
This paper deals with the synthesis of hexagonal-shaped silver nanoplates with diameters ranging from 15 to 20 nm along with a smooth nanobulk of 120 nm. These nanoplates were prepared by a kinetically controlled solution growth method using mild reducing agent dextrose, polyvinylpyrrolidone (PVP Mw 40 k Da) as the capping agent and urea as a habit modifier and at a moderate temperature of 50°C. The crystal structure of the highly faceted particles consists mostly of (111) surfaces as revealed by both X-ray diffraction (XRD) studies and transmission electron microscopy (TEM)
Novel mixed-method, inclusive protocol involving global key stakeholders, including carers as experts, to co-develop relevant Caregiver-Reported Outcome Domains (CRODs) in skin disease
Chicken and duck myotubes are highly susceptible and permissive to influenza virus infection
Skeletal muscle, at 30 to 40% of body mass, is the most abundant soft tissue in the body. Besides its primary function in movement and posture, skeletal muscle is a significant innate immune organ with the capacity to produce cytokines and chemokines and respond to proinflammatory cytokines. Little is known about the role of skeletal muscle during systemic influenza A virus infection in any host and particularly avian species. Here we used primary chicken and duck multinucleated myotubes to examine their susceptibility and innate immune response to influenza virus infections. Both chicken and duck myotubes expressed avian and human sialic acid receptors and were readily susceptible to low-pathogenicity (H2N3 A/mallard duck/England/7277/06) and high-pathogenicity (H5N1 A/turkey/England/50-92/91 and H5N1 A/turkey/Turkey/1/05) avian and human H1N1 (A/USSR/77) influenza viruses. Both avian host species produced comparable levels of progeny H5N1 A/turkey/Turkey/1/05 virus.Notably, the rapid accumulation of viral nucleoprotein and matrix (M) gene RNA in chicken and duck myotubes was accompanied by extensive cytopathic damage with marked myotube apoptosis (widespread microscopic blebs, caspase 3/7 activation, and annexin V binding at the plasma membrane). Infected chicken myotubes produced significantly higher levels of proinflammatory cytokines than did the corresponding duck cells. Additionally, in chicken myotubes infected with H5N1 viruses, the induction of interferon beta (IFN-beta) and IFN-inducible genes, including the melanoma differentiation-associated protein 5 (MDA-5) gene, was relatively weak compared to infection with the corresponding H2N3 virus. Our findings highlight that avian skeletal muscle fibers are capable of productive influenza virus replication and are a potential tissue source of infection
Diversity of Nontypeable Haemophilus influenzae Strains Colonizing Australian Aboriginal and Non-Aboriginal Children
Nontypeable Haemophilus influenzae (NTHI) strains are responsible for respiratory-related infections which cause a significant burden of disease in Australian children. We previously identified a disparity in NTHI culture-defined carriage rates between Aboriginal and non-Aboriginal children (42% versus 11%). The aim of this study was to use molecular techniques to accurately determine the true NTHI carriage rates (excluding other culture-identical Haemophilus spp.) and assess whether the NTHI strain diversity correlates with the disparity in NTHI carriage rates. NTHI isolates were cultured from 595 nasopharyngeal aspirates collected longitudinally from asymptomatic Aboriginal (n = 81) and non-Aboriginal (n = 76) children aged 0 to 2 years living in the Kalgoorlie-Boulder region, Western Australia. NTHI-specific 16S rRNA gene PCR and PCR ribotyping were conducted on these isolates. Confirmation of NTHI by 16S rRNA gene PCR corrected the NTHI carriage rates from 42% to 36% in Aboriginal children and from 11% to 9% in non-Aboriginal children. A total of 75 different NTHI ribotypes were identified, with 51% unique to Aboriginal children and 13% unique to non-Aboriginal children (P < 0.0001). The strain richness (proportion of different NTHI ribotypes) was similar for Aboriginal (19%, 65/346) and non-Aboriginal children (19%, 37/192) (P = 0.909). Persistent carriage of the same ribotype was rare in the two groups, but colonization with multiple NTHI strains was more common in Aboriginal children than in non-Aboriginal children. True NTHI carriage was less than that estimated by culture. The Aboriginal children were more likely to carry unique and multiple NTHI strains, which may contribute to the chronicity of NTHI colonization and subsequent diseas
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