Graph Neural Networks for Power Allocation in Wireless Networks with Full Duplex Nodes

Due to mutual interference between users, power allocation problems in wireless networks are often non-convex and computationally challenging. Graph neural networks (GNNs) have recently emerged as a promising approach to tackling these problems and an approach that exploits the underlying topology of wireless networks. In this paper, we propose a novel graph representation method for wireless networks that include full-duplex (FD) nodes. We then design a corresponding FD Graph Neural Network (F-GNN) with the aim of allocating transmit powers to maximise the network throughput. Our results show that our F-GNN achieves state-of-art performance with significantly less computation time. Besides, F-GNN offers an excellent trade-off between performance and complexity compared to classical approaches. We further refine this trade-off by introducing a distance-based threshold for inclusion or exclusion of edges in the network. We show that an appropriately chosen threshold reduces required training time by roughly 20% with a relatively minor loss in performance

Motivating actions to mitigate plastic pollution

Designing effective policy interventions to motivate mitigation actions requires more realistic assumptions about human decision-making based on empirical evidence from the behavioural sciences. We therefore need to consider behavioural rather than only economic costs and benefits in policy intervention designs

Robust Reinforcement Learning Objectives for Sequential Recommender Systems

Attention-based sequential recommendation methods have demonstrated promising results by accurately capturing users' dynamic interests from historical interactions. In addition to generating superior user representations, recent studies have begun integrating reinforcement learning (RL) into these models. Framing sequential recommendation as an RL problem with reward signals, unlocks developing recommender systems (RS) that consider a vital aspect-incorporating direct user feedback in the form of rewards to deliver a more personalized experience. Nonetheless, employing RL algorithms presents challenges, including off-policy training, expansive combinatorial action spaces, and the scarcity of datasets with sufficient reward signals. Contemporary approaches have attempted to combine RL and sequential modeling, incorporating contrastive-based objectives and negative sampling strategies for training the RL component. In this study, we further emphasize the efficacy of contrastive-based objectives paired with augmentation to address datasets with extended horizons. Additionally, we recognize the potential instability issues that may arise during the application of negative sampling. These challenges primarily stem from the data imbalance prevalent in real-world datasets, which is a common issue in offline RL contexts. While our established baselines attempt to mitigate this through various techniques, instability remains an issue. Therefore, we introduce an enhanced methodology aimed at providing a more effective solution to these challenges

Salivary free light chains as a new biomarker to measure psychological stress: the impact of a university exam period on salivary immunoglobulins, cortisol, DHEA and symptoms of infection:the impact of a university exam period on salivary immunoglobulins, cortisol, DHEA and symptoms of infection

Introduction: Measurement of immunoglobulin free light chains (FLCs) in saliva can serve as a non-invasive biomarker in health and behavioural research. FLCs have been explored in relation to physiological stress but FLC responses to psychological stress and their relationship with infections remain unknown. This study aimed to investigate the impact of exam period stress on salivary FLCs alongside other established biomarkers of stress and whether FLCs relate to symptoms of infection. Methods: 58 healthy adults studying at university completed saliva samples and questionnaires in a period without exams (baseline), and again prior to the start of an exam period. Saliva samples were assessed for FLCs, IgA, cortisol and dehydroepiandrosterone (DHEA). Measures of life events stress, perceived stress, anxiety and depression were completed. Students also reported incidence and severity of symptoms of infection and rated general well-being at baseline, prior to, during and after the exam period. Exercise, sleep and alcohol consumption were also assessed at both timepoints. Results: FLCs secretion rates were significantly lower at the exam period compared to baseline (p &lt;.01), with reductions of 26% and 25% for κ FLC and λ FLC, respectively. In agreement, salivary IgA secretion rate was lower at exams (non-significant trend, p =.07). Cortisol concentration significantly increased at exams (p &lt;.05) while DHEA did not change, leading to an increase in the cortisol:DHEA ratio (p =.06). Depression (p &lt;.05) and anxiety increased from baseline to exams and life stress reported in the build up to the exam period was higher compared with baseline (p &lt;.001). Well-being significantly decreased from baseline to exams (p &lt;.01). The proportion of participants reporting infection symptoms (70%) was unchanged between baseline and prior to exams. No significant relationships were found between FLCs or other saliva parameters and infection symptoms, well-being or stress/psychological measures. Changes in saliva parameters between timepoints were independent of health behaviours. Conclusions: Salivary FLCs are responsive to life events stress and corroborate with IgA. This preliminary study highlights the potential utility of FLCs as a new salivary biomarker in stress research.</p

Investigating the utility of saliva immunoglobulins for the detection of myeloma and using myeloma proteins to clarify partition between oral and systemic immunity

OBJECTIVES Myeloma is characterised by the presence of monoclonal immunoglobulin (M-protein) and the free light chain (FLC) in blood. We investigated whether these M-proteins and FLC are detectable in myeloma patients' saliva to evaluate its utility for non-invasive screening and monitoring of haematological malignancies. METHODS A total of 57 patients with monoclonal gammopathy and 26 age-matched healthy participants provided paired serum and saliva samples for immunoglobulin characterisation and quantification. RESULTS Myeloma patients had IgG or IgA M-protein levels ranging up to five times and FLC levels up to a thousand times normal levels of polyclonal immunoglobulins. Despite these highly elevated levels, only two IgG and no IgA M-proteins or FLC could be detected in paired saliva samples. Most patients had reduced levels of serum polyclonal immunoglobulins, but all had normal levels of salivary IgA. CONCLUSIONS Immunoglobulin transfer from blood is not determined by levels in the systemic circulation and more likely dictated by periodontal inflammation and the integrity of the oral epithelium. Immunoglobulins secreted by bone marrow plasma cells do not substantially enter saliva, which represents a poor medium for myeloma diagnosis. These findings, along with normal salivary IgA levels despite systemic immunoparesis, support a strong partitioning of oral from systemic humoral immunity

Detecting Structure of Complex Network by Quantum Bosonic Dynamics

We introduce a non-interacting boson model to investigate topological structure of complex networks in the present paper. By exactly solving this model, we show that it provides a powerful analytical tool in uncovering the important properties of real-world networks. We find that the ground state degeneracy of this model is equal to the number of connected components in the network and the square of coefficients in the expansion of ground state gives the averaged time for a random walker spending at each node in the infinite time limit. Furthermore, the first excited state appears always on its largest connected component. To show usefulness of this approach in practice, we carry on also numerical simulations on some concrete complex networks. Our results are completely consistent with the previous conclusions derived by graph theory methods.Comment: 4 pages, 3 figure

Detection of carbon monoxide's 4.6 micron fundamental band structure in WASP-39b's atmosphere with JWST NIRSpec G395H

Carbon monoxide (CO) is predicted to be the dominant carbon-bearing molecule in giant planet atmospheres and, along with water, is important for discerning the oxygen and therefore carbon-to-oxygen ratio of these planets. The fundamental absorption mode of CO has a broad, double-branched structure composed of many individual absorption lines from 4.3 to 5.1 μm, which can now be spectroscopically measured with JWST. Here we present a technique for detecting the rotational sub-band structure of CO at medium resolution with the NIRSpec G395H instrument. We use a single transit observation of the hot Jupiter WASP-39b from the JWST Transiting Exoplanet Community Early Release Science (JTEC ERS) program at the native resolution of the instrument (R ~ 2700) to resolve the CO absorption structure. We robustly detect absorption by CO, with an increase in transit depth of 264 ± 68 ppm, in agreement with the predicted CO contribution from the best-fit model at low resolution. This detection confirms our theoretical expectations that CO is the dominant carbon-bearing molecule in WASP-39b's atmosphere and further supports the conclusions of low C/O and supersolar metallicities presented in the JTEC ERS papers for WASP-39b

Effects of Simulated Microgravity on Embryonic Stem Cells

There have been many studies on the biological effects of simulated microgravity (SMG) on differentiated cells or adult stem cells. However, there has been no systematic study on the effects of SMG on embryonic stem (ES) cells. In this study, we investigated various effects (including cell proliferation, cell cycle distribution, cell differentiation, cell adhesion, apoptosis, genomic integrity and DNA damage repair) of SMG on mouse embryonic stem (mES) cells. Mouse ES cells cultured under SMG condition had a significantly reduced total cell number compared with cells cultured under 1 g gravity (1G) condition. However, there was no significant difference in cell cycle distribution between SMG and 1G culture conditions, indicating that cell proliferation was not impaired significantly by SMG and was not a major factor contributing to the total cell number reduction. In contrast, a lower adhesion rate cultured under SMG condition contributed to the lower cell number in SMG. Our results also revealed that SMG alone could not induce DNA damage in mES cells while it could affect the repair of radiation-induced DNA lesions of mES cells. Taken together, mES cells were sensitive to SMG and the major alterations in cellular events were cell number expansion, adhesion rate decrease, increased apoptosis and delayed DNA repair progression, which are distinct from the responses of other types of cells to SMG

Association between bone mineral density and type 2 diabetes mellitus: a meta-analysis of observational studies

Type 2 diabetes mellitus (T2DM) influences bone metabolism, but the relation of T2DM with bone mineral density (BMD) remains inconsistent across studies. The objective of this study was to perform a meta-analysis and meta-regression of the literature to estimate the difference in BMD (g/cm2) between diabetic and non-diabetic populations, and to investigate potential underlying mechanisms. A literature search was performed in PubMed and Ovid extracting data from articles prior to May 2010. Eligible studies were those where the association between T2DM and BMD measured by dual energy X-ray absorptiometry was evaluated using a cross-sectional, cohort or case–control design, including both healthy controls and subjects with T2DM. The analysis was done on 15 observational studies (3,437 diabetics and 19,139 controls). Meta-analysis showed that BMD in diabetics was significantly higher, with pooled mean differences of 0.04 (95% CI: 0.02, 0.05) at the femoral neck, 0.06 (95% CI: 0.04, 0.08) at the hip and 0.06 (95% CI: 0.04, 0.07) at the spine. The differences for forearm BMD were not significantly different between diabetics and non-diabetics. Sex-stratified analyses showed similar results in both genders. Substantial heterogeneity was found to originate from differences in study design and possibly diabetes definition. Also, by applying meta-regression we could establish that younger age, male gender, higher body mass index and higher HbA1C were positively associated with higher BMD levels in diabetic individuals. We conclude that individuals with T2DM from both genders have higher BMD levels, but that multiple factors influence BMD in individuals with T2DM

Meta-analyses identify DNA methylation associated with kidney function and damage

Chronic kidney disease is a major public health burden. Elevated urinary albumin-to-creatinine ratio is a measure of kidney damage, and used to diagnose and stage chronic kidney disease. To extend the knowledge on regulatory mechanisms related to kidney function and disease, we conducted a blood-based epigenome-wide association study for estimated glomerular filtration rate (n = 33,605) and urinary albumin-to-creatinine ratio (n = 15,068) and detected 69 and seven CpG sites where DNA methylation was associated with the respective trait. The majority of these findings showed directionally consistent associations with the respective clinical outcomes chronic kidney disease and moderately increased albuminuria. Associations of DNA methylation with kidney function, such as CpGs at JAZF1, PELI1 and CHD2 were validated in kidney tissue. Methylation at PHRF1, LDB2, CSRNP1 and IRF5 indicated causal effects on kidney function. Enrichment analyses revealed pathways related to hemostasis and blood cell migration for estimated glomerular filtration rate, and immune cell activation and response for urinary albumin-to-creatinineratio-associated CpGs