Heterogeneous cyber-physical network coexistence through interference contribution rate and uplink power control algorithm (ICR-UPCA) in 6G edge cells

Optimizing power control for interference mitigation at the network cell edge is pivotal in enhancing capacity within a heterogeneous cyber-physical infrastructure, such as smart cities, manufacturing, healthcare, energy grids, transportation, and agriculture, among others. In this paper, we consider the intricate dynamics of Internet of Things (IoT) 5/6G edge users, with a particular focus on the Interference Contribution Rate (ICR), where macro and femtocells are critical network infrastructures. Existing approaches has drawbacks such as computational complexity, overhead, and co-channel interference, among others. However, to fully address interference challenges from the coexistence of diverse network hierarchies, preserving the Quality of Service for femtocell users is prioritized. The paper concurrently enhances the handoff mechanism of cell edge users in the macro cell network. A two-tier heterogeneous network (HetNet) is utilized to initially assess the contribution of edge user equipment (UE) to interference levels during its active state while quantifying it as ICR. Game theory is used to formulate a cohesive model for the coexistence of macro cell (MUE) and femtocell users (FUE). ICR-based uplink power control and reference signal received quality (RSRQ)-based handoff algorithms are deployed to regulate interference levels and enhance the Signal-to-Interference-Noise Ratio (SINR) of the MUE at the cell edge. This is achieved through coordinated transmit power adjustments by both user types. Results indicate a 6.67 % channel capacity loss (interference tolerance) by the FUE, leading to a 12.5 % improvement, translating to approximately 4 Mbps and 1 Mbps channel enhancements, respectively. The MUE and FUE can effectively coordinate power control with minimal overhead, accepting compromises in network channel quality. This approach facilitates improved MUE data access rates while ensuring the preservation of FUE. We show that interference is successfully mitigated through power control in heterogeneous networks with lower computational complexity

Interoception in functional motor symptoms and functional seizures: Preliminary evidence of intact accuracy alongside reduced insight and altered sensibility

Altered interoception may be a pathophysiological mechanism in functional neurological disorder (FND). However, findings have been inconsistent across interoceptive dimensions in FND including functional motor symptoms (FMS) and seizures (FS). Here, individuals with FMS/FS (n = 17) and healthy controls (HC, n = 17) completed measures of interoceptive accuracy and insight (adapted heartbeat tracking task [HTT] with confidence ratings), a time estimation control task (TET) and the Multidimensional Assessment of Interoceptive Awareness-2 (MAIA-2) to assess interoceptive sensibility. The groups did not differ in interoceptive accuracy (p = 1.00, g = 0.00) or confidence (p = .99, g = 0.004), although the FMS/FS group displayed lower scores on the "Not-Distracting" (p < .001, g = 1.42) and "Trusting" (p = .005, g = 1.17) MAIA-2 subscales, relative to HCs. The groups did not differ in TET performance (p = .82, g = 0.08). There was a positive relationship between HTT accuracy and confidence (insight) in HCs (r = .61, p = .016) but not in FMS/FS (r = 0.11, p = .69). HTT confidence was positively correlated with MAIA-2 "Self-Regulation" (r = 0.77, p = .002) and negatively correlated with FND symptom severity (r = -0.84, p < .001) and impact (r = -0.86, p < .001) in FMS/FS. Impaired interoceptive accuracy may not be a core feature in FMS/FS, but reduced insight and altered sensibility may be relevant. Reduced certainty in self-evaluations of bodily experiences may contribute to the pathogenesis of FND symptoms

Deploying aptameric sensing technology for rapid pandemic monitoring

The genome of virulent strains may possess the ability to mutate by means of antigenic shift and/or antigenic drift as well as being resistant to antibiotics with time. The outbreak and spread of these virulent diseases including avian influenza (H1N1), severe acute respiratory syndrome (SARS-Corona virus), cholera (Vibrio cholera), tuberculosis (Mycobacterium tuberculosis), Ebola hemorrhagic fever (Ebola Virus) and AIDS (HIV-1) necessitate urgent attention to develop diagnostic protocols and assays for rapid detection and screening. Rapid and accurate detection of first cases with certainty will contribute significantly in preventing disease transmission and escalation to pandemic levels. As a result, there is a need to develop technologies that can meet the heavy demand of an all-embedded, inexpensive, specific and fast biosensing for the detection and screening of pathogens in active or latent forms to offer quick diagnosis and early treatments in order to avoid disease aggravation and unnecessary late treatment costs. Nucleic acid aptamers are short, single-stranded RNA or DNA sequences that can selectively bind to specific cellular and biomolecular targets. Aptamers, as new-age bioaffinity probes, have the necessary biophysical characteristics for improved pathogen detection. This article seeks to review global pandemic situations in relation to advances in pathogen detection systems. It particularly discusses aptameric biosensing and establishes application opportunities for effective pandemic monitoring. Insights into the application of continuous polymeric supports as the synthetic base for aptamer coupling to provide the needed convective mass transport for rapid screening is also presented

Objective and subjective neurocognitive functioning in functional motor symptoms and functional seizures: preliminary findings

INTRODUCTION: This study aimed to provide a preliminary assessment of objective and subjective neurocognitive functioning in individuals with functional motor symptoms (FMS) and/or functional seizures (FS). We tested the hypotheses that the FMS/FS group would display poorer objective attentional and executive functioning, altered social cognition, and reduced metacognitive accuracy. METHOD: Individuals with FMS/FS (n = 16) and healthy controls (HCs, n = 17) completed an abbreviated CANTAB battery, and measures of intellectual functioning, subjective cognitive complaints, performance validity, and comorbid symptoms. Subjective performance ratings were obtained to assess local metacognitive accuracy. RESULTS: The groups were comparable in age (p = 0.45), sex (p = 0.62), IQ (p = 0.57), and performance validity (p-values = 0.10-0.91). We observed no impairment on any CANTAB test in this FMS/FS sample compared to HCs, although the FMS/FS group displayed shorter reaction times on the Emotional Bias task (anger) (p = 0.01, np2 = 0.20). The groups did not differ in subjective performance ratings (p-values 0.15). Whilst CANTAB attentional set-shifting performance (total trials/errors) correlated with subjective performance ratings in HCs (p-values<0.005, rs = -0.85), these correlations were non-significant in the FMS/FS sample (p-values = 0.10-0.13, rs-values = -0.46-0.50). The FMS/FS group reported more daily cognitive complaints than HCs (p = 0.006, g = 0.92), which were associated with subjective performance ratings on CANTAB sustained attention (p = 0.001, rs = -0.74) and working memory tests (p < 0.001, rs = -0.75), and with depression (p = 0.003, rs = 0.70), and somatoform (p = 0.003, rs = 0.70) and psychological dissociation (p-values<0.005, rs-values = 0.67-0.85). CONCLUSIONS: These results suggest a discordance between objective and subjective neurocognitive functioning in this FMS/FS sample, reflecting intact test performance alongside poorer subjective cognitive functioning. Further investigation of neurocognitive functioning in FND subgroups is necessary

T Wave Alternans in high arrhythmic risk patients: Analysis in time and frequency domains: A pilot study

BACKGROUND: T wave alternans (TA) is a repolarisation phenomenon manifesting as a microvolt beat to beat change in the amplitude of the T wave and ST segment. TA has been shown to be a predictor of arrhythmic risk in unselected myocardial infarction populations. TA has not been used to differentiate risk within the ischaemic cardiomyopathy population. METHODS: The subjects investigated comprised, Group 1: 7 stable patients with remote (>20 months) extensive myocardial scarring and no arrhythmic events (NYHA 3 and 4). Group2: 9 post infarction patients with malignant arrhythmia and implantable defibrillator. During breath holding, 20 continuous QRST complexes from each patients X, Y and Z leads were digitally recorded. Time domain, resultant absolute difference vectors (ATA), were calculated for alternate resultant T wave sequences. Group differences between the magnitude and temporal distribution of mean ATAs and their spectral and cross-spectral analysis were compared. RESULTS: Group 1 v Group 2 mean ATAs were 10.7 (7.17) v 11.7 (8.48) respectively, not significant. Each group had a homogenous temporal distribution of ATAs. Both group's largest mean ATA frequency components were between 0 to 25 Hz, the largest ATA component being at the DC frequency. Cross spectral analysis showed no significant differences in group ATA frequency content. CONCLUSION: The frequency content and microvolt magnitude of T wave alternans was not significantly different in these two groups. The specificity of T wave alternans for differentiating arrhythmic risk in post infarction scarring and heart failure needs investigation

North American carbon dioxide sources and sinks: magnitude, attribution, and uncertainty

North America is both a source and sink of atmospheric carbon dioxide (CO2). Continental sources - such as fossil-fuel combustion in the US and deforestation in Mexico - and sinks - including most ecosystems, and particularly secondary forests - add and remove CO2 from the atmosphere, respectively. Photosynthesis converts CO2 into carbon as biomass, which is stored in vegetation, soils, and wood products. However, ecosystem sinks compensate for only similar to 35% of the continent's fossil-fuel-based CO2 emissions; North America therefore represents a net CO2 source. Estimating the magnitude of ecosystem sinks, even though the calculation is confounded by uncertainty as a result of individual inventory- and model-based alternatives, has improved through the use of a combined approach. Front Ecol Environ 2012; 10(10): 512-519, doi:10.1890/12006

The yeast P5 type ATPase, Spf1, regulates manganese transport into the endoplasmic reticulum

The endoplasmic reticulum (ER) is a large, multifunctional and essential organelle. Despite intense research, the function of more than a third of ER proteins remains unknown even in the well-studied model organism Saccharomyces cerevisiae. One such protein is Spf1, which is a highly conserved, ER localized, putative P-type ATPase. Deletion of SPF1 causes a wide variety of phenotypes including severe ER stress suggesting that this protein is essential for the normal function of the ER. The closest homologue of Spf1 is the vacuolar P-type ATPase Ypk9 that influences Mn2+ homeostasis. However in vitro reconstitution assays with Spf1 have not yielded insight into its transport specificity. Here we took an in vivo approach to detect the direct and indirect effects of deleting SPF1. We found a specific reduction in the luminal concentration of Mn2+ in ∆spf1 cells and an increase following it’s overexpression. In agreement with the observed loss of luminal Mn2+ we could observe concurrent reduction in many Mn2+-related process in the ER lumen. Conversely, cytosolic Mn2+-dependent processes were increased. Together, these data support a role for Spf1p in Mn2+ transport in the cell. We also demonstrate that the human sequence homologue, ATP13A1, is a functionally conserved orthologue. Since ATP13A1 is highly expressed in developing neuronal tissues and in the brain, this should help in the study of Mn2+-dependent neurological disorders

Performing meta-analysis with incomplete statistical information in clinical trials

<p>Abstract</p> <p>Background</p> <p>Results from clinical trials are usually summarized in the form of sampling distributions. When full information (mean, SEM) about these distributions is given, performing meta-analysis is straightforward. However, when some of the sampling distributions only have mean values, a challenging issue is to decide how to use such distributions in meta-analysis. Currently, the most common approaches are either ignoring such trials or for each trial with a missing SEM, finding a similar trial and taking its SEM value as the missing SEM. Both approaches have drawbacks. As an alternative, this paper develops and tests two new methods, the first being the prognostic method and the second being the interval method, to estimate any missing SEMs from a set of sampling distributions with full information. A merging method is also proposed to handle clinical trials with partial information to simulate meta-analysis.</p> <p>Methods</p> <p>Both of our methods use the assumption that the samples for which the sampling distributions will be merged are randomly selected from the same population. In the prognostic method, we predict the missing SEMs from the given SEMs. In the interval method, we define intervals that we believe will contain the missing SEMs and then we use these intervals in the merging process.</p> <p>Results</p> <p>Two sets of clinical trials are used to verify our methods. One family of trials is on comparing different drugs for reduction of low density lipprotein cholesterol (LDL) for Type-2 diabetes, and the other is about the effectiveness of drugs for lowering intraocular pressure (IOP). Both methods are shown to be useful for approximating the conventional meta-analysis including trials with incomplete information. For example, the meta-analysis result of Latanoprost versus Timolol on IOP reduction for six months provided in <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> was 5.05 ± 1.15 (Mean ± SEM) with full information. If the last trial in this study is assumed to be with partial information, the traditional analysis method for dealing with incomplete information that ignores this trial would give 6.49 ± 1.36 while our prognostic method gives 5.02 ± 1.15, and our interval method provides two intervals as Mean ∈ [4.25, 5.63] and SEM ∈ [1.01, 1.24].</p> <p>Conclusion</p> <p>Both the prognostic and the interval methods are useful alternatives for dealing with missing data in meta-analysis. We recommend clinicians to use the prognostic method to predict the missing SEMs in order to perform meta-analysis and the interval method for obtaining a more cautious result.</p

Evaluation of the current knowledge limitations in breast cancer research: a gap analysis

BACKGROUND A gap analysis was conducted to determine which areas of breast cancer research, if targeted by researchers and funding bodies, could produce the greatest impact on patients. METHODS Fifty-six Breast Cancer Campaign grant holders and prominent UK breast cancer researchers participated in a gap analysis of current breast cancer research. Before, during and following the meeting, groups in seven key research areas participated in cycles of presentation, literature review and discussion. Summary papers were prepared by each group and collated into this position paper highlighting the research gaps, with recommendations for action. RESULTS Gaps were identified in all seven themes. General barriers to progress were lack of financial and practical resources, and poor collaboration between disciplines. Critical gaps in each theme included: (1) genetics (knowledge of genetic changes, their effects and interactions); (2) initiation of breast cancer (how developmental signalling pathways cause ductal elongation and branching at the cellular level and influence stem cell dynamics, and how their disruption initiates tumour formation); (3) progression of breast cancer (deciphering the intracellular and extracellular regulators of early progression, tumour growth, angiogenesis and metastasis); (4) therapies and targets (understanding who develops advanced disease); (5) disease markers (incorporating intelligent trial design into all studies to ensure new treatments are tested in patient groups stratified using biomarkers); (6) prevention (strategies to prevent oestrogen-receptor negative tumours and the long-term effects of chemoprevention for oestrogen-receptor positive tumours); (7) psychosocial aspects of cancer (the use of appropriate psychosocial interventions, and the personal impact of all stages of the disease among patients from a range of ethnic and demographic backgrounds). CONCLUSION Through recommendations to address these gaps with future research, the long-term benefits to patients will include: better estimation of risk in families with breast cancer and strategies to reduce risk; better prediction of drug response and patient prognosis; improved tailoring of treatments to patient subgroups and development of new therapeutic approaches; earlier initiation of treatment; more effective use of resources for screening populations; and an enhanced experience for people with or at risk of breast cancer and their families. The challenge to funding bodies and researchers in all disciplines is to focus on these gaps and to drive advances in knowledge into improvements in patient care