Two-way beamforming optimization for full-duplex SWIPT systems

In this paper, we investigate the problem of two-way relay beamforming optimization to maximize the achievable sum-rate of a simultaneous wireless information and power transfer (SWIPT) system with a full-duplex (FD) multiple-input multiple-output (MIMO) amplify-and-forward (AF) relay. In particular, we address the optimal joint design of the receiver power splitting (PS) ratio and the beamforming matrix at the relay node given the channel state information (CSI). Our contribution is an iterative algorithm based on difference of convex (DC) programming and one-dimensional searching to achieve the joint optimal solution. Simulation results are provided to demonstrate the effectiveness of the proposed algorithm

Joint Transmit Power and Relay Two-Way Beamforming Optimization for Energy-Harvesting Full-Duplex Communications

This paper studies the joint optimization problem of two-way relay beamforming, the receiver power splitting (PS) ratio as well as the transmit power at the sources to maximize the achievable sum-rate of a simultaneous wireless information and power transfer (SWIPT) system with a full-duplex (FD) multiple-input multiple- output (MIMO) amplify and forward (AF) relay, assuming perfect channel state information (CSI). In particular, our contribution is an iterative algorithm based on the difference of convex programming (DC) and one dimensional searching to achieve the joint solution. Simulation results are provided to demonstrate the effectiveness of the proposed algorithm

Sirt1 attenuates kidney disorders in male offspring due to maternal high-fat diet

© 2019, MDPI AG. All rights reserved. Maternal obesity has been associated with kidney disorders in male offspring. Our previous studies have demonstrated that Sirtuin (SIRT)1, an essential regulator of metabolic stress responses, is suppressed in the offspring as the result of maternal high-fat diet (HFD) consumption, which is likely to underpin the adverse metabolic and renal outcomes. To examine if SIRT1 overexpression or activation early in life can protect the offspring kidney, wild-type (WT) and transgenic (Tg) offspring were born to the same diet-induced obese female C57BL/6 mice through breeding with hemizygous SIRT1-transgenic (Tg) male mice and examined for renal pathological changes. In separate experiments, SIRT1 activator SRT1720 (25 mg/kg/2 days i.p) was administrated in WT offspring over 6 weeks of postnatal high-fat diet exposure. The results show that offspring born to obese dams have increased kidney weight, higher levels of renal triglycerides, and increased expression of oxidative stress, inflammatory, and fibrotic markers, as well as increased albuminuria compared to offspring of control dams. Both SIRT1 overexpression and SRT1720 treatment attenuated renal lipid contents and expression of lipogenesis, oxidative stress, and inflammatory markers; however, fibrosis was modestly reduced and albuminuria was not affected. The findings suggest that SIRT1 therapy can ameliorate some pathological mechanisms of kidney programming due to maternal obesity but may not be sufficient to prevent the resulting chronic kidney injury

The association between dementia and the risk of hypoglycaemia events among patients with diabetes mellitus: a propensity-score matched cohort analysis

Background: Hypoglycaemia commonly occurs in patients diagnosed with diabetes mellitus (DM) and dementia. The impact of dementia on hypoglycaemic events is controversial. Thus, we evaluated whether dementia increases the risk of hypoglycaemic events in older patients diagnosed with DM. Design: A retrospective cohort study. Setting: We used the IQVIA Medical Research Data (IMRD-UK) database (formerly known as the THIN database). Participants: All patients aged ≥55 years and diagnosed with DM who were prescribed at least two prescriptions of antidiabetic medication between 2000 and 2017. Two groups of patients, dementia and non-dementia group, were propensity-score (PS) matched at 1:2. The risk of hypoglycaemia was assessed through a Cox regression analysis. Main outcome and measures: Hypoglycaemic events were determined during the follow-up period by Read codes. Results: From the database, 133,664 diabetic patients were identified, with a mean follow-up of 6.11 years. During the study period, 7,762 diabetic patients diagnosed with dementia were matched with 12,944 diabetic patients who had not been diagnosed with dementia. The PS-matched Cox regression analysis showed that patients diagnosed with dementia were at a 2-fold increased risk for hypoglycaemic events compared with those not diagnosed with dementia (hazard ratio [HR], 2.00; 95% CI, 1.63–2.66). A similar result was shown for a multivariable analysis using all patient data (adjusted HR, 2.25; 95% CI, 2.22–2.32). Conclusion: Our findings suggest that diabetic patients with a diagnosis of dementia have a statistically significant higher risk of experiencing hypoglycaemia

Did the accuracy of oral amoxicillin dosing of children improve after British National Formulary dose revisions in 2014? National cross-sectional survey in England.

OBJECTIVES: Inaccurate antibiotic dosing can lead to treatment failure, fuel antimicrobial resistance and increase side effects. The British National Formulary for Children (BNFC) guidance recommends oral antibiotic dosing according to age bands as a proxy for weight. Recommended doses of amoxicillin for children were increased in 2014 'after widespread concerns of under dosing'. However, the impact of dose changes on British children of different weights is unknown, particularly given the rising prevalence of childhood obesity in the UK. We aimed to estimate the accuracy of oral amoxicillin dosing in British children before and after the revised BNFC guidance in 2014. SETTING AND PARTICIPANTS: We used data on age and weights for 1556 British children (aged 2-18 years) from a nationally representative cross-sectional survey, the Health Survey for England 2013. INTERVENTIONS: We calculated the doses each child would receive using the BNFC age band guidance, before and after the 2014 changes, against the 'gold standard' weight-based dose of amoxicillin, as per its summary of product characteristics. PRIMARY OUTCOME MEASURE: Assuming children of different weights were equally likely to receive antibiotics, we calculated the percentage of the children who would be at risk of misdosing by the BNFC age bands. RESULTS: Before 2014, 54.6% of children receiving oral amoxicillin would have been underdosed and no child would have received more than the recommended dose. After the BNFC guidance changed in 2014, the number of children estimated as underdosed dropped to 5.8%, but 0.5% of the children would have received too high a dose. CONCLUSIONS: Changes to the BNFC age-banded amoxicillin doses in 2014 have significantly reduced the proportion of children who are likely to be underdosed, with only a minimal rise in the number of those above the recommended range

Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows.

MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a machine learning algorithm. We then provide optimized techniques to validate the identified miRNAs through over-expression/loss-of-function studies. Overall, these protocols apply to any field in biology where high-dimensional data are produced. For complete details on the use and execution of this protocol, please refer to Wong et al. (2021a)

Universal versus selective ultrasonography to screen for large for gestational age infants and associated morbidity

Objective To compare the diagnostic effectiveness of selective versus universal ultrasonography as a screening test for large for gestational age (LGA) infants, and to determine whether previously described ultrasonic markers of excessive fetal growth could identify which suspected LGA fetuses were at increased risk of neonatal morbidity. Methods We analysed data from a prospective cohort study of nulliparous women, the Pregnancy Outcome Prediction study. All women had clinically indicated scans as per routine care. Additionally, all women had blinded ultrasonic estimated fetal weight (EFW) performed at around 36 weeks of gestational age (wkGA). Screen positive for LGA was defined as an EFW >90th percentile ≥34wkGA. Results The current analysis included 3,866 eligible women. Of these, 177 (5%) infants had a birth weight >90th percentile. 1,354 (35%) women had a clinically indicated ultrasonography ≥34wkGA. The sensitivity of selective ultrasonography was 27% and the sensitivity of universal ultrasonography was 38%. The specificity of both approaches was high (99% and 97%, respectively). Using universal ultrasonography, neonatal outcome differed (P for interaction) by abdominal circumference growth velocity (ACGV) for both any neonatal morbidity (P = 0.08) and severe adverse neonatal outcome (P = 0.03). LGA fetuses with increased ACGV had a relative risk (95% CI, P) of any neonatal morbidity of 2.0 (1.1-3.6, P = 0.04) and severe adverse neonatal outcome of 6.5 (2.0-21.1, P = 0.01), whereas LGA fetuses with normal ACGV were not at increased risk. Conclusion Screening using universal ultrasonographic fetal biometry increases the detection of LGA infants and combined with ACGV identifies infants at increased risk of adverse neonatal outcome.The work was supported by the National Institute for Health Research (NIHR) Cambridge Comprehensive Biomedical Research Centre (Women's Health theme), and a project grant from the Stillbirth and neonatal death society (Sands). The study was also supported GE Healthcare (donation of two Voluson i ultrasound systems for this study), and by the NIHR Cambridge Clinical Research Facility, where all research visits took place

Oral cancer: role of the basement membrane in invasion

The document attached has been archived with permission from the Australian Dental Association. An external link to the publisher’s copy is included.Invasive growth of cancer cells is a complex process involving specific interactions between tumour cells and the orderly, integrated complexes of the extracellular matrix. Basement membranes have been proposed as one constituent of extra-cellular matrix which carries responsibility for regulating invasion and metastasis.David F. Wilson, Jiang De-Jun, Angela M. Pierce and Ole W. Wiebki

Perovskite solar cells: a deep analysis using current–voltage and capacitance–voltage techniques

Perovskite solar cells exhibiting~14–15% efficiency were experimentally measured using current–voltage (I–V) and capacitance–voltage (C–V) techniques in order to extract material and device properties, and understand the action of photovoltaic (PV) operation. Deep analyses were carried out on dark- and illuminated I–V curves, and dark C–V curves. Results were compared with those of graded bandgap solar cells fabricated on inorganic n-type window layers. These analyses according to a physicist’s point of view lead to understand the perovskite solar cell as a graded bandgap solar cell built on a p-type window layer. I–V and C–V results show very similar behaviour and the principle of PV action is identical. Once the stability issues with perovskites are solved, these devices have very high potential of producing next generation solar cells reaching at least mid-20% efficiency values

Prediction of Low-Voltage Tetrafluoromethane Emissions Based on the Operating Conditions of an Aluminium Electrolysis Cell

Greenhouse gas (GHG) generation is inherent in the production of aluminium by a technology that uses carbon anodes. Most of those GHG are composed of CO2 produced by redox reaction that occurs in the cell. However, a significant fraction of the annual GHG production is composed of perfluorocarbons (PFC) resulting from anode effects (AE). Multiple investigations have shown that tetrafluoromethane (CF4) can be generated under low-voltage conditions in the electrolysis cells, without global anode effect. The aim of this paper is to find a quantitative relationship between monitored cell parameters and the emissions of CF4. To achieve this goal, a predictive algorithm has been developed using seven cell indicators. These indicators are based on the cell voltage, the noise level and other parameters calculated from individual anode current monitoring. The predictive algorithm is structured into three different steps. The first two steps give qualitative information while the third one quantitatively describes the expected CF4 concentration at the duct end of the electrolysis cells. Validations after each step are presented and discussed. Finally, a sensitivity analysis was performed to understand the effect of each indicator on the onset of low-voltage PFC emissions. The standard deviation of individual anode currents was found to be the dominant variable. Cell voltage, noise level, and maximum individual anode current also showed a significant correlation with the presence of CF4 in the output gas of an electrolysis cell