CalibFPA: A Focal Plane Array Imaging System based on Online Deep-Learning Calibration

Compressive focal plane arrays (FPA) enable cost-effective high-resolution (HR) imaging by acquisition of several multiplexed measurements on a low-resolution (LR) sensor. Multiplexed encoding of the visual scene is typically performed via electronically controllable spatial light modulators (SLM). An HR image is then reconstructed from the encoded measurements by solving an inverse problem that involves the forward model of the imaging system. To capture system non-idealities such as optical aberrations, a mainstream approach is to conduct an offline calibration scan to measure the system response for a point source at each spatial location on the imaging grid. However, it is challenging to run calibration scans when using structured SLMs as they cannot encode individual grid locations. In this study, we propose a novel compressive FPA system based on online deep-learning calibration of multiplexed LR measurements (CalibFPA). We introduce a piezo-stage that locomotes a pre-printed fixed coded aperture. A deep neural network is then leveraged to correct for the influences of system non-idealities in multiplexed measurements without the need for offline calibration scans. Finally, a deep plug-and-play algorithm is used to reconstruct images from corrected measurements. On simulated and experimental datasets, we demonstrate that CalibFPA outperforms state-of-the-art compressive FPA methods. We also report analyses to validate the design elements in CalibFPA and assess computational complexity

Efficient channel estimation for reconfigurable MIMO antennas: Training techniques and performance analysis

Multifunctional and reconfigurable multiple-input multiple-output (MR-MIMO) antennas are capable of dynamically changing the operation frequencies, polarizations, and radiation patterns, and can remarkably enhance system capabilities. However, in coherent communication systems, using MR-MIMO antennas with a large number of operational modes may incur prohibitive complexity due to the need for channel state estimation for each mode. To address this issue, we derive an explicit relation among the radiation patterns for the antenna modes and the resulting channel gains. We propose a joint channel estimation/prediction scheme where only a subset of all the antenna modes is trained for estimation, and then, the channels associated with the modes that are not trained are predicted using the correlations among the different antenna modes. We propose various training mechanisms with reduced overhead and improved estimation performance, and study the impact of channel estimation error and training overhead on the MR-MIMO system performance. We demonstrate that one can achieve significantly improved data rates and lower error probabilities utilizing the proposed approaches. For instance, under practical settings, we observe about 25% throughput increase or about 3-dB signal-to-noise ratio improvement under the same training overhead with respect to non-reconfigurable antenna systems. © 2002-2012 IEEE

Making waves: Lessons learned from the COVID-19 anthropause in the Netherlands on urban aquatic ecosystem services provisioning and management

Contains fulltext : 284054.pdf (Publisher’s version ) (Open Access

Cyprus women's health research (COHERE) initiative: determining the relative burden of women's health conditions and related co-morbidities in an Eastern Mediterranean population

Background: There is lack of population level data on prevalence and distribution of common benign women's health conditions such as endometriosis, uterine fibroids, polycystic ovary syndrome from the Eastern Mediterranean region despite their significant consequences on quality of life. In particular, there is complete absence of any health statistics from Northern Cyprus, which is an emerging region in Europe. The Cyprus Women's Health Research (COHERE) Initiative is the first large-scale cross-sectional study in the region, aiming to determine the relative burden of benign women's health conditions and related co-morbidities in women living in Northern Cyprus. Methods: The COHERE Initiative is a cross-sectional study aiming to recruit 8000 women aged 18 55 years and residing for at least the past 5 years in Northern Cyprus. The study is composed of two main steps: (1) Baseline recruitment, including (i) completion of a detailed health questionnaire, which is an expanded version of the World Endometriosis Research Foundation (WERF) Endometriosis Phenome Harmonisation Project (EPHect) standardised questionnaire, including questions on demographics, menstrual history, hormone use, pregnancy, pain (pelvic pain, bladder and bowel pain, migraine), medical history, family history of illnesses, medication use, life-style factors in relation to a wide range of reproductive and endocrine conditions, resource use (ii) measurement of weight, height, waist/hip circumference and blood pressure, (iii) collection of saliva samples for genotyping. (2) Gynaecology clinic follow up, including a pelvic ultrasound scan (USS). There is also a follow-up food frequency questionnaire (FFQ) targeted to all women taking part in the baseline recruitment with an aim to collect more detailed data on dietary habits. Discussion: The COHERE Initiative will generate prevalence rates for conditions, define the clinical profiles for women's health conditions, and estimate the economic burden of these conditions in Northern Cyprus. The results will also provide insights into the current status of health-care among women living in a currently under-investigated region. The genetic findings will inform future gene mapping studies for investigation of the heritable component of conditions in this population/region. Moreover, the results will be compared with other centres collecting data using EPHect tools globally and will help determine population differences and similarities in disease patterns and clinical profiles. The COHERE Initiative will serve as a resource to conduct hypothesis-driven follow-up studies investigating effect of the Mediterranean life-style' as well as genetic factors on common benign women's health conditions that maybe specific to Eastern Mediterranean populations

A Multifaceted Analysis of Immune-Endocrine-Metabolic Alterations in Patients with Pulmonary Tuberculosis

Our study investigated the circulating levels of factors involved in immune-inflammatory-endocrine-metabolic responses in patients with tuberculosis with the aim of uncovering a relation between certain immune and hormonal patterns, their clinical status and in vitro immune response. The concentration of leptin, adiponectin, IL-6, IL-1β, ghrelin, C-reactive protein (CRP), cortisol and dehydroepiandrosterone (DHEA), and the in vitro immune response (lymphoproliferation and IFN-γ production) was evaluated in 53 patients with active untreated tuberculosis, 27 household contacts and 25 healthy controls, without significant age- or sex-related differences. Patients had a lower body mass index (BMI), reduced levels of leptin and DHEA, and increased concentrations of CRP, IL-6, cortisol, IL-1β and nearly significant adiponectin values than household contacts and controls. Within tuberculosis patients the BMI and leptin levels were positively correlated and decreased with increasing disease severity, whereas higher concentrations of IL-6, CRP, IL-1β, cortisol, and ghrelin were seen in cases with moderate to severe tuberculosis. Household contacts had lower DHEA and higher IL-6 levels than controls. Group classification by means of discriminant analysis and the k-nearest neighbor method showed that tuberculosis patients were clearly different from the other groups, having higher levels of CRP and lower DHEA concentration and BMI. Furthermore, plasma leptin levels were positively associated with the basal in vitro IFN-γ production and the ConA-driven proliferation of cells from tuberculosis patients. Present alterations in the communication between the neuro-endocrine and immune systems in tuberculosis may contribute to disease worsening

Getting ‘Smad' about obesity and diabetes

Recent findings on the role of transforming growth factor (TGF)-β/Smad3 signaling in the pathogenesis of obesity and type 2 diabetes have underscored its importance in metabolism and adiposity. Indeed, elevated TGF-β has been previously reported in human adipose tissue during morbid obesity and diabetic neuropathy. In this review, we discuss the pleiotropic effects of TGF-β/Smad3 signaling on metabolism and energy homeostasis, all of which has an important part in the etiology and progression of obesity-linked diabetes; these include adipocyte differentiation, white to brown fat phenotypic transition, glucose and lipid metabolism, pancreatic function, insulin signaling, adipocytokine secretion, inflammation and reactive oxygen species production. We summarize the recent in vivo findings on the role of TGF-β/Smad3 signaling in metabolism based on the studies using Smad3−/− mice. Based on the presence of a dual regulatory effect of Smad3 on peroxisome proliferator-activated receptor (PPAR)β/δ and PPARγ2 promoters, we propose a unifying mechanism by which this signaling pathway contributes to obesity and its associated diabetes. We also discuss how the inhibition of this signaling pathway has been implicated in the amelioration of many facets of metabolic syndromes, thereby offering novel therapeutic avenues for these metabolic conditions

Oncogenic Signaling Pathways in The Cancer Genome Atlas.

Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions and DNA methylation in 9,125 tumors profiled by The Cancer Genome Atlas (TCGA), we analyzed the mechanisms and patterns of somatic alterations in ten canonical pathways: cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGFβ signaling, p53 and β-catenin/Wnt. We charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity. Eighty-nine percent of tumors had at least one driver alteration in these pathways, and 57% percent of tumors had at least one alteration potentially targetable by currently available drugs. Thirty percent of tumors had multiple targetable alterations, indicating opportunities for combination therapy