Kalman-Filter Based Hybridization of Classic and Cold Atom Interferometry Accelerometers for Future Satellite Gravity Missions

Proof-of-principle demonstrations have been made for cold atom interferometer (CAI) sensors. Using CAI-based accelerometers in the next generation of satellite gravimetry missions can provide long-term stability and precise measurements of the non-gravitational forces acting on the satellites. This would allow a better understanding of climate change processes and geophysical phenomena which require long-term monitoring of mass variations with sufficient spatial and temporal resolution. The proposed accuracy and long-term stability of CAI-based accelerometers appear promising, while there are some major drawbacks in the long dead times and the comparatively small dynamic range of the sensors. One interesting way to handle these limitations is to use a hybridization with a conventional navigation sensor. This study discusses one possible solution to employ measurements of a CAI accelerometer together with a conventional Inertial Measurement Unit (IMU) using a Kalman filter framework. A hybrid navigation solution of these two sensors for applications on ground has already been demonstrated in simulations. Here, we adapt this method to a space-based GRACE-like gravimetry mission. A simulation is performed, where the sensitivity of the CAI accelerometer is estimated based on state-of-the-art ground sensors and further published space scenarios. Our results show that the Kalman filter framework can be used to combine the measurements of conventional inertial measurement units with the CAI accelerometers measurements in a way to benefit from the high accuracy of the conventional IMU measurements in higher frequencies together with the high stability of CAI measurements in lower frequencies. We will discuss the challenges, potential solutions, and the possible performance limits of the proposed hybrid accelerometry scenario

Validity and reliability of the Arabic version of Activities of Daily Living (ADL)

Background. The Activity of Daily Living (ADL) is an instrument that screens elderly respondents for physical functioning and assesses whether they are dependent or independent in their daily activities. This study demonstrates a translation procedure and obtains the reliability and validity of a translated, Arabic ADL. Methods. The ADL was translated to Arabic through a forward translation method followed by a committee-consensual approach. The ADL and the Arabic Mini-Mental State Examination (AMMSE) were administered to an opportunistic sample of 354 Lebanese elderly living in nursing homes who did not have dementia. Results. Reliability split half measures, sensitivity, and negative predictive values were high across all dimensions of the ADL with the exception of feeding. There were non-significant differences on the scored ADL between the three age groups: young age, middle age and older old. In addition, a non-significant difference was found on the scored ADL between the high and low AMMSE scores. Conclusion. Overall, the translated ADL was consistent and valid measure for assessing daily activities in elderly nursing home residents. As it is quick and easy to use, the ADL in Arabic could help caregivers and doctors to prescribe appropriate physical exercise for elderly Arabic speaking patients

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Cardiac Tissue Engineering: Implications for Pediatric Heart Surgery

Children with severe congenital malformations, such as single-ventricle anomalies, have a daunting prognosis. Heart transplantation would be a therapeutic option but is restricted due to a lack of suitable donor organs and, even in case of successful heart transplantation, lifelong immune suppression would frequently be associated with a number of serious side effects. As an alternative to heart transplantation and classical cardiac reconstructive surgery, tissue-engineered myocardium might become available to augment hypomorphic hearts and/or provide new muscle material for complex myocardial reconstruction. These potential applications of tissue engineered myocardium will, however, impose major challenges to cardiac tissue engineers as well as heart surgeons. This review will provide an overview of available cardiac tissue-engineering technologies, discuss limitations, and speculate on a potential application of tissue-engineered heart muscle in pediatric heart surgery

Оценка надежности высоконадежных систем с учетом ЗИП

Предложены приближенные верхние и нижние оценки коэффициента готовности высоконадежной восстанавливаемой системы со структурной избыточностью. Полученные расчетные соотношения могут использоваться для оценки надежности высоконадежных систем с учетом различных стратегий пополнения ЗИП

Blurred lines: work, eldercare and HRM

peer-reviewedThe full text of this article will not be available in ULIR until the embargo expires on the 27/06/2020Increased levels of female labour market participation have impacted on the ability of families to provide care for elderly relatives in many industrialised societies. While work–family balance has received significant academic attention, less attention has focused specifically on individuals with eldercare responsibility, a cohort which accounts for a growing segment of the labour market internationally. Taking a qualitative research approach this paper uses work/family border theory to the constraints and facilitators to reconciling care and employment for employees working full-time in Ireland. The findings highlight the significant impact that eldercare provision has on employees with regard to day-to-day work commitments. We find that while general work–life balance policies exist within organisations, that the design and functionality of such policies are of limited value to elder caregivers. Furthermore, this paper highlights how the lack of formal HR policies around eldercare within organisations results in a reliance on supervisory discretion. We make some recommendations for organisational level strategies to address the needs of a growing number of caregivers.peer-reviewe

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment