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There is an ongoing debate on the importance of genetic factors in cancer development, where gene-centered cancer predisposition seems to show that only 5 to 10% of the cancer cases are inheritable. By conducting a systematic analysis of germline genomes of 9712 cancer patients representing 22 common cancer types along with 16,670 noncancer individuals, we identified seven cancer-associated germline genomic patterns (CGGPs), which summarized trinucleotide mutational spectra of germline genomes. A few CGGPs were consistently enriched in the germline genomes of patients whose tumors had smoking signatures or correlated with oncogenesis- and genome instability–related mutations. Furthermore, subgroups defined by the CGGPs were significantly associated with distinct oncogenic pathways, tumor histological subtypes, and prognosis in 13 common cancer types, suggesting that germline genomic patterns enable to inform treatment and clinical outcomes. These results provided evidence that cancer risk and clinical outcomes could be encoded in germline genomes. Germline variants when organized as genomic patterns are associated with cancer risk, oncogenic pathways, and clinical outcomes.

Non-orthogonal multiple access (NOMA) has been proposed as a promising technology that is capable of improving the spectral efficiency of fifth-generation wireless networks and beyond. However, in practical communication scenarios, transceiver architectures inevitably suffer from radio frequency (RF) front-end related impairments that cause non-negligible performance degradation. This issue can be addressed by analog and digital signal processing algorithms, but factors such as time-varying hardware characteristics and imperfect compensation schemes result to detrimental residual distortions. In the present contribution we investigate the physical layer security of NOMA-based amplify-and-forward relay systems under such realistically incurred residual hardware impairment (RHI) effects. Exact and asymptotic analytic expressions for the corresponding outage probability (OP) and intercept probability (IP) of the considered set up over multipath fading channels are derived and corroborated by respective simulation results. Based on this, it is shown that RHI affects both the legitimate users and eavesdroppers by increasing the OP and decreasing the IP. For a fixed OP, RHI generally increases the corresponding IP, thereby reducing the secure performance of the system. Further interesting insights are also provided, verifying the importance of the offered results for the effective design and deployment of secure cooperative communication systems. acceptedVersion Peer reviewed

An over 200 W high-power first-order random Raman fiber laser (RRFL) at 1238 nm is demonstrated. The laser is based on a half-open cavity with a piece of 30 m phosphosilicate fiber. This RRFL is pumped by a conventional 1064 nm Yb-doped fiber laser. After suppressing the silica Raman component, a maximum output power of 206.7 W is obtained with a full width half-maximum linewidth of 7.1 nm at a pump power of 346.3 W, corresponding to an optical-to-optical efficiency of 59.7%. To the best of our knowledge, this is the highest reported output power of RRFL on the basis of phosphosilicate fiber with the shortest cavity length.

The COnstrain Dark Energy with X-ray clusters (CODEX) sample contains the largest flux limited sample of X-ray clusters at $0.35 < z < 0.65$. It was selected from ROSAT data in the 10,000 square degrees of overlap with BOSS, mapping a total number of 2770 high-z galaxy clusters. We present here the full results of the CFHT CODEX program on cluster mass measurement, including a reanalysis of CFHTLS Wide data, with 25 individual lensing-constrained cluster masses. We employ $lensfit$ shape measurement and perform a conservative colour-space selection and weighting of background galaxies. Using the combination of shape noise and an analytic covariance for intrinsic variations of cluster profiles at fixed mass due to large scale structure, miscentring, and variations in concentration and ellipticity, we determine the likelihood of the observed shear signal as a function of true mass for each cluster. We combine 25 individual cluster mass likelihoods in a Bayesian hierarchical scheme with the inclusion of optical and X-ray selection functions to derive constraints on the slope $��$, normalization $��$, and scatter $��_{\ln ��| ��}$ of our richness-mass scaling relation model in log-space: $\left = ����+ ��$, with $��= \ln (M_{200c}/M_{\mathrm{piv}})$, and $M_{\mathrm{piv}} = 10^{14.81} M_{\odot}$. We find a slope $��= 0.49^{+0.20}_{-0.15}$, normalization $ \exp(��) = 84.0^{+9.2}_{-14.8}$ and $��_{\ln ��| ��} = 0.17^{+0.13}_{-0.09}$ using CFHT richness estimates. In comparison to other weak lensing richness-mass relations, we find the normalization of the richness statistically agreeing with the normalization of other scaling relations from a broad redshift range ($0.0 37 pages, 12 figures

Neutrophils play a critical role in host defense against Pseudomonas aeruginosa infection. Mechanisms underlying the negative regulation of neutrophil function in bacterial clearance remain incompletely defined. Here, we demonstrate that protein tyrosine phosphatase-1B (PTP1B) is a negative regulator of P. aeruginosa clearance by neutrophils. PTP1B-deficient neutrophils display greatly enhanced bacterial phagocytosis and killing, which are accompanied by increased Toll-like receptor 4 (TLR4) signaling activation and nitric oxide (NO) production following P. aeruginosa infection. Interestingly, PTP1B deficiency mainly upregulates the production of IL-6 and IFN-β, leads to enhanced TLR4-dependent STAT1 activation and iNOS expression by neutrophils following P. aeruginosa infection. Further studies reveal that PTP1B and STAT1 are physically associated. These findings demonstrate a negative regulatory mechanism in neutrophil underlying the elimination of P. aeruginosa infection though a PTP1B-STAT1 interaction.

Today's Industrial IoT (IIoT) applications often employ large-scale and dense sensor deployments for environmental monitoring. A hierarchical Bluetooth Low Energy (BLE) based architecture can facilitate power efficiency and reliability for data collection in dense networks. But if the network is static with fixed parameter settings, it can not be adaptable to dynamic application requirements. Although BLE is a parametric protocol, it does not provide any built-in feature for parameter tuning. To achieve network adaptability, we introduce and design SoftBLE, a Software Defined Networking (SDN) framework that provides controllability for BLE based 2-tier networks. It takes advantages of advanced control knobs recently available in BLE protocol stacks. SoftBLE is complemented by two orchestration algorithms to optimize gateway and sensor parameters. Evaluation results from both an experimental testbed and a large-scale simulation study show that almost all the SoftBLE sensors can save around 70% of transmission power while keeping Packet Reception Rate (PRR) above 99.9%.

Remote sensing-derived cropland products have depicted the location and extent of agricultural lands with an ever increasing accuracy. However, limited attention has been devoted to distinguishing between actively cropped fields and fallowed fields within agricultural lands, and in particular so in grass fallow systems of semi-arid areas. In the Sahel, one of the largest dryland regions worldwide, crop-fallow rotation practices are widely used for soil fertility regeneration. Yet, little is known about the extent of fallow fields since fallow is not explicitly differentiated within the cropland class in any existing remote sensing-based land use/cover maps, regardless of the spatial scale. With a 10 m spatial resolution and a 5-day revisit frequency, Sentinel-2 satellite imagery made it possible to disentangle agricultural land into cropped and fallow fields, facilitated by Google Earth Engine (GEE) for big data handling. Here we produce the first Sahelian fallow field map at a 10 m resolution for the baseline year 2017, accomplished by designing a remote sensing driven protocol for generating reference data for mapping over large areas. Based on the 2015 Copernicus Dynamic Land Cover map at 100 m resolution, the extent of fallow fields in the cropland class is estimated to be 63% (403,617 km2) for the Sahel in 2017. Similar results are obtained for five contemporary cropland products, with fallow fields occupying 57–62% of the cropland area. Yet, it is noted that the total estimated area coverage depends on the quality of the different cropland products. The share of cropped fields within the Copernicus cropland area is found to be higher in the arid regions (200–300 mm rainfall) as compared to the semi-arid regions (300–600 mm rainfall). The woody cover fraction within cropped and fallow fields is found to have a reversed pattern between arid (higher woody cover in cropped fields) and semi-arid (higher woody cover in fallow fields) regions. The method developed, using cloud-based Earth Observation (EO) data and computation on the GEE platform, is expected to be reproducible for mapping the extent of fallow fields across global croplands. Future applications based on multi-year time series is expected to improve our understanding of crop-fallow rotation dynamics in grass fallow systems being key in teasing apart how cropland intensification and expansion affect environmental variables, such as soil fertility, crop yields and local livelihoods in low-income regions such as the Sahel. The mapping result can be visualized via a web viewer (https://buwuyou.users.earthengine.app/view/fallowinsahel).

This study presents a multiparameter analysis of aerosol trends over the last 2 decades at regional and global scales. Regional time series have been computed for a set of nine optical, chemical-composition and mass aerosol properties by using the observations from several ground-based networks. From these regional time series the aerosol trends have been derived for the different regions of the world. Most of the properties related to aerosol loading exhibit negative trends, both at the surface and in the total atmospheric column. Significant decreases in aerosol optical depth (AOD) are found in Europe, North America, South America, North Africa and Asia, ranging from −1.2 % yr−1 to −3.1 % yr−1. An error and representativity analysis of the spatially and temporally limited observational data has been performed using model data subsets in order to investigate how much the observed trends represent the actual trends happening in the regions over the full study period from 2000 to 2014. This analysis reveals that significant uncertainty is associated with some of the regional trends due to time and space sampling deficiencies. The set of observed regional trends has then been used for the evaluation of 10 models (6 AeroCom phase III models and 4 CMIP6 models) and the CAMS reanalysis dataset and of their skills in reproducing the aerosol trends. Model performance is found to vary depending on the parameters and the regions of the world. The models tend to capture trends in AOD, the column Ångström exponent, sulfate and particulate matter well (except in North Africa), but they show larger discrepancies for coarse-mode AOD. The rather good agreement of the trends, across different aerosol parameters between models and observations, when co-locating them in time and space, implies that global model trends, including those in poorly monitored regions, are likely correct. The models can help to provide a global picture of the aerosol trends by filling the gaps in regions not covered by observations. The calculation of aerosol trends at a global scale reveals a different picture from that depicted by solely relying on ground-based observations. Using a model with complete diagnostics (NorESM2), we find a global increase in AOD of about 0.2 % yr−1 between 2000 and 2014, primarily caused by an increase in the loads of organic aerosols, sulfate and black carbon.