Approximately 30% of eukaryotic proteins contain hydrophobic signals for localization to the secretory pathway. These proteins can be mislocalized in the cytosol due to mutations in their targeting ...signals, certain stresses, or intrinsic inefficiencies in their translocation. Mislocalized proteins (MLPs) are protected from aggregation by the Bag6 complex and degraded by a poorly characterized proteasome-dependent pathway. Here, we identify the ubiquitin ligase RNF126 as a key component of the MLP degradation pathway. In vitro reconstitution and fractionation studies reveal that RNF126 is the primary Bag6-dependent ligase. RNF126 is recruited to the N-terminal Ubl domain of Bag6 and preferentially ubiquitinates juxtahydrophobic lysine residues on Bag6-associated clients. Interfering with RNF126 recruitment in vitro prevents ubiquitination, and RNF126 depletion in cells partially stabilizes a Bag6 client. Bag6-dependent ubiquitination can be recapitulated with purified components, paving the way for mechanistic analyses of downstream steps in this cytosolic quality control pathway.
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•The chaperone Bag6 recruits the ubiquitin ligase RNF126 to its Ubl domain•RNF126 is necessary and sufficient for optimal ubiquitination of Bag6 clients•Purified Bag6-client complex supports ubiquitination by recombinant RNF126•Bag6-associated mislocalized protein is stabilized by loss of RNF126 in cells
Proteins that fail to be localized to the correct compartment must be degraded to avoid the cellular damage caused by their accumulation. These mislocalized proteins are recognized by the Bag6 complex. The study by Rodrigo-Brenni et al. finds that Bag6 recruits a ubiquitin ligase called RNF126 that tags mislocalized proteins for degradation.
Pimaradienoic acid (PA; ent-pimara-8(14),15-dien-19-oic acid) is a pimarane diterpene found in plants such as Vigueira arenaria Baker (Asteraceae) in the Brazilian savannas. Although there is ...evidence on the analgesic and in vitro inhibition of inflammatory signaling pathways, and paw edema by PA, its anti-inflammatory effect deserves further investigation. Thus, the objective of present study was to investigate the anti-inflammatory effect of PA in carrageenan-induced peritoneal and paw inflammation in mice. Firstly, we assessed the effect of PA in carrageenan-induced leukocyte recruitment in the peritoneal cavity and paw edema and myeloperoxidase activity. Next, we investigated the mechanisms involved in the anti-inflammatory effect of PA. The effect of PA on carrageenan-induced oxidative stress in the paw skin and peritoneal cavity was assessed. We also tested the effect of PA on nitric oxide, superoxide anion, and inflammatory cytokine production in the peritoneal cavity. PA inhibited carrageenan-induced recruitment of total leukocytes and neutrophils to the peritoneal cavity in a dose-dependent manner. PA also inhibited carrageenan-induced paw edema and myeloperoxidase activity in the paw skin. The anti-inflammatory mechanism of PA depended on maintaining paw skin antioxidant activity as observed by the levels of reduced glutathione, ability to scavenge the ABTS cation and reduce iron as well as by the inhibition of superoxide anion and nitric oxide production in the peritoneal cavity. Furthermore, PA inhibited carrageenan-induced peritoneal production of inflammatory cytokines TNF-α and IL-1β. PA presents prominent anti-inflammatory effect in carrageenan-induced inflammation by reducing oxidative stress, nitric oxide, and cytokine production. Therefore, it seems to be a promising anti-inflammatory molecule that merits further investigation.
This work proposes diffusion normalized least mean M-estimate algorithm based on the modified Huber function, which can equip distributed networks with robust learning capability in the presence of ...impulsive interference. In order to exploit the system's underlying sparsity to further improve the learning performance, a sparse-aware variant is also developed by incorporating the <inline-formula><tex-math notation="LaTeX">l_0</tex-math></inline-formula>-norm of the estimates into the update process. We then analyze the transient, steady-state and stability behaviors of the algorithms in a unified framework. In particular, we present an analytical method that is simpler than conventional approaches to deal with the score function since it removes the requirements of integrals and Price's theorem. Simulations in various impulsive noise scenarios show that the proposed algorithms are superior to some existing diffusion algorithms and the theoretical results are verifiable.
Purpose
Previous compassion scales measured correlates or consequences of compassion, included mindfulness in their definition and do not fully operationalize the affective, cognitive, behavioral, ...and interpersonal skills involved in cultivating compassion. The proposed Compassion Questionnaires towards Self (CQS) and Others (CQO) aim to operationalize compassion towards self and others by grounding them in affective, cognitive, behavioral, and interpersonal dimensions with each representing a set of skills that can be cultivated through training and practice.
Methods
Based on the proposed theoretical approach, the CQS and CQO items were developed through consultations with a panel of eight graduate students and a group of ten experts in the field. A series of three studies were conducted to validate the questionnaires and test their clinical utility.
Results
Results from the three studies suggested the merging of the affective and cognitive dimensions, yielding three independent dimensions for both the CQS and CQO. These findings were additionally supported by convergent and discriminant evidence. In addition, results suggested that CQS and CQO subscales’ scores are moderately associated with mindfulness measures and are sensitive to mindfulness training or meditation practice and experience.
Conclusions.
The CQS and CQO are the first questionnaires that operationalize compassion towards self and others as sets of affective, cognitive, behavioral, and interpersonal skills/abilities that are independent from mindfulness, and they have important theoretical and practical implications. Limitations as well as theoretical and practical implications of the CQS and CQO are thoroughly discussed.
Block diagonalization (BD) based precoding techniques are well-known linear transmit strategies for multiuser MIMO (MU-MIMO) systems. By employing BD-type precoding algorithms at the transmit side, ...the MU-MIMO broadcast channel is decomposed into multiple independent parallel single user MIMO (SU-MIMO) channels and achieves the maximum diversity order at high data rates. The main computational complexity of BD-type precoding algorithms comes from two singular value decomposition (SVD) operations, which depend on the number of users and the dimensions of each user's channel matrix. In this work, low-complexity precoding algorithms are proposed to reduce the computational complexity and improve the performance of BD-type precoding algorithms. We devise a strategy based on a common channel inversion technique, QR decompositions, and lattice reductions to decouple the MU-MIMO channel into equivalent SU-MIMO channels. Analytical and simulation results show that the proposed precoding algorithms can achieve a comparable sum-rate performance as BD-type precoding algorithms, substantial bit error rate (BER) performance gains, and a simplified receiver structure, while requiring a much lower complexity.
•A closed formula for the fractional derivation based on Gaussian function.•Analysed expression is based on Caputo–Fabrizio definition.•Gaussian based derivatives are applied on practical signal ...processing problems.•Convolution properties increase applicability of Gaussian based derivatives.•Gaussian parameters give additional customising to fractional filter design.
The Gaussian function has been employed in a vast number of practical and theoretical applications since it was proposed. Likewise, Gaussian function and its ordinary derivatives are considered as powerful tools for signal processing and control applications, e.g., smoothing, sampling, change detection, blob detection, and transforms based on the Hermite polynomials. Nonetheless, it has impressive characteristics hidden amongst its fractional derivatives eager to be explored and studied in-depth. This work proposes a closed formula for the (n+ν)–order fractional derivative of the Gaussian function, based on the Caputo–Fabrizio definition, as an approach for analysing those attributes. The obtained expression was numerically tested with several fractional orders, and their resulting behaviours were eventually analysed. Finally, three practical applications on signal processing via this closed formula were discussed, i.e., customisable wavelets, image processing filters, and Rayleigh distributions.
► A large scale hydrodynamic modeling approach based on limited data was developed. ► Large scale 1D hydrodynamic models using limited data can have good performance. ► Necessary information for ...large scale hydrodynamic models can be extracted from STRM. ► 1D hydrodynamic models can be used for flow routing in large scale hydrologic models. ► The model can also provide good water level and flood inundation results.
In this paper, we present a large-scale hydrologic model with a full one-dimensional hydrodynamic module to calculate flow propagation on a complex river network. The model uses the full Saint–Venant equations and a simple floodplain storage model, and therefore is capable of simulating a wide range of fluvial processes such as flood wave delay and attenuation, backwater effects, flood inundation and its effects on flood waves. We present the model basic equations and GIS algorithms to extract model parameters from relatively limited data, which is globally available, such as the SRTM DEM. GIS based algorithms include the estimation of river width and depth using geomorphological relations, river cross section bottom level and floodplain geometry extracted from DEM, etc. We also show a case study on one of the major tributaries of the Amazon, the Purus River basin. A model validation using discharge and water level data shows that the model is capable of reproducing the main hydrological features of the Purus River basin. Also, realistic floodplain inundation maps were derived from the results of the model. Our main conclusion is that it is possible to employ full hydrodynamic models within large-scale hydrological models even using limited data for river geometry and floodplain characterization.
In the fog computing paradigm, fog nodes are placed on the network edge to meet end-user demands with low latency, providing the possibility of new applications. Although the role of the cloud ...remains unchanged, a new network infrastructure for fog nodes must be created. The design of such an infrastructure must consider user mobility, which causes variations in workload demand over time in different regions. Properly deciding on the location of fog nodes is important to reduce the costs associated with their deployment and maintenance. To meet these demands, this paper discusses the problem of locating fog nodes and proposes a solution which considers time-varying demands, with two classes of workload in terms of latency. The solution was modeled as a mixed-integer linear programming formulation with multiple criteria. An evaluation with real data showed that an improvement in end-user service can be obtained in conjunction with the minimization of the costs by deploying fewer servers in the infrastructure. Furthermore, results show that costs can be further reduced if a limited blocking of requests is tolerated.
•The SWOT satellite would likely observe 50–100m wide rivers, globally.•We compare potential SWOT observation extent to the current river gauge network.•SWOT detection of 50m rivers (vs. 100m) would ...yield substantial resolution gains.•SWOT would improve observation of global runoff at scales >10–50,000km2.•SWOT and gauges combined would most improve understanding of global runoff patterns.
Despite its importance as a major element of the global hydrologic cycle, runoff remains poorly constrained except at the largest spatial scales due to limitations of the global stream gauge network and inadequate data sharing. Efforts using remote sensing to infer runoff from discharge estimates are limited by characteristics of present-day sensors. The proposed Surface Water and Ocean Topography (SWOT) mission, a joint project between the United States and France, aims to substantially improve space-based estimates of river discharge. However, the extent of rivers observable by SWOT, likely limited to those wider than 50–100m, remains unknown. Here, we estimate the extent of SWOT river observability globally using a downstream hydraulic geometry (DHG) approach combining basin areas from the Hydro1k and Hydrosheds elevation products, discharge from the Global Runoff Data Centre (GRDC), and width estimates from a global width–discharge relationship. We do not explicitly consider SWOT-specific errors associated with layover and other phenomena in this analysis, although they have been considered in formulation of the 50–100m width thresholds. We compare the extent of SWOT-observable rivers with GRDC and USGS gauge datasets, the most complete datasets freely available to the global scientific community. In the continental US, SWOT would match USGS river basin coverage only at large scales (>25,000km2). Globally, SWOT would substantially improve on GRDC observation extent: SWOT observation of 100m (50m) rivers will allow discharge estimation in >60% of 50,000km2 (10,000km2) river basins. In contrast, the GRDC observes fewer than 30% (15%) of these basins. SWOT could improve characterization of global runoff processes, especially with a 50m observability threshold, but in situ gauge data remains essential and must be shared more freely with the international scientific community.
In this paper, we propose buffer-aided physical-layer network coding (PLNC) techniques for improving data transmission over cooperative networks. In particular, we develop buffer-aided PLNC schemes ...and relay pair selection algorithms for direct-sequence code-division multiple access (DS-CDMA) systems. We devise PLNC techniques based on optimal linear network coding matrices according to the maximum likelihood and minimum mean-square error design criteria in order to generate the network coded symbols that are sent to the destination. In the proposed buffer-aided PLNC schemes, relay pair selection algorithms are developed to obtain the relay pair and the packets in the buffer entries with the best performance and the associated link combinations are used for the data transmission. An analysis of the computational complexity of the proposed techniques along with their sum-rate analysis is carried out. Simulation results show that the proposed techniques significantly outperform previously reported approaches.
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