Fast radio bursts (FRBs) are brief radio emissions from distant astronomical sources. Some are known to repeat, but most are single bursts. Nonrepeating FRB observations have had insufficient ...positional accuracy to localize them to an individual host galaxy. We report the interferometric localization of the single-pulse FRB 180924 to a position 4 kiloparsecs from the center of a luminous galaxy at redshift 0.3214. The burst has not been observed to repeat. The properties of the burst and its host are markedly different from those of the only other accurately localized FRB source. The integrated electron column density along the line of sight closely matches models of the intergalactic medium, indicating that some FRBs are clean probes of the baryonic component of the cosmic web.
The frequency dependence of radio pulse arrival times provides a probe of structures in the intervening media. Demorest et al. was the first to show a short-term (∼100-200 days) reduction in the ...electron content along the line of sight to PSR J1713+0747 in data from 2008 (approximately MJD 54750) based on an apparent dip in the dispersion measure of the pulsar. We report on a similar event in 2016 (approximately MJD 57510), with average residual pulse-arrival times −3.0, −1.3, and −0.7 s at 820, 1400, and 2300 MHz, respectively. Timing analyses indicate possible departures from the standard −2 dispersive-delay dependence. We discuss and rule out a wide variety of potential interpretations. We find the likeliest scenario to be lensing of the radio emission by some structure in the interstellar medium, which causes multiple frequency-dependent pulse arrival-time delays.
We studied 351 patients with smoldering multiple myeloma (SMM) in whom the underlying primary molecular cytogenetic subtype could be determined based on cytoplasmic immunoglobulin fluorescent in situ ...hybridization studies. Hundred and fifty-four patients (43.9%) had trisomies, 127 (36.2%) had immunoglobulin heavy chain (IgH) translocations, 14 (4%) both trisomies and IgH translocations, 53 (15.1%) no abnormalities detected and 3 (0.9%) had monosomy13/del(13q) in the absence of any other abnormality. Among 127 patients with IgH translocations, 57 were t(11;14), 36 t(4;14), 11 musculoaponeurotic fibrosarcoma (MAF) translocations, and 23 other or unknown IgH translocation partner. Time to progression (TTP) to symptomatic multiple myeloma was significantly shorter in patients with the t(4;14) compared with patients with t(11;14), median 28 versus 55 months, respectively, P=0.025. The median TTP was 28 months with t(4;14) (high-risk), 34 months with trisomies alone (intermediate-risk), 55 months with t(11;14), MAF translocations, other/unknown IgH translocations, monosomy13/del(13q) without other abnormalities, and those with both trisomies and IgH translocations (standard-risk), and not reached in patients with no detectable abnormalities (low-risk), P=0.001. There was a trend to shorter TTP with deletion 17p (median TTP, 24 months). Overall survival from diagnosis of SMM was significantly inferior with t(4;14) compared with t(11;14), median 105 versus 147 months, respectively, P=0.036.
Due to extensive root system, connected rhizome bamboos are considered suitable for improving soil properties within a short period, though most of the claims are anecdotal and need to be supported ...with quantified data. The study evaluates seven bamboo species viz., Bambusa balcooa, Bambusa bambos, Bambusa vulgaris, Bambusa nutans, Dendrocalamus hamiltonii, Dendrocalamus stocksii and Dendrocalamus strictus for their rooting pattern and impact on soil health properties. Coarse and fine root intensity was maximum in B. vulgaris. Coarse root biomass ranged from 0.6 kg m
in B. nutans to 2.0 kg m
in B. vulgaris and B. bambos. Fine root biomass ranged from 1.1 kg m
in B. nutans to 4.5 kg m
in D. hamiltonii. Contribution of fine roots in terms of intensity and biomass was much higher than coarse roots. Fine root biomass showed declining trend with increase in soil depth in all the species. During sixth year, the litter fall ranged from 8.1 Mg ha
in D. stocksii to 12.4 Mg ha
in D. hamiltonii. Among soil physical properties significant improvement were recorded in hydraulic conductivity, water stable aggregates and mean weight diameter. Soil pH, organic carbon and available phosphorus under different species did not reveal any significant changes, while significant reduction was observed in total nitrogen and potassium. Significant positive correlation was observed between WSA and iron content. Soil microbial population and enzyme activities were higher in control plot. Considering root distribution, biomass, soil hydraulic conductivity and water stable aggregates, B. bambos, B. vulgaris and D. hamiltonii are recommended for rehabilitation of degraded lands prone to soil erosion.
Although reduced-intensity conditioning (RIC) and non-myeloablative (NMA)-conditioning regimens have been used for over a decade, their relative efficacy vs myeloablative (MA) approaches to ...allogeneic hematopoietic cell transplantation in patients with AML and myelodysplasia (MDS) is unknown. We compared disease status, donor, graft and recipient characteristics with outcomes of 3731 MA with 1448 RIC/NMA procedures performed at 217 centers between 1997 and 2004. The 5-year univariate probabilities and multivariate relative risk outcomes of relapse, TRM, disease-free survival (DFS) and OS are reported. Adjusted OS at 5 years was 34, 33 and 26% for MA, RIC and NMA transplants, respectively. NMA conditioning resulted in inferior DFS and OS, but there was no difference in DFS and OS between RIC and MA regimens. Late TRM negates early decreases in toxicity with RIC and NMA regimens. Our data suggest that higher regimen intensity may contribute to optimal survival in patients with AML/MDS, suggesting roles for both regimen intensity and graft vs leukemia in these diseases. Prospective studies comparing regimens are needed to confirm this finding and determine the optimal approach to patients who are eligible for either MA or RIC/NMA conditioning.
•Shape based clustering model is proposed for solar radiation prediction.•Effect of various combinations of meteorological parameters is analyzed.•Combination of models give better result in ...comparison to single model.•Sunshine duration is prime parameter for prediction.•Wind speed has least effect on prediction.
Estimation of solar radiation is of considerable importance because of the increasing requirement for the design, optimization and performance evaluation of the solar energy systems. This paper presents the development of pattern similarity based clustering algorithm and its application in solar radiation estimation. In the present work continuous density, Hidden Markov Model (HMM) with Pearson R model is utilized for the extraction of shape based clusters from the input meteorological parameters and it is then processed by the Generalized Fuzzy Model (GFM) to accurately estimate the solar radiation. Instead of using distance function as an index of similarity here shape/patterns of the data vectors are used as the similarity index for clustering, which overcomes few of the shortcomings associated with distance based clustering approaches. The estimation method used here exploits the pattern identification prowess of the HMM for cluster selection and generalization and nonlinear modeling capabilities of GFM to predict the solar radiation. The data of solar radiation and various meteorological parameters (sun shine hour, ambient temperature, relative humidity, wind speed and atmospheric pressure) to carry out the present work is taken from the comprehensive weather monitoring station made at Solar Energy Centre, Gurgaon, India. To consider the effect of each meteorological parameter on the estimation of solar radiation the proposed model is applied on 15 different sets comprising of various combinations of input meteorological parameters. The meteorological data of three years from 2009 to 2011 (915days) is used to estimate the solar radiation. Out of these 915days data, the first 750days data is used for the training of the proposed paradigm and rest 165days data is used for validating the model. The results of estimation using all the sets of various combination of meteorological parameter are analyzed and it is found that the sunshine duration is the prime parameter for the estimation of solar radiation. The next important parameter, which influences the estimation of solar radiation, is temperature followed by relative humidity, atmospheric pressure and wind speed. It is interesting to note that worse results are obtained for the sets which are not using sunshine duration as an input. The best performance is achieved by the set which uses all the parameters except the wind speed. The Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and correlation co-efficient (R-value) of the proposed paradigm for the best performing combination of meteorological parameter are 7.9124, 3.0083 and 0.9921 respectively which shows that the proposed model results are in good agreement with the actual measured solar radiation.
The present work is aimed at the design of Levenberg–Marquardt (LM) and adaptive linear network (ADALINE) based soft sensors and their application in inferential control of a multicomponent ...distillation process. Further the ADALINE sensor is trained online using past measurements, to adapt the changes in the inputs and is termed as dynamic ADALINE (D-ADALINE) sensor. The soft sensors are then used in the control loop to obtain LM based inferential controller (LMIC), ADALINE based inferential controller (ADIC) and D-ADALINE based inferential controller (DADIC) for the process. The performance of dynamic controller is also analyzed for different inputs and sampling intervals. The comparison of results shows the efficient and robust prediction capability of D-ADALINE sensor and hence DADIC proves to be the best controller.
► The LM neural network and adaptive linear network based soft sensors are designed. ► The ADALINE sensor is trained online to obtain the dynamic ADALINE soft sensor. ► The designed soft sensors are used to obtain inferential controllers, i.e., LMIC, ADIC and DADIC. ► The performance of DADIC is analyzed for appropriate inputs and sampling intervals.
Deposits formation on heat transfer surfaces is one of the main problems associated to biomass co-combustion. It reduces plant efficiency and availability and increases maintenance costs. It is ...obvious that an increasing amount of low-temperature melting components in fuel ash accelerates and aggravates this process. Research is done to evaluate the validity of thermal analysis methods to characterise fusion of biomass and waste ashes. Laboratory ashes from a set of biomass and waste fuels are leached in successive steps. The original and the leached ashes are analysed by Thermo-Mechanical Analysis (TMA). Traces obtained from TMA show to be promising ash fingerprints to classify deposition tendencies. Additionally Simultaneous Thermal Analysis (STA) is performed on selected samples. Furthermore, improved chemical equilibrium calculations are proposed to predict the proportion of melted species resulting from combustion of biomass fuels. The model takes into account the reactivity of the inorganic matter in the fuel as issued from ash leaching.
In this paper adaptive control of nonlinear dynamical systems using diagonal recurrent neural network (DRNN) is proposed. The structure of DRNN is a modification of fully connected recurrent neural ...network (FCRNN). Presence of self-recurrent neurons in the hidden layer of DRNN gives it an ability to capture the dynamic behaviour of the nonlinear plant under consideration (to be controlled). To ensure stability, update rules are developed using lyapunov stability criterion. These rules are then used for adjusting the various parameters of DRNN. The responses of plants obtained with DRNN are compared with those obtained when multi-layer feed forward neural network (MLFFNN) is used as a controller. Also, in example 4, FCRNN is also investigated and compared with DRNN and MLFFNN. Robustness of the proposed control scheme is also tested against parameter variations and disturbance signals. Four simulation examples including one-link robotic manipulator and inverted pendulum are considered on which the proposed controller is applied. The results so obtained show the superiority of DRNN over MLFFNN as a controller.
•DRNN is successfully applied to control non linear dynamical systems (both SISO and MIMO systems).•Lyapunov stability criterion is used to derive weight update rule.•Learning ability of DRNN is tested and compared with MLFFNN and FCRNN.•Robustness of DRNN, FCRNN and MLFFNN is tested and compared. Both parameter variations and disturbance signal impact are considered.•Structure of DRNN is compared with MLFFNN and FCRNN in terms of dynamical behavior and count of weights.
An increasing number of genetic variants have been implicated in autism spectrum disorders (ASDs), and the functional study of such variants will be critical for the elucidation of autism ...pathophysiology. Here, we report a de novo balanced translocation disruption of TRPC6, a cation channel, in a non-syndromic autistic individual. Using multiple models, such as dental pulp cells, induced pluripotent stem cell (iPSC)-derived neuronal cells and mouse models, we demonstrate that TRPC6 reduction or haploinsufficiency leads to altered neuronal development, morphology and function. The observed neuronal phenotypes could then be rescued by TRPC6 complementation and by treatment with insulin-like growth factor-1 or hyperforin, a TRPC6-specific agonist, suggesting that ASD individuals with alterations in this pathway may benefit from these drugs. We also demonstrate that methyl CpG binding protein-2 (MeCP2) levels affect TRPC6 expression. Mutations in MeCP2 cause Rett syndrome, revealing common pathways among ASDs. Genetic sequencing of TRPC6 in 1041 ASD individuals and 2872 controls revealed significantly more nonsynonymous mutations in the ASD population, and identified loss-of-function mutations with incomplete penetrance in two patients. Taken together, these findings suggest that TRPC6 is a novel predisposing gene for ASD that may act in a multiple-hit model. This is the first study to use iPSC-derived human neurons to model non-syndromic ASD and illustrate the potential of modeling genetically complex sporadic diseases using such cells.
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