Cloning and Sequencing of a Cellobiohydrolase Gene from Trichoderma harzianum FP108

A cbh1 cellobiohydrolase gene was cloned and sequenced from the fungus Trichoderma harzianum FP108. The cloning was performed by PCR amplification of T. harzianum genomic DNA, using PCR primers whose sequence was based on the cbh1 gene from Trichoderma reesei. The 3\u27 end of the gene was isolated by inverse PCR; attempts to clone regions upstream of the 5\u27 end of the gene were unsuccessful. Sequence comparisons suggest that this gene is closely related to cbb1 genes from other Trichoderma species. In particular, all catalytically important amino acids in the protein sequence deduced from the T harzianum cbb1 gene are conserved between species

Asymptotically Optimal Motion Planning for Learned Tasks Using Time-Dependent Cost Maps

In unstructured environments in people’s homes and workspaces, robots executing a task may need to avoid obstacles while satisfying task motion constraints, e.g., keeping a plate of food level to avoid spills or properly orienting a finger to push a button. We introduce a sampling-based method for computing motion plans that are collision-free and minimize a cost metric that encodes task motion constraints. Our time-dependent cost metric, learned from a set of demonstrations, encodes features of a task’s motion that are consistent across the demonstrations and, hence, are likely required to successfully execute the task. Our sampling-based motion planner uses the learned cost metric to compute plans that simultaneously avoid obstacles and satisfy task constraints. The motion planner is asymptotically optimal and minimizes the Mahalanobis distance between the planned trajectory and the distribution of demonstrations in a feature space parameterized by the locations of task-relevant objects. The motion planner also leverages the distribution of the demonstrations to significantly reduce plan computation time. We demonstrate the method’s effectiveness and speed using a small humanoid robot performing tasks requiring both obstacle avoidance and satisfaction of learned task constraints

All-Sky Microwave Imager Data Assimilation at NASA GMAO

Efforts in all-sky satellite data assimilation at the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center have been focused on the development of GSI configurations to assimilate all-sky data from microwave imagers such as the GPM Microwave Imager (GMI) and Global Change Observation Mission-Water (GCOM-W) Advanced Microwave Scanning Radiometer 2 (AMSR-2). Electromagnetic characteristics associated with their wavelengths allow microwave imager data to be relatively transparent to atmospheric gases and thin ice clouds, and highly sensitive to precipitation. Therefore, GMAOs all-sky data assimilation efforts are primarily focused on utilizing these data in precipitating regions. The all-sky framework being tested at GMAO employs the GSI in a hybrid 4D-EnVar configuration of the Goddard Earth Observing System (GEOS) data assimilation system, which will be included in the next formal update of GEOS. This article provides an overview of the development of all-sky radiance assimilation in GEOS, including some performance metrics. In addition, various projects underway at GMAO designed to enhance the all-sky implementation will be introduced

Assimilating All-Sky Microwave Radiance Data to Improve NASA GEOS Forecasts and Analysis

The NASA Global Modeling and Assimilation Office (GMAO) has been pursuing efforts to utilize all-sky (clear+cloudy+precipitating) MW radiance data and has developed a system to assimilate all-sky GPM Microwave Imager (GMI) radiance data in the Goddard Earth Observing System (GEOS) during the last PMM funding period. The system provides additional constraints on the analysis process near the storm regions and adjusts the geophysical parameters such as precipitation, cloud, moisture, surface pressure, and wind by combining information from GMI radiance measurements and model forecasts in an optimal manner. The system proved that assimilating the GMI all-sky radiance data improve the GEOS atmospheric analyses and forecasts. This all-sky data framework has been included in the GEOS Forward Processing (FP) system since July 11, 2018 and assimilates all-sky GMI data in real-time for GEOS global analysis and forecast production at the GMAO. We are currently extending this all-sky GMI radiance data assimilation system to assimilate more all-sky MW radiance data from other sensors such as the Microwave Humidity Sounder (MHS), the Advanced Technology Microwave Sounder (ATMS), the Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Microwave Scanning Radiometer 2 (AMSR2), and the Sounder for Atmospheric Profiling of Humidity in the Intertropics by Radiometery (SAPHIR) onboard the GPM constellation spacecrafts. Preliminary results from this extended all-sky system show increased benefit from cloud- and precipitation-affected MW radiances with much larger spatial and temporal coverages compared to the all-sky system assimilating GMI alone and improved GEOS forecast skills especially for lower tropospheric humidity fields

Physics-informed neural network for friction-involved nonsmooth dynamics problems

Friction-induced vibration (FIV) is very common in engineering areas. Analysing the dynamic behaviour of systems containing a multiple-contact point frictional interface is an important topic. However, accurately simulating nonsmooth/discontinuous dynamic behaviour due to friction is challenging. This paper presents a new physics-informed neural network approach for solving nonsmooth friction-induced vibration or friction-involved vibration problems. Compared with schemes of the conventional time-stepping methodology, in this new computational framework, the theoretical formulations of nonsmooth multibody dynamics are transformed and embedded in the training process of the neural network. Major findings include that the new framework not only can perform accurate simulation of nonsmooth dynamic behaviour, but also eliminate the need for extremely small time steps typically associated with the conventional time-stepping methodology for multibody systems, thus saving much computation work while maintaining high accuracy. Specifically, four kinds of high-accuracy PINN-based methods are proposed: (1) single PINN; (2) dual PINN; (3) advanced single PINN; (4) advanced dual PINN. Two typical dynamics problems with nonsmooth contact are tested: one is a 1-dimensional contact problem with stick-slip, and the other is a 2-dimensional contact problem considering separation-reattachment and stick-slip oscillation. Both single and dual PINN methods show their advantages in dealing with the 1-dimensional stick-slip problem, which outperforms conventional methods across friction models that are difficult to simulate by the conventional time-stepping method. For the 2-dimensional problem, the capability of the advanced single and advanced dual PINN on accuracy improvement is shown, and they provide good results even in the cases when conventional methods fail.Comment: 38 Pages, 24 figure

Electroexcitation of the Δ+(1232)\Delta^{+}(1232) at low momentum transfer

We report on new p$(e,e^\prime p)\pi^\circ$ measurements at the $\Delta^{+}(1232)$ resonance at the low momentum transfer region. The mesonic cloud dynamics is predicted to be dominant and rapidly changing in this kinematic region offering a test bed for chiral effective field theory calculations. The new data explore the low $Q^2$ dependence of the resonant quadrupole amplitudes while extending the measurements of the Coulomb quadrupole amplitude to the lowest momentum transfer ever reached. The results disagree with predictions of constituent quark models and are in reasonable agreement with dynamical calculations that include pion cloud effects, chiral effective field theory and lattice calculations. The reported measurements suggest that improvement is required to the theoretical calculations and provide valuable input that will allow their refinements

Database of cattle candidate genes and genetic markers for milk production and mastitis

A cattle database of candidate genes and genetic markers for milk production and mastitis has been developed to provide an integrated research tool incorporating different types of information supporting a genomic approach to study lactation, udder development and health. The database contains 943 genes and genetic markers involved in mammary gland development and function, representing candidates for further functional studies. The candidate loci were drawn on a genetic map to reveal positional overlaps. For identification of candidate loci, data from seven different research approaches were exploited: (i) gene knockouts or transgenes in mice that result in specific phenotypes associated with mammary gland (143 loci); (ii) cattle QTL for milk production (344) and mastitis related traits (71); (iii) loci with sequence variations that show specific allele-phenotype interactions associated with milk production (24) or mastitis (10) in cattle; (iv) genes with expression profiles associated with milk production (207) or mastitis (107) in cattle or mouse; (v) cattle milk protein genes that exist in different genetic variants (9); (vi) miRNAs expressed in bovine mammary gland (32) and (vii) epigenetically regulated cattle genes associated with mammary gland function (1). Fourty-four genes found by multiple independent analyses were suggested as the most promising candidates and were further in silico analysed for expression levels in lactating mammary gland, genetic variability and top biological functions in functional networks. A miRNA target search for mammary gland expressed miRNAs identified 359 putative binding sites in 3′UTRs of candidate genes

IRES-mediated translation of cellular messenger RNA operates in eIF2α- independent manner during stress

Physiological and pathophysiological stress attenuates global translation via phosphorylation of eIF2α. This in turn leads to the reprogramming of gene expression that is required for adaptive stress response. One class of cellular messenger RNAs whose translation was reported to be insensitive to eIF2α phosphorylation-mediated repression of translation is that harboring an Internal Ribosome Entry Site (IRES). IRES-mediated translation of several apoptosis-regulating genes increases in response to hypoxia, serum deprivation or gamma irradiation and promotes tumor cell survival and chemoresistance. However, the molecular mechanism that allows IRES-mediated translation to continue in an eIF2α-independent manner is not known. Here we have used the X-chromosome linked Inhibitor of Apoptosis, XIAP, IRES to address this question. Using toeprinting assay, western blot analysis and polysomal profiling we show that the XIAP IRES supports cap-independent translation when eIF2α is phosphorylated both in vitro and in vivo. During normal growth condition eIF2α-dependent translation on the IRES is preferred. However, IRES-mediated translation switches to eIF5B-dependent mode when eIF2α is phosphorylated as a consequence of cellular stress

IRES-mediated translation of cellular messenger RNA operates in eIF2α- independent manner during stress

Physiological and pathophysiological stress attenuates global translation via phosphorylation of eIF2α. This in turn leads to the reprogramming of gene expression that is required for adaptive stress response. One class of cellular messenger RNAs whose translation was reported to be insensitive to eIF2α phosphorylation-mediated repression of translation is that harboring an Internal Ribosome Entry Site (IRES). IRES-mediated translation of several apoptosis-regulating genes increases in response to hypoxia, serum deprivation or gamma irradiation and promotes tumor cell survival and chemoresistance. However, the molecular mechanism that allows IRES-mediated translation to continue in an eIF2α-independent manner is not known. Here we have used the X-chromosome linked Inhibitor of Apoptosis, XIAP, IRES to address this question. Using toeprinting assay, western blot analysis and polysomal profiling we show that the XIAP IRES supports cap-independent translation when eIF2α is phosphorylated both in vitro and in vivo. During normal growth condition eIF2α-dependent translation on the IRES is preferred. However, IRES-mediated translation switches to eIF5B-dependent mode when eIF2α is phosphorylated as a consequence of cellular stress