Numerical prediction of load-displacement behaviors of adhesively bonded joints at different extension rates and temperatures

The present work focuses on simulation of nonlinear mechanical behaviors of adhesively bonded DLS (double lap shear) joints for variable extension rates and temperatures using the implicit ABAQUS solver. Load-displacement curves of DLS joints at nine combinations of extension rates and environmental temperatures are initially obtained by conducting tensile tests in a UTM. The joint specimens are made from dual phase (DP) steel coupons bonded with a rubber-toughened adhesive. It is shown that the shell-solid model of a DLS joint, in which substrates are modeled with shell elements and adhesive with solid elements, can effectively predict the mechanical behavior of the joint. Exponent Drucker-Prager or Von Mises yield criterion together with nonlinear isotropic hardening is used for the simulation of DLS joint tests. It has been found that at a low temperature (-20 degrees C), both Von Mises and exponent Drucker-Prager criteria give close prediction of experimental load-extension curves. However. at a high temperature (82 degrees C), Von Mises condition tends to yield a perceptibly softer joint behavior, while the corresponding response obtained using exponent Drucker-Prager criterion is much closer to the experimental load-displacement curve.

Gene patent practice across plant and human genomes

The uses of genetic sequences to inform, enable or create products or services for human biomedicine are substantially different from their uses in crop-based agriculture. Here, we explore what similarities and differences may emerge in patent use and strategies, and map patent-disclosed sequences onto three important plant genomes: maize (corn), rice and soybean. We focus on those referenced in the granted patent claims to compare their uses to the approach used in human gene patenting.

The ownership question of plant gene and genome intellectual properties

The restructuring of the crop agriculture industry over the past two decades has enabled patent holders to exclude, prevent and deter others from using certain research tools and delay or block further follow-on inventions

CSSP (Consensus Secondary Structure Prediction): a web-based server for structural biologists

Sequence-structure correlation studies are important in deciphering the relationships between various structural aspects, which may shed light on the protein-folding problem. The first step of this process is the prediction of secondary structure for a protein sequence of unknown three-dimensional structure. To this end, a web server has been created to predict the consensus secondary structure using well known algorithms from the literature. Furthermore, the server allows users to see the occurrence of predicted secondary structural elements in other structure and sequence databases and to visualize predicted helices as a helical wheel plot. The web server is accessible at http://bioserver1.physics.iisc.ernet.in/cssp/.

Prediction of a large-gap quantum-spin-Hall insulator: Diamond-like GaBi bilayer

A quantum-spin-Hall (QSH) state was achieved experimentally, albeit at a low critical temperature because of the narrow band gap of the bulk material. Twodimensional topological insulators are critically important for realizing novel topological applications. Using density functional theory (DFT), we demonstrated that hydrogenated GaBi bilayers (HGaBi) form a stable topological insulator with a large nontrivial band gap of 0.320 eV, based on the state-of-the-art hybrid functional method, which is implementable for achieving QSH states at room temperature. The nontrivial topological property of the HGaBi lattice can also be confirmed from the appearance of gapless edge states in the nanoribbon structure. Our results provide a versatile platform for hosting nontrivial topological states usable for important nanoelectronic device applications.

Structures of three different neutral polysaccharides of Acinetobacter baumannii, NIPH190, NIPH201, and NIPH615, assigned to K30, K45, and K48 capsule types, respectively, based on capsule biosynthesis gene clusters

Neutral capsular polysaccharides (CPSs) were isolated from Acinetobacter baumannii NIPH190, NIPH201, and NIPH615. The CPSs were found to contain common monosaccharides only and to be branched with a side-chain 1→3-linked β-d-glucopyranose residue. Structures of the oligosaccharide repeat units (K units) of the CPSs were elucidated by 1D and 2D 1H and 13C NMR spectroscopy. Novel CPS biosynthesis gene clusters, designated KL30, KL45, and KL48, were found at the K locus in the genome sequences of NIPH190, NIPH201, and NIPH615, respectively. The genetic content of each gene cluster correlated with the structure of the CPS unit established, and therefore, the capsular types of the strains studied were designated as K30, K45, and K48, respectively. The initiating sugar of each K unit was predicted, and glycosyltransferases encoded by each gene cluster were assigned to the formation of the linkages between sugars in the corresponding K unit.

Prediction of compressive strength of SCC and HPC with high volume fly ash using ANN

An artificial neural network (ANN) is presented to predict a 28-day compressive strength of a normal and high strength self compacting concrete (SCC) and high performance concrete (HPC) with high volume fly ash. The ANN is trained by the data available in literature on normal volume fly ash because data on SCC with high volume fly ash is not available in sufficient quantity. Further, while predicting the strength of HPC the same data meant for SCC has been used to train in order to economise on computational effort. The compressive strengths of SCC and HPC as well as slump flow of SCC estimated by the proposed neural network are validated by experimental results.

Prediction of Ultimate Capacity of Laterally Loaded Piles in Clay: A Relevance Vector Machine Approach

This study investigates the potential of Relevance Vector Machine (RVM)-based approach to predict the ultimate capacity of laterally loaded pile in clay. RVM is a sparse approximate Bayesian kernel method. It can be seen as a probabilistic version of support vector machine. It provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. RVM model outperforms the two other models based on root-mean-square-error (RMSE) and mean-absolute-error (MAE) performance criteria. It also stimates the prediction variance. The results presented in this paper clearly highlight that the RVM is a robust tool for prediction Of ultimate capacity of laterally loaded piles in clay.

Pulse-echo ultrasound transit time spectroscopy: A comparison of experimental measurements and simulation prediction

Considering ultrasound propagation through complex composite media as an array of parallel sonic rays, a comparison of computer simulated prediction with experimental data has previously been reported for transmission mode (where one transducer serves as transmitter, the other as receiver) in a series of ten acrylic step-wedge samples, immersed in water, exhibiting varying degrees of transit time inhomogeneity. In this study, the same samples were used but in pulse-echo mode, where the same ultrasound transducer served as both transmitter and receiver, detecting both ‘primary’ (internal sample interface) and ‘secondary’ (external sample interface) echoes. A transit time spectrum (TTS) was derived, describing the proportion of sonic rays with a particular transit time. A computer simulation was performed to predict the transit time and amplitude of various echoes created, and compared with experimental data. Applying an amplitude-tolerance analysis, 91.7±3.7% of the simulated data was within ±1 standard deviation (STD) of the experimentally measured amplitude-time data. Correlation of predicted and experimental transit time spectra provided coefficients of determination (R2) ranging from 100.0% to 96.8% for the various samples tested. The results acquired from this study provide good evidence for the concept of parallel sonic rays. Further, deconvolution of experimental input and output signals has been shown to provide an effective method to identify echoes otherwise lost due to phase cancellation. Potential applications of pulse-echo ultrasound transit time spectroscopy (PE-UTTS) include improvement of ultrasound image fidelity by improving spatial resolution and reducing phase interference artefacts.

Sediment concentration prediction and statistical evaluation for annual load estimation

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.

Roles of forced nicotine exposure and Comt gene disruption in the development of addiction-related behavioural and neurochemical changes in mice

Activation of midbrain dopamine systems is thought to be critically involved in the addictive properties of abused substances. Drugs of abuse increase dopamine release in the nucleus accumbens and dorsal striatum, which are the target areas of mesolimbic and nigrostriatal dopamine pathways, respectively. Dopamine release in the nucleus accumbens is thought to mediate the attribution of incentive salience to rewards, and dorsal striatal dopamine release is involved in habit formation. In addition, changes in the function of prefrontal cortex (PFC), the target area of mesocortical dopamine pathway, may skew information processing and memory formation such that the addict pays an abnormal amount of attention to drug-related cues. In this study, we wanted to explore how long-term forced oral nicotine exposure or the lack of catechol-O-methyltransferase (COMT), one of the dopamine metabolizing enzymes, would affect the functioning of these pathways. We also wanted to find out how the forced nicotine exposure or the lack of COMT would affect the consumption of nicotine, alcohol, or cocaine. First, we studied the effect of forced chronic nicotine exposure on the sensitivity of dopamine D2-like autoreceptors in microdialysis and locomotor activity experiments. We found that the sensitivity of these receptors was unchanged after forced oral nicotine exposure, although an increase in the sensitivity was observed in mice treated with intermittent nicotine injections twice daily for 10 days. Thus, the effect of nicotine treatment on dopamine autoreceptor sensitivity depends on the route, frequency, and time course of drug administration. Second, we investigated whether the forced oral nicotine exposure would affect the reinforcing properties of nicotine injections. The chronic nicotine exposure did not significantly affect the development of conditioned place preference to nicotine. In the intravenous self-administration paradigm, however, the nicotine-exposed animals self-administered nicotine at a lower unit dose than the control animals, indicating that their sensitivity to the reinforcing effects of nicotine was enhanced. Next, we wanted to study whether the Comt gene knock-out animals would be a suitable model to study alcohol and cocaine consumption or addiction. Although previous work had shown male Comt knock-out mice to be less sensitive to the locomotor-activating effects of cocaine, the present study found that the lack of COMT did not affect the consumption of cocaine solutions or the development of cocaine-induced place preference. However, the present work did find that male Comt knock-out mice, but not female knock-out mice, consumed ethanol more avidly than their wild-type littermates. This finding suggests that COMT may be one of the factors, albeit not a primary one, contributing to the risk of alcoholism. Last, we explored the effect of COMT deficiency on dorsal striatal, accumbal, and prefrontal cortical dopamine metabolism under no-net-flux conditions and under levodopa load in freely-moving mice. The lack of COMT did not affect the extracellular dopamine concentrations under baseline conditions in any of the brain areas studied. In the prefrontal cortex, the dopamine levels remained high for a prolonged time after levodopa treatment in male, but not female, Comt knock-out mice. COMT deficiency induced accumulation of 3,4-dihydroxyphenylacetic acid, which increased further under levodopa load. Homovanillic acid was not detectable in Comt knock-out animals either under baseline conditions or after levodopa treatment. Taken together, the present results show that although forced chronic oral nicotine exposure affects the reinforcing properties of self-administered nicotine, it is not an addiction model itself. COMT seems to play a minor role in dopamine metabolism and in the development of addiction under baseline conditions, indicating that dopamine function in the brain is well-protected from perturbation. However, the role of COMT becomes more important when the dopaminergic system is challenged, such as by pharmacological manipulation.

Influence of environmental and instrumental variables on the non-invasive prediction of Brix in pineapple using near infrared spectroscopy

The Brix content of pineapple fruit can be non-invasively predicted from the second derivative of near infrared reflectance spectra. Correlations obtained using a NIRSystems 6500 spectrophotometer through multiple linear regression and modified partial least squares analyses using a post-dispersive configuration were comparable with that from a pre-dispersive configuration in terms of accuracy (e.g. coefficient of determination, R2, 0.73; standard error of cross validation, SECV, 1.01°Brix). The effective depth of sample assessed was slightly greater using the post-dispersive technique (about 20 mm for pineapple fruit), as expected in relation to the higher incident light intensity, relative to the pre-dispersive configuration. The effect of such environmental variables as temperature, humidity and external light, and instrumental variables such as the number of scans averaged to form a spectrum, were considered with respect to the accuracy and precision of the measurement of absorbance at 876 nm, as a key term in the calibration for Brix, and predicted Brix. The application of post-dispersive near infrared technology to in-line assessment of intact fruit in a packing shed environment is discussed.

Cloning Of Rice Dna And Identification Of Transfer-Rna Gene Clones

THE rapid development of recombinant DNA technology has brought forth a revolution in biology'>", it aids us to have a closer look at the 'way genes are organized, eS11 ecially in the complex eucaryotic genornes'<", Although many animal and yeast genes have been studied in detail using recombinant DNA technology, plant genes have seldom been targets for such studie., Germination is an ideal process to study gene expression .because it effects a . shift in the metabolic status of seeds from a state of 'dormancy to an active one. AJ;l understanding of gene organization and regulation darin.g germination can be accomplblted by molecular cloning of DNA from seeds lik.e rice. To study the status of histone, rRNA tRNA and other genes in the rice genome, a general method was developed to clone eucarvotic DNA in a' plasmid vector pBR 322. This essentially ~ involves the following steps. The rice embryo and plasmid pBR 322 DNAs were cut witll restriction endonuclease Bam Hi to generate stick.Y ends, The plasmid DNA was puosphatased, the DNA~ ware a~·tnealed and joined 'by T4 phage DNA ligase. The recombinant DNA molecules thus produced were transjerred into E. coli and colonies containing them Were selected by their sensitivity to tetracycline and resistance to ampicillin, Two clones were identified . 2S haVing tRNA genes by hybridization of the DNA in the clones \vitl1 32P-la.belled rice tRNAs.

Association of microRNA 17–92 cluster host gene (MIR17HG) polymorphisms with breast cancer

Breast cancer incidence and mortality rates are increasing despite our current knowledge on the disease. Ninety-five percent of breast cancer cases correspond to sporadic forms of the disease and are believed to involve an interaction between environmental and genetic determinants. The microRNA 17–92 cluster host gene (MIR17HG) has been shown to regulate expression of genes involved in breast cancer development and progression. Study of single-nucleotide polymorphisms (SNPs) located in this cluster gene could help provide a further understanding of its role in breast cancer. Therefore, this study investigated six SNPs in the MIR17HG using two independent Australian Caucasian case–control populations (GRC-BC and GU-CCQ BB populations) to determine association to breast cancer susceptibility. Genotyping was undertaken using chip-based matrix assisted laser desorption ionisation time-of-flight (MALDI-TOF) mass spectrometry (MS). We found significant association between rs4824505 and breast cancer at the allelic level in both study cohorts (GRC-BC p = 0.01 and GU-CCQ BB p = 0.03). Furthermore, haplotypic analysis of results from our combined population determined a significant association between rs4824505/rs7336610 and breast cancer susceptibility (p = 5 × 10−4). Our study is the first to show that the A allele of rs4824505 and the AC haplotype of rs4824505/rs7336610 are associated with risk of breast cancer development. However, definitive validation of this finding requires larger cohorts or populations in different ethnical backgrounds. Finally, functional studies of these SNPs could provide a deeper understanding of the role that MIR17HG plays in the pathophysiology of breast cancer.