Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetics of morphine, yield and its candidate characters in opium poppy (Papaver somniferum L.)

Combining ability in opium poppy, Papaver somniferum L. was analyzed through full diallel cross comprising five parents, 20 F1s (including reciprocals) and 20 F2s (including reciprocals). The analysis of variance revealed significant differences for all the characters demonstrating considerable variation among genotypes. Estimates of components of general and specific combining ability variances exhibited equal importance of both additive and non additive gene actions for the expression of all the characters. However, higher magnitude of SCA components of variance indicated preponderance of non –additive effects for all the traits except for leaves/plant, seed yield and opium yield in F2 generation. The average degree of dominance was more than unity, showed over dominance and also conferred above findings. Among the parents NB-1KR401-3/3 for capsules/plant, stem diameter, capsule wt/plant, capsule size, peduncle length and seed yield, NB-5KR3-2-2/1 for days to 50% flowering, plant height leaves/plant, capsule wt/plant, and seed yield, Papline and 58/1 for plant height and opium yield and NB-5KR40-7/2/-3 for morphine content were found good general combiners. Inclusion of lines with good GCA in a single or multiple crosses followed by intermating i.e. population improvement approaches may be expected to offer genetic improvement in breeding for higher opium, seed yield and its component traits.
An Area and Power Efficient Cartesian Phase Shifter + Mixer Circuit Applied to WLAN System

A two-antenna array receiver is designed for WLAN application to build a maximum ratio combiner (MRC) system. A new signal-path Cartesian phase generation and combination technique is proposed to shift the RF signal by 22.5 phase steps. The 3 dB improvement in received SNR is achieved in comparison to single path receiver. The 0.29 mm^2 RF paths consumes 30 mW in 0.13 mum CMOS process.
RCDP: Raptor-based content delivery protocol for unicast communication in wireless networks for ITS

Recent advances in forward error correction (FEC) coding techniques were focused on addressing the challenges of multicast and broadcast delivery. However, FEC approaches can also be used for unicast content delivery in order to solve transmission control protocol issues found in wireless networks. In thispaper, we exploit the error resilient properties of Raptor codes by proposing Raptor-based content delivery protocol (RCDP) — a novel solution for reliable and bidirectional unicast communication in lossy links that can improve content delivery in situations where the wireless network is the bottleneck. RCDP has been designed, validated, optimized, and its performance has been analyzed in terms of throughput and resource efficiency. Experimental results show that RCDP is a highly efficient solution for environments characterized by high delays and packet losses making it very suitable for intelligent transport system oriented applications since it achieves significant performance improvements when compared to traditional transport layer protocols.
A Principle for Describing and Verifying Brain Mechanisms Using Ongoing Activity

Not even the most informed scientist can setup a theory that takes all brain signals into account. A neuron not only receives neuronal short range and long range input from all over the brain but a neuron also receives input from the extracellular space, astrocytes and vasculature. Given this complexity, how does one describe and verify a typical brain mechanism in vivo? Common to most described mechanisms is that one focuses on how one specific input signal gives rise to the activity in a population of neurons. This can be an input from a brain area, a population of neurons or a specific cell type. All remaining inputs originating from all over the brain are lumped together into one background input. The division into two inputs is attractive since it can be used to quantify the relative importance of either input. Here we have chosen to extract the specific and the background input by means of recording and inhibiting the specific input. We summarize what it takes to estimate the two inputs on a single trial level. The inhibition should not only be strong but also fast and the specific input measurement has to be tailor-made to the inhibition. In essence, we suggest ways to control electrophysiological experiments in vivo. By applying those controls it may become possible to describe and verify many brain mechanisms, and it may also allow the study of the integration of spontaneous and ongoing activity, which in turn governs cognition and behavior.
Output regulation of periodic signals for DPS: an infinite-dimensional signal Generator

In this note, we consider output regulation and disturbance rejection of periodic signals via state feedback in the setting of exponentially stabilizable linear infinite-dimensional systems. We show that if an infinite-dimensional exogenous system is generating periodic reference signals, solvability of the state feedback regulation problem is equivalent to solvability of the so called equations. This result allows us to consider asymptotic tracking of periodic reference signals which only have absolutely summable Fourier coefficients, while in related existing work the reference signals are confined to be infinitely smooth. We also discuss solution of the regulator equations and construct the actual feedback law to achieve output regulation in the single-input-single-output (SISO) case: The output regulation problem is solvable if the transfer function of the stabilized plant does not have zeros at the frequencies i/spl omega//sub n/ of the periodic reference signals and if the sequence ([CR(i/spl omega//sub n/, A+BK)B]/sup -1/ /spl times/(Q/spl phi//sub n/-CR(i/spl omega//sub n/, A+BK)P/spl phi//sub n/)) /sub n/spl isin/z//spl isin/l/sup n2/. A one-dimensional heat equation is used as an illustrative example.
COMBINATION THERAPY USING ATNF BINDING PROTEIN FOR TREATING TNF MEDIATED DISEASES

4,179,337 12/1979 Davis et al. 4,289,690 9/1981 Pestka et al. . 4,766,106 8/1988 Katre et al. . 4,847,325 7/1989 Shadle et al. 4,917,888 4/1990 Katre et al. . 4,935,233 6/1990 Bell et al. 4.959,314 9/1990 Mark et al. 5,116,964 5/1992 Capon et al. 5,122,614 6/1992 Zalipsky. 5,136,021 8/1992 Dembinski et al. . 5,153,265 10/1992 Shadle et al. 5,166.322 11/1992 Shaw et al. 5,211945 5/1993 Wallach et al. . 5,252,714 10/1993 Harris et al. 5,359,037 10/1994 Wallach et al. 5,395,760 3/1995 Smith et al. 5,446,090 8/1995 Harris. 5,478,925 12/1995 Wallach et al. 5,512,544 4/1996 Wallach et al. . 5,605,690 2/1997 Jacobs et al. . 5,610,279 3/1997 Brockhaus et al. . 5,633,145 5/1997 Feldmann et al. . 5,695,953 12/1997 Wallach et al. 5,712,155 1/1998 Smith et al. 5,739,208 4/1998 Harris. 5,747,639 5/1998 Seely. 5,808,029 9/1998 Brockhaus et al. . 5,811.261 9/1998 Wallach et al. . 5,843,791 12/1998 Hauptmann et al. 5,863,786 1/1999 Feldmann et al. . 6,096,728 8/2000 Collins et al. . 514/62 FOREIGN PATENT DOCUMENTS
A fast automatic low-rank determination algorithm for noisy matrix completion

Rank estimation is an important factor for low-rank based matrix completion, and most works devoted to this problem have considered the minimization of nuclear norm instead of matrix rank. However, when nuclear norm minimization shifts to `regularization' due to noise, it is difficult to estimate original matrix rank, precisely. In present paper, we propose a new fast algorithm to precisely estimate matrix rank and perform completion without using nuclear norm. In our extensive experiments, the proposed algorithm significantly outperformed nuclear-norm based method for accuracy, especially and Incremental OptSpace regarding computational time. Our model selection scheme has many promising extensions for constrained matrix factorizations and tensor decompositions, and these extensions could be useful for wide range of practical applications.
Comparison of frame margin probability training to other discriminative methods for multi-condition speech recognition

Our earlier frame margin probability discriminative training (FMPDT) algorithm has shown its advantage over maximum likelihood estimation (MLE) on multi-condition speech recognition. This paper reports our recent improvement on FMPDT and compares it with minimum classification error (MCE) and minimum phone error (MPE). We rewrite the re-estimation formulae of MCE, MPE in a unified linear interpolation way which facilitates this comparison. We compare the recognition results for MCE and MPE, FMPDT using the Aurora2 standard database and HTK3.4, and find the proposed method can give more balanced improvements under different conditions than other discriminative training algorithms.
Determinants of Human Computation Game Acceptance

Human computation games (HCGs) are information systems that use video games to harness human intelligence to solve large-scale problems that are beyond the capacity of artificial intelligence. HCGs present researchers with opportunities to solve computational problems in an enjoyable way. Despite their increasing popularity, insufficient research has been conducted to examine the predictors of players' acceptance for HCGs based on sound theoretical frameworks. This study proposed an integrated model that incorporates hedonic and utilitarian factors to predict players' acceptance of a HCG for music tagging.
On the Performance of Parametric Polymorphism in Maple Laurentiu

With the introduction of support for generics in mainstream programming languages, we see an renewed interest in writing generic code. Maple offers the possibility to write generic code using module-producing functions. There is usually a performance cost associated with the use of generics, and this paper analyzes the cost of using these in Maple. We created sets of tests for different styles of generics and compared their performance with specialized Maple code. The first set of tests implemented generics in the style of parameterized abstract data types, with Maple modules providing functions that operated on data values. The second set of tests implemented generics in the style of parameterized object-oriented classes, where each data value was embodied in its own module object. The test functions were based on the popular SciMark benchmark for scientific computation in Java. The results show a small degradation of performance when using generics modeled on abstract data types and high performance degradation when using an object-oriented approach.
Using factorization machines for student modeling

Predicting student performance (PSP), one of the task in Student Modeling, has been taken into account by educational data mining community recently. Previous works show that good results can be achieved by casting the PSP to rating prediction task in recommender systems, where students, tasks and performance scores are mapped to users, items and ratings respectively, and thus, matrix factorization one of the most prominent approaches for rating prediction task is an appropriate choice. In this work, we propose using Factorization Machines which combine the advantages of Support Vector Machines with factorization models for the problem of PSP. Experiments on two large data sets show that this approach can improve the prediction results over the standard matrix factorization.
Cognitive, language and social-cognitive skills of individuals with fragile X syndrome with and without autism.

BACKGROUND It is not known whether those with co-morbid fragile X syndrome (FXS) and autism represent a distinct subtype of FXS; whether the especially severe cognitive delays seen in studies of young children with co-morbid FXS and autism compared with those with only FXS continue into adolescence and young adulthood; and whether autism in those with FXS is 'true autism', i.e. reflects the same underlying problems as idiopathic autism. METHOD We compared the non-verbal IQ of adolescents and young adults with co-morbid FXS and autism (n = 10) with those with only FXS (n = 44). We then created a subsample of those with FXS only, matched on non-verbal IQ, mental age and gender (n = 21) to the subsample of those with co-morbid FXS and autism. We compared the two groups on measures of expressive language, receptive language (lexical, grammatical morphology and syntactic patterns), and a theory of mind task. RESULTS Those with co-morbid FXS and autism had lower non-verbal IQs than those with only FXS. The participants with co-morbid FXS and autism did not perform as well as the cognitive ability- and gender-matched participants with only FXS on the three measures of receptive language or the theory of mind task; there were no differences on the expressive language measure. CONCLUSIONS Our findings support the notion that those with co-morbid FXS and autism represent a distinct subtype of FXS, with more impairment in receptive language and theory of mind even when controlling for their lower non-verbal IQ relative to those with only FXS. The greater cognitive impairments observed in those with co-morbid FXS and autism continues into adolescence and young adulthood; and the autism seen in those with FXS appears to be the same as idiopathic autism.
Distributed System Development in B

The B-Method is a method for the stepwise derivation of sequential programs. In this paper we show how the B-Method can be used for designing distributed systems by embedding action systems within this method. The action system formalism is designed for the construction of parallel and distributed systems in a stepwise manner within the refinement calculus. We describe how action systems are written in B AMN. We also show the correspondence between refinement rules for action systems and the proof obligations generated in the B-Method. Furthermore, we propose an extension of the B-Method to cover parallel and distributed systems. Familiarity with B AMN is assumed.
DArT Markers Effectively Target Gene Space in the Rye Genome

Large genome size and complexity hamper considerably the genomics research in relevant species. Rye (Secale cereale L.) has one of the largest genomes among cereal crops and repetitive sequences account for over 90% of its length. Diversity Arrays Technology is a high-throughput genotyping method, in which a preferential sampling of gene-rich regions is achieved through the use of methylation sensitive restriction enzymes. We obtained sequences of 6,177 rye DArT markers and following a redundancy analysis assembled them into 3,737 non-redundant sequences, which were then used in homology searches against five Pooideae sequence sets. In total 515 DArT sequences could be incorporated into publicly available rye genome zippers providing a starting point for the integration of DArT- and transcript-based genomics resources in rye. Using Blast2Go pipeline we attributed putative gene functions to 1101 (29.4%) of the non-redundant DArT marker sequences, including 132 sequences with putative disease resistance-related functions, which were found to be preferentially located in the 4RL and 6RL chromosomes. Comparative analysis based on the DArT sequences revealed obvious inconsistencies between two recently published high density consensus maps of rye. Furthermore we demonstrated that DArT marker sequences can be a source of SSR polymorphisms. Obtained data demonstrate that DArT markers effectively target gene space in the large, complex, and repetitive rye genome. Through the annotation of putative gene functions and the alignment of DArT sequences relative to reference genomes we obtained information, that will complement the results of the studies, where DArT genotyping was deployed, by simplifying the gene ontology and microcolinearity based identification of candidate genes.
Bearing Strength and Failure Behavior of Bolted GLARE Joints

Glass fiber reinforced aluminum laminates (GLARE) are main important types of fibre metal laminates composite material. The composite sandwich is manufactured by inserting glass fibre composite laminate between two chemically treated aluminium thin sheet. GLARE material is manufactured with three stacking sequences using random mate layered glass fibre of 1, 2, and 4 layers. The strength and failure of mechanically fastened glass fiber aluminum reinforced epoxy (GLARE) joints are experimentally investigated. The results indicate that bearing strength of GLARE increases with increasing number of glass fiber reinforced laminates but with limitation of that thickness not largely increasing to avoid delamination. Modes of failure for the bolted joint are enhanced to bearing modes for all types of specimens. Index Term-GLARE, Bolted Joint, Aluminum, Reinforced
Functional Dissection of a Rice Dr1/DrAp1 Transcriptional Repression Complex Article, publication date, and citation information can be found at www.plantcell.org/cgi/doi/10.1105/tpc.010320.

We characterized rice cDNA sequences for OsDr1 and OsDrAp1, which encode structural homologs of the eukaryotic general repressors Dr1 and DrAp1, respectively. OsDr1 and OsDrAp1 are nuclear proteins that interact with each other and with the TATA binding protein/DNA complex. In vitro and in vivo functional analyses showed that OsDrAp1 functions as a repressor, unlike its role in other eukaryotic systems, in which DrAp1 is a corepressor. OsDr1 and OsDrAp1 functioned together as a much stronger repressor than either one alone. Functional dissections revealed that the N-terminal histone-fold domains of OsDr1 and OsDrAp1 were necessary and sufficient for their repression and protein–protein interaction with each other. The unique glutamine- and proline-rich domain of OsDr1 had no repression activity. The basic amino acid–rich region and an arginine and glycine repeat domain of OsDrAp1 enhanced its repression activity. Thus, although OsDr1 and OsDrAp1 function as repressors, the functions of the two components are reversed compared with those of their nonplant counterparts.
Prediction of subgrade resilient modulus for flexible pavement design

Resilient modulus of subgrade soils is an important input in mechanistic pavement design. The primary objective of this work is to investigate the resilient modulus of four typical Victorian fine-grained subgrade soils under traffic-like repeated loading and to suggest empirical predictive models incorporating physical properties and/or strength of the soils along with the stress state. A repeated load triaxial testing procedure was developed, which is capable of collecting resilient and permanent deformation data from the same specimen. Stress levels for testing were defined as percentages of the confined and/or unconfined soil static strengths. Stress dependency of resilient modulus was studied through the models (such as bilinear model, power model, deviatoris stress model and octahedral stress model) found in the literature and other possible combinations of deviator, confining and octahedral stresses. A semi-logarithmic model was proposed for the prediction of resilient modulus of the fine-grained subgrade soils. Calibration of model constants by soil properties was investigated. An altervative prediction model was also developed based on unconfined compressive strength and deviator stress. Resilient modulus values were back calculated using both the semi-logarithmic model and the model based on unconfined compressive strength and deviator stress. Predicted values were compared with the measured values. Predictive capability of the proposed models were proven for use in flexible pavement design. Key words: Resilient modulus, fine-grained subgrade soils, repeated loading, flexible pavement design.
An Algorithm for Generating Strongly Chordal Graphs

Strongly chordal graphs are a subclass of chordal graphs. The interest in this subclass stems from the fact that many problems which are NP-complete for chordal graphs are solvable in polynomial time for this subclass. However, we are not aware of any algorithm that can generate instances of this class, often necessary for testing purposes. In this paper, we address this issue. Our algorithm first generates chordal graphs, using an available algorithm and then adds enough edges to make it strongly chordal, unless it is already so. The edge additions are based on a totally balanced matrix characterizations of strongly chordal graphs.
2016 Third International Conference on Information Retrieval and Knowledge Management Ontology Modeling of Malaysian Food Composition 1

— Each new design solution must contain a novelty element. Thus, case adaptation becomes an important subtask in case-based design. This subtask plays the role of modifying the previous solution of the best retrieved case. Generally, adaptation task requires for domain knowledge, and domain-and task-heuristics. This paper demonstrates the process of modeling a domain knowledge using ontology. The domain ontology models the dietitians' knowledge where they use it in designing the dietary menu plan. The method used for ontology modeling is Ontology Development 101 (OD 101). The domain ontology was built from scratch. MyFCO has successfully modeled the domain knowledge of the dietary menu planning. We evaluated the quality of the domain ontology by using it in the design case adaptation for dietary menu planning application. The iterative process emphasized by OD 101 enabled a novice ontology developer to model the ontology in a simpler and more flexible way. This contributes to the success factor of ontology modeling for domain knowledge.
Dystrophin Dp 71 f associates with components of the b 1-integrin adhesion complex in PC 12 cell neurites

Dystrophin Dp71 has been implicated with cognitive impairment shown by Duchenne muscular dystrophy patients. To study Dp71 neural role, we used PC12 cell line, since these cells differentiate into sympathetic like neurons when stimulated with nerve growth factor. Previously in undifferentiated PC12 cells, it was demonstrated that dystrophin Dp71f is a key component of the b1-integrin adhesion complex that confers proper complex assembly. Since integrin based mediated adhesion is important during neuronal differentiation, it was important to know if dystrophin Dp71f was a structural component of the b1-integrin adhesion complex in neurites of nerve growth factor stimulated PC12 cells. In the present work, by performing immunofluorescence assays, we determined the association of dystrophin Dp71f with some components of the b1-integrin adhesion complex such as b1-integrin subunit, talin, a-actinin and vinculin in neurites of nerve growth factor stimulated PC12 cells seeded onto the extracellular matrix protein laminin. The association was stronger in neural growth cones suggesting that dystrophin Dp71f is important for the function that the b1-integrin complex has during neurite out-growth.