Performance of Sorghum Hybrids in Relation to Sources of Resistance to Biotype C of the Greenbug

This paper presents results of research on the agronomic performance of sorghum [Sorghum bicolor (L.) Moench.] hybrids derived from several germplasm sources that possess resistance to biotype C of the greenbug [Schizaphis graminum (Rondani)]. Significant differences among hybrids with resistance from different sources were evident for grain yield, seeds/head, heads/plant, days to midbloom, and plant height. SA7536-1 seemed superior to KS30, IS809, and PI264453 resistance sources in potential for producing high-yielding hybrids with resistance to biotype C. Greater numbers of seeds/head was the component largely responsible for the yield advantage of the SA7536-1 hybrids

Human Gait Recognition from Motion Capture Data in Signature Poses

Most contribution to the field of structure-based human gait recognition has been done through design of extraordinary gait features. Many research groups that address this topic introduce a unique combination of gait features, select a couple of well-known object classiers, and test some variations of their methods on their custom Kinect databases. For a practical system, it is not necessary to invent an ideal gait feature -- there have been many good geometric features designed -- but to smartly process the data there are at our disposal. This work proposes a gait recognition method without design of novel gait features; instead, we suggest an effective and highly efficient way of processing known types of features. Our method extracts a couple of joint angles from two signature poses within a gait cycle to form a gait pattern descriptor, and classifies the query subject by the baseline 1-NN classier. Not only are these poses distinctive enough, they also rarely accommodate motion irregularities that would result in confusion of identities. We experimentally demonstrate that our gait recognition method outperforms other relevant methods in terms of recognition rate and computational complexity. Evaluations were performed on an experimental database that precisely simulates street-level video surveillance environment

An Evaluation Framework and Database for MoCap-Based Gait Recognition Methods

As a contribution to reproducible research, this paper presents a framework and a database to improve the development, evaluation and comparison of methods for gait recognition from Motion Capture (MoCap) data. The evaluation framework provides implementation details and source codes of state-of-the-art human-interpretable geometric features as well as our own approaches where gait features are learned by a modification of Fisher's Linear Discriminant Analysis with the Maximum Margin Criterion, and by a combination of Principal Component Analysis and Linear Discriminant Analysis. It includes a description and source codes of a mechanism for evaluating four class separability coefficients of feature space and four rank-based classifier performance metrics. This framework also contains a tool for learning a custom classifier and for classifying a custom query on a custom gallery. We provide an experimental database along with source codes for its extraction from the general CMU MoCap database

Performance of S1 and Half-sib Family Composites of IAP3BR(M) Random-mating Grain Sorghum Population

Performance of S1 and half-sib (HS) family composites from the random-mating sorghum (Sorghum bicolor L. Moench) population IAP3BR(M) was evaluated in six environments in Iowa. Composites from C0 through C4 for both family types showed that mass selection for heavy 100-seed weight was effective for increasing seed size in the population. Grain yield also increased over cycles among HS bulks, but decreased in the S1 bulks. Selection for large seed through four cycles resulted in fewer seeds/panicle in both family types, and in an increase in the means for days to midbloom and plane height. Inbreeding effects determined from half-sib and S1 family means were significant (

Badania kinetyczne procesu odzysku złota z rozcieńczonych roztworów chlorkowych metodą fotoelektrochemiczną

Au(III) was recovered from an acidic aqueous solution via a photoreduction technique under UV light irradiation. Titanium dioxide nanopowder was applied as a photocatalyst. Gold was deposited onto TiO2 surface in the form of nanoparticles with average dimensions between 20 and 30 nm. The influence of the Au(III), TiO2 and methanol initial concentrations on the reaction rate was determined. It was shown, that the rate of the gold photoreduction strongly depends on the concentration of TiO2 and methanol. The recovery of gold from the diluted acidic solutions containing as much as 1.97 and 0.197 mg/dm3 of Au(III) was also carried out. Obtained results suggest, that it is possible to recover about 45% of gold. Besides the losses during the filtration process due to the application of very fine TiO2 particles, oxygen dissolved in the solution as well as the hydrogen ions may take part in parasitic reactions and thus decrease the Au yield.Przeprowadzono odzysk jonów Au(III) z kwaśnych, chlorkowych roztworów wodnych metodą fotoredukcji pod wpływem światła UV. Jako fotokatalizator wykorzystano proszek dwutlenku tytanu o rozmiarach nanometrycznych. W wyniku redukcji kompleksu chlorkowego Au(III), na powierzchni TiO2 otrzymano fazę metaliczną w formie nanocząstek o rozmiarach w zakresie od 20 do 30 nm. Zbadano wpływ stężeń początkowych Au(III), TiO2 i metanolu. Badania wykazały, że szybkość fotoredukcji Au(III) silnie zależy od stężenia dwutlenku tytanu i metanolu. Przeprowadzono również badania nad odzyskiem złota z rozcieńczonych roztworów zawierających 1.97 i 0.197 mg/dm3 Au(III). Otrzymane wyniki wskazują, że przyjęta metoda pozwala odzyskać około 45% złota z roztworu. Niska wydajność procesu może być spowodowana stratami w procesie filtracji związanymi z zastosowaniem nanokrystalicznego TiO2, tlenem rozpuszczonym w roztworze oraz jonami H+, które mogą ulegać redukcji w konkurencyjnych, równoległych reakcjach