Geographic Variation in Alkaloid Production in <Emphasis Type="Italic">Conium maculatum</Emphasis> Populations Experiencing Differential Herbivory by <Emphasis Type="Italic">Agonopterix alstroemeriana</Emphasis>

Conium maculatum, a Eurasian weed naturalized in North America, contains high concentrations of piperidine alkaloids that act as chemical defenses against herbivores. C. maculatum was largely free from herbivory in the United States, until approximately 30 yr ago, when it was reassociated via accidental introduction with a monophagous European herbivore, the oecophorid caterpillar Agonopterix alstroemeriana. At present, A. alstroemeriana is found in a continuum of reassociation time and intensities with C. maculatum across the continent; in the Pacific Northwest, A. alstroemeriana can cause severe damage, resulting in some cases in complete defoliation. Studies in biological control and invasion biology have yet to determine whether plants reassociated with a significant herbivore from the area of indigeneity increase their chemical defense investment in areas of introduction. In this study, we compared three locations in the United States (New York, Washington, and Illinois) where C. maculatum experiences different levels of herbivory by A. alstroemeriana to determine the association between the intensity of the interaction, as measured by damage, and chemical defense production. Total alkaloid production in C. maculatum was positively correlated with A. alstroemeriana herbivory levels: plants from New York and Washington, with higher herbivory levels, invested two and four times more N to alkaloid synthesis than did plants from Illinois. Individual plants with lower concentrations of alkaloids from a single location in Illinois experienced more damage by A. alstroemeriana, indicative of a preference on the part of the insect for plants with less chemical defense. These results suggest that A. alstroemeriana may act either as a selective agent or inducing agent for C. maculatum and increase its toxicity in its introduced range.     

A study of sulfur bridges in filled natural rubber vulcanizates by pyrolysis gas chromatography with flame-photometric detection

Natural rubber vulcanizates of two formulations, with sulfur/N-cyclohexyl-2-benzothiazolesulfenamide (CBS) and tetramethylthiuram disulfide (TMTD), respectively, were analyzed by pyrolysis gas chromatography. A sulfur-selective flame-photometric detector was utilized. The main pyrolysis products were identified as CS₂ and some thiophenes. The yields of the pyrolysis products from the two types of rubber were very different. The yields also varied with the curing time of the rubbers.     

Catalytic combustion of trichloroethene over Ru/Al2O3: Reaction mechanism and kinetic study

The performance of 0.5% Ru/Al₂O₃ for the deep oxidation of trichloroethene (1000–2500 ppmV, WHSV = 55 h⁻¹) in air was studied in this work. Experiments were carried out both at dry and wet (20,000 ppmV of H₂O) conditions. Catalytic performance was studied in terms of activity and selectivity for the different reaction products (CO₂, HCl, Cl₂, C₂Cl₄, CCl₄ and CHCl₃). Both the activity and the selectivity for total combustion are higher than other catalysts suggested in the literature for this process (especially Pd and Pt).The main organic by-products are CCl₄ and CHCl₃, whereas in all the other catalysts tested in the literature, tetrachloroethene is the main organic by-product. This fact suggests that the mechanism of the combustion reaction, involving a double-bond scission, is essentially specific for this catalyst.Kinetic data was fit to a pseudo-first order kinetic expression, providing fairly good fit.     

Fatty acid composition of spanish shortenings with special emphasis on <Emphasis Type="Italic">trans</Emphasis> unsaturation content as determined by fourier transform infrared spectroscopy and gas chromatography

A Fourier transform infrared spectroscopic procedure was used to analyze 34 edible fats (22 shortenings and 12 vegetable margarines) as neat fats (IR_NF) to determine their total trans fatty acid (TFA) content. The sloping baseline was corrected with a reference spectrum based on a nonprocessed olive oil. The calibration was done using seven partially hydrogenated fats with an individual TFA content previously determined by the combination of gas chromatography (GC) with argentation thin-layer chromatography. Taking into account the different absorptivities of various trans isomers, different correction factors were calculated using the calibration standards (0.83 and 1.71 for single trans bonds in both diethylene and triethylene and for trans, trans-diethylene fatty acids, respectively) and applied to calculate the total TFA of samples. Moreover, the samples were converted to their methyl esters and reanalyzed following the same procedure (IR_FAME). Differences in TFA content of fats were not found when a t-test was used to compare the results obtained by IR_NF vs. either IR_FAME or GC, suggesting that IR of neat fats could be used, thus avoiding the need to prepare sample solutions in organic solvents and to prepare fatty acid methyl esters. The mean TFA content (determined by IR_NF) of a representative group of Spanish shortenings (22 samples) that varied widely in terms of fat sources, processes, and purposes (bakery, sandwiches, ice cream, coatings, chocolate coverings) was 6.55±11.40%, although more than 54% contained <3% of TFA. Fatty acid composition of shortenings by direct GC using a 100-m polar cyanopolysiloxane capillary column indicated that the mean trans-18∶2 isomer content was 0.58%, ranging from 0.9 to 3.4%. Small amounts of trans-18∶3 isomers (<0.3%) were observed in 18 of the 22 shortenings studied; the maximal value was <2%. The mean value of the fraction saturated+TFA of shortenings was high (59.95±12.73%), including two values higher than 83%.     

Cobalt-Molybdenum Sulfide Catalysts Prepared by In Situ Activation of Bimetallic (Co-Mo) Alkylthiomolybdates

Unsupported cobalt-molybdenum sulfide catalysts were prepared from bimetallic CoMo alkyl precursors by in situ activation during the hydrodesulfurization (HDS) of dibenzothiophene (DBT). The bimetallic CoMo precursors were prepared by reaction of tetraalkylammonium thiomolybdate salts, (R₄N)₂MoS₄ (where R = H, methyl, butyl, pentyl or hexyl), with CoCl₂ in water at a Co/Mo molar ratio of 0.3. These catalysts exhibit a Swiss-cheese-like morphology, high surface areas (from 52 up to 320 m²/g), high content of carbon (C/Mo = 2.2-3.3) and type IV adsorption-desorption isotherms of nitrogen. The in situ activation of these tetraalkylammonium thiobimetalate precursors leads to a mesoporous structure with pore size ranging from 2 to 4.5 nm. X-ray diffraction showed that the structure of unsupported cobalt-molybdenum sulfide catalysts corresponds to a poorly crystalline structure characteristic of 2H-MoS₂ with low-stacked layers. The nature of the alkyl group strongly affects both the surface area and the HDS activity. The catalytic activity is strongly enhanced when using carbon-containing precursors; the CoMo catalysts prepared by in situ activation of Co/[N(C₄H₉)₄]₂MoS₄ presents the highest HDS activity. The highest surface area of the catalysts was observed for the CoMo catalyst formed from Co/[N(C₆H₁₃)₄N]₂MoS₄.     

An approach based on current and sound signals for in-process tool wear monitoring

This paper presents a tool condition monitoring system (TCMS) for on-line tool wear monitoring in turning. The proposed TCMS was developed taking into account the necessary trade-off between cost and performance to be applicable in practice, in addition to a high success rate. The monitoring signals were the feed motor current and the sound signal. The former was used to estimate the feed cutting force using the least squares version of support vector machines (LS-SVM). Singular spectrum analysis (SSA) was used to extract information correlated with tool wear from the sound signal. The estimated feed cutting force and the SSA decomposition of the sound signal alone with the cutting conditions constitute the input data to the TCMS. Again LS-SVM was used to estimate tool condition and its reliability for on-line implementation was validated by experiments using AISI 1040 steel. The results showed that the proposed TCMS is fast and reliable for tool condition monitoring.     

Warm deep drawing of wrought magnesium alloy sheets produced by semi-solid roll strip-casting process

This paper is concerned with the development of a continuous strip-casting technology to facilitate the manufacture of magnesium sheet alloys economically whilst maintaining high quality. Established in the paper is warm formability of cast magnesium alloy sheets after being hot rolled by semi-solid roll strip-casting process. It has been found that magnesium sheet with 2.0–4.0 mm thickness could be produced at a speed of 25 m/min. Hot rolling and annealing temperatures during hot rolling were also changed to examine which condition would be appropriate for producing wrought magnesium alloys with good formability. Microstructures of the crystals of the manufactured wrought magnesium alloys were observed. It has been found that a limiting drawing ratio of 2.7 was possible in a warm deep-drawing test of the cast magnesium alloy sheets after being hot rolled.     

Pointwise and pairwise clothing annotation: combining features from social media

In this paper, we present effective algorithms to automatically annotate clothes from social media data, such as Facebook and Instagram. Clothing annotation can be informally stated as recognizing, as accurately as possible, the garment items appearing in the query photo. This task brings huge opportunities for recommender and e-commerce systems, such as capturing new fashion trends based on which clothes have been used more recently. It also poses interesting challenges for existing vision and recognition algorithms, such as distinguishing between similar but different types of clothes or identifying a pattern of a cloth even if it has different colors and shapes. We formulate the annotation task as a multi-label and multi-modal classification problem: (i) both image and textual content (i.e., tags about the image) are available for learning classifiers, (ii) the classifiers must recognize a set of labels (i.e., a set of garment items), and (iii) the decision on which labels to assign to the query photo comes from a set of instances that is used to build a function, which separates labels that should be assigned to the query photo, from those that should not be assigned. Using this configuration, we propose two approaches: (i) the pointwise one, called MMCA, which receives a single image as input, and (ii) a multi-instance classification, called M3CA, also known as pairwise approach, which uses pair of images to create the classifiers. We conducted a systematic evaluation of the proposed algorithms using everyday photos collected from two major fashion-related social media, namely pose.com and chictopia.com. Our results show that the proposed approaches provide improvements when compared to popular first choice multi-label, multi-modal, multi-instance algorithms that range from 20 % to 30 % in terms of accuracy.