Electroantennographic and behavioral responses of the sphinx moth Manduca sexta to host plant headspace volatiles

Coupled gas chromatography with electroantennographic detection (GC-EAD) using antennae of adult female Manduca sexta was employed to screen for olfactory stimulants present in headspace collections from four species of larval host plants belonging to two families: Solanaceae—Lycopersicon esculentum (tomato), Capiscum annuum (bell pepper), and Datura wrightii; and Martyniaceae—Proboscidea parviflora. Headspace volatiles were collected from undamaged foliage of potted, living plants. GC–EAD revealed 23 EAD-active compounds, of which 15 were identified by GC-mass spectrometry. Identified compounds included aliphatic, aromatic, and terpenoid compounds bearing a range of functional groups. Nine EAD-active compounds were common to all four host plant species: (Z)-3-hexenyl acetate, nonanal, decanal, phenylacetaldehyde, methyl salicylate, benzyl alcohol, geranyl acetone, (E)-nerolidol, and one unidentified compound. Behavioral responses of female moths to an eight-component synthetic blend of selected tomato headspace volatiles were tested in a laboratory wind tunnel. Females were attracted to the blend. A comparison of responses from antennae of males and females to bell pepper headspace volatiles revealed that males responded to the same suite of volatiles as females, except for (Z)-3-hexenyl benzoate. EAD responses of males also were lower for (Z)- and (E)-nerolidol and one unidentified compound. Electroantennogram EAG dose–response curves for the 15 identified EAD-active volatiles were recorded. At the higher test doses (10–100 g), female antennae yielded larger EAG responses to terpenoids and to aliphatic and aromatic esters. Male antennae did respond to the higher doses of (Z)-3-hexenyl benzoate, indicating that they can detect this compound. On the basis of ubiquity of the EAD-active volatiles identified to date in host plant headspace collections, we suggest that M. sexta uses a suite of volatiles to locate and identify appropriate host plants.     

How In-Home Technologies Mediate Caregiving Relationships in Later Life

In-home technologies can support older adults' activities of daily living, provide physical safety and security, and connect elders to family and friends. They facilitate aging in place while reducing caregiver burden. One of older adults' primary concerns about in-home technologies is their potential to reduce human contact, particularly from cherished caregivers. In this exploratory in situ study, we provided an ecosystem of networked monitoring technologies to six older adults and their caregivers. We analyzed the amount and content of communication between them. The amount of noncomputer-mediated communication did not decrease through the 6-week study. The content of communication coalesced into four themes: communication about the technologies, communication facilitated by technologies, intrusiveness of technologies, and fun and playfulness with the technologies. Results suggest that in-home technologies, designed with sensitivity to older adults' primary motivations, have the potential to shape and tailor important relationships in later life.     

Autoregressive model-based fuzzy clustering and its application for detecting information redundancy in air pollution monitoring networks

Fuzzy clustering enables the simultaneous membership of objects in two or more clusters. This is particularly pertinent where time series are concerned, because very often patterns of time series change over time. Thus, a time series might belong to different clusters over different periods of time, in which case, crisp clustering is unable to capture this multi-cluster membership. In this paper, we adopt a Fuzzy C-Medoids approach to clustering time series based on autoregressive estimates of models fitted to the time series. We illustrate very good performance of this approach in a range of simulation studies. By means of two applications, we also show the usefulness of this clustering approach in the air pollution monitoring, by considering air pollution time series, i.e., CO time series, CO₂ time series and NO time series monitored on world and urban scales. In particular, we show that, by considering in the clustering process, the autoregressive representation of these air pollution time series, we are able to detect possible information redundancy in the monitoring networks and then, decreasing the number of monitoring stations, to reduce the monitoring costs and then to increase the monitoring efficiency of the networks.     

'Tacitus' project: identifying multi-sensory perceptions in creative 3D practice for the development of a haptic computing system for applied artists

This paper outlines the major motivating factors concerning a novel collaborative project between Edinburgh College of Art and Edinburgh Virtual Environment Centre. The Tacitus project will investigate the use of multi-modal virtual environments, specifically, the haptic (touch) modality, with regards to the creative processes employed by designers working within the field of applied arts. The salient areas of research are described, and the methods by which information regarding these areas will be obtained are considered. Initial investigations have revealed a strong need to mimic the traditional applied artists' workspaces, with co-location of visual and haptic cues a priority.     

Examining teacher growth in professional learning groups for in‐service teachers of mathematics

Abstract

Teachers may face important challenges when encouraged to improve their mathematics teaching. Their personal beliefs, knowledge, confidence and personal intentions towards growth and change are all complex factors which may influence teachers’ capacity, and their decisions about personal change in their teaching. In this study, intermediate teachers and the conversations that took place during their monthly Professional Learning Group meetings over a one‐year period were examined in order to better understand issues teachers face in their growth and development as teachers of mathematics. We critically examine the notion and meaning of success to different stakeholders.     

A double-threshold image binarization method based on edge detector

This paper presents a new double-threshold image binarization method based on the edge and intensity information. We first find seeds near the image edges and present an edge connection method to close the image edges. Then, we use closed image edges to partition the binarized image that is generated using a high threshold, and obtain a primary binarization result by filling the partitioned high-threshold binary image with the seeds. Finally, the final binarization result is obtained by remedying the primary binarization result with the low-threshold binary image. Compared with the classical binarization methods and the similar binarization methods, our method is effective on the binarization of images with low contrast, noise and non-uniform illumination.     

Column and batch reactive transport experiment parameter estimation using a genetic algorithm

This paper focuses on the application of a genetic algorithm (GA) in estimating the fate and transport parameters of a reacting solute from the column and batch experiments involving a saturated porous medium. A program is developed using C++ to model the column and batch data using kinetically controlled one- or two-site sorption models including linear and/or nonlinear forms. The objective of the algorithm is to minimize the sum of squared differences between the measured and modeled solute concentration data associated with column effluent (i.e., “breakthrough curves”). The GA is capable of estimating transport and reactions parameters such as forward and reverse reaction rates and parameters of the nonlinear reaction models, from a given set of measured data. Further simulations have been performed to estimate the appropriate configurations of the GA, which assist the method in estimating the fate and transport parameters more efficiently. It is shown that a wide range of the GA parameters can lead to convergence to appropriate estimations. The results obtained from this study show that the capability of GAs to fit the column and batch experiment data is promising.     

Severity of delayed (“secondary”) cerebral energy failure after acute hypoxia-ischemia is related to the time integral of acute ATP depletion

The aim of this study was to reproduce the delayed (secondary) cerebral energy failure previously described in birth-asphyxiated newborn infants and to investigate relationships between primary insult severity and the extent of the delayed energy failure. Phosphorus (³¹P) magnetic resonance spectroscopy (MRS) at 7 T was used to study the brains of 12 newborn piglets during an acute, reversible, cerebral hypoxic-ischemic episode which continued until nucleotide triphosphates (NTP) were depleted. After reperfusion and reoxygenation, spectroscopy was continued for 48 h. High-energy metabolite concentrations returned to near normal levels after the insult, but later they fell as delayed energy failure developed. The time integral of NTP depletion in the primary insult correlated strongly with the minimum [phosphocreatine (PCr)]/[inorganic orthophosphate (P_i)] observed 24–48 h after the insult. (Linear regression analysis gave slope –8.04 h^–1; ordinate intercept=1.23;r=0.92;P<0.0001.) This model is currently being used to investigate the therapeutic potential of various cerebroprotective strategies including hypothermia.     

Glyphosate Adsorption from Water Using Hierarchically Porous Metal–Organic Frameworks

The selective removal of one ligand in mixed-ligand MOFs upon thermolysis provides a powerful strategy to introduce additional mesopores without affecting the overall MOF structure. By varying the initial ligand ratio, MOFs of the MIL-125-Ti family with two distinct hierarchical pore architectures are synthesized, resembling either large cavities or branching fractures. The performance of the resulting hierarchically porous MOFs is evaluated toward the adsorptive removal of glyphosate (N-(phosphonomethyl)glycine) from water, and the adsorption kinetics and mechanism are examined. Due to their strong affinity for phosphoric groups, the numerous Ti–OH groups resulting from the selective ligand removal act as natural anchor points for effective glyphosate uptake. The relationships between contact duration, glyphosate concentration, and adsorbent dosage are investigated, and the impact of these parameters on the effectiveness of glyphosate removal from contaminated water samples is examined. The introduction of additional mesopores has increased the adsorption capacities by nearly 3 times with record values exceeding 440.9 mg g⁻¹, which ranks these MOFs among the best-reported adsorbents.