Publications by authors named "David Towers"

Background: Mosquitoes are carriers of tropical diseases, thus demanding a comprehensive understanding of their behaviour to devise effective disease control strategies. In this article we show that machine learning can provide a performance assessment of 2D and 3D machine vision techniques and thereby guide entomologists towards appropriate experimental approaches for behaviour assessment. Behaviours are best characterised via tracking-giving a full time series of information.

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Article Synopsis
  • Barrier bednets (BBnets) are special bednets with an extra panel to catch more mosquitoes above the net, which could make them better than regular bednets.
  • Researchers tested two types of nets—PermaNet 3.0 (P3) and untreated nets—with additional barriers and found that the treated barriers helped kill more mosquitoes.
  • The study showed that BBnets could work well with existing bednets, making them safer and more effective against mosquito bites.
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  • Mosquito-borne diseases cause about a million deaths each year, prompting the need for new ways to control transmission, especially as mosquitoes develop resistance to current insecticides.
  • Researchers have developed a novel methodology using machine learning to analyze mosquito flight patterns, allowing for the identification of male, female, and mating couples through trajectory analysis.
  • This approach has the potential to enhance genetic control strategies for mosquitoes by providing insights into their mating behaviors, achieving a balanced accuracy of 64.5% and an ROC AUC score of 68.4% in field tests.
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Background: The success of insecticide treated bed nets (ITNs) for malaria vector control in Africa relies on the behaviour of various species of Anopheles. Previous research has described mosquito behavioural alterations resulting from widespread ITN coverage, which could result in a decrease in net efficacy. Here, behaviours were compared including timings of net contact, willingness to refeed and longevity post-exposure to two next-generation nets, PermaNet 3.

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Using intensity gradient- or sparsity-based focus metrics, the ability to accurately localize the three-dimensional (3D) position of a small object in a digital holographic reconstruction of a large field of view is hindered in the presence of multiple nearby objects. A more accurate alternative method for 3D localization, based on evaluation of the complex reconstructed volume, is proposed. Simulations and experimental data demonstrate a reduction in depth positional error for single objects and a notably improved axial resolution of multiple objects in close proximity.

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Robust imaging techniques for tracking insects have been essential tools in numerous laboratory and field studies on pests, beneficial insects and model systems. Recent innovations in optical imaging systems and associated signal processing have enabled detailed characterization of nocturnal mosquito behaviour around bednets and improvements in bednet design, a global essential for protecting populations against malaria. Nonetheless, there remain challenges around ease of use for large-scale recordings and extracting data reliably in the critical areas of the bednet where the optical signal is attenuated.

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Background: Insecticide-treated nets (ITNs) are losing efficacy against pyrethroid-resistant malaria vector populations throughout Africa. Safeguarding bed net efficacy, vital for effective malaria control, requires greater knowledge of mosquito-ITN interactions and how this impacts on the mosquito.

Methods: A purpose-built benchtop apparatus with a closed 10 cm cubic chamber (the 'Baited-box') was used to video record behaviour of individual free-flying female Anopheles gambiae during approach and blood-feeding on a human hand through untreated nets and ITNs at close range.

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Transmission of Plasmodium falciparum malaria parasites occurs when nocturnal Anopheles mosquito vectors feed on human blood. In Africa, where malaria burden is highest, bednets treated with pyrethroid insecticide were highly effective in preventing mosquito bites and reducing transmission, and essential to achieving unprecedented reductions in malaria until 2015 (ref. ).

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Article Synopsis
  • - The study focused on how wild Anopheles arabiensis mosquitoes behave around long-lasting insecticide-treated nets (LLINs) compared to untreated nets in Mwanza, Tanzania, using an infrared tracking system to monitor their movements for one hour.
  • - Results indicated that mosquitoes spent significantly less time flying near LLINs, particularly in 'bouncing' flight behavior, and were notably less active above the human volunteer under LLINs compared to untreated nets.
  • - Most of the mosquito activity occurred at the net roof with untreated nets showing higher rates of mosquito visits and resting above the volunteer’s torso, revealing that LLINs are more effective in reducing mosquito interactions than untreated nets.
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Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision.

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Long-lasting insecticidal bed nets (LLINs) protect humans from malaria transmission and are fundamental to malaria control worldwide, but little is known of how mosquitoes interact with nets. Elucidating LLIN mode of action is essential to maintain or improve efficacy, an urgent need as emerging insecticide resistance threatens their future. Tracking multiple free-flying Anopheles gambiae responding to human-occupied bed nets in a novel large-scale system, we characterised key behaviours and events.

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Few studies have investigated how attentional control is affected by transient affective states while taking individual differences in affective traits into consideration. In this study, participants completed a color-word Stroop task immediately after undergoing a positive, neutral or negative affective context manipulation (ACM). Behavioral performance was unaffected by any ACM considered in isolation.

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Recent advances in multiwavelength interferometry techniques [Appl. Opt.52, 5758 (2013)] give new insights to phase unwrapping problems and allow the fringe order information contained in the measured phase to be extracted with low computational effort.

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The capability model of frontal electroencephalographic (EEG) asymmetry suggests that brain activity during emotional challenge will be a more powerful indicator of predispositions toward psychopathology than activity observed at rest. EEG data were assessed during a resting baseline and a facial emotion task, wherein individuals with (n = 143) and without (n = 163) lifetime major depressive disorder (MDD) made approach (angry and happy) and withdrawal (afraid and sad) facial expressions. EEG asymmetry during emotional challenge was a more powerful indicator of MDD status than resting asymmetry for average, Cz, and linked mastoid references, results in support of the capability model.

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Multiwavelength interferometry provides a solution to a number of applications in metrology for the measurement of optical path differences longer than the source wavelength. To this day, the method of excess fractions (EF) has proved to provide very long, unambiguous measurement ranges with the highest reliability for a given set of wavelengths and level of phase noise. This is achieved because EF combines the individual phase values in an equivalent least-square problem and evaluates the correspondence for all possible solutions.

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Multiwavelength interferometry (MWI) is a well established technique in the field of optical metrology. Previously, we have reported a theoretical analysis of the method of excess fractions that describes the mutual dependence of unambiguous measurement range, reliability, and the measurement wavelengths. In this paper wavelength, selection strategies are introduced that are built on the theoretical description and maximize the reliability in the calculated fringe order for a given measurement range, number of wavelengths, and level of phase noise.

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Resting frontal encephalographic (EEG) asymmetry, often conceptualized as a trait marker for depression, is influenced by occasion-specific factors, including time of year and the time of day of the recording session as demonstrated recently (Peterson and Harmon-Jones, 2009). The current study examined the influence of seasonal and chronological variables on resting frontal asymmetry, and also assessed whether different reference montages or surface transformations were equally susceptible to these influences. In a direct replication attempt, contrary to previous findings, no simple time of year by time of day interaction was found.

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The method of excess fractions (EF) is well established to resolve the fringe order ambiguity generated in interferometric detection. Despite this background, multiwavelength interferometric absolute long distance measurements have only been reported with varying degrees of success. In this paper we present a theoretical model that can predict the unambiguous measurement range in EF based on the selected measurement wavelengths and phase noise.

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A network consisting of left dorsolateral prefrontal cortex (LDLPFC) and dorsal anterior cingulate cortex (dACC) has been implicated in top-down attentional control. Few studies have systematically investigated how this network is altered in psychopathology, despite evidence that depression and anxiety are associated with attentional control impairments. Functional MRI and dense-array event-related brain potential (ERP) data were collected in separate sessions from 100 participants during a color-word Stroop task.

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Phase-based fringe projection metrology systems have been widely used to obtain the shape of 3D objects. One vital step is calibration, which defines the relationship between the phase and depth data. Existing calibration methods are complicated because of the dependence of the relationship on the pixel position.

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Background: Although it has been argued that frontal electroencephalographic (EEG) asymmetry at rest may be a risk marker for major depressive disorder (MDD), it is unclear whether a pattern of relatively less left than right activity characterizes depressed individuals during emotional challenges. Examination of frontal asymmetry during emotion task manipulations could provide an assessment of the function of systems relevant for MDD, and test the limits of frontal EEG asymmetry as a marker of risk for depression.

Methods: EEG data were assessed during a facial emotion task, wherein 306 individuals age 18-34 (31% male) with (n=143) and without (n=163) DSM-IV defined lifetime MDD made directed facial actions of approach (angry and happy) and withdrawal (afraid and sad) expressions.

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Resting frontal electroencephalographic (EEG) asymmetry has been hypothesized as a marker of risk for major depressive disorder (MDD), but the extant literature is based predominately on female samples. Resting frontal asymmetry was assessed on 4 occasions within a 2-week period in 306 individuals aged 18-34 (31% male) with (n = 143) and without (n = 163) lifetime MDD as defined by the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (American Psychiatric Association, 1994). Lifetime MDD was linked to relatively less left frontal activity for both sexes using a current source density (CSD) reference, findings that were not accounted for solely by current MDD status or current depression severity, suggesting that CSD-referenced EEG asymmetry is a possible endophenotype for depression.

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Relatively less right parietal activity may reflect reduced arousal and signify risk for major depressive disorder (MDD). Inconsistent findings with parietal electroencephalographic (EEG) asymmetry, however, suggest issues such as anxiety comorbidity and sex differences have yet to be resolved. Resting parietal EEG asymmetry was assessed in 306 individuals (31% male) with (n=143) and without (n=163) a DSM-IV diagnosis of lifetime MDD and no comorbid anxiety disorders.

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A conventional microscope produces a sharp image from just a single object-plane. This is often a limitation, notably in cell biology. We present a microscope attachment which records sharp images from several object-planes simultaneously.

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