Modelling the time-evolution of phytoplankton size spectra from satellite remote sensing

A dynamic size-structured model is developed for phytoplankton and nutrients in the oceanic mixed layer and applied to extract phytoplankton biomass at discrete size fractions from remotely sensed, ocean-colour data. General relationships between cell size and biophysical processes (such as sinking, grazing, and primary production) of phytoplankton were included in the model through a bottom–up approach. Time-dependent, mixed-layer depth was used as a forcing variable, and a sequential data-assimilation scheme was implemented to derive model trajectories. From a given time-series, the method produces estimates of size-structured biomass at every observation, so estimates seasonal succession of individual phytoplankton size, derived here from remote sensing for the first time. From these estimates, normalized phytoplankton biomass size spectra over a period of 9 years were calculated for one location in the North Atlantic. Further analysis demonstrated that strong relationships exist between the seasonal trends of the estimated size spectra and the mixed-layer depth, nutrient biomass, and total chlorophyll. The results contain useful information on the time-dependent biomass flux in the pelagic ecosystem.

The phenology of phytoplankton blooms: ecosystems indicators from remote sensing

Remote sensing offers many advantages in the development of ecosystem indicators for the pelagic zone of the ocean. Particularly suitable in this context are the indicators arising from time series that can be constructed from remotely sensed data. For example, using ocean-colour radiometry, the phenology of phytoplankton blooms can be assessed. Metrics defined in this way show promise as informative indicators for the entire pelagic ecosystem. A simple phytoplankton–substrate model, with forcing dependent on latitude and day number is used to explore the qualitative features of bloom phenology for comparison with the results observed in a suite of 10-year time series of chlorophyll concentration, as assessed by remote sensing, from the Northwest Atlantic Ocean. The model reveals features of the dynamics that might otherwise have been overlooked in evaluation of the observational data.

Nutrient sensing and signalling in plants: Potassium and phosphorus

Potassium and phosphorus are important macronutrients for crops but are often deficient in the field. Very little is known about how plants sense fluctuations in K and P and how information about K and P availability is integrated at the whole plant level into physiological and metabolic adaptations. This chapter reviews recent advances in discovering molecular responses of plants to K and P deficiency by microarray experiments. These studies provide us not only with a comprehensive picture of adaptive mechanisms, but also with a large number of transcriptional markers that can be used to identify upstream components of K and P signalling pathways. On the basis of the available information we discuss putative receptors and signals involved in the sensing and integration of K and P status both at the cellular and at the whole plant level. These involve membrane potential, voltage-dependent ion channels, intracellular Ca and pH, and transcription factors, as well as hormones and metabolites for systemic signalling. Genetic screens of reporter lines for transcriptional markers and metabolome analysis of K- and P-deficient plants are likely to further advance our knowledge in this area in the near future.

Electrochemical sensing of 2D condensation in amyloid peptides

The interfacial behavior of the model amyloid peptide octamer YYKLVFFC (peptide 1) and two other amyloid peptides YEVHHQKLVFF (peptide 2) and KKLVFFA (peptide 3) at the metal|aqueous solution interface was studied by voltammetric and constant current chronopotentiometric stripping (CPS). All three peptides are adsorbed in a wide potential range and exhibit different interfacial organizations depending on the electrode potential. At the least negative potentials, chemisorption of peptide 1 occurs through the formation of a metal sulfur bond. This bond is broken close to −0.6 V. The peptide undergoes self-association at more negative potentials, leading to the formation of a “pit” characteristic of a 2D condensed film. Under the same conditions the other peptides do not produce such a pit. Formation of the 2D condensed layer in peptide 1 is supported by the time, potential and temperature dependences of the interfacial capacity and it is shown that presence of the 2D layer is reflected by the peptide CPS signals due to the catalytic hydrogen evolution. The ability of peptide 1 to form the potential-dependent 2D condensed layer has been reported neither for any other peptide nor for any protein molecule. This ability might be related to the well-known oligomerization and aggregation of Alzheimer amyloid peptides.

Comparison of the radiative properties and direct radiative effect of aerosols from a global aerosol model and remote sensing data over ocean

A global aerosol transport model (Oslo CTM2) with main aerosol components included is compared to five satellite retrievals of aerosol optical depth (AOD) and one data set of the satellite-derived radiative effect of aerosols. The model is driven with meteorological data for the period November 1996 to June 1997 which is the time period investigated in this study. The modelled AOD is within the range of the AOD from the various satellite retrievals over oceanic regions. The direct radiative effect of the aerosols as well as the atmospheric absorption by aerosols are in both cases found to be of the order of 20 Wm−2 in certain regions in both the satellite-derived and the modelled estimates as a mean over the period studied. Satellite and model data exhibit similar patterns of aerosol optical depth, radiative effect of aerosols, and atmospheric absorption of the aerosols. Recently published results show that global aerosol models have a tendency to underestimate the magnitude of the clear-sky direct radiative effect of aerosols over ocean compared to satellite-derived estimates. However, this is only to a small extent the case with the Oslo CTM2. The global mean direct radiative effect of aerosols over ocean is modelled with the Oslo CTM2 to be –5.5 Wm−2 and the atmospheric aerosol absorption 1.5 Wm−2.

In situ and remote-sensing measurements of the mean microphysical and optical properties of industrial pollution aerosol during ADRIEX

We present a summary of the principal physical and optical properties of aerosol particles using the FAAM BAE-146 instrumented aircraft during ADRIEX between 27 August and 6 September 2004, augmented by sunphotometer, lidar and satellite retrievals. Observations of anthropogenic aerosol, principally from industrial sources, were concentrated over the northern Adriatic Sea and over the Po Valley close to the aerosol sources. An additional flight was also carried out over the Black Sea to compare east and west European pollution. Measurements show the single-scattering albedo of dry aerosol particles to vary considerably between 0.89 and 0.97 at a wavelength of 0.55 μm, with a campaign mean within the polluted lower free troposphere of 0.92. Although aerosol concentrations varied significantly from day to day and during individual days, the shape of the aerosol size distribution was relatively consistent through the experiment, with no detectable change observed over land and over sea. There is evidence to suggest that the pollution aerosol within the marine boundary layer was younger than that in the elevated layer. Trends in the aerosol volume distribution show consistency with multiple-site AERONET radiometric observations. The aerosol optical depths derived from aircraft measurements show a consistent bias to lower values than both the AERONET and lidar ground-based radiometric observations, differences which can be explained by local variations in the aerosol column loading and by some aircraft instrumental artefacts. Retrievals of the aerosol optical depth and fine-mode (<0.5 μm radius) fraction contribution to the optical depth using MODIS data from the Terra and Aqua satellites show a reasonable level of agreement with the AERONET and aircraft measurements.

The integration of lipid-sensing and anti-inflammatory effects: how the PPARs play a role in metabolic balance

The peroxisomal proliferating-activated receptors (PPARs) are lipid-sensing transcription factors that have a role in embryonic development, but are primarily known for modulating energy metabolism, lipid storage, and transport, as well as inflammation and wound healing. Currently, there is no consensus as to the overall combined function of PPARs and why they evolved. We hypothesize that the PPARs had to evolve to integrate lipid storage and burning with the ability to reduce oxidative stress, as energy storage is essential for survival and resistance to injury/infection, but the latter increases oxidative stress and may reduce median survival (functional longevity). In a sense, PPARs may be an evolutionary solution to something we call the 'hypoxia-lipid' conundrum, where the ability to store and burn fat is essential for survival, but is a 'double-edged sword', as fats are potentially highly toxic. Ways in which PPARs may reduce oxidative stress involve modulation of mitochondrial uncoupling protein (UCP) expression (thus reducing reactive oxygen species, ROS), optimising forkhead box class O factor (FOXO) activity (by improving whole body insulin sensitivity) and suppressing NFkB (at the transcriptional level). In light of this, we therefore postulate that inflammation-induced PPAR downregulation engenders many of the signs and symptoms of the metabolic syndrome, which shares many features with the acute phase response (APR) and is the opposite of the phenotype associated with calorie restriction and high FOXO activity. In genetically susceptible individuals (displaying the naturally mildly insulin resistant 'thrifty genotype'), suboptimal PPAR activity may follow an exaggerated but natural adipose tissue-related inflammatory signal induced by excessive calories and reduced physical activity, which normally couples energy storage with the ability to mount an immune response. This is further worsened when pancreatic decompensation occurs, resulting in gluco-oxidative stress and lipotoxicity, increased inflammatory insulin resistance and oxidative stress. Reactivating PPARs may restore a metabolic balance and help to adapt the phenotype to a modern lifestyle.

Exploring writing in products in students with language impairments and autism spectrum disorders

Oral language skills scaffold written text production; students with oral language difficulties often experience writing problems. The current study examines the ways in which oral language problems experienced by students with language impairment (LI) and students with autism spectrum disorders (ASD) impact on their production of written text. One hundred and fifty seven participants (Mage = 10;2) with LI or ASD completed standardized measures of oral language, transcription, working memory, and nonverbal ability and produced a written narrative text assessed for productivity, grammatical accuracy, and quality. Measures of transcription, productivity, and grammatical accuracy, but not text quality, were poorer for students with LI. Transcription skills accounted for the majority of variance in the writing of the LI cohort. For the ASD cohort, handwriting, oral language and autism symptomatology were significant predictors. When students with ASD also experienced language problems, their performance was equivalent to that observed in the LI cohort.

Targeting Staphylococcus aureus quorum sensing with non-peptidic small molecule inhibitors

A series of 3-oxo-C12-HSL, tetramic acid and tetronic acid analogues was synthesized to gain insights into the structural requirements for quorum sensing inhibition in Staphylococcus aureus. Compounds active against agr were non-competitive inhibitors of the auto-inducing peptide (AIP)-activated AgrC receptor, by altering the activation efficacy of the cognate AIP-1. They appeared to act as negative allosteric modulators and are exemplified by 3-tetradecanoyltetronic acid 17 which reduced nasal cell colonization and arthritis in a murine infection model.

Abnormal functional activation and maturation of fronto-striato-temporal and cerebellar regions during sustained attention in autism spectrum disorder

Objective Sustained attention problems are common in people with autism spectrum disorder (ASD) and may have significant implications for the diagnosis and management of ASD and associated comorbidities. Furthermore, ASD has been associated with atypical structural brain development. The authors used functional MRI to investigate the functional brain maturation of attention between childhood and adulthood in people with ASD. Method Using a parametrically modulated sustained attention/vigilance task, the authors examined brain activation and its linear correlation with age between childhood and adulthood in 46 healthy male adolescents and adults (ages 11–35 years) with ASD and 44 age- and IQ-matched typically developing comparison subjects. Results Relative to the comparison group, the ASD group had significantly poorer task performance and significantly lower activation in inferior prefrontal cortical, medial prefrontal cortical, striato-thalamic, and lateral cerebellar regions. A conjunction analysis of this analysis with group differences in brain-age correlations showed that the comparison group, but not the ASD group, had significantly progressively increased activation with age in these regions between childhood and adulthood, suggesting abnormal functional brain maturation in ASD. Several regions that showed both abnormal activation and functional maturation were associated with poorer task performance and clinical measures of ASD and inattention. Conclusions The results provide first evidence that abnormalities in sustained attention networks in individuals with ASD are associated with underlying abnormalities in the functional brain maturation of these networks between late childhood and adulthood.

The effect of chosen extraterrestrial solar spectrum on clear-sky atmospheric absorption and heating rates in the near infrared

The extraterrestrial solar spectrum (ESS) is an important component in near infrared (near-IR) radiative transfer calculations. However, the impact of a particular choice of the ESS in these regions has been given very little attention. A line-by-line (LBL) transfer model has been used to calculate the absorbed solar irradiance and solar heating rates in the near-IR from 2000-10000 cm−1(1-5 μm) using different ESS. For overhead sun conditions in a mid-latitude summer atmosphere, the absorbed irradiances could differ by up to about 11 Wm−2 (8.2%) while the tropospheric and stratospheric heating rates could differ by up to about 0.13 K day−1 (8.1%) and 0.19 K day−1 (7.6%). The spectral shape of the ESS also has a small but non-negligible impact on these factors in the near-IR.

Emotional and behavioural problems in children with language impairments and children with autism spectrum disorders

Background: Although it is well-established that children with language impairment (LI) and children with autism spectrum disorders (ASD) both show elevated levels of emotional and behavioural problems, the level and types of difficulties across the two groups have not previously been directly compared. Aims: To compare levels of emotional and behavioural problems in children with LI and children with ASD recruited from the same mainstream schools. Methods & Procedures: We measured teacher-reported emotional and behavioural problems using the Strengths and Difficulties Questionnaire (SDQ) in a sample of 5-to-13-year old children with LI (N=62) and children with ASD (N=42) attending mainstream school but with identified special educational needs. Outcomes & Results: Both groups showed similarly elevated levels of emotional, conduct and hyperactivity problems. The only differences between the LI and ASD groups were on subscales assessing peer problems (which were higher in the ASD group) and prosocial behaviours (which were higher in the LI group). Overall, there were few associations between emotional and behavioural problems and child characteristics, reflecting the pervasive nature of these difficulties in children with LI and children with ASD, although levels of problems were higher in children with ASD with lower language ability. However, in the ASD group only, a measure of family social economic status was associated with language ability and attenuated the association between language ability and emotional and behavioural problems. Conclusions & Implications: Children with LI and children with ASD in mainstream school show similarly elevated levels of emotional and behavioural problems, which require monitoring and may benefit from intervention. Further work is required to identify the child, family and situational factors that place children with LI and children with ASD at risk of emotional and behavioural problems, and whether these differ between the two groups. This work can then guide the application of evidence-based interventions to these children.

Translation and usability of autism screening and diagnostic tools for autism spectrum conditions in India

There is a critical need for screening and diagnostic tools (SDT) for autism spectrum conditions (ASC) in regional languages in South Asia. To address this, we translated four widely used SDT (Social Communication Disorder Checklist, Autism Spectrum Quotient, Social Communication Questionnaire, and Autism Diagnostic Observation Schedule) into Bengali and Hindi, two main regional languages (∼ 360 million speakers), and tested their usability in children with and without ASC. We found a significant difference in scores between children with ASC (n = 45 in Bengali, n = 40 in Hindi) and typically developing children (n = 43 in Bengali, n = 42 in Hindi) on all SDTs. These results demonstrate that these SDTs are usable in South Asia, and constitute an important resource for epidemiology research and clinical diagnosis in the region.

Complex extreme learning machine applications in terahertz pulsed signals feature sets

This paper presents a novel approach to the automatic classification of very large data sets composed of terahertz pulse transient signals, highlighting their potential use in biochemical, biomedical, pharmaceutical and security applications. Two different types of THz spectra are considered in the classification process. Firstly a binary classification study of poly-A and poly-C ribonucleic acid samples is performed. This is then contrasted with a difficult multi-class classification problem of spectra from six different powder samples that although have fairly indistinguishable features in the optical spectrum, they also possess a few discernable spectral features in the terahertz part of the spectrum. Classification is performed using a complex-valued extreme learning machine algorithm that takes into account features in both the amplitude as well as the phase of the recorded spectra. Classification speed and accuracy are contrasted with that achieved using a support vector machine classifier. The study systematically compares the classifier performance achieved after adopting different Gaussian kernels when separating amplitude and phase signatures. The two signatures are presented as feature vectors for both training and testing purposes. The study confirms the utility of complex-valued extreme learning machine algorithms for classification of the very large data sets generated with current terahertz imaging spectrometers. The classifier can take into consideration heterogeneous layers within an object as would be required within a tomographic setting and is sufficiently robust to detect patterns hidden inside noisy terahertz data sets. The proposed study opens up the opportunity for the establishment of complex-valued extreme learning machine algorithms as new chemometric tools that will assist the wider proliferation of terahertz sensing technology for chemical sensing, quality control, security screening and clinic diagnosis. Furthermore, the proposed algorithm should also be very useful in other applications requiring the classification of very large datasets.

Thermal remote sensing of sea surface temperature

Sea surface temperature has been an important application of remote sensing from space for three decades. This chapter first describes well-established methods that have delivered valuable routine observations of sea surface temperature for meteorology and oceanography. Increasingly demanding requirements, often related to climate science, have highlighted some limitations of these ap-proaches. Practitioners have had to revisit techniques of estimation, of characterising uncertainty, and of validating observations—and even to reconsider the meaning(s) of “sea surface temperature”. The current understanding of these issues is reviewed, drawing attention to ongoing questions. Lastly, the prospect for thermal remote sens-ing of sea surface temperature over coming years is discussed.