ReadingAct RGB-D action dataset and human action recognition from local features

For general home monitoring, a system should automatically interpret people’s actions. The system should be non-intrusive, and able to deal with a cluttered background, and loose clothes. An approach based on spatio-temporal local features and a Bag-of-Words (BoW) model is proposed for single-person action recognition from combined intensity and depth images. To restore the temporal structure lost in the traditional BoW method, a dynamic time alignment technique with temporal binning is applied in this work, which has not been previously implemented in the literature for human action recognition on depth imagery. A novel human action dataset with depth data has been created using two Microsoft Kinect sensors. The ReadingAct dataset contains 20 subjects and 19 actions for a total of 2340 videos. To investigate the effect of using depth images and the proposed method, testing was conducted on three depth datasets, and the proposed method was compared to traditional Bag-of-Words methods. Results showed that the proposed method improves recognition accuracy when adding depth to the conventional intensity data, and has advantages when dealing with long actions.

Preliminary leaf area index estimates from airborne small footprint full-waveform LiDAR data

This study has compared preliminary estimates of effective leaf area index (LAI) derived from fish-eye lens photographs to those estimated from airborne full-waveform small-footprint LiDAR data for a forest dataset in Australia. The full-waveform data was decomposed and optimized using a trust-region-reflective algorithm to extract denser point clouds. LAI LiDAR estimates were derived in two ways (1) from the probability of discrete pulses reaching the ground without being intercepted (point method) and (2) from raw waveform canopy height profile processing adapted to small-footprint laser altimetry (waveform method) accounting for reflectance ratio between vegetation and ground. The best results, that matched hemispherical photography estimates, were achieved for the waveform method with a study area-adjusted reflectance ratio of 0.4 (RMSE of 0.15 and 0.03 at plot and site level, respectively). The point method generally overestimated, whereas the waveform method with an arbitrary reflectance ratio of 0.5 underestimated the fish-eye lens LAI estimates.

Anthelmintic activities against Haemonchus contortus or Trichostrongylus colubriformis from small ruminants are influenced by structural features of condensed tannins

Plants containing condensed tannins (CTs) may hold promise as alternatives to synthetic anthelmintic (AH) drugs for controlling gastrointestinal nematodes (GINs). However, the structural features that contribute to the AH activities of CTs remain elusive. This study probed the relationships between CT structures and their AH activities. Eighteen plant resources were selected based on their diverse CT structures. From each plant resource, two CT fractions were isolated and their in vitro AH activities were measured with the Larval Exsheathment Inhibition Assay, which was applied to Haemonchus contortus and Trichostrongylus colubriformis. Calculation of mean EC50 values indicated that H. contortus was more susceptible than T colubriformis to the different fractions and that the F1 fractions were less efficient than the F2 ones, as indicated by the respective mean values for H.contortus F1 = 136.9 ± 74.1 µg/ml; and for H.contortus F2 = 108.1 ± 53.2 µg/ml and for T colubriformis F1 = 233 ± 54.3 µg/ml and F2=166 ± 39.9 µg/ml. The results showed that the AH activity against H. contortus was associated with the monomeric subunits that give rise to prodelphinidins (P < 0.05) and with CT polymer size (P < 0.10). However, for T. colubriformis AH activity was correlated only with prodelphinidins (P < 0.05). These results suggest that CTs have different modes of action against different parasite species.

Distinct clinical and neuropathological features of G51D SNCA mutation cases compared with SNCA duplication and H50Q mutation

Background: We and others have described the neurodegenerative disorder caused by G51D SNCA mutation which shares characteristics of Parkinson’s disease (PD) and multiple system atrophy (MSA). The objective of this investigation was to extend the description of the clinical and neuropathological hallmarks of G51D mutant SNCA-associated disease by the study of two additional cases from a further G51D SNCA kindred and to compare the features of this group with a SNCA duplication case and a H50Q SNCA mutation case. Results: All three G51D patients were clinically characterised by parkinsonism, dementia, visual hallucinations, autonomic dysfunction and pyramidal signs with variable age at disease onset and levodopa response. The H50Q SNCA mutation case had a clinical picture that mimicked late-onset idiopathic PD with a good and sustained levodopa response. The SNCA duplication case presented with a clinical phenotype of frontotemporal dementia with marked behavioural changes, pyramidal signs, postural hypotension and transiently levodopa responsive parkinsonism. Detailed post-mortem neuropathological analysis was performed in all cases. All three G51D cases had abundant α-synuclein pathology with characteristics of both PD and MSA. These included widespread cortical and subcortical neuronal α-synuclein inclusions together with small numbers of inclusions resembling glial cytoplasmic inclusions (GCIs) in oligodendrocytes. In contrast the H50Q and SNCA duplication cases, had α-synuclein pathology resembling idiopathic PD without GCIs. Phosphorylated α-synuclein was present in all inclusions types in G51D cases but was more restricted in SNCA duplication and H50Q mutation. Inclusions were also immunoreactive for the 5G4 antibody indicating their highly aggregated and likely fibrillar state. Conclusions: Our characterisation of the clinical and neuropathological features of the present small series of G51D SNCA mutation cases should aid the recognition of this clinico-pathological entity. The neuropathological features of these cases consistently share characteristics of PD and MSA and are distinct from PD patients carrying the H50Q or SNCA duplication.

Living to die and dying to live: the survival strategy behind leaf senescence

Senescence represents the final developmental act of the leaf, during which the leaf cell is dismantled in a coordinated manner to remobilize nutrients and to secure reproductive success. The process of senescence provides the plant with phenotypic plasticity to help it adapt to adverse environmental conditions. Here, we provide a comprehensive overview of the factors and mechanisms that control the onset of senescence. We explain how the competence to senesce is established during leaf development, as depicted by the senescence window model. We also discuss the mechanisms by which phytohormones and environmental stresses control senescence, as well as the impact of source-sink relationships on plant yield and stress tolerance. In addition, we discuss the role of senescence as a strategy for stress adaptation and how crop production and food quality could benefit from engineering or breeding crops with altered onset of senescence.

Understanding 2H/1H systematics of leaf wax n-alkanes in coastal plants at Stiffkey saltmarsh, Norfolk, UK

Interpretation of sedimentary n-alkyl lipid d2H data is complicated by a limited understanding of factors controlling interspecies variation in biomarker 2H/1H composition. To distinguish between the effects of interrelated environmental, physical and biochemical controls on the hydrogen isotope composition of n-alkyl lipids, we conducted linked d2H analyses of soil water, xylem water, leaf water and n-alkanes from a range of C3 and C4 plants growing at a UK saltmarsh (i) across multiple sampling sites, (ii) throughout the 2012 growing season, and (iii) at different times of the day. Soil waters varied isotopically by up to 35& depending on marsh sub-environment, and exhibited site-specific seasonal shifts in d2H up to a maximum of 31 per mil. Maximum interspecies variation in xylem water was 38 per mil, while leaf waters differed seasonally by a maximum of 29 per mil. Leaf wax n-alkane 2H/1H, however, consistently varied by over 100 per mil throughout the 2012 growing season, resulting in an interspecies range in the ewax/leaf water values of -79 per mil to –227 per mil. From the discrepancy in the magnitude of these isotopic differences, we conclude that mechanisms driving variation in the 2H/1H composition of leaf water, including (i) spatial changes in soil water 2H/1H, (ii) temporal changes in soil water 2H/1H, (iii) differences in xylem water 2H/1H, and (iv) differences in leaf water evaporative 2H-enrichment due to varied plant life forms, cannot explain the range of n-alkane d2H values we observed. Results from this study suggests that accurate reconstructions of palaeoclimate regimes from sedimentary n-alkane d2H require further research to constrain those biological mechanisms influencing species-specific differences in 2H/1H fractionation during lipid biosynthesis, in particular where plants have developed biochemical adaptations to water-stressed conditions. Understanding how these mechanisms interact with environmental conditions will be crucial to ensure accurate interpretation of hydrogen isotope signals from the geological record.

Time-lapse geophysical investigations over known archaeological features using electrical resistivity imaging and earth resistance

Electrical methods of geophysical survey are known to produce results that are hard to predict at different times of the year, and under differing weather conditions. This is a problem which can lead to misinterpretation of archaeological features under investigation. The dynamic relationship between a ‘natural’ soil matrix and an archaeological feature is a complex one, which greatly affects the success of the feature’s detection when using active electrical methods of geophysical survey. This study has monitored the gradual variation of measured resistivity over a selection of study areas. By targeting difficult to find, and often ‘missing’ electrical anomalies of known archaeological features, this study has increased the understanding of both the detection and interpretation capabilities of such geophysical surveys. A 16 month time-lapse study over 4 archaeological features has taken place to investigate the aforementioned detection problem across different soils and environments. In addition to the commonly used Twin-Probe earth resistance survey, electrical resistivity imaging (ERI) and quadrature electro-magnetic induction (EMI) were also utilised to explore the problem. Statistical analyses have provided a novel interpretation, which has yielded new insights into how the detection of archaeological features is influenced by the relationship between the target feature and the surrounding ‘natural’ soils. The study has highlighted both the complexity and previous misconceptions around the predictability of the electrical methods. The analysis has confirmed that each site provides an individual and nuanced situation, the variation clearly relating to the composition of the soils (particularly pore size) and the local weather history. The wide range of reasons behind survey success at each specific study site has been revealed. The outcomes have shown that a simplistic model of seasonality is not universally applicable to the electrical detection of archaeological features. This has led to the development of a method for quantifying survey success, enabling a deeper understanding of the unique way in which each site is affected by the interaction of local environmental and geological conditions.

Responses of leaf traits to climatic gradients: adaptive variation versus compositional shifts

Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature, but Parea increased with temperature. Although the adaptive nature of many of these trait-climate relationships is understood qualitatively, a key challenge for modelling is to predict them quantitatively. Models must take into account that community-level responses to climatic gradients can be influenced by shifts in PFT composition, such as the replacement of deciduous by evergreen trees, which may run either parallel or counter to trait variation within PFTs. The importance of PFT shifts varies among traits, being important for biophysical traits but less so for physiological and chemical traits. Finally, models should take account of the diversity of trait values that is found in all sites and PFTs, representing the "pool" of variation that is locally available for the natural adaptation of ecosystem function to environmental change.

Linguistic innovations in IRC: Cypriot-Greek phonological features

The Cypriot Greek variety (CG), spoken in the island of Cyprus, is relatively distinct from Standard Greek (SG) in all linguistic domains and, especially, in the area of pronunciation. Youth language, within the Greek-Cypriot context, is an area of study that has, until recently, received little attention. Tsiplakou (2004) makes reference to the emergence of a new slang among young Greek-Cypriots, influenced by new comedy series, in which the actors make extensive use of ‘exaggeratedly peasant’ CG. As these comedy series become increasingly popular, the use of marked regional features becomes evident in the speech style of young Greek-Cypriots. A preliminary study has also revealed that marked CG linguistic features are equally evident in the online interactions of young internet users (Themistocleous 2005). In this study, I examine the use of CG phonological elements in a corpus of messages collected from channel #Cyprus, of Internet Relay Chat (IRC). It is demonstrated that young Greek-Cypriots use language in creative ways, in order to represent in writing phonological features, typical of their informal speech.

Relative importance of transpiration rate and leaf morphological traits for the regulation of leaf temperature

Urban greening solutions such as green roofs help improve residents’ thermal comfort and building insulation. However, not all plants provide the same level of cooling. This is partially due to differences in plant structure and function, including different mechanisms that plants employ to regulate leaf temperature. Ranking of multiple leaf/plant traits involved in the regulation of leaf temperature (and, consequently, plants’ cooling ‘service’) is not well understood. We therefore investigated the relative importance of water loss, leaf colour, thickness and extent of pubescence for the regulation of leaf temperature, in the context of species for semi-extensive green roofs. Leaf temperature were measured with an infrared imaging camera in a range of contrasting genotypes within three plant genera (Heuchera, Salvia and Sempervivum). In three glasshouse experiments (each evaluating three or four genotypes of each genera) we varied water availability to the plants and assessed how leaf temperature altered depending on water loss and specific leaf traits. Greatest reductions in leaf temperature were closely associated with higher water loss. Additionally, in non-succulents (Heuchera, Salvia), lighter leaf colour and longer hair length (on pubescent leaves) both contributed to reduced leaf temperature. However, in succulent Sempervivum, colour/pubescence made no significant contribution; leaf thickness and water loss rate were the key regulating factors. We propose that this can lead to different plant types having significantly different potentials for cooling. We suggest that maintaining transpirational water loss by sustainable irrigation and selecting urban plants with favourable morphological traits is the key to maximising thermal benefits provided by applications such as green roofs.

Specific leaf area and leaf area index in developing stands of Fagus sylvatica L. and Picea abies Karst

European beech (Fagus sylvatica L.) and Norway spruce (Picea abies Karst.) are two of the most ecologically and economically important forest tree species in Europe. These two species co-occur in many locations in Europe, leading to direct competition for canopy space. Foliage characteristics of two naturally regenerated pure stands of beech and spruce with fully closed canopies were contrasted to assess the dynamic relationship between foliage adaptability to shading, stand LAI and tree growth. We found that individual leaf size is far more conservative in spruce than in beech. Individual leaf and needle area was larger at the top than at the bottom of the canopy in both species. Inverse relationship was found for specific leaf area (SLA), highest SLA values were found at lowest light availability under the canopy. There was no difference in leaf area index (LAI) between the two stands, however LAI increased from 10.8 to 14.6 m2m-2 between 2009 and 2011. Dominant trees of both species were more efficient in converting foliage mass or area to produce stem biomass, although this relationship changed with age and was species-specific. Overall, we found larger foliage plasticity in beech than in spruce in relation to light conditions, indicating larger capacity to exploit niche openings.

A Genetic Algorithm for the selection of structural MRI features for classification of Mild Cognitive Impairment and Alzheimer's Disease

This work investigates the problem of feature selection in neuroimaging features from structural MRI brain images for the classification of subjects as healthy controls, suffering from Mild Cognitive Impairment or Alzheimer’s Disease. A Genetic Algorithm wrapper method for feature selection is adopted in conjunction with a Support Vector Machine classifier. In very large feature sets, feature selection is found to be redundant as the accuracy is often worsened when compared to an Support Vector Machine with no feature selection. However, when just the hippocampal subfields are used, feature selection shows a significant improvement of the classification accuracy. Three-class Support Vector Machines and two-class Support Vector Machines combined with weighted voting are also compared with the former and found more useful. The highest accuracy achieved at classifying the test data was 65.5% using a genetic algorithm for feature selection with a three-class Support Vector Machine classifier.