The co-occurrence of autism and Williams syndrome: a case study report

This paper describes a longitudinal case study detailing the communication profile of one child with both Williams syndrome (WS) and autism. The participant was administered two standardized assessments of language and general cognitive abilities. His parents completed the Pre-Verbal Communication Schedule; and a sample of the child's spontaneous interaction was analyzed. The results show that this child presents with markedly delayed language and communication skills and that his communication profile is the opposite of the assumed 'typical' WS profile. The conclusion is that clinicians need to be aware of the co-occurrence of genetic disorders, such as WS and autism in order to facilitate accurate diagnosis and effective treatment.

Fundamental deficits of auditory perception in Wernicke’s aphasia

Objective: This work investigates the nature of the comprehension impairment in Wernicke’s aphasia, by examining the relationship between deficits in auditory processing of fundamental, non-verbal acoustic stimuli and auditory comprehension. Wernicke’s aphasia, a condition resulting in severely disrupted auditory comprehension, primarily occurs following a cerebrovascular accident (CVA) to the left temporo-parietal cortex. Whilst damage to posterior superior temporal areas is associated with auditory linguistic comprehension impairments, functional imaging indicates that these areas may not be specific to speech processing but part of a network for generic auditory analysis. Methods: We examined analysis of basic acoustic stimuli in Wernicke’s aphasia participants (n = 10) using auditory stimuli reflective of theories of cortical auditory processing and of speech cues. Auditory spectral, temporal and spectro-temporal analysis was assessed using pure tone frequency discrimination, frequency modulation (FM) detection and the detection of dynamic modulation (DM) in “moving ripple” stimuli. All tasks used criterion-free, adaptive measures of threshold to ensure reliable results at the individual level. Results: Participants with Wernicke’s aphasia showed normal frequency discrimination but significant impairments in FM and DM detection, relative to age- and hearing-matched controls at the group level (n = 10). At the individual level, there was considerable variation in performance, and thresholds for both frequency and dynamic modulation detection correlated significantly with auditory comprehension abilities in the Wernicke’s aphasia participants. Conclusion: These results demonstrate the co-occurrence of a deficit in fundamental auditory processing of temporal and spectrotemporal nonverbal stimuli in Wernicke’s aphasia, which may have a causal contribution to the auditory language comprehension impairment Results are discussed in the context of traditional neuropsychology and current models of cortical auditory processing.

TRCM: a methodology for temporal analysis of evolving concepts in Twitter

The Twitter network has been labelled the most commonly used microblogging application around today. With about 500 million estimated registered users as of June, 2012, Twitter has become a credible medium of sentiment/opinion expression. It is also a notable medium for information dissemination; including breaking news on diverse issues since it was launched in 2007. Many organisations, individuals and even government bodies follow activities on the network in order to obtain knowledge on how their audience reacts to tweets that affect them. We can use postings on Twitter (known as tweets) to analyse patterns associated with events by detecting the dynamics of the tweets. A common way of labelling a tweet is by including a number of hashtags that describe its contents. Association Rule Mining can find the likelihood of co-occurrence of hashtags. In this paper, we propose the use of temporal Association Rule Mining to detect rule dynamics, and consequently dynamics of tweets. We coined our methodology Transaction-based Rule Change Mining (TRCM). A number of patterns are identifiable in these rule dynamics including, new rules, emerging rules, unexpected rules and ?dead' rules. Also the linkage between the different types of rule dynamics is investigated experimentally in this paper.

Perfectionism as a transdiagnostic process: a clinical review

Perfectionism is a risk and maintaining factor for eating disorders, anxiety disorders and depression. The objective of this paper is to review the four bodies of evidence supporting the notion that perfectionism is a transdiagnostic process. First, a review of the literature was conducted that demonstrates the elevation of perfectionism across numerous anxiety disorders, depression, and eating disorders compared to healthy controls. Data is presented that shows perfectionism increases vulnerability for eating disorders, and that it maintains obsessive–compulsive disorder, social anxiety and depression as it predicts treatment outcome in these disorders. Second, evidence is examined showing that elevated perfectionism is associated with co-occurrence of psychopathology. Third, the different conceptualisations of perfectionism are reviewed, including a cognitive-behavioural conceptualisation of clinical perfectionism that can be utilised to understand this transdiagnostic process. Fourth, evidence that treatment of perfectionism results in reductions in anxiety, depression and eating pathology is reviewed. Finally,the importance of clinicians considering the routine assessment and treatment of perfectionism is outlined.

Autistic symptomatology and language ability in autism spectrum disorder and specific language impairment

Background: Autism spectrum disorders (ASD) and specific language impairment (SLI) are common developmental disorders characterised by deficits in language and communication. The nature of the relationship between them continues to be a matter of debate. This study investigates whether the co-occurrence of ASD and language impairment is associated with differences in severity or pattern of autistic symptomatology or language profile. Methods: Participants (N = 97) were drawn from a total population cohort of 56,946 screened as part of study to ascertain the prevalence of ASD, aged 9 to 14 years. All children received an ICD-10 clinical diagnosis of ASD or No ASD. Children with nonverbal IQ 80 were divided into those with a language impairment (language score of 77 or less) and those without, creating three groups: children with ASD and a language impairment (ALI; N = 41), those with ASD and but no language impairment (ANL; N = 31) and those with language impairment but no ASD (SLI; N = 25). Results: Children with ALI did not show more current autistic symptoms than those with ANL. Children with SLI were well below the threshold for ASD. Their social adaptation was higher than the ASD groups, but still nearly 2 SD below average. In ALI the combination of ASD and language impairment was associated with weaker functional communication and more severe receptive language difficulties than those found in SLI. Receptive and expressive language were equally impaired in ALI, whereas in SLI receptive language was stronger than expressive. Conclusions: Co-occurrence of ASD and language impairment is not associated with increased current autistic symptomatology but appears to be associated with greater impairment in receptive language and functional communication.

Attention processes in children with movement difficulties, reading difficulties or both

Reading difficulties (RD) and movement difficulties (MD) co-occur more often in clinical populations than expected for independent disorders. In this study, we investigated the pattern of association between attentional processes, RD and MD in a population of 9 year old school children. Children were screened to identify index groups with RD, MD or both, plus a control group. These groups were then tested on a battery of cognitive attention assessments (TEA-Ch). Results confirmed that the occurrence of RD and MD was greater than would be predicted for independent disorders. Additionally, children with MD, whether or not combined with RD, had poor performance on all attention measures when compared with typically developing children. Children with RD only, were no poorer on measures of attention than typical children. The results are discussed with respect to approaches proposed to account for the co-occurrence of disorders.

Multimodal semantic-associative collateral labelling and indexing of still images

A novel framework for multimodal semantic-associative collateral image labelling, aiming at associating image regions with textual keywords, is described. Both the primary image and collateral textual modalities are exploited in a cooperative and complementary fashion. The collateral content and context based knowledge is used to bias the mapping from the low-level region-based visual primitives to the high-level visual concepts defined in a visual vocabulary. We introduce the notion of collateral context, which is represented as a co-occurrence matrix, of the visual keywords, A collaborative mapping scheme is devised using statistical methods like Gaussian distribution or Euclidean distance together with collateral content and context-driven inference mechanism. Finally, we use Self Organising Maps to examine the classification and retrieval effectiveness of the proposed high-level image feature vector model which is constructed based on the image labelling results.

Semantic-driven context-aware visual information indexing and retrieval: applied in the film post-production domain

A large volume of visual content is inaccessible until effective and efficient indexing and retrieval of such data is achieved. In this paper, we introduce the DREAM system, which is a knowledge-assisted semantic-driven context-aware visual information retrieval system applied in the film post production domain. We mainly focus on the automatic labelling and topic map related aspects of the framework. The use of the context- related collateral knowledge, represented by a novel probabilistic based visual keyword co-occurrence matrix, had been proven effective via the experiments conducted during system evaluation. The automatically generated semantic labels were fed into the Topic Map Engine which can automatically construct ontological networks using Topic Maps technology, which dramatically enhances the indexing and retrieval performance of the system towards an even higher semantic level.

Semantic-associative visual content labelling and retrieval: A multimodal approach

A novel framework referred to as collaterally confirmed labelling (CCL) is proposed, aiming at localising the visual semantics to regions of interest in images with textual keywords. Both the primary image and collateral textual modalities are exploited in a mutually co-referencing and complementary fashion. The collateral content and context-based knowledge is used to bias the mapping from the low-level region-based visual primitives to the high-level visual concepts defined in a visual vocabulary. We introduce the notion of collateral context, which is represented as a co-occurrence matrix of the visual keywords. A collaborative mapping scheme is devised using statistical methods like Gaussian distribution or Euclidean distance together with collateral content and context-driven inference mechanism. We introduce a novel high-level visual content descriptor that is devised for performing semantic-based image classification and retrieval. The proposed image feature vector model is fundamentally underpinned by the CCL framework. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval, respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicate that the proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models. (C) 2007 Elsevier B.V. All rights reserved.

Amygdalar function reflects common individual differences in emotion and pain regulation success

Although the co-occurrence of negative affect and pain is well recognized, the mechanism underlying their association is unclear. To examine whether a common self-regulatory ability impacts the experience of both emotion and pain, we integrated neuroimaging, behavioral, and physiological measures obtained from three assessments separated by substantial temporal intervals. Out results demonstrated that individual differences in emotion regulation ability, as indexed by an objective measure of emotional state, corrugator electromyography, predicted self-reported success while regulating pain. In both emotion and pain paradigms, the amygdala reflected regulatory success. Notably, we found that greater emotion regulation success was associated with greater change of amygdalar activity following pain regulation. Furthermore, individual differences in degree of amygdalar change following emotion regulation were a strong predictor of pain regulation success, as well as of the degree of amygdalar engagement following pain regulation. These findings suggest that common individual differences in emotion and pain regulatory success are reflected in a neural structure known to contribute to appraisal processes.

Integrated visual vocabulary in latent Dirichlet allocation-based scene classification for IKONOS image

Scene classification based on latent Dirichlet allocation (LDA) is a more general modeling method known as a bag of visual words, in which the construction of a visual vocabulary is a crucial quantization process to ensure success of the classification. A framework is developed using the following new aspects: Gaussian mixture clustering for the quantization process, the use of an integrated visual vocabulary (IVV), which is built as the union of all centroids obtained from the separate quantization process of each class, and the usage of some features, including edge orientation histogram, CIELab color moments, and gray-level co-occurrence matrix (GLCM). The experiments are conducted on IKONOS images with six semantic classes (tree, grassland, residential, commercial/industrial, road, and water). The results show that the use of an IVV increases the overall accuracy (OA) by 11 to 12% and 6% when it is implemented on the selected and all features, respectively. The selected features of CIELab color moments and GLCM provide a better OA than the implementation over CIELab color moment or GLCM as individuals. The latter increases the OA by only ∼2 to 3%. Moreover, the results show that the OA of LDA outperforms the OA of C4.5 and naive Bayes tree by ∼20%. © 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) [DOI: 10.1117/1.JRS.8.083690]

Synergy of extreme drought and shrub invasion reduce ecosystem functioning and resilience in water-limited climates

Extreme drought events and plant invasions are major drivers of global change that can critically affect ecosystem functioning and alter ecosystem-atmosphere exchange. Invaders are expanding worldwide and extreme drought events are projected to increase in frequency and intensity. However, very little is known on how these drivers may interact to affect the functioning and resilience of ecosystems to extreme events. Using a manipulative shrub removal experiment and the co-occurrence of an extreme drought event (2011/2012) in a Mediterranean woodland, we show that native shrub invasion and extreme drought synergistically reduced ecosystem transpiration and the resilience of key-stone oak tree species. Ecosystem transpiration was dominated by the water use of the invasive shrub Cistus ladanifer, which further increased after the extreme drought event. Meanwhile, the transpiration of key-stone tree species decreased, indicating a competitive advantage in favour of the invader. Our results suggest that in Mediterranean-type climates the invasion of water spending species and projected recurrent extreme drought events may synergistically cause critical drought tolerance thresholds of key-stone tree species to be surpassed, corroborating observed higher tree mortality in the invaded ecosystems. Ultimately, this may shift seasonally water limited ecosystems into less desirable alternative states dominated by water spending invasive shrubs.

A robust two-dimensional hydrogen-bonded network for the predictable assembly of ternary co-crystals of furosemide

Consideration of the geometrical features of the functional groups present in furosemide has enabled synthesis of a series of ternary co-crystals with predictable structural features, containing a robust asymmetric two-dimensional network.

Synthesis, structural analysis, and magnetic behaviour of three fumarate bridged coordination polymers: five-fold interpenetrated diamond-like net of Ni-II, sheets of Ni-II and Co-II

The hydrothermal reactions of Ni(NO3)(2).6H(2)O, disodium fumarate (fum) and 1,2-bis(4-pyridyl)ethane (bpe)/1,3-bis(4-pyridyl) propane (bpp) in aqueous-methanol medium yield one 3-D and one 2-D metal-organic hybrid material, [Ni(fum)(bpe)] (1) and [Ni(fum)(bpp)(H2O)] (2), respectively. Complex 1 possesses a novel unprecedented structure, the first example of an "unusual mode" of a five-fold distorted interpenetrated network with metal-ligand linkages where the four six-membered windows in each adamantane-type cage are different. The structural characterization of complex 2 evidences a buckled sheet where nickel ions are in a distorted octahedral geometry, with two carboxylic groups, one acting as a bis-chelate, the other as a bis-monodentate ligand. The metal ion completes the coordination sphere through one water molecule and two bpp nitrogens in cis position. Variable-temperature magnetic measurements of complexes 1 and 2 reveal the existence of very weak antiferromagnetic intramolecular interactions and/or the presence of single-ion zero field splitting (D) of isolated Ni-II ions in both the compounds. Experimentally, both the J parameters are close, comparable and very small. Considering zero-field splitting of Ni-II, the calculated D values are in agreement with values reported in the literature for Ni-II ions. Complex 3, [{Co(phen)}(2)(fum)(2)] (phen=1,10-phenanthroline) is obtained by diffusing methanolic solution of 1,10-phenanthroline on an aqueous layer of disodium fumarate and Co(NO3)(2).6H(2)O. It consists of dimeric Co-II(phen) units, doubly bridged by carboxylate groups in a distorted syn-syn fashion. These fumarate anions act as bis-chelates to form corrugated sheets. The 2D layer has a (4,4) topology, with the nodes represented by the centres of the dimers. The magnetic data were fitted ignoring the very weak coupling through the fumarate pathway and using a dimer model.