The Gestational Effects of Maternal Bone Marker Molecules on Fetal Growth,Metabolism and Long-Term Metabolic Health: A Systematic Review

Fetal exposure in adverse environmental factors during intrauterine life can lead to various biological adjustments, affecting not only in utero development of the conceptus, but also its later metabolic and endocrine wellbeing. During human gestation, maternal bone turnover increases, as reflected by molecules involved in bone metabolism, such as vitamin D, osteocalcin, sclerostin, sRANKL, and osteoprotegerin; however, recent studies support their emerging role in endocrine functions and glucose homeostasis regulation. Herein, we sought to systematically review current knowledge on the effects of aforementioned maternal bone biomarkers during pregnancy on fetal intrauterine growth and metabolism, neonatal anthropometric measures at birth, as well as on future endocrine and metabolic wellbeing of the offspring. A growing body of literature converges on the view that maternal bone turnover is likely implicated in fetal growth, and at least to some extent, in neonatal and childhood body composition and metabolic wellbeing. Maternal sclerostin and sRANKL are positively linked with fetal abdominal circumference and subcutaneous fat deposition, contributing to greater birthweights. Vitamin D deficiency correlates with lower birthweights, while research is still needed on intrauterine fetal metabolism, as well as on vitamin D dosing supplementation during pregnancy, to diminish the risks of low birthweight or SGA neonates in high-risk populations.     

Adhesion of electrodeposited nanocrystalline Ni–W coatings on Cu

A study was performed on the adhesion of nanocrystalline Ni–W alloy coatings, on copper, with the help of a scratch testing apparatus. The nanocrystalline Ni–W coatings were electrodeposited on copper substrates. The tungsten content in the Ni–W alloy coating was found to be 42?wt-% (19?at.-%). The results obtained from the scratch experiments showed that the nanocrystalline Ni–W coatings on copper suffer tensile failure and minor delamination. The mean cohesive and adhesive critical loads were found to be in the range of 19–85?N and 34–102?N, respectively and to increase with increasing thickness of the coatings.     

3D extrusion of multi-biomaterial lattices using an environmentally informed workflow

The conventional building material palette has been proven limited in terms of adaptability to our current environmental challenges. Innovations in computational design and digital manufacturing have supported the broadening of biomaterial applications as an alternative. While biomaterials are characteristically responsive to stimuli such as temperature and humidity, their unpredictable behaviour is a hurdle to standardization and architectural utilisation. To examine the nexus between material formulation, computation and manufacturing, multi-biomaterial lattice structures were produced through an environmentally informed workflow. Customized biomaterial development resulted in three candidate biopolymer blends with varying levels of hydro-responsiveness and transparency. The computational strategy included a machine learning clustering algorithm to customise results and dictate material distribution outputs. To test the workflow, environmental data of solar radiation exposure and solar heat gain from a specific location was used to inform the material deposition via pneumatic extrusion for the design and digital fabrication of a deformation-controlled prototype of 350 mm × 350 mm. This led to a series of multi-biomaterial wall panel components that can be applied at architectural scale. In future, these techniques can support the incorporation of living elements to be embedded within the built environment for truly animate architecture.     

Physiological and perceptual features of dysarthria in Moebius syndrome: directions for treatment

The functioning of the major subsystems of the speech production apparatus of a 12 year old female with Moebius syndrome was investigated using a battery of perceptual and physiological instrumental measures. Perceptual tests administered included: The Assessment of Intelligibility of Dysarthric Speech; the Frenchay Dysarthria Assessment; and a perceptual analysis of a speech sample based on a reading of the Grandfather Passage. Instrumental procedures included: spirometric and kinematic analysis of speech breathing; electroglottographic and aerodynamic evaluation of laryngeal function; nasometric assessment of velopharyngeal function; and evaluation of lip and tongue function using a variety of strain-gauge and pressure transducers. Consistent with the pathophysiological basis of Moebius syndrome, the major dysfunctions of the speech production mechanism were found at the level of the articulatory valve. Somewhat unexpectedly, however, impaired function was also identified at the level of the velopharyngeal and laryngeal valves by both the perceptual and instrumental assessments and at the level of the respiratory system by the physiological analysis alone. The results are discussed with reference to the neurological basis and clinical features of Moebius syndrome. The implications of the findings for the treatment of congenital dysarthria associated with Moebius syndrome are also discussed. The advantage of instrumental analysis over perceptual assessments in defining treatment goals for children with congenital dysarthria is highlighted.     

A method for fast digital simulation of induction motor drive systems including the power electronic circuit

Contents A method for fast digital simulation of induction motor drive systems based on a simple numerical algorithm is proposed. An efficient technique is used for the automatic formulation of the power electronic circuit which is based on the fundamental loop matrix modification. A discrete-time model of the induction machine, which can be directly interfaced with the power electronic circuit, is introduced. Computer results of a drive system that illustrate the capabilities of the method are also presented.

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Eine Methode für schnelle Simulation von Antriebssystemen mit Induktionsmotor einschliesslich Leistungselektronikschaltung

Übersicht Eine Methode für schnelle digitale Simulation eines Antriebssystems mit Induktionsmotor basierend auf einfachen numerischen Algorithmen wird vorgeschlagen. Eine wirkungsvolle Technik für die automatische Formulierung der Gleichungen für die Leistungselektronikschaltungen wird verwendet, die auf einer Modifikation der fundamentalen Maschenmatrix beruht. Ein zeitdiskretes Modell für die Induktionsmaschine wird eingeführt, das direkt mit der Leistungselektronikschaltung verbunden werden kann. Rechenresultate für ein Antriebssystem zur Illustration der Methodenfähigkeit werden ebenfalls vorgestellt.

     

Quantifying the Poorly Known Role of Groundwater in Agriculture: the Case of Cyprus

Agriculture in the Mediterranean region is constrained by limited water resources and in many countries irrigation demand exceeds the renewable water supply. This paper presents a comprehensive approach to (a) quantify the consumptive green (soil moisture provided by precipitation) and blue (irrigation) water use for crop production, (b) distinguish the contribution of groundwater to irrigation supply and (c) estimate groundwater over-abstraction. A spatiotemporally explicit soil water balance model, based on the FAO-56 dual crop coefficient approach, which includes the computation of evaporation losses of the different irrigation systems, was applied to the 5,760-km² area of the Republic of Cyprus for the agro-meteorological years 1995–2009. The model uses national agricultural statistics, community-level data from the agricultural census and daily data from 34 meteorological stations and 70 precipitation gauges. Groundwater over-abstraction is quantified per groundwater body, based on the sustainable abstraction rates specified in the Cyprus River Basin Management Plan, as prepared for the EU Water Framework Directive. It was found that, on average, total agricultural water use was 506 Mm³/year, of which 62 % is attributed to green water use and 38 % to blue water use. Groundwater contributed, on average, 81 % (151 Mm³/year) to blue water use and exceeded the recommended abstraction rates by 45 % (47 Mm³/year). Even though the irrigated area decreased by 18 % during the 2008 drought year, relative to the wettest year (2003), total blue water use decreased by only 1 %. The limited surface water supply during the driest year resulted in a 37 % increase in groundwater use, relative to the wettest year, and exceeded the sustainable abstraction rate by 53 % (55 Mm³/year). Overall, the model provides objective and quantitative outcomes that can potentially contribute to the improvement of water resource management in Mediterranean environments, in the light of climate change and expected policy reforms.     

Audio-visual speaker diarization using fisher linear semi-discriminant analysis

Speaker diarization aims to automatically answer the question “who spoke when” given a speech signal. In this work, we have focused on applying the FLsD approach, a semi-supervised version of Fisher Linear Discriminant analysis, both in the audio and the video signals to form a complete multimodal speaker diarization system. Extensive experiments have proven that the FLsD method boosts the performance of the face diarization task (i.e. the task of discovering faces over time given only the visual signal). In addition, we have proven through experimentation that applying the FLsD method for discriminating between faces is also independent of the initial feature space and remains relatively unaffected as the number of faces increases. Finally, a fusion method is proposed that leads to performance improvement in comparison to the best individual modality, which is the audio signal.     

Dependent mixtures of Dirichlet processes

An approach to modeling dependent nonparametric random density functions is presented. This is based on the well known mixture of Dirichlet process model. The idea is to use a technique for constructing dependent random variables, first used for dependent gamma random variables. While the methodology works for an arbitrary number of dependent random densities, with each pair having their own dependent structure, the mathematics and estimation algorithm is focused on two dependent random density functions. Simulations and a real data example are presented.     

Multimodal and ontology-based fusion approaches of audio and visual processing for violence detection in movies

In this paper we present our research results towards the detection of violent scenes in movies, employing advanced fusion methodologies, based on learning, knowledge representation and reasoning. Towards this goal, a multi-step approach is followed: initially, automated audio and visual analysis is performed to extract audio and visual cues. Then, two different fusion approaches are deployed: (i) a multimodal one that provides binary decisions on the existence of violence or not, employing machine learning techniques, (ii) an ontological and reasoning one, that combines the audio-visual cues with violence and multimedia ontologies. The latter reasons out not only the existence of violence or not in a video scene, but also the type of violence (fight, screams, gunshots). Both approaches are experimentally tested, validated and compared for the binary decision problem of violence detection. Finally, results for the violence type identification are presented for the ontological fusion approach. For evaluation purposes, a large dataset of real movie data has been populated.