Perinatal Hypoxic-Ischemic Encephalopathy

Perinatal hypoxic-ischemic encephalopathy (HIE) is an important cause of brain injury in the newborn and can result in long-term devastating consequences. Perinatal hypoxia is a vital cause of long-term neurologic complications varying from mild behavioural deficits to severe seizure, mental retardation, and/or cerebral palsy in the newborn. In the mammalian developing brain, ongoing research into pathophysiological mechanism of neuronal injury and therapeutic strategy after perinatal hypoxia is still limited. With the advent of promising therapy of hypothermia in HIE, this paper reviews the pathophysiology of HIE and the future potential neuroprotective strategies for clinical potential for hypoxia sufferers

Abstraction models at system level for networked interactive multimedia scripting

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (p. 85-86).by Jimmy Chi-Ming Lai.M.Eng

Distributed Indexing Schemes for k-Dominant Skyline Analytics on Uncertain Edge-IoT Data

Skyline queries typically search a Pareto-optimal set from a given data set to solve the corresponding multiobjective optimization problem. As the number of criteria increases, the skyline presumes excessive data items, which yield a meaningless result. To address this curse of dimensionality, we proposed a k-dominant skyline in which the number of skyline members was reduced by relaxing the restriction on the number of dimensions, considering the uncertainty of data. Specifically, each data item was associated with a probability of appearance, which represented the probability of becoming a member of the k-dominant skyline. As data items appear continuously in data streams, the corresponding k-dominant skyline may vary with time. Therefore, an effective and rapid mechanism of updating the k-dominant skyline becomes crucial. Herein, we proposed two time-efficient schemes, Middle Indexing (MI) and All Indexing (AI), for k-dominant skyline in distributed edge-computing environments, where irrelevant data items can be effectively excluded from the compute to reduce the processing duration. Furthermore, the proposed schemes were validated with extensive experimental simulations. The experimental results demonstrated that the proposed MI and AI schemes reduced the computation time by approximately 13% and 56%, respectively, compared with the existing method.Comment: 13 pages, 8 figures, 12 tables, to appear in IEEE Transactions on Emerging Topics in Computin

Gaussian process machine learning-based surface extrapolation method for improvement of the edge effect in surface filtering

Filtering for signal and data is an important technology to reduce and/or remove noise signal for further extraction of desired information. However, it is well known that significant distortions may occur in the boundary areas of the filtered data because there is no sufficient data to be processed. This drawback largely affects the accuracy of topographic measurements and characterizations of precision freeform surfaces, such as freeform optics. To address this issue, a Gaussian process machine learning-based method is presented for extrapolation of the measured surface to an extended measurement area with high accuracy prior to filtering the surface. With the extrapolated data, the edge distortion can be effectively reduced. The effectiveness of this method was evaluated using both simulated and experimental data. Successful implementation of the proposed method not only addresses the issue in surface filtering but also provides a promising solution for numerous applications involving filtering processes

Interaction-induced first order correlation between spatially-separated 1D dipolar fermions

We calculate the ground-state properties of fermionic dipolar atoms or molecules in a one-dimensional double-tube potential by using the Luttinger liquid theory and the density matrix renormalization-group calculation. When the external field is applied near a magic angle with respect to the double-tube plane, the long-ranged dipolar interaction can generate a spontaneous correlation between fermions in different tubes, even when the bare intertube tunneling rate is negligibly small. Such interaction-induced correlation strongly enhances the contrast of the interference fringes and therefore can be easily observed in the standard time-of-flight experiment.Comment: Same as the published versio

Shares in the EMCA : the time is ripe for true no par value shares in the EU, and the 2nd directive is not an obstacle

The most interesting proposal in the draft European Model Companies Act ( EMCA) concerning shares and the focus of this Article is the recommendation to introduce true no par value shares, as they have been in use in the US for many years and were introduced in Australia, New Zealand but also Finland more recently. Contrary to what has often been assumed, the 2nd EU Company Law Directive does not preclude no par value shares. There is nothing in the wording of the Directive to suggest otherwise, and the reference in the Directive to shares without a nominal value is a reference to Belgian law, which has allowed true no par value shares in all but name since at least 1913. EU member states could therefore introduce such shares even for public companies. True no par value shares offer a far more flexible framework in case of capital increases or mergers, but since under a no par value system there is no link between par value and shareholder rights, additional disclosure about these rights might be warranted under a no par value system. Traditional par value shares offer no protection to creditors, shareholders or other stakeholders, so that their abolition should not be mourned. The threat of new share issues at an unacceptably high discount is more efficiently countered by disclosure and shareholder decision rights

Energy saving evaluation of the ventilated BIPV walls."

ABSTRACT This study integrates photovoltaic (PV) system, building structure, and heat flow mechanism to propose the ventilated building-integrated photovoltaics (BIPV) walls. Energy-saving potential of the ventilated BIPV walls was investigated via engineering considerations and computational fluid dynamics (CFD) simulations. The results show that the heat removal rate and indoor heat gain of the proposed ventilated BIPV walls were dominantly affected by outdoor wind velocity and airflow channel width. Correlations for predicting the heat removal rate and indoor heat gain are introduced. After considering building construction practices, this prototype was transformed into a curtain wall structure that complemented the design of the overall construction