4,948 research outputs found
Long-term outcome of ten children with opsoclonus-myoclonus syndrome
Opsoclonus-myoclonus syndrome (OMS) in children is a rare neurological condition with opsoclonus, myoclonus, ataxia and irritability in the first 2 years of life. It can be idiopathic, parainfectious, or paraneoplastic with tumours of the neural crest. Few studies of long-term follow-up after OMS have been published. We investigated the motor, cognitive and behavioural outcome of ten patients (eight girls and two boys) seen between 1987 and 2002. We reviewed the records and reassessed the patients. A ganglioneuroma was found in one patient and a neuroblastoma in another. Tumour resection did not influence the OMS. The age at diagnosis was 10-24months and the follow-up period 1-17years (average 6.5years). The interval between the first signs and symptoms and starting treatment was 2-12weeks: treatment consisted of different immunosupressants. Remission was achieved within 5months in seven, and relapses were present in seven of ten. At follow-up, only one child had mild ataxia. IQ testing was performed in nine with scores below 75 in four and above 85 in four. Attention deficit and visuomotor difficulties led to school problems with special needs, also in those three children with normal IQs. Only two children were attending regular schools. Behavioural problems were reported in seven, and speech difficulties were present in five. In conclusion, the long-term outcome in our patients with OMS was dominated by cognitive and behavioural problems and not by ataxia. Compared with previous reports, our patients were treated earlier. Larger studies and uniform treatment protocols are needed to demonstrate whether early and prolonged immunosupressant therapy has a favourable influence on outcom
Good corporate social performance may lead to higher credit ratings
But only for firms whose countries share the same values, find Christian Klein, Christoph Stellner and Bernhard Zwerge
Approximating Intersections and Differences Between Linear Statistical Shape Models Using Markov Chain Monte Carlo
To date, the comparison of Statistical Shape Models (SSMs) is often solely
performance-based, carried out by means of simplistic metrics such as
compactness, generalization, or specificity. Any similarities or differences
between the actual shape spaces can neither be visualized nor quantified. In
this paper, we present a new method to qualitatively compare two linear SSMs in
dense correspondence by computing approximate intersection spaces and
set-theoretic differences between the (hyper-ellipsoidal) allowable shape
domains spanned by the models. To this end, we approximate the distribution of
shapes lying in the intersection space using Markov chain Monte Carlo and
subsequently apply Principal Component Analysis (PCA) to the posterior samples,
eventually yielding a new SSM of the intersection space. We estimate
differences between linear SSMs in a similar manner; here, however, the
resulting spaces are no longer convex and we do not apply PCA but instead use
the posterior samples for visualization. We showcase the proposed algorithm
qualitatively by computing and analyzing intersection spaces and differences
between publicly available face models, focusing on gender-specific male and
female as well as identity and expression models. Our quantitative evaluation
based on SSMs built from synthetic and real-world data sets provides detailed
evidence that the introduced method is able to recover ground-truth
intersection spaces and differences accurately.Comment: Accepted to WACV'2
On the Non-Associativity of Analog Computations
The energy efficiency of analog forms of computing makes it one of the most
promising candidates to deploy resource-hungry machine learning tasks on
resource-constrained system such as mobile or embedded devices. However, it is
well known that for analog computations the safety net of discretization is
missing, thus all analog computations are exposed to a variety of imperfections
of corresponding implementations. Examples include non-linearities, saturation
effect and various forms of noise. In this work, we observe that the ordering
of input operands of an analog operation also has an impact on the output
result, which essentially makes analog computations non-associative, even
though the underlying operation might be mathematically associative. We conduct
a simple test by creating a model of a real analog processor which captures
such ordering effects. With this model we assess the importance of ordering by
comparing the test accuracy of a neural network for keyword spotting, which is
trained based either on an ordered model, on a non-ordered variant, and on real
hardware. The results prove the existence of ordering effects as well as their
high impact, as neglecting ordering results in substantial accuracy drops.Comment: Published at the ECML PKDD Conference 2023, at the 4th Workshop on
IoT, Edge, and Mobile for Embedded Machine Learnin
Individual investment advice is key for sustainable investment behaviour
Given the global environmental and societal challenges of the 21st century, the concept of sustainability is becoming increasingly important in the financial markets. It seems necessary to involve private individuals in the transition to a sustainable economy. However, investment preferences are very heterogeneous, so that investment products customised to "averaged" preferences often fail to achieve the goal of promoting sustainable [...
Computational Urban Planning: Using the Value Lab as Control Center
Urban planning involves many aspects and various disciplines, demanding an asynchronous planning approach. The level of complexity rises with each aspect to be considered and makes it difficult to find universally satisfactory solutions. To improve this situation we propose a new approach, which complement traditional design methods with a computational urban plan- ning method that can fulfil formalizable design requirements automatically. Based on this approach we present a design space exploration framework for complex urban planning projects. For a better understanding of the idea of design space exploration, we introduce the concept of a digital scout which guides planners through the design space and assists them in their creative explorations. The scout can support planners during manual design by informing them about potential im- pacts or by suggesting different solutions that fulfill predefined quality requirements. The planner can change flexibly between a manually controlled and a completely automated design process. The developed system is presented using an exemplary urban planning scenario on two levels from the street layout to the placement of building volumes. Based on Self-Organizing Maps we implemented a method which makes it possible to visualize the multi-dimensional solution space in an easily analysable and comprehensible form
Einflussfaktoren auf die Wahl einer Markteintrittsstrategie: Eine meta-analytische Untersuchung der Entscheidung zwischen Tochtergesellschaft und Kooperation
Zusammenfassung: Die Wahl einer Markteintrittsstrategie, eine der wichtigsten Entscheidungen im Kontext der Internationalisierung, wurde in zahlreichen empirischen Untersuchungen analysiert. Die vorliegenden Ergebnisse sind vielfältig, teilweise kontrovers und nur noch schwer zu überschauen. In der vorliegenden Meta-Analyse werden empirische Ergebnisse zur Entscheidung zwischen den Alternativen Tochtergesellschaft und Kooperation integriert. Auf Basis von 61 empirischen Untersuchungen wird analysiert, welche Einflussfaktoren auf die Entscheidung bislang betrachtet wurden und welche bei der Kombination der bisherigen Studienergebnisse einen signifikanten Einfluss aufweisen. Zugleich wird ein Bezug zu unterschiedlichen theoretischen Ansätzen, welche einen Erklärungsbeitrag zur Wahl der Markteintrittsentscheidung liefern, hergestellt. Als Ergebnisse können zusammenfassend signifikante Einflüsse der Mitarbeiterzahl des Unternehmens, der Machtabstandstoleranz im Stammland, der landesspezifischen internationalen Erfahrung, der Werbe- und Exportintensität, der internationalen Produktdiversifikation, des Marktwachstums, der Ressourcen-Intensität der Auslandseinheit, der Marktgröße, der staatlichen Restriktionen im Gastland und des Länderrisikos festgestellt werden. Nicht-signifikante Ergebnisse werden für eine Vielzahl von Variablen erzielt, so für die Faktorspezifität, die F&E-Intensität, die Größe der Tochtergesellschaft, das Vermögen und den Umsatz des Unternehmen
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