177 research outputs found
Maternal health development programs : comparing priorities of bilateral and private donors
Background: The face of international aid for health and development is changing. Private donors such as foundations and corporations are playing an increasingly important role, working in international development as direct operators or in partnerships with governments. This study compares maternal health programs of new development actors to traditional governmental donors. It aims to investigate what maternal health programs large governmental donors, foundations and corporate donors are conducting, and how and why they differ.
Methods: A total of 263 projects were identified and analyzed. We focus on nine categories of maternal health programs: family planning services, focus on specific diseases, focus on capacity building, use of information and communication technology (ICT), support of research initiatives, cooperation with local non-state or state partners and cooperation with non-local non-state or state partners. Data analysis was carried out using Generalized Linear Mixed-Effects Models (GLMER).
Results: Maternal health policies of public and private donors differ with regard to strategic approaches, as can be seen in their diverging positions regarding disease focus, family planning services, capacity building, and partner choice. Bilateral donors can be characterized as focusing on family planning services, specific diseases and capacity-building while disregarding research and ICT. Bilateral donors cooperate with local public authorities and with governments and NGOs from other developed countries. In contrast, corporations focus their donor activities on specific diseases, capacity-building and ICT while disregarding family planning services and research. Corporations cooperate with local and in particular with non-local non-state actors. Foundations can be characterized as focusing on family planning services and research, while disregarding specific diseases, capacity-building and ICT. Foundations cooperate less than other donors; but when they do, they cooperate in particular with non-state actors, local as well as non-local.
Conclusions: These findings should help developing coordination mechanisms that embrace the differences and similarities of the different types of donors. As donor groups specialize in different contexts, NGOs and governments working on development and health aid may target donors groups that have specialized in certain issues
La ecología política de las asociaciones empresariales españolas en el sector de la información y las comunicaciones
This article is about the multi-faceted adaptation processes of business associations caused by changes in their politico-economic environments. It is argued that technological innovations, accompanied by high economic growth rates have led to the establishment of new business associations in the information and communications sector. The incorporation of these newly founded associations into existing structures of interest representation is mediated by the inclusiveness of membership in national peak associations. It is argued that the Spanish peak association CEOE has adopted a generous stance towards the inclusion of new affiliations thereby facilitation the consolidation of the newly developed system of organized business interests.Este artículo analiza los procesos reforma y adaptación de las asociaciones empresariales españolas provocados por los cambios en el entorno político y económico. Las innovaciones tecnológicas, junto con un fuerte ritmo de crecimiento muy elevado, ha dado lugar al surgimiento de nuevos tipos de asociaciones empresariales en el sector de la información y comunicación. La incorporación de estas nuevas asociaciones en las estructuras de representación de intereses tradicionales se caracteriza, principalmente, por la escasa inclusión en las asociaciones nacionales más importantes. No obstante, en el caso de España, la CEOE ha adoptado una posición que favorece esta inclusión, facilitando así la consolidación de los mecanismos de representación de intereses más recientes
Aminophthalimide as a mimetic of purines and a fluorescent RNA base surrogate for RNA imaging
Die Digitalisierung von Verwaltungsleistungen : die Auswirkungen auf die Bearbeitungszeit am Beispiel des eUmzugCH
Durch die Einführung von eUmzugCH wurde der Umzugsprozess für meldepflichtige Personen in der Schweiz digitalisiert. Die Einwohnerinnen und Einwohner sind nicht mehr auf die begrenzten Öffnungszeiten der Verwaltungen angewiesen, um ihren Zu-, Weg- oder Umzug zu melden. Durch eUmzugCH sollen Zuzüge verwaltungsintern effizienter abgewickelt werden können.
Diese Studie soll Aufschluss darüber geben, inwiefern die Einführung von eUmzugCH den Arbeitsaufwand der Einwohnerkontrolle beeinflusst.
Es wurden insgesamt vier Einwohnerkontrollen ausgewählt, bei welchen die Ausführungen von Anmeldungen von meldepflichtigen Personen am Schalter oder über eUmzugCH zu einer der Haupttätigkeiten gehört und bei welchen die Ausführung dieses Prozesses ähnlich häufig durchgeführt wird. Für die Datenerhebung wurde das Laufzettelverfahren angewendet, mit dem die Prozesszeiten bei der Bearbeitung des eUmzugs und am Schalter erhoben werden können. Die Datenanalyse wurde unter Verwendung von LMER (Linear Mixed-Effects Models) durchgeführt.
Die Auswertung der Daten des Laufzettelverfahrens in vier Gemeinden im Kanton Zürich zeigt, dass die Einführung von eUmzugCH zu einer Reduktion des verwaltungsseitigen Arbeitsaufwands im Vergleich zu den Schalteranmeldungen von eUmzugCH führt. Es ist deutlich erkennbar, dass die Arbeitsausführung von Zuzügen über eUmzugCH von den Mitarbeitenden der Einwohnerkontrolle effizienter und schneller abgewickelt werden kann. Wie die Auswertungen der methodischen Erhebung zeigen, sind auch die Verzögerungen, die durch fehlende Unterlagen entstehen, bei den Zuzügen über eUmzugCH geringer. Die Einführung von eUmzugCH hat daher eine positive Auswirkung auf den Arbeitsaufwand der Einwohnerkontrolle
The fog of fraud - how to reduce insurance fraud
Abstract Most insurance companies publish few data on the occurrence and detection of insurance fraud, although the credible announcement of thoroughly auditing claim reports might act as a powerful deterrence. We show that uncertainty about fraud detection may be an effective strategy to deter ambiguity averse agents from reporting false insurance claims. As committing to a fraud detection strategy eliminates this uncertainty, it might be optimal not to commit and abstain from publishing data on fraud detection. JEL classifications: D8, K
Bevölkerungsumfrage in der Schweiz, Deutschland und Österreich zur nationalen Contact Tracing-App : eine Studie des Instituts für Verwaltungsmanagement der ZHAW
Circular Regression Trees and Forests with an Application to Probabilistic Wind Direction Forecasting
While circular data occur in a wide range of scientific fields, the
methodology for distributional modeling and probabilistic forecasting of
circular response variables is rather limited. Most of the existing methods are
built on the framework of generalized linear and additive models, which are
often challenging to optimize and to interpret. Therefore, we suggest circular
regression trees and random forests as an intuitive alternative approach that
is relatively easy to fit. Building on previous ideas for trees modeling
circular means, we suggest a distributional approach for both trees and forests
yielding probabilistic forecasts based on the von Mises distribution. The
resulting tree-based models simplify the estimation process by using the
available covariates for partitioning the data into sufficiently homogeneous
subgroups so that a simple von Mises distribution without further covariates
can be fitted to the circular response in each subgroup. These circular
regression trees are straightforward to interpret, can capture nonlinear
effects and interactions, and automatically select the relevant covariates that
are associated with either location and/or scale changes in the von Mises
distribution. Combining an ensemble of circular regression trees to a circular
regression forest yields a local adaptive likelihood estimator for the von
Mises distribution that can regularize and smooth the covariate effects. The
new methods are evaluated in a case study on probabilistic wind direction
forecasting at two Austrian airports, considering other common approaches as a
benchmark
Remember the past: a comparison of time-adaptive training schemes for non-homogeneous regression
Non-homogeneous regression is a frequently used post-processing method for increasing the predictive skill of probabilistic ensemble weather forecasts. To adjust for seasonally varying error characteristics between ensemble forecasts and corresponding observations, different timeadaptive training schemes, including the classical sliding training window, have been developed for non-homogeneous regression. This study compares three such training approaches with the sliding-window approach for the application of post-processing near-surface air temperature forecasts across central Europe. The predictive performance is evaluated conditional on three different groups of stations located in plains, in mountain foreland, and within mountainous terrain, as well as on a specific change in the ensemble forecast system of the European Centre for Medium-Range Weather Forecasts (ECMWF) used as input for the post-processing. The results show that time-adaptive training schemes using data over multiple years stabilize the temporal evolution of the coefficient estimates, yielding an increased predictive performance for all station types tested compared to the classical sliding-window approach based on the most recent days only. While this may not be surprising under fully stable model conditions, it is shown that “remembering the past” from multiple years of training data is typically also superior to the classical sliding-window approach when the ensemble prediction system is affected by certain model changes. Thus, reducing the variance of the non-homogeneous regression estimates due to increased training data appears to be more important than reducing its bias by adapting rapidly to the most current training data only
Tackling tumour cell heterogeneity at the super-resolution level in human colorectal cancer tissue
Tumour cell heterogeneity, and its early individual diagnosis, is one of the most fundamental problems in cancer diagnosis and therapy. Single molecule localisation microscopy (SMLM) resolves subcellular features but has been limited to cultured cell lines only. Since nuclear chromatin architecture and microRNAs are critical in metastasis, we introduce a first-in-field approach for quantitative SMLM-analysis of chromatin nanostructure in individual cells in resected, routine-pathology colorectal carcinoma (CRC) patient tissue sections. Chromatin density profiles proved to differ for cells in normal and carcinoma colorectal tissues. In tumour sections, nuclear size and chromatin compaction percentages were significantly different in carcinoma versus normal epithelial and other cells of colorectal tissue. SMLM analysis in nuclei from normal colorectal tissue revealed abrupt changes in chromatin density profiles at the nanoscale, features not detected by conventional widefield microscopy. SMLM for microRNAs relevant for metastasis was achieved in colorectal cancer tissue at the nuclear level. Super-resolution microscopy with quantitative image evaluation algorithms provide powerful tools to analyse chromatin nanostructure and microRNAs of individual cells from normal and tumour tissue at the nanoscale. Our new perspectives improve the differential diagnosis of normal and (metastatically relevant) tumour cells at the single-cell level within the heterogeneity of primary tumours of patients
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