Taxation of E-Commerce: Persistent Problems and Recent Developments

E-Commerce über das Internet bedeutet neue Herausforderungen für die Besteuerung. Im Bereich der Einkommens- und Unternehmensbesteuerung entsteht ein großes Potential zur Verlagerung von Einkünften in Niedrigsteuerländer, insbesondere durch Gestaltung von Verrechnungspreisen und durch Übertragung von immateriellen Wirtschaftsgütern. Längerfristig sind dadurch erhebliche Steuerausfälle zu befürchten. Bei der Umsatzsteuer (Mehrwertsteuer) entstehen Probleme, wenn ausländische Anbieter an inländische Endverbraucher elektronische Produkte oder Dienstleistungen online verkaufen. Die Mehrwertsteuer sollte in dem Land erhoben werden, wo der Verbrauch stattfindet, was gegenwärtig nicht der Fall ist, andernfalls drohen Wettbewerbsverfälschungen und ungerechte Steuerbelastungen. Dies erfordert besondere technische Lösungen sowie eine verstärkte internationale Kooperation der Finanzbehörden. Grundsätzlich sollte der e-commerce nicht steuerlich privilegiert werden, sondern sich aufgrund seiner spezifischen Wettbewerbsvorteile durchsetzen, andererseits sollte er aber auch nicht durch aufwendige steuertechnische Anforderungen behindert werden

Behavioural activation by mental health nurses for late-life depression in primary care: a randomized controlled trial

Background: Depressive symptoms are common in older adults. The effectiveness of pharmacological treatments and the availability of psychological treatments in primary care are limited. A behavioural approach to depression treatment might be beneficial to many older adults but such care is still largely unavailable. Behavioural Activation (BA) protocols are less complicated and more easy to train than other psychological therapies, making them very suitable for delivery by less specialised therapists. The recent introduction of the mental health nurse in primary care centres in the Netherlands has created major opportunities for improving the accessibility of psychological treatments for late-life depression in primary care. BA may thus address the needs of older patients while improving treatment outcome and lowering costs.The primary objective of this study is to compare the effectiveness and cost-effectiveness of BA in comparison with treatment as usual (TAU) for late-life depression in Dutch primary care. A secondary goal is to explore several potential mechanisms of change, as well as predictors and moderators of treatment outcome of BA for late-life depression. Methods/design: Cluster-randomised controlled multicentre trial with two parallel groups: a) behavioural activation, and b) treatment as usual, conducted in primary care centres with a follow-up of 52 weeks. The main inclusion criterion is a PHQ-9 score > 9. Patients are excluded from the trial in case of severe mental illness that requires specialized treatment, high suicide risk, drug and/or alcohol abuse, prior psychotherapy, change in dosage or type of prescribed antidepressants in the previous 12 weeks, or moderate to severe cognitive impairment. The intervention consists of 8 weekly 30-min BA sessions delivered by a trained mental health nurse. Discussion: We expect BA to be an effective and cost-effective treatment for late-life depression compared to TAU. BA delivered by mental health nurses could increase the availability and accessibility of non-pharmacological treatments for late-life depression in primary care. Trial registration: This study is retrospectively registered in the Dutch Clinical Trial Register NTR6013on August 25th 2016. © 2017 The Author(s)

Keine Angst vor dem Blackout : Ein dezentral organisierter Schwarzstart ist machbar!

[no abstract available

Telomerase-pulsed dendritic cells: preclinical results and outcome of a clinical phase I/II trial in patients with metastatic renal cell carcinoma

Objective: Therapeutic vaccination with dendritic cells (DC) showed promising results in first clinical trials in cases of metastatic renal cell carcinoma (RCC). Human telomerase reverse transcriptase (hTERT) could be a potential target because it is detectable in more than 85% of human tumors including RCC

TLR2 Mediates Recognition of Live Staphylococcus epidermidis and Clearance of Bacteremia

Background: Staphylococcus epidermidis (SE) is a nosocomial pathogen that causes catheter-associated bacteremia in the immunocompromised, including those at the extremes of age, motivating study of host clearance mechanisms. SE-derived soluble components engage TLR2; but additional signaling pathways have also been implicated, and TLR2 can play complex, at times detrimental, roles in host defense against other Staphylococcal spp. The role of TLR2 in responses of primary blood leukocytes to live SE and in clearance of SE bacteremia, the most common clinical manifestation of SE infection, is unknown. Methodology/Principal Findings: We studied TLR2-mediated recognition of live clinical SE strain 1457 employing TLR2- transfected cells, neutralizing anti-TLR antibodies and TLR2-deficient mice. TLR2 mediated SE-induced cytokine production in human embryonic kidney cells, human whole blood and murine primary macrophages, in part via recognition of a soluble TLR2 agonist. After i.v. challenge with SE, early (1 h) cytokine/chemokine production and subsequent clearance of bacteremia (24-48 h) were markedly impaired in TLR2-deficient mice. Conclusions/Significance: TLR2 mediates recognition of live SE and clearance of SE bacteremia in vivo

Active matrix-based pressure sensor system with a 4 × 16 printed decoder designed with a flexible hybrid organic process design kit

The innovative field of printed sensor with a demand for high accuracy, sensitivity and durability has enabled a wide application area in sensing, healthcare etc. A large-area printed sensor system on a flexible foil substrate emplying p-type organic field-effect transistors (OFETs) is presented. Thereby, the OFET is fabricated through a hybrid manufacturing process, including photolithographically structured source- and drain-electrodes, ink-jet printed organic semiconductor, and spin-coated dielectric. Moreover, a dedicated device model, derived from the variable range hopping model, is developed and integrated together with process related design rules, materials properties and geometric information into a comprehensive process design kit (FH_OPDK). The FH_OPDK is integrated in a commercial electronic design automation tool and is used to design and perform post-layout simulations on logic gates, such as INV, NAND2, and NOR2 as well as circuitry such as ring oscillators and a 4 × 16 digital decoder. Several circuit topologies have been tested and evaluated in a detailed model-hardware correlation analysis. Finally we have optimized logic gates and the decoder in a PMOS only, pseudo CMOS design style. To demonstrate the feasibility of the full sensor system in hardware a 16 × 16 active matrix pressure sensor on a flexible substrate integrated with a 4 × 16 binary decoder was fabricated and tested. We have integrated our flexible hybrid sensor system with a PCB board and a microcontroller to demonstrate the hardware readout platform capable of detecting the weight of objects and visualizing a digital map of applied forces

Linking pharmacy dispensing data to other administrative health datasets to measure the compliance and effectiveness of RSV immunoprophylaxis

Introduction Respiratory Syncytial Virus (RSV) causes considerable morbidity in children. RSV vaccines are in development, but the only current preventive measure is immunoprophylaxis with monoclonal antibody, palivizumab. Australia has no uniform palivizumab guidelines. In Western Australia palivizumab is licensed for use in high risk children but compliance and effectiveness is unknown. Objectives and Approach We conducted a retrospective cohort study using palivizumab data from multiple pharmacy dispensing datasets which had been linked with routine laboratory, hospital morbidity, emergency department presentations, deaths and perinatal data for a cohort of infants admitted to Level 3 Neonatal Intensive Care Units (NICU) between 2002 and 2013. We identified palivizumab eligible infants as those who were extremely premature (<28 weeks gestation) with bronchopulmonary dysplasia and/or who identified as Indigenous and were NICU inpatients during the annual winter RSV season (May-October). We describe the use of palivizumab in infants that did and did not fit the eligibility criteria. Results The NICU cohort included 24,367 infants, of which 1754 had at least 1 RSV-confirmed infection before age 5 years. A total of 686 (2.8%) cohort infants were eligible for palivizumab. Palivizumab dispensing data were amalgamated from 5 pharmacy datasets. Overall, 173 of the palivizumab eligible infants (25.2%) had at least 1 palivizumab dose (27% 1 dose, 34% 2 doses, 28% 3 doses and 11% 4 or more doses). From 2011 when palivizumab guidelines were formalised, 143 (75%) had at least 1 dose. Compliance with at least 1 palivizumab dose was highest in 2011 (84.9%). From 2002-2013, 98 infants were given palivizumab outside eligibility criteria (33% 1 dose, 33% 2 doses, 34% 3 or more doses) with annual use increasing since 2008. Conclusion/Implications This is the first time pharmacy dispensing data have been linked to other datasets to measure use and effectiveness. Compliance with palivizumab guidelines was high from 2011. These data will be used to measure the effectiveness of palivizumab against RSV-confirmed infections and respiratory infection-related hospitalisations up to age 5 years

Model-Assisted Forest Yield Estimation with Light Detection and Ranging

Previous studies have demonstrated that light detection and ranging (LiDAR)-derived variables can be used to model forest yield variables, such as biomass, volume, and number of stems. However, the next step is underrepresented in the literature: estimation of forest yield with appropriate confidence intervals. It is of great importance that the procedures required for conducting forest inventory with LiDAR and the estimation precision of such procedures are sufficiently documented to enable their evaluation and implementation by land managers. In this study, we demonstrated the regression estimator, a model-assisted estimator (approximately design-unbiased), using LiDAR-derived variables for estimation of total forest yield. The LiDAR-derived variables are statistics associated with vegetation height and cover. The estimation procedure requires complete coverage of the forest with LiDAR and a random sample of precisely georeferenced field measurement plots. Regression estimation relies on sample-based ordinary least squares (OLS) regression models relating forest yield and LiDAR-derived variables. Estimation was performed using the OLS models and LiDAR-derived variables for the entire population. Regression estimates of basal area, volume, stand density, and biomass were much more precise than simple random sampling estimates (design effects were 0.25, 0.24, 0.44, and 0.27, respectively).Keywords: Model-assisted, Regression estimation, Design-based LiDAR, Forest Inventor