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Innovative models for multi-territorial licensing of musical works for online use: an answer to the fragmentation problem?
No full textOnline music services (Spotify, Deezer or Apple Music) offering access to millions of songs via streaming or download have become increasingly popular with end users in Europe, who prefer having constant access to large numbers of musical works on any device. However, in order to operate on an EU-wide level, these services face a complex licensing process, resulting in high transaction costs and presenting a substantial barrier to entry for new online music services. This thesis suggests that the complex licensing process is due to the threefold fragmentation in the multi-territorial online music licensing market in Europe – territorial fragmentation, rights’ fragmentation and repertoire fragmentation. Efforts to facilitate the multi-territorial licensing process have come from both the EU legislator and the music industry. However, they benefited mainly rightholders (particularly major music publishers) but have not properly accounted for the interests of online music services as users. While these efforts have addressed the territorial fragmentation, they have neglected other forms of fragmentation and contributed to the proliferation of individual licensing and the rising number of licensing entities, thus rendering the licensing landscape more complex.
This thesis provides policy recommendations to ameliorate the impact of fragmentation on online music services and facilitate multi-territorial licensing. The past policy options and legislature are analysed in order to determine whether they can inform future solutions. Such future solutions should also be mindful of the technical challenges connected with digital music metadata administration. The suggestions in this thesis could be implemented by way of the EU Collective Rights Management Directive amendment. They are divided into two parts – measures to reduce the impact of the current fragmentation on online music services and measures to prevent future fragmentation. In order to reach these conclusions, the thesis utilises qualitative empirical research methods, doctrinal and economically-informed research, and policy analysis
Measuring the performance of government bond portfolios with index‐based level, slope, and curvature factors
No full textThis paper introduces a three-factor interest rate risk model to improve the measurement of active bond fund performance. Traditional models assume a linear relationship between risk exposure and expected returns, leading to biases. By incorporating level, slope, and curvature factors derived from Treasury index returns, the proposed model better captures the nonlinear nature of bond returns. Empirical tests on passive and active US government bond portfolios confirm its accuracy in estimating passive style returns and active alpha. The study also provides the first performance analysis of fixed-income separate accounts, revealing their economic significance and superior value-added performance over mutual funds
Classroom disruptions: impact on teachers' gaze patterns
No full textBackground
Teachers are expected to create an effective learning environment in their classroom while keeping an eye on classroom disruptions. This requires high monitoring competences as part of their noticing and professional vision. However, novice teachers often struggle dealing with critical situations and show ineffective monitoring behavior.
Aims
Using dynamic scanpath analyses, this eye-tracking study examined monitoring strategies of novice and expert teachers to understand how classroom disruptions affect teachers’ gaze behavior and what constitutes effective monitoring.
Sample
The sample consisted of 15 expert and 18 novice teachers.
Methods
Participants watched a short classroom video in which several minor and one major disruption occurred while their eye movements were recorded with an eye tracker. We analyzed their scanpaths by comparing Shannon entropy values to investigate the predictability of gaze transitions and the stability of their gaze patterns.
Results
Compared to novices, experts showed higher transition probabilities in their gaze behavior, both before and after the major disruption. Similarly, experts showed lower entropy scores, indicating more stable gaze behavior, whereas novices with higher entropy scores showed exploratory gaze behavior. In general, experts showed more adaptive monitoring strategies, returning to their routine gaze behavior more quickly than novices after an unexpected disruption.
Conclusions
This study enriches the cognitive theory of visual expertise by adding new expertise characteristics of teachers’ dynamic gaze behavior and situation-specific skills in disruptive classroom events. At the same time, the results reveal monitoring strategies that can be addressed in teacher education to enhance professional vision and classroom management
BFH: Keine Haftung des Grundstückserwerbers für unrichtige Steuerausweise in übernommenen Mietverträgen: Urteil vom 05.12.2024 - V R 16/22; BGB §§ 566, 578 UStG §§ 1c, 14c, 14 ZVG § 57 [Urteilsanmerkung]
No full text"Bist du am Ende auch gläubig geworden?": Verhandlungen des Jüdischen im Werk Auguste Hauschners
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Molecular characterization of a "severe psychosis" subgroup in the PsyCourse study [Abstract]
No full textIdentification of biological biomarkers and pathways underlying heterogeneity in disorders from the psychotic-to-affective spectrum remains a critical challenge for precision psychiatry. The PsyCourse Study (1) is a longitudinal, multicentric investigation of 1,320 individuals diagnosed with severe mental disorders, within which five clinical subgroups were previously identified based on phenotypic data (n=1,223) (2). Among these, a "severe psychosis" subgroup (n=86) exhibits the highest symptom burden and functional impairment. Here, we test the hypothesis that the probability of severe-psychosis-subgroup membership maps onto distinct molecular signatures across genomic and lipidomic layers of biology.
We first replicated the original classifier using an L2-regularized L1-loss support vector machine algorithm with end-to-end pre-processing, including dimensionality reduction, imputation, and pruning, within a nested-cross validation structure. We achieved > 95% balanced accuracy in re-assigning individuals to the five subgroups and thereby successfully replicate the original subgroup labels from (2). Array-based genotyping data (GSA v3.0, Illumina) underwent standard quality control and imputation. Polygenic risk scores (PRS) for several phenotypes, including ADHD, schizophrenia, bipolar disorder, educational attainment, plasma lipid levels, and big five personality traits were calculated based on the latest genome-wide association studies following the continuous shrinkage approach (PRS-CS) (3). Lipidomic data from untargeted liquid chromatography mass-spectrometry (LC-MS) was processed as previously described (4). From a total of 1361 identified lipid species, after excluding non-annotated lipid species, removing lipid species based on skewness and kurtosis, and removing lipids affected by fasting-status from the analysis, we obtained log-transformed intensity values for 361 lipids in n=623 individuals.
Data analysis is currently still on-going and results will be presented at the conference. First, we will evaluate each feature’s individual association with subgroup membership. For each lipid species and each PRS, we will fit a univariate linear model, controlling for sex, age, BMI and diagnosis and adjusting for multiple testing. This univariate "screen" will identify the top 20 candidate lipid species and polygenic risk scores for complex modeling. Second, we will fit a multivariate linear regression model to assess whether lipidomic and genomic data jointly predict the probability of subgroup membership. We will perform principal-component analysis on the lipid panel and PRS to reduce multicollinearity, retaining components that explain 80% of variance. Appropriate regularization strategies will be implemented to account for the high dimensionality of the model. Model tuning will be performed within a nested cross-validation framework. Performance will be evaluated with R2 and root mean squared error (RMSE) on a held-out test data fold. Features with nonzero weights will be mapped to known lipid pathways and genetic networks to contextualize molecular signatures regarding lipid metabolism and neurobiological processes.
These analyses will help test the hypothesis if molecular underpinnings of affective and non-affective psychosis transcend traditional diagnostic categories. Ultimately, delineating the biological architecture of psychosis severity could potentially open up new avenues of treatment, inform personalized treatment strategies, and improve outcomes in severe mental illness
Real-world evidence analysis of oral and long-acting injectable antipsychotic treatment patterns among patients with schizophrenia in Germany [Abstract]
No full textBackground: The pharmacological treatment landscape of schizophrenia in Germany is diverse, and comprehensive information about treatment patterns is limited. This study provides an overview of the demographics of patients with schizophrenia in Germany, alongside exploring treatment patterns of both oral antipsychotics (OAs) and long-acting injectable antipsychotics (LAIs), including discontinuation and adherence rates.
Methods: This cross-sectional, retrospective claims database study examined a prevalent schizophrenia population using the German InGef research database from January 2020 to December 2022. Adult patients with ≥1 inpatient and/or ≥2 outpatient ICD-10-GM schizophrenia diagnoses during the enrolment period (January–December 2021) and treatment with ≥1 antipsychotic in the 1-year post-index period were included. Daily estimated OA intake was calculated using the WHO Daily Defined Dose. The number of LAI injections was estimated using representative injection intervals as recommended in the package leaflets and clinical practice guidelines. Treatment discontinuation was defined as a gap of 60 days after the days of supply of the previous prescription of the initial agent without a refill. Adherence was calculated using the proportion of days covered, with high adherence defined as a score of ≥0.8.
Results: A total of 11,291 patients with schizophrenia were included. Among those meeting the inclusion criteria, 53.8% were male, and the average age was 52.1 (± 16.9) years. As a first observable prescription during the post-index period, 68.9% were prescribed 1 OA, 10.7% received 1 LAI and among those with combination therapy on the same day, 18.5% had ≥2 OAs, 0.05% had ≥2 LAIs and 1.87% had ≥1 OA and LAI.
The final cohort comprised 8238 patients who received 1 antipsychotic drug, defined as the index agent, that was also prescribed to ≥100 patients. Olanzapine, risperidone, quetiapine and aripiprazole were the most commonly prescribed OAs (17.7%, 16.8%, 15.2% and 11.6%, respectively), while paliperidone, aripiprazole, flupentixol and risperidone were the most commonly prescribed LAIs (5.7%, 2.3%, 2.1% and 1.8%, respectively).
Patients prescribed LAIs showed lower treatment discontinuation rates compared to those prescribed OAs (18–27% vs 26–75%). Patients prescribed LAIs remained on treatment for longer on average until discontinuation than patients receiving OAs (144–191 days vs 106–163 days). Among OAs, olanzapine (n=1457) and ziprasidone (n=100) had the lowest proportion of discontinuations (36% and 26%, respectively), with patients treated with olanzapine, ziprasidone and aripiprazole remaining on treatment the longest (163, 162 and 155 days, respectively). The proportions of treatment switches to different molecules for patients on OAs and LAIs were relatively comparable (5–32% and 6–14%, respectively). Overall, a greater proportion of patients prescribed LAIs demonstrated high adherence, compared to OAs (39–52% vs 0–46%). Among OAs, more patients prescribed ziprasidone and olanzapine demonstrated high adherence (46% and 33%, respectively) compared to other OAs.
Conclusions: In this dataset from Germany, LAIs are less commonly prescribed than OAs, despite demonstrating better adherence and discontinuation outcomes. These findings are consistent with previous literature [1]. However, within OAs, some molecules exhibit more favourable outcomes than others
