The biotech venture market faces intense capital demands and regulatory scrutiny, yet academic research on VC networks remains rooted in software and consumer-tech contexts. This dissertation investigates how repeated co-investment ties and domain-expertise homophily influence a venture's exit likelihood, timing, and route amid the sector's pronounced technological and market uncertainty. Using a novel panel of 11,680 biotechnology start-ups from the United States, Canada, and Europe (2010-2024), we apply pooled logit, Cox proportional-hazards, multinomial logit, and Fine-Gray competing-risk models. Our findings show that both average prior co-investment and investor homophily exhibit robust inverted-U relationships with exit outcomes. Moderate familiarity and scientific overlap maximize exit probability, while either sparse or excessive embedding reduces success. Governance mechanisms also play a crucial role: participation of a pharmaceutical corporate VC or a highly independent board flattens the negative effects of over-embedding, enabling syndicates to sustain exit momentum at higher levels of familiarity or homogeneity. Furthermore, the optimal degree of embeddedness is route
Large language models (LLMs) are deep learning algorithms being used to perform natural language processing tasks in various fields, from social sciences to finance and biomedical sciences. Developing and training a new LLM can be very computationally expensive, so it is becoming a common practice to take existing LLMs and finetune them with carefully curated datasets for desired applications in different fields. Here, we present BioFinBERT, a finetuned LLM to perform financial sentiment analysis of public text associated with stocks of companies in the biotechnology sector. The stocks of biotech companies developing highly innovative and risky therapeutic drugs tend to respond very positively or negatively upon a successful or failed clinical readout or regulatory approval of their drug, respectively. These clinical or regulatory results are disclosed by the biotech companies via press releases, which are followed by a significant stock response in many cases. In our attempt to design a LLM capable of analyzing the sentiment of these press releases,we first finetuned BioBERT, a biomedical language representation model designed for biomedical text mining, using financial textual da
Biotechnologies are being commercialized at historic rates. In 2020, 74 biotech startups went public through an Initial Public Offering (IPO), and 60 went through the IPO process in the first six months of 2021. However, the traits associated with biotech startups obtaining recent IPOs have not been reported. Here we build a database of biotechs that underwent an IPO in the first half of 2021. By analyzing leadership, technological focus, clinical trials, and financing, we found that advanced degrees among the leadership, clinical trials, and intellectual property are important factors for biotech startups. The data also suggest that large private rounds can decrease time-to-IPO and affect post-IPO stock performance. Notably, these traits were often exhibited by the 138 biotech IPOs in 2018-2019, suggesting 2021 data were not driven by COVID.
Patents serve as valuable indicators of innovation and provide insights into the spaces of innovation and venture formation within geographic regions. In this study, we utilise patent data to examine the dynamics of innovation and venture formation in the biotech sector across the United Kingdom (UK). By analysing patents, we identify key regions that drive biotech innovation in the UK. Our findings highlight the crucial role of biotech incubators in facilitating knowledge exchange between scientific research and industry. However, we observe that the incubators themselves do not significantly contribute to the diversity of innovations which might be due to the underlying effect of geographic proximity on the influences and impact of the patents. These insights contribute to our understanding of the historical development and future prospects of the biotech sector in the UK, emphasising the importance of promoting innovation diversity and fostering inclusive enterprise for achieving equitable economic growth.
This study investigates the relationship between tweet sentiment across diverse categories: news, company opinions, CEO opinions, competitor opinions, and stock market behavior in the biotechnology sector, with a focus on understanding the impact of social media discourse on investor sentiment and decision-making processes. We analyzed historical stock market data for ten of the largest and most influential pharmaceutical companies alongside Twitter data related to COVID-19, vaccines, the companies, and their respective CEOs. Using VADER sentiment analysis, we examined the sentiment scores of tweets and assessed their relationships with stock market performance. We employed ARIMA (AutoRegressive Integrated Moving Average) and VAR (Vector AutoRegression) models to forecast stock market performance, incorporating sentiment covariates to improve predictions. Our findings revealed a complex interplay between tweet sentiment, news, biotech companies, their CEOs, and stock market performance, emphasizing the importance of considering diverse factors when modeling and predicting stock prices. This study provides valuable insights into the influence of social media on the financial sector
Residential electricity profiles are undergoing significant changes due to the increasing adoption of distributed renewable generation, heat pumps, and electric vehicles. Up-to-date real-world measurements are essential for characterizing these evolving consumption patterns and providing a timely empirical foundation for research. This paper presents a dataset of 15-minute smart meter measurements from 2,447 residential installations in Switzerland, covering the years 2023 and 2024. The dataset encompasses both active and reactive energy (withdrawal and injection) of diverse installation types, including apartments, single-family houses, heat pumps, and common building areas. A subset of the associated customers participated in a pilot project featuring novel grid tariffs and automated load control. The corresponding price profiles and metadata are also included. The dataset aims to support research focusing on distribution grid modeling, load forecasting, and the assessment of time-varying tariffs.
We present an astonishingly simple and elegant proof of the celebrated Basel problem.
Science and technology systems - and their epistemic communities - are usually hierarchical and composed of a number of strong, large, leading organizations, along with a number of smaller and less influential ones. Moreover, these hierarchical patterns have a spatial structure: the leading organizations are concentrated in a few places, creating a science and technology center, whereas the majority of locations are peripheral. In the example of biotech research in China, we found dynamic changes in center-periphery patterns. These results are based on a network analysis of evolving co-authorship networks from 2001 to 2009 that were built combining national and international databases. Therefore, our results are not only relevant for evaluating the spatial structure and dynamics in the Chinese biotech system and its integration into the global knowledge network, but also revive a discussion on persistence and processes of change in the systems theory for sciencebased industries.
This paper investigates the mental health penalty for women after childbirth in Switzerland. Leveraging insurance data, we employ a staggered difference-in-difference research design. The findings reveal a substantial mental health penalty for women following the birth of their first child. Approximately four years after childbirth, there is a one percentage point (p.p.) increase in antidepressant prescriptions, representing a 50% increase compared to pre-birth levels. This increase rises to 1.7 p.p. (a 75% increase) six years postpartum. The mental health penalty is likely not only a direct consequence of giving birth but also a consequence of the changed life circumstances and time constraints that accompany it, as the penalty is rising over time and is higher for women who are employed.
In this study we test whether principal components of the strain rate and stress tensors align within Switzerland. We find that 1) Helvetic Nappes line (HNL) is the relevant tectonic boundary to define different domains of crustal stress/surface strain rates orientations and 2) orientations of T- axes (of moment tensor solutions) and long-term asthenosphere cumulative finite strain (from SKS shear wave splitting) are consistent at the scale of the Alpine arc in Switzerland. At a more local scale, we find that seismic activity and surface deformation are in agreement but in three regions (Basel, Swiss Jura and Ticino); possibly because of the low levels of deformation and/or seismicity. In the Basel area, deep seismicity exists while surface deformation is absent. In the Ticino and the Swiss Jura, where seismic activity is close to absent, surface deformation is detected at a level of ~2 10E-8/yr (~6.3 10E-16/s).
In this paper, we discuss some problems of elementary plane differential geometry and kinematics. Although the results are not new, the consistent use of complex-valued functions (plane curves) of a real variable (parameter) allows to derive them ab ovo in a particularly simple, uniform and transparent way. A number of examples with figures complete the explanations.
The Basel problem consists in finding the sum of the reciprocals of the squares of the positive integers. It was finally solved in 1735 by Leonhard Euler. In this paper, we propose a simple proof based on the Weierstrass Sine product formula and L'Hôpital's rule.
On 22 September 2023 the inauguration of the "Stachelschützenhaus" at Basel's Petersplatz (St. Peter's Square) as an EPS Historic Site was hosted by the University of Basel. In the following article we will focus first on Daniel Bernoulli's career path, before discussing his major scientific achievements and finally adding some aspects of the inauguration ceremony (the colloquium talks, the visit of today's laboratories in the Stachelschützenhaus, and the unveiling of the plaque).
Inspired by the recent debate on the macroeconomic implications of the new bank regulatory standards known as Basel III, we tried to find out in this study that the impact of Basel III liquidity and capital requirements in Bangladesh proposed by Basel Committee on Banking Supervision (BCBS, 2010a). A small set of macro variables, using a sample of 22 private commercial banks operating in Bangladesh for the period of 2010-2014, are used to estimate long-run relationships among the variables. The macroeconomic variables are included The profitability of banks, GDP, banks' lending to private sector, Net Stable Funding Ratio, Tier 1 capital Ratio, Interest rate spread, real interest rate. The cost is quantified using Driscoll and Kraay panel data models with fixed effect. Impact of higher capital and liquidity requirement on Interest rate spread and lending to private sector of banks were considered as the cost to the economy as a whole whereas impact of higher capital and liquidity requirement on profitability of banks(ROE) was considered as the cost of banks. Here it is found that, the interest rate level is positively affected by the tighter liquidity and capital requirements which
We present SwissBERT, a masked language model created specifically for processing Switzerland-related text. SwissBERT is a pre-trained model that we adapted to news articles written in the national languages of Switzerland -- German, French, Italian, and Romansh. We evaluate SwissBERT on natural language understanding tasks related to Switzerland and find that it tends to outperform previous models on these tasks, especially when processing contemporary news and/or Romansh Grischun. Since SwissBERT uses language adapters, it may be extended to Swiss German dialects in future work. The model and our open-source code are publicly released at https://github.com/ZurichNLP/swissbert.
Euler's solution in 1734 of the Basel problem, which asks for a closed form expression for the sum of the reciprocals of all perfect squares, is one of the most celebrated results of mathematical analysis. In the modern era, numerous proofs of it have been produced, each emphasizing a different style of calculation, as a way of testing the power of some demonstration method. It's often thought that solutions using calculus need to involve advanced contour integration techniques or geometric coordinate transformations. We show that this is not the case, as the result can be derived by analyzing basic properties of a particular one-dimensional integral, and as such, can be obtained with techniques typical of regular calculus tests and math competitions.
Switzerland experienced one of the warmest summers during 2022. Extreme heat has been linked to increased mortality. Monitoring the mortality burden attributable to extreme heat is crucial to inform policies, such as heat warnings, and prevent heat-related deaths. In this study, we evaluate excess mortality during summer 2022, identify vulnerable populations and estimate temperature thresholds for heat warnings. We use nationwide mortality and population data in Switzerland during 2011-2022 by age, sex, day and canton. We develop a Bayesian ensemble modelling approach with dynamic population to predict expected mortality in summer 2022 and calculate excess by comparing expected with observed mortality. We account for covariates associated with mortality such as ambient temperature, national holidays and spatiotemporal random effects to improve predictions. After accounting for the effect of the COVID-19 pandemic, we found a 3% (95% credible interval: 0%-6%) excess mortality during summer 2022. We observed a total of 456 (5-891) excess deaths during summer 2022 in people older than 80 years. There was weak evidence of excess mortality in the other age groups. The highest excess mort
This survey analyzed the quality of the PDF documents on online repositories in Switzerland, examining their accessibility for people with visual impairments. Two minimal accessibility features were analyzed: the PDFs had to have tags and a hierarchical heading structure. The survey also included interviews with the managers or heads of multiple Swiss universities' repositories to assess the general opinion and knowledge of PDF accessibility. An analysis of interviewee responses indicates an overall lack of awareness of PDF accessibility, and showed that online repositories currently have no concrete plans to address the issue. This paper concludes by presenting a set of recommendations for online repositories to improve the accessibility of their PDF documents.
Bill would let Homeland Security chief decide when an AI should be shut down
The BaseL Stellar Library (BaSeL) is a library of synthetic spectra which has already been used in various astrophysical applications (stellar clusters studies, characterization and choice of the COROT potential targets, eclipsing binaries,...). This library could provide useful indications to 1) choose the best photometric system for the GAIA strategy by evaluating their expected performances and 2) apply systematically the BaSeL models for any sample of GAIA targets. In this context, we describe one of the future developments of the BaSeL interactive web site to probe the GAIA photometric data: an automatic determination of atmospheric parameters from observed colours.