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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

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

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

For quadratic fields \(k=\mathbb{Q}(\sqrt{d})\) with discriminant \(d\), \(3\)-class group \(\mathrm{Cl}_3(k)\simeq (\mathbb{Z}/3\mathbb{Z})^2\), and four \textit{simple} \(3\)-principalization types \(\varkappa(k)\in\lbrace (1122),(3122),(1231),(2231)\rbrace\), we establish necessary and sufficient conditions for the Galois group \(S=\mathrm{Gal}(\mathrm{F}_3^\infty(k)/k)\) of the unramified Hilbert \(3\)-class field tower of \(k\) to coincide with the Galois group \(M=\mathrm{Gal}(\mathrm{F}_3^2(k)/k)\) of the maximal metabelian unramified \(3\)-extension of \(k\). In the case of non-coincidence, we study the path between \(M\) and \(S\) in the descendant tree of the elementary bicyclic \(3\)-group \((\mathbb{Z}/3\mathbb{Z})^2\). For two \textit{complex} \(3\)-principalization types \(\varkappa(k)\in\lbrace (2122),(4231)\rbrace\), we show that infinitely many non-metabelian possible Galois groups \(S=\mathrm{Gal}(\mathrm{F}_3^\infty(k)/k)\) with presumably unbounded derived length \(\mathrm{dl}(S)\) share a common metabelianization \(M=S/S^{\prime\prime}\), whence only partial criteria can be stated. Minimal discriminants \(d>0\) with assigned simple \(3\)-principalization typ

Recent cosmological surveys and datasets have highlighted a variety of tensions to the concordance model of our universe, $Λ$CDM. Of particular interest is the Hubble tension, the $5.5σ$ discrepancy between measurements of the Hubble constant $H_0$ using high redshift CMB data from Planck ($67.27\pm0.60$km$\text{s}^{-1}\text{Mpc}^{-1}$) and low redshift supernovae from SH0ES ($73.2\pm1.3$km$\text{s}^{-1}\text{Mpc}^{-1}$). To avoid stepping on any toes, we have initiated the CROCS collaboration to resolve this tension, gathering experts from across many fields of cosmology, astrophysics, astronomy, machine learning, data science, philosophy, and astrology. In this paper, we present findings from CROCS Data Release 1, corresponding to the first $\sim3$ days and 27 minutes (rest frame) of observation. We perform a robust statistical analysis, showing that Planck and SH0ES both suffer from imperial biasing systematics (IBS) at $5σ$ significance. Accounting for these errors by converting to metric units reconciles the high and low redshift data, with $H_0 = 69.00\pm0.420$km$\text{s}^{-1}\text{Mpc}^{-1}$. We thus report that our results are sufficient to end the Hubble tension for good.

A $(3, 6)$-fullerene is a cubic planar graph whose faces all have 3 or 6 sides. We give an exact enumeration of $(3, 6)$-fullerenes with $V$ vertices. We also enumerate $(3, 6)$-fullerenes with mirror symmetry, with 3-fold rotational symmetry, and with both types of symmetry. The resulting formulas are expressed in terms of the prime factorization of $V$.

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.

We study translative arrangements of centrally symmetric convex domains in the plane (resp., of congruent balls in the Euclidean $3$-space) that neither pack nor cover. We define their soft density depending on a soft parameter and prove that the largest soft density for soft translative packings of a centrally symmetric convex domain with $3$-fold rotational symmetry and given soft parameter is obtained for a proper soft lattice packing. Furthermore, we show that among the soft lattice packings of congruent soft balls with given soft parameter the soft density is locally maximal for the corresponding face centered cubic (FCC) lattice.

Let $F$ and $H$ be $k$-uniform hypergraphs. We say $H$ is $F$-saturated if $H$ does not contain a subgraph isomorphic to $F$, but $H+e$ does for any hyperedge $e ot\in E(H)$. The saturation number of $F$, denoted $\mathrm{sat}_k(n,F)$, is the minimum number of edges in a $F$-saturated $k$-uniform hypergraph $H$ on $n$ vertices. Let $C_3^{(3)}$ denote the $3$-uniform loose cycle on $3$ edges. In this work, we prove that \[ \left(\frac{4}3+o(1)\right)n\leq \mathrm{sat}_3(n,C_3^{(3)})\leq \frac{3}2n+O(1). \] This is the first non-trivial result on the saturation number for a fixed short hypergraph cycle.

We obtain all coset $n$-valued topological groups on $S^3$ and $\mathbb{R}P^3$, arising from compact Lie groups Sp(1) and SO(3) and there finite groups of automorphisms.

Ultrafast X-rays revealed how a molecule converts absorbed light into motion in just trillionths of a second。 Individual atoms recorded different stages of the process, opening a powerful new window into light-driven chemistry

NASA is preparing for future astronaut landings on the Moon with an unusually ambitious orbital rehearsal。 During Artemis III in 2027, Orion astronauts will rendezvous and dock separately with prototype lunar landers from Blue Origin and SpaceX, allowing crews and ground teams to test the complex maneuvers needed for later missions

Engineers have transformed a notoriously brittle cobalt-aluminum compound into a material that is both extremely strong and capable of bending without breaking。 Their nanoscale design produced a yield strength about six to 10 times greater than high-strength structural steel while sustaining substantial deformation at room temperature。 The approach

Primordial black holes may occasionally pass through white dwarf stars and trigger enormous Type Ia supernova explosions。 Researchers found that these events could explain chemical patterns seen in supernova remnants, nearby explosions, and stars across the Milky Way

Autonomous vehicle giant disturbs residents' sleep

Tracking smells in turbulent air takes a keen sense of direction and sharp memory

Popular AI-powered food apps may make calorie counting easier, but they may also leave out a surprisingly large part of the meal。 Four apps underestimated calories and fat by about one-third when tested against carefully prepared meals。 High-fat ketogenic dishes appeared to cause the most trouble, while carbohydrates were measured more consistently