The three smallest compact arithmetic hyperbolic 5-orbifolds

We determine the three hyperbolic 5-orbifolds of smallest volume among compact arithmetic orbifolds, and we identify their fundamental groups with hyperbolic Coxeter groups. This gives two different ways to compute the volume of these orbifolds.Comment: 11 page

UAMM: UBET Automated Market Maker

Automated market makers (AMMs) are pricing mechanisms utilized by decentralized exchanges (DEX). Traditional AMM approaches are constrained by pricing solely based on their own liquidity pool, without consideration of external markets or risk management for liquidity providers. In this paper, we propose a new approach known as UBET AMM (UAMM), which calculates prices by considering external market prices and the impermanent loss of the liquidity pool. Despite relying on external market prices, our method maintains the desired properties of a constant product curve when computing slippages. The key element of UAMM is determining the appropriate slippage amount based on the desired target balance, which encourages the liquidity pool to minimize impermanent loss. We demonstrate that our approach eliminates arbitrage opportunities when external market prices are efficient

Onchain Sports Betting using UBET Automated Market Maker

The paper underscores how decentralization in sports betting addresses the drawbacks of traditional centralized platforms, ensuring transparency, security, and lower fees. Non-custodial solutions empower bettors with ownership of funds, bypassing geographical restrictions. Decentralized platforms enhance security, privacy, and democratic decision-making. However, decentralized sports betting necessitates automated market makers (AMMs) for efficient liquidity provision. Existing AMMs like Uniswap lack alignment with fair odds, creating risks for liquidity providers. To mitigate this, the paper introduces UBET AMM (UAMM), utilizing smart contracts and algorithms to price sports odds fairly. It establishes an on-chain betting framework, detailing market creation, UAMM application, collateral liquidity pools, and experiments that exhibit positive outcomes. UAMM enhances decentralized sports betting by ensuring liquidity, decentralized pricing, and global accessibility, promoting trustless and efficient betting

Vegetation Cover Analysis of Hazardous Waste Sites in Utah and Arizona Using Hyperspectral Remote Sensing

This study investigated the usability of hyperspectral remote sensing for characterizing vegetation at hazardous waste sites. The specific objectives of this study were to: (1) estimate leaf-area-index (LAI) of the vegetation using three different methods (i.e., vegetation indices, red-edge positioning (REP), and machine learning regression trees), and (2) map the vegetation cover using machine learning decision trees based on either the scaled reflectance data or mixture tuned matched filtering (MTMF)-derived metrics and vegetation indices. HyMap airborne data (126 bands at 2.3 x 2.3 m spatial resolution), collected over the U. S. Department of Energy uranium processing sites near Monticello, Utah and Monument Valley, Arizona, were used. Grass and shrub species were mixed on an engineered disposal cell cover at the Monticello site while shrub species were dominant in the phytoremediation plantings at the Monument Valley site. Regression trees resulted in the best calibration performance of LAI estimation (R-2 > 0.80. The use of REPs failed to accurately predict LAI (R-2 < 0.2). The use of the MTMF-derived metrics (matched filter scores and infeasibility) and a range of vegetation indices in decision trees improved the vegetation mapping when compared to the decision tree classification using just the scaled reflectance. Results suggest that hyperspectral imagery are useful for characterizing biophysical characteristics (LAI) and vegetation cover on capped hazardous waste sites. However, it is believed that the vegetation mapping would benefit from the use of higher spatial resolution hyperspectral data due to the small size of many of the vegetation patches (<1 m) found on the sites.open111

Heavy quark flavour dependence of multiparticle production in QCD jets

After inserting the heavy quark mass dependence into QCD partonic evolution equations, we determine the mean charged hadron multiplicity and second multiplicity correlators of jets produced in high energy collisions. We thereby extend the so-called dead cone effect to the phenomenology of multiparticle production in QCD jets and find that the average multiplicity of heavy-quark initiated jets decreases significantly as compared to the massless case, even taking into account the weak decay products of the leading primary quark. We emphasize the relevance of our study as a complementary check of $b$-tagging techniques at hadron colliders like the Tevatron and the LHC.Comment: Version revised, accepted for publication in JHEP, 21 pages and 7 figure

Participation of the Melanocortin-1 Receptor in the UV Control of Pigmentation

The cloning of the melanocortin-1 receptor (MC1R) gene from human melanocytes and the demonstration that these cells respond to the melanocortins α-melanocyte stimulating hormone (α-MSH) and adrenocorticotropic hormone (ACTH) with increased proliferation and melanogenesis have renewed the interest in investigation the physiological role of these hormones in regulating human pigmentation. α-Melanocyte stimulating hormone and ACTH are both synthesized in the human epidermis, and their synthesis is upregulated by exposure to ultraviolet radiation (UVR). Activation of the MC1R by ligand binding results in stimulation of cAMP formation, which is a principal mechanism for inducing melanogenesis. The increase in cAMP is required for the pigmentary response of human melanocytes to UVR, and for allowing them to overcome the UVR-induced G1 arrest. Treatment of human melanocytes with α-MSH increases eumelanin synthesis, an effect that is expected to enhance photoprotection of the skin. Population studies have revealed more than 20 allelic variants of the MC1R gene. Some of these variants are overexpressed in individuals with skin type I or II, red hair, and poor tanning ability. Future studies will aim at further exploration of the role of these variants in MC1R function, and in determining constitutive human pigmentation, the response to sun exposure, and possibly the susceptibility to skin cancer

T‐cell epitope content comparison (EpiCC) of swine H1 influenza A virus hemagglutinin

Background: Predicting vaccine efficacy against emerging pathogen strains is a significant problem in human and animal vaccine design. T‐cell epitope cross‐conservation may play an important role in cross‐strain vaccine efficacy. While influenza A virus (IAV) hemagglutination inhibition (HI) antibody titers are widely used to predict protective efficacy of 1 IAV vaccine against new strains, no similar correlate of protection has been identified for T‐cell epitopes. Objective: We developed a computational method (EpiCC) that facilitates pairwise comparison of protein sequences based on an immunological property—T‐cell epitope content—rather than sequence identity, and evaluated its ability to classify swine IAV strain relatedness to estimate cross‐protective potential of a vaccine strain for circulating viruses. Methods: T‐cell epitope relatedness scores were assessed for 23 IAV HA sequences representing the major H1 swine IAV phylo‐clusters circulating in North American swine and HA sequences in a commercial inactivated vaccine (FluSure XP®). Scores were compared to experimental data from previous efficacy studies. Results: Higher EpiCC scores were associated with greater protection by the vaccine against strains for 23 field IAV strain vaccine comparisons. A threshold for EpiCC relatedness associated with full or partial protection in the absence of cross‐reactive HI antibodies was identified. EpiCC scores for field strains for which FluSure protective efficacy is not yet available were also calculated. Conclusion: EpiCC thresholds can be evaluated for predictive accuracy of protection in future efficacy studies. EpiCC may also complement HI cross‐reactivity and phylogeny for selection of influenza strains in vaccine development

In silico assessment of potential druggable pockets on the surface of α1-Antitrypsin conformers

The search for druggable pockets on the surface of a protein is often performed on a single conformer, treated as a rigid body. Transient druggable pockets may be missed in this approach. Here, we describe a methodology for systematic in silico analysis of surface clefts across multiple conformers of the metastable protein α1-antitrypsin (A1AT). Pathological mutations disturb the conformational landscape of A1AT, triggering polymerisation that leads to emphysema and hepatic cirrhosis. Computational screens for small molecule inhibitors of polymerisation have generally focused on one major druggable site visible in all crystal structures of native A1AT. In an alternative approach, we scan all surface clefts observed in crystal structures of A1AT and in 100 computationally produced conformers, mimicking the native solution ensemble. We assess the persistence, variability and druggability of these pockets. Finally, we employ molecular docking using publicly available libraries of small molecules to explore scaffold preferences for each site. Our approach identifies a number of novel target sites for drug design. In particular one transient site shows favourable characteristics for druggability due to high enclosure and hydrophobicity. Hits against this and other druggable sites achieve docking scores corresponding to a Kd in the µM–nM range, comparing favourably with a recently identified promising lead. Preliminary ThermoFluor studies support the docking predictions. In conclusion, our strategy shows considerable promise compared with the conventional single pocket/single conformer approach to in silico screening. Our best-scoring ligands warrant further experimental investigation

Biological measurement beyond the quantum limit

Quantum noise places a fundamental limit on the per photon sensitivity attainable in optical measurements. This limit is of particular importance in biological measurements, where the optical power must be constrained to avoid damage to the specimen. By using non-classically correlated light, we demonstrated that the quantum limit can be surpassed in biological measurements. Quantum enhanced microrheology was performed within yeast cells by tracking naturally occurring lipid granules with sensitivity 2.4 dB beyond the quantum noise limit. The viscoelastic properties of the cytoplasm could thereby be determined with a 64% improved measurement rate. This demonstration paves the way to apply quantum resources broadly in a biological context