Proving Expected Sensitivity of Probabilistic Programs with Randomized Variable-Dependent Termination Time

The notion of program sensitivity (aka Lipschitz continuity) specifies that changes in the program input result in proportional changes to the program output. For probabilistic programs the notion is naturally extended to expected sensitivity. A previous approach develops a relational program logic framework for proving expected sensitivity of probabilistic while loops, where the number of iterations is fixed and bounded. In this work, we consider probabilistic while loops where the number of iterations is not fixed, but randomized and depends on the initial input values. We present a sound approach for proving expected sensitivity of such programs. Our sound approach is martingale-based and can be automated through existing martingale-synthesis algorithms. Furthermore, our approach is compositional for sequential composition of while loops under a mild side condition. We demonstrate the effectiveness of our approach on several classical examples from Gambler's Ruin, stochastic hybrid systems and stochastic gradient descent. We also present experimental results showing that our automated approach can handle various probabilistic programs in the literature

Enhanced heterologous protein productivity by genome reduction in Lactococcus lactis NZ9000

Background: The implementation of novel chassis organisms to be used as microbial cell factories in industrial applications is an intensive research field. Lactococcus lactis, which is one of the most extensively studied model organisms, exhibits superior ability to be used as engineered host for fermentation of desirable products. However, few studies have reported about genome reduction of L. lactis as a clean background for functional genomic studies and a model chassis for desirable product fermentation. Results: Four large nonessential DNA regions accounting for 2.83% in L. lactis NZ9000 (L. lactis 9 k) genome (2,530,294 bp) were deleted using the Cre-loxP deletion system as the first steps toward a minimized genome in this study. The mutants were compared with the parental strain in several physiological traits and evaluated as microbial cell factories for heterologous protein production (intracellular and secretory expression) with the red fluorescent protein (RFP) and the bacteriocin leucocin C (LecC) as reporters. The four mutants grew faster, yielded enhanced biomass, achieved increased adenosine triphosphate content, and diminished maintenance demands compared with the wild strain in the two media tested. In particular, L. lactis 9 k-4 with the largest deletion was identified as the optimum candidate host for recombinant protein production. With nisin induction, not only the transcriptional efficiency but also the production levels of the expressed reporters were approximately three-to fourfold improved compared with the wild strain. The expression of lecC gene controlled with strong constitutive promoters P5 and P8 in L. lactis 9 k-4 was also improved significantly. Conclusions: The genome-streamlined L. lactis 9 k-4 outcompeted the parental strain in several physiological traits assessed. Moreover, L. lactis 9 k-4 exhibited good properties as platform organism for protein production. In future works, the genome of L. lactis will be maximally reduced by using our specific design to provide an even more clean background for functional genomics studies than L. lactis 9 k-4 constructed in this study. Furthermore, an improved background will be potentially available for use in biotechology.Peer reviewe

Templated Growth of Covalently Bonded Three-Dimensional Carbon Nanotube Networks Originated from Graphene

A template-assisted method that enables the growth of covalently bonded three-dimensional carbon nanotubes (CNTs) originating from graphene at a large scale is demonstrated. Atomic force microscopy-based mechanical tests show that the covalently bonded CNT structure can effectively distribute external loading throughout the network to improve the mechanical strength of the material

Discovery, Biosynthesis, and Characterization of Rodencin, a Two-Component Lanthipeptide, Harboring d-Amino Acids Introduced by the Unusual Dehydrogenase RodJ_A

Lanthipeptides, a group of ribosomally synthesized and post-translationally modified peptides (RiPPs), exhibit diverse structures and bioactivities. Their biosynthetic enzymes serve as valuable tools for peptide bioengineering. Here, we report a class II lanthipeptide biosynthetic gene cluster in a Bacillus strain, driving the biosynthesis of a two-component lanthipeptide, termed rodencin, featured by the presence of two different d-amino acids, i.e., d-Ala and d-Abu. Rodencin displays synergistic antimicrobial activity against food-borne pathogens such as Bacillus cereus, Staphylococcus aureus, and Listeria monocytogenes. The α-peptide of rodencin contains one d-Ala and the β-peptide features both d-Ala and d-Abu. These are installed by dehydratases RodM1 and RodM2 and dehydrogenase RodJA, the activities of which were successfully reconstituted using a dedicated E. coli expression system.</p

The spin alignment of vector mesons with light front quarks

The global spin alignment of the vector meson has been observed in relativistic heavy ion collisions, but is still on hot debates in the theoretical community. Here we propose to apply the light front framework to explain this phenomenon since the light front form explicitly describes the hadron spin including both the quark spin and the orbital angular momentum. After applying the light front spinor, we find that the spin alignment in the polarization of vector mesons with $\rho_{00}>1/3$ can be naturally manifested and in particular, the obtained spin alignment for $\phi$ meson is in good agreement with the experimental data. This implies that to explain the spin alignment it is important to properly include the contribution from the gluon interactions that are presented in terms of the orbital angular momentum of the hadron bound state.Comment: 7 pages, 2 figure

Antiviral activities and applications of ribosomally synthesized and post-translationally modified peptides (RiPPs)

The emergence and re-emergence of viral epidemics and the risks of antiviral drug resistance are a serious threat to global public health. New options to supplement or replace currently used drugs for antiviral therapy are urgently needed. The research in the field of ribosomally synthesized and post-translationally modified peptides (RiPPs) has been booming in the last few decades, in particular in view of their strong antimicrobial activities and high stability. The RiPPs with antiviral activity, especially those against enveloped viruses, are now also gaining more interest. RiPPs have a number of advantages over small molecule drugs in terms of specificity and affinity for targets, and over protein-based drugs in terms of cellular penetrability, stability and size. Moreover, the great engineering potential of RiPPs provides an efficient way to optimize them as potent antiviral drugs candidates. These intrinsic advantages underscore the good therapeutic prospects of RiPPs in viral treatment. With the aim to highlight the underrated antiviral potential of RiPPs and explore their development as antiviral drugs, we review the current literature describing the antiviral activities and mechanisms of action of RiPPs, discussing the ongoing efforts to improve their antiviral potential and demonstrate their suitability as antiviral therapeutics. We propose that antiviral RiPPs may overcome the limits of peptide-based antiviral therapy, providing an innovative option for the treatment of viral disease

An Algebraic Method to Fidelity-based Model Checking over Quantum Markov Chains

Fidelity is one of the most widely used quantities in quantum information that measure the distance of quantum states through a noisy channel. In this paper, we introduce a quantum analogy of computation tree logic (CTL) called QCTL, which concerns fidelity instead of probability in probabilistic CTL, over quantum Markov chains (QMCs). Noisy channels are modelled by super-operators, which are specified by QCTL formulas; the initial quantum states are modelled by density operators, which are left parametric in the given QMC. The problem is to compute the minimumfidelity over all initial states for conservation. We achieve it by a reduction to quantifier elimination in the existential theory of the reals. The method is absolutely exact, so that QCTL formulas are proven to be decidable in exponential time. Finally, we implement the proposed method and demonstrate its effectiveness via a quantum IPv4 protocol

Unbending strategies shepherd cooperation and suppress extortion in spatial populations

Evolutionary game dynamics on networks typically consider the competition among simple strategies such as cooperation and defection in the Prisoner's Dilemma and summarize the effect of population structure as network reciprocity. However, it remains largely unknown regarding the evolutionary dynamics involving multiple powerful strategies typically considered in repeated games, such as the zero-determinant (ZD) strategies that are able to enforce a linear payoff relationship between them and their co-players. Here, we consider the evolutionary dynamics of always cooperate (AllC), extortionate ZD (extortioners), and unbending players in lattice populations based on the commonly used death-birth updating. Out of the class of unbending strategies, we consider a particular candidate, PSO Gambler, a machine-learning-optimized memory-one strategy, which can foster reciprocal cooperation and fairness among extortionate players. We derive analytical results under weak selection and rare mutations, including pairwise fixation probabilities and long-term frequencies of strategies. In the absence of the third unbending type, extortioners can achieve a half-half split in equilibrium with unconditional cooperators for sufficiently large extortion factors. However, the presence of unbending players fundamentally changes the dynamics and tilts the system to favor unbending cooperation. Most surprisingly, extortioners cannot dominate at all regardless of how large their extortion factor is, and the long-term frequency of unbending players is maintained almost as a constant. Our analytical method is applicable to studying the evolutionary dynamics of multiple strategies in structured populations. Our work provides insights into the interplay between network reciprocity and direct reciprocity, revealing the role of unbending strategies in enforcing fairness and suppressing extortion.Comment: 21 pages, 6 figure

FFN: a Fine-grained Chinese-English Financial Domain Parallel Corpus

Large Language Models (LLMs) have stunningly advanced the field of machine translation, though their effectiveness within the financial domain remains largely underexplored. To probe this issue, we constructed a fine-grained Chinese-English parallel corpus of financial news called FFN. We acquired financial news articles spanning between January 1st, 2014, to December 31, 2023, from mainstream media websites such as CNN, FOX, and China Daily. The dataset consists of 1,013 main text and 809 titles, all of which have been manually corrected. We measured the translation quality of two LLMs -- ChatGPT and ERNIE-bot, utilizing BLEU, TER and chrF scores as the evaluation metrics. For comparison, we also trained an OpenNMT model based on our dataset. We detail problems of LLMs and provide in-depth analysis, intending to stimulate further research and solutions in this largely uncharted territory. Our research underlines the need to optimize LLMs within the specific field of financial translation to ensure accuracy and quality.Comment: a simplified version of this paper is accepted by International Conference on Asian Language Processing 202