Whole-genome demography of COVID-19 virus during its pandemic period and on panvalent vaccine design.

With over 16 million submitted genomic sequences, the SARS-CoV-2 (SC2) virus, the cause of the most recent worldwide COVID-19 pandemic, has become the most sequenced genome of all known viruses, revealing, for example, a vast number of expanding viral lineages. Since the pandemic phase appears to be over, we performed a retrospective re-examination of the demographic grouping pattern and their genomic characteristics during the entire pandemic period up to the peak of the last pandemic wave. For our study, we extracted from the NCBI only unique viral sequences and converted each sequence data to a relational vector, indicating the presence/absence of each variational event compared to a reference sequence. Our study revealed several genomic features that are unexpected or different from those of previous studies. For example, approximately 44,000 variants with unique sequences emerged during the pandemic period; they group into only four major viral-genomic groups and each has a set of mostly unique highly-conserved variant-genotypes (HCVGs); and a small set from the first (ancestral) group was inherited by the three (descendant) groups, suggesting that HCVGs in the next group may be predictable from the current group(s). Such a concept may be potentially important in designing panvalent vaccines against the current and future waves of viral infections

A Single-Machine Scheduling Problem with Uncertainty in Processing Times and Outsourcing Costs

We consider a single-machine scheduling problem with an outsourcing option in an environment where the processing time and outsourcing cost are uncertain. The performance measure is the total cost of processing some jobs in-house and outsourcing the rest. The cost of processing in-house jobs is measured as the total weighted completion time, which can be considered the operating cost. The uncertainty is described through either an interval or a discrete scenario. The objective is to minimize the maximum deviation from the optimal cost of each scenario. Since the deterministic version is known to be NP-hard, we focus on two special cases, one in which all jobs have identical weights and the other in which all jobs have identical processing times. We analyze the computational complexity of each case and present the conditions that make them polynomially solvable

F^2-Softmax: Diversifying Neural Text Generation via Frequency Factorized Softmax

Despite recent advances in neural text generation, encoding the rich diversity in human language remains elusive. We argue that the sub-optimal text generation is mainly attributable to the imbalanced token distribution, which particularly misdirects the learning model when trained with the maximum-likelihood objective. As a simple yet effective remedy, we propose two novel methods, F^2-Softmax and MefMax, for a balanced training even with the skewed frequency distribution. MefMax assigns tokens uniquely to frequency classes, trying to group tokens with similar frequencies and equalize frequency mass between the classes. F^2-Softmax then decomposes a probability distribution of the target token into a product of two conditional probabilities of (i) frequency class, and (ii) token from the target frequency class. Models learn more uniform probability distributions because they are confined to subsets of vocabularies. Significant performance gains on seven relevant metrics suggest the supremacy of our approach in improving not only the diversity but also the quality of generated texts.Comment: EMNLP 202

The effect of sustained-release CARvedilol in patients with hypErtension and heart failure with preserved ejection fraction: a study protocol for a pilot randomized controlled trial (CARE-preserved HF)

BackgroundAlthough beta-blockers improve clinical outcomes in heart failure with reduced ejection fraction, the benefit of beta-blockers in heart failure with preserved ejection fraction (HFpEF) is uncertain. Global longitudinal strain (GLS) is a robust predictor of heart failure outcomes, and recent studies have shown that beta-blockers are associated with improved survival in those with low GLS (GLS <14%) but not in those with GLS ≥14% among patients with LVEF ≥40%. Therefore, the objective of this trial is to evaluate the effect of sustained-release carvedilol (carvedilol-SR) on the outcome [N-terminal pro-B-natriuretic peptide (NT-proBNP) concentration] in patients with hypertension and HFpEF and will assess the differential effects of these drugs on the outcome, according to the GLS categories.MethodsThis prospective randomized double-blind multicenter trial (CARE-preserved HF) will include 100 patients with HFpEF from three tertiary hospitals in South Korea. Patients with HFpEF and hypertension aged ≥20 years who have evidence of functional and structural heart disease on echocardiography and elevated natriuretic peptide will be enrolled. Eligible participants will be randomized 1:1 to either the carvedilol-SR group (n = 50) or the placebo group (n = 50). Patients in the carvedilol-SR group will receive 8, 16, 32, or 64 mg carvedilol-SR once daily for 6 months, and the dose of carvedilol will be up-titrated at the discretion of the treating physicians. The primary efficacy outcome was the time-averaged proportional change in N-terminal pro-B-natriuretic peptide concentration from baseline to months 3 and 6. We will also evaluate the differential effects of carvedilol-SR on primary outcomes according to GLS, using a cut-off of 14% or the median value.DiscussionThis randomized controlled trial will investigate the efficacy and safety of carvedilol-SR in patients with HFpEF and hypertension. Clinical Trial RegistrationClinicalTrial.gov, identifier NCT05553314