Non-polynomial Worst-Case Analysis of Recursive Programs

We study the problem of developing efficient approaches for proving worst-case bounds of non-deterministic recursive programs. Ranking functions are sound and complete for proving termination and worst-case bounds of nonrecursive programs. First, we apply ranking functions to recursion, resulting in measure functions. We show that measure functions provide a sound and complete approach to prove worst-case bounds of non-deterministic recursive programs. Our second contribution is the synthesis of measure functions in nonpolynomial forms. We show that non-polynomial measure functions with logarithm and exponentiation can be synthesized through abstraction of logarithmic or exponentiation terms, Farkas' Lemma, and Handelman's Theorem using linear programming. While previous methods obtain worst-case polynomial bounds, our approach can synthesize bounds of the form $\mathcal{O}(n\log n)$ as well as $\mathcal{O}(n^r)$ where $r$ is not an integer. We present experimental results to demonstrate that our approach can obtain efficiently worst-case bounds of classical recursive algorithms such as (i) Merge-Sort, the divide-and-conquer algorithm for the Closest-Pair problem, where we obtain $\mathcal{O}(n \log n)$ worst-case bound, and (ii) Karatsuba's algorithm for polynomial multiplication and Strassen's algorithm for matrix multiplication, where we obtain $\mathcal{O}(n^r)$ bound such that $r$ is not an integer and close to the best-known bounds for the respective algorithms.Comment: 54 Pages, Full Version to CAV 201

Disparities and risks of sexually transmissible infections among men who have sex with men in China: a meta-analysis and data synthesis.

BACKGROUND: Sexually transmitted infections (STIs), including Hepatitis B and C virus, are emerging public health risks in China, especially among men who have sex with men (MSM). This study aims to assess the magnitude and risks of STIs among Chinese MSM. METHODS: Chinese and English peer-reviewed articles were searched in five electronic databases from January 2000 to February 2013. Pooled prevalence estimates for each STI infection were calculated using meta-analysis. Infection risks of STIs in MSM, HIV-positive MSM and male sex workers (MSW) were obtained. This review followed the PRISMA guidelines and was registered in PROSPERO. RESULTS: Eighty-eight articles (11 in English and 77 in Chinese) investigating 35,203 MSM in 28 provinces were included in this review. The prevalence levels of STIs among MSM were 6.3% (95% CI: 3.5-11.0%) for chlamydia, 1.5% (0.7-2.9%) for genital wart, 1.9% (1.3-2.7%) for gonorrhoea, 8.9% (7.8-10.2%) for hepatitis B (HBV), 1.2% (1.0-1.6%) for hepatitis C (HCV), 66.3% (57.4-74.1%) for human papillomavirus (HPV), 10.6% (6.2-17.6%) for herpes simplex virus (HSV-2) and 4.3% (3.2-5.8%) for Ureaplasma urealyticum. HIV-positive MSM have consistently higher odds of all these infections than the broader MSM population. As a subgroup of MSM, MSW were 2.5 (1.4-4.7), 5.7 (2.7-12.3), and 2.2 (1.4-3.7) times more likely to be infected with chlamydia, gonorrhoea and HCV than the broader MSM population, respectively. CONCLUSION: Prevalence levels of STIs among MSW were significantly higher than the broader MSM population. Co-infection of HIV and STIs were prevalent among Chinese MSM. Integration of HIV and STIs healthcare and surveillance systems is essential in providing effective HIV/STIs preventive measures and treatments. TRIAL REGISTRATION: PROSPERO NO: CRD42013003721

Chromosomal-level assembly of the Asian Seabass genome using long sequence reads and multi-layered scaffolding

We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical and genetic mapping along with shared synteny from closely related fish species to derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50 size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various regions across the species' native range. SNP analyses identified high levels of genetic diversity and confirmed earlier indications of a population stratification comprising three clades with signs of admixture apparent in the South-East Asian population. The quality of the Asian seabass genome assembly far exceeds that of any other fish species, and will serve as a new standard for fish genomics

A Mycobacterium tuberculosis cluster demonstrating the use of genotyping in urban tuberculosis control

Background: DNA fingerprinting of Mycobacterium tuberculosis isolates offers better opportunities to study links between tuberculosis (TB) cases and can highlight relevant issues in urban TB control in low-endemic countries. Methods: A medium-sized molecular cluster of TB cases with identical DNA fingerprints was used for the development of a visual presentation of epidemiologic links between cases. Results: Of 32 cases, 17 (53%) were linked to the index case, and 11 (34%) to a secondary case. The remaining four (13%) could not be linked and were classified as possibly caused by the index patient. Of the 21 cases related to the index case, TB developed within one year of the index diagnosis in 11 patients (52%), within one to two years in four patients (19%), and within two to five years in six patients (29%). Conclusion: Cluster analysis underscored several issues for TB control in an urban setting, such as the recognition of the outbreak, the importance of reinfections, the impact of delayed diagnosis, the contribution of pub-related transmissions and its value for decision-making to extend contact investigations. Visualising cases in a cluster diagram was particularly useful in finding transmission locations and the similarities and links between patients

The LRRK2 Arg1628Pro variant is a risk factor for Parkinson's disease in the Chinese population

The c.G4883C variant in the leucine-rich repeat kinase 2 (LRRK2) gene (protein effect: Arg1628Pro) has been recently proposed as a second risk factor for sporadic Parkinson's disease in the Han Chinese population (after the Gly2385Arg variant). In this paper, we analyze the Arg1628Pro variant and the associated haplotype in a large sample of 1,337 Han subjects (834 patients and 543 controls) ascertained from a single referral center in Taiwan. In our sample, the Arg1628Pro allele was more frequent among patients (3.8%) than among controls (1.8%; p = 0.004, OR 2.13, 95% CI 1.29-3.52). Sixty heterozygous and two homozygous carriers of the Arg1628Pro variant were identified among the patients, of which only one was also a carrier of the LRRK2 Gly2385Arg variant. We also show that carriers of the Arg1628Pro variant share a common, extended haplotype, suggesting a founder effect. Parkinson's disease onset age was similar in patients who carried the Arg1628Pro variant and in those who did not carry it. Our data support the contention that the Arg1628Pro variant is a second risk factor for Parkinson's disease in the Han Chinese population. Adding the estimated effects of Arg1628Pro (population attributable risk [PAR] ∼4%) and Gly2385Arg variants (PAR ∼6%) yields a total PAR of ∼10%

AdaSpline-Net for Improved Short-Term Solar Irradiance Forecasting

Neural networks utilizing backpropagation are a powerful tool for solar irradiance forecasting, which is vital for climate research and energy market operations. This study addresses the challenge of modeling complex, nonlinear relationships between weather parameters by introducing an innovative adaptive B-spline activation function. The piecewise polynomial approach proposed in this work, integrated into the neural network framework and optimized using the Adaptive Moment Estimation (Adam) algorithm, allows for effective parameter tuning after each epoch, resulting in enhanced forecasting accuracy. Unlike traditional activation functions, which suffer from issues like the "dying ReLU" problem, the adaptive B-spline function provides smooth, flexible mappings with continuous gradients, allowing it to capture intricate data patterns effectively. This adaptability makes it particularly suitable for high-precision environmental applications. Validation using real-world datasets from Singapore and Hawaii shows that the adaptive B-spline significantly outperforms conventional activation functions, delivering up to a 10% improvement in forecasting accuracy for both training and testing datasets. Furthermore, its robustness across various neural network architectures demonstrates its adaptability and compatibility with backpropagation. This research highlights the potential of optimized B-spline activation functions to improve the accuracy and dependability of neural network-based forecasting models