Memetic algorithms (MAs) represent one of the recent growing areas in evolutionary algorithm (EA) research. The term MAs is now widely used as a synergy of evolutionary or any population-based approach with separate individual learning or local improvement procedures for problem search. Quite often, MAs are also referred to in the literature as Baldwinian EAs, Lamarckian EAs, cultural algorithms, or genetic local searches. In the last decade, MAs have been demonstrated to converge to high-quality solutions more efficiently than their conventional counterparts on a wide range of real-world problems. Despite the success and surge in interests on MAs, many of the successful MAs reported have been crafted to suit problems in very specific domains. Given the restricted theoretical knowledge available in the field of MAs and the limited progress made on formal MA frameworks, we present a novel probabilistic memetic framework that models MAs as a process involving the decision of embracing the separate actions of evolution or individual learning and analyzing the probability of each process in locating the global optimum. Further, the framework balances evolution and individual learning by governing the learning intensity of each individual according to the theoretical upper bound derived while the search progresses. Theoretical and empirical studies on representative benchmark problems commonly used in the literature are presented to demonstrate the characteristics and efficacies of the probabilistic memetic framework. Further, comparisons to recent state-of-the-art evolutionary algorithms, memetic algorithms, and hybrid evolutionary-local search demonstrate that the proposed framework yields robust and improved search performance.

At present, the successful transmission of drug‐resistant Mycobacterium tuberculosis, including multidrug‐resistant (MDR) and extensively drug‐resistant (XDR) strains, in human populations, threatens tuberculosis control worldwide. Differently from many other bacteria, M. tuberculosis drug resistance is acquired mainly through mutations in specific drug resistance‐associated genes. The panel of mutations is highly diverse, but depends on the affected gene and M. tuberculosis genetic background. The variety of genetic profiles observed in drug‐resistant clinical isolates underlines different evolutionary trajectories towards multiple drug resistance, although some mutation patterns are prominent. This review discusses the intrinsic processes that may influence drug resistance evolution in M. tuberculosis, such as mutation rate, drug resistance‐associated mutations, fitness cost, compensatory mutations and epistasis. This knowledge should help to better predict the risk of emergence of highly resistant M. tuberculosis strains and to develop new tools and strategies to limit the development and spread of MDR and XDR strains.

The recent spread of African swine fever (ASF) in the People's Republic of China and neighbouring countries in Asia has had significant economic consequences with an estimated direct cost of $55-$130 billion. This pandemic, originally detected in Republic of Georgia in 2007, has devastated the swine industry in large geographical areas of Southeast Asia with 14 countries reporting ASF outbreaks since the first documented case was confirmed in the city of Shenyang, Liaoning Province, China, on 3 August 2018. In the absence of any available vaccines, the control of ASF relies on the detection and culling of infected animals. The United States Department of Agriculture recently developed a recombinant experimental vaccine candidate, ASFV-G-ΔI177L, by deleting the I177L gene from the genome of the highly virulent pandemic ASFV strain Georgia, which efficaciouly protects pigs from the parental virus. Here, the initial studies were extended demonstrating that ASFV-G-ΔI177L is able to protect pigs against the virulent ASFV isolate currently circulating and producing disease in Vietnam with similar efficacy as reported against the Georgia strain. Comparative studies performed using a large number of pigs of European and Vietnamese origin demonstrated that a minimum protective dose of 10 2 HAD 50 of ASFV-G-ΔI177L equally protects animals of both breeds. In concurrence with those results, the onset of immunity in these animal breed showed appearance of protection in approximately one-third of the animals by the second week post vaccination, with full protection achieved by the fourth week post vaccination. Therefore, results presented here demonstrated that ASFV-G-ΔI177L is able to induce protection against virulent Vietnameese ASFV field strains and is effective in protecting local breeds of pigs as efficiently as previously shown for European cross-bred pigs. To our knowledge, this is the first report showing the efficacy of a Georgia 2007 based vaccine candidate in Asian breed of pigs or challenged with an Asian ASFV strain.

Over the recent years, there has been increasing research activities made on improving the efficacy of Memetic Algorithm (MA) for solving complex optimization problems. Particularly, these efforts have revealed the success of MA on a wide range of real world problems. MAs not only converge to high quality solutions, but also search more efficiently than their conventional counterparts. Despite the success and surge in interests on MAs, there is still plenty of scope for furthering our understanding on how and why synergy between populationbased and individual learning searchers would lead to successful Memetic Algorithms. In this paper we outline several important design issues of Memetic Algorithms and present a systematic study on each. In particular, we conduct extensive experimental studies on the impact of each individual design issue and their relative impacts on memetic search performances by means of three commonly used synthetic problems. From the empirical studies obtained, we attempt to reveal the behaviors of several MA variants to enhance our understandings on MAs.

Background African swine fever (ASF), caused by the ASF virus (ASFV), was first reported in Vietnam in 2019 and spread rapidly thereafter. Better insights into ASFV characteristics and early detection by surveillance could help control its spread. However, the pathogenicity and methods for early detection of ASFV isolates from Vietnam have not been established. Therefore, we investigated the pathogenicity of ASFV and explored alternative sampling methods for early detection. Results Ten pigs were intramuscularly inoculated with an ASFV strain from Vietnam (titer, 103.5 HAD50/mL), and their temperature, clinical signs, and virus excretion patterns were recorded. In addition, herd and environmental samples were collected daily. The pigs died 5–8 days-post-inoculation (dpi), and the incubation period was 3.7 ± 0.5 dpi. ASFV genome was first detected in the blood (2.2 ± 0.8) and then in rectal (3.1 ± 0.7), nasal (3.2 ± 0.4), and oral (3.6 ± 0.7 dpi) swab samples. ASFV was detected in oral fluid samples collected using a chewed rope from 3 dpi. The liver showed the highest viral loads, and ear tissue also exhibited high viral loads among 11 tissues obtained from dead pigs. Overall, ASFV from Vietnam was classified as peracute to acute form. The rope-based oral fluid collection method could be useful for early ASFV detection and allows successful ASF surveillance in large pig farms. Furthermore, ear tissue samples might be a simple alternative specimen for diagnosing ASF infection in dead pigs. Conclusions Our data provide valuable insights into the characteristics of a typical ASFV strain isolated in Vietnam and suggest an alternative, non-invasive specimen collection strategy for early detection.

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Endophytic microbes associated with medicinal plants are considered to be potential producers of various bioactive secondary metabolites. The present study investigated the distribution, antimicrobial activity and genetic features of endophytic actinomycetes isolated from the medicinal plant Cinnamomum cassia Presl collected in Hoa Binh province of northern Vietnam. Based on phenotypic characteristics, 111 actinomycetes were isolated from roots, stems and leaves of the host plants by using nine selective media. The isolated actinomycetes were mainly recovered from stems (n = 67; 60.4%), followed by roots (n = 29; 26.1%) and leaves (n = 15; 13.5%). The isolates were accordingly assigned into 5 color categories of aerial mycelium, of which gray is the most dominant (n = 42; 37.8%), followed by white (n = 33; 29.7%), yellow (n = 25; 22,5%), red (n = 8; 7.2%) and green (n = 3; 2.7%). Of the total endophytic actinomycetes tested, 38 strains (occupying 34.2%) showed antimicrobial activity against at least one of nine tested microbes and, among them, 26 actinomycetes (68.4%) revealed anthracycline-like antibiotics production. Analysis of 16S rRNA gene sequences deposited on GenBank (NCBI) of the antibioticproducing actinomycetes identified 3 distinct genera, including Streptomyces, Microbacterium, and Nocardia, among which Streptomyces genus was the most dominant and represented 25 different species. Further genetic investigation of the antibioticproducing actinomycetes found that 28 (73.7%) and 11 (28.9%) strains possessed genes encoding polyketide synthase (pks) and nonribosomal peptide synthetase (nrps), respectively. The findings in the present study highlighted endophytic actinomycetes from C. cassia Presl which possessed

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