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Objective To analyze the epidemic characteristics of hand foot and mouth disease (HFMD) in Sichuan province from 2017 to 2021 and to provide evidence for prevention and control. Methods A descriptive analysis was conducted by downloading the case-data of HFMD in Sichuan province during 2017 to 2021 from the Chinese National Notifiable Infectious Disease Reporting System. Results A total of 442 079 cases of HFMD were reported from 2017 to 2021, including 627 severe cases and 4 deaths. The average annual incidence rate was 106.17/100 000.Cases in children aged 5 or younger accounted for 90.99%. Boys had higher incidence than girls (1.35:1). The scattered children accounted for 63.34%. Two peaks of incidence were observed other years, except for a few years, with the highest occurring between April to July and the second occurring in November to December. The incidence in Chengdu plain and its surrounding areas were significantly higher than other regions. Other enteroviruses (non-enterovirus 71 and Coxsackie virus A16) were the main pathogen, accounting for 71.45%; Coxsackie virus A16 accounted for 21.20% and enterovirus 71 accounted for 7.35%. Conclusion The incidence of HFMD in Sichuan Province is high from 2017 to 2021. The proportion of severe cases has significantly decreased (χ² = 273.241, P <0.001), and the main pathogen is the other enteroviruses (non-enterovirus 71 and Coxsackie virus A16). [ABSTRACT FROM AUTHOR]

Sporotrichosis is a subacute or chronic infectious disease caused by sporothrix. It is mainly caused by Sporothrix inoculation after accidental skin injury during human labor. The clinical manifestations of sporotrichosis are variable, ranging from nodules, plaques, ulcers, verrucous lesions, and subcutaneous masses. Some reports indicate that sporotrichosis can mimic psoriasis-like lesions. We herein report a case of sporotrichosis mimicking rosacea lesions. In addition, the patient had a history of nasal trauma, and we believe that the patient was inoculated with Sporothrix after the nasal skin was damaged during labor activities. The patient was given itraconazole 200 mg orally daily for 3 months, which effectively resolved the rash. [ABSTRACT FROM AUTHOR]

A *memory consistency model* (or simply *memory model*) defines the possible values that a shared-memory read may return in a multithreaded programming language. Choosing a memory model involves an inherent performance-programmability tradeoff. The Java language has adopted a *relaxed* (or *weak*) memory model that is designed to admit most traditional compiler optimizations and obviate the need for hardware fences on most shared-memory accesses. The downside, however, is that programmers are exposed to a complex and unintuitive semantics and must carefully declare certain variables as `volatile` in order to enforce program orderings that are necessary for proper behavior. This paper proposes a simpler and stronger memory model for Java through a conceptually small change: *every* variable has `volatile` semantics by default, but the language allows a programmer to tag certain variables, methods, or classes as `relaxed` and provides the current Java semantics for these portions of code. This *volatile-by-default* semantics provides *sequential consistency* (SC) for all programs by default. At the same time, expert programmers retain the freedom to build performance-critical libraries that violate the SC semantics. At the outset, it is unclear if the `volatile`-by-default semantics is practical for Java, given the cost of memory fences on today's hardware platforms. The core contribution of this paper is to demonstrate, through comprehensive empirical evaluation, that the `volatile`-by-default semantics is arguably acceptable for a predominant use case for Java today -- server-side applications running on Intel x86 architectures. We present VBD-HotSpot, a modification to Oracle's widely used HotSpot JVM that implements the `volatile`-by-default semantics for x86. To our knowledge VBD-HotSpot is the first implementation of SC for Java in the context of a modern JVM. VBD-HotSpot incurs an average overhead versus the baseline HotSpot JVM of 28% for the Da Capo benchmarks, which is significant though perhaps less than commonly assumed. Further, VBD-HotSpot incurs average overheads of 12% and 19% respectively on standard benchmark suites for big-data analytics and machine learning in the widely used Spark framework.