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Results of the Simulated Development regarding Rainfall on the Phenology involving Nitraria tangutorum underneath Very Dry out and also Wet Many years.
An ontology-mediated query (OMQ) consists of a database query paired with an ontology. When evaluated on a database, an OMQ returns not only the answers that are already in the database, but also those answers that can be obtained via logical reasoning using rules from ontology. There are many open questions regarding the complexities of problems related to OMQs. Motivated by the use of ontologies in practice, new reasoning problems which have never been considered in the context of ontologies become relevant, since they can improve the usability of ontology enriched systems. This thesis deals with various reasoning problems that emerge from ontology-mediated querying and it investigates the computational complexity of these problems. We focus on ontologies formulated in Horn description logics, which are a popular choice for ontologies in practice. In particular, the thesis gives results regarding the data complexity of OMQ evaluation by completely classifying complexity and rewritability questions for OMQs based on an EL ontology and a conjunctive query. Furthermore, the query-by-example problem, and the expressibility and verification problem in ontology-based data access are introduced and investigated.A most promising approach to answering queries in ontology-based data access (OBDA) is through query rewriting. In this paper we present novel rewriting approaches for several extensions of OBDA. The goal is to understand their relative expressiveness and to pave the way for efficient query answering algorithms.We present onto2problog, a tool that supports ontology-mediated querying of probabilistic data via probabilistic logic programming engines. Our tool supports conjunctive queries on probabilistic data under ontologies encoded in the description logic ELH dr , thus capturing a large part of the OWL 2 EL profile.
Due to the coronavirus disease 2019 (COVID-19) pandemic, nosocomial transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of great concern to clinicians of all specialties. Currently there are no published data available on the prevalence of the infection in ophthalmology patients presenting for intravitreal injection (IVI). The purpose of this retrospective study was to estimate the prevalence of SARS-CoV‑2 infection in patients presenting for IVI at our hospital.

Patients presenting for IVI in April 2020 at our hospital who had been screened for SARS-CoV‑2 infection using nasopharyngeal and oropharyngeal specimen for real-time reverse transcription polymerase chain reaction analysis were included in a retrospective study. To assess the representativity of this sample for IVI patients, characteristics were compared with patients presenting for IVI during March-April 2019.

The study included 279 patients and 319 historic control patients. Of 277 valid test results, one SARS-CoV‑2 positive patient was found, resulting in a carrier rate of 0.36% with a 95% Clopper-Pearson confidence interval of 0.01-1.99%. No differences in sex (57.7% vs.59.9% female,
 = 0.650), age (77.63 ± 10.29 vs.77.59 ± 10.94 years,
 = 0.962), and region of residence were found between groups.

The study provides an estimate for the prevalence of SARS-CoV‑2 infection in asymptomatic patients presenting for IVI. While these data may be used as a baseline, further research is needed to assess the development of SARS-CoV‑2 prevalence in this patient group in order to support risk assessment and infection prevention strategies.
The study provides an estimate for the prevalence of SARS-CoV‑2 infection in asymptomatic patients presenting for IVI. While these data may be used as a baseline, further research is needed to assess the development of SARS-CoV‑2 prevalence in this patient group in order to support risk assessment and infection prevention strategies.As social media become a staple for knowledge discovery and sharing, questions arise about how self-organizing communities manage learning outside the domain of organized, authority-led institutions. Yet examination of such communities is challenged by the quantity of posts and variety of media now used for learning. This paper addresses the challenges of identifying (1) what information, communication, and discursive practices support successful online communities, (2) whether such practices are similar on Twitter and Reddit, and (3) whether machine learning classifiers can be successfully used to analyze larger datasets of learning exchanges. This paper builds on earlier work that used manual coding of learning and exchange in Reddit 'Ask' communities to derive a coding schema we refer to as 'learning in the wild'. This schema of eight categories explanation with disagreement, agreement, or neutral presentation; socializing with negative, or positive intent; information seeking; providing resources; and comments about forum rules and norms. To compare across media, results from coding Reddit's AskHistorians are compared to results from coding a sample of #Twitterstorians tweets (n = 594). High agreement between coders affirmed the applicability of the coding schema to this different medium. LIWC lexicon-based text analysis was used to build machine learning classifiers and apply these to code a larger dataset of tweets (n = 69,101). This research shows that the 'learning in the wild' coding schema holds across at least two different platforms, and is partially scalable to study larger online learning communities.Physically-based methods in remote sensing provide benefits over statistical approaches in monitoring biophysical characteristics of vegetation. However, physically-based models still demand large computational resources and often require rather detailed informative priors on various aspects of vegetation and atmospheric status. Spectral invariants and photon recollision probability theories provide a solid theoretical framework for developing relatively simple models of forest canopy reflectance. Empirical validation of these theories is, however, scarce. Here we present results of a first empirical validation of a model based on photon recollision probability at the level of individual trees. selleck chemicals Multiangular spectra of pine, spruce, and oak tree seedlings (height = 0.38-0.7 m) were measured using a goniometer, and tree hemispherical reflectance was derived from those measurements. We evaluated the agreement between modeled and measured tree reflectance. The model predicted the spectral signatures of the tree seedlings in the wavelength range between 400 and 2300 nm well, with wavelength-specific bias between -0.
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