Notes

Pregnancy results in people along with structurel coronary disease: a single center experience.
The genus Klebsiella comprises species that cause nosocomial and community-acquired infections. A dataset was created to compile the sequence type (ST) and capsule type (K-locus) information predicted for 172 worldwide isolates of Klebsiella spp. whose complete genomes could be retrieved from the GenBank (NCBI) repository. The dataset also includes information related to one multidrug-resistant strain (B31) isolated from a patient who was admitted to an intensive care unit in the Northeast region of Brazil. This strain was phenotypically characterized and submitted to whole-genome sequencing and comparative genomics analysis as we recently reported [1]. The dataset also compiles information on Pathogenicity Islands (PIs), Resistance Islands (RIs) and Miscellaneous Islands (MIS) present in the genome of strain B31. The information provided here may support outbreak prevention policies and future epidemiological studies involving Klebsiella spp.The dataset presented in this article supports "Intensive livestock farming as a major determinant of the exposure to anticoagulant rodenticides in raptors of the Canary Islands (Spain)" (Rial-Berriel et al., 2020). A Geographic Information System (GIS) analysis on the influence of the influence of livestock activity on exposure to anticoagulant rodenticides in raptors in the Canary Islands was performed. This dataset provides geographic information on the localization of each raptor (either positive or negative for anticoagulant rodenticides, n = 308), as well as the concentrations of each compound found in their livers. In addition, we present complementary analyses to those included in the main article, such as the detailed analysis of the farming activity influence on anticoagulant rodenticide exposure of raptors, by island and by raptor species.The Mw7.5 Palu-Donggala earthquake occurred on 28 September 2018 and caused significant damage in Palu City and the surrounding Central Sulawesi region of Indonesia. The earthquake initiated a series of catastrophic landslides (classified as flowslides) [1,2], collapsed buildings, and generated tsunami waves that impacted Palu Bay's coast. The earthquake claimed over 4000 lives, making it the deadliest natural disaster of 2018. We performed a post-earthquake field reconnaissance and collected perishable data at the sites of five significant flowslides (named for the communities where they occurred Balaroa, Petobo, Lolu Village, Jono Oge, and Sibalaya), as well as at other damage locations in the mesoseismal region. Our field team consisted of five U.S.-based members, who were sponsored by the U.S. National Science Foundation-supported Geotechnical Extreme Events Reconnaissance (GEER) organization [3], in collaboration with geologists, geotechnical engineers, and other researchers from Indonesia's Center for Eonnaissance dataset is openly available on DesignSafe [6]. The data collected by the field team and subsequent mapping efforts, which document the morphology and patterns of movements of the flowslides, may be used by researchers studying liquefaction-induced flowslides. In addition, the displacement mapping provides a unique dataset for researchers who are calibrating and verifying simulation models of landslide displacements, or who are seeking a validation dataset for image correlation analysis (including machine learning routines). This dataset is associated with original research presented in ";East Palu Valley Flowslides Induced by the 2018 MW 7.5 Palu-Donggala Earthquake" [1] and also is the basis of research presented by Gallant et al. [2].A total of 80 participants were recruited from three private middle SES schools of Rahim Yar Khan, Pakistan to explore the narrative skills development in Urdu-speaking preschoolers aged between 4-and-5 years. Data collection was completed using a two-stage sampling technique (convenience and purposive). After obtaining parental consent, the participants were screened for their intellectual functioning. Three personal narrative samples, using conversational maps, were collected from the participants who passed the screening. The narrative data were analysed on both macro and microstructural levels by using high point analysis and use of cohesions (conjunctive and referential), mean length of utterances in words (MLUw), the total number of words (TNW), and the number of different words (NDW). The data presented here include age and gender of participants, their scores on the verbal IQ test, the scores obtained on macro-and microstructural levels. The results based on differences and relationships of the data obtained are published somewhere else [1]. The data can be reused by comparing the obtained figures with the adult population, children from different age bands, children with different developmental disorders, and at cross-linguistic levels as narratives are said to be significantly influenced by cultures.This document contains supplemental material for the paper [2]. The notations in this document are the same as in [2]. In particular, we first present here the proof of Theorem 1 in [2]. This theorem expresses the locally most powerful unbiased (LMPU) test, which is a general method for local detection, in the presence of known nuisance parameters. Second, we present here the Matlab code of the LMPU and the generalized LMPU for the special case of detection of a small deviation in the frequency of sinusoidal signals, which arises in various signal processing applications.Covid-19 pandemic has spread fast almost all countries in the world including Indonesia. In order to slow such pandemic confirmed cases, Indonesian local and central governments apply a lockdown-like policy. We call this Large-Scale Social Restriction (Pembatasan Sosial Berskala Besar, known as PSBB) and PSBB-variant that is Expanded and Tightened Social Restriction or Pembatasan Sosial yang Diperluas dan Diperketat (PSDD). In this paper, we present number of cases and case fatality rate before, during and after such lockdown-like policy. This article contains Covid-19 risk data of several cities and provinces in Indonesia. We have used central and local government Covid-19 tracking sites to determine the daily risks for several cities and provinces in Indonesia. Bcl-2 lymphoma All data were extracted on August 22, 2020. We developed these data and calculated daily rate of confirmed and active cases, case fatality rate and rate of case fatality rate before, during and after lockdown-like policy. Furthermore, such risk modeling is used to forecast of what so-called Value-at-Risk (VaR).
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