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The dataset SCARED-C is introduced in the context of assessing robustness in endoscopic depth prediction models. It is part of the EndoDepth benchmark, which is designed to evaluate the performance of monocular depth prediction models specifically for endoscopic scenarios. The dataset features 16 different types of image corruptions, each with five levels of severity, encompassing challenges like lens distortion, resolution alterations, specular reflection, and color changes that are typical in endoscopic imaging. The purpose of SCARED-C is to test the robustness of depth estimation models by exposing them to various common endoscopic corruptions. This dataset is a valuable tool for developing and evaluating depth prediction algorithms that can handle the unique challenges presented by endoscopic procedures, ensuring more accurate and reliable outcomes in medical imaging.

Introduction: The Burden of Nursing Care has not been defined as a theoretical or operational concept, however, there are several studies that demonstrate its impact on the quality of nursing care, the increase of adverse events and the health of nursing staff. Objective: To analyze attributes, factors, antecedents, and consequences linked to the concept of Nursing Care Burden in order to clarify its meaning. Materials and Methods: Concept analysis based on Walker and Avant's methodological proposal, through which the characteristics that define a concept with its attributes are examined. Results: The burden of nursing care is the relationship between patient needs and the time available for direct activities, management, and education. Both intrinsic and extrinsic patient factors can influence the patient's level of dependency and needs, increasing nursing interventions and hours of care, thus impacting the burden of care. Discussion: The Nursing Burden of Care involves patient-centered care with adequate resources. It requires planning and leadership on the part of the nursing professional. Lack of competencies and experience, coupled with institutional inflexibility, increases the burden, and leads to dissatisfaction and adverse events. Conclusions: The burden of nursing care is a concept with epistemic grounding in the interactive-integrative view, since it focuses on meeting patients' needs through direct care nursing interventions, management, and education.

SWOT Data Collection

This dataset contains the output folder compiled by SeqLengthPlot applied to the toxin candidates identified by DeTox in the paired-end of Savalia savaglia. The folder seq_length_DeTox_output_Ss_PE_candidate_toxins contains: • seq_above99aa.fasta: Retrieved FASTA file containing the toxin candidates with lengths of 100 aa and above, after splitting the input FASTA file based on the given threshold. • seq_below100bp.fasta: Retrieved FASTA file containing the toxin candidates with lengths below 100 aa, after splitting the input FASTA file based on the given threshold. • seq_length_distribution_above99aa.png: PNG image file showing a histogram of toxin candidate lengths of 100 aa and above on a linear scale. • seq_length_distribution_above99_log.png: PNG image file showing a histogram of toxin candidate lengths of 100 aa and above on a logarithmic scale. • seq_length_distribution_below100aa.png: PNG image file showing a histogram of toxin candidate lengths below 100 aa on a linear scale. • seq_length_distribution_below100_log.png: PNG image file showing a histogram of toxin candidate lengths below 100 aa on a logarithmic scale. • seq_length_stats_by_threshold_100.txt: Text file containing detailed statistics of the toxin candidate lengths in the input FASTA file, including the total number of sequences, the number of sequences 100 aa and above, the number of sequences below 100 aa, and the corresponding minimum and maximum lengths.

This is pre/post data of testing data of nurse practitioner students following educational preparation with simulation.

Assessment risk of collapse for Aparados da Serra Geral Cloud Forests

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An Atomic Force Microscope (AFM) is a type of microscope that belongs to a family of microscopes known as Scanning Probe Microscopes (SPMs). Such microscopes use a physical probe tip, mounted on a cantilever, that is scanned back and forth, in a raster pattern, over the sample surface. In a way, this method can be likened to a blind man who uses a stick to “see” the terrain on which he is on. The deflection of the AFM cantilever as the probe tip moves over the sample surface is tracked by a laser beam that is reflected at the back side of the AFM cantilever. A position sensitive photodetector detects the deflection of the laser and such information is used in the feedback loop to create a 3D topographic image after the scanning process. An AFM is an SPM that makes use of the electrostatic forces between the cantilever tip and the sample to generate an image. A magnetic force microscope (MFM) is an SPM makes use of magnetic forces, while a scanning tunneling microscope (STM) is an SPM that uses the electrical current flowing between the sample and the cantilever tip. The AFM was developed to overcome the challenges faced by its predecessor, the STM. Unlike the STM, which can only image conducting or semiconducting samples, an AFM can image conducting and semiconducting materials, as well as polymers, ceramics, composites, and biological samples. Depending on the information that is needed, the AFM can be operated in two basic modes of imaging. The first one is called the Static or Contact Mode. The second mode is known as the Dynamic Mode under which we have the Tapping (intermittent contact mode) and the Non-Contact Mode. In this activity, we are going to visualize and analyze AFM data using Gwyddion, a free and Open-Source software for visualizing and analyzing data obtained using Scanning Probe Microscopy techniques, like AFM. The said software can be used for general height field and image processing. Gwyddion can be downloaded from http://gwyddion.net/download.php. Image processing of AFM data are of two kinds: First, are those processes that compensate for instrument defects or to remove artifacts, and the second, are processes that quantify surface information.

Original input and output of calculation using 4*4*4 supercell and 2*2*2 kpoint. Meaning of the content can be guessed according to the names of the files. For example, nebIn is CI-NEB calculation of nitrogen interstitial In.

Included are 1) the resultant clustering locations for perturbation, sway referenced, and cross-task EEG sources, 2) the relative frequency band power for each participant of their respective fronto-central cross-task cluster, and 3) the relative frequency power for each participant of the source representing N1 or event-related response during the perturbation task. Participants were randomized into two groups (cTBS over SMA, or SHAM cTBS; n = 10 each) and completed both standing balance tasks with eyes closed.