Satisfiers and Hygiene Factors: Residents' Perceptions of Strengths and Limitations of Their Learning Environment

Abstract Background Efforts are underway to enhance learner input into the accreditation of educational programs, including residencies and fellowships. Objectives To aggregate the perspectives of residents and fellows from a cross-section of specialties to highlight common dimensions in learners' perceptions of strengths and opportunities for improvement (OFIs) in their program and to assess whether the ACGME Resident Survey captures areas important to residents' perceptions of their learning environment. Results The data set included 206 core and 193 subspecialty programs representing a wide range of specialties and subspecialties. Comments on strengths and OFIs addressed most of the items in the Resident Survey, with items not addressed in the survey also not represented in the ACGME requirements. The findings suggest that some program attributes are mentioned only in their absence (hygiene factors), whereas other dimensions (satisfiers), particularly quality and quantity of residents' interactions with faculty, procedural volume, and variety and didactic offerings, are critical to learners' perceptions of the quality of their learning environment. For some strengths, residents indicated their programs exceeded the ACGME standards, and for areas identified as OFIs, comments suggested programs were in compliance, but the residents desired more. Mentioned in this context were opportunities to perform research, access to board preparation courses and career counseling, and availability of new technology, including new patient care modalities. Conclusions The findings allow insight into program attributes important to residents' perceptions of their learning environment. Programs may find the results helpful in suggesting areas for improvement in their learning environment.

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Opportunities to improve the measurement of audit quality: a call for collaboration between the profession and academics

Maandblad Voor Accountancy en Bedrijfseconomie ◽

10.5117/mab.90.31359 ◽

2016 ◽

Vol 90 (9) ◽

pp. 352-351 ◽

Cited By ~ 2

Author(s):

Jeroen van Raak ◽

Ulrike Thürheimer

Keyword(s):

Audit Quality ◽

Audit Fees ◽

Class Action ◽

Financial Statement ◽

Accrual Quality ◽

Wide Range ◽

External Stakeholders ◽

Insight Into ◽

Considerable Doubt

Audit research relies on a wide range of publicly available measures to examine which factors influence the quality of financial statement audits. While research to date has to rely largely on remote proxies due to a lack of access to proprietary data, there is considerable doubt about the validity of these proxies and the inferences drawn based on these proxies. In order to provide insight into the reliability of these measures, Rajgopal, Srinivasan & Zheng (2015) investigate whether commonly used proxies for audit quality (i.e. auditor size, abnormal audit fees, accrual quality, and the propensity to meet and beat analyst targets) are associated with deficiencies reported in SEC investigations and class-action lawsuits. Such alleged deficiencies reflect how external stakeholders assess audit performance. Their study indicates that the use of such proxies is highly problematic and that the performance of these measures, with the exception of auditor size, is poor.

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Panoramic stitching of heterogeneous single-cell transcriptomic data

10.1101/371179 ◽

2018 ◽

Cited By ~ 17

Author(s):

Brian Hie ◽

Bryan Bryson ◽

Bonnie Berger

Keyword(s):

Single Cell ◽

Cell Types ◽

Data Sets ◽

Cell Type ◽

Data Set ◽

Wide Range ◽

Data Set Integration ◽

Biological Patterns ◽

Insight Into ◽

Comprehensive Reference

AbstractResearchers are generating single-cell RNA sequencing (scRNA-seq) profiles of diverse biological systems1–4 and every cell type in the human body.5 Leveraging this data to gain unprecedented insight into biology and disease will require assembling heterogeneous cell populations across multiple experiments, laboratories, and technologies. Although methods for scRNA-seq data integration exist6,7, they often naively merge data sets together even when the data sets have no cell types in common, leading to results that do not correspond to real biological patterns. Here we present Scanorama, inspired by algorithms for panorama stitching, that overcomes the limitations of existing methods to enable accurate, heterogeneous scRNA-seq data set integration. Our strategy identifies and merges the shared cell types among all pairs of data sets and is orders of magnitude faster than existing techniques. We use Scanorama to combine 105,476 cells from 26 diverse scRNA-seq experiments across 9 different technologies into a single comprehensive reference, demonstrating how Scanorama can be used to obtain a more complete picture of cellular function across a wide range of scRNA-seq experiments.

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Feeding Mathematical Modeling of Superalloy Vacuum-Electromagnetic Casting and its Application

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.629.171 ◽

2012 ◽

Vol 629 ◽

pp. 171-175

Author(s):

Wen Zhong Jin ◽

Su Fang Li ◽

Wei Zhang

Keyword(s):

Mathematical Modeling ◽

Mathematical Model ◽

New Technology ◽

Experimental Results ◽

Electromagnetic Stirring ◽

Shrinkage Cavity ◽

Vacuum Casting ◽

Electromagnetic Casting ◽

Wide Range

The new technology of superalloy vacuum-electromagnetic casting was developed and the feeding mathematical model melt in vacuum-electromagnetic casting was established. The availability of mathematical model was approved by the experiments of the IN100 superalloy. The experimental results indicate that the feeding capacity of melt in vacuum casting can be greatly increased by imposing the 50Hz, 60A rotating electromagnetic stirring, which can decrease the central shrinkage cavity in superalloy ingots, so the quality of the superalloy ingots can be wide-range improved.

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Multidimensional phenotyping predicts lifespan and quantifies health in C. elegans

10.1101/681197 ◽

2019 ◽

Cited By ~ 1

Author(s):

Céline N. Martineau ◽

André E. X. Brown ◽

Patrick Laurent

Keyword(s):

Simple Model ◽

Objective Measure ◽

Quantitative Model ◽

Model Organisms ◽

Wild Type ◽

Data Set ◽

C Elegans ◽

Wide Range ◽

Initial Hypothesis

AbstractAgeing affects a wide range of phenotypes at all scales, but an objective measure of ageing remains challenging, even in simple model organisms. We assumed that a wide range of phenotypes at the organismal scale rather than a limited number of biomarkers of ageing would best describe the ageing process. Hundreds of morphological, postural and behavioural features are extracted at once from high resolutions videos. A quantitative model using this multi-parametric dataset can predict the biological age and lifespan of individual C. elegans. We show that the quality of predictions on a held-out data set increases with the number of features added to the model, supporting our initial hypothesis. Despite the large diversity of ageing mechanisms, including stochastic insults, our results highlight a robust ageing trajectory, but variable ageing rates along that trajectory. We show that healthspan, which we defined as the range of abilities of the animals, is correlated to lifespan in wild-type worms.

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Managing Nitrogen, Potassium, and Boron in New Guinea Impatiens: Is More Better?

HortScience ◽

10.21273/hortsci.39.4.777b ◽

2004 ◽

Vol 39 (4) ◽

pp. 777B-777

Author(s):

Dharmalingam S. Pitchay* ◽

Jonathan M. Frantz ◽

Jonathan M. Locke ◽

Charles Krause

Keyword(s):

New Guinea ◽

Production Costs ◽

Plant Performance ◽

Nutrient Deficiencies ◽

Tissue Samples ◽

Wide Range ◽

New Guinea Impatiens ◽

Reflectance Measurements ◽

Insight Into

Growers tend to over fertilize their plants as a way to minimize the likelihood of encountering nutrient deficiencies that would reduce the quality of their plants. Much of the nutrition literature focuses on the nutritional extremes namely of toxicity and deficiency. Once plants get to this stage, little can be done to correct the problem. Characteristics of plant performance in super-optimal conditions, yet below toxic levels, is less well known, and needs to be developed to help growers identify problems in their production practices before they impact sales. New Guinea Impatiens were grown over a wide range of N, K, and B levels, from 15% to 400% full strength Hoagland's solution for each nutrient after establishing transplanted rooted cuttings in a peat: perlite soilless media. Plants were grown for four weeks during treatment, during which time the flowers were pinched. After only 2 weeks of treatment, plants with 200% and 400% N were significantly shorter than control plants and plants with 15% N. Reflectance measurements and photographs were made twice a week. At the end of the four weeks, plant tissue was analyzed for form of N, root development and structure, and leaf area. Tissue samples were also analyzed with SEM and energy dispersive X-ray analysis to determine changes in nutrient location and tissue structure. This data provides insight into the nutrition economy of plants in general, tests the use of reflectance spectrometry as a method of detecting super-optimal fertilizer concentrations, and will help growers optimize their fertilization requirements to reduce production costs yet maintain high plant quality.

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Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening

SLAS DISCOVERY Advancing Life Sciences ◽

10.1177/2472555220919345 ◽

2020 ◽

Vol 25 (6) ◽

pp. 655-664

Author(s):

Wienand A. Omta ◽

Roy G. van Heesbeen ◽

Ian Shen ◽

Jacob de Nobel ◽

Desmond Robers ◽

...

Keyword(s):

Machine Learning ◽

Training Set ◽

Data Set ◽

Genome Wide ◽

Machine Learning Model ◽

Exploratory Data ◽

Interfering Rna ◽

Insight Into ◽

Training Sets

There has been an increase in the use of machine learning and artificial intelligence (AI) for the analysis of image-based cellular screens. The accuracy of these analyses, however, is greatly dependent on the quality of the training sets used for building the machine learning models. We propose that unsupervised exploratory methods should first be applied to the data set to gain a better insight into the quality of the data. This improves the selection and labeling of data for creating training sets before the application of machine learning. We demonstrate this using a high-content genome-wide small interfering RNA screen. We perform an unsupervised exploratory data analysis to facilitate the identification of four robust phenotypes, which we subsequently use as a training set for building a high-quality random forest machine learning model to differentiate four phenotypes with an accuracy of 91.1% and a kappa of 0.85. Our approach enhanced our ability to extract new knowledge from the screen when compared with the use of unsupervised methods alone.

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Method for Gauging Usage Opportunities for Partially Automated Vehicles with Application to Public Travel Survey Data Sets

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2625-05 ◽

2017 ◽

Vol 2625 (1) ◽

pp. 43-50

Author(s):

Kenneth P. Laberteaux ◽

Karim Hamza ◽

Alan Berger ◽

Casey L. Brown

Keyword(s):

Fuzzy Inference ◽

Automated Driving ◽

Data Set ◽

Inference System ◽

Travel Survey ◽

Human Driver ◽

Wide Range ◽

Light Duty Vehicle ◽

Vehicle Automation

Vehicle automation has garnered a significant amount of interest in recent years. When the automated driving (AD) capability of a vehicle is assessed, it is important to distinguish between full automation, in which no human driver is required, and partial automation, in which a human driver may be required to intervene or take control of the vehicle occasionally for portions of the trip. This paper presents a method for assessing usage opportunities of partial AD in light-duty vehicle fleets. Key assumptions are that ( a) the longer the time fraction of driving in which AD is active, the better, and ( b) drivers will value having longer contiguous sections of AD-active time over having to frequently regain vehicle control. Given second-by-second records of real-world driving trips, the method uses a fuzzy inference system to estimate the fraction of driving time at a certain quality-of-use level. Performing the quality-of-use assessment for all trips and vehicles in a representative data set can then provide insight into the fraction of the population that would likely find partial AD desirable. To demonstrate the proposed method, data on vehicle trips from public travel surveys in California (California Household Travel Survey) and Atlanta, Georgia (Atlanta Regional Commission Travel Survey), were used along with simplified prototypical models for partial AD. Simulation results were generally in agreement with common perceptions but showed a wide range of possibilities, which could have been narrowed down further when more detailed trip data became available.

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User Adoption Of Internet Of Things: Determining Factors That Directly Affect Internet Of Things Service Adoption And Applying Them To An Existing System

10.32920/ryerson.14653911.v1 ◽

2021 ◽

Author(s):

Revathi Gopalakrishnan

Keyword(s):

Internet Of Things ◽

Technology Acceptance ◽

New Technology ◽

Intention To Use ◽

Service Adoption ◽

User Adoption ◽

Determining Factors ◽

Acceptance Model ◽

Insight Into

Internet of Things (IoT) is defined as a convergence of multiple technologies that interconnect physical and virtual objects over a network to improve our quality of life. These services deal with numerous interactions between devices, each having its own functionality and user flows. A large emphasis has always been placed on the technical aspects of IoT but very little importance has been given to researching factors that could have a significant effect on a user’s intention to use and adopt these services. Technology Acceptance Model (TAM) and Value-based Adoption Model (VAM) are two of the most widely used models to discovering the potential user’s intention to use a new technology. This paper examines these models to provide insight into determining factors that directly affect IoT service adoption by users and applies it to developing a coherent and engaging user interface for an existing IoT system.

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IMPROVEMENT OF INFORMATION SUPPORT FOR THE FUNCTIONING OF THE INCLUSIVE EDUCATION SYSTEM

Educational Analytics of Ukraine ◽

10.32987/2617-8532-2021-2-82-92 ◽

2021 ◽

pp. 82-92

Author(s):

Andrii Lytvynchuk ◽

◽

Hanna Tereshchenko ◽

Andrii Kyrianov ◽

Ivan Gaiduk ◽

...

Keyword(s):

Inclusive Education ◽

Education System ◽

Individual Development ◽

Automated System ◽

Information Support ◽

Educational Services ◽

Special Educational Needs ◽

Data Set ◽

Wide Range

The purpose of the article is to study current trends and ways of improving information support for the functioning of an inclusive education system in Ukraine. The automated system of inclusive resource center (AS «IRC») is defined as a set of software and hardware, based on information and telecommunication technologies provide for the creation of a single integrated information space in inclusive education for the processing of the information generated by the operation of the AS «IRC» and their information support. It is determined that through AS «IRC» teachers of general secondary education institutions and preschool institutions have the opportunity to compile individual development programs for children with special educational needs (SEN), using the findings previously developed by the experts of the inclusive resource centre. EMIS features are described in Ukraine, which operates by collecting information on enrolment, attendance, grade repetition, expulsion from school and graduation. A template is provided for the minimum recommended set of questions to identify children with SEN. Such monitoring makes it possible to identify and detail the difficulties faced by children / teachers, in contrast to the exclusive identification of disability (a certain nosology that is medically confirmed). The development of an inclusive education system in Ukraine is moving towards ensuring the availability and quality of educational services for children with SEN, which aims to improve the quality of information support. In the process of improving the functioning of the AS «IRC» indicators of inclusive education, it is necessary to ensure an organic combination of data already contained in the system with the data set (indicators) that will be collected to assess the effectiveness of educational services in the inclusive education segment. It is substantiated that data sets on the development of inclusive education should be clearly and consistently defined, and should include a wide range of information on children with SEN.

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iEVENT INFORMATION : MEDIA INFORMASI DAN PUBLIKASI JADWAL KEGIATAN KAMPUS

CCIT Journal ◽

10.33050/ccit.v6i3.366 ◽

2013 ◽

Vol 6 (3) ◽

pp. 372-389

Author(s):

Ary Budi Warsito ◽

Untung Rahardja ◽

Aghnia Sabila

Keyword(s):

Reference Material ◽

Support System ◽

Teaching And Learning ◽

New Technology ◽

Learning System ◽

Quality Of Education ◽

Wide Range ◽

The World ◽

Information Media

Liabilities to document an event in the world of education is the provision that created in order to improve the quality and the quality of education in Indonesia. As well as reference material that can be used as an ingredient to evaluate a wide range of events that have been implemented. So, to support this Perguruan Tinggi Raharja which is one institution that engages in computer science is always innovative and creative in order to solve these problems, by applying an iLearning learning system, based on 4B (Belajar, Bekerja, Bermain, and Berdoa) by using a new technology device, iPad. In iLearning, learning system of teaching and learning process requires the applications contained in the iPad. Based on the results of surveys and studies have been performed, have not all applications support are included in the iPad, especially applications that can support the process of making and publication about events that are held, so it created one of the supporting applications as one of the iEvent Information applications that support system, especially in terms of learning iLearning publicize campus events that have been held or to be carried out.

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