Who\u27s to Blame? How Attributions of Blame Impact Perceptions of Effective Leaders

The objective of this study was to examine third-party observers’ perceptions of a coach and the leadership qualities that he exhibited when he engaged in different attributions of blame in a high-stakes scenario. When a leader blames himself for a negative outcome, there may be a link to transformational leadership such that the leader is actively caring about the well-being of his followers and putting them first. In contrast, when a leader blames one of his followers for a negative outcome, there may be a link to transactional leadership such that he is putting responsibility on a follower and dealing with an immediate concern (Eberlin & Tatum, 2008). Most of the research regarding leadership styles and blame has been conducted regarding businesses, so the current study aims to extend this research into a sport context by having undergraduate university participants (N = 57) read a scenario about a high school football player and his coach. Both individuals make a number of mistakes that result in the football team’s disqualification from the state playoffs. Individuals either read that the coach blamed the player for the disqualification, or that he blamed himself. Results showed that the coach was seen as more transformational and more competent when engaged in self-blame but was not seen as more transactional when engaged in player-blame. Additionally, results showed that all participants, regardless of condition, attributed the most blame to the player. The findings from the current study can inform best leadership practices in a sport context, as well as provide information on how undergraduate university students perceive effective leadership in relation to attributions of blame

Viscoelasticity mapping by identification of local shear wave dynamics

Estimation of soft tissue elasticity is of interest in several clinical applications. For instance, tumors and fibrotic lesions are notoriously stiff compared with benign tissue. A fully quantitative measure of lesion stiffness can be obtained by shear wave (SW) elastography. This method uses an acoustic radiation force to produce laterally propagating SWs that can be tracked to obtain the velocity, which in turn is related to Young's modulus. However, not only elasticity, but also viscosity plays an important role in the propagation process of SWs. In fact, viscosity itself is a parameter of diagnostic value for the detection and characterization of malignant lesions. In this paper, we describe a new method that enables imaging viscosity from SW elastography by local model-based system identification. By testing the method on simulated data sets and performing in vitro experiments, we show that the ability of the proposed technique to generate parametric maps of the viscoelastic material properties from SW measurements, opening up new possibilities for noninvasive tissue characterization.</p

Основы теории действий в условиях неопределенности

Цель исследования: рассмотреть теорию непредвиденных обстоятельств, включая взаимосвязь между непредвиденными ситуациями и управленческими показателями, на основе которых можно будет вывести алгоритм действий в условиях неопределенности для каждого предприятия в отдельности (так как не существует универсальных систем, которые можно применять в любой организации)

Synthetic Elastography using B-mode Ultrasound through a Deep Fully-Convolutional Neural Network

Shear-wave elastography (SWE) permits local estimation of tissue elasticity, an important imaging marker in biomedicine. This recently-developed, advanced technique assesses the speed of a laterally-travelling shear wave after an acoustic radiation force "push" to estimate local Young's moduli in an operator-independent fashion. In this work, we show how synthetic SWE (sSWE) images can be generated based on conventional B-mode imaging through deep learning. Using side-by-side-view B-mode/SWE images collected in 50 patients with prostate cancer, we show that sSWE images with a pixel-wise mean absolute error of 4.5+/-0.96 kPa with regard to the original SWE can be generated. Visualization of high-level feature levels through t-Distributed Stochastic Neighbor Embedding reveals substantial overlap between data from two different scanners. Qualitatively, we examined the use of the sSWE methodology for B-mode images obtained with a scanner without SWE functionality. We also examined the use of this type of network in elasticity imaging in the thyroid. Limitations of the technique reside in the fact that networks have to be retrained for different organs, and that the method requires standardization of the imaging settings and procedure. Future research will be aimed at development of sSWE as an elasticity-related tissue typing strategy that is solely based on B-mode ultrasound acquisition, and the examination of its clinical utility.Comment: (c) 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Blind source separation for clutter and noise suppression in ultrasound imaging:review for different applications

Blind source separation (BSS) refers to a number of signal processing techniques that decompose a signal into several 'source' signals. In recent years, BSS is increasingly employed for the suppression of clutter and noise in ultrasonic imaging. In particular, its ability to separate sources based on measures of independence rather than their temporal or spatial frequency content makes BSS a powerful filtering tool for data in which the desired and undesired signals overlap in the spectral domain. The purpose of this work was to review the existing BSS methods and their potential in ultrasound imaging. Furthermore, we tested and compared the effectiveness of these techniques in the field of contrast-ultrasound super-resolution, contrast quantification, and speckle tracking. For all applications, this was done in silico, in vitro, and in vivo. We found that the critical step in BSS filtering is the identification of components containing the desired signal and highlighted the value of a priori domain knowledge to define effective criteria for signal component selection

Views of general practice staff about the use of a patient-oriented treatment decision aid in shared decision making for patients with type 2 diabetes:A mixed-methods study

BACKGROUND: Decision aids can be used to support shared decision making (SDM). A patient-oriented treatment decision aid (DA) was developed for type 2 diabetes but its use by general practice staff appeared to be limited. OBJECTIVES: To explore views of practice staff towards SDM and the DA. DESIGN: A mixed-methods study within the Dutch PORTDA-diab trial. SETTING AND PARTICIPANTS: Included were 17 practices with staff members who were responsible for routine diabetes care and had worked with the DA, and 209 of their patients. METHODS: Interviews were conducted focusing on applicability, usefulness and feasibility of the DA. Interviews were tape-recorded, transcribed verbatim and subjected to content analysis for identifying and classifying views. Patient-reported data about the use of the DA were collected. Associations between specific views and use of the DA were tested using Pearson point-biserial correlation. RESULTS: The majority of practice staff expressed positive views towards SDM, which was associated with making more use of the DA. Most of the staff expressed that the DA stimulated a two-way conversation. By using the DA, several became aware of their paternalistic approach. Some staff experienced a conflict with the content of the DA, which was associated with making less use of the DA. CONCLUSIONS: The DA was considered useful by practice staff to support SDM. A positive view towards SDM was a facilitator, whereas experiencing a conflict with the content of the DA was a barrier for making use of the DA

Wastewater monitoring for detection of public health markers during the COVID-19 pandemic: Near-source monitoring of schools in England over an academic year

Background Schools are high-risk settings for infectious disease transmission. Wastewater monitoring for infectious diseases has been used to identify and mitigate outbreaks in many near-source settings during the COVID-19 pandemic, including universities and hospitals but less is known about the technology when applied for school health protection. This study aimed to implement a wastewater surveillance system to detect SARS-CoV-2 and other public health markers from wastewater in schools in England. Methods A total of 855 wastewater samples were collected from 16 schools (10 primary, 5 secondary and 1 post-16 and further education) over 10 months of school term time. Wastewater was analysed for SARS-CoV-2 genomic copies of N1 and E genes by RT-qPCR. A subset of wastewater samples was sent for genomic sequencing, enabling determination of the presence of SARS-CoV-2 and emergence of variant(s) contributing to COVID-19 infections within schools. In total, >280 microbial pathogens and >1200 AMR genes were screened using RT-qPCR and metagenomics to consider the utility of these additional targets to further inform on health threats within the schools. Results We report on wastewater-based surveillance for COVID-19 within English primary, secondary and further education schools over a full academic year (October 2020 to July 2021). The highest positivity rate (80.4%) was observed in the week commencing 30th November 2020 during the emergence of the Alpha variant, indicating most schools contained people who were shedding the virus. There was high SARS-CoV-2 amplicon concentration (up to 9.2x106 GC/L) detected over the summer term (8th June - 6th July 2021) during Delta variant prevalence. The summer increase of SARS-CoV-2 in school wastewater was reflected in age-specific clinical COVID-19 cases. Alpha variant and Delta variant were identified in the wastewater by sequencing of samples collected from December to March and June to July, respectively. Lead/lag analysis between SARS-CoV-2 concentrations in school and WWTP data sets show a maximum correlation between the two-time series when school data are lagged by two weeks. Furthermore, wastewater sample enrichment coupled with metagenomic sequencing and rapid informatics enabled the detection of other clinically relevant viral and bacterial pathogens and AMR. Conclusions Passive wastewater monitoring surveillance in schools can identify cases of COVID-19. Samples can be sequenced to monitor for emerging and current variants of concern at the resolution of school catchments. Wastewater based monitoring for SARS-CoV-2 is a useful tool for SARS-CoV-2 passive surveillance and could be applied for case identification and containment, and mitigation in schools and other congregate settings with high risks of transmission. Wastewater monitoring enables public health authorities to develop targeted prevention and education programmes for hygiene measures within undertested communities across a broad range of use cases

Monitoring occurrence of SARS-CoV-2 in school populations: A wastewater-based approach

Clinical testing of children in schools is challenging, with economic implications limiting its frequent use as a monitoring tool of the risks assumed by children and staff during the COVID-19 pandemic. Here, a wastewater-based epidemiology approach has been used to monitor 16 schools (10 primary, 5 secondary and 1 post-16 and further education) in England. A total of 296 samples over 9 weeks have been analysed for N1 and E genes using qPCR methods. Of the samples returned, 47.3% were positive for one or both genes with a detection frequency in line with the respective local community. WBE offers a low cost, non-invasive approach for supplementing clinical testing and can provide longitudinal insights that are impractical with traditional clinical testing

Donald J. Jamison Sr. v. Utah Home Fire Insurance Company : Brief of Respondent

Appeal from the Judgment of the Third Judicial District Court, Salt Lake County- Honorable Stewart M. Hanson, Jr