scholarly journals Lost in translation

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 620 ◽  
Author(s):  
Parashkev Nachev ◽  
Geraint Rees ◽  
Richard Frackowiak
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Explanatory Models ◽  
Neural Systems ◽  
Individual Level ◽  
Large Scale Data ◽  
The Individual ◽  
Adaptive Nature ◽  
Lost In Translation ◽  
The Brain

Translation in cognitive neuroscience remains beyond the horizon, brought no closer by supposed major advances in our understanding of the brain. Unless our explanatory models descend to the individual level—a cardinal requirement for any intervention—their real-world applications will always be limited. Drawing on an analysis of the informational properties of the brain, here we argue that adequate individualisation needs models of far greater dimensionality than has been usual in the field. This necessity arises from the widely distributed causality of neural systems, a consequence of the fundamentally adaptive nature of their developmental and physiological mechanisms. We discuss how recent advances in high-performance computing, combined with collections of large-scale data, enable the high-dimensional modelling we argue is critical to successful translation, and urge its adoption if the ultimate goal of impact on the lives of patients is to be achieved.

scholarly journals Lost in translation

F1000Research ◽  
2019 ◽  
Vol 7 ◽  
pp. 620 ◽  
Author(s):  
Parashkev Nachev ◽  
Geraint Rees ◽  
Richard Frackowiak
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Explanatory Models ◽  
Neural Systems ◽  
Individual Level ◽  
Large Scale Data ◽  
The Individual ◽  
Adaptive Nature ◽  
Lost In Translation ◽  
The Brain

Translation in cognitive neuroscience remains beyond the horizon, brought no closer by supposed major advances in our understanding of the brain. Unless our explanatory models descend to the individual level—a cardinal requirement for any intervention—their real-world applications will always be limited. Drawing on an analysis of the informational properties of the brain, here we argue that adequate individualisation needs models of far greater dimensionality than has been usual in the field. This necessity arises from the widely distributed causality of neural systems, a consequence of the fundamentally adaptive nature of their developmental and physiological mechanisms. We discuss how recent advances in high-performance computing, combined with collections of large-scale data, enable the high-dimensional modelling we argue is critical to successful translation, and urge its adoption if the ultimate goal of impact on the lives of patients is to be achieved.

Evaluation of Large-scale Data to Detect Irregularity in Payment for Medical Services

2016 ◽  
Vol 55 (03) ◽  
pp. 284-291
Author(s):  
Junghyun Park ◽  
Seokjoon Yoon ◽  
Minki Kim
Keyword(s):  
Large Scale ◽  
Healthcare Sector ◽  
Benford’S Law ◽  
Individual Level ◽  
Large Scale Data ◽  
Level Data ◽  
Depth Analysis ◽  
Benford's Law ◽  
The Individual ◽  
Scale Data

SummaryBackground: Sophisticated anti-fraud systems for the healthcare sector have been built based on several statistical methods. Although existing methods have been developed to detect fraud in the healthcare sector, these algorithms consume considerable time and cost, and lack a theoretical basis to handle large-scale data.Objectives: Based on mathematical theory, this study proposes a new approach to using Benford’s Law in that we closely examined the individual-level data to identify specific fees for in-depth analysis.Methods: We extended the mathematical theory to demonstrate the manner in which large-scale data conform to Benford’s Law. Then, we empirically tested its applicability using actual large-scale healthcare data from Korea’s Health Insurance Review and Assessment (HIRA) National Patient Sample (NPS). For Benford’s Law, we considered the mean absolute deviation (MAD) formula to test the large-scale data.Results: We conducted our study on 32 diseases, comprising 25 representative diseases and 7 DRG-regulated diseases. We performed an empirical test on 25 diseases, showing the applicability of Benford’s Law to large-scale data in the healthcare industry. For the seven DRG-regulated diseases, we examined the individual-level data to identify specific fees to carry out an in-depth analysis. Among the eight categories of medical costs, we considered the strength of certain irregularities based on the details of each DRG-regulated disease.Conclusions: Using the degree of abnormality, we propose priority action to be taken by government health departments and private insurance institutions to bring unnecessary medical expenses under control. However, when we detect deviations from Benford’s Law, relatively high contamination ratios are required at conventional significance levels.

scholarly journals Addressing the reliability fallacy: Similar group effects may arise from unreliable individual effects

2017 ◽  
Author(s):  
Juliane H. Fröhner ◽  
Vanessa Teckentrup ◽  
Michael N. Smolka ◽  
Nils B. Kroemer
Keyword(s):  
Large Scale ◽  
Intertemporal Choice ◽  
Subjective Evaluation ◽  
Brain Activation ◽  
Activation Patterns ◽  
Individual Level ◽  
The Individual ◽  
Global And Local ◽  
Main Effects ◽  
The Brain

AbstractTo cast valid predictions of future behavior or diagnose disorders, the reliable measurement of a “biomarker” such as the brain activation to prospective reward is a prerequisite. Surprisingly, only a small fraction of functional magnetic resonance imaging (fMRI) studies report or cite the reliability of brain activation maps involved in group analyses. Here, using simulations and exemplary longitudinal data of 126 healthy adolescents performing an intertemporal choice task, we demonstrate that reproducing a group activation map over time is not a sufficient indication of reliable measurements at the individual level. Instead, selecting regions based on significant main effects at the group level may yield estimates that fail to reliably capture individual variance in the subjective evaluation of an offer. Collectively, our results call for more attention on the reliability of supposed biomarkers at the level of the individual. Thus, caution is warranted in employing brain activation patterns prematurely for clinical applications such as diagnosis or tailored interventions before their reliability has been conclusively established by large-scale studies. To facilitate assessing and reporting of the reliability of fMRI contrasts in future studies, we provide a toolbox that incorporates common measures of global and local reliability.

Perceived Trust and Confidence for Cryptocurrency Adoption

2022 ◽  
pp. 250-279
Author(s):  
Ewilly Jie Ying Liew ◽  
Wei Li Peh ◽  
Zhuan Kee Leong
Keyword(s):  
Large Scale ◽  
Social Impact ◽  
Public Perceptions ◽  
Middle Income ◽  
Individual Level ◽  
Perceived Trust ◽  
Middle Income Countries ◽  
Regulatory Bodies ◽  
The Individual ◽  
National Databases

This chapter seeks to examine the influence of public perceptions of trust in people and confidence in institutions on cryptocurrency adoption, taking into account the individual-level demographic factors and the regional-level contextual factors. Data is obtained from three large-scale international surveys and national databases and analyzed using R software. The multivariate results demonstrate that individuals' public perceptions of trust and confidence significantly contribute to cryptocurrency adoption. Lower perceived trust in people and higher perceived confidence in civil service and international regulatory bodies increase cryptocurrency adoption, while perceived confidence in political and financial institutions discourages cryptocurrency adoption. Additionally, the univariate results find significant comparisons of gender and perceived trust differences on the predictors of cryptocurrency adoption. This chapter discusses and provides insights on the social impact and future of cryptocurrency adoption, particularly among the upper- and lower-middle-income countries.

scholarly journals Expression of Hybrid Peptide EF-1 in Pichia pastoris, Its Purification, and Antimicrobial Characterization

Molecules ◽  
2020 ◽  
Vol 25 (23) ◽  
pp. 5538
Author(s):  
Zhongxuan Li ◽  
Qiang Cheng ◽  
Henan Guo ◽  
Rijun Zhang ◽  
Dayong Si
Keyword(s):  
Pichia Pastoris ◽  
High Performance ◽  
Large Scale ◽  
Expression System ◽  
Reversed Phase ◽  
E Coli ◽  
Cell Membrane Permeabilization ◽  
Bactericidal Activities ◽  
The Individual ◽  
Industrial Level

EF-1 is a novel peptide derived from two bacteriocins, plantaricin E and plantaricin F. It has a strong antibacterial activity against Escherichia coli and with negligible hemolytic effect on red blood cells. However, the chemical synthesis of EF-1 is limited by its high cost. In this study, we established a heterologous expression of EF-1 in Pichia pastoris. The transgenic strain successfully expressed hybrid EF-1 peptide, which had a molecular weight of ~5 kDa as expected. The recombinant EF-1 was purified by Ni2+ affinity chromatography and reversed-phase high performance liquid chromatography (RP-HPLC), which achieved a yield of 32.65 mg/L with a purity of 94.9%. The purified EF-1 exhibited strong antimicrobial and bactericidal activities against both Gram-positive and -negative bacteria. Furthermore, propidium iodide staining and scanning electron microscopy revealed that EF-1 can directly induce cell membrane permeabilization of E. coli. Therefore, the hybrid EF-1 not only preserves the individual properties of the parent peptides, but also acquires the ability to disrupt Gram-negative bacterial membrane. Meanwhile, such an expression system can reduce both the time and cost for large-scale peptide production, which ensures its potential application at the industrial level.

Children’s Height and Parental Unemployment: A Large-Scale Anthropometric Study on Eastern Germany, 1994–2006

2010 ◽  
Vol 11 (1) ◽  
pp. 1-24 ◽  
Author(s):  
Jörg Baten ◽  
Andreas Böhm
Keyword(s):  
Employment Status ◽  
Large Scale ◽  
Psychological Effects ◽  
Average Height ◽  
Panel Analysis ◽  
Individual Level ◽  
Parental Unemployment ◽  
The Individual ◽  
Anthropometric Study

Abstract The average height of children is an indicator of the quality of nutrition and healthcare. In this study, we assess the effect of unemployment and other factors on this variable. In the Eastern German Land of Brandenburg, a dataset of 253,050 preschool height measurements was compiled and complemented with information on parents’ schooling and employment status. Unemployment might have negative psychological effects, with an impact on parental care. Both a panel analysis of districts and an assessment at the individual level yield the result that increasing unemployment, net out-migration and fertility were in fact reducing height.

The Effect of Public Service Motivation at Individual, Group, and Organisational Levels of Citizenship Behaviour

2020 ◽  
Vol 33 (1) ◽  
pp. 39-58
Author(s):  
Kuo-Tai Cheng ◽  
Yuan-Chieh Chang ◽  
Changyen Lee
Keyword(s):  
Public Service ◽  
Organizational Citizenship Behavior ◽  
Large Scale ◽  
Public Service Motivation ◽  
Employee Attitudes ◽  
Public Utility ◽  
Citizenship Behavior ◽  
Perceived Effectiveness ◽  
Individual Level ◽  
The Individual

This study conceptualizes and empirically investigates how dimensions of public service motivation affect perceived citizenship behaviour in the context of government-owned utilities. This study used a large-scale questionnaire survey from four utility sectors in Taiwan (N = 1,087). The emergent model suggests that compassion (COM) and self-sacrifice (SS) affect the perceived effectiveness of individual-level Organizational Citizenship Behavior (OCB). Commitment to the Public Interest (CPI) and Attraction to Public Policy making (APP) affect perceived effectiveness of OCB at the group and organisational levels, respectively. The results support the expected contribution of OCB, from the individual to the group levels, and from the group level to the organisational level. Public utility managers should strive to improve employee attitudes and motivation towards greater levels of OCB.

Research on the Innovation Method of HRM Based on Information Technology

2014 ◽  
Vol 687-691 ◽  
pp. 4485-4488
Author(s):  
Man Jing Zhang
Keyword(s):  
Firm Performance ◽  
Hierarchical Linear Modeling ◽  
Psychological Contract ◽  
High Performance ◽  
Affective Commitment ◽  
Organizational Level ◽  
Linear Modeling ◽  
Individual Level ◽  
Relational Contract ◽  
The Individual

As an organization s strategy to manage the employment relationship, high-performance work system (HPWS) may lead to superior firm performance and favorable employee outcomes through cultivating the relational aspects of employee’s psychological contract. In this study, we investigated the processes (mediation and moderation) linking HPWS and outcomes at both the organizational and individual levels. Hierarchical linear modeling (HLM) analysis on a sample of 1129 employees from 92 firms in the Pearl River Delta of China indicated that HPWS was associated with increased firm performance and decreased turnover rate at the organizational level, and relational contract fully mediated the cross-level relationships between HPWS and employees affective commitment and in-role performance at the individual level. In addition, perceived supervisor support moderated the HPWS and relational contract relationship. We discuss theoretical and practical implications to end of this paper.

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