Можливості ефективної організації та стимулювання бажаних трансформацій

У статті розглядається поняття інформаційного впливу як багаторівневого феномена. Вводиться розмежування між інформаційними впливами під час взаємодії різних соціальних систем і змальовано ефект інформаційного впливу на соціально-економічний розвиток суспільства. У статті автор продовжує аналіз власної концепції розвитку соціальних технологій постмодерного м’якого управління з точки зору стану національної безпеки. Він розробляє модель постмодерного інформаційного впливу – стимулювання бажаних змін.The article examines the notion of information influence as a multilevel phenomenon. The division is applied between information influence of different social systems interaction and the impact of information influence upon society’s social and economic development is shown. In the article the author continues analysis of his conception of postmodern soft management social technologies development from the point of view of national security situation. He elaborates the model of postmodern information influence – desirable changes stimulation

Eating disorders in weight-related therapy (EDIT): Protocol for a systematic review with individual participant data meta-analysis of eating disorder risk in behavioural weight management

The Eating Disorders In weight-related Therapy (EDIT) Collaboration brings together data from randomised controlled trials of behavioural weight management interventions to identify individual participant risk factors and intervention strategies that contribute to eating disorder risk. We present a protocol for a systematic review and individual participant data (IPD) meta-analysis which aims to identify participants at risk of developing eating disorders, or related symptoms, during or after weight management interventions conducted in adolescents or adults with overweight or obesity. We systematically searched four databases up to March 2022 and clinical trials registries to May 2022 to identify randomised controlled trials of weight management interventions conducted in adolescents or adults with overweight or obesity that measured eating disorder risk at pre- and post-intervention or follow-up. Authors from eligible trials have been invited to share their deidentified IPD. Two IPD meta-analyses will be conducted. The first IPD meta-analysis aims to examine participant level factors associated with a change in eating disorder scores during and following a weight management intervention. To do this we will examine baseline variables that predict change in eating disorder risk within intervention arms. The second IPD meta-analysis aims to assess whether there are participant level factors that predict whether participation in an intervention is more or less likely than no intervention to lead to a change in eating disorder risk. To do this, we will examine if there are differences in predictors of eating disorder risk between intervention and no-treatment control arms. The primary outcome will be a standardised mean difference in global eating disorder score from baseline to immediately post-intervention and at 6- and 12- months follow-up. Identifying participant level risk factors predicting eating disorder risk will inform screening and monitoring protocols to allow early identification and intervention for those at risk

An interactive, multi-modal approach to analysing high-resolution image mass spectrometry data

The output resolution of imaging mass spectrometers is increasing rapidly due to advances in engineering and the use of tiling. Imaging-MS data is often displayed as a total-ion-count (TIC) image; however, anatomical structures are not easily identifiable from TIC images. For this purpose, additional high-resolution images that originate from different imaging modalities, such as stained histological data, are preferred. These modalities are most useful when fused; i.e., when the corresponding images are spatially aligned with respect to each other. The viewing and analysis of such data is ideally performed in real-time and at the highest possible resolution, allowing users to interactively query the combination of all fused data at the highest detail. However, proper alignment between modalities and interactively presenting large volumes of data is as of yet a challenge. We present a system for the simultaneous viewing and analysis of high-resolution data from different imaging modalities. Fusion is provided in such a way that interaction in one modality can be mapped to different modalities. For example, anatomical structures can be identified from histological data and their spatial extent mapped to a corresponding region-of-interest in the image MS data, allowing the analysis of its chemical compounds. In turn, the MS data can be analysed and filtered, for example using multi-variate analysis such as PCA, and the result mapped back to structures in other modalities. Level-of-detail, region-of-interest and asynchronous data processing algorithms ensure that the system can be operated interactively at the highest resolution

An interactive, multi-modal approach to analysing high-resolution image mass spectrometry data

The output resolution of imaging mass spectrometers is increasing rapidly due to advances in engineering and the use of tiling. Imaging-MS data is often displayed as a total-ion-count (TIC) image; however, anatomical structures are not easily identifiable from TIC images. For this purpose, additional high-resolution images that originate from different imaging modalities, such as stained histological data, are preferred. These modalities are most useful when fused; i.e., when the corresponding images are spatially aligned with respect to each other. The viewing and analysis of such data is ideally performed in real-time and at the highest possible resolution, allowing users to interactively query the combination of all fused data at the highest detail. However, proper alignment between modalities and interactively presenting large volumes of data is as of yet a challenge. We present a system for the simultaneous viewing and analysis of high-resolution data from different imaging modalities. Fusion is provided in such a way that interaction in one modality can be mapped to different modalities. For example, anatomical structures can be identified from histological data and their spatial extent mapped to a corresponding region-of-interest in the image MS data, allowing the analysis of its chemical compounds. In turn, the MS data can be analysed and filtered, for example using multi-variate analysis such as PCA, and the result mapped back to structures in other modalities. Level-of-detail, region-of-interest and asynchronous data processing algorithms ensure that the system can be operated interactively at the highest resolution