Integrating the Totality of Food and Nutrition Evidence for Public Health Decision Making and Communication

The interpretation and integration of epidemiological studies detecting weak associations (RR < 2) with data from other study designs (e.g., animal models and human intervention trials) is both challenging and vital for making science-based dietary recommendations in the nutrition and food safety communities. The 2008 ILSI North America “Decision-Making for Recommendations and Communication Based on Totality of Food-Related Research” workshop provided an overview of epidemiological methods, and case-study examples of how weak associations have been incorporated into decision making for nutritional recommendations. Based on the workshop presentations and dialogue among the participants, three clear strategies were provided for the use of weak associations in informing nutritional recommendations for optimal health. First, enable more effective integration of data from all sources through the use of genetic and nutritional biomarkers; second, minimize the risk of bias and confounding through the adoption of rigorous quality-control standards, greater emphasis on the replication of study results, and better integration of results from independent studies, perhaps using adaptive study designs and Bayesian meta-analysis methods; and third, emphasize more effective and truthful communication to the public about the evolving understanding of the often complex relationship between nutrition, lifestyle, and optimal health

CommAID: Visual Analytics for Communication Analysis through Interactive Dynamics Modeling

Communication consists of both meta-information as well as content. Currently, the automated analysis of such data often focuses either on the network aspects via social network analysis or on the content, utilizing methods from text-mining. However, the first category of approaches does not leverage the rich content information, while the latter ignores the conversation environment and the temporal evolution, as evident in the meta-information. In contradiction to communication research, which stresses the importance of a holistic approach, both aspects are rarely applied simultaneously, and consequently, their combination has not yet received enough attention in automated analysis systems. In this work, we aim to address this challenge by discussing the difficulties and design decisions of such a path as well as contribute CommAID, a blueprint for a holistic strategy to communication analysis. It features an integrated visual analytics design to analyze communication networks through dynamics modeling, semantic pattern retrieval, and a user-adaptable and problem-specific machine learning-based retrieval system. An interactive multi-level matrix-based visualization facilitates a focused analysis of both network and content using inline visuals supporting cross-checks and reducing context switches. We evaluate our approach in both a case study and through formative evaluation with eight law enforcement experts using a real-world communication corpus. Results show that our solution surpasses existing techniques in terms of integration level and applicability. With this contribution, we aim to pave the path for a more holistic approach to communication analysis.Comment: 12 pages, 7 figures, Computer Graphics Forum 2021 (pre-peer reviewed version

Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding

We introduce meta-prompting, an effective scaffolding technique designed to enhance the functionality of language models (LMs). This approach transforms a single LM into a multi-faceted conductor, adept at managing and integrating multiple independent LM queries. By employing high-level instructions, meta-prompting guides the LM to break down complex tasks into smaller, more manageable subtasks. These subtasks are then handled by distinct "expert" instances of the same LM, each operating under specific, tailored instructions. Central to this process is the LM itself, in its role as the conductor, which ensures seamless communication and effective integration of the outputs from these expert models. It additionally employs its inherent critical thinking and robust verification processes to refine and authenticate the end result. This collaborative prompting approach empowers a single LM to simultaneously act as a comprehensive orchestrator and a panel of diverse experts, significantly enhancing its performance across a wide array of tasks. The zero-shot, task-agnostic nature of meta-prompting greatly simplifies user interaction by obviating the need for detailed, task-specific instructions. Furthermore, our research demonstrates the seamless integration of external tools, such as a Python interpreter, into the meta-prompting framework, thereby broadening its applicability and utility. Through rigorous experimentation with GPT-4, we establish the superiority of meta-prompting over conventional scaffolding methods: When averaged across all tasks, including the Game of 24, Checkmate-in-One, and Python Programming Puzzles, meta-prompting, augmented with a Python interpreter functionality, surpasses standard prompting by 17.1%, expert (dynamic) prompting by 17.3%, and multipersona prompting by 15.2%.Comment: https://github.com/suzgunmirac/meta-promptin

Comparing and Contrasting e-Government Maturity Models: A Qualitative-Meta Synthesis

The e-government maturity model has dissimilar stages that range from basic to advance online interaction competence. E-government’s portals use the stages to determine maturity. The aim of this paper is to evaluate e-government maturity models through a comprehensive review of related literature by identifying and mapping cohesions across the models. Apparently, the paper picks seventeen different e-government maturity models and makes contrasts and comparisons using a qualitative meta-synthesis method. Ideally, the paper draws two key results namely presence, communication and integration are main stages involved in all the maturity models and the level of interaction and complexity are found in all models

Integrated Electro-Optics Modulator

Electro-optic modulation (EOM) is an essentially important optical manipulation for on-chip photonics, optical communication and optical sensing. With emerging demands on efficient, broadband electro-optic modulation, the high-performance, integrated electro-optic modulation becomes indispensable. By manipulating phase or amplitude of optical field, optical information will be coded/modulated for communication or modulation. Through advanced micro/nano fabrication technique, the electro-optics crystal could be cut into the required volume/shape as specific, integrated modulator, waveguide or meta-surface for nano-photonic applications, paving a solid way for the imminent nano-photonic devices. Herein, the basic electro-optics effects, opto-electronic applications, methods of fabrication/integration, and future prospect of lithium niobate crystal are discussed or introduced. Demonstrations of box-sealed EOM, in-fiber EOM and the fabricated lithium niobate waveguides on substrate will be found here

A Foundational View on Integration Problems

The integration of reasoning and computation services across system and language boundaries is a challenging problem of computer science. In this paper, we use integration for the scenario where we have two systems that we integrate by moving problems and solutions between them. While this scenario is often approached from an engineering perspective, we take a foundational view. Based on the generic declarative language MMT, we develop a theoretical framework for system integration using theories and partial theory morphisms. Because MMT permits representations of the meta-logical foundations themselves, this includes integration across logics. We discuss safe and unsafe integration schemes and devise a general form of safe integration

FRIENDS - A flexible architecture for implementing fault tolerant and secure distributed applications

FRIENDS is a software-based architecture for implementing fault-tolerant and, to some extent, secure applications. This architecture is composed of sub-systems and libraries of metaobjects. Transparency and separation of concerns is provided not only to the application programmer but also to the programmers implementing metaobjects for fault tolerance, secure communication and distribution. Common services required for implementing metaobjects are provided by the sub-systems. Metaobjects are implemented using object-oriented techniques and can be reused and customised according to the application needs, the operational environment and its related fault assumptions. Flexibility is increased by a recursive use of metaobjects. Examples and experiments are also described

Secure Integration of Desktop Grids and Compute Clusters Based on Virtualization and Meta-Scheduling

Reducing the cost for business or scientific computations, is a commonly expressed goal in today’s companies. Using the available computers of local employees or the outsourcing of such computations are two obvious solutions to save money for additional hardware. Both possibilities exhibit security related disadvantages, since the deployed software and data can be copied or tampered if appropriate countermeasures are not taken. In this paper, an approach is presented to let a local desktop machines and remote cluster resources be securely combined into a singel Grid environment. Solutions to several problems in the areas of secure virtual networks, meta-scheduling and accessing cluster schedulers from desktop Grids are proposed