MTVE is an open-source software tool (citeware) that can be applied in laboratory and online experiments to implement video communication. The tool enables researchers to gather video data from these experiments in a way that these videos can be later used for automatic analysis through machine learning techniques. The browser-based tool comes with an easy user interface and can be easily integrated into z-Tree, oTree (and other experimental or survey tools). It provides the experimenters control over several communication parameters (e.g., number of participants, resolution), produces high-quality video data, and circumvents the Cocktail Party Problem (i.e., the problem of separating speakers solely based on audio input) by producing separate files. Using some of the recommended Voice-to-Text AI, the experimenters can transcribe individual files. MTVE can merge these individual transcriptions into one conversation.

In 2009, the Robert Koch Institute (RKI) and the 16 German federal state public health authorities (PHAs) established a weekly epidemiological teleconference (EpiLag) to discuss infectious disease (ID) events and foster horizontal and vertical information exchange. We present the procedure, discussed ID topics and evaluation results of EpiLag after 10 years. We analysed attendance, duration of EpiLag and the frequency of reported events. Participants (RKI and state PHA) were surveyed regarding their satisfaction with logistics, contents and usefulness of EpiLag (Likert scales). Between 2009 and 2018, RKI hosted 484 EpiLag conferences with a mean duration of 25 min (range: 4–60) and high participation (range: 9–16; mean: 15 PHAs). Overall, 2975 ID events (39% international, 9% national and 52% subnational) were presented (mean: 6.1 per EpiLag), most frequently on measles (18%), salmonellosis (8%) and influenza (5%). All responding participants (14/16 PHAs and 9/9 at RKI) were satisfied with the EpiLag's organization and minutes and deemed EpiLag useful for an overview and information distribution on ID events relevant to Germany. EpiLag is time efficient, easily applicable and useful for a low-threshold event communication. It supports PHAs in crises and strengthens the network of surveillance stakeholders. We recommend its implementation to other countries or sectors.

Culture allows humans to adapt to a diversity of contexts. Participatory experience in technical activities and activity with artefacts provide the basis for learning traditional technical skills. Some populations of non-human animals use tools. The ways in which artefacts influence the development of a traditional skill in non-human species can provide insight into essential supports for technical traditions in humans and shared learning processes across species. In wild bearded capuchins, nut cracking leaves edible pieces of nuts, nut shells and stones used as hammers at anvil sites. We addressed how mastery of cracking nuts by young monkeys is associated with interactions with these objects. We studied monkeys’ reuse of nuts, hammers and anvils and the outcome of attempts to crack nuts, and from these data derived their behavioural variability and proficiency in nut cracking. Behavioural variability was the most robust predictor of whether a monkey collects pieces of nuts cracked by others or reuses stones and nuts, and was a stronger predictor of proficiency than age. Young monkeys were increasingly likely to reuse the stone used by another after the other monkey had left the anvil as they increasingly focused their behaviour on actions relevant to cracking nuts.

Recent international communicable disease crises have highlighted the need for countries to assure their preparedness to respond effectively to public health emergencies. The objective of this study was to critically review existing tools to support a country’s assessment of its health emergency preparedness. We developed a framework to analyze the expected effectiveness and utility of these tools. Through mixed search strategies, we identified 12 tools with relevance to public health emergencies. There was considerable consensus concerning the critical preparedness system elements to be assessed, although their relative emphasis and means of assessment and measurement varied considerably. Several tools identified appeared to have reporting requirements as their primary aim, rather than primary utility for system self-assessment of the countries and states using the tool. Few tools attempted to give an account of their underlying evidence base. Only some tools were available in a user-friendly electronic modality or included quantitative measures to support the monitoring of system preparedness over time. We conclude there is still a need for improvement in tools available for assessment of country preparedness for public health emergencies, and for applied research to increase identification of system measures that are valid indicators of system response capability.

The purpose of this study was to identify the self-report physical activity (PA) tool best suited for assessment of PA in community-dwelling older adults with multiple chronic conditions (MCC). PA can positively influence physical and psychological health in this population. Although self-report PA tools exist, little is known about the psychometric properties and feasibility of using these tools in older adults with MCC. A systematic literature review from 2000 to 2018 was conducted of studies reporting on the psychometric properties and feasibility of 18 self-report PA tools for community-dwelling older adults (≥ 65 years) to determine the suitability of these tools for use in older adults with MCC. Based on an assessment of the available evidence for the psychometric properties and feasibility of 18 different self-report PA tools, the Physical Activity Assessment Scale for the Elderly (PASE) is recommended as the best-suited self-report PA tool for older adults with MCC.

The central objective of the present author's research is to develop a system supporting the design of a technological process (a computer-aided process planning system) that functions similarly to a human expert in the field in question. The use of neural networks makes the creation of such a system possible. The proposed method uses a system of three blocks of neural networks, and involves the creation of neural networks to be used for the selection of machines, tools, and machining parameters. These networks are built for each process operation separately; that is, a set of neural networks is created for each selection. For the construction of models, different types of neural networks (multilayer networks with error backpropagation, radial basis function, and Kohonen) with different structures were employed, and the networks that made the best selections were identified. A method was also developed for the elimination of defects occurring during the production process. When a defect comes to light, this method suggests changes to the technological process, thus improving the quality of that process. Guidelines for the elimination of defects are produced in the form of decision rules. Such a computer-aided process planning system will be especially useful for process engineers who do not yet have sufficient experience in the design of technological processes, or who have only recently joined a particular manufacturing enterprise and are not fully familiar with its machines and other means of production (tools and instrumentation). It should be emphasized that such a system performs an advisory role, and it is always the process engineer who makes the final decision. The neural network models were tested on real data from an enterprise. A computer-aided process planning system based on rules and neural network models enables the intelligent design of technological processes.

In events such as earthquakes or terrorist attacks, hospitals may be victims of disasters. They may need to transfer patients to outside facilities rather than continue to provide on-site care. Following the Northridge earthquake, eight hospitals in the damaged area were the foci of a United States National Science Foundation study that examined the status of the hospitals' pre-event planning, post-event evacuationdecision-making, and internal and external evacuation processes. Building on this experience, this paper offers a standardized data collection tool, which will enable researchers to record hospital evacuation information in a systematic manner so that comparable data can be accumulated, evacuation research methods can be improved, and consensus on methods can be reached. The study's principal subjects include: (1) hospital demographics; (2) description of existing disaster response plans; (3) an event's impacts on hospital operations; (4) decision-making and incident command; (5) movement of patients within the facility; (6) movement of patients to off-site institutions; and (7) hospital recovery.