Mechanical power output is a key performance-determining variable in many cyclic sports. In rowing, instantaneous power output is commonly determined as the dot product of handle force moment and oar angular velocity. The aim of this study was to show that this commonly used proxy is theoretically flawed and to provide an indication of the magnitude of the error. To obtain a consistent dataset, simulations were performed using a previously proposed forward dynamical model. Inputs were previously recorded rower kinematics and horizontal oar angle, at 20 and 32 strokes∙min−1. From simulation outputs, true power output and power output according to the common proxy were calculated. The error when using the common proxy was quantified as the difference between the average power output according to the proxy and the true average power output (P̅residual), and as the ratio of this difference to the true average power output (ratiores./rower). At stroke rate 20, P̅residual was 27.4 W and ratiores./rower was 0.143; at stroke rate 32, P̅residual was 44.3 W and ratiores./rower was 0.142. Power output in rowing appears to be underestimated when calculated according to the common proxy. Simulations suggest this error to be at least 10% of the true power output.
Societal actors across scales and geographies increasingly demand visual applications of systems thinking – the process of understanding and changing the reality of a system by considering its whole set of interdependencies – to address complex problems affecting food and agriculture. Yet, despite the wide offer of systems mapping tools, there is still little guidance for managers, policy-makers, civil society and changemakers in food and agriculture on how to choose, combine and use these tools on the basis of a sufficiently deep understanding of socio-ecological systems. Unfortunately, actors seeking to address complex problems with inadequate understandings of systems often have limited influence on the socio-ecological systems they inhabit, and sometimes even generate unintended negative consequences. Hence, we first review, discuss and exemplify seven key features of systems that should be – but rarely have been – incorporated in strategic decisions in the agri-food sector: interdependency, level-multiplicity, dynamism, path dependency, self-organization, non-linearity and complex causality. Second, on the basis of these features, we propose a collective process to systems mapping that grounds on the notion that the configuration of problems (i.e., how multiple issues entangle with each other) and the configuration of actors (i.e., how multiple actors relate to each other and share resources) represent two sides of the same coin. Third, we provide implications for societal actors - including decision-makers, trainers and facilitators - using systems mapping to trigger or accelerate systems change in five purposive ways: targeting multiple goals; generating ripple effects; mitigating unintended consequences; tackling systemic constraints, and collaborating with unconventional partners.
MULTIFILE
An essential condition to use mathematics to solve problems is the ability to recognize, imagine and represent relations between quantities. In particular, covariational reasoning has been shown to be very challenging for students at all levels. The aim of the project Interactive Virtual Math (IVM) is to develop a visualization tool that supports students’ learning of covariation graphs. In this paper we present the initial development of the tool and we discuss its main features based on the results of one preliminary study and one exploratory study. The results suggest that the tool has potential to help students to engage in covariational reasoning by affording construction and explanation of different representations and comparison, relation and generalization of these ones. The results also point to the importance of developing tools that elicit and build upon students' self-productions
Climate change is one of the most critical global challenges nowadays. Increasing atmospheric CO2 concentration brought by anthropogenic emissions has been recognized as the primary driver of global warming. Therefore, currently, there is a strong demand within the chemical and chemical technology industry for systems that can covert, capture and reuse/recover CO2. Few examples can be seen in the literature: Hamelers et al (2013) presented systems that can use CO2 aqueous solutions to produce energy using electrochemical cells with porous electrodes; Legrand et al (2018) has proven that CDI can be used to capture CO2 without solvents; Shu et al (2020) have used electrochemical systems to desorb (recover) CO2 from an alkaline absorbent with low energy demand. Even though many efforts have been done, there is still demand for efficient and market-ready systems, especially related to solvent-free CO2 capturing systems. This project intends to assess a relatively efficient technology, with low-energy costs which can change the CO2 capturing market. This technology is called whorlpipe. The whorlpipe, developed by Viktor Schauberger, has shown already promising results in reducing the energy and CO2 emissions for water pumping. Recently, studies conducted by Wetsus and NHL Stenden (under submission), in combination with different companies (also members in this proposal) have shown that vortices like systems, like the Schauberger funnel, and thus “whorlpipe”, can be fluid dynamically represented using Taylor-Couette flows. This means that such systems have a strong tendency to form vortices like fluid-patterns close to their air-water interface. Such flow system drastically increase advection. Combined with their higher area to volume ratio, which increases diffusion, these systems can greatly enhance gas capturing (in liquids), and are, thus, a unique opportunity for CO2 uptake from the air, i.e. competing with systems like conventional scrubbers or bubble-based aeration.
Prompt and timely response to incoming cyber-attacks and incidents is a core requirement for business continuity and safe operations for organizations operating at all levels (commercial, governmental, military). The effectiveness of these measures is significantly limited (and oftentimes defeated altogether) by the inefficiency of the attack identification and response process which is, effectively, a show-stopper for all attack prevention and reaction activities. The cognitive-intensive, human-driven alarm analysis procedures currently employed by Security Operation Centres are made ineffective (as opposed to only inefficient) by the sheer amount of alarm data produced, and the lack of mechanisms to automatically and soundly evaluate the arriving evidence to build operable risk-based metrics for incident response. This project will build foundational technologies to achieve Security Response Centres (SRC) based on three key components: (1) risk-based systems for alarm prioritization, (2) real-time, human-centric procedures for alarm operationalization, and (3) technology integration in response operations. In doing so, SeReNity will develop new techniques, methods, and systems at the intersection of the Design and Defence domains to deliver operable and accurate procedures for efficient incident response. To achieve this, this project will develop semantically and contextually rich alarm data to inform risk-based metrics on the mounting evidence of incoming cyber-attacks (as opposed to firing an alarm for each match of an IDS signature). SeReNity will achieve this by means of advanced techniques from machine learning and information mining and extraction, to identify attack patterns in the network traffic, and automatically identify threat types. Importantly, SeReNity will develop new mechanisms and interfaces to present the gathered evidence to SRC operators dynamically, and based on the specific threat (type) identified by the underlying technology. To achieve this, this project unifies Dutch excellence in intrusion detection, threat intelligence, and human-computer interaction with an industry-leading partner operating in the market of tailored solutions for Security Monitoring.
