Preliminary Results From Detection of Microplastics in Liquid Samples Using Flow Cytometry

Microplastics are globally recognized as contaminants in freshwater and marine aquatic systems. To date there is no universally accepted protocol for isolation and quantification of microplastics from aqueous media. Various methodologies exist, many of which are time consuming and have the potential to introduce contaminants into samples, thereby obscuring characterization of the environmental microplastic load. Here, we present first steps in the detection of microplastics in liquid samples, based on their fluorescent staining followed by high throughput analysis and quantification using Flow Cytometry. Using controlled laboratory settings nine polymer types [polystyrene (PS); polyethylene (PE); polyethylene terephthalate (PET/PETE); high density polyethylene (HDPE); low density polyethylene (LDPE); polyvinyl chloride (PVC); polypropylene (PP); nylon (PA); polycarbonate (PC)] were tested for identification and quantification in freshwater. All nine plastic types were stained with 10 μg/mL Nile Red in 10% dimethyl sulfoxide with a 10 min incubation time. The lowest spatial detectable limit for plastic particles was 200 nm. Out of the nine polymer types chosen for the study PS, PE, PET, and PC were well-identified; however, results for other plastic types (PVC, PP, PA, LDPE, and HDPE) were masked to certain extent by Nile Red aggregation and precipitation. The methodology presented here permits identification of a range of particle sizes and types. It represents a significant step in the quantification of microplastics by replacing visual data interpretation with a sensitive and automated method

Symbolic Model Checking for Dynamic Epistemic Logic

Dynamic Epistemic Logic (DEL) can model complex information scenarios in a way that appeals to logicians. However, existing DEL implementations are ad-hoc, so we do not know how the framework really performs. For this purpose, we want to hook up with the best available model-checking and SAT techniques in computational logic. We do this by first providing a bridge: a new faithful representation of DEL models as so-called knowledge structures that allow for symbolic model checking. Next, we show that we can now solve well-known benchmark problems in epistemic scenarios much faster than with existing DEL methods. Finally, we show that our method is not just a matter of implementation, but that it raises significant issues about logical representation and update

Local Search for Flowshops with Setup Times and Blocking Constraints

Permutation flowshop scheduling problem (PFSP) is a classical combinatorial optimisation problem. There exist variants of PFSP to capture different realistic scenarios, but significant modelling gaps still remain with respect to real-world industrial applications such as the cider production line. In this paper, we propose a new PFSP variant that adequately models both overlapable sequence-dependent setup times (SDST) and mixed blocking constraints. We propose a computational model for makespan minimisation of the new PFSP variant and show that the time complexity is NP Hard. We then develop a constraint-guided local search algorithm that uses a new intensifying restart technique along with variable neighbourhood descent and greedy selection. The experimental study indicates that the proposed algorithm, on a set of wellknown benchmark instances, significantly outperforms the state-of-the-art search algorithms for PFSP

The Interpreted System Model of Knowledge, Belief, Desire and Intention

We present a new model of knowledge, belief, desire and intention, called the interpreted KBDI-system model (or KBDI-model for short). The key point of the interpreted KBDI-system model is that we express an agent’s knowledge, belief, desire and intention as a set of runs (computing paths), which is exactly a system in the interpreted system model, a well-known agent model due to Halpern and his colleagues. Our KBDI-model is computationally grounded in that we are able to associate a KBDI-model with a computer program, and formulas, involving agents ’ knowledge, belief, desire (goal) and intention, can be understood as properties of program computations. We present a sound and complete proof system with respect to our KBDI-model and explore how symbolic model checking techniques can be applied to model checking multi-agent systems with KBDI-models. 1

Identifying groups at risk for 1-year membership termination from a fitness center at enrollment

The vast majority of Americans do not engage in adequate regular physical activity despite its well-known health benefits. Even when individuals attempt to become more active by joining a fitness center, estimates suggest that nearly half terminate their membership within the first 6 months. A better understanding of who is at risk for early membership termination upon joining may help researchers develop targeted interventions to improve the likelihood that individuals will successfully maintain memberships and physical activity. This study's purpose was to identify, based on a wellness assessment (WA) used in fitness centers, individuals at risk for fitness membership termination prior to 1-year. Center members (N = 441; Mage = 41.9, SD = 13.1; 74.4% female) completed a comprehensive WA of stress, life satisfaction, physical fitness, metabolic health, and sleep quality at the beginning of their memberships and were followed for one year. Latent class analyses utilized the WA to identify four groups: (a) healthy, (b) unhealthy, (c) poor psychological wellness, and (d) poor physical wellness. Participants in the poor psychological wellness group (OR = 2.24, p = 0.007) and the unhealthy group (OR = 2.40, p = 0.037) were significantly more likely to terminate their memberships at 1-year as compared to the healthy group. Participants with poor physical wellness visited the fitness center less frequently than healthy participants (p < 0.01). Results suggest that poor psychological wellness is a risk factor for terminating memberships, whereas poor physical wellness is not. Future studies should replicate these latent classes and develop targeted interventions to address psychological wellness as a method to improve fitness membership retention. Keywords: Exercise, Retention, Adherence, Psychological stress, Quality of lif