Diagnosing Extrusion Process Based on Displacement Signal and Simple Decision Tree Classifier

The article presents an extensive analysis of the literature related to the diagnosis of the extrusion process and proposes a new, unique method. This method is based on the observation of the punch displacement signal in relation to the die, and then approximation of this signal using a polynomial. It is difficult to find in the literature even an attempt to solve the problem of diagnosing the extrusion process by means of a simple distance measurement. The dominant feature is the use of strain gauges, force sensors or even accelerometers. However, the authors managed to use the displacement signal, and it was considered a key element of the method presented in the article. The aim of the authors was to propose an effective method, simple to implement and not requiring high computing power, with the possibility of acting and making decisions in real time. At the input of the classifier, authors provided the determined polynomial coefficients and the SSE (Sum of Squared Errors) value. Based on the SSE values only, the decision tree algorithm performed anomaly detection with an accuracy of 98.36%. With regard to the duration of the experiment (single extrusion process), the decision was made after 0.44 s, which is on average 26.7% of the extrusion experiment duration. The article describes in detail the method and the results achieved.

Application of Calcium-rich Clay Mineral Under Nonwoven Fabric Mats and Sand Armor as Cap Layer for Interrupting N and P Release from River Sediments

This work investigates the applicability of thermally treated calcium-rich clay minerals (CRCMs), such as sepiolite (SPL), attapulgite (ATT), and dolomite (DLM) to hinder the nitrogen (N) and phosphorus (P) release from river sediments. A non-woven fabric mat (NWFM) or a sand layer were also capped as armor layers, i.e., placed over CRCMs to investigate the capping impact on the N/P release. The capping efficiency was evaluated in a cylindrical reactor, consisting of CRCMs, armor layers, sediments, and sampled water. We monitored N/P concentrations, dissolved oxygen (DO), oxidation reduction potential, pH, and electric conductivity in overlying water over 70 days. The DO concentrations in the uncapped and capped conditions were preserved for 30 days and 70 days (until the end of experiment duration), respectively. ATT showed higher efficiency for NH4-N and T-N than the other two materials, and the capping efficiency of NH4-N was measured as 96.4%, 93.7%, and 61.6% when capped with 2 cm sand layer, 1 cm sand layer, and NWFM layer, respectively. DLM showed a superior rejection capability of PO4-P to ATT and SPL, reported as 97.2% when capped with 2 cm sand armor. The content of weakly adsorbed-P was lower in the uncapped condition than in the capping condition. It can be concluded that ATT and DLM can be used as capping agents to deactivate N and P, respectively, to reduce water contamination from sediments of the eutrophic river.

Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude

Predicting the impacts of multiple stressors is important for informing ecosystem management, but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively, or antagonistically. Here we use process-based models to study how interactions generalise across three levels of bio-logical organisation (physiological, population, and community) for a simulated two-stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics, and consumer presence. Our results help explain why meta-analyses of multiple stressor experimental results have struggled to identify predictors of consistently non-additive interactions in the natural environment. Experiments run over longer temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management.

Mental State Detection Using Riemannian Geometry on Electroencephalogram Brain Signals

The goal of this study was to implement a Riemannian geometry (RG)-based algorithm to detect high mental workload (MWL) and mental fatigue (MF) using task-induced electroencephalogram (EEG) signals. In order to elicit high MWL and MF, the participants performed a cognitively demanding task in the form of the letter n-back task. We analyzed the time-varying characteristics of the EEG band power (BP) features in the theta and alpha frequency band at different task conditions and cortical areas by employing a RG-based framework. MWL and MF were considered as too high, when the Riemannian distances of the task-run EEG reached or surpassed the threshold of the baseline EEG. The results of this study showed a BP increase in the theta and alpha frequency bands with increasing experiment duration, indicating elevated MWL and MF that impedes/hinders the task performance of the participants. High MWL and MF was detected in 8 out of 20 participants. The Riemannian distances also showed a steady increase toward the threshold with increasing experiment duration, with the most detections occurring toward the end of the experiment. To support our findings, subjective ratings (questionnaires concerning fatigue and workload levels) and behavioral measures (performance accuracies and response times) were also considered.

DEVELOPMENT OF A PLANT FOR THE INTRODUCTION OF ENERGY-SAVING LIGHT TECHNOLOGY FOR GROWING GREATER WAX MOTH IN AN INDUSTRIAL SCALE

The larvae of the greater wax moth (Galleria mellonella L.) are not only a serious pest of bee colonies, but also a valuable raw material for the production of biologically active substances widely used in pharmaceuticals, cosmetology, food industry, animal feed, as well as a source of high-quality protein. We have developed an energy-saving installation for industrial insect cultivation, consisting of two modules: the first for butterflies (adults), the second for larvae, pupae and eggs. To implement energy-saving light technology, experiments with a large wax moth were carried out in the laboratory of Udmurt Federal Research Center of the Ural Branch of the Russian Academy of Sciences. The experiments were repeated 4 times. There were 20 specimens of G. mellonella in each experiment. The air temperature was maintained at 28° C, air humidity 50%. The influence of the duration and wavelength of radiation (400 nm, 491 nm, 546 nm and 577 nm) on the number of adults that moved to the module for butterflies and on the mass of laid eggs was studied. The radiation of 400 nm turned out to be the most effective, since 45% of butterflies moved to it and the mass of laid eggs was 32%, which is significantly higher than that of the radiation of 491, 546 and 577 nm. The duration of the radiation was 10 minutes, 30 minutes and 60 min. With an experiment duration of 60 min. 45% of the large wax moth is transferred to the butterfly module, with an experiment duration of 30 minutes. - 44%, and with an experiment duration of 10 minutes, 43% of the large wax moth moved. Therefore, it is recommended to maintain the operating time of LEDs with a wavelength of 400 nm for 30 minutes. The aim of the research is to develop an installation for the implementation of energy-saving light technology for the cultivation of larvae of the greater wax moth (Galleria mellonella L.) on an industrial scale

Increasing physical activity by Gamification among Brazilian high school students: a pilot study

This pilot study aimed to evaluate the effectiveness of a Gamification-based intervention on physical activity levels of High School students. This quasi experimental study was conducted in two federal high schools in Southern Brazil. One class from each school was selected to be either intervention (INT) or control (CON) group. Experiment duration was two weeks, and both groups downloaded My Active Life app. INT group (n = 69) participants received daily app alerts with messages of encouragement to practice physical activity. They also received a score based on the percentage of goal achieved. CON group (n = 35) only had access to total number of steps per day. INT group showed a lower decrease in physical activity at school compared to CON group (p = 0.024). No effect of intervention was observed in physical activity out of school (p = 0.911). Gamification-based intervention prevented a decrease in physical activity at school among male (F = 10.680; p = 0.004), students at first half of high school (F = 12.668; p = 0.002), and adequate body mass index (F = 4.640; p = 0.037), and with lower perception of barriers to physical activity (F = 5.437; p = 0.024). Although we did not observe an increase in physical activity at school, gamification-based intervention may mitigate its decrease among adolescents.

Event-driven acquisition for content-enriched microscopy

In fluorescence microscopy, the amount of information that can be collected from the sample is limited, often due to constraints imposed by photobleaching and phototoxicity. Here, we report an event-driven acquisition (EDA) framework, which combines real-time, neural network-based recognition of events of interest with automated control of the imaging parameters in an instant structured illumination microscope (iSIM). On-the-fly prioritization of imaging rate or experiment duration is achieved by switching between a slow imaging rate to detect the onset of biological events of interest and a fast imaging rate to enable high information content during their progression. In this way, EDA allows the data capture of mitochondrial and bacterial divisions at imaging rates that match their dynamic timescales, while extending the accessible imaging duration, and thereby increases the density of relevant information in the acquired data.

Root Foraging Precision: Do Experimental Conditions Matter?

Purpose: Root foraging precision, i.e., preferential root proliferation in nutrient-rich patches in heterogeneous soil, contributes significantly to plant nutrient acquisition. The ability to forage is usually studied experimentally, although often under different conditions. It remains unclear whether different experimental conditions affect root foraging precision. We studied the effect of experiment duration, pot size and root separation on root foraging precision and the appropriateness of using root foraging as species-specific values in databases and meta-analyses.Methods: We cultivated three perennial species in pots with spatially heterogeneous nutrient supplies and manipulated the experiment duration (4 – 10 weeks). We partly replicated the experiment in two consecutive years. In two of the three species we compared outcomes when root types were separated and unseparated, and for one species we also manipulated pot size. We assessed the effects of the manipulated factors on foraging precision expressed as the ratio of root biomass in nutrient-rich and poor patches.Results: Root foraging precision was not affected by experiment duration or pot size. Separating roots to use only the fine ones for root foraging assessment amplified foraging precision values and reduced their intraspecific variation.Conclusions: Our study investigated various methods of the root foraging research and their impact on the root foraging precision. Root foraging precision is invariable to the studied factors, therefore it is suitable as a species-specific trait, if the effect of other factors (such as nutrient patch characteristics) is taken into account.