Development and research of the parameters control system of the artificial ecosystem environment by the fuzzy-logic system

The paper considers the solution of scientific and practical problem of development and research of control system of parameters of environment of artificial ecosystem, creation of structural and basic electric scheme of system, drawing up of algorithm of its work. The study consists of statistical processing of the results of direct repeated measurements of soluble oxygen level, pH, temperature in the aquarium of the artificial ecosystem, analysis of errors and total standard uncertainty of measurement results, construction of a system with fuzzy logic to determine the impact of aquatic parameters on aquarium water quality. The system makes it possible to measure illuminance up to 45,000 lux, air temperature in the range from 12 to 42 0C, water temperature in the range from 15 to 28 0C, pH level from 5 to 9, dissolved oxygen level from 5 to 10 mg / l, has a proximity sensor , has the ability to turn on, if necessary, heating, water aeration, additional light sources. The measurement error on each of the channels does not exceed 2.5%. The need to create a control system arose due to the fact that there is a need to ensure the natural development of plants and fish in an artificial ecosystem that mimics the environment as close as possible to the natural one. In order for the ecosystem to perform its functions, it is necessary to timely control these parameters and respond quickly to the parameters exceeding the critical values. This task can be accomplished only by creating a control system. In order to bring people closer to the wildlife of exotic countries of the world, you can create corners of wildlife at school, enterprise, institution. An artificial ecosystem, which is a clear and versatile example of wildlife, will help students in the formation of a new culture of relationships with nature, the environment, and allow workers to relax morally by observing wildlife. Such a fruitful rest affects the recovery of people. The artificial ecosystem helps to involve children with talent in research work, in designing projects, performing works related to creativity.

Improved cellular automata model shows that indirect apoptotic cell death due to vascular damage enhances the local control of tumors by single fraction high-dose irradiation

We investigated the effects of indirect apoptotic cell death due to vascular damage on tumor response to a single large dose with an improved two-dimensional cellular automata model. The tumor growth was simulated by considering the oxygen and nutrients supplied to the tumor through the blood vessels. The cell damage processes were modeled by taking account of the direct cell death and the indirect death due to the radiation-induced vascular damages. The radiation increased the permeation of oxygen and nutrients through the blood vessel or caused the breakdown of the vasculature. The amount of oxygen in cancer cells affected the response of cancer cells to radiation and the tumor growth rate after irradiation. The lack of oxygen led to the apoptotic death of cancer cells. We calculated the tumor control probability (TCP) at different radiation doses, D, the probability of apoptotic death, PO2_ap, the threshold of the oxygen level for indirect apoptotic death, O2t, the average oxygen level in cancer cells, [O2]av, and the vessel survival probability after radiation damage, Pv. Due to the vessel damage, indirect cell death led to a 4% increase in TCP for the dose ranging from 15 Gy to 20 Gy. TCP increased with increasing PO2_ap and O2t due to increased apoptotic death. The variation of TCP as a function of [O2]av exhibited the minimum at [O2]av of 2.7%. The apoptosis increased as [O2]av decreased, leading to an increasing TCP. On the other hand, the direct radiation damage increased, and the apoptosis decreased for higher [O2]av, resulting in a higher TCP. We showed by modeling the radiation damage of blood vessels in a 2D CA simulation that the indirect apoptotic death of cancer cells, caused by the reduction of the oxygen level due to vascular damage after high dose irradiation, increased TCP.

LI-Care: A LabVIEW and IoT Based eHealth Monitoring System

This paper presents a Laboratory Virtual Instrument Engineering Workbench (LabVIEW) and Internet of Things (IoT)-based eHealth monitoring system called LI-Care to facilitate the diagnosis of the health condition cost-effectively. The system measures the heart rate, body temperature, blood pressure, oxygen level, and breathing rate, and provides an electrocardiogram (ECG). The required sensors are integrated on a web-based application that keeps track of the essential parameters and gives an alarm indication if one or more physiological parameters go beyond the safe level. It also employs a webcam to obtain the patient view at any time. LabVIEW enables the effortless interfacing of various biomedical sensors with the computer and provides high-speed data acquisition and interactive visualizations. It also provides a web publishing tool to access the interactive window remotely through a web browser. The web-based application is accessible to doctors who are experts in that particular field. They can obtain the real-time reading and directly perform a diagnosis. The parameters measured by the proposed system were validated using the traditional measurement systems, and the Root Mean Square (RMS) errors were obtained for the various parameters. The maximum RMS error as a percentage was 0.159%, which was found in the temperature measurement, and its power consumption is 1 Watt/h. The other RMS errors were 0.05% in measurement of systolic pressure, 0.029% in measurement of diastolic pressure, 0.059% in measurement of breathing rate, 0.002% in measurement of heart rate, 0.076% in measurement of oxygen level, and 0.015% in measurement of ECG. The low RMS errors and ease of deployment make it an attractive alternative for traditional monitoring systems. The proposed system has potential applications in hospitals, nursing homes, remote monitoring of the elderly, non-contact monitoring, etc.

The impact of cigarette smoking on the quality of sleep in Polish men

Quality of sleep directly impacts quality of life, whilst lifestyle significantly impacts night rest. Cigarette smoking is a serious threat to overall health, including sleep. Nicotine in cigarettes affects the nervous system, whilst the respiratory system is impacted by carcinogenic substances, such as dusts and tarred substances, inhaled with smoke. Cigarettes are assumed to be a risk factor in sleep disorders, including breathing sleep disorders. This study’s aim was to analyze the impact of cigarette smoking on adult men’s polysomnographic parameters. Polysomnographic records for 94 adult men were obtained from the polysomnography laboratory in Opolskie Province, Poland. Additionally co-morbidities, height, weight and frequency of smoking were also noted. Three groups of men were categorised according to the frequency with which they smoked: non-smokers, smoking less than a pack a day, smoking more than a pack a day. Compared to non-smokers and mild smokers, men who were heavy smokers also exhibited the longest sleepless time (H=8.11; p=0.017), the maximum waking time following the onset of sleep (H=7.99; p= 0.018), the lowest sleep efficiency across the three groups (H=7.96; p=0.019), the greatest number of apnea events per hour of sleep (H=6.23; p= 0.045), the lowest Oxygen Level Nadir (H=11.44; p= 0.003) and the highest rate of limb movements per hour of sleep (H=9.81; p=0.007). The dose effect was identified, which correlated more cigarettes men smoked per day with lower sleep quality.

Dynamics of the Great Oxidation Event from a 3D photochemical-climate model

From the Archean toward the Proterozoic, the Earth's atmosphere underwent a major shift from anoxic to oxic conditions, around 2.4 to 2.1 Gyr, known as the Great Oxidation Event (GOE). This rapid transition may be related to an atmospheric instability caused by the formation of the ozone layer. Previous works were all based on 1D photochemical models. Here, we revisit the GOE with a 3D photochemical-climate model to investigate the possible impact of the atmospheric circulation and the coupling between the climate and the dynamics of the oxidation. We show that the diurnal, seasonal and transport variations do not bring significant changes compared to 1D models. Nevertheless, we highlight a temperature dependence for atmospheric photochemical losses. A cooling during the late Archean could then have favored the triggering of the oxygenation. In addition, we show that the Huronian glaciations, which took place during the GOE, could have introduced a fluctuation in the evolution of the oxygen level. Finally, we show that the oxygen overshoot which is expected to have occurred just after the GOE, was likely accompanied by a methane overshoot. Such high methane concentrations could have had climatic consequences and could have played a role in the dynamics of the Huronian glaciations.

A floating photovoltaic system for fishery aeration

Photovoltaic panel as a producer of renewable energy is increasingly being utilized. The electrical energy produced by photovoltaic panel can be used for aeration in fish ponds located quite isolated and far from the main electricity grid. Aeration is important for fishery because it affects the dissolved oxygen level in the water. The system uses two units of 50 Wp floating solar panels and four units of DC aerator of 12 Volt/0.28 A. The measurement of solar irradiance, solar panel temperature, output voltage and current was conducted to monitor floating solar panel performance. Dissolved oxygen level measured in the water without aeration was 3 - 3.9 mg/L while after using floating photovoltaic panels to supply the electrical energy for aerators, dissolved oxygen level in the water was increased to 4.1 - 4.8 mg/L.

Model-based representational similarity analysis of blood-oxygen-level-dependent fMRI captures threat learning in social interactions

Past research has shown that attributions of intentions to other's actions determine how we experience these actions and their consequences. Yet, it is unknown how such attributions affect our learning and memory. Addressing this question, we combined neuroimaging with an interactive threat learning paradigm in which two interaction partners (confederates) made choices that had either threatening (shock) or safe (no shock) consequences for the participants. Importantly, participants were led to believe that one partner intentionally caused the delivery of shock, whereas the other did not (i.e. unintentional partner). Following intentional versus unintentional shocks, participants reported an inflated number of shocks and a greater increase in anger and vengeance. We applied a model-based representational similarity analysis to blood-oxygen-level-dependent (BOLD)-MRI patterns during learning. Surprisingly, we did not find any effects of intentionality. The threat value of actions, however, was represented as a trial-by-trial increase in representational similarity in the insula and the inferior frontal gyrus. Our findings illustrate how neural pattern formation can be used to study a complex interaction.