Association between the dysfunctions of the stomatognathic system and the disorders in the statics of the body

INTRODUCTION The stomatognathic system is a group of tissues and organs consisting of: the mandible, teeth (upper and lower), two temporomandibular joints, muscles, ligaments and numerous vessels: nerve, blood and lymph. We define the body posture as an individual, individual feature of each person, which is expressed by the figure. A defect of posture or a disorder of the body statics is any anomaly from the correct posture that may be congenital or acquired. OBJECTIVE The main aim of the study was to assess the relationship between dysfunctions of the stomatognathic system and disturbances in body statics. The research was conducted from January to February 2022 using the proprietary questionnaire, which was made available online (Google Forms). RESULTS At least one symptom of body statics disorders was noticeable in 77 people from the group of people with problems within the stomatognathic system (88,51%). Only 10 people with disorders of the masticatory system motor system did not report any postural abnormalities (11,49%). The results of the research show that there is a statistically significant relationship between the occurrence of dysfunctions within the stomatognathic system and disturbances in body statics (x2 = 28,11 > x2 = 22,4570,001;6 - statistically significant relationship, rc = 0,304 - average strength of the relationship). CONCLUSIONS The complexity of the issue shows that focusing on only one problem may not produce the measured therapeutic effects. Only comprehensive and properly planned treatment brings the maximum therapeutic effect

Symptoms of functional disorders of the stomatognathic system among students

INTRODUCTION The stomatognathic system is a morphological and functional group of tissues and organs, the main task of which is food intake, initial chewing and digestion, but also emotional expression, speech articulation and breathing. Dysfunctions in the masticatory system may take the form of: muscle or joint pain, excessive muscle tension, crackles in the temporomandibular joints and reduced mobility, tooth clenching or ear ailments, especially in the form of: noise, hypersensitivity or deterioration of hearing. OBJECTIVE The main aim of the study was to assess the occurrence of functional dysfunctions of the stomatognathic system among students. The research was carried out from January to February 2022 using the proprietary online questionnaire and the results were statistically analyzed using the chi-square test. RESULTS There was a statistically significant relationship (p≤0,05) between the occurrence of stomatognathic system disorders and the location of the headache (rc = 0,0252 – weak strength of the relationship), muscle tension (rc = 0,304 - average strength of the relationship) and ear ailments (rc = 0,35 - average strength of the relationship). CONCLUSIONS The most important issue in the treatment of stomatognathic system disorders is the interdisciplinary and holistic view of the patient. It is important to introduce multidirectional and multi-stage therapy, thanks to which we can achieve maximum therapeutic effects

Disorders of the statics of the body and the temporomandibular joint

INTRODUCTION The temporomandibular joint is a synovial, complex (hinge-sliding) joint that connects the temporal bone with the mandible by means of an articular disc. Temporomandibular joint dysfunctions most often concern several disease entities and include various symptoms and ailments. One of the first symptoms of the disease is pain that stems from a muscle or joint. In addition, we can observe: limitations in the mobility and range of movement of the jaw, problems with chewing food, crackles in the joint, pain in pressure and touch of the muscles, earaches and noise or changes in the appearance of the face (the so-called "square face"). Any deviation from the correct body posture is called a posture defect. OBJECTIVE The main aim of the study is to present the significant relationship between disturbed statics of the body and the temporomandibular joint, thanks to which we can explain the importance of proper planning of diagnostics as well as conducting dental and physiotherapeutic therapy. THE WEIGHT OF THE BODCIES The materials used to write the article include scientific works from 1992-2021. The data was collected using the PubMed search engine and manual filtering. 80 publications were qualified for the analysis. SUMMARY According to the analyzed literature, we believe that there is a relationship between disturbances in the body statics and the stomatognathic system. The complexity of the issue shows that it is important to conduct multi-directional and interdisciplinary therapy

MCPA decomposition method in soil matrix using ozone as an oxidant ***

In presented research a method for remediation of MCPA contaminated soil based on the combination of fluidization process technique and ozone was utilized. Exposition of soil contaminated with MCPA at the concentration of 0,1 % w/w on the a mixture of air and ozone allowed for removal of over 90% of MCPA in form of MCPA 2-ethylhexanol-ester (MCPA 2-EHE) in laboratory conditions. The efficacy of the method was proven by GC-MS analysis of MCPA concentration profile during soil remediation procedure and by comparing of kinetic data, such as half life time, with the natural half life time of MCPA in the soil.

A global atmospheric electricity monitoring network for climate and geophysical research

The Global atmospheric Electric Circuit (GEC) is a fundamental coupling network of the climate system connecting electrically disturbed weather regions with fair weather regions across the planet. The GEC sustains the fair weather electric field (or potential gradient, PG) which is present globally and can be measured routinely at the surface using durable instrumentation such as modern electric field mills, which are now widely deployed internationally. In contrast to lightning or magnetic fields, fair weather PG cannot be measured remotely. Despite the existence of many PG datasets (both contemporary and historical), few attempts have been made to coordinate and integrate these fragmented surface measurements within a global framework. Such a synthesis is important elvinin order to fully study major influences on the GEC such as climate variations and space weather effects, as well as more local atmospheric electrical processes such as cloud electrification, lightning initiation, and dust and aerosol charging. The GloCAEM (Global Coordination of Atmospheric Electricity Measurements) project has brought together experts in atmospheric electricity to make the first steps towards an effective global network for atmospheric electricity monitoring, which will provide data in near real time. Data from all sites are available in identically-formatted files, at both one second and one minute temporal resolution, along with meteorological data (wherever available) for ease of interpretation of electrical measurements. This work describes the details of the GloCAEM database and presents what is likely to be the largest single analysis of PG data performed from multiple datasets at geographically distinct locations. Analysis of the diurnal variation in PG from all 17 GloCAEM sites demonstrates that the majority of sites show two daily maxima, characteristic of local influences on the PG, such as the sunrise effect. Data analysis methods to minimise such effects are presented and recommendations provided on the most suitable GloCAEM sites for the study of various scientific phenomena. The use of the dataset for a further understanding of the GEC is also demonstrated, in particular for more detailed characterization of day-to-day global circuit variability. Such coordinated effort enables deeper insight into PG phenomenology which goes beyond single-location PG measurements, providing a simple measurement of global thunderstorm variability on a day-to-day timescale. The creation of the GloCAEM database is likely to enable much more effective study of atmospheric electricity variables than has ever been possible before, which will improve our understanding of the role of atmospheric electricity in the complex processes underlying weather and climate

Relativistic electron beams above thunderclouds

Non-luminous relativistic electron beams above thunderclouds have been detected by the radio signals of low frequency ∼40–400 kHz which they radiate. The electron beams occur ∼2–9 ms after positive cloud-to-ground lightning discharges at heights between ∼22–72 km above thunderclouds. Intense positive lightning discharges can also cause sprites which occur either above or prior to the electron beam. One electron beam was detected without any luminous sprite which suggests that electron beams may also occur independently of sprites. Numerical simulations show that beams of electrons partially discharge the lightning electric field above thunderclouds and thereby gain a mean energy of ∼7 MeV to transport a total charge of ∼−10 mC upwards. The impulsive current ∼3 × 10<sup>−3</sup> Am<sup>−2</sup> associated with relativistic electron beams above thunderclouds is directed downwards and needs to be considered as a novel element of the global atmospheric electric circuit

Challenges in coupling atmospheric electricity with biological systems

The atmosphere is host to a complex electric environment, ranging from a global electric circuit generating fluctuating atmospheric electric fields to local lightning strikes and ions. While research on interactions of organisms with their electrical environment is deeply rooted in the aquatic environment, it has hitherto been confined to interactions with local electrical phenomena and organismal perception of electric fields. However, there is emerging evidence of coupling between large- and small-scale atmospheric electrical phenomena and various biological processes in terrestrial environments that even appear to be tied to continental waters. Here, we synthesize our current understanding of this connectivity, discussing how atmospheric electricity can affect various levels of biological organization across multiple ecosystems. We identify opportunities for research, highlighting its complexity and interdisciplinary nature and draw attention to both conceptual and technical challenges lying ahead of our future understanding of the relationship between atmospheric electricity and the organization and functioning of biological systems

Measuring global signals in the potential gradient at high latitude sites

Previous research has shown that the study of the global electrical circuit can be relevant to climate change studies, and this can be done through measurements of the potential gradient near the surface in fair weather conditions. However, potential gradient measurements can be highly variable due to different local effects (e.g., pollution, convective processes). In order to try to minimize these effects, potential gradient measurements can be performed at remote locations where anthropogenic influences are small. In this work we present potential gradient measurements from five stations at high latitudes in the Southern and Northern Hemisphere. This is the first description of new datasets from Halley, Antarctica; and Sodankyla, Finland. The effect of the polar cap ionospheric potential can be significant at some polar stations and detailed analysis performed here demonstrates a negligible effect on the surface potential gradient at Halley and Sodankyla. New criteria for determination of fair weather conditions at snow covered sites is also reported, demonstrating that wind speeds as low as 3m/s can loft snow particles, and that the fetch of the measurement site is an important factor in determining this threshold wind speed. Daily and seasonal analysis of the potential gradient in fair weather conditions shows great agreement with the “universal” Carnegie curve of the global electric circuit, particularly at Halley. This demonstrates that high latitude sites, at which the magnetic and solar influences are often present, can also provide globally representative measurement sites for study of the global electric circuit

Automatic detection of Ionospheric Alfvén Resonances in magnetic spectrograms using U-net

Ionospheric Alfven Resonances (IARs) are weak discrete non-stationary Alfven waves along magnetic field lines, at periods of ~0.5-20 Hz, that occur during local night-time, particularly during low geomagnetic activity. They are detectable through time-frequency analysis (spectrograms) of measurements made by sensitive search coil magnetometers. The IARs are generated by the interaction of electromagnetic energy partially trapped in the Earth-ionosphere cavity with the main geomagnetic field and their behavior provides proxy information about atmospheric ion density between 100-1000 km altitude. Limited methods exist to automatically detect and analyse their properties and behavior as they are difficult to extract using standard image and signal processing techniques. We present a new method for the detection of IARs based on the fully convolutional neural network U-net. U-net was chosen as it is able to perform accurate image segmentation and it can be trained in a supervised fashion on a relatively small labeled dataset utilizing data augmentation. We show that the resulting predictive model generated by training the U-net is able to detect IAR signals while mislabelling considerably less noise than other data analysis methods. We achieved our best results by using a training set of 178 hand-digitized examples from high-quality spectrograms measured at the Eskdalemuir Geophysical Observatory (UK). We find that the network converges in ten iterations with a final intersection over union (IoU) metric of 0.9 and a training loss of below 0.2. We use the trained network to extract IARs from over 2300 images, covering six years of search coil magnetometer data measured at the Eskdalemuir Observatory. U-net can also automatically handle missing data or days without IARs, giving a null result as expected. This constitutes the first use of a neural network for pattern recognition of unstructured image data such as spectrograms containing IAR signals, though the method is applicable to other types of resonances or geophysical features in the time-frequency domain