The very high need for personal protective equipment (PPE) impacts the waste generated after using these tools. Therefore, to deal with mask waste during the COVID-19 pandemic, this study was carried out on the processing of mask waste using a thermal process and studied how the potential of this process was for the effectiveness of mask waste processing during the pandemic. This research was conducted on Honeymoon Beach by collecting data on mask waste generated during the pandemic, then measuring the waste proximate, ultimate, and calorific value and testing the thermal process using TGA and Piro GC-MS measurements. Most waste masks found on Honeymoon Beach are non-reusable masks, 94.74%, while reusable masks are 5.26%. The waste is then subjected to thermal processing and analysis using TGA and Piro GC-MS. Based on the data obtained, the thermal process can reduce the mass of non-reusable and reusable mask samples by 99.236% and 88.401%, respectively.The results of the Piro GC-MS analysis show that the lit mask waste will produce fragments of compounds that can be reused as fuel. The process is simple and easy and produces residues that can be reused to reduce environmental pollution due to waste generation during the COVID-19 pandemic.

This paper is concerned with the determination of the auditory filter shape using the notched noise method with noise bands symmetrically located above and below a probe frequency of 10 kHz. Unlike in the classical experiments conducted with the use of Patterson method the levels as well as power spectrum densities of the lower and upper component bands of the notched noise masker were not the same and were set such as to produce the same amount of masking at the 10-kHz frequency. The experiment consisted of three conditions in which the following values were determined: (I) the detection threshold for a 10-kHz probe tone in the presence of a noise masker presented below the tone’s frequency; (II) the level of a noise masker presented above the 10-kHz probe tone frequency, at which the masker just masked the probe tone, (III) the detection threshold for a probe tone in the presence of a notched-noise masker. The data show a considerable amount of variability across the subjects, however, the resulting frequency characteristics of the auditory filters are consistent with those presented in the literature so that the Equivalent Rectangular Bandwidth is less than 11% of their centre frequency.

Voice controlled management systems are based on speech recognition techniques. The use of such systems in combat aircraft is complex due to a number of critical factors which affect the accuracy of speech recognition, such as high level of ambient noise and vibration, use of oxygen masks, serious psycho-physical stress of speakers, etc. One of the specificity of the oxygen mask application is overpressure breathing. The results of the simulations presented in this paper show that the presence of overpressure on the order of 1000 Pa in the vocal tract has a significant influence on the first two formant frequencies. The formants discrimination field is significantly reduced when oxygen mask is used, influencing both perceptive and automatic discrimination of spoken vowels.

In modern conditions in the field of medicine, raster image analysis systems are becoming more widespread, which allow automating the process of establishing a diagnosis based on the results of instrumental monitoring of a patient. One of the most important stages of such an analysis is the detection of the mask of the object to be recognized on the image. It is shown that under the conditions of a multivariate and multifactorial task of analyzing medical images, the most promising are neural network tools for extracting masks. It has also been determined that the known detection tools are highly specialized and not sufficiently adapted to the variability of the conditions of use, which necessitates the construction of an effective neural network model adapted to the definition of a mask on medical images. An approach is proposed to determine the most effective type of neural network model, which provides for expert evaluation of the effectiveness of acceptable types of models and conducting computer experiments to make a final decision. It is shown that to evaluate the effectiveness of a neural network model, it is possible to use the Intersection over Union and Dice Loss metrics. The proposed solutions were verified by isolating the brachial plexus of nerve fibers on grayscale images presented in the public Ultrasound Nerve Segmentation database. The expediency of using neural network models U-Net, YOLOv4 and PSPNet was determined by expert evaluation, and with the help of computer experiments, it was proved that U-Net is the most effective in terms of Intersection over Union and Dice Loss, which provides a detection accuracy of about 0.89. Also, the analysis of the results of the experiments showed the need to improve the mathematical apparatus, which is used to calculate the mask detection indicators.

Faster R-CNN is an algorithm development that continuously starts from CNN then R-CNN and Faster R-CNN. The development of the algorithm is needed to test whether the heuristic algorithm has optimal provisions. Broadly speaking, faster R-CNN is included in algorithms that are able to solve neural network and machine learning problems to detect a moving object. One of the moving objects in the current phenomenon is the use of masks. Where various countries in the world have issued endemic orations after the Covid 19 pandemic occurred. Detection tool has been prepared that has been tested at the mandatory mask door, namely for mask users. In this paper, the role of the Faster R-CNN algorithm has been carried out to detect masks poured on Internet of Thinks (IoT) devices to automatically open doors for standard mask users. From the results received that testing on the detection of moving mask objects when used reaches 100% optimal at a distance of 0.5 to 1 meter and 95% at a distance of 1.5 to 2 meters so that the process of sending detection signals to IoT devices can be carried out at a distance of 1 meter at the position mask users to automatic doors.

This paper proposes a speech enhancement method using the multi-scales and multi-thresholds of the auditory perception wavelet transform, which is suitable for a low SNR (signal to noise ratio) environment. This method achieves the goal of noise reduction according to the threshold processing of the human ear's auditory masking effect on the auditory perception wavelet transform parameters of a speech signal. At the same time, in order to prevent high frequency loss during the process of noise suppression, we first make a voicing decision based on the speech signals. Afterwards, we process the unvoiced sound segment and the voiced sound segment according to the different thresholds and different judgments. Lastly, we perform objective and subjective tests on the enhanced speech. The results show that, compared to other spectral subtractions, our method keeps the components of unvoiced sound intact, while it suppresses the residual noise and the background noise. Thus, the enhanced speech has better clarity and intelligibility.

In order to achieve accurate identification and segmentation of ore under complex working conditions, machine vision and neural network technology are used to carry out intelligent detection research on ore, an improved Mask RCNN instance segmentation algorithm is proposed. Aiming at the problem of misidentification of stacked ores caused by the loss of deep feature details during the feature extraction process of ore images, an improved Multipath Feature Pyramid Network (MFPN) was proposed. The network firstly adds a single bottom-up feature fusion path, and then adds with the top-down feature fusion path of the original algorithm, which can enrich the deep feature details and strengthen the fusion of the network to the feature layer, and improve the accuracy of the network to the ore recognition. The experimental results show that the algorithm proposed in this paper has a recognition accuracy of 96.5% for ore under complex working conditions, and the recall rate and recall rate function values reach 97.4% and 97.0% respectively, and the AP75 value is 6.84% higher than the original algorithm. The detection results of the ore in the actual scene show that the mask size segmented by the network is close to the actual size of the ore, indicating that the improved network model proposed in this paper has achieved a good performance in the detection of ore under different illumination, pose and background. Therefore, the method proposed in this paper has a good application prospect for stacked ore identification under complex working conditions.

Since March 11, 2020, the global community has faced the challenges of the COVID-19 pandemic. In response, numerous countries, including the Republic of Lithuania, mandated the wearing of face masks to curb the virus’s spread. Yet, a section of the Lithuanian populace resisted this move, voicing concerns about the inconvenience of mask-wearing and potential privacy infringements. These concerns endured, even amidst debates on the masks’ effectiveness. This article explores how the Lithuanian public responded to mask-wearing protocols during the pandemic. Survey analysis highlighted a troubling trend: many individuals dispose of face masks with their regular trash, often without proper packaging. Most masks are sourced from pharmacies or are provided by employers and are typically thrown away after just one day of use. The data underscores a significant knowledge gap in correct mask disposal, as a significant portion ends up mingled with general household waste, without proper containment. Moreover, many people keep used masks in pockets or bags. Notably, during the pandemic, an estimated 2 mln adult Lithuanians may have generated roughly 15.24 Mg of hazardous plastic waste through mask disposal.

The paper discusses the characteristics of spatial electromagnetic noise generators, as well as the formation of a broadband noise signal. A number of well-known methods for assessing the quality of masking noise interference and the approaches used in them have been described. Approaches to the measurement of masking noise were also determined in assessing their quality. In conclusion, additional methods are proposed for assessing the quality of masking noises, such as searching for correlation of noise in different frequency sub-bands and using statistical and (or) graphical methods (tests) for randomness.

In this article, we study tilted fiber Bragg gratings (TFBGs) with tilt angles of 6◦ and 8◦, their transmission spectra, and spectral parameters that have a linear dependence on the refractive index of the environment. It is shown that there can be several such characteristics, such as the minimum, width and energy of the spectrum. The linear dependence of the spectrum width on the refractive index does not depend on the tilt angle. The linear dependence of the spectrum minimum is only observed for a tilt angle of 8◦. The results of this work can be used to create a sensor system based on an optical fiber.

The aim of this work is to present problems related to tinnitus symptoms, its pathogenesis, hypotheses on tinnitus causes, and therapy treatment to reduce or mask the phantom noise. In addition, the hypothesis on the existence of parasitic quantization that accompanies hearing loss has been recalled. Moreover, the paper describes a study carried out by the Authors with the application of high-frequency dither having specially formed spectral characteristics. Discussion on preliminary results obtained and conclusions are also contained.

The foregoing article is an attempt at answering the question, whether Fiodor Sologub is rightly called a eulogist of evil and an apologist of devil, as well as a God-iconoclast. For this purpose the author is trying to revise the hitherto views concerning the fi gure of God in the lyric of the Russian poet. In the effect of conducted studies it was established that the myth of Sologub, “the literary Jack the Ripper”, functioning well until today was based on unjust and often prejudicial opinions of persons from the symbolist’s generation, as well as of the later experts in literature, who ascribed to them the “crimes” committed by the protagonists of his novels (sadism, erotomania, necrophilia and Satanism). The key problem of God-iconoclasty in turn, as it has been revealed, is connected with the issue of literary mask, a play with the reader. On one hand, the poet’s God-iconoclasty is an attempt of “getting inscribed” in the creative tendency that predominated in the Russian literature of that time (the “diabolic symbolism”), on the other – it constitutes one of the stages in looking for God and the development of lyrical “I”, carrying autobiographical traits.

Coronaviruses present a considerable concern for humans and animals. The current world- wide pandemic of SARS-CoV-2 virus showed many gaps in understanding of coronaviruses spread and transmission. Because of lack of effective vaccine against SARS-CoV-2 the only preventive measures are represented by wearing protective masks and gloves thus limiting potential risk of contact with the airborne virus. Inversely, the limited time of protective function of the masks presents another drawback of their use. Therefore, the application of disinfection agent dispersed on the surface of protective masks may enhance their effectivity and safety of their application. The aim of the study was to examine the virucidal efficacy of low-concentra- ted sodium hypochlorite dispersed using ultrasonic humidifier on the surface of surgery masks. The study was conducted using SARS-CoV-2 surrogate virus, namely porcine epidemic diarrhea virus (PEDV) representing a model with similar biophysical properties and genomic structure to human coronaviruses. Five different concentrations of the disinfectant with different content of sodium hypochlorite were selected for the study. A final concentration of 0.228 g/L sodium hypochlorite effectively inactivated the PED virus and may support the biosafety of masks usage.

The design of a low complexity multiplier-less narrow transition band filter bank for the channelizer of multistandard software-defined radio (SDR) is investigated in this paper. To accomplish this, the modal filter and complementary filter in the upper and lower branches of the conventional Frequency Response Masking (FRM) architecture are replaced with two power-complementary and linear phase filter banks. Secondly, a new masking strategy is proposed to fully exploit the potential of the numerous spectra replicas produced by the interpolation of the modal filter, which was previously ignored in the existing FRM design. In this scheme, the two masking filters are appropriately modulated and alternately masked over the spectra replicas from 0 to 2π, to generate even and odd channels. This Alternate Masking Scheme (AMS) increases the potency of the Modified FRM (ModFRM) architecture for the design of computationally efficient narrow transition band uniform filter bank (termed as ModFRM-FB). Finally, by combining the adjoining ModFRM-FB channels, Non-Uniform ModFRMFB (NUModFRM-FB) for extracting different communication standards in the SDR channelizer is created. To reduce the total power consumption of the architecture, the coefficients of the proposed system are made multiplier-less using Matching Pursuits Generalized Bit-Planes (MPGBP) algorithm. In this method, filter coefficients are successively approximated using a dictionary of vectors to give a sum-of-power-of-two (SOPOT) representation. In comparison to all other general optimization techniques, such as genetic algorithms, the suggested design method stands out for its ease of implementation, requiring no sophisticated optimization or exhaustive search schemes. Another notable feature of the suggested approach is that, in comparison to existing methods, the design time for approximation has been greatly reduced. To further bring down the complexity, adders are reused in recurrent SOPOT terms using the Common Subexpression Elimination (CSE) technique without compromising the filter performance.

This article brings together two authors/two poems and makes them enter into an intertextual dialogue that involves the discourses of the new materialism (Catherine Malabou), postphenomenology (Natalie Depraz and Marc Richir) and Delphic maxims. Concepts like plasticity, transformation masks, alterations in the passage of time (chronos, kairos, aeon), subjectivity, emotional excess, and the living body are used to establish the foundations a poetic conversation, which, for all one knows, may be fortuitous or in a way preordained.