MORAL MESSAGE ON THE VIDEO JOURNALIST CLIP “YURA YUNITA- TUTUR BATIN”: (Charles Sanders Peirce Semiotics Analysis)

Abstract: This research discusses the moral message contained the video clip Yura Yunita entitled Tutur Batin. This research focuses on knowing what are the moral messages contained in the video clip “Yura Yunita- Tutur batin". The research was to find out what the moral message conveyed in the video clip, researcher conduct qualitative methods and data obtained and then analyzed by Charles Sanders Peirce's semiotic approach to determine the symbolic meaning of the moral message to be conveyed in the video clip. The results showed that in the video clip “Yura Yunita-Tutur batin " those are many moral messages that we can take lessons for ourselves, among others, in the first scene women must be brave and strong, in the second scene shows that do not feel discouraged and insecure, the fourth scene shows the moral message do not look at someone from the physical, and scene 5 to 7 there is a moral message that is not perfect is not a problem because every human being has their own uniqueness.   Keywords: Moral Message, Semiotics, Video cli

Neural correlates of intentional switching from ternary to binary meter in a musical hemiola pattern

Musical rhythms are often perceived and interpreted within a metrical framework that integrates timing information hierarchically based on interval ratios. Endogenous timing processes facilitate this metrical integration and allow us using the sensory context for predicting when an expected sensory event will happen (“predictive timing”). Previously, we showed that listening to metronomes and subjectively imagining the two different meters of march and waltz modulated the resulting auditory evoked responses in the temporal lobe and motor-related brain areas such as the motor cortex, basal ganglia, and cerebellum. Here we further explored the intentional transitions between the two metrical contexts, known as hemiola in the Western classical music dating back to the sixteenth century. We examined MEG from 12 musicians while they repeatedly listened to a sequence of 12 unaccented clicks with an interval of 390 ms, and tapped to them with the right hand according to a 3 + 3 + 2 + 2 + 2 hemiola accent pattern. While participants listened to the same metronome sequence and imagined the accents, their pattern of brain responses significantly changed just before the “pivot” point of metric transition from ternary to binary meter. Until 100 ms before the pivot point, brain activities were more similar to those in the simple ternary meter than those in the simple binary meter, but the pattern was reversed afterwards. A similar transition was also observed at the downbeat after the pivot. Brain areas related to the metric transition were identified from source reconstruction of the MEG using a beamformer and included auditory cortices, sensorimotor and premotor cortices, cerebellum, inferior/middle frontal gyrus, parahippocampal gyrus, inferior parietal lobule, cingulate cortex, and precuneus. The results strongly support that predictive timing processes related to auditory-motor, fronto-parietal, and medial limbic systems underlie metrical representation and its transitions

Analysis of images recorded during welding processes,

Abstract In the paper elements of a system of assessment of a welding process and welded joints have been presented. The system was based on the application of one thermovision and two CCD cameras. In the paper exemplary results of processing and analysis of thermal and ordinary images have been discussed. Introduction The course of a welding process significantly influences the quality of welds. In order to obtain high quality joints proper parameters of welding process are required to be stable. In most cases by a correct welded joints one assumes the joints which are characterized not only by required mechanical properties but also by aesthetic quality. While the selection of proper welding parameters for an experienced welder does not make difficulties, the stability of these parameters is often not easy to be ensured. Abnormality of the process is caused by numerous factors which are often random. Examples are instability of passing of a filler wire, smudges of dirt, inaccuracy of preparation of element edges, deformations of elements as effects of thermal phenomena. These factors are reasons of common welding defects, such as excessive undercuts, partial or lack of joint penetration, cracks, overheatings, excessive convexity or concavity of a face of weld, blisters, bubbles and holes Maintenance of the high quality welding process and welds can be obtained by means of constant control of process parameters. One describes different approaches to the process inspection. Examples are measurements of amperage, voltage and flow of shielding gas The main problem concerning the application of vision systems seems to be a proper image analysis. In welding industry methods based on image analysis are being used for seam tracking Issues described in the paper are a part of investigations aimed at development of a system of controlling automatic welding processes. According to this approach, the vision system consists of three cameras. A crucial role is played be an IR camera, which observes a welding arc and pool, and the joint that is getting cold. Observation of the process is also aided by two CCD cameras, which record correspondingly images representing the arc and the joint. There are two goals of image analysis. The first one is to asses the stability of welding process, which is performed by means of determination of geometrical parameters of the arc. Secondly, some common defects of joints are supposed to be detected. It should be stressed that the application of IR camera lets us to detect not only surface defects but also defects and phenomena that do not manifest themselves on the surface. Presented experiments were carried out with the use of series of samples divided into some groups characterized by: correctly prepared surface, surface covered with rust, and parts covered with some impurities Overview of the vision system The welding process can be realized with the use of different devices. In industrial production automated and equipped with robots stands are commonly used, they enable MIG or MAG welding. Usually in such automated processes elements to be joined move and a welding device passing the filled wire is motionless. The vision system elaborated within the framework of the research described in the paper has been assigned to such processes. General overview of the system was presented in figure 1. The system let us to record, archive, process, analyze and recognize two types of images acquired by three presented cameras: -hot area that includes sub-areas of arc, metal in fluid and solidification phases and welded elements, -self-cooling area consisting of weld and welded elements sub-areas. The system has included hardware and software part

Breaking down the clotting conundrum: analyzing the role of plasma tissue plasminogen activator in COVID-19 patients through a systematic review and meta-analysis

INTRODUCTION: The SARS-CoV-2 virus pandemic has been a global challenge for medical services in terms of patient care and early prognosis of hospitalized patients' situations. Early identification and classification of COVID-19 patients in hospitals is critical for optimal management. The purpose of this study is to compile existing data on tissue plasminogen activator (tPA) concentrations in COVID-19 patients. MATERIAL AND METHODS: A systematic review and meta-analysis were carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Guidelines. Qualified articles were found systematically using relevant databases such as PubMed Central, Scopus, EMBASE, and the Cochrane databases until May 4th, 2023. RESULTS: Tissue plasminogen activator levels among COVID-19 positive vs negative patients T-PA levels among COVID-19 positive vs negative patients varied and amounted to 26.67 ± 40.65 vs 4.68 ± 3.83, respectively (SMD = 2.49; 95% CI: 1.85 to 3.14; p < 0.001). The mean t-PA level among patients requiring ICU admission was 24.06 ± 12.44, compared to 16.55 ± 10.01 for patients not treated in the ICU (SMD = 0.69; 95% CI: −0.68 to 2.05; p = 0.32). Moreover, t-PA levels among severe COVID-19 compared to non-severe were 11.89 ± 9.05 and 16.87 ± 20.39, respectively (SMD = 2.74; 95% CI: −0.71 to 6.19; p = 0.12). The t-PA values were, respectively: 15.33 ± 8.01 for patients who survived hospital discharge, and 19.04 ± 11.88 for patients who died in hospital due to COVID-19 (SMD = −0.50; 95% CI: −2.45 to 1.44; p = 0.61). CONCLUSIONS: According to this meta-analysis, the key conclusion of this study is that COVID-19 infection is connected to t-PA levels. Nonetheless, extensive prospective studies addressing the possible diagnostic relevance of t-PA as a marker of COVID-19 severity are required to corroborate the presented results

Evaluation of machinery technical state on the basis of statistical features of thermographic images

Termografia jest jedną z bardzo dynamicznie rozwijających się dziedzin nauki, umożliwiającą bezkontaktowy pomiar temperatury. Znajduje ona coraz częściej zastosowanie w diagnostyce maszyn i urządzeń. Za pomocą kamery termowizyjnej możliwa jest obserwacja rozkładu temperatury w wielu punktach obserwowanego obiektu i jej jednoczesny bezkontaktowy pomiar oraz rejestracja w postaci obrazu termograficznego. Ogromny potencjał informacyjny, jaki posiada obraz termograficzny, stanowi źródło informacji diagnostycznych przydatnych w diagnozowaniu maszyn i urządzeń. W celu wydobycia tych informacji konieczne jest prowadzenie analizy obrazu termograficznego. W artykule przedstawiono wyniki badań termograficznych polegających na wyznaczaniu wybranych cech statystycznych serii obrazów termograficznych rejestrowanych w równoodległych chwilach czasu podczas działania maszyny wirnikowej.Thermography is one of the most dynamically developing domains of science, which allows us to carry out non-contact temperature measurement. It finds more often and often the application in machinery and apparatus diagnostics. With the use of a thermographic camera one can simultaneously observe the distribution of temperature in many points of an object, measure it and record in the form of a thermographic image. Immense informative potential of a thermographical image is a source of diagnostic information, which can be used in diagnosing of machines and apparatus. In order to extract this information, thermographical image analysis is necessary to be applied. In the article results of thermographical investigations were presented. The research consists in recording of thermographical images during operation of rotating machinery and their analysis with the use of statistical analysis methods of images

Thermographic Criteria of Evaluation of Technical Condition of Machinery and Equipment

Infrared thermography is used for the diagnosis purposes of various machines and devices. Despite the huge potential of thermography as a diagnostic tool, beginning thermographers are not always able to correctly assess and classify condition of the investigated object. The article presents an overview of current standards, and characterizes the methods and criteria for assessing the condition of machines and equipment

Identification of technical state on the basis of analysis of state trajectory in eigenspace

Dysponując danymi uczącymi zarejestrowanymi podczas działania obiektu w różnych chwilach czasu "makro" oraz w różnych stanach technicznych, możliwe jest wyznaczenie przekształcenia przestrzeni wartości cech do przestrzeni wartości cech głównych. Posiadając parametry przekształcenia, można wyznaczyć wartości cech głównych w dowolnych chwilach czasu "makro". Poz.wala to na wyznaczenie trajektorii wartości cech głównych w dziedzinie czasu "makro" w oparciu o nowe, wcześniej nie analizowane dane pochodzące z badanego obiektu lub obiektu tej samej klasy. Wyznaczone trajektorie mogą być cennym źródłem informacji o zachodzących zmianach stanu technicznego maszyny podczas jej eksploatacji.Learning data obtained during machine operation in different moments of "macro" time and with taking into account different technical states make it possible to obtain transformation of a space of feature values of observed signals to the eigenspace of feature values. Basing on parameters of this transformation it is possible to obtain feature eigenvalues in any moment of "macro" time. It allows us to determine feature eigenvalues trajectory in "macro" time domain on the basis of new data which was previously unanalyzed and was taken from investigated object. Determined trajectories can be an important source of information about technical state of a machine