The design and analysis of quartic double well potential with stochastic resonance for communication systems

Non-linearity and noise are two phenomena that are expected to be essential to future advanced technologies. Although largely abstained, in general, from introduction into current communication systems, the counter-intuitive phenomenon called Stochastic Resonance (SR) can be introduced into communication systems in an innovative form. Therefore, in this thesis, the most prominent dynamical system in the SR field, the double well potential, namely the over-damped Duffing equation with symmetric bistable potential, has been studied in order to reveal its signal processing capabilities for communication systems. Within this thesis, the double well potential was designed in order to detect a binary pulse amplitude modulated (BPAM) signal subject to a background noise. The bit-error-rate (BER) performance was enhanced by adding various resonant signals to the input. In addition, the eye patterns of system output indicated that, while decreasing BER, a resonant causes a strong fluctuation. It was eliminated by a use of two systems coupled in parallel, which provided further performance improvement. The results inferred that the double well potential performs filtering and modulation. Following that, the double well potential was designed as a lowpass filter by determining the DC gain and cut-off frequency. Through simulations, as a filter, its noise suppression performance was shown to be better than that of various orders of Butterworth filters. The analog and digital modulation capabilities of the double well potential have also been investigated. In order to clarify the relation between input signal and modulation parameters, the differential equation driving the output was solved, and thus the output was expressed as a function of modulation parameters. It was shown that the output is a multivariate analog modulated signal. In terms of digital modulation, the output of system processing a PAM signal has been interpreted by means of a Markov chain. The results indicated that this process consists of a convolutional coding and multidimensional modulation. In addition, the presence of noise induced coding was found. Finally, the system was designed to obtain a pulse width position modulated (PWPM) output. Throughout the project, detection, filtering, modulation and coding capabilities have been demonstrated, it has been concluded that the double well potential is an sophisticated signal processing tool

A stochastic resonator to detect BPAM signals ; analysis, PSR designs, and sine-induced SR

A Stochastic Resonator has been considered as an alternative signal processing tool because of its noise-induced performance enhancement ability. Here, the resonator parameters, steady states and transition time of the system are redefined for BPAM signals such that the region in which the resonator benefits from noise can be identified. Simple parameter-induced stochastic resonance (PSR) designs are then built, based on this analysis in order to configure the resonator in the optimum region. Furthermore, Sine-induced SR based on using a periodic signal instead of noise is introduced to enhance the system performance and compared with noise-enhanced SR (NSR). It is shown that Sine-induced SR provides a performance enhancement as it needs less power and does not require an adjustment relevant to the background noise. The results indicate that a resonator improves the receiver performance by eliminating noise if its parameters and BPAM characteristics are set accurately as given in the PSR designs, otherwise the resonator can benefit from either a noise as in NSR, or a sine wave as proposed

Near- and Mid-Infrared Spectroscopy Combined with Machine Learning Algorithms to Determine Minerals and Antioxidant Activity in Commercial Cheese

Erzincan Tulum Cheese (ETC) holds a significant place among the most popular cheeses in Türkiye. It has been awarded Protected Geographical Indication status, which restricts the allowable milk species, its production area, and specific sheep breed used in its production. Mineral content and antioxidant activity of ETC were aimed to be predicted using conventional FT-NIR and a portable FT-MIR spectrometer combined with partial least square regression (PLSR) and machine learning algorithms based on conditional entropy. Seventy ETC samples were analyzed for their mineral (Al, Ca, Cr, Cu, Fe, K, Mg, Mn, Na, and P) content using ICP-MS. The samples' antioxidant activity was measured using the DPPH•+ scavenging activity method. PLSR combined with FT-NIR spectral data correlated with antioxidant activity (r=0.89) and minerals (as low as r=0.83) except for Cr and Fe. FT-MIR data provided a good correlation for minerals (as low as r=0.82) except for Cr and Mn and a moderate correlation with antioxidant activity (r=0.64). Information theory was applied to select wavenumbers used in machine learning algorithms, and better results were obtained compared to PLSR. Overall, FT-NIR and FT-MIR spectroscopy provided rapid (~ 1 min), non-destructive, sensitive, and reliable output for mineral and antioxidant activity predictions in commercial cheese samples

The use of symmetric quartic potential well for noise filtering

In this letter, a symmetric quartic potential well is considered for use as a low-pass filter in BPAM receivers. By using the BPAM input to force a change in the shape of the well, the output can be considered as the position of a particle in the well. The potential well has been designed to pass the BPAM signal and suppress the background noise. Within the paper, DC gain and cut-o. frequency are defined where the potential well is subject to a noise free single pulse. The effects of the background noise are also discussed. These initial results are applicable to other pulse modulation methods. Moreover, it is revealed that the cut-o. frequency plays a significant role on the BPAM detector. Finally, a new result for the probability of error is introduced which clearly shows that the potential well filters out the background noise as much as a lowpass Butterworth filter does

Association of soluble ST2 Level with 6-month Mortality and/or Recurrent Cardiovascular-Related Hospitalization in Pulmonary Embolism Associação do Nível de ST2 Solúvel com Mortalidade em 6 Meses e/ou Hospitalização Recorrente Relacionada a Doenças Cardiovasculares em Embolia Pulmonar

Background: The association of soluble suppression of tumorigenesis-2 (sST2) levels with prognosis in pulmonary embolism (PE) is unknown. Objective: This study aimed to investigate the relationship between sST2 levels in patients with acute PE and 6-month mortality and recurrent hospitalizations. Methods: This prospective study included 100 patients with acute PE. Patients were classified into two groups according to 6-month mortality and the presence of recurrent Cardiovascular-Related hospitalizations. Two groups were compared. A p-value of 0.05 was considered statistically significant. Results: Soluble ST2 levels were significantly higher in the group with mortality and recurrent hospitalizations. (138.6 ng/mL (56.7-236.8) vs. 38 ng/mL (26.3-75.4); p89.9 with a specificity of 90.6% and a sensitivity of 65.2%, according to the receiver operating characteristic curve (area under the curve = 0.798; 95% CI, 0.705–0.891; p <0.0001). After adjusting for confounding factors that were either statistically significant in the univariate analysis or for the variables correlated with the sST2 levels, sST2 level (OR = 1.019, 95% CI: 1.009-1.028, p 0.001) and C-reactive protein (CRP) (OR = 1.010, 95% CI: 1.001-1.021, p = 0.046) continued to be significant predictors of 6-month mortality and/or recurrent Cardiovascular-Related hospitalization in the multiple logistic regression model via backward stepwise method. Conclusion: Soluble ST2 level seems to be a biomarker to predict 6-month mortality and/or recurrent Cardiovascular-Related hospitalization in patients with acute PE

Seroprevalence of coronavirus disease 2019 (COVID-19) among health care workers from three pandemic hospitals of Turkey

COVID-19 is a global threat with an increasing number of infections. Research on IgG seroprevalence among health care workers (HCWs) is needed to re-evaluate health policies. This study was performed in three pandemic hospitals in Istanbul and Kocaeli. Different clusters of HCWs were screened for SARS-CoV-2 infection. Seropositivity rate among participants was evaluated by chemiluminescent microparticle immunoassay. We recruited 813 non-infected and 119 PCR-confirmed infected HCWs. Of the previously undiagnosed HCWs, 22 (2.7%) were seropositive. Seropositivity rates were highest for cleaning staff (6%), physicians (4%), nurses (2.2%) and radiology technicians (1%). Non-pandemic clinic (6.4%) and ICU (4.3%) had the highest prevalence. HCWs in "high risk" group had similar seropositivity rate with "no risk" group (2.9 vs 3.5 p = 0.7). These findings might lead to the re-evaluation of infection control and transmission dynamics in hospitals