Electrochemical detection of kynurenic acid in the presence of tryptophan with the carbon paste electrode modified with the flower-like nanostructures of zinc oxide doped with terbium

With the help of a hydrothermal approach in this study, we could provide flower-like nanostructures (NSs) of zinc oxide (ZnO) doped with Tb (FL-NS Tb3+/ZnO). Then, FL-NS Tb3+/ZnO morphology was investigated by energy-dispersive X-ray spectroscopy (EDX), scanning electron microscopy (SEM), X-ray powder diffraction (XRD), and map analysis. The results revealed higher activity centers and porosity of this nanocomposite, which were followed by acceptable electrochemical function. Hence, it can be utilized for fabricating an electrochemical sensor with an appropriate response for the simultaneous determination of kynurenic acid (KYN) and tryptophan (TRP). However, as compared with the modified carbon paste electrode (FL-NS Tb3+/ZnO/CPE), the bare carbon paste electrode (BCPE) exhibited a weak response toward KYN and TRP but the modified electrode was followed by a high current response for KYN and TRP at a potential 0.35 and 0.809 V. Therefore, cyclic voltammetry (CV) was applied in optimal experimental conditions to study the electrochemical behaviors of KYN and TRP over the surface of the proposed modified electrode. Moreover, we used differential pulse voltammetry (DPV) for quantitative measurements. It was found that this new modified electrode linearly ranged from 0.001 to 700.0 μM, with detection limits of 0.34 nM and 0.22 nM for KYN and TRP, respectively. In addition, KYN and TRP in real samples can be analyzed by this sensor, with a recovery of 97.75%−103.6% for the spiked KYN and TRP in real samples

Diagnostic Accuracy of Rapid Antigen Tests for COVID-19 Detection: A Systematic Review With Meta-analysis

Introduction: Reverse transcription-polymerase chain reaction (RT-PCR) to detect SARS-CoV-2 is time-consuming and sometimes not feasible in developing nations. Rapid antigen test (RAT) could decrease the load of diagnosis. However, the efficacy of RAT is yet to be investigated comprehensively. Thus, the current systematic review and meta-analysis were conducted to evaluate the diagnostic accuracy of RAT against RT-PCR methods as the reference standard. Methods: We searched the MEDLINE/Pubmed and Embase databases for the relevant records. The QUADAS-2 tool was used to assess the quality of the studies. Diagnostic accuracy measures [i.e., sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratios (PLR), negative likelihood ratios (NLR), and the area under the curve (AUC)] were pooled with a random-effects model. All statistical analyses were performed with Meta-DiSc (Version 1.4, Cochrane Colloquium, Barcelona, Spain). Results: After reviewing retrieved records, we identified 60 studies that met the inclusion criteria. The pooled sensitivity and specificity of the rapid antigen tests against the reference test (the real-time PCR) were 69% (95% CI: 68–70) and 99% (95% CI: 99–99). The PLR, NLR, DOR and the AUC estimates were found to be 72 (95% CI: 44–119), 0.30 (95% CI: 0.26–0.36), 316 (95% CI: 167–590) and 97%, respectively. Conclusion: The present study indicated that using RAT kits is primarily recommended for the early detection of patients suspected of having COVID-19, particularly in countries with limited resources and laboratory equipment. However, the negative RAT samples may need to be confirmed using molecular tests, mainly when the symptoms of COVID-19 are present. Keywords: COVID-19, SARS-CoV-2, rapid antigen test, specificity, sensitivity, meta-analysi

Investigation of Uncertainty to Artificial Intelligence Models in Tabriz Wastewater Treatment Plant

In this paper, the uncertainty of artificial intelligence models for evaluting performance of the activated sludge unit of the Tabriz treatment plant is assessed. In this regard, daily data of pollution parameters, particularly Biochemical Oxygen Demand and Chemical Oxygen Demand, are utilized. All data were collected daily during the years (2015-2020) and the best parameters were selected using the correlation coefficient criterion. The TSSi, TDSi, VSSi, pHi parameters and also, BODe and CODe with a one-day delay were selected as model input and BODe and CODe were selected as model output. The calculations of uncertainties were performed in two models of Feed Forward Neural Network as point prediction and lower upper bound estimation method to provide the Prediction Interval. The LUBE method, unlike the classical methods of calculating PI, estimates PI without the need for data distribution information. In this method, the FFNN was trained with two outputs indicating the upper and lower limits of the prediction. PICP assessment and comparing it with μ values, caused γ values to equal zero that, in the continuation of the calculation process caused CWC extraction with the minimum possible amount and production of PI for computational data and observations with the possibility of controlling random changes in the activated sludge section. So, the convergence of the LUBE method has the ability to effectively control the uncertainty between the parameters of the biological section of activated sludge using PI. The time required to build PI is considerably short. Numerical results show approximately 99% success in calculations and coverage of modeling uncertainties. Providing an oscillating range of uncertainties can be a valuable aid in improving economic conditions as well as reducing activated sludge control time and better treatment plant monitoring. Despite the design criteria for BODe of 20 mg per liter, PI results show a supply of 12% of the design index. However, considering the supply of the remaining 88% in terms of quality standard for the use of effluents and returned water, according to the Deputy of Strategic Supervision, publication 535, at the rate of 31 mg per liter in the activated sludge sector, the proper performance of the treatment plant is demonstrated. The LUBE method is an efficient method, so by providing an optimized range of fluctuations for computational data, the smallest abnormal changes in the activated sludge section due to controlling the amount of food for the micro-organisms present in this section; also, the pollution indicators with the least computing time are also reported. In addition, due to the high cost of activated sludge in the wastewater treatment sector, from an economic point of view, it also helps reduce costs. According to the non-linear behavior of bacteria during the reduction of food, as well as the control of mortality caused by the reduction of food, it can be considered a very effective tool

Thermal conductivity prediction for nitrogen and carbon monoxide at the zero density regime via semi-empirically based assessment

24-32Thermal conductivity coefficients for gaseous states of N₂ and CO have been calculated by the inversion technique in conjunction with Wang Chang-Uhlenbeck-de Boer (WCUB) approach of the kinetic theory of gases for considering the various contributions of the molecular degrees of freedom to the thermal conductivity. The values of calculated thermal conductivity coefficients are commensurate with best experimental values

Psychometric Properties of the Persian Version of Penn Parkinson Daily Activities Questionnaire-15

Introduction: Appropriate information about the ability of patients with Parkinson disease (PD) to perform cognitive instrumental activities of daily living (IADL) is necessary. The present study aimed to assess the psychometric properties of the Persian version of the Penn Parkinson daily activities questionnaire-15 (PDAQ-15). Methods: A total of 165 knowledgeable informants of PD patients completed the PDAQ-15. The clinical dementia rating scale, Hoehn and Yahr staging, hospital anxiety and depression scale (HADS), and Lawton IADL scale were used in the study. Internal consistency and test-retest reliability were evaluated by the Cronbach α coefficient and intraclass correlation coefficient (ICC), respectively. To examine the dimensionality of the questionnaire, exploratory factor analysis was used. The construct validity was assessed using the Spearman rank correlation test. To assess the discriminative validity, PDAQ-15 scores were compared across cognitive stages. Results: The PDAQ-15 showed strong internal consistency (the Cronbach α=0.99) and test-retest reliability (ICC= 0.99). Only one dimension was identified for the PDAQ-15 in the factor analysis. There was a strong correlation between PDAQ-15 with the depression domain of the HADS scale and the Lawton IADL scale (rs=|0.71–0.95|). The correlation of PDAQ-15 with the anxiety domain of the HADS scale was moderate (rs=0.66). Discriminative validity analysis showed that the PDAQ-15 has significant power to discriminate between PD patients across cognitive stages. Conclusion: These results suggest that the PDAQ-15 is a valid and reliable PD-specific instrument and can be useful in clinical and research settings

Prediction of the Void Ratio Parameter in Mineral Tailings Using Gene Expression Programming

Mineral tailing deposits are one of the most important issues in the field of geotechnical engineering. The void ratio of mineral tailings is an essential parameter for investigating the geotechnical behavior of tailings. However, there has not yet been a comprehensive empirical formulation for initial prediction of the void ratio of mineral tailings. In this study, the void ratio of various types of mineral waste is estimated by using gene expression programming (GEP). Therefore, taking into consideration the effective physical parameters that affect the estimation of this parameter, eight different models are presented. A reliable experimental database collected from different sources in the literature was applied to develop the GEP models. The performance of the developed GEP models was measured based on coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE). According to the results, the model with effective stress σ′, initial void ratio (e0), and parameters of R2 = 0.92, MAE = 0.109, and RMSE = 0.180 performed the best. Finally, a new empirical formulation for the initial prediction of the void ratio parameter is proposed based on the aforementioned analyses