Detection of COVID-19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods

Since the first case of COVID-19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful approach to detect COVID-19 and COVID-19 findings from computed tomography images using pre-trained models using two different datasets. COVID-19, influenza A (H1N1) pneumonia, bacterial pneumonia and healthy lung image classes were used in the first dataset. Consolidation, crazy-paving pattern, ground-glass opacity, ground-glass opacity and consolidation, ground-glass opacity and nodule classes were used in the second dataset. The study consists of four steps. In the first two steps, distinctive features were extracted from the final layers of the pre-trained ShuffleNet, GoogLeNet and MobileNetV2 models trained with the datasets. In the next steps, the most relevant features were selected from the models using the Sine–Cosine optimization algorithm. Then, the hyperparameters of the Support Vector Machines were optimized with the Bayesian optimization algorithm and used to reclassify the feature subset that achieved the highest accuracy in the third step. The overall accuracy obtained for the first and second datasets is 99.46% and 99.82%, respectively. Finally, the performance of the results visualized with Occlusion Sensitivity Maps was compared with Gradient-weighted class activation mapping. The approach proposed in this paper outperformed other methods in detecting COVID-19 from multiclass viral pneumonia. Moreover, detecting the stages of COVID-19 in the lungs was an innovative and successful approach.     

Intrinsic plagiarism analysis

Research in automatic text plagiarism detection focuses on algorithms that compare suspicious documents against a collection of reference documents. Recent approaches perform well in identifying copied or modified foreign sections, but they assume a closed world where a reference collection is given. This article investigates the question whether plagiarism can be detected by a computer program if no reference can be provided, e.g., if the foreign sections stem from a book that is not available in digital form. We call this problem class intrinsic plagiarism analysis; it is closely related to the problem of authorship verification. Our contributions are threefold. (1) We organize the algorithmic building blocks for intrinsic plagiarism analysis and authorship verification and survey the state of the art. (2) We show how the meta learning approach of Koppel and Schler, termed “unmasking”, can be employed to post-process unreliable stylometric analysis results. (3) We operationalize and evaluate an analysis chain that combines document chunking, style model computation, one-class classification, and meta learning.     

Characterization and elemental analysis of wood pellets obtained from low-valued types of wood

In this study, we compared the quality of wood pellets obtained from several different raw materials, i.e., Rhododendron ponticum (Type 1), Laurus nobilis (Type 2), and Castanea sativa (Type 3). The quality of the wood pellets was characterized mainly by their bulk density, moisture content, ash content, volatiles, sulfur content in the ash, total sulfur content, heating values, elemental analysis of the ash, and chlorine content. The results showed that bulk density was similar for each type of pellet. In quality values, ash content and the sulfur content in the ash were found to be lower for Type 3 (Chestnut wood pellets) than they were for the other two types. The results also showed that dry samples of Type 1, Type 2, and Type 3 wood pellets had heating values of 5057, 4691, and 4571 kcal/kg, respectively, whereas the original (undried) samples had heating values of 4571, 4409, and 4293 kcal/kg, respectively.     

Physical and chemical properties of chufa (Cyperus esculentus L) tubers grown in the Çukurova region of Turkey

Four lines of chufa (Cyperus esculentus) grown in 1998 and 1999 in the Çukurova region of Turkey were analysed for their physical properties, proximate chemical composition and fatty acid contents. The chufa lines contained on average (g kg^?1) 932.8 dry matter, 245.0 crude lipid, 256.8 starch, 14.3 ash, 50.5 protein, 89.1 crude fibre, 17.1 reducing sugar, 154.3 total sugar and 130.4 sucrose. Hunter L, a⁺ and b⁺ colour values of ground chufa samples were in the ranges 55.93–60.59, 3.71–5.09 and 15.60–16.85 respectively. Individual chufa tubers weighed between 0.224 and 0.283 g. The fatty acid composition of chufa oil included (g kg^?1) 689.2–732.9 oleic acid, 125.5–141.2 palmitic acid and 99.6–154.6 linoleic acid, which is comparable with that of olive oil. After storage for 1 year the differences in mean values were significant (p < 0.05). © 2002 Society of Chemical Industry     

Effects of Different Treatments on the Inactivation of Various Seedborne Viruses in Some Vegetables

In this study, we considered the efficacy of seed treatments for the inactivation of some seedborne viruses in tomato, pepper, melon, squash, bean and lettuce seeds, which are essential for human nutrition and seed production in our country. A total of 325 seed samples obtained from various farmers and foundations were tested by DAS-ELISA and RT-PCR procedures. Eight seed lots infected with Tomato mosaic tobamovirus (ToMV), Tobacco mosaic tobamovirus (TMV), Cucumber mosaic cucumovirus (CMV), Soybean mosaic potyvirus (SMV) and Lettuce mosaic potyvirus (LMV) were selected as research materials. Virus inactivation treatments were made by using acetic acid (CH₃COOH), hydrogen peroxide (H₂O₂), hydrochloric acid (HCl), sodium hypochlorite (NaClO), Triton X 100, dry heat, heated water, ozone (O₃), and UV (305 nm wavelength). The most effective treatments for reducing virus concentration were HCl, heated water (65 °C) and ozone (10 g m^?3). These treatments reduced concentrations of seed-borne viruses in ranges of 51%, 42%, and 32%, respectively. Other treatments were less effective and reduced virus concentrations in the range of 27%–12%. HCl and ozone treatments were the most effective and applicable methods because they did not have negative effect on seed germination.     

Multisystemic therapy for adolescents with poorly controlled type I diabetes: Stability of treatment effects in a randomized controlled trial.

The primary purpose of the present study was to determine whether multisystemic therapy (MST), an intensive, home-based psychotherapy, improved regimen adherence, metabolic control, and rates of hospitalization for diabetic ketoacidosis (DKA) among adolescents with chronically poorly controlled Type 1 diabetes 6 months after the completion of treatment. A randomized controlled trial was conducted with 127 adolescents and their families. Mean participant age was 13.2 years. Sixty-three percent of participants were African American, and 51% were female. Data were collected at baseline, treatment termination, and 6-month follow-up. Changes in glycated hemoglobin (HbA1c), frequency of blood glucose testing (BGT), and rate of DKA admissions were assessed. In intent-to-treat analyses, a main effect of MST on DKA admissions was found at both treatment termination and follow-up. Improvements in BGT were moderated by family composition; only 2-parent MST families maintained improvements at follow-up. Improvements in HbA1c for the MST group at treatment termination were lost at follow-up. Results show that intensive, home-based psychotherapy created stable reductions in serious lapses in adherence, as indexed by episodes of DKA, among youth with poorly controlled diabetes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Particulate Dry Deposition and Overall Deposition Velocities of Polycyclic Aromatic Hydrocarbons

Previous studies have shown that the dry deposition of semivolatile organic compounds to the Great Lakes can account for a significant fraction of their total inputs. However, there is no generally accepted method to directly measure dry deposition. In this study the particulate dry deposition of polycyclic aromatic hydrocarbons (PAHs) was measured using smooth surrogate surfaces during the winter of 1996–1997 in Chicago. Concurrently, ambient air samples were collected. Average particulate Σ13-PAH fluxes and ambient concentrations were 120±28?μg/m2?d and 30±16?ng/m3, respectively. The measured particulate dry deposition fluxes were similar to those measured in other urban areas. Overall dry deposition velocities of PAHs calculated using the dry deposition fluxes and ambient concentrations averaged 4.5±3.1?cm/s. This value is higher than values typically used to estimate PAH particulate deposition, however, it agrees well with values determined using similar techniques. The overall dry deposition velocity for individual PAHs generally decreased with increasing molecular weight. This finding is consistent with the previous experimental studies that have shown that a greater fraction of the higher molecular weight PAHs are associated with fine particles relative to the lower molecular weight compounds.