Purpose: Medical professionals throughout the world prefer to use conventional stethoscopes to listen to respiratory sounds. Listening to respiratory sounds through stethoscopes is a subjective matter, and proper diagnosis of the disease depends on the skills and ability of the doctor. Computerized analysis of respiratory sounds can help doctors and researchers to characterize different abnormal respiratory patterns and make informed decisions. Materials and Methods: This study includes previously reported work in different normal and abnormal respiratory sounds. The IEEE, PubMed, Google Scholar and Elsevier databases were searched and studies with the keywords of lung sound analysis, respiratory sound analysis, and respiratory sound classification were included. Detailed characteristics of normal and abnormal respiratory sounds are mentioned. In addition, Time-amplitude characteristics of different respiratory sound plots are obtained using MATLAB and ICBHI database. This study systematically discusses different approaches for respiratory sound analysis like visual analysis of the time-amplitude signals, frequency analysis, and spectral analysis using fast Fourier transform, statistical analysis, and machine learning approach. A list of relevant datasets is mentioned that can help researchers to do further analysis in this domain. Results: The careful observations and analysis show the possibility of predicting respiratory diseases by extracting suitable parameters such as the frequency response and spectral characteristics of the signal. Power spectral density can help us to calculate the maximum, median frequency over an extended period. Using machine learning we can estimate the energy, entropy, spectral features, and wavelets of the signals. Conclusion: Computer-based respiratory sound analysis can help medical professionals in making informed decisions. This will help in early diagnosis and devise effective treatment plans for the patients.

Adiantum capillus-veneris L. (Pare-siavashan) is a plant from the Pteridaceae family with many uses in traditional and folk medicine. This plant grows in different parts of the world. According to the references of Persian medicine, it has many positive effects on the digestive system, urogenital system, integumentary system, eyes, spleen, edema, and respiratory system (e. g., dyspnea). It is used in folk medicine in parts of the world to cure menstrual disorders, cold, cough, abdominal pain, fever, headache, bronchitis, hair loss, and diabetes. Contemporary researchers have proven the antioxidant, antimicrobial, and anti-inflammatory effects of this plant. The clinical studies conducted on the effects of this plant on respiratory diseases are few and more research is necessary. According to the properties mentioned for this plant, its use in the treatment of asthma and inflammatory diseases of the respiratory tract and its infections can be considered.

Background: Agate is a hard silica stone with bands of various colors, which is used in jewelry. The agate grinding workers are exposed to silica dust.Objective: To determine the prevalence of respiratory diseases in agate grinding workers and the associated factors.Methods: In this cross-sectional study, 170 agate grinding workers from Mashhad, northeastern Iran, were examined. Medical and occupational history for respiratory illnesses was taken using respiratory questionnaire of the national program of silicosis control, lung examination, spirometry and chest radiography. Chest x-rays were interpreted according to the International Labor Office (ILO) classification system, 2000.Results: The mean±SD of age and work duration of the participants were 31.2±10.1 and 13±8.2 years, respectively. The prevalence of silicosis among agate workers was 12.9% (95% CI: 7.9%-18.0%); 18 workers had simple and 4 had complicated silicosis. There was a significant (p<0.05) relationship between contracting silicosis and exposure duration. 20 (11.7%) workers had symptoms consistent with chronic bronchitis and 8 (4.7%) showed asthma and asthma-like symptoms. The most frequent disorder observed in spirometry was the restrictive pattern (n=43, 30%). In the agate grinders, clinical and spirometry findings did not match with radiological findings.Conclusion: Agate grinding workers are at increased risk for respiratory diseases, specifically for silicosis and chronic bronchitis. The disease is related to silica dust exposure, poor ventilation and inappropriate personal protection.

Background: Urban heat island (UHI) is being intensified with the progress of urbanization. Meanwhile, res-piratory diseases caused by high temperature become common. This study explores the influences of UHI on respiratory diseases (J00-J99) and the evolutionary characteristics of the spatial pattern of such influences. Methods: The pattern– process– function and the influencing mechanism of UHI on respiratory diseases were evaluated through landscape pattern indexes from 1992 to 2018 in Tianjin, China. The basis was on data from Landsat TM/OLI/TIRS remote-sensing images, meteorological stations, and mortality of respiratory diseases. Results: The fluctuating influence of UHI on the respiratory diseases in Tianjin has increased from 1992 to 2018, showing a significant phase-based characteristic. During 2011-2018, the influence has soared greatly, and mortality risk has increased by 101%, and the influenced area has reached 349 km² . Furthermore, the regional space clustered, and the influenced patches are in irregular shape, and the highly influenced area is enlarged. Moreover, the indexes of the landscape level of the influenced areas all decrease. The patches at all levels are fragmented and distributed discontinuously. Spatially, the influenced areas gradually extend from the urban center to the suburbs. Conclusion: UHI causes a higher mortality of respiratory diseases because it increases daily average air tem-perature in summer. With respect to landscape pattern, the influenced areas at low level is highly interconnect-ed and relatively concentrated, whereas the influenced area at high level is distributed in clusters. In general, the influenced area is fragmented and discontinuously distributed in urban center.

187 commercial chicken flocks affected with respiratory diseases were examined for Ornithobacterium rhinotracheale isolation. The bacterium was isolated from 105 (56.2%) poultry flocks. Drug sensitivity test using standard disk diffusion technique was performed with 19 antibiotics. All the isolates were susceptible to tiamulin and most of them were susceptible to chloramphenicol and linco-spectin. All the isolates were resistant to sulfamethoxazole-trimethoprim, colistin and neomycin and most of them were resistant to gentamicin, lincomycin, erythromycin, tetracycline, and enrofloxacin. One isolate from a native turkey was also tested. This isolate was resistant to sulfamethoxazole-trimethoprim, colistin, neomycin and gentamicin, but was sensitive to other tested antimicrobials. Because of acquired antibiotic resistance, and various result of antibiotic therapy, it must be stressed to prevent the infection.