BACTERIAL AND SENSITIVITY PATTERN OF PATHOGENS CAUSING VENTILATOR-ASSOCIATED PNEUMONIA IN INTENSIVE CARE UNIT

Highlight:1. Antimicrobial resistance bacteria isolated from VAP patients are often associated with high mortality and length of hospital stay. 2. Mortality in VAP patients was 33.3% and the VAP group had a longer hospital stay compared to the non-VAP group. 3. The three most predominant bacteria that were found were A. baumannii, P. aeruginosa, K. pneumoniae. Cefoperazone-sulbactam, meropenem and amikacin were more than 70% sensitive against these bacteria.Abstract:Background: Ventilator-Associated Pneumonia (VAP) is the most common nosocomial infection in Intensive Care Unit (ICU). Antimicrobial resistant bacteria isolated from VAP patients are often associated with high mortality and length of hospital stay. Objective: This study aimed to analyze the pattern and sensitivity among pathogens that caused VAP in ICU. Materials and Methods: The study was conducted retrospectively by extracting the data of bacterial isolates from sputum specimens in the Laboratory of Clinical Microbiology, Dr. Soetomo General Academic Hospital, Surabaya, Indonesia and confirming the clinical data on patients suffering from VAP in ICU ward. The study started from January until December 2017. Results: The total 148 pathogens were isolated, 18 of them were diagnosed as VAP, and 130 were not VAP. The most predominant isolates in the VAP group were Acinetobacter baumannii as many as 38 (9%) followed by Pseudomonas aeruginosa 22 (2%), E. coli 16 (7%), and Klebsiella pneumoniae 11 (1%). The pathogens showed a sensitivity rate above 70% to cefoperazone-sulbactam (SCF), meropenem (MEM) and amikacin (AK). Mortality in VAP patients was 33.3% and the VAP group had a longer hospital stay compared to non-VAP group. Conclusion: The three most predominant bacteria that were found were A. baumannii, P. aeruginosa, K. pneumoniae. The pathogens had sensitivity rate above 70% to cefoperazone-sulbactam, meropenem, and amikacin.

Study of Investment in the Organic Fertilizer Industry to Improve Community Economists

Based on the results of observations of organic waste in the village of Jogotirto Berbah, Sleman, it is known that the amount of household organic waste and cow dung from 2015 to 2020 continues to increase by ± 12% per year. In Jogotirto, the average person produces 0.36 kg of organic waste per day and 15 kg of dry cow dung per day. In 2020 the amount of household organic waste is 8,477 kg per day, while for cow dung is 16,787.75 kg per day. Analysis of the study of the establishment of the organic fertilizer industry is carried out by processing household organic waste and solid cow dung by fermentation. This fermentation process is carried out anaerobically for 21 days. The organic fertilizer processing process is carried out by mixing cow dung and household waste with varying ratios. From the results of research on making organic fertilizer, it is known that a mixture of cow dung and household waste with a mixture ratio of 2: 1 contains nitrogen compounds as much as 1.04%, organic C 17.6%, phosphorus 1.7% and potassium as much as 7.02%. Based on the analysis of investment feasibility using the Net Present Value method, the fertilizer industry can generate a profit of 200.18% for 5 years. Analysts using the ROR method can provide a profit of 31.7% per year and the analysis using the pay back method is known that the period of capital will return after 3.85 years. Based on the sensitivity test of the fertilizer industry, it is still said to be safe for changes in influencing parameters, namely the sensitivity rate of 20%. This study of the establishment of the organic fertilizer industry aims to provide advice to the government in the context of improving the community's economy.

Using a recurrent neural network with S2 characteristics, efficient identification of localised cortical dysplasia

Focal cortical dysplasia (FCD) is an inborn anomaly in brain growth and morphological deformation in lesions of the brain which induces focal seizures. Neurosurgical therapies were performed for the detection of FCD. Furthermore, it can be overcome through the presurgical evaluation of epilepsy. The surgical result is attained basically through the output of the presurgical output. In preprocessing the process of increasing true positives with the decrease in false negatives occurs which results in an effective outcome. MRI (Magnetic Resonance Imaging) outputs are efficient to predict the FCD lesions through T1- MPRAGE and T2- FLAIR efficient output can be obtained. In our proposed work we extract the S2 features through the testing of T1, T2 images. Using RNN-LSTM (Recurrent neural network-Long short-term memory) test images were trained and the FCD lesions were segmented. The output of our work is compared with the proposed work yields better results compared to the existing system such as artificial neural network (ANN), support vector machine (SVM), and convolution neural network (CNN). This approach obtained an accuracy rate of 0.195% (ANN), 0.20% (SVM), 0.14% (CNN), specificity rate of 0.23% (ANN), 0.15% (SVM), 0.13% (CNN) and sensitivity rate of 0.22% (ANN), 0.14% (SVM), 0.08% (CNN) respectively in comparison with RNN-LSTM.

SENSITIVITY OF THREE THYROTROPIN RECEPTOR ANTIBODY ASSAYS IN THYROID-ASSOCIATED ORBITOPATHY

Background: Thyrotropin receptor autoantibodies (TSH-R-Ab) are indispensable biomarkers in the laboratory assessment of thyroid-associated orbitopathy (TAO). Clinical sensitivity of three different assays for TSH-R-Ab determination was evaluated in patients with TAO. Methods: 87 consecutive TAO patients were enrolled and their serum samples analyzed in parallel with three assays. An ECLIA competitive binding and a chemiluminescent bridge immunoassay were used to measure total and binding TSH-R-Ab concentration, while their functional activity was determined using a stimulatory TSH-R-Ab (TSAb) cell-based bioassay. Results: Compared to the two binding assays (ECLIA p<0.001, bridge p=0.003), the TSAb bioassay was more sensitive pertaining to the positive detection of TSH-R-Ab in TAO patients. No difference (p=0.057) was noted between the ECLIA and bridge assays regarding sensitivity rate. All patients with active and/or moderate-to-severe TAO tested positive in the TSAb bioassay (100% and 100%, respectively), while the positivity rates for bridge and ECLIA binding assays were 89.7% and 82.1% for active TAO, and 90.2% and 86.3% for severe TAO, respectively. Negative predictive values of the bioassay, bridge, and ECLIA assays were 100%, 75%, and 71%, respectively for active TAO, and 100%, 86%, and 71%, respectively for moderate-to-severe TAO. The superiority of the bioassay was most prominent in euthyroid (ET) TAO. Positivity rates of the TSAb bioassay, bridge and ECLIA binding assays were 89.6%, 75%, and 64.6%, respectively for inactive TAO; 86.1%, 69.4%, and 52.8%, respectively for mild TAO; 87.5%, 62.5%, and 12.5%, respectively for euthyroid TAO. The bridge assay correlated better with the ECLIA binding assay (ρ=0.893, p<0.001), compared to the bioassay (ρ=0.669, p<0.001). Conclusions: In patients with TAO of various activity and severity, the TSAb bioassay demonstrates a superior clinical performance compared to both ECLIA and bridge binding assays.

Pemantau Gas Metana, Suhu, dan Kelembaban sebagai Penyebab Efek Rumah Kaca Dipadang Lamun Berbasis Internet Of Things

Seagrass is a plant that covers coastal areas/shallow seas that can produce methane gas (CH4) during the decomposition process. The occurrence of decay caused by microbes in seagrass plants that have died in the process produces methane gas (CH4) as the cause of the greenhouse effect. Methane gas monitoring system (CH4) is proposed using MQ-4 sensor, temperature and humidity sensor (DHT11) using NodeMCU ESP8266 module, SD Card module as backup data storage and processed with local database and through mysql database the data will be displayed on the website page for information. . From the tests carried out, the response time for DHT11 is 5.6 seconds and MQ-4 is 1.5 seconds. It has a reading sensitivity rate of 99.92% for DHT11, 99.997% for MQ-4. The accuracy rate for DHT11 is a multiple of 1. For the MQ-4 sensor it has an accuracy level of 2 digits behind the comma. The tool has a data transfer rate of up to that which appears on the front-end 0.2736. With this tool, checking measurement results can be done quickly and can be done from anywhere.

COVID-19 Diagnosis Using Capsule Network and Fuzzy C -Means and Mayfly Optimization Algorithm

The COVID-19 epidemic is spreading day by day. Early diagnosis of this disease is essential to provide effective preventive and therapeutic measures. This process can be used by a computer-aided methodology to improve accuracy. In this study, a new and optimal method has been utilized for the diagnosis of COVID-19. Here, a method based on fuzzy C -ordered means (FCOM) along with an improved version of the enhanced capsule network (ECN) has been proposed for this purpose. The proposed ECN method is improved based on mayfly optimization (MFO) algorithm. The suggested technique is then implemented on the chest X-ray COVID-19 images from publicly available datasets. Simulation results are assessed by considering a comparison with some state-of-the-art methods, including FOMPA, MID, and 4S-DT. The results show that the proposed method with 97.08% accuracy and 97.29% precision provides the highest accuracy and reliability compared with the other studied methods. Moreover, the results show that the proposed method with a 97.1% sensitivity rate has the highest ratio. And finally, the proposed method with a 97.47% F 1 -score rate gives the uppermost value compared to the others.

Credit-worthiness Prediction in Energy-Saving Finance Using Machine Learning Model

Companies can form their own "ESCO model" with their capitals. Unfortunately, customer's creditworthiness was becoming more crucial for ESCO. Machine learning was used to predict the creditworthiness of clients in ESCO financing processes. This research aimed to develop a scoring model to leverage a machine learning and life cycle cost analysis (LCCA) to evaluate alternative financing for Energy Saving in Indonesia. The results of calculations using multinomial logistic regression showed that the accuracy value of prediction data with test data was 88.3562 %. The prediction rate result that refers to the percentage of correct predictions among all test data was 91.67%, and False Positive Rate (FPR) was 39.44%. The True Positive Rate was called Recall or 'Sensitivity Rate' as it was defined as several positive cases that were correctly identified (TPR) was 92.20%. We found the machine learning methods for creditworthiness prediction in retrofitting projects were fresh and worth a shot. It was hoped that this new practice would grow in popularity and become standard among ESCOs. Unfortunately, current machine-learning-based creditworthiness scoring practices lacked explain ability and interpretability. Unfortunately, ESCO must penalize the retrofitting project. As a result, since retrofitting was a new industry, the credit approval process was challenging to communicate to consumers. The most important thing for ESCO to deal with the project was to have a friendship and know-how with the client. Research from these case studies led to a clearer understanding of the factors affecting all parties' decisions to implement and continue with their ESCO project.

Molecular Epidemiology and Characteristics of CTX-M-55 Extended-Spectrum β-Lactamase-Producing Escherichia coli From Guangzhou, China

In recent years, the CTX-M-55 extended-spectrum β-lactamase (ESBL)-positive rate has gradually increased in the clinic. To identify the molecular epidemiology and characteristics of blaCTX–M–55-positive isolates, a total of 374 non-repetitive ESBL-producing Escherichia coli strains were collected from patients in two hospitals in Guangzhou, and 89 blaCTX–M–55-positive isolates were selected by CTX-M-1-group PCR amplification and confirmed by DNA sequencing. Whole-genome sequencing was used to analyze the resistance phenotype, plasmid types, phylogenetic relationships and genetic environment of the blaCTX–M–55 gene. Conjugation experiments and PCR were performed to confirm whether the plasmid harboring blaCTX–M–55 gene could be transferred. The results showed that all blaCTX–M–55-positive isolates were resistant to ceftriaxone, and 88.76 and 76.40% were resistant to ceftazidime and cefepime, respectively. The resistance rates to levofloxacin and sulfamethoxazole were 66.29 and 59.55%, respectively. However, the sensitivity rate of piperacillin/tazobactam, amoxicillin/clavulanate, and amikacin exceeded 90%. All blaCTX–M–55-positive isolates were sensitive to carbapenems. Thirty-two STs were detected in the blaCTX–M–55-positive isolates, among which the detection rate of ST1193 was relatively high (19.10%, 17/89), and other ST types were scattered. It remains to be seen whether ST1193 carrying the blaCTX–M–55 gene can become a popular clone strain in this region in the future. The plasmid types carrying the blaCTX–M–55 gene included IncI1, IncFII, IncFIC, IncFIB, IncHI2, IncI2, and IncX/Y, among which the IncI1 and IncFII plasmids were the main plasmids, accounting for 37.80 and 28.09%, respectively. Among them, 11 strains of the IncI1 plasmid existed in ST1193 strains. The blaCTX–M–55 gene was found on chromosomes of 13 isolates, and seemed to be increasing annually. Up to five distinct types of genetic environments surrounding the blaCTX–M–55 gene were analyzed. The most common structure was type II “ISEcp1-blaCTX–M–55-ORF477.” In conclusion, whether ST1193, which carries blaCTX–M–55 gene, will be an epidemic clone of this region in the future remains to be concerned. The plasmids IncI1 and IncFII, and mobile elements such as ISEcp1 and IS26 may be the main factors leading to the spread and prevalence of CTX-M-55 genotypes.

Training Effects and Intelligent Evaluated Pattern of the Holistic Music Educational Approach for Children with Developmental Delay

This study focuses on the holistic music educational approach for young children developed by music therapists and experts, which combines technology with music, integrates it into the local culture, and frameworks it for holistic education. This method includes 231 children in Taiwan’s early intervention education system for children with developmental delay. The learning occurs twice a week for 40 min over 32 weeks. The results show that implementing the holistic music educational approach can significantly improve children’s ability with developmental delay and that supportive training has a positive effect. In addition, the decision tree explores and develops an intelligently evaluated pattern with highly effective learning. This model has a sensitivity rate of 90.6% on the in-sample, and the comprehensive indicator F is 79.9%, so it has a high reference value. In the future, those involved in education will be able to use the data mining to use the auxiliary decision-making system as an assessment tool for young children participating in education pre- and midterm of the course, to prejudge its continued implementation and learning effectiveness, to decide whether to continue to invest in and adjust the curriculum, and to make more effective use of educational resources.

STATISTICAL INVESTIGATION OF I-SHAPED STIFFENED RECTANGULAR PLATE BY TAGUCHI RESPONSE EVALUATION

In this research, the buckling of stiffened rectangular plate with square opening is studied using techniques of FEA. The stiffener used for analysis is I shaped placed on edges and in vertical configuration. Critical buckling loads are determined from load multiplier values obtained from FEA simulation. The features of stiffener are further optimized with Taguchi response technique to acquire essential responses of variables with respect to yield variables. The sensitivities of various optimization parameters are also determined. The results indicated that substantial enhancement in buckling resistance can be achieved through optimized dimensions of stiffeners. For safety-factor least both lower width and upper width shows positive sensitivities with lower width sensitivity rate is 54.041 (positive) and upper width rate is additionally 54.041 (positive). Hence, both upper width measurements and lower width has same impact on factor noticed for SPSW.