EFFECTIVE MICROORGANISMS (EM) DISPERSION SYSTEM FOR DILUTING POLLUTANT IN RIVER

Nowadays, effective microorganism technology is widely used in treating and improving water quality for its environmentally friendly properties. The quality of river water can be considered as one of the most important concern for official authorities worldwide. In Malaysia, the local government is tending to enhance the water quality of rivers in the county by utilizing effective microorganism technology. Determining the suitable amount of the EM to improve water quality is one of the barriers that need to overcome. This report discusses one of the proposed methods for solving the issue of distributing random amount of effective microorganism (EM) in river. Utilizing an automated control system is the focal objective of this writing to dilute pollutant in river. By using such technology, effective microorganism will be poured into the river in mud-ball form based on the need of it. In this paper, developing a prototype consists of well-designed control system to test and study the impact of EM dispensation in a tank of water will be explained in details

Real options modeling and valuation of price adjustment flexibility with an application to the leasing industry

Uncertainty poses not only threats but also opportunities. This study sought to build the scientific foundation for introducing a real options (ROs) methodology for price risk management to the leasing industry. A price risk management that allows for both coping with threats and taking advantage of opportunities. In the leasing industry, fixed rate long-term lease contracts help contract parties stabilize cash flows within volatile markets. The contract\u27s term, however, may be extended long enough that prevent capturing the opportunities of gaining greater profits or reducing expenses. Therefore, the flexibility that enables participants to take advantage of favorable market price is desirable. This discussion is dedicated to the study of three different forms of price adjustments flexibility: 1) single-sided price adjustment flexibility (SSPAF). 2) double-sided price adjustment flexibility (DSPAF) with the preemptive right to exercise. 3) DSPAF with the non-preemptive right to exercise. Each was designed to meet various participants flexibility requirements and budgets. An ROs methodology was developed to model, price, and optimize these flexibility clauses. The proposed approach was then tested in the example of Time Charter (TC) rate contracts from the maritime transport industry. Both the metric and the process for quantifying the benefit of the proposed flexibility clauses are provided. This work provides an alternative approach to the price risk management, which is accessible to all participants in the leasing industry. It is also the starting point in studying the multiple-party, multiple-exercisable price adjustment flexibility. Moreover, both the flexibility designs and the proposed ROs methodology for price risk management are applicable to not only other forms of lease contracts but also to other forms of contract relationships. --Abstract, page iii

EFFECTIVE MICROORGANISMS (EM) DISPERSION SYSTEM FOR DILUTING POLLUTANT IN RIVER

Nowadays, effective microorganism technology is widely used in treating and improving water quality for its environmentally friendly properties. The quality of river water can be considered as one of the most important concern for official authorities worldwide. In Malaysia, the local government is tending to enhance the water quality of rivers in the county by utilizing effective microorganism technology. Determining the suitable amount of the EM to improve water quality is one of the barriers that need to overcome. This report discusses one of the proposed methods for solving the issue of distributing random amount of effective microorganism (EM) in river. Utilizing an automated control system is the focal objective of this writing to dilute pollutant in river. By using such technology, effective microorganism will be poured into the river in mud-ball form based on the need of it. In this paper, developing a prototype consists of well-designed control system to test and study the impact of EM dispensation in a tank of water will be explained in details

The Burden of Surgical Cancellations and No-Shows : Quality management study from a large regional hospital in Oman

Objectives: The operating theatre (OT) is a vital facility that utilises a considerable portion of the hospital’s budget; thus proper OT utilisation is essential. Surgical cancellation is a leading cause of OT underutilisation. This study aimed to report the rate and reasons for surgical cancellations and no-shows in a large regional hospital in Oman. Methods: This study took place as part of a retrospective quality management project at the Ibri Regional Hospital, Ibri, Oman. All elective surgical procedures scheduled between January and December 2014 were included. Cancelled procedures were reviewed to determine the reasons for cancellation. Results: A total of 4,814 elective procedures were scheduled during the study period; of these, 1,235 (26%) were cancelled. Patient no-shows were the most prevalent reason for surgical cancellation (63%), followed by surgical reasons (17%); in contrast, OT-associated reasons were responsible for only 2% of cancellations. According to speciality, general surgery had the highest percentage of total cancellations (65%), while ear, nose and throat had the highest rate of surgical cancellations among their scheduled cases (42%). Conclusion: Ibri Regional Hospital had a higher surgical cancellation rate due to no-shows than those reported in the literature. Regular audits, quality management projects and the appointment of a dedicated procedure booking coordinator may enhance proper utilisation of the OT, potentially saving funds, conserving resources and alleviating the burden of cancellations

Jednonukleotidni polimorfizmi gena za β-laktoglobulin, k-kazein i DGAT1 kao kandidati za stroge selekcijske kriterije holštajnskih krava s obzirom na sastav i proizvodnost mlijeka

The aim of this study was to investigate β-Lactoglobulin, k-casein and DGAT1 gene polymorphism and to associate this polymorphism with milk composition and performance traits in Holstein cattle using the PCR-DNA sequencing approach. On the basis of farm records, accurate phenotypic data for milk composition and performance traits were obtained for seventy Holstein dairy cows. Blood samples were collected from each animal into tubes containing disodium EDTA as an anticoagulant for DNA extraction. PCR was carried out for amplification of fragments of exon 4 (301-bp) of β-Lactoglobulin, exon 4 (373-bp) of k-casein, and exon 7 (321-bp) of DGAT1 genes. DNA sequencing assessment elaborated single nucleotide polymorphisms (SNPs) in the investigated genes amongst the enrolled dairy cows. On the basis of the dairy cows that harbored identified SNPs in each gene, the animals were allocated into different groups. The least square means of the groups revealed a significant association (P ≤ 0.05) between SNPs and milk production and performance traits. Logistic regression model confirmed a highly significant effect of the identified SNPs on the studied traits, where a moderate to strong relationship was detected between the predictor (SNPs) and the grouping variable (Milk composition and performance traits). Consequently, the identified SNPs in β-Lactoglobulin, k-casein and DGAT1 genes could be used as candidates for developing marker assisted selection (MAS) for milk composition and performance traits in Holstein dairy cattle.Cilj rada bio je, primjenom PCR-DNA metode i analize sljedova, istražiti polimorfizme gena za β-Lactoglobulin, k-kazein i DGAT1 te procijeniti njihovu povezati sa sastavom mlijeka i svojstvima proizvodnosti goveda holštajnske pasmine. Na temelju evidencija s farmi dobiveni su točni fenotipski podaci o sastavu mlijeka i proizvodnosti 70 muznih krava. Za ekstrakciju DNK prikupljeni su uzorci krvi pojedinačnih krava u epruvete koje su sadržavale dinatrijev EDTA kao antikoagulans. PCR je proveden za amplifikaciju fragmenata egzona 4 (301-bp) β-laktoglobulina, egzona 4 (373-bp) k-kazeina i egzona 7 (321-bp) gena DGAT1. Analiza sljedova DNK prikazala je jednonukleotidne polimorfizme (SNPs) u istraženim genima. Uzevši u obzir krave kod kojih su utvrđeni SNP-ove u svakom genu, životinje su raspoređene u različite skupine. Srednje vrijednosti (LSM) skupina pokazale su znakovitu povezanost (P<0,05) između SNP-ova i svojstava proizvodnosti mlijeka. Model logističke regresije potvrdio je visoko znakovit učinak identificiranih SNP-ova na istraživana svojstva, pri čemu je ustanovljena umjerena do jaka povezanost između prediktora (SNP-ovi) i varijabli grupiranja (sastav mlijeka i proizvodnost mlijeka). Posljedično, identificirani SNP-ovi u genima β-Lactoglobulina, k-kazeina i DGAT1 mogli bi se koristiti kao kandidatni pri razvoju postupaka selekcije uz pomoć markera (MAS) za sastav mlijeka i svojstva proizvodnosti u mliječnih goveda pasmine holštajn

Predicting Heart Disease using Neural Networks

Cardiovascular diseases, including heart disease, pose a significant global health challenge, contributing to a substantial burden on healthcare systems and individuals. Early detection and accurate prediction of heart disease are crucial for timely intervention and improved patient outcomes. This research explores the potential of neural networks in predicting heart disease using a dataset collected from Kaggle, consisting of 1025 samples with 14 distinct features. The study's primary objective is to develop an effective neural network model for binary classification, identifying the presence or absence of heart disease. The neural network architecture includes an input layer, a hidden layer, and an output layer, designed to capture intricate relationships within the dataset. Rigorous training and validation processes, accompanied by data preprocessing steps, ensure the model's robustness and generalization capabilities. The results demonstrate promising performance, with an accuracy of 92% and an average error of 0.062. Moreover, an analysis of feature importance highlights key predictors, including "oldpeak," "thalach," "trestbps," "ca," "thal," "cp," "chol," "sex," "restecg," "age," "slope," "fbs," and "exang." This research contributes to the field of predictive healthcare by leveraging neural networks to enhance heart disease prediction. The developed model offers the potential for early identification of individuals at risk, facilitating timely medical interventions and ultimately improving public health. Further exploration of machine learning techniques in healthcare promises to reshape disease prediction and prevention strategies

An S-Band Microstrip Patch Antenna Design and Simulation for Wireless Communication Systems

In this paper, a 3.5 GHz microstrip patch antenna for the future of wireless communication is designed and studied. As a substrate, Rogers RT/Duroid5880 is utilized. This material has a thickness of 0.077mm and a dielectric loss of 2.2. The proposed antenna layout is simulated using the CST studio suite of software programs. This research aimed to achieve a lower return loss, higher gain, lower VSWR, directivity, and improved efficiency. The simulation revealed that the return loss, gain, VSWR, and directivity were correspondingly -13.772 dB, 7.55 dB, 1.5152, and 8.43dBi. The efficiency was 89.56%. This antenna has been developed and assessed for use in various wireless communication applications with a 3.5 GHz operating frequency, which is used as a reference antenna in communication satellites, weather radar, surface ship radar, wireless LAN-802.11b and 802.11g, multimedia applications in mobile TV and satellite radio, optical communications at 1460 to 1530 nm wavelength, and is utilized for other wireless fidelity applications