Evolution of FCC - Past Present and Future and The Challenges of Operating a High Temperature CFB System

The fluid catalytic cracking (FCC) process is one of the most important circulating fluidized bed processes. Although the FCC process has been in commercial operation for over 60 years, the technology continues to evolve in order to meet new challenges, which include processing more difficult feedstock and meeting more stringent environmental regulations. This paper presents selected snap-shots of a few challenges (high temperature erosion, corrosion and emission control) that the FCC process faces today and the new challenges yet to come in the near future

A Study of the Relationship Between Transformational Leadership and Teacher Empowerment at Daruna Ratchaburi Witaed Suksa School in Ratchaburi Province, Thailand

The purpose of this study was to investigate the relationship between Transformational Leadership and Teacher Empowerment based on the perceptions of teachers at the school of Daruna Ratchaburi Witaed Suksa in Ratchaburi Province, Thailand. Based on two variables, there were three objectives: (1) To identify the level of teachers' perceptions on Transformational School Leadership, (2) To examine the level of teachers' perceptions on Teacher Empowerment, (3) To determine if there were any significant relationship between two of those variables. In this study, the quantitative methodology was used along with 106 participant teachers at the school of DRWS. In research findings, it showed the overall scores of Transformational School Leadership and Six Dimensions of Teacher Empowerment got high level in the perceptions of teachers. Then, the positive significant correlation had occurred between Transformational School Leadership and Teacher Empowerment. Considering those results, both of those variables were moving in the same direction. It, thus, could be said the more Transformational School Leadership performed in the school, the greater teachers felt empowerment in their work life. Thus, it was recommended that in order to apply on the concept of beginning from school principal to teacher empowering, through which the feeling of empowerment of the teachers, would flow to student empowerment (Short & Reinhard,1992), it required to conduct the relationship of Transformational School Leadership, Teacher Empowerment, and Student Achievement in both at the private and public educational sectors, in Thailand

UCSY-SC1: A Myanmar speech corpus for automatic speech recognition

This paper introduces a speech corpus which is developed for Myanmar Automatic Speech Recognition (ASR) research. Automatic Speech Recognition (ASR) research has been conducted by the researchers around the world to improve their language technologies. Speech corpora are important in developing the ASR and the creation of the corpora is necessary especially for low-resourced languages. Myanmar language can be regarded as a low-resourced language because of lack of pre-created resources for speech processing research. In this work, a speech corpus named UCSY-SC1 (University of Computer Studies Yangon - Speech Corpus1) is created for Myanmar ASR research. The corpus consists of two types of domain: news and daily conversations. The total size of the speech corpus is over 42 hrs. There are 25 hrs of web news and 17 hrs of conversational recorded data.The corpus was collected from 177 females and 84 males for the news data and 42 females and 4 males for conversational domain. This corpus was used as training data for developing Myanmar ASR. Three different types of acoustic models  such as Gaussian Mixture Model (GMM) - Hidden Markov Model (HMM), Deep Neural Network (DNN), and Convolutional Neural Network (CNN) models were built and compared their results. Experiments were conducted on different data  sizes and evaluation is done by two test sets: TestSet1, web news and TestSet2, recorded conversational data. It showed that the performance of Myanmar ASRs using this corpus gave satisfiable results on both test sets. The Myanmar ASR  using this corpus leading to word error rates of 15.61% on TestSet1 and 24.43% on TestSet2

Prevalence of Depression and its Associated Factors Among Adults during Third Wave of COVID-19 Pandemic in Malaysia, 2021

Malaysia recently entered third-wave of COVID-19 pandemic starting from October 2020 to end of January 2021. Therefore, objective of our study was to identify the prevalence of depression and its associated factors among adults during third wave of COVID-19 pandemic in Malaysia. A total of 1468 Malaysian adults participated in this cross-sectional web-based survey. A standardized questionnaire was generated using the Google Form, and the link was shared through social media such as Facebook, Twitter, Instagram and WhatsApp. Patient Health Questionnaires (PHQ-9) was used to assess the levels of depression. Among 1468 participants, 320 (22 %) and 358 (24.6 %) indicated to have moderate to severe depression during third-wave of COVID-19 in Malaysia. Multiple predictors were identified that contributed to depression. These included female gender, family’s source income affected by the pandemic, do not perform exercise, victim of abuse and those with family and/or friends infected with COVID-19 virus. COVID-19 pandemic had caused the implementation of lockdown and physical distancing in Malaysia and nations across the globe. The pandemic had brought serious negative impacts on mental health of the adults especially depression especially during third wave of pandemic. The findings of our study suggested that new interventions or strategies are needed to be developed to address the severity of depression among Malaysian adults

Assessment of Post-Traumatic Stress Disorders and its Associations with Suicidal Behaviour among Adults Following Movement Control Order During COVID-19 Pandemic in Malaysia

A rapid review of previous outbreaks shows that a quarantine policy had greater effects on one’s psychological state including post-traumatic stress disorder (PTSD), confusion and anger caused by various stressors. This study aimed to assess the levels of Post-Traumatic Stress Disorder (PTSD) and its associations with suicidal behavior among Malaysian adults following Movement Control Order (MCO) during the COVID-19 pandemic in Malaysia. This cross-sectional study was distributed using an online standardized questionnaire composed of three parts, the socio-demographic characteristics, PTSD assessment using PTSD Checklist for DSM-5 and the suicidal behavior assessment using Suicidal Behaviors Questionnaire-Revised (SBQ-R). Almost half of the respondents had high PTSD symptoms (41.7 %) and low PTSD was 58.3 % among Malaysian adults. Furthermore, 69.6 % of participants had no suicidal behavior but, 30.4 % from the participants has suicidal behavior. This study found single status with highest PTSD (83.3 %) and marital status had significant correlation with PTSD which p-value was < 0.05. Malay was high percentage in high PTSD (74.6 %) and significant correlation between race and PTSD (p < 0.05). Employment status also had significant correlation with PTSD with p-value was 0.002 and students was counted highest PTSD (65.7 %). This study identified some socio-demographic factors and suicidal behavior associated with PTSD among Malaysian adults, which may lay ground for further interventions

Factors associated with psychological distress among Myanmar residents during COVID-19 pandemic crises

Background: COVID-19 pandemic reached a public health emergency status of international concern. The impacts and events associated with this were associated with adverse psychological impacts among the general public globally. This study aimed to determine the prevalence of psychological distress and to identify predictors associated with psychological distress due to the COVID-19 pandemic among the population in Myanmar. Design and Methods: A cross-sectional survey was conducted from March to April 2020 among adults, 18 years old and above, who reside in Myanmar through a structured questionnaire distributed in social media platforms. Univariate and Bivariate analyses were used to estimate the prevalence of COVID-19 Peritraumatic Distress Index (CPDI) symptoms and to test the associations between CPDI and the exposure variables. Logistic Regression Analysis was done to identify significant predictors of distress. Results: There were 530 participants in this study.37.4% of them did not have psychological distress,55.6% experienced mild to moderate psychological distress, and 7% experienced severe psychological distress due to COVID-19 pandemic. Simple and Multiple Logistic Regression Analyses were performed to determine the factors associated with psychological distress due to COVID-19. Conclusions: It was shown that the self-employed group and age group older than 45 years old had more psychological distress than others. However, Buddhists and people from the capital city had less distress than other religions and districts. This study recommends the government to develop better strategies for self-employed groups, elders, and the poor for a support, relief, and resettlement of their ruined status

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Water Quality Assessment of Two Popular Lakes in Yangon, Myanmar

This study aimed to characterize and access the existing water quality of the two popular lakes (Kandawgyi Lake and Innya Lake) in Yangon, Myanmar. The water samples were collected from different locations of the lakes and inlet points of the lakes. The collected samples were analyzed for different physical and chemical parameters such as oxygen demand, nutrient concentrations, solids, and alkalinity. In order to access the state of the lake’s water quality, the samples were compared with standard water quality values. Most of the water quality parameters of the inlet points were found to be above the standard water quality values in both lakes. Biochemical oxygen demand and chemical oxygen demand are also much greater than the limit of the compared standard (especially in inlet drain waters). It was found that continuous polluted water drains from catchment area to main inlets of both lakes. Algae blooming can be seen visually in Kandawgyi Lake , in which water quality is more deteriorated than Innya Lake. This paper will serve as a baseline data which could be used for water quality monitoring and evaluation of the lake

Building HMM-SGMM Continuous Automatic Speech Recognition on Myanmar Web News

Myanmar language is a tonal and analyticlanguage. It can be considered as an under-resourcedlanguage because of its linguistic resource availability.Therefore, speech data collection is a very challengingtask in building Myanmar automatic speechrecognition. Today a lot of speech data are freelyavailable on the Internet and we can collect it easily.Therefore, in this system, we take the advantages ofInternet and we use daily news from the Web inbuilding our speech corpus. In this paper, we willpresent about the task of data collection, the effect ofAutomatic Speech Recognition (ASR) performanceaccording to amount of training data, language modelsize and error analysis of the experimental result. Theexperiments will be developed using Hidden MarkovModel (HMM) with Gaussian Mixture Model (GMM)and Subspace Gaussian Mixture Model (SGMM). As aresult, using our developed 5 hours training data, thissystem achieves word error rate (WER) of 7.6% onclose test data and 31.9% on open test data withHMM-SGMM