シンリンケイリュウニオケルイワナヘノホウシャセイセシウムイコウノヒョウカ

博士（農学)東京農工大

Phytochemical Studies of Some Bangladeshi Plants

Chapter 1 consists of a general description of the plant families Annonaceae, Piperaceae, Meliaceae, Rubiaceae and Euphorbiaceae, in particular in terms of their main secondary metabolites and their biological activity. Chapter 2 presents a brief account of the biosynthetic pathways leading to the alkaloids, flavonoids and triterpenoids described in later chapters. Chapter 3 describes the isolation of three novel methylated flavonoids from the bark of Desmos longiflorus (Annonaceae). The structures were determined largely by use of HMQC, HMBC and NOE difference techniques. Two other new compounds, a lanostane and a protoberberine alkaloid, were also obtained from the extract together with several known aporphine alkaloids, steroids, benzyl benzoate and the cyclohexane derivative, crotepoxide. Chapter 4 concerns the structural elucidation, by 2D NMR methods, of a new 2-oxo-11beta,16-epoxy-16-epicafestol derivative from Cojfea bengalensis (Rubiaceae). Chapter 5 discusses the isolation of several isoquinoline alkaloids and the known sesquiterpenoid spathulenol from the Annonnaceous species Artabotrys odoratissimus. Chapter 6 describes the isolation and characterisation of two new and one known bisdehydroaporphine alkaloids from the bark extract and a known aporphine alkaloid from the leaf extract of Polyalthia bullata (Abetannonaceae) which is valued in Malaysia as an aphrodisiac (tonquat ali). Chapter 7 gives an account of the isolation of the cyclohexene derivative zeylenol and two new pseudosugars from another Annonaceae, Annona roxburghiana. In Chapter 8 the isolation of the known compounds, lupeol, lupeone, scopoletin and betulin 3 caffeate from Antidesma ghaesembilla (Euphorbiaceae) is discussed. In Chapter 9 the isolation of one new and six known dammarane triterpenoids and the sesquiterpenoid viridiflorol from Amoora cucullata (Meliaceae) is discussed. The final Chapter 10 gives an account of an investigation of Piper chaba (Piperaceae) which produced piperanine, 2,4-decadienoic acid piperidide, pellitorine and the lignan (-)-kusunokinin

DEMOGRAPHIC AND SOCIO-ECONOMIC DETERMINANTS OF WOMEN EMPLOYMENT IN BANGLADESH

The purpose of the present study is to examine the major factors related to the participation of women in the economic activities of Bangladesh, using the data of the nationally representative provided by the Bangladesh Demographic and Health Survey (BDHS) 2017/18. The survey interviewed a total of 20127 women aged 15-49 on social, economic, and demographic factors. The study used women's occupations as the dependent variable to understand the patterns and dynamics of women's participation in economic activities in Bangladesh. The result shows that 49.6% of women didn’t associate with any work, 7.9% of women worked as a professional, technical or managerial specialist, and 42.5% of women worked as non-professional, such as: in agriculture, and domestic-related work. Two policy implications emerged from the study: 1) The economic activity of women in Bangladesh is still low, most of them earn their livelihood utilizing non-professional works; 2) Women who are relatively from poorer families, not very well educated, located in the rural area are largely seen in economic activities in Bangladesh. Finally, the study indicates an idea about important determinants of women's employment, as poor women with little formal education remain economically active. The study recommends that women must be provided with new skills and knowledge to expand their ability and the education of women must be given the highest priority, which is the fundamental problem.The purpose of the present study is to examine the major factors related to the participation of women in the economic activities of Bangladesh, using the data of the nationally representative provided by the Bangladesh Demographic and Health Survey (BDHS) 2017/18. The survey interviewed a total of 20127 women aged 15-49 on social, economic, and demographic factors. The study used women's occupations as the dependent variable to understand the patterns and dynamics of women's participation in economic activities in Bangladesh. The result shows that 49.6% of women didn’t associate with any work, 7.9% of women worked as a professional, technical or managerial specialist, and 42.5% of women worked as non-professional, such as: in agriculture, and domestic-related work. Two policy implications emerged from the study: 1) The economic activity of women in Bangladesh is still low, most of them earn their livelihood utilizing non-professional works; 2) Women who are relatively from poorer families, not very well educated, located in the rural area are largely seen in economic activities in Bangladesh. Finally, the study indicates an idea about important determinants of women's employment, as poor women with little formal education remain economically active. The study recommends that women must be provided with new skills and knowledge to expand their ability and the education of women must be given the highest priority, which is the fundamental problem

Constrained coordinated distributed control of smart grid with asynchronous information exchange

Smart grid constrained optimal control is a complex issue due to the constant growth of grid complexity and the large volume of data available as input to smart device control. In this context, traditional centralized control paradigms may suffer in terms of the timeliness of optimization results due to the volume of data to be processed and the delayed asynchronous nature of the data transmission. To address these limits of centralized control, this paper presents a coordinated, distributed algorithm based on distributed, local controllers and a central coordinator for exchanging summarized global state information. The proposed model for exchanging global state information is resistant to fluctuations caused by the inherent interdependence between local controllers, and is robust to delays in information exchange. In addition, the algorithm features iterative refinement of local state estimations that is able to improve local controller ability to operate within network constraints. Application of the proposed coordinated, distributed algorithm through simulation shows its effectiveness in optimizing a global goal within a complex distribution system operating under constraints, while ensuring network operation stability under varying levels of information exchange delay, and with a range of network sizes

Training and Development Practice of Banks from an International Perspective with Special Emphasis on Bangladesh: Findings from the Literatures

The review is a collection of findings of journal articles. This descriptive work is based on training and development in banking industry. The banks are growing concerns and technologies, systems, processes, and procedures are changing here and consequently the employees need to know how and adapt to a new environment or situation for why they are supposed to go through the training and development processes. The review is aimed at extracting the findings from various journal articles from international perspective with special focus on Bangladeshi literatures. The findings have encrypted by naming and describing the findings in the journal articles under review. Lastly, the summarized discussion highlighted the possible suggestions to the banks emphasizing the importance of training and development in the industry. Keywords: Training and Development, Commercial Banks, Banglades

Classification of Human Monkeypox Disease Using Deep Learning Models and Attention Mechanisms

As the world is still trying to rebuild from the destruction caused by the widespread reach of the COVID-19 virus, and the recent alarming surge of human monkeypox disease outbreaks in numerous countries threatens to become a new global pandemic too. Human monkeypox disease syndromes are quite similar to chickenpox, and measles classic symptoms, with very intricate differences such as skin blisters, which come in diverse forms. Various deep-learning methods have shown promising performances in the image-based diagnosis of COVID-19, tumor cell, and skin disease classification tasks. In this paper, we try to integrate deep transfer-learning-based methods, along with a convolutional block attention module (CBAM), to focus on the relevant portion of the feature maps to conduct an image-based classification of human monkeypox disease. We implement five deep-learning models, VGG19, Xception, DenseNet121, EfficientNetB3, and MobileNetV2, along with integrated channel and spatial attention mechanisms, and perform a comparative analysis among them. An architecture consisting of Xception-CBAM-Dense layers performed better than the other models at classifying human monkeypox and other diseases with a validation accuracy of 83.89%.Comment: This paper is currently under review at ICCIT 202