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"This book introduces mathematicians to real applications from physiology. Using mathematics to analyze physiological systems, the authors focus on models reflecting current research in cardiovascular and pulmonary physiology. In particular, they present models describing blood flow in the heart and the cardiovascular system, as well as the transport of oxygen and carbon dioxide through the respiratory system and a model for baroreceptor regulation. Applied Mathematical Models in Human Physiology is the only book available that analyzes up-to-date models of the physiological system at several levels of detail. Some are simple real-time models that can be directly used in larger systems, while others are more detailed reference models that show the underlying physiological mechanisms and provide parameters for and validation of simpler models. The book also covers two-dimensional modeling of the fluid dynamics in the heart and its ability to pump, and includes a discussion of modeling wave-propagation throughout the systemic arteries.The models presented can be used as case studies in courses on mathematical modeling or as an inspiration for the study and development of physiological models. The first two chapters of the book provide an excellent introduction to the physiologic concepts necessary for understanding the modeling assumptions and methodologies. The remaining chapters describe six different models of the cardiovascular and pulmonary system. Each model is introduced by a case study and can be studied individually."

"Keberadaan showroom di kawasan batik Trusmi kini menjadi wadah bagi sebagian besar pengrajin tradisional untuk mendistribusikan hasil produksi batiknya. Hal tersebut karena efektifitas dan fasilitas yang ditawarkan showroom kepada pengrajin. Uniknya, ada beberapa pengrajin tradisional yang lebih memilih melakukan produksi dan distribusi secara mandiri. Mereka memanfaatkan human capital dan social capital dalam menjalankan usaha batiknya. Pada tulisan ini saya akan memaparkan bentuk-bentuk human capital dan social capital sehingga keduanya menghasilkan pilihan rasional (rational choice). Tulisan ini juga berusaha memaparkan Usaha-usaha yang mereka lakukan dalam memutuskan suatu pilihan rasional dalam menjalankan usaha batiknya penting dilakukan di tengah proses distribusi yang baru dengan kemunculan showroom dan distribusi oleh pengrajin tradisional sendiri. Pendekatan etnografi saya gunakan untuk mengetahui bentuk-bentuk pengetahuan tiap individu, serta hubungan sosial yang membentuk kepercayaan, obligasi, dan ekspektasi yang ada dalam hubungan antar individu.

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The existence of the showrooms in the Trusmi batik now are become a distributor for most traditional craftsmen to complete their batik products. This is because the effectiveness and facilities offered by showrooms for craftsmen. Uniqueness things, there are several traditional craftsmen who prefer to do independent production and distribution. They use human capital and social capital in running their batik business. In this paper I will describe the forms of human capital and social capital so as to produce rational choices. This paper also tries to explain the efforts they made in making choices in their batik business are important to do in the midst of the new distribution process with the appearance of showrooms and distribution by traditional craftsmen themselves. I use ethnography perspective to understand the forms of knowledge of each individual, as well as social relationships that shape the beliefs, agreements, and expectations that exist in relationships between individuals."

"Mathematical Models in Biology is an introductory book for readers interested in biological applications of mathematics and modeling in biology. A favorite in the mathematical biology community, it shows how relatively simple mathematics can be applied to a variety of models to draw interesting conclusions. Connections are made between diverse biological examples linked by common mathematical themes. A variety of discrete and continuous ordinary and partial differential equation models are explored. Although great advances have taken place in many of the topics covered, the simple lessons contained in Mathematical Models in Biology are still important and informative.Shortly after the publication of Mathematical Models in Biology, the genomics revolution turned Mathematical Biology into a prominent area of interdisciplinary research. With this new millennium, biologists have discovered that mathematics is not only useful, but indispensable! As a result, there has been much resurgent interest in, and a huge expansion of, the fields collectively called mathematical biology. This book serves as a basic introduction to concepts in deterministic biological modeling."

"This textbook provides an introduction to the field of mathematical biology through the integration of classical applications in ecology with more recent applications to epidemiology, particularly in the context of spread of infectious diseases. "

"Triclustering merupakan salah satu teknik data mining yang bertujuan untuk mengelompokkan data berbentuk tiga dimensi secara simultan. Salah satu pendekatan yang digunakan dalam triclustering adalah pendekatan pattern-based, contohnya Timesvector. Metode timesvector dirancang khusus untuk pengelompokan data deret waktu tiga dimensi yang bertujuan menangkap pola ekspresi gen yang sama atau berbeda antara dua atau lebih kondisi eksperimen. Implementasi metode timesvector dilakukan pada data ekspresi gen human embryonic stem cell (H1-hESC) yang diberi protein morfogenetik tulang (BMP4) dan dikondisikan di dalam ruang dengan tingkat oksigen 4% dan 20, serta diamati pada 6 titik waktu berbeda selama 120 jam. Triclustering dilakukan dengan lima skenario menggunakan cluster sejumlah 257 dan threshold yang berbeda. Berdasarkan skenario tersebut, metode timesvector menghasilkan skenario terbaik pada skenario dengan threshold 1,5 yang menggunakan validasi berdasarkan nilai coverage. Berdasarkan hasil skenario terbaik, dihasilkan 9 pola DEP, 24 pola ODEP, dan 37 pola SEP dan dari pola tersebut dilakukan analisis Gene Ontology (GO) untuk mengukur kualitas tricluster dalam penggambaran konsep GO. Analisis GO menggunakan Database for Annotation, Visualization, and Integrated Discovery (DAVID) tools untuk menghitung nilai p-value. Pada analisis GO dipilih p-value terkecil pada pola DEP, ODEP, dan SEP sebagai tricluster terbaik, yaitu DEP pada tricluster ke 8, ODEP pada tricluster ke-1, dan SEP pada tricluster ke-26. Berdasarkan tricluster terbaik pada pola DEP dan ODEP dapat dikatakan bahwa kondisi oksigen tingkat fisiologis 4 % dan tingkat atmosfer 20 % memiliki perbedaan dalam mengidentifikasi gen kandidat pada H1-hESC yang mampu berdiferensiasi menjadi trofoblas, sedangkan SEP tidak memiliki perbedaan dalam mengidentifikasi gen kandidat pada H1-hESC dengan dua kondisi berbeda.

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Triclustering is one of the data mining techniques that aims to cluster three-dimensional data simultaneously. One of the approaches used in triclustering is a pattern-based approach, such as Timesvector. The timesvector method is specifically designed for clustering three-dimensional time series data that aims to capture gene expression patterns that are the same or different between two or more experimental conditions. The implementation of the timesvector method was performed on human embryonic stem cell (H1-hESC) gene expression data treated with bone morphogenetic protein (BMP4) and conditioned in a chamber with 4% and 20 oxygen levels and observed at 6 different time points for 120 hours. Triclustering was performed with five scenarios using 257 clusters and different thresholds. Based on these scenarios, the timesvector method produces the best scenario in the scenario with a threshold of 1.5 which uses validation based on the coverage value. Based on the results of the best scenario, 9 DEP patterns, 24 ODEP patterns, and 37 SEP patterns were generated from these patterns. Gene Ontology (GO) analysis was carried out to measure the quality of the tricluster in describing the GO concept. GO analysis uses Database for Annotation, Visualization, and Integrated Discovery (DAVID) tools to calculate the p-value. In the GO analysis, the smallest p value in the DEP, ODEP, and SEP patterns was selected as the best tricluster, namely DEP in the 8th tricluster, ODEP in the 1st tricluster, and SEP in the 26th tricluster. Based on the best tricluster in the DEP and ODEP patterns, it can be said that the oxygen conditions of 4% physiological level and 20% atmospheric level have differences in identifying candidate genes in H1-hESC that are able to differentiate into trophoblasts, while SEP has no difference in identifying candidate genes in H1-hESC with two different conditions."