การผลิตไฟฟ้าด้วยระบบผสมผสานเธอร์โมอิเล็กทริกร่วมกับระบบระบายความร้อนแบบปิดด้วยน้ำมันพืชเหลือทิ้งในอุตสาหกรรมครัวเรือน

การผลิตไฟฟ้าด้วยระบบผสมผสานเธอร์โมอิเล็กทริกร่วมกับระบบระบายความร้อนแบบปิดด้วยน้ำมันพืชเหลือทิ้งในอุตสาหกรรมครัวเรือน ปวัฒวงศ์  บำรุงขันท์1, ภุชงค์  จันทร์จิระ1, ปิติพร รุจนเวชช์2 1คณะศึกษาศาสตร์ มหาวิทยาลัยศรีนครินทรวิโรฒ 114 สุขุมวิทย 23 เขตวัฒนา กรุงเทพ 10110 2คณะครุศาสตร์อุตสาหกรรมและเทคโนโลยี มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าธนบุรี 126 ถนนประชาอุทิศ แขวงบางมด เขตทุ่งครุ กรุงเทพมหานคร 10140 บทคัดย่อ งานวิจัยนี้เป็นการผลิตไฟฟ้าจากหน่วยประมวลผลกลางของคอมพิวเตอร์ส่วนบุคคล (Personal computer) โดยการออกแบบระบบผสมผสานเธอร์โมอิเล็กทริกเข้ากับระบบระบายความร้อนด้วยของเหลว เพื่อให้ได้มาซึ่งพลังงานไฟฟ้าจากเธอร์โมอิเล็กทริกที่ถ่ายเทความร้อนให้กับเธอร์โมอิเล็กทริก จำนวน 1 โมดูล ทดสอบผ่านโปรแกรมสำเร็จรูป Furmark CPU burner ที่การควบคุมอุณหภูมิห้องอยู่ที่ 25 องศาเซลเซียส ในการทดลองการถ่ายเทความร้อนที่ได้จากการทำงานของหน่วยประมวลผลกลางจะถ่ายเทมายังเธอร์โมอิเล็กทริกด้านร้อน ส่วนด้านเย็นของเธอร์โมอิเล็กทริกจะถูกระบายความร้อนด้วยเครื่องแลกเปลี่ยนความร้อนร่วมกับระบบระบายความร้อนด้วยของเหลว ด้วยการศึกษาระบบระบายความร้อน จากน้ำกลั่น น้ำยาหล่อเย็น และน้ำมันพืชเหลือทิ้ง จากการทดลองทำการควบคุมอุณหภูมิด้านร้อนเฉลี่ย 100 องศาเซลเซียส พบว่า ระบบผสมผสานการระบายความร้อนด้วยน้ำมันพืชเหลือทิ้งร่วมกับเธอร์โมอิเล็กทริกให้กำลังไฟฟ้า 2.02 วัตต์ ประสิทธิภาพ 2.04% ที่ผลต่างอุณหภูมิเฉลี่ย 61 องศาเซลเซียส ชี้ให้เห็นว่าที่การควบคุมอุณหภูมิด้านร้อนคงที่ ระบบระบายความร้อนด้วยน้ำมันพืชเหลือทิ้งสามารถเป็นทางเลือกสำหรับการผลิตไฟฟ้าได้ และเมื่อวิเคราะห์ระยะเวลาคืนทุน ของระบบผลิตกระแสไฟฟ้าจากหน่วยประมวลผลกลางของการผสมผสานเธอร์โมอิเล็กทริกร่วมกับระบบระบายความร้อนด้วยน้ำมันพืชเหลือทิ้ง จะให้ระยะเวลาคืนทุน 1.11 ปี คำสำคัญ : เธอร์โมอิเล็กทริก, ประสิทธิภาพ, ผลต่างอุณหภูมิ, หน่วยประมวลผลกลาง, น้ำมันพืชเหลือทิ้ง  Generating electricity of thermoelectric hybrid cooling system with waste cooking oil in cottage industry   Pawatwong Bamroongkhan1, Puchong Chanjira1, Pitiporn Ruchanawet2 1Faculty of Education, Srinakharinwirot Univetsity 114 Sukhumvit 23 Wattana Bangkok 10110 2Faculty of Industrial Education and Technology, King Mongkut’s University of Technology Thonburi, 126 Pracha-Uthit Road, Bangmod, Thungkru, Bangkok, 10140 Abstract This research were to produce electricity from the through of the personal computer by used thermally integrated system with a liquid cooling system. In order to obtain the electrical energy from the thermoelectric 1 module heat transfer through Furmark CPU burner software at room temperature control at 25 ° C in the heat transfer experiment from the processor. The heat was transferred to the thermoelectric. Thermoelectric cooling was cooled by a heat exchanger in combination with a liquid cooling system. Study distilled water, coolant water and waste vegetable oil. With an average temperature of 100 ° C, the average heat and waste vegetable oil system combined with thermoelectric generate 2.02W of power, 2.04% efficiency at an average temperature difference of 61 ° C pointing out that constant temperature control. The waste vegetable oil extraction system can be an alternative for electricity generation. When the payback period, the system of power generation from the central processing unit of the thermoelectric mixture together with the waste vegetable oil cooling system. The payback period is 1.11 years. Keywords: Thermoelectric, Efficiency, Temperature difference, Processor, Waste Vegetable Oi

Advances at the interface: merging information technologies with genomic methodologies

Deoxyribonucleic acid (DNA) is a molecule whose importance towers like a colossus in the sweeping field of biomedicine. The chemical structure of double stranded DNA is itself a helical tower that forms not only the backbone of medical research, but of life itself. Yet, we cannot let DNA be constrained to this role of solid, rigid building block if we wish to utilize its full potential. In its single stranded form, DNA can take on unexpected tertiary shapes that allow it to interact with polymerases, proteins, and organic molecules. This ability gives nucleic acids immense potential for molecular recognition. From monitoring a state of health to identifying toxins in drug development, using DNA as a sensing element can bring valuable information. Clinical diagnostics have benefited enormously from the sensitivity, specificity, and rapidity of nucleic acid testing (NAT). It can be easy to take blood donor screening, heritable genotyping of newborns, and other standard operating procedures for granted in the developed world. Developing nations with as few as one physician for every 100 people are lacking in the healthcare infrastructure (to say the least) to provide these molecular tests. The key to unlocking the progressions made by NAT in identifying causative agents of disease comes in the form of a ubiquitous tool: mobile phones. Almost 7B people in the world own cell phones. By combining the optical imaging capabilities and computational powers of mobile phones with a streamlined amplification platform, the ability to detect diseases becomes available to those who could truly reap its benefits.The synergistic nature of merged technologies is something that extends beyond nucleic acid amplification tests (NAATs) to analysis of recombinant DNA products. Most fields have single-use products that are essential for one purpose but otherwise hidden from view. When brought to the attention of other disciplines, nucleic acid analysis tools such as next generation sequencing (NGS) can segue from providing information on full genomes to identifying highly represented DNA affinity agents from candidate pools. Bringing the systems of particle display, high throughput sequencing (HTS), and in situ microarray synthesis to a sequence selection process enhances screening capabilities to the extent that hundreds of sequences can be identified en masse as binding to thousands of targets

Structural Elucidation of Membrane Proteins Involved in Photosynthesis

abstract: Over the last century, X-ray crystallography has been established as the most successful technique for unravelling the structure-function relationship in molecules. For integral membrane proteins, growing well-ordered large crystals is a challenge and hence, there is room for improving current methods of macromolecular crystallography and for exploring complimentary techniques. Since protein function is deeply associated with its structural dynamics, static position of atoms in a macromolecule are insufficient to unlock the mechanism. The availability of X-ray free electron lasers presents an opportunity to study micron-sized crystals that could be triggered (using light, small molecules or physical conditions) to capture macromolecules in action. This method of ‘Time-resolved serial crystallography’ answers key biological questions by capturing snapshots of conformational changes associated with multi-step reactions. This dissertation describes approaches for studying structures of large membrane protein complexes. Both macro and micro-seeding techniques have been implemented for improving crystal quality and obtaining high-resolution structures. Well-diffracting 15-20 micron crystals of active Photosystem II were used to perform time-resolved studies with fixed-target Roadrunner sample delivery system. By employing continuous diffraction obtained up to 2 A, significant progress can be made towards understanding the process of water oxidation. Structure of Photosystem I was solved to 2.3 A by X-ray crystallography and to medium resolution of 4.8 A using Cryogenic electron microscopy. Using complimentary techniques to study macromolecules provides an insight into differences among methods in structural biology. This helps in overcoming limitations of one specific technique and contributes in greater knowledge of the molecule under study.Dissertation/ThesisDoctoral Dissertation Biochemistry 201

Data integration strategies for informing computational design in synthetic biology

PhD ThesisThe potential design space for biological systems is complex, vast and multidimensional. Therefore, effective large-scale synthetic biology requires computational design and simulation. By constraining this design space, the time- and cost-efficient design of biological systems can be facilitated. One way in which a tractable design space can be achieved is to use the extensive and growing amount of biological data available to inform the design process. By using existing knowledge design efforts can be focused on biologically plausible areas of design space. However, biological data is large, incomplete, heterogeneous, and noisy. Data must be integrated in a systematic fashion in order to maximise its benefit. To date, data integration has not been widely applied to design in synthetic biology. The aim of this project is to apply data integration techniques to facilitate the efficient design of novel biological systems. The specific focus is on the development and application of integration techniques for the design of genetic regulatory networks in the model bacterium Bacillus subtilis. A dataset was constructed by integrating data from a range of sources in order to capture existing knowledge about B. subtilis 168. The dataset is represented as a computationally-accessible, semantically-rich network which includes information concerning biological entities and their relationships. Also included are sequence-based features mined from the B. subtilis genome, which are a useful source of parts for synthetic biology. In addition, information about the interactions of these parts has been captured, in order to facilitate the construction of circuits with desired behaviours. This dataset was also modelled in the form of an ontology, providing a formal specification of parts and their interactions. The ontology is a major step towards the unification of the data required for modelling with a range of part catalogues specifically designed for synthetic biology. The data from the ontology is available to existing reasoners for implicit knowledge extraction. The ontology was applied to the automated identification of promoters, operators and coding sequences. Information from the ontology was also used to generate dynamic models of parts. The work described here contributed to the development of a formalism called Standard Virtual Parts (SVPs), which aims to represent models of biological parts in a standardised manner. SVPs comprise a mapping between biological parts and modular computational models. A genetic circuit designed at a part-level abstraction can be investigated in detail by analysing a circuit model composed of SVPs. The ontology was used to construct SVPs in the form of standard Systems Biology Markup Language models. These models are publicly available from a computationally-accessible repository, and include metadata which facilitates the computational composition of SVPs in order to create models of larger biological systems. To test a genetic circuit in vitro or in vivo, the genetics elements necessary to encode the enitites in the in silico model, and their associated behaviour, must be derived. Ultimately, this process results in the specification for synthesisable DNA sequence. For large models, particularly those that are produced computationally, the transformation process is challenging. To automate this process, a model-to-sequence conversion algorithm was developed. The algorithm was implemented as a Java application called MoSeC. Using MoSeC, both CellML and SBML models built with SVPs can be converted into DNA sequences ready to synthesise. Selection of the host bacterial cell for a synthetic genetic circuit is very important. In order not to interfere with the existing cellular machinery, orthogonal parts from other species are used since these parts are less likely to have undesired interactions with the host. In order to find orthogonal transcription factors (OTFs), and their target binding sequences, a subset of the data from the integrated B. subtilis dataset was used. B. subtilis gene regulatory networks were used to re-construct regulatory networks in closely related Bacillus species. The system, called BacillusRegNet, stores both experimental data for B. subtilis and homology predictions in other species. BacillusRegNet was mined to extract OTFs and their binding sequences, in order to facilitate the engineering of novel regulatory networks in other Bacillus species. Although the techniques presented here were demonstrated using B. subtilis, they can be applied to any other organism. The approaches and tools developed as part of this project demonstrate the utility of this novel integrated approach to synthetic biology.EPSRC: NSF: The Newcastle University School of Computing Science