Microprocessor controlled novel 4-quadrant DC-DC converter

The thesis describes a novel 4-quadrant DC-DC converter, supplied by a 28V DC voltage source, with an output voltage which may be continuously varied between +180V and -180V DC. A prototype 1.2kW DC-DC converter was designed and built, with emphasis given to the optimization of both the converter size and efficiency. This was achieved by means of a computer-based simulation study, which determined the optimal switching frequency and the size of the inductors and capacitors while maintaining a high unit efficiency. Mos-Gated Bimos switches, which feature the advantages of both mosfets and bipolar transistors, were developed to achieve high switching speed during high power operation. A digital-controlled DC servo system based on a 16-bit Intel 8086 microprocessor was designed, to provide both motor speed and position control. Speed and position detection circuits and the structure and the interfacing arrangement of the microprocessor system were designed and constructed. Several control algorithms were developed, including PID Control Algorithm and Current-Limit Control Algorithm. Based on open loop transfer function of the system, derived through mathematical modelling using the State-Space Averaging Method, the constants for the control algorithms were obtained to meet the dynamic performance specified for the system. Computer simulation was carried out to assist with the design of the converter and the control system. It is expected that drives into which the novel converter is incorporated will find many applications in situations where accurate positional control is required, particularly in battery-operated DC-servo system, such as satellite system, robots and some military vehicles

EviPrompt: A Training-Free Evidential Prompt Generation Method for Segment Anything Model in Medical Images

Medical image segmentation has immense clinical applicability but remains a challenge despite advancements in deep learning. The Segment Anything Model (SAM) exhibits potential in this field, yet the requirement for expertise intervention and the domain gap between natural and medical images poses significant obstacles. This paper introduces a novel training-free evidential prompt generation method named EviPrompt to overcome these issues. The proposed method, built on the inherent similarities within medical images, requires only a single reference image-annotation pair, making it a training-free solution that significantly reduces the need for extensive labeling and computational resources. First, to automatically generate prompts for SAM in medical images, we introduce an evidential method based on uncertainty estimation without the interaction of clinical experts. Then, we incorporate the human prior into the prompts, which is vital for alleviating the domain gap between natural and medical images and enhancing the applicability and usefulness of SAM in medical scenarios. EviPrompt represents an efficient and robust approach to medical image segmentation, with evaluations across a broad range of tasks and modalities confirming its efficacy

A Day-ahead Optimal Economic Dispatch Schedule for Multi Energy Interconnected Region

AbstractThe energy supply center of the multi energy interconnected region is an energy station, which contains many types of energy supply equipment to match the cold, heating and power loads. This paper proposed a day-ahead optimal economic dispatch model for multi energy interconnected region based on centralized and interconnected energy exchange framework. In the model, the constraints of regional network topology are taken into account. The model is solved by the interior point method in this paper. A case study shows that by performing the schedule made by the dispatch model, the daily operation cost of the multi energy interconnected region decreasing remarkably, thus demonstrates the effectiveness of the proposed economic dispatch schedule

Food–energy–water nexus optimization brings substantial reduction of urban resource consumption and greenhouse gas emissions

Urban sustainability is a key to achieving the UN sustainable development goals (SDGs). Secure and efficient provision of food, energy, and water (FEW) resources is a critical strategy for urban sustainability. While there has been extensive discussion on the positive effects of the FEW nexus on resource efficiency and climate impacts, measuring the extent to which such synergy can benefit urban sustainability remains challenging. Here, we have developed a systematic and integrated optimization framework to explore the potential of the FEW nexus in reducing urban resource demand and greenhouse gas (GHG) emissions. Demonstrated using the Metropolis Beijing, we have identified that the optimized FEW nexus can reduce resource consumption and GHG emissions by 21.0 and 29.1%, respectively. These reductions come with increased costs compared to the siloed FEW management, but it still achieved a 16.8% reduction in economic cost compared to the business-as-usual scenario. These findings underscore the significant potential of FEW nexus management in enhancing urban resource efficiency and addressing climate impacts, while also identifying strategies to address trade-offs and increase synergies

Cross-Media Semantic Matching based on Sparse Representation

With the rapid growth of multi-modal data, cross-media retrieval has aroused many research interests. In this paper, the cross-media retrieval includes two tasks: query image retrieves relevant text and query text retrieves relevant images. With the development of sparse representation, two independent sparse representation classifiers are used to map the heterogeneous features of images and texts into their common semantic space before implementing similarity comparison. The proposed method makes full use of semantic information, and it is effective in the retrieving task. The performance of this method was evaluated on Wiki dataset, NUS-WIDE dataset, Wiki dataset with CNN features and Pascal dataset with CNN features. The experimental results validate its effectiveness compared with several state-of-the-art algorithms on the Mean Average Precision and other performance indexes

Whether interstitial space features were the main factors affecting sediment microbial community structures in Chaohu Lake

Sediments cover a majority of Earth’s surface and are essential for global biogeochemical cycles. The effects of sediment physiochemical features on microbial community structures have attracted attention in recent years. However, the question of whether the interstitial space has significant effects on microbial community structures in submerged sediments remains unclear. In this study, based on identified OTUs (operational taxonomic units), correlation analysis, RDA analysis, and Permanova analysis were applied into investigating the effects of interstitial space volume, interstitial gas space, volumetric water content, sediment particle features (average size and evenness), and sediment depth on microbial community structures in different sedimentation areas of Chaohu Lake (Anhui Province, China). Our results indicated that sediment depth was the closest one to the main environmental gradient. The destruction effects of gas space on sediment structures can physically affect the similarity of the whole microbial community in all layers in river dominated sedimentation area (where methane emits actively). However, including gas space, none of the five interstitial space parameters were significant with accounting for the microbial community structures in a sediment layer. Thus, except for the happening of active physical destruction on sediment structures (for example, methane ebullition), sediment interstitial space parameters were ineffective for affecting microbial community structures in all sedimentation areas

A decade of complex fractionated electrograms catheter-based ablation for atrial fibrillation: Literature analysis, meta-analysis and systematic review

AbstractBackgroundIt has been a decade since the complex fractionated atrial electrograms (CFAEs) were first established following the publication of Nademanee's standards. However, the status and focus of CFAE research are unclear, as is the efficacy of additional CFAE ablation in atrial fibrillation (AF). This literature review and meta-analysis were designed to determine the status of CFAE research and the efficacy and complications of CFAE ablation alone, pulmonary vein isolation (PVI) alone and PVI plus CFAE ablation in AF.MethodsWith the assistance from reference librarians and investigators trained in systematic review, we conducted a literature search of MEDLINE (via PubMed), Embase, the Cochrane Library, ScienceDirect, Wiley Blackwell and Web of Knowledge, using “complex fractionated atrial electrograms” for MeSH and keyword search.ResultsThe literature on CFAEs increased from 2007, mainly focusing on mapping studies, with mechanism studies increasing significantly from 2012. Fifteen trials with 1525 patients were qualified for our meta-analysis. Success rates were as follows. Overall (P < 0.001): CFAE ablation alone, 23.5–26.2%; PVI, 64.7%; PVI plus CFAE ablation, 67.0%. Single ablation: PVI, 60.4%; PVI plus CFAEs, 68.8% (OR 1.53, 95% CI 1.07–2.20, P = 0.02). Re-ablation: PVI, 69.0%; PVI plus CFAEs, 77.2% (OR 1.54, 95% CI 1.06–2.24, P = 0.02). Paroxysmal AF: PVI, 76.7%; PVI plus CFAEs, 79.1% (OR 1.20, 95% CI 0.79–1.81, P = 0.39). Persistent or permanent AF: PVI, 47.9%; PVI plus CFAEs, 58.7% (OR = 1.59, 95% CI 1.13–2.24, P = 0.008). Complication rates: PVI, 2.6%; PVI plus CFAEs, 3.4% (OR 1.22, 95% CI 0.58–2.57, P = 0.61).ConclusionsIn the literature, CFAE mapping studies preceded mechanism studies. CFAE ablation alone is insufficient for the treatment of AF. Additional CFAE ablation after adequate PVI or PVI plus linear ablation improves the outcome of single ablation and re-ablation without increasing complications, especially in persistent or permanent AF. There are insufficient data to support a similar improvement in paroxysmal AF or inducible AF after PVI for paroxysmal AF

2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research

Significant interest exists in establishing synergistic research in bioinformatics, systems biology and intelligent computing. Supported by the United States National Science Foundation (NSF), International Society of Intelligent Biological Medicine (http://www.ISIBM.org), International Journal of Computational Biology and Drug Design (IJCBDD) and International Journal of Functional Informatics and Personalized Medicine, the ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (ISIBM IJCBS 2009) attracted more than 300 papers and 400 researchers and medical doctors world-wide. It was the only inter/multidisciplinary conference aimed to promote synergistic research and education in bioinformatics, systems biology and intelligent computing. The conference committee was very grateful for the valuable advice and suggestions from honorary chairs, steering committee members and scientific leaders including Dr. Michael S. Waterman (USC, Member of United States National Academy of Sciences), Dr. Chih-Ming Ho (UCLA, Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Wing H. Wong (Stanford, Member of United States National Academy of Sciences), Dr. Ruzena Bajcsy (UC Berkeley, Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Qu Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Andrzej Niemierko (Harvard), Dr. A. Keith Dunker (Indiana), Dr. Brian D. Athey (Michigan), Dr. Weida Tong (FDA, United States Department of Health and Human Services), Dr. Cathy H. Wu (Georgetown), Dr. Dong Xu (Missouri), Drs. Arif Ghafoor and Okan K Ersoy (Purdue), Dr. Mark Borodovsky (Georgia Tech, President of ISIBM), Dr. Hamid R. Arabnia (UGA, Vice-President of ISIBM), and other scientific leaders. The committee presented the 2009 ISIBM Outstanding Achievement Awards to Dr. Joydeep Ghosh (UT Austin), Dr. Aidong Zhang (Buffalo) and Dr. Zhi-Hua Zhou (Nanjing) for their significant contributions to the field of intelligent biological medicine

A systematic investigation of the performance of copper-, cobalt-, iron-, manganese-, and nickel-based oxygen carriers for chemical looping combustion technology through simulation studies

The Integrated Gasification Combined Cycle coupled with chemical looping combustion (IGCC-CLC) is one of the most promising technologies that allow generation of cleaner energy from coal by capturing carbon dioxide (CO2). It is essential to compare and evaluate the performances of various oxygen carriers (OC), used in the CLC system; these are crucial for the success of IGCC-CLC technology. Research on OCs has hitherto been restricted to small laboratory and pilot scale experiments. It is therefore necessary to examine the performance of OCs in large-scale systems with more extensive analysis. This study compares the performance of five different OCs – copper, cobalt, iron, manganese and nickel oxides – for large-scale (350–400 MW) IGCC-CLC processes through simulation studies. Further, the effect of three different process configurations: (i) water-cooling, (ii) air-cooling and (iii) air-cooling along with air separation unit (ASU) integration of the CLC air reactor, on the power output of IGCC-CLC processes – are also investigated. The simulation results suggest that iron-based OCs, with 34.3% net electrical efficiency and ~100% CO2 capture rate lead to the most efficient process among all the five studied OCs. A net electrical efficiency penalty of 7.1–8.1% points leads to the IGCC-CLC process being more efficient than amine based post-combustion capture technology and equally efficient to the solvent based pre-combustion capture technology. The net electrical efficiency of the IGCC-CLC process increased by 0.6–2.1% with the use of air-cooling and ASU integration, compared with the water- and air-cooling cases. This work successfully demonstrates a correlation between the reaction enthalpies of different OCs and power output, which suggests that the OCs with higher values of reaction enthalpy for oxidation (ΔHr, oxidation) with air-cooling are more valuable for the IGCC-CLC