Guest Editorial to the Special Letters Issue on Emerging Technologies in Multiparameter Biomedical Optical Imaging and Image Analysis

The past two decades have witnessed revolutionary advances in biomedical imaging modalities capable of providing biological and physiological information from the cellular scale to the organ level. Recent advances have also been focused on cost-effective, noninvasive, portable, and molecularimaging technologies for imaging at microscopic, mesoscopic, and macroscopic levels. These technologies have significant potential to advance biomedical research and clinical practice. They can also provide a better understanding and monitoring of physiological and functional disorders, which could lead to mainstream diagnostic technologies of the future

Predictive control co-design for enhancing flexibility in residential housing with battery degradation

Buildings are responsible for about a quarter of global energy-related CO2 emissions. Consequently, the decarbonisation of the housing stock is essential in achieving net-zero carbon emissions. Global decarbonisation targets can be achieved through increased efficiency in using energy generated by intermittent resources. The paper presents a co-design framework for simultaneous optimal design and operation of residential buildings using Model Predictive Control (MPC). The framework is capable of explicitly taking into account operational constraints and pushing the system to its efficiency and performance limits in an integrated fashion. The optimality criterion minimises system cost considering time-varying electricity prices and battery degradation. A case study illustrates the potential of co-design in enhancing flexibility and self-sufficiency of a system operating under different conditions. Specifically, numerical results from a low-fidelity model show substantial carbon emission reduction and bill savings compared to an a-priori sizing approach

Pengaruh Dekok Daun Sirih (Piper betle L) Sebagai Bahan Teat Dipping pada Sapi Perah Friesian Holstein

Daun sirih merupakan tanaman herbal yang banyak manfaat dan memiliki antibakteri yang baik. Penelitian ini bertujuan mengetahui penggunaan dekok daun sirih hijau (Piper betle L.) sebagai bahan teat dipping terhadap persentase penurunan CMT dan TPC susu sapi FH laktasi 1, 2 dan 3 serta tingkat penggunaan dekok daun sirih hijau (Piper betle L.) yang dapat menurunkan jumlah bakteri paling tinggi dan mengurangi tingkat kejadian mastitis. Ternak penelitian adalah 36 ekor induk sapi perah Friesian Holstein (FH) laktasi 1, 2 dan 3. Metode penelitian menggunakan eksperimental dengan rancangan acak lengkap faktorial yang terdiri atas 12 perlakuan dan masing-masing diulang sebanyak 3 kali . Hasil penelitian menunjukkan bahwa perlakuan berpengaruh sangat nyata (P<0,01) terhadap California Mastitis Test (CMT) dan Total Plate Count (TPC). Kesimpulan menunjukkan bahwa perlakuan dekok daun sirih 50% dan 60% menghasilkan paling efektif terhadap penurunan persentase CMT dan TPC, serta periode laktasi tidak mempengaruhi dalam penurunan persentase CMT dan TPCDaun sirih merupakan tanaman herbal yang banyak manfaat dan memiliki antibakteri yang baik. Penelitian ini bertujuan mengetahui penggunaan dekok daun sirih hijau (Piper betle L.) sebagai bahan teat dipping terhadap persentase penurunan CMT dan TPC susu sapi FH laktasi 1, 2 dan 3 serta tingkat penggunaan dekok daun sirih hijau (Piper betle L.) yang dapat menurunkan jumlah bakteri paling tinggi dan mengurangi tingkat kejadian mastitis. Ternak penelitian adalah 36 ekor induk sapi perah Friesian Holstein (FH) laktasi 1, 2 dan 3. Metode penelitian menggunakan eksperimental dengan rancangan acak lengkap faktorial yang terdiri atas 12 perlakuan dan masing-masing diulang sebanyak 3 kali . Hasil penelitian menunjukkan bahwa perlakuan berpengaruh sangat nyata (P<0,01) terhadap California Mastitis Test (CMT) dan Total Plate Count (TPC). Kesimpulan menunjukkan bahwa perlakuan dekok daun sirih 50% dan 60% menghasilkan paling efektif terhadap penurunan persentase CMT dan TPC, serta periode laktasi tidak mempengaruhi dalam penurunan persentase CMT dan TPC

Guest Editorial to the Special Letters Issue on Emerging Technologies in Multiparameter Biomedical Optical Imaging and Image Analysis

The past two decades have witnessed revolutionary advances in biomedical imaging modalities capable of providing biological and physiological information from the cellular scale to the organ level. Recent advances have also been focused on cost-effective, noninvasive, portable, and molecularimaging technologies for imaging at microscopic, mesoscopic, and macroscopic levels. These technologies have significant potential to advance biomedical research and clinical practice. They can also provide a better understanding and monitoring of physiological and functional disorders, which could lead to mainstream diagnostic technologies of the future

Predictive control co-design for enhancing flexibility in residential housing with battery degradation

Buildings are responsible for about a quarter of global energy-related CO2 emissions. Consequently, the decarbonisation of the housing stock is essential in achieving net-zero carbon emissions. Global decarbonisation targets can be achieved through increased efficiency in using energy generated by intermittent resources. The paper presents a co-design framework for simultaneous optimal design and operation of residential buildings using Model Predictive Control (MPC). The framework is capable of explicitly taking into account operational constraints and pushing the system to its efficiency and performance limits in an integrated fashion. The optimality criterion minimises system cost considering time-varying electricity prices and battery degradation. A case study illustrates the potential of co-design in enhancing flexibility and self-sufficiency of a system operating under different conditions. Specifically, numerical results from a low-fidelity model show substantial carbon emission reduction and bill savings compared to an a-priori sizing approach

A modelling workflow for predictive control in residential buildings

Despite a large body of research, the widespread application of Model Predictive Control (MPC) to residential buildings has yet to be realised. The modelling challenge is often cited as a significant obstacle. This chapter establishes a systematic workflow, from detailed simulation model development to control-oriented model generation to act as a guide for practitioners in the residential sector. The workflow begins with physics-based modelling methods for analysis and evaluation. Following this, model-based and data-driven techniques for developing low-complexity, control-oriented models are outlined. Through sections detailing these different stages, a case study is constructed, concluding with a final section in which MPC strategies based on the proposed methods are evaluated, with a price-aware formulation producing a reduction in operational space-heating cost of 11%. The combination of simulation model development, control design and analysis in a single workflow can encourage a more rapid uptake of MPC in the sector

A Modelling Workflow for Predictive Control in Residential Buildings

Despite a large body of research, the widespread application of Model Predictive Control (MPC) to residential buildings has yet to be realised. The modelling challenge is often cited as a significant obstacle. This chapter establishes a systematic workflow, from detailed simulation model development to control-oriented model generation to act as a guide for practitioners in the residential sector. The workflow begins with physics-based modelling methods for analysis and evaluation. Following this, model-based and data-driven techniques for developing low-complexity, control-oriented models are outlined. Through sections detailing these different stages, a case study is constructed, concluding with a final section in which MPC strategies based on the proposed methods are evaluated, with a price-aware formulation producing a reduction in operational space-heating cost of 11%. The combination of simulation model development, control design and analysis in a single workflow can encourage a more rapid uptake of MPC in the sector

MPC and optimal design of residential buildings with seasonal storage: a case study

Residential buildings account for about a quarter of the global energy use. As such, residential buildings can play a vital role in achieving net-zero carbon emissions through efficient use of energy and balance of intermittent renewable generation. This chapter presents a co-design framework for simultaneous optimisation of the design and operation of residential buildings using Model Predictive Control (MPC). The adopted optimality criterion maximises cost savings under time-varying electricity prices. By formulating the co-design problem using model predictive control, we then show a way to exploit the use of seasonal storage elements operating on a yearly timescale. A case study illustrates the potential of co-design in enhancing flexibility and self-sufficiency of a system operating on multiple timescales. In particular, numerical results from a low-fidelity model report approximately doubled bill savings and carbon emission reduction compared to the a priori sizing approach