System Model Research Articles

Adaptive variable gain linear active disturbance rejection control parameter optimization in magnetic levitation

The magnetic levitation ball system is characterized by strong nonlinearity, multiple disturbances, and intrinsic instability, which has long been a thorny problem in the field of control engineering. The magnetic levitation system can be continuously and stably levitated, even in a complex environment. In this thesis, the model of the magnetic levitation ball system is firstly constructed according to the kinetic theory and simplified according to the actual situation. After that, a linear active disturbance rejection control (LADRC) controller for the magnetic levitation ball system is designed. Considering that there are many parameters in the LADRC controller and it is difficult to obtain the optimal control effect by manual tuning, an adaptive variable gain LADRC algorithm is proposed to optimize the control strategy of LADRC parameters. An adaptive iterative algorithm is used to adaptively adjust the bandwidth of the linear extended state observer (LESO) in LADRC, and the convergence of the algorithm is demonstrated by using the Lyapunov function. To solve the problem that the proportional and differential gains of the LADRC controller can only be adjusted unidirectionally and simultaneously, this paper proposes an error variable gain algorithm. The aim is to realize the non-unidirectional and more detailed adjustment of the controller parameters, and it is rigorously analyzed and demonstrated through simulation and experiment. The results show that the proposed algorithm is better than proportional–integral–derivative (PID), sliding mode control (SMC), and LADRC in terms of dynamic performance, steady-state performance, and anti-interference.

Dynamics of Shoreline Changes Along the Coast of Subarnarekha and Budhabalanga River Estuary, North Eastern Coast of India Using DSAS Technique: A Geospatial Technology Approach

ABSTRACTThe coastal regions represent one of the most significant environmental and economic resources, offering critical ecosystems that support biodiversity. Shoreline change analysis offers critical insights into coastal dynamics, providing trends in erosion and accretion, enabling effective coastal management and hazard mitigation. In the current study, shoreline change is assessed utilizing the Digital Shoreline Analysis System (DSAS) model for Subarnarekha and Budhabalanga river estuaries in Baleswar district, Odisha, India. The shoreline was extracted using multitemporal satellite images like Landsat‐5 and Landsat‐7 for the years 1991, 2000, and 2011. Similarly Sentinel‐2 and Landsat‐8 satellite imagery were used for the year 2022. The satellite data from 1991 to 2022 were processed using Envi, ArcGIS softwares and the shoreline is extracted for each year using band ratioing methods to demarcate shoreline. In the current research, the net accretion and erosion along the coast were analyzed using the GIS (geographic information systems) technique and the DSAS model. The four important statistical parameters of the DSAS model utilized in the study area are end point rate (EPR), net shoreline movement (NSM), linear regression rate (LRR), and least median of squares (LMS). The shoreline change analysis for the coast of Subarnarekha and Budhabalanga river estuary area from 1991 to 2022 reveals that 44% of the coast is under accretion, 7% is under stable coast, and 23% is under erosion. According to the findings, the coastal area of the recent study is both progressive and regressive in nature. For the study area, the average rates of shoreline accretion and erosion are 1.05 m and 0.45 m per year, respectively. The study gives information on erosion and accretion near the Subarnarekha and Budhabalanga river estuaries, which will aid in the development of an adaptive shoreline management strategy and coastal vulnerability assessment.

Stakeholder-led proactive risk assessment of medication safety in the pharmaceutical supply chain

Abstract Introduction In 2022/23, 1.08 billion medications were dispensed to patients using NHS England, at a cost of £19.04 billion1 . However, Elliot et al (2019)2 estimate every year there are 237 million medication errors at some point of the medication process, with a high associated cost. Increasingly, media is reporting medication shortages of critical medicines3 that can contribute to errors of omission. Medication errors suggests system, tasks and processes should be explored to understand if they have been poorly designed. This paper is a pre-Brexit study that examines the pharmaceutical supply chain with stakeholders. Aim To explore risk to medication safety in the pharmaceutical supply chain using qualitative interviews of stakeholders across the supply chain and proactive risk assessment method SHERPA (Systematic Human Error Reduction and Prediction Approach). Method 1. Qualitative interviews with process models System process models were developed (by literature, field observations and interviewees) and employed to elicit stakeholder perceptions about risk to medication safety in 31 qualitative interviews. Participants included pharmacists, wholesalers, pharmaceutical industry representatives, regulators and policymakers. Ethical approval was granted by Cambridge LREC to include healthcare professionals and 6 patients. Interviews were audio-recorded, transcribed and thematically analysed using N-Vivo. 2. Focus group for SHERPA Six stakeholders participated in the SHERPA focus group4 , including pharmacists and representatives from pharmaceutical manufacturing and wholesale industries. Interview participants were invited and those that agreed, attended. The SHERPA template was completed by the group. The session was audio-recorded, transcribed and thematically analysed using N-Vivo. Results The system models led to a greater understanding of the current system ‘as-is’ and created an overview of the supply chain. SHERPA is a validated method and provided the rigour to risk assess the supply chain process and identify sources of risk. However, the error mode terminology required adjustment to healthcare. Across all supply routes, the main source of risk was failure to supply medicines that caused errors of omission and the risk of counterfeit medicines. Failure to supply resulted from shortages that take place from trading activities that result in stockpiling or exporting of medicines. A lack of robust regulation and parallel imports increased the risk of counterfeit medicines. Stakeholders highlighted deficiencies in the supply chain and poor performance of stakeholders, as medication safety concerns. In order of frequency, the deficiencies include fragmented supply chain; complacency by stakeholders; poor communication and integration across supply chain; and end-user often regarded as the pharmacist, rather than the patient. Discussion and conclusion From the findings, strategies emerged as possible solutions. These included communication of shortages in each component of supply chain; robust counterfeit strategies; use of technology (automation/digital tools); and re-design tasks and processes in dispensaries and wards. Staff training, education, and revalidation of stakeholders is vital. Key limitations in this study include biases that can occur from recruitment strategy and small sample size. The SHERPA method posed terminology problems. In conclusion, this multi-method approach reveals risk and possible solutions to improve safety and reduce cost in the NHS. It is clear this study needs to be repeated to understand the impact of Brexit and current reconfiguration of NHS.

Weakening of global terrestrial carbon sequestration capacity under increasing intensity of warm extremes.

The net ecosystem exchange (NEE), determining terrestrial carbon sequestration capacity, is strongly controlled by climate change and has exhibited substantial year-to-year fluctuations. How the increased frequency and intensity of warm extremes affect NEE variations remains unclear. Here, we combined multiple NEE datasets from atmospheric CO2 inversions, Earth system models, eddy-covariance data-driven methods and climate datasets to show that the terrestrial carbon sequestration capacity is weakened during warm extreme occurrences over the past 40 years, primarily contributed by tropical regions (81% ± 48%). The underlying mechanism can be rooted in the overwhelmingly decreased trend of gross primary productivity compared with terrestrial ecosystem respiration. Additionally, the weakened terrestrial carbon sequestration capacity is mainly driven by the transition from temperature or soil moisture control to vapour pressure deficit control, which is associated with the increasing intensity of warm extremes. Our findings suggest that warm extremes threaten the global carbon sequestration function of terrestrial ecosystems. Therefore, more attention should be given to the evolution of the increasing intensity of warm extremes in future climate projections.

An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation

Abstract. Aerosols constitute important substance components of the Earth's atmosphere and have a profound influence on climate dynamics, radiative properties, and biogeochemical processes. Here we introduce updated emission schemes for dust, sea-salt, and marine primary organic aerosols (MPOA), as well as augmented secondary organic aerosol (SOA) formation pathways within the Community Earth System Model (CESM; version 2.1.3). The modified dust emission scheme shifts the original hotspot-like dust emission to a more continuous distribution, improving the dust aerosol optical depth (DAOD) simulations at stations in north Africa and central Asia. This update also reduces dust residence time from 4.1 to 1.6 d, enhancing concentration simulations downwind of dust source regions. For sea-salt emissions, we incorporate an updated sea surface temperature (SST) modulation and introduce a relative-humidity-dependent correction factor for sea-salt particle size, with SST having a significantly larger impact on sea-salt emissions (16.1 %) compared to the minor effect of humidity (−0.3 %). We then extend our modelling to incorporate emissions of marine primary organic aerosols (MPOA) as mixed externally with sea-salt aerosols, coupled offline with the ocean component Parallel Ocean Program (POP2). The results underscore the substantial influence of phytoplankton diversity on MPOA emissions, with 148 % variability simulated among different phytoplankton types, highlighting the role of biological variability in aerosol modelling. Furthermore, we refine the model's chemical mechanisms by including the irreversible aqueous uptake of dicarbonyl compounds as a new pathway for SOA formation, contributing an additional 37 % to surface SOA concentrations. These improvements enrich the ability of the CESM to use intricate linkages between different components of the Earth system, thereby enabling a more comprehensive description of natural aerosol emissions, chemical processes, and their impacts.

Projected future changes in extreme precipitation over China under stratospheric aerosol intervention in the UKESM1 climate model

Abstract. Extreme precipitation events are linked to severe economic losses and casualties in China every year; hence, exploring the potential mitigation strategies to minimize these events and their changes in frequency and intensity under global warming is of importance, particularly for the populous subregions. In addition to global warming scenarios, this study examines the effects of the potential deployment of stratospheric aerosol injection (SAI) on hydrological extremes in China based on the SAI simulations (G6sulfur) of the Geoengineering Model Intercomparison Project (GeoMIP) by the UK Earth System Model (UKESM1) simulations. G6sulfur is compared with simulations of the future climate under two different emission scenarios (SSP5-8.5 and SSP2-4.5) and a reduction in the solar constant (G6solar) to understand the effect of SAI on extreme precipitation patterns. The results show that under global warming scenarios, precipitation and extreme wet climate events during 2071–2100 are projected to increase relative to the control period (1981–2010) across all the subregions in China. Extreme drought events show a projected increase in southern China. The G6sulfur and G6solar experiments show statistically similar results to those under SSP2-4.5 in extreme precipitation intensities of China in UKESM1. These results are encouraging. The efficacy of SAI in decreasing extreme precipitation events and consecutive wet days is more pronounced than that of G6solar when compared to SSP2-4.5. While both G6sulfur and G6solar show drying at high-latitude regions, which is consistent with our understanding of the spin-down of the hydrological cycle under SRM. Given the limitations of the current model and the small ensemble size, and considering that the hydrological effects are less beneficial than those indicated for temperature, it is recommended that further, more comprehensive research be performed, including using multiple models, to better understand these impacts.

Fuzzy logic controller of a step-up boost converter applied to a photovoltaic system

the constantly increasing global energy need and the polluting nature of fossil energies have increased the interest in the development of renewable energies. Among them, photovoltaic energy. The function of a photovoltaic (PV) system is to ensure the conversion of solar energy into electrical energy and the conditioning of this energy in order to adapt it to various needs. The performance of a PV system depends essentially on the quality of the conditioning of the energy, which allows the optimal transfer of the energy of the PV generator, and the management of the energy produced to meet energy needs by incorporating of converters. In this article, we present an intelligent approach to improve and optimize the performance of a photovoltaic system, by the fuzzy MPPT control. Our system consists of a photovoltaic panel, a Boost-type DC-DC converter con-sidered as an adaptation stage between the PV and the load. The IC technique was compared with FLC to evaluate the best and most accurate controller for MPPT. The results suggest that the use of FLC could improve the MPPT and increase the sTableility of the PV system. System modeling and simulation performed with Matlab/Simulink.

Performance of water quality simulation model for lifting drainage water joints and mixing zone determination

Limited water resources with gradual increase in water demand led to higher dependence on drainage water as one of the non-conventional water resources in Egypt. However, there was no precise approach for using such resource. The practices ranged between stopping lifting drainage water to main canals at many locations due to the water quality degradation in the drains and pure dependence on polluted drainage water by farmers. This implies the importance of applying the mathematical models that provide precise and flexible alternative for the dependence on the drainage water. This procedure could save the big investments that were used in the lifting stations while mitigating the environmental hazards. Cornell Mixing Zone Expert System (CORMIX) model is one of these mathematical simulation models. The study used surface discharge sub-model (CORMIX3) to define the mixing zone between the lifted drainage water from Mehalet Rough drain and the freshwater in Mit Yazid canal, by investigated biochemical oxygen demand (BOD) and total dissolved solids (TDS). The simulation results verified that the two investigated parameters met WQ standards for the Egyptian law 48/1982. BOD standard value was met after 448.36 m, in 723 s. TDS standard value was met after 4.46 m, in 7.8 s. This was far ahead of the first municipal station regardless low quality of these parameters in the drain. This is the first time to apply this model in the irrigation sector in Egypt, and the results were promising for defining the precise approach to reuse the drainage water in Egypt.

Recent Progress on Air, Liquid, PCM, Heat Pipe, and Hybrid Modes of Thermal Management in Lithium-Ion Batteries

This study emphasises lithium-ion batteries, which have been the subject of extensive research due to their wide range of benefits, including extended life cycle, minimal discharge, and high energy density. However, the temperature sensitivity of the batteries presents a notable obstacle that can negatively impact their performance and longevity when operating under extreme conditions. To overcome this challenge, implementing an effective battery thermal management system (BTMS) is imperative. Battery thermal management is crucial for ensuring the safety and longevity of lithium-ion batteries, especially in high-demand applications like electric vehicles. This comprehensive review explores a variety of BTMS technologies, including air-cooling methods, liquid-cooling techniques, heat pipes, and PCM materials. While air-cooled BTMS is a safe and straightforward design, its lower heat capacity and thermal efficiency limit its use to low-capacity batteries. However, forced air-cooled BTMS is an excellent solution for high charging/discharging rates, as air flows through channels within the battery packs to optimize cooling. Liquid-cooled BTMS also shows promise, although designers must ensure the sealing cover is secure to prevent leaks. Heat pipes (HP) offer a unique approach to controlling battery temperature, while Phase change materials (PCM) thermal management is notable for its ability to absorb significant heat by latent heat. Hybrid cooling combines fins, nanofluids, PCM, and microchannels-based cooling and can significantly enhance battery performance under high charging/discharging rates. Furthermore, lithium-ion batteries are extensively used in various applications, including the Electric vehicle industry. Keeping the lithium-ion battery temperature within the optimal range is important and is accomplished by a suitable BTMS. Different methods, such as air cooling, Liquid cooling, Heat pipe, and PCM materials, are used in BTMS. An effective thermal management system and efficient battery model are absolutely necessary. Each of the techniques in BTMS has its own benefits and drawbacks. The effectiveness of thermal management configurations and methods can vary. Thus, evaluating performance and optimal configuration is crucial before implementation.

Assessing the Manufacturability and Critical Quality Attribute Profiles of Anti-IL-8 Immunoglobulin G Mutant Variants.

Early-phase manufacturability assessment of high-concentration therapeutic monoclonal antibodies (mAbs) involves screening of process-related risks impacting their translation into the clinic. Manufacturing a mAb at scale relies on cost-effective and robust approaches to derisk manufacturability parameters, such as viscosity, conformational stability, aggregation, and process-related impurities. Using a panel of model anti-IL-8 IgG1 mutants, we investigate upstream and downstream processability, phase behavior, and process-related impurities. We correlate trends in the biophysical properties of mAbs with their cell growth, expression, filtration flux, solubility, and post-translational modifications. We find significant trends in increased relative free light chain expression with heavy chain mutants and detect a requirement for adjusted operation pH for cation exchange polishing steps with charge-altering variants. Moreover, trends between phase stability and high-concentration viscosity were observed. We also investigated unique correlations between increased glycosylation and biophysical behavior. Further in-depth analysis and modeling are required to elucidate the impact of the mAb sequence on the metabolism of the expression system, solubility limits, and alternative gelation models as future directions.

Integration of disamenity costs and equality considerations regarding onshore wind power expansion and distribution into energy system optimization models

BackgroundSocial acceptance of energy infrastructure projects affects public support for the energy transition and is essential for the transition’s sustainability and success. Despite extensive research focusing on the social acceptance of renewable energy, and on the acceptance of onshore wind power in particular, energy system models have largely prioritized techno-economic aspects. This focus has created a gap between model results and decision-makers’ needs. In this study, we offer recommendations for integrating disamenity costs and equality considerations—two critical social aspects related to onshore wind power—into energy system optimization. To achieve this, we use a spatially distributed model from a climate-neutral Germany and explore various implementations and trade-offs of these two social aspects.ResultsWe identified effective linear formulations for both disamenity costs and equality considerations as model extensions, notably outperforming quadratic alternatives, which exhibit longer solution times (+ 50–115%). Our findings reveal that the endogenous consideration of disamenity costs in the optimization approach can significantly reduce the human population’s exposure to wind turbines, decreasing the average disamenity per turbine by 53%. Drawing on notions of welfare economics, we employ two different approaches for integrating equality into the optimization process, permitting the modulation of the degree of equality within spatial distributions in energy system models. The trade-offs of the two social aspects compared to the cost-optimal reference are moderate, resulting in a 2–3% increase in system costs.ConclusionsDisamenity costs emerge as a predominant factor in the distribution of onshore wind power in energy system optimization models. However, existing plans for onshore wind power distribution in Germany underscore equality as the driving factor. The inclusion of social aspects in energy system models facilitates the identification of socially superior wind turbine locations. Neglecting disamenity costs and equality considerations leads to an overestimation of the practical solution space for decision-makers and, consequently, the resulting energy system designs.

Multi-timescale modeling and order reduction towards stability analysis of isolated microgrids

Microgrids incorporate a significant proportion of renewable energy sources and power electronic converters in the energy conversion process, creating a sustainable and clean energy infrastructure. However, the multi-timescale dynamics of microgrids are interactively coupled under a nonlinear structure, which makes it difficult to gain insight into the instability mechanisms without a high-fidelity reduced-order model that preserves the main dynamic behaviors of the system. For the isolated AC microgrid dominated by voltage source inverters (VSI), a detailed state-space model of the system, including the inverter, network, and load, is first developed. Based on this model, the eigenvalue analysis is carried out, and a participation factor analysis tool is also utilized to identify the relevant dynamics that have a strong impact on the system's dominant mode. Furthermore, to simplify the system modeling process without losing essential dynamic interactions, a novel multi-timescale coupled reduced-order model is proposed using a transfer function-based order reduction method, which retains the open-loop gain characteristics to preserve the critical couplings between fast inner loop dynamics and slow droop control dynamics. Finally, the accuracy of the reduced-order model is verified by comparing it with the detailed model and the conventional singular perturbation reduced-order model through eigenvalue distribution and time-domain simulation analysis.

Drift compensation system of an autocollimator based on reciprocal roll angles and a feedback combination target

To address the issues of limited field of view and beam drift in traditional autocollimation measurements, a novel, to our knowledge, autocollimation measurement method is proposed. This method is based on the principle of full-circle continuous measurement using reciprocal roll angles of a compound biaxial system, combined with a feedback and compensation mechanism for beam drift using both calibration and compensation targets. A self-collimating small-angle measurement system model, coupled with a compound biaxial turntable and combined target, is established using ray tracing and perspective projection transformation techniques. Additionally, a closed-loop beam drift compensation system is developed by applying a BP neural network and a PID control algorithm. Experimental tests on the compensation system demonstrate a significant improvement in measurement accuracy and stability. The results show that this method satisfies the requirements for small-angle autocollimation measurement, and the method also enhances the overall stability of the autocollimation system.

Climate Conundrum: A Wet or Dry European and Northern African Climate During the Middle Miocene

AbstractEnd of 21st‐century hydroclimate projections suggest an expansion of subtropical dry zones, with Mediterranean and Sahel regions becoming much drier. However, paleobotanical assemblage evidence from the middle Miocene (17‐12 Ma), suggests both regions were instead humid environments. Here we show that by modifying regional sea surface temperatures (SST) in an Earth System Model (CESM1.2) simulation of the middle Miocene, the increased ocean evaporation and integrated water vapor flux overrides any drying effects associated with warming‐induced land‐surface evaporation driven by atmospheric CO2 concentrations. These modifications markedly reduce the bias in the model‐data comparison for this period. A vegetation model (BIOME4) forced with simulated climatologies predicts both regions were dominated by mixed forest, which is largely consistent with the paleobotanical record. This study unveils the potential for wetter subtropical Mediterranean climates associated with warming, presenting an alternative scenario from future drying projections with localized SST warming governing regional climate change.

Monovalent Ion Effect on Liquid-Liquid Phase Separation of Aqueous Polyphosphate-Salt Mixtures.

Polyphosphate (polyP) is one of the most conserved biomacromolecules and can form aggregates, such as polyP granules in bacteria, which are generated through liquid-liquid phase separation (LLPS). Studies have examined the mechanism of polyP aggregation using LLPS systems containing artificial polyP molecules as aggregation system models, where LLPS is typically induced by multivalent salts and polyelectrolytes. Although the typical concentrations of monovalent ions in living cells are approximately 100 times higher than those of divalent ions, the effects of monovalent ions on the LLPS of polyP solutions are little known. This study demonstrated that submolar NaCl induces LLPS of polyP solutions, whereas other monovalent salts did not induce LLPS at the same concentrations. Small-angle X-ray scattering measurements revealed that NaCl significantly stabilizes the intermolecular association of polyP, inducing LLPS. These findings suggest that the modulation of monovalent ion concentrations is an underlying mechanism of polyP aggregate formation and deformation within living cells.

Innovation and Sustainability in the Amazon with the Use of Blockchain

Objective: The general objective of this study is to model the implementation of a blockchain system for solid wastemanagement in a government agency. The specific objectives of the results are to identify the main challenges in implementing a blockchain system for solid waste management in Public Management (1); characterize the blockchain models identified in this investigation (2); and develop a blockchain system model for solid waste management in a government agency (3). Theoretical Framework: The Theory of New Public Management, discussed in Madan and Ashok (2022), is the basis of this study, considering the notes of these authors, who address the dominant paradigm in public administration. Method: This research has a qualitative or mixed approach, as it includes parametric elements based on architecture such as blockchain, supported by bibliographical research and documentary analysis. The bibliographical research was based on elements of an integrated solid waste management system, through a framework, as conceptualized in the specific topic of this study. The Content Analysis method was used to research documents and other textual or audiovisual databases on solid waste management and blockchain technology. This research method allowed us to extract relevant information from the data collected, organize it into thematic categories, and interpret it in light of the theoretical framework obtained. By applying Content Analysis, patterns, meanings, and nuances were identified that could enrich the understanding of the phenomenon studied, ensuring an in-depth and contextualized analysis. Results and Discussion: The scenario of research on solid waste management in Brazil is marked by significantchallenges that reflect the complexity of the country's socioeconomic and environmental context. According to Agência Brasil (2023), the generation of solid waste has increased alarmingly, with data from 2021 indicating that more than 80 million tons were produced, of which only 32.5% were correctly disposed of. Thisreality highlights the urgent need for effective and innovative public policies that address integrated waste management. Research Implications: The relevance of implementing a blockchain system in public governance is highlighted, considering the growing demand for innovative and sustainable solutions. Originality/Value: This study is of interest to government managers, academics involved in applied research onblockchain in waste management, politicians and other leaders committed to excellence in management, and other professionals committed to promising results in the relationship between innovation and sustainability in organizations.

Unifying Model Execution and Deductive Verification with Interaction Trees in Isabelle/HOL

Model execution allows us to prototype and analyse software engineering models by stepping through their possible behaviours, using techniques like animation and simulation. On the other hand, deductive verification allows us to construct formal proofs demonstrating satisfaction of certain critical properties in support of high-assurance software engineering. To ensure coherent results between execution and proof, we need unifying semantics and automation. In this paper, we mechanise Interaction Trees (ITrees) in Isabelle/HOL to produce an execution and verification framework. ITrees are coinductive structures that allow us to encode infinite labelled transition systems, yet they are inherently executable. We use ITrees to create verification tools for stateful imperative programs, concurrent programs with message passing in the form of the CSP and Circus languages, and abstract system models in the style of the Z and B methods. We demonstrate how ITrees can account for diverse semantic presentations, such as structural operational semantics, a relational program model, and CSP's failures-divergences trace model. Finally, we demonstrate how ITrees can be executed using the Isabelle code generator to support the animation of models.

IPEM topical report: the first UK survey of cone beam CT dose indices in radiotherapy verification imaging for adult patients

Cone beam CT is integral to most modern radiotherapy treatments. The application of daily and repeat CBCT imaging can lead to high imaging doses over a large volume of tissue that extends beyond the treatment site. Hence, it is important to ensure exposures are optimised to keep doses as low as reasonably achievable, whilst ensuring images are suitable for the clinical task. This IPEM topical report presents the results of the first UK survey of dose indices in radiotherapy CBCT. Dose measurements, as defined by the cone beam dose index (CBDIw), were collected along with protocol information for seven treatment sites. Where a range of optimised protocols were available in a centre, a sample of patient data demonstrating the variation in protocol use were requested. Protocol CBDIwvalues were determined from the average dosimetry data for each type of linear accelerator, and median CBDIwand scan length were calculated for each treatment site at each centre. Median CBDIwvalues were compared and summary statistics derived that enable the setting of national dose reference levels (DRLs). A total of 63 UK radiotherapy centres contributed data. The proposed CBDIwDRLs are; prostate 20.6 mGy, gynaecological 20.8 mGy, breast 5.0 mGy, 3D-lung 6.0 mGy, 4D-lung 11.8 mGy, brain 3.5 mGy and head/neck 4.2 mGy. However, large differences between models of imaging system were noted. Where centres had pro-active optimisation strategies in place, such as sized based protocols with selection criteria, dose reductions on the 'average' patient were possible compared with vendor defaults. Optimisation of scan length was noted in some clinical sites, with Elekta users tending to fit different collimators for prostate imaging (relatively short) compared with gynaecological treatments (longest). This contrasts with most Varian users who apply the default scan length in most cases.

Memprot.GPCR-ModSim: Modelling and simulation of membrane proteins in a nutshell.

Memprot.GPCR-ModSim leverages our previous web-based protocol, which was limited to class-A G protein-coupled receptors, to become the first one-stop web server for the modelling and simulation of any membrane protein system. Motivated by the exponential growth of experimental structures and the breakthrough of deep-learning-based structural modelling, the server accepts as input either a membrane-protein sequence, in which case it reports the associated AlphaFold model, or a 3D (experimental, modelled) structure, including quaternary complexes with associated proteins and/or ligands of any kind. In both cases, the molecular dynamics (MD) protocol produces a membrane-embedded, solvated, and equilibrated system, ready to be used as a starting point for further MD simulations, including ligand-binding free energy calculations. Memprot.GPCR-ModSim web server is publicly available at https://memprot.gpcr-modsim.org/. The standalone modules for 3D modelling (PyModSim) or membrane embedding and MD equilibration (PyMemDyn) are available at the GitHub repository https://github.com/GPCR-ModSim/. Supplementary data are available at Bioinformatics online.

Simulation and Optimization of a Hybrid Photovoltaic/Li-Ion Battery System

The coupling of solar cells and Li-ion batteries is an efficient method of energy storage, but solar power suffers from the disadvantages of randomness, intermittency and fluctuation, which cause the low conversion efficiency from solar energy into electric energy. In this paper, a circuit model for the coupling system with PV cells and a charge controller for a Li-ion battery is presented in the MATLAB/Simulink environment. A new three-stage charging strategy is proposed to explore the changing performance of the Li-ion battery, comprising constant-current charging, maximum power point tracker (MPPT) charging and constant-voltage charging stages, among which the MPPT charging stage can achieve the fastest maximum power point (MPP) capture and, therefore, improve battery charging efficiency. Furthermore, the charge controller can improve the lifetime of the battery through the constant-current and constant-voltage charging scheme. The simulation results indicate that the three-stage charging strategy can achieve an improvement in the maximum power tracking efficiency of 99.9%, and the average charge controller efficiency can reach 96.25%, which is higher than that of commercial chargers. This work efficiently matches PV cells and Li-ion batteries to enhance solar energy storages, and provides a new optimization idea for hybrid PV/Li-ion systems.