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The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. An increasing number of countries are investigating options to stop the spread of the emerging zoonotic infection Salmonella Dublin (S. Dublin), which mainly spreads among bovines and with cattle manure. Detailed surveillance and cattle movement data from an 11-yr period in Denmark provided an opportunity to gain new knowledge for mitigation options through a combined social network and simulation modeling approach. The analysis revealed similar network trends for noninfected and infected cattle farms despite stringent cattle movement restrictions imposed on infected farms in the national control program. The strongest predictive factor for farms becoming infected was their cattle movement activities in the previous month, with twice the effect of local transmission. The simulation model indicated an endemic S. Dublin occurrence, with peaks in outbreak probabilities and sizes around observed cattle movement activities. Therefore, pre- and postmovement measures within a 1-mo time window may help reduce S. Dublin spread. [ABSTRACT FROM AUTHOR]

To elucidate the design and fabrication methodologies employed in creating a personalized cleft lip simulation model, primarily intended for enhancing surgical training and diverse applications. The study further sought to assess the viability of integrating this simulation model into undergraduate oral experiments and instructional settings. Facial data from individuals with cleft lip conditions were acquired using a scanner. Subsequent stages involved reverse engineering and the utilization of 3D printing technology to generate a cleft lip silicone simulation model. The molding process entailed injecting silicone into a polylactic acid mold. The study enrolled 53 undergraduate students majoring in dentistry, who were randomly assigned to either a control or experimental group. A dedicated instructor guided each group independently, employing a combination of multiple-choice tests and surveys to gauge real-time evaluations and discern inter-group disparities. We successfully designed and produced a personalized cleft lip simulation model, demonstrating notable efficacy in the context of cleft lip experimental teaching. Statistical analysis revealed a significant difference (P < 0.05) in the scores of the experimental group students on multiple-choice questions pertaining to cleft lip surgical procedures. Survey outcomes indicated that the experimental group students exhibited higher confidence levels in cleft lip surgery, as reflected from their responses to relevant questions, compared to the traditional group students. These differences were statistically significant (P < 0.05). The simulation model developed in this study emerges as a reliable and cost-effective training and teaching tool for cleft lip surgery. [ABSTRACT FROM AUTHOR]

Infection control measures are effective for nosocomial COVID-19 prevention but bear substantial health-economic costs, motivating their "de-escalation" in settings at low risk of SARS-CoV-2 transmission. Yet consequences of de-escalation are difficult to predict, particularly in light of novel variants and heterogeneous population immunity. To estimate how infection control measure de-escalation influences nosocomial COVID-19 risk. An individual-based transmission model was used to simulate SARS-CoV-2 outbreaks and control measure de-escalation in a French long-term care hospital with multi-modal control measures in place (testing and isolation, universal masking, single-occupant rooms). Estimates of COVID-19 case fatality rates (CFRs) from reported outbreaks were used to quantify excess COVID-19 mortality due to de-escalation. In a population fully susceptible to infection, de-escalating both universal masking and single rooms resulted in hospital-wide outbreaks of 114 (95% CI: 103–125) excess infections, compared with five (three to seven) excess infections when de-escalating only universal masking or 15 (11–18) when de-escalating only single rooms. When de-escalating both measures and applying CFRs from the first wave of COVID-19, excess patient mortality ranged from 1.57 (1.41–1.71) to 9.66 (8.73–10.57) excess deaths/1000 patient-days. By contrast, when applying CFRs from subsequent pandemic waves and assuming susceptibility to infection among 40–60% of individuals, excess mortality ranged from 0 (0–0) to 0.92 (0.77–1.07) excess deaths/1000 patient-days. The de-escalation of bundled COVID-19 control measures may facilitate widespread nosocomial SARS-CoV-2 transmission. However, excess mortality is probably limited in populations at least moderately immune to infection and given CFRs resembling those estimated during the 'post-vaccine' era. [ABSTRACT FROM AUTHOR]

Germline BRCA mutations (gBRCAm) occur in 4%–8% patients with metastatic pancreatic cancer (mPC); guidelines recommend platinum-based chemotherapies and olaparib maintenance in this population. We evaluated, through modeling, the role of treatments and gBRCA testing on health outcomes of mPC patients. A decision tree/partitioned survival model was developed to assess lifetime health outcomes for four strategies: 1) no testing; 2) early testing/no olaparib maintenance; 3) early testing (i.e., before 1L treatment)/olaparib maintenance; and 4) late testing/olaparib maintenance. Treatment patterns were assumed to follow current practice in the United States. Overall survival and progression-free survival curves were extrapolated from pivotal trials, including POLO trial for outcomes from olaparib maintenance after at least 16 weeks of platinum-based chemotherapy. Among patients with g BRCA m, almost twice as many patients received platinum-based regimens in strategies involving early testing compared to when early testing was not employed (78.7 % vs 40.2 %). Health outcomes were highest in the strategy with early testing and available olaparib treatment whether considering progression-free life years (PF LYs, 1.27 vs 0.55–0.87), LYs (1.82 vs 0.95–1.27) or quality adjusted life years (QALYs, 1.15 vs 0.73–0.92 for others). Consistent patterns of results were observed in the overall cohort of mPC patients (i.e., irrespective of gBRCAm). Patients with mPC achieved longest health outcomes (as measured by mean PF LYs, LYs and QALYs) with a scenario of early g BRCA testing and availability of olaparib maintenance. The results were primarily driven by improved health outcomes associated with higher efficacy of platinum-based chemotherapies and olaparib used in gBRCAm patients. [ABSTRACT FROM AUTHOR]

Food security remains a critical concern in Indonesia, prompting the need for adequate food availability nationwide. Maize, as a prominent staple crop, faces demand imbalances across the country. To address this issue, a system dynamics model is developed to analyze the dynamics of maize supply and demand in East Java. The model captures the non-linear and dynamic relationships inherent in maize production and consumption. Through a rigorous research methodology, this study presents a comprehensive system dynamics model that depicts the current state and dynamics of maize supply. The key findings shed light on the factors influencing maize availability in East Java and provide insights for policymakers to enhance food security. By utilizing a systems approach, this research contributes to the understanding of maize supply dynamics and supports the development of strategies to ensure sufficient food supply in the region. [ABSTRACT FROM AUTHOR]

The article describes the method of synthesis of the simulation model of pulse converters with the control system, intended for implementation in FPGA. The technique is based on the structural representation of integro-differential and algebraic equations and the method of switching breaking functions. The models you develop allow you to bring modeling time closer to real. The method is described by an example of a solar battery energy conversion channel of an automatic spacecraft power supply system. The paper considers the possibility of implementing a solar-hydrogen energy supply scheme. This concept involves the accumulation of excess energy in the form of chemical energy on board the spacecraft. [ABSTRACT FROM AUTHOR]

• Simulations models for ACS normal and faulty states were developed. • Trained fault diagnosis model achieved a validation accuracy of 99.00%. • A data set of about 50,000 entries can be used to train a satisfactory model. • A reduced proportion of normal state data improves the model sensitivity. In the present study, performance simulation models and diagnosis method of faulty states in air-cycle refrigeration systems in civil aircrafts are developed, and the effects of the training data set on the diagnosis accuracy were analyzed. A base model for normal state simulation of air-cycle refrigeration system (ACS) was established based on the existing method with several modifications to improve accuracy and performance. Dedicated models for faulty states were developed according to the causes of fault. Based on the established models, a data set was generated. Preliminary training of multiple two-layer neural network models is performed with the existing data set, and the trained model achieved a validation accuracy of 99.00 % which confirms the feasibility of using double-layer neural network for fault identification and classification based on simulation data. The effects of the training data set to the model are analyzed, and it was concluded that: a data set of about 50,000 entries can be used to train a satisfactory diagnostic model; the proportion of normal state data needs to be reduced appropriately to improve the sensitivity of the model to faulty states; it is possible to largely reduce the number of sensors with smaller effect to the diagnosis accuracy. [ABSTRACT FROM AUTHOR]

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Orbital compartment syndrome is a potentially blinding eye condition. Timely diagnosis and treatment are paramount to optimize visual outcomes. Lateral canthotomy and cantholysis is the definitive management and a required competency for emergency physicians and ophthalmologists. Lack of confidence in the procedure can result in delayed treatment and poor outcomes. Our aim was to create a low-cost, realistic, simulation model to ensure trainees were confident in performing lateral canthotomy and cantholysis. A model was created using equipment found in the emergency department. This model's efficacy was assessed using pre- and post-teaching questionnaires measuring learner's self-perceived confidence. Forty-seven emergency medicine and 18 ophthalmology registrars rated their confidence in the procedure using a 5-point Likert scale (1 = not very confident, 5 = extremely confident); 42% (n = 27) of participants felt 'quite confident' (4 on Likert scale) in carrying out the procedure unsupervised out of hours after the teaching session, compared with 9.23% (n = 6) before (p < 0.01). Our model resulted in significant increases in all three measures of confidence (diagnosing orbital compartment syndrome, locating the necessary equipment and performing canthotomy and cantholysis) and was rated as 4.35 (1 = not at all helpful, 5 = extremely helpful) in understanding the anatomy of the region. Sixty-six percent (n = 43) of participants stated they would like further simulation teaching. Our model is low cost, easy to assemble, and anatomically correct. The user can 'strum' the inferior canthal tendon without cutting the lower lid, appreciating the difference between canthotomy and cantholysis. Use of this model significantly increased the number of learners who felt "quite confident" with performing the procedure. Use of this model should be considered for trainees in ophthalmology and emergency medicine. [ABSTRACT FROM AUTHOR]

This work presents a decision-support system for predictive analysis of truck arrivals, dwell times and possible congestion situations in seaport, through a methodology that encompasses machine learning algorithms, data visualization tools and discrete-event simulation models. This decision-support system makes it possible to have a detailed planning of the arrival and transit times of trucks in the port to predict land congestion events; and to know in advance the needs in relation to services or stopovers, and how long each truck will be in the port facilities. The system also allows for the planning and sizing of waiting areas according to expected arrivals and dwell times of trucks in port, at the same time that it optimizes port value spaces, and reduces unnecessary journeys and associated emissions, by evaluating the relationship between the sea side and the demand in land accesses. This will eventually help to improve coexistence and port-city integration between urban and heavy traffic. The system has been validated in the Port of Santander (Spain) with satisfactory results in terms of operational improvement. [ABSTRACT FROM AUTHOR]

Kanban systems are still the most popular method for pull control of material replenishment. In the Industry 4.0 era, the so-called eKanban represents a digital version of the classic Kanban. Thereby, in some eKanban variants, capturing actual stock-level by digital sensors would help or helps already to reduce capturing time and human failures. Currently, such digital sensors are not really beneficial because they are wired and expensive to install. In this paper, we investigate the potential of battery-powered stock-level sensors for eKanban systems using a simulation study. Battery- powered stock-level sensors are easier to install and, therefore, more beneficial than wired sensors if the battery´s lifetime is long enough. Because of the limited energy, it makes sense to trigger such sensor systems dynamically depending on the actual and predicted stock levels and on order points for minimum stock. For example, the sensor systems usually sleep and capture the stock-level only in a fixed interval for example every hour. Besides fixed intervals, it can be useful to trigger such sensors dynamically by reducing the activations in time with no or few material take-outs. To identify the best trigger strategy, this paper investigates how artificial intelligence (AI) methods, in this case, reinforcement learning, can be deployed. Thereby, the used material flow simulation maps the application scenario of a four-stage assembly line and compares the AI-based trigger with a manually operated demand notification. In this way, it can be shown that battery lifetime is increased fourteen times more compared to the manually operated demand notification, and battery runtimes of several months can be achieved by AI-based optimization of the sensor energy consumption. This approach leads to an eKanban solution becoming more economical, and thus smaller companies can also consider digitizing their material flow control [ABSTRACT FROM AUTHOR]

Dental pulp regeneration exploits tissue engineering concepts using stem cells/scaffolds/growth-factors. Extracted collagen is commonly used as a biomaterial-scaffold due to its biocompatibility/biodegradability and mimics the natural extracellular matrix. Adding biomolecules into a collagen-scaffold enhanced pulp regeneration. Acemannan, β-(1-4)-acetylated-polymannose, is a polysaccharide extracted from aloe vera. Acemannan is a regenerative biomaterial. Therefore, acemannan could be a biomolecule in a collagen-scaffold. Here, acemannan and native collagen were obtained and characterized. The AceCol-scaffold's physical properties were investigated using FTIR, SEM, contact angle, swelling, pore size, porosity, compressive modulus, and degradation assays. The AceCol-scaffold's biocompatibility, growth factor secretion, osteogenic protein expression, and calcification were evaluated in vitro. The AceCol-scaffolds demonstrated higher hydrophilicity, swelling, porosity, and larger pore size than the collagen scaffolds (p < 0.05). Better cell-cell and cell-scaffold adhesion, and dentin extracellular matrix protein (BSP/OPN/DSPP) expression were observed in the AceCol-scaffold, however, DSPP expression was not detected in the collagen group. Significantly increased cellular proliferation, VEGF and BMP2 expression, and mineralization were detected in the AceCol-scaffold compared with the collagen-scaffold (p < 0.05). Computer simulation revealed that acemannan's 3D structure changes to bind with collagen. In conclusion, the AceCol-scaffold synergistically provides better physical and biological properties than collagen. The AceCol-scaffold is a promising material for tissue regeneration. [ABSTRACT FROM AUTHOR]

• This is a comprehensive oversight on the availability and validation of simulation models in the field of pediatric surgery. • The number of validated simulation models for pediatric surgery procedures is growing, however, few are available. • This indicates a need for more efforts to develop adequate simulation models and make these available for widespread use. Introduction: This review evaluates the validation and availability of simulation models in the field of pediatric surgery that can be used for training purposes. MEDLINE and EMBASE were searched for studies describing a simulation models in pediatric surgery. Articles were included if face, content and/or construct validity was described. Additionally, the costs and availability were assessed. Validation scores for each model were depicted as percentage (0–100), based on the reported data, to compare the outcomes. A score of >70% was considered adequate. Forty-three studies were identified, describing the validation process of 38 simulation models. Face validity was evaluated in 33 articles, content in 36 and construct in 19. Twenty-two models received adequate validation scores (>70%). The majority (27/38, 70%) was strictly inanimate. Five models were available for purchase and eleven models were replicable based on the article. The number of validated inanimate simulation models for pediatric surgery procedures is growing, however, few are replicable or available for widespread training purposes. Level of evidence: Level II. [ABSTRACT FROM AUTHOR]

This study sought to corroborate microwave remote sensing and simulation models to efficiently delineate groundnut cultivation area and to estimate the yield by integration. Near real-time information on crop acreage and yield estimation is essential for making policy decisions. S1A SAR data were downloaded for entire crop growth period of groundnut during Kharif monsoon seasons (June – October) of 2019 and 2020 and were processed using MAPSCAPE RIICE software to extract groundnut cultivated area in the study districts of Tamil Nadu. Spectral dB curve groundnut generated using multi-date Sentinel 1 A SAR data showed a minimum at sowing, reached a peak at the pod development stage and decreased after that towards maturity. Groundnut area map was generated with a classification accuracy of 85.2 and 84.8 per cent with a kappa coefficient of 0.70, and total groundnut area of 104343 and 116199 ha was mapped during Kharif monsoon season 2019 and 2020, respectively. The mean agreement of 75.01 and 84.94 per cent was observed between DSSAT model simulated LAI and observed LAI at thirty monitoring locations in the study area during Kharif monsoon season 2019 and 2020, respectively, whereas agreement for yield was 82.11 and 83.70 per cent with RMSE of less than 20 per cent. Spatial distribution of groundnut LAI and yield was estimated by assimilating dB from satellite image and from DSSAT model, respectively. The estimated mean spatial LAI was 2.81 and 3.52, whereas mean spatial pod yield was 2124 and 2195 Kg ha−1 during Kharif monsoon season 2019 and 2020, respectively with RMSE of less than 20 per cent and R2 for integrating satellite products and simulation model for spatial estimates during both the year was >0.70, it shows the fitness of products towards increased accuracy of estimation. [Display omitted] • Accurate and instantaneous information on acreage and yield is essential for policy-making, crop insurance, and sustainable management. Due to estimation accuracy, the multi-date Sentinel 1 A Synthetic Aperture Radar data estimates groundnut area and maximum leaf area derived from backscattering which can be integrated into DSSAT CROPGRO Peanut model for generating yields at a spatial scale well before harvest of crop for quick decision making. [ABSTRACT FROM AUTHOR]

Numerous experimental data indicate that higher viscosity solutions make it easier to obtain coarser fibers. However, the influences of viscosity on the whipping behavior of the jet and their subsequent impacts on the formation of terminal fiber during electrospinning remain topics of ongoing research. Simulation model and experiment presented in this study aim to solve these problems. The simulation model alters the dimensionless parameter F ve to predict the impacts of different viscosities on the bending behavior of the electrospun jet, while the experiment observes this behavior under different viscosities by regulating the solution concentration. The consistency of the simulation and experimental data implies the accuracy of the conclusions in this paper. Furthermore, the simulation model and experiment have demonstrated that a higher viscosity jet results in a smaller radius of the jet trajectory and lower jet velocity, which in turn leads to the formation of coarser fiber. [Display omitted] • A research strategy of simulation model and experiment. • A dimensionless parameter is utilized to predict the impacts of different viscosities on bending behavior in simulation process. • Jet trajectory and jet velocity are used to characterize the bending behavior of the electrospun jet. • A smaller radius of the jet trajectory and lower jet velocity produce coarser electrospun fibers. [ABSTRACT FROM AUTHOR]

• Compensatory growth in both pasture and feedlot finishing increased profitability. • Feedlot finishing reduced greenhouse gas emissions per unit of beef produced. • The forage-only farm systems were net producers of human-edible energy and protein. This study evaluates nutritional and management strategies aimed at exploiting compensatory growth (CG) in weanling-to-beef systems in Uruguay. The evaluation encompassed productivity, economic viability, and environmental impact. The Grange Beef System Model, augmented with Uruguayan national technical coefficients, was used. Four weanling-to-beef systems were modeled: 1) forage only with no CG (FNC), 2) forage only with management improvements to exploit CG (forage with CG; FWC), 3) forage with concentrate supplementation during two winter feeding periods (forage with supplementation; FWS), and 4) forage with supplementation during the first winter followed by feedlot finishing (forage with feedlot; FWF). The systems purchased spring-born Angus calves at 8 months of age and 180 kg live weight (LW) and finished with a slaughter weight of 550 kg. FWS system was used as reference with the performance parameters obtained during 5 years of systems experimentation. FNC used the performance parameters of FWS but during winter periods, LW gain was lower due to the absence of concentrate supplementation. FWC used the previous FNC performance parameters, but increased LW gain after the first and second winter restriction period due to improved grazing management practices thereby exploiting CG. FWF is based on the FWS system but instead of moderate supplementation during the second winter (concentrate: 3.0 kg/d/head), steers are feedlot finished (concentrate: 9.5 kg/d/head) exploiting CG due to previous summer-autumn restriction period. FNC and FWC increased age at slaughter, reducing net beef production by 21 and 11 % relative to FWS, respectively. In contrast, FWF reduced age at slaughter, increasing beef production by 93 % compared to FWS. FWS and FNC had similar profitability expressed in net margin; however, FWC and FWF increased net margin by 33 and 107 % compared to the FWS, respectively. FNC and FWC increased greenhouse gas (GHG) emissions intensity per beef produced by 17 and 3 % relative to FWS, respectively; meanwhile, FWF reduced GHG intensity by 10 % relative to FWS. Due to the inclusion of concentrates in the diet for FWS and FWF systems, the only net producers of human edible energy and protein were the forage-only systems (FNC and FWC). In summary, strategically harnessing CG in both pasture and feedlot finishing stages within a weanling-to-beef system in Uruguay successfully increased profitability. Feedlot finishing reduced GHG emissions per beef produced. However, the forage-only farm systems emerged as the only net producers of human-edible energy and protein. [ABSTRACT FROM AUTHOR]

Solar absorption refrigeration cycle consumes almost no electricity, but its low refrigeration efficiency and intermittent operation issues need addressing. Based on the viewpoint of cold energy grade production matching air-conditioning cooling load grade, a solar absorption refrigeration cycle integrated with a dual-cooling grade-compression cycle (SARC-DGC) is proposed to boost the solar utilization and achieve all-weather cooling, which includes solar absorption refrigeration (SAR) subsystem, subcooled water circulating (SWC) subsystem and dual-cooling grade-compression refrigeration (DGR) subsystem. The simulation models of proposed cycle are developed by lumped-parameter and distributed-parameter methods, and the simulation results are validated with experimental results. The hourly characteristics of SARC-DGC cycle on a typical day are evaluated and compared with those of the conventional solar absorption refrigeration (SAR) cycle and air-cooled compression refrigeration (ACR) cycle. The results show that the hourly cooling performance of SARC-DGC cycle is well matched with the building cooling load demand, so as to realize the cold energy grade production and utilization. The working hours of SAR subsystem are 42.86 % longer than that of conventional SAR cycle, with a 31.92 % increase in daily cooling capacity, while the daily power consumption of the proposed cycle is on average 27.31 % lower than that of conventional ACR cycle. • Solar refrigeration absorption cycle with grade-compression cycle is proposed. • Simulation models for performance of proposed cycle are developed and validated. • Hourly cooling performance of the cycle is well matched with cooling load demand. • Performances of novel cycle are superior to absorption or compression cycle. [ABSTRACT FROM AUTHOR]

This article presents a study of implantable blood pressure sensors based on a probe made up of four piezoresistors. An original method combining both measurements and calculations allows extracting the values of each piezoresistor without degrading the probe is developed. This study made it possible to create a simulation model in Cadence/Pspice electronic simulation software, considering the variation of the piezoresistor according to the temperature and the pressure. To our knowledge, no simulation model considering both the variation of the temperature and the pressure of each piezoresistor exists in the literature. So, the simulation of the sensor allows to quickly test the efficiency of the compensation circuit before its realization. Once the thermal drifts of the sensor have been quantified, a circuit based on PNP transistors is developed to compensate this thermal drift. This analog compensation technique ensures low cost, compactness and low power consumption. It proved experimentally effective in reducing thermal drift of the sensor. For example, the experimental thermal drift of the sensor is reduced from 9.97 mmHg/°C without compensation to 2.12 mmHg/°C after compensation at the pressure of 300 mmHg. This method has been validated with 3 pressure levels (0, 100, 200 and 300 mmHg). [Display omitted] • Drift thermal quantification of implantable blood pressure sensors based on a probe made up of four piezoresistors. • Development of an original method combining both measurement and calculation allows extracting the values of each resistor. • Development of simulation model of the sensor depending on the variation of temperature and pressure. • Real compensation of the drift thermal (9.97 mmHg/°C without compensation and 2.12 mmHg/°C after compensation at 300 mmHg). • Method has been validated by measurement and simulation with 3 pressure levels (0, 100, 200 and 300 mmHg) from 34°C to 39°C. [ABSTRACT FROM AUTHOR]

Acquiring actual data for developing data-based prediction models for the optimization of control setpoints (hereinafter referred to as optimal control (OC)) in heating, ventilation, and air conditioning (HVAC) systems is challenging, especially when changing control setpoints while considering all possible boundary conditions. Thus, considering the scalability of OC, it is a promising solution to generate sufficient learning data according to the control settings using a highly accurate simulation model, build a source model, and expand the learning model based on the actual data of the target system. This is the first study to improve the scalability of OC aiming to develop a deep neural network (DNN) model to predict the power consumption of a heat source system. First, this study will construct a calibrated heat source system simulation model and then use the generated learning data to train a DNN model. The actual operation conditions of the target building and heating system located in Vietnam were analyzed using operation data. A physics-based simulation model of the target heat source system was developed and calibrated using actual operation data to improve accuracy. By using the calibrated simulation, sufficient learning data was generated for all control settings allowing for the development of a learning model based on DNN that predicted the power consumption of the heat source system. In addition, a highly accurate prediction model through hyperparameter optimization was secured. [ABSTRACT FROM AUTHOR]

Integrating circular economy into vertical farming holds promises to transform the current economic landscape and bolster environmental sustainability. However, knowledge gaps persist regarding the efficiency of vertical farming methods within the circular economy context, particularly in the development of a simulation model aimed at resource optimization and waste reduction. This study aimed to analyze the vertical farming methods in the circular economy framework and introduce a zero-waste circular economy model both experimentally and through simulation. In the study, a circular economy model was proposed and implemented, utilizing waste generated from hydroponics and aquaponics, alongside vermicompost tea and aerobic compost tea/quick compost, as nutrients for six distinct halophyte plants in the secondary farming setup. The model serves as a valuable tool for identifying and assessing critical factors influencing the circular economy principle, as well as for optimizing resource allocation and management. Over six weeks, plant growth was monitored and compared across the vertical farming methods. Results show that both hydroponic and aquaponic waste proved superior growth compared to the alternatives, highlighting vertical farming's potential for the circular economy. Using the results from the experimental observation, a simulation model was developed. The simulation model's accuracy was validated by comparing outcomes with actual data. Furthermore, the model was used to optimize for balancing resources and capacities in each stage of vertical farming. The vertical farming circular economy model proposed in this study can serve as a blueprint for agriculturalists and decision-makers to adopt more sustainable and efficient farming practices that not only reduce waste but also generate profits. • Circular economy integration into vertical farming. • Introduction of a zero-waste circular economy model. • Vertical farming analysis through the circular economy simulation model. [ABSTRACT FROM AUTHOR]

• A software application was developed to simulate sprinkler water distribution on undulating hilly terrain. • A water application rate conversion from flat to hilly terrain was deduced by the principle of water volume conservation. • An indoor experimental platform was set up to replicate the sprinkler arrangement on a hill, devoid of plant canopy. The hilly terrain modifies the droplet landing positions in comparison to flat ground, complicating the prediction of sprinkler water distribution on such uneven regions. Utilizing a digital elevation model combined with droplet dynamics and evaporation models, droplet landing positions were calculated on both flat and uneven terrains. From the droplet landing positions and the corresponding water application rates on flat terrain, the water application rate on hilly terrains was deduced using the principle of water volume conservation. Subsequently, a software application was developed to assist in this prediction. Using the radial water distribution data from an individual sprinkler under various operating pressures and the elevation data of a hill, the software predicts the water distribution for either an individual sprinkler or an entire solid-set sprinkler irrigation system on the hill. This allows for the calculation of the average water application rate (h ¯) and distribution uniformity (UCS) for combined sprinklers. The simulated water application rate on hilly terrains was validated using an experimental platform that replicates the sprinkler arrangement on a hill, devoid of plant canopy. Our findings indicate that the simulated water application rate for a sprinkler on hilly terrain aligns closely with the observed values, achieving a confidence coefficient (c) of 0.96. The developed software reliably predicts sprinkler water distribution on hilly terrains with significant accuracy for the conditions studied. We compared the UCS of the flat, hilly slope, and homogeneous slope terrains and found that the hilly slope better reflects the uneven water distribution owing to the undulating characteristics of the hilly terrain. [ABSTRACT FROM AUTHOR]

Japan's compact-city policy addresses rapid population decline and aging to ensure sustainable development. However, its implementation requires significant time, financial resources, and complex stakeholder collaborations. Faced with these challenges, we asked: How can the cost-and-effect of planning be simply and automatically recognized by stakeholders? To address this, a simulation model was developed for evaluating urban planning strategies within the compact-city framework. Our model integrates pseudo-people-flow data and includes three fundamental modules and five sub-models to simulate and predict urban metrics, including population, administrative costs, visitors, and traffic volume from 2015 to 2040. Four scenarios-baseline, location optimization, new road and new station installation-were analyzed. Findings suggest that 1) new station project could mitigate population decline, 2) both location optimization and new station projects improve public services efficiency and sustainability, 3) urban vitality could be enhanced by new station construction, generating a new urban core, and 4) compact city policy may also reduce and concentrate traffic volume, shortening car trips. The model's efficiency and uncertainty were examined, and user experiments highlighted the potential of digital tools to democratize urban planning, making it accessible for non-expert stakeholders and fostering informed participation. This research advances the use of technology in participatory urban planning. • A cost-and-effect simulation model is developed for compact city approaches, integrating multiple modules and sub-models. • The model predicts future administrative cost, population, number of visitors, and traffic volume from 2015 to 2040. • Conducted a comparative analysis of four development scenarios under compact city policy framework in Japan. • Demonstrated the model's computational efficiency, integrating into a web application for participatory urban planning. • Highlighted digital tools' role in urban planning, advocating accessible technology for informed decisions for non-experts. [ABSTRACT FROM AUTHOR]

A novel agar-based phantom was developed and assessed for ultrasonography (USG)-guided brain biopsy training. The phantom provides visual cues combined with sonologic cues, allowing multimodal training. Impact of multimodal training is evaluated through pretraining and posttraining trials. Twenty-five participants were divided based on experience with USG-based procedures into familiar (≥3 procedures performed in the past) (n = 14) and unfamiliar (<3 procedures performed) (n = 11). Agar phantoms with an opaque top and transparent middle layer were constructed in transparent glass bowls, each having 12 embedded targets. Participants underwent 2 supervised trials of USG-guided biopsy with aluminum foil covering the glass bowls, eliminating visual cues. Between 2 trials, participants underwent unsupervised self-training on a phantom without foil cover, providing visual cues. Performance was measured through insonation efficiency (EfI), biopsy efficiency (EfB), efficiency score (Ef), error score (Er), and performance score (PS). Scores were compared between and within the 2 groups before and after training. Impact of the self-training session on subjective comfort levels with the procedure was assessed through feedback forms. Familiars had better pretraining EfB, Ef, Er, and PS (P < 0.001) compared with unfamiliars. After training, both performed similarly on all metrics. After training, familiars improved only in EfI (P = 0.001), with the unfamiliars showing significance in all metrics except EfI. Simulation and phantom-based models can never supplant training through supervised skill application in vivo but our model supplements training by enabling technical skill acquisition, especially for beginners in USG-guided brain biopsy. [ABSTRACT FROM AUTHOR]

Regulatory changes worldwide are requiring air conditioning and heat pump equipment manufacturers to switch refrigerants to alternatives with reduced global warming potential (GWP). Design of air-to-refrigerant fin-and-tube heat exchangers (FTHXs) is critical to overall performance of this equipment and is not currently well understood with low-GWP refrigerants. This paper presents a simulation study exploring the impact of design changes for a FTHX used in an indoor residential evaporator originally designed for R410A. Simulation results are used to generate design guidelines for FTHXs using HFO refrigerants R1234yf and R1234ze(E), evaluated using cooling capacity, refrigerant-side pressure drop and ratio of the two as critical metrics. When evaluated at identical operational conditions, with fixed refrigerant outlet superheat, it was found that for a fixed slab size, the FTHX was most sensitive to number of circuits, followed by tube diameter, number of tubes in the FTHX, and fin density. For the low-GWP HFOs, circuitry modifications led to maximum increase in FTHX capacity of 20%, and maximum decrease in refrigerant-side pressure drop of 88.6%. Based on simulation results, it is concluded that additional coil face area is required to match both capacity and refrigerant pressure drop, compared with R410A, this is demonstrated with two proposed FTHX designs. One design prioritizes increased FTHX capacity, and the other a reduction in refrigerant pressure drop. All these results culminated in design guidelines for HFOs that suggest it will be challenging to achieve both the same capacity and pressure drop characteristics as R410A without modifications to FTHX size. [ABSTRACT FROM AUTHOR]

To meet industry's expectations for manufacturing ceramic parts by stereolithography, a better comprehension of the process, in particular laser scattering through the ceramic slurry is mandatory. This knowledge makes it possible to define adapted printing conditions to control the dimensions, homogeneity of the conversion and mechanical properties of the green parts, in order to achieve better resolutions and optimize the properties of sintered parts. This approach is focused on the development of a 3D polymerization modeling for stereolithography process able to predict curing and associated thermal phenomena. First, a design of experiments is carried out to identify material-dependent parameters, calibrate and validate the model, then able to predict monomer conversion rates and dimensions after curing depending on manufacturing parameters. Finally, temperature variation and exposure homogeneity have been evaluated. These results will allow, in future studies, to interpret the differences of deformations and mechanical properties of green parts. [ABSTRACT FROM AUTHOR]

• Experimental and simulative investigation of a high-temperature heat pump up to 160°C • Utilization of R600 (n-Butane) in sub-critical and trans-critical operation • COP of 3.1 for 160°C supply temperature and 60°C heat source inlet temperature • The influence of operating parameters on the optimum high pressure is depicted • Increased suction gas superheat in the internal heat exchanger improves the COP Process heat supply by high-temperature heat pumps exploiting waste heat is an effective method for enabling the decarbonisation of industrial processes. Key aspects for the application of this technology are the supply temperature levels and efficiencies that can be achieved. This work investigates an R600 (n-butane) high-temperature vapour compression heat pump (HTHP) capable of utilizing waste heat at temperature levels between 40 and 60°C and lifting it to supply temperatures between 110°C in sub-critical and 160°C in trans-critical operation. The HTHP prototype is designed as a single-stage cycle, comprising an inverter-driven suction-gas-cooled reciprocating compressor, low-pressure accumulator and internal heat exchanger (IHX) for suction gas superheating. The influence of the operating parameters high pressure and suction gas superheat ("internal parameters") plus the heat source temperature, the heat sink inlet and outlet temperatures and the compressor speed ("external parameters") on the COP and heating capacity are studied using data from both the prototype and the simulation model. The optimum high pressure depends on the operating conditions, an increase of suction gas superheat increases the COP. In sub-critical operation, a heating capacity of 30.7 kW at a COP of 4.4 is reached at a source inlet temperature of 60°C heating the sink from 80 to 110°C. Trans-critical operation enables a heat sink outlet temperature of 160°C, offering a heating capacity of 24.2 kW at a COP of 3.1. [ABSTRACT FROM AUTHOR]

Constructing simulation models can be a complex and time-consuming task, in particular if the models are constructed from scratch or if a general-purpose simulation modeling tool is used. In this paper, we propose a model construction framework, which aims to simplify the process of constructing discrete event simulation models for emergency medical service (EMS) policy analysis. The main building blocks used in the framework are a set of general activities that can be used to represent different EMS care chains modeled as flowcharts. The framework allows to build models only by specifying input data, including demographic and statistical data, and providing a care chain of activities and decisions. In a case study, we evaluated the framework by using it to construct a model for the simulation of the EMS activities related to acute stroke. Our evaluation shows that the predefined activities included in the framework are sufficient to build a simulation model for the rather complex case of acute stroke. [ABSTRACT FROM AUTHOR]

Model-, Software-, and Hardware-in-the-Loop simulations are used in the Virtual Commissioning of machines and plants to reduce costly control errors early in the engineering process. Each simulation type represents a different grade of detail. As a result, the underlying models change on every transition between the three types. Regarding the model structure there is no solution to enable a continuous and effortless transition. This work proposes a model extension concept which allows cycling all X-in-the-Loop configurations during Virtual Commissioning. The extension includes abundant submodules describing every component transformation required to switch to a specific simulation configuration. [ABSTRACT FROM AUTHOR]

In this work, a numerical simulation model was developed to investigate the complex heat and mass transfer process inside the molten pool during plasma surfacing. The temperature distribution and fluid flow were employed to depict the evolution of the molten pool. The findings revealed that the maximum temperature is located on the surface of the cladding layer corresponding to the position of heat source, and the temperature distribution follows a Gaussian distribution along the scanning direction. Thermal accumulation is obvious due to the continuous energy input in the initial stage, as a result, the maximum temperature and fluid flow velocity gradually increase with the deposition process. The maximum temperature and fluid flow velocity at 4.0 s are 1893 K and 0.281 m/s in case 110 A, respectively. The predicted shapes and dimensions are consistent with the results of the deposition experiments, with a maximum error of no more than 15 %. In order to investigate the impact of WC particles on the solidification microstructure of nickel composite layers, corresponding plasma surfacing experiment was implemented. The solidification characteristics of the microstructure follow planar-cellular-columnar-equiaxed crystals in the bonding layer and WC particles-columnar-equiaxed dendritic crystals in hard layer, respectively. Furthermore, the Ni dendritic near the retained WC particles transformed into columnar crystals due to temperature gradient in the local area. • Solidification behavior of WC reinforced nickel cladding layers is investigated. • Simulation model is used to analyze the temperature/flow field, G and R values. • G/R ratio demonstrate a decreasing trend from the bottom to top of the coating. • Gradient G/R ratio corresponds to planar-cellular-columnar-equiaxed crystal growth. • WC doping changes the growth model resulting in local columnar crystal growth. [ABSTRACT FROM AUTHOR]

This study introduces the proposed deterministic methodology for calculating the roughness parameters involved in the Greenwood-Tripp equation for asperity contact pressure. A robust methodology that takes into consideration the maximum possible peak morphology and establishes more stringent calculation conditions is proposed. The stability of the proposed method is examined on various samples taken from different engine components using an optical interferometer. The roughness parameters obtained from different methodologies and using different optical interferometer resolutions are compared, and then, these parameters are introduced into simulation model that employs the Greenwood-Tripp equation. The results demonstrate the sensitivity of the simulation model to the roughness parameters used. [Display omitted] • A novel method for calculating the roughness parameters for the Greenwood-Tripp model. • The proposed method employs a more detailed peak morphology and stricter conditions. • Comparison of the robustness of the proposed method with those of previous methods. • Virtual test rig simulation for friction torque and maximum asperity contact pressure. • High sensitivity of the simulation results to different roughness parameters. [ABSTRACT FROM AUTHOR]

Injection-equipment-sharing networks play an important role in hepatitis C virus (HCV) transmission among people who inject drugs (PWID). Direct-acting antiviral (DAA) treatments for HCV infection and interventions to prevent HCV transmission are critical components of an overall hepatitis C elimination strategy, but how they contribute to the elimination outcomes in different PWID network settings are unclear. We developed an agent-based network model of HCV transmission through the sharing of injection equipment among PWID and parameterized and calibrated the model with rural PWID data in the United States. We modeled curative and preventive interventions at annual coverage levels of 12.5 %, 25 %, or 37.5 % (cumulative percentage of eligible individuals engaged), and two allocation approaches: random vs targeting PWID with more injection partners (hereafter 'degree-based'). We compared the impact of these intervention strategies on prevalence and incidence of HCV infections. We conducted sensitivity analysis on key parameters governing the effects of curative and preventive interventions and PWID network characteristics. Combining curative and preventive interventions at 37.5 % annual coverage with degree-based allocation decreased prevalence and incidence of HCV infection by 67 % and 70 % over two years, respectively. Curative interventions decreased prevalence by six to 12 times more than preventive interventions, while curative and preventive interventions had comparable effectiveness on reducing incidence. Intervention impact increased with coverage almost linearly across all intervention strategies, and degree-based allocation was always more effective than random allocation, especially for preventive interventions. Results were sensitive to parameter values defining intervention effects and network mean degree. DAA treatments are effective in reducing both prevalence and incidence of HCV infection in PWID, but preventive interventions play a significant role in reducing incidence when intervention coverage is low. Increasing coverage, including efforts in reaching individuals with the most injection partners, preventing reinfection, and improving compliance and retention in preventive services can substantially improve the outcomes. PWID network characteristics should be considered when designing hepatitis C elimination programs. [ABSTRACT FROM AUTHOR]

A Non-Fungible Token (NFT) is a digital asset that is proof of ownership and originality in the digital world. It is generally a unique data unit that can be created from a digital file. But it is not just any digital file; it must be audio, video, image, or photo. This fact is mainly limiting. However, there are many other digital files for which the connection with NFT and blockchain technology would make sense. Such digital files include, among other things, various simulation models. With the development of the use of simulation models for the needs of managing multiple types of logistics processes daily, the questions of how to prevent the unauthorised copying of any simulation model and protect the copyright of its authors are coming to the fore. NFT and blockchain represent a robust technology whose possibilities of use are gradually expanding, while simulation models could be one area of their application. The paper presents the result of research that will enable the implementation of NFT and blockchain technology in simulation models. The research outcome confirmed the possibility of creating an NFT through the decentralised public blockchain XRP Ledger (XRPL) and the marketplace xrp. cafe, which can be used to verify the ownership and originality of the simulation model. [ABSTRACT FROM AUTHOR]

• A systematic 3-D magnetic particle imaging simulation model is proposed. • The simulation model features a more comprehensive MPI system parameters setting. • The credibility of our model is evaluated by using real measurement data. • An open-source simulation software based on our simulation model is developed. Magnetic particle imaging (MPI) is an emerging imaging technology in medical tomography that utilizes the nonlinear magnetization response of superparamagnetic iron oxide (SPIO) particles to determine the in vivo spatial distribution of nanoparticle contrast agents. The reconstruction image quality of MPI is determined by the characteristics of magnetic particles, the setting of the MPI scanner parameters, and the hardware interference of MPI systems. We explore a feasible method to systematically and quickly analyze the impact of these factors on MPI reconstruction image quality. We propose a systematic 3-D MPI simulation model. The MPI simulation model has the capability of quickly producing the simulated reconstruction images of a scanned phantom, and quantitative analysis of MPI reconstruction image quality can be achieved by comparing the differences between the input image and output image. These factors are mainly classified as imaging parameters and interference parameters in our model. In order to reduce the computational time of the simulation model, we introduce GPU parallel programming to accelerate the processing of large complex matrix data. For ease of use, we also construct a reliable, high-performance, and open-source 3-D MPI simulation software tool based on our model. The efficiency of our model is evaluated by using OpenMPIData. To demonstrate the capabilities of our model, we conduct simulation experiments using parameters consistent with a real MPI scanner for improving MPI image quality. The experimental results show that our simulation model can systematically and quickly evaluate the impact of imaging parameters and interference parameters on MPI reconstruction image quality. We developed an easy-to-use and open-source 3-D MPI simulation software tool based on our simulation model incorporating all the stages of MPI formation, from signal acquisition to image reconstruction. In the future, our simulation model has potential guiding significance to practical MPI images. [ABSTRACT FROM AUTHOR]

Understanding the expansion mechanism of polyurethane polymer grout can supply guidance for accurate grouting. However, most of the polymer grout expansion calculations were defined simplistically by the polymer density-expansion pressure empirical relationship expression, which failed to meet the time history of the expansion pressure during the polymer reaction process. The objective of this paper was to investigate the expansion mechanism of polyurethane foam in various constraint conditions during the whole polymer reaction process. A model describing the expansion mechanism of polyurethane foam was established based on the energy conservation principle, the chemical reaction kinetic equation solved by the Runge-Kutta method, and the ideal gas state equation. The model was proved applicable compared to the experiments under fixed volume and fixed confining pressure boundaries. In addition, the effects of grouting quantity, confining pressure, initial temperature, and physical foaming agent content on the grout expansion pressure, density, and components conversions were discussed. The results showed that the expansion pressure of polymer grout gradually increased with time under the fixed volume conditions, and the grout expansion pressure increased as the density increased. The final grout expansion pressure will increase with the increase of initial temperature or the content of physical blowing agent. Under the fixed confining pressure condition, the polymer grout density gradually decreased with time, the grout density increased as the confining pressure increased while the conversions of the two components alcohol and isocyanate increased. The final density decreases with the increase of initial temperature or the content of physical blowing agent. [Display omitted] • Established a model describing the expansion mechanism of polyurethane foam. • Confirmed the model's applicability through experiments under fixed volume and pressure conditions. • Revealed the laws of grout expansion pressure, temperature, density, and component conversion. • Studied the effects of grouting quantity, confining pressure, initial temperature, and foaming agent content on expansion. [ABSTRACT FROM AUTHOR]

The continuous-flow pasteurization apparatus was presented, and the electric field within orange juice was produced via an oscillating magnetic field at 50 kHz, causing the volumetric heating of the juice with initial conductivity of 6.85 mS/cm and 8.76 mS/cm. The process principle, especially numerical relationships between excitation voltage, magnetic field, induced electric field (IEF), induced current density, and temperature profile were elaborated. When applying a rectangular wave of the voltage at 50–1000 V, the waveforms of the magnetic field and IEF in the juice were sine-like and sawtooth waves, respectively. Through electromagnetic simulation, the model was established, which indicated the indirect heating of orange juice via oscillating magnetic field was feasible. As the magnetic field increased, the outlet temperature and induced current density in the juice was improved. Notably, the 4–5 logs CFU/ml inactivation effects on aerobic bacteria, yeast and mold in orange juice could be achieved at 65 °C for 60 s after the treatment. • Engineering characteristics of induced electric field technology was elaborated. • Electromagnetic simulation model was conduced to verify its thermal effect. • Waveform of magnetic field and induced electric field was investigated. • Difference between experimental and predicted temperature was not significant. • Inactivation effects on aerobic bacteria, yeast and mold was achieved. [ABSTRACT FROM AUTHOR]

Avian eggshells exhibit excellent antimicrobial properties. In this study, we conducted simulation experiments to explore the defense mechanisms of eggshell membranes with regards to their physical features. We developed a mathematical model for the movement of microorganisms and estimated their penetration ratio into eggshell membranes based on several factors, including membrane thickness, microbial size, directional drift, and attachment probability to membrane fibers. These results not only suggest that an eggshell membrane with multiple layers and low porosity indicates high antimicrobial performance, but also imply that the fibrous network structure of the membrane might contribute to effective defense. Our simulation results aligned with experimental findings, specifically in measuring the penetration time of Escherichia coli through the eggshell membrane. We briefly discuss the significance and limitations of this pilot study, as well as the potential for these results, to serve as a foundation for the development of antimicrobial materials. [ABSTRACT FROM AUTHOR]

The aims of this research were (1) to develop a model to simulate a herd of cows and quarter milk flowrates for a milking and derive quarter and udder milking durations and box duration (i.e., the time a cow spends inside the robot) for a group of cows milked with an automatic milking system (AMS); (2) to validate the simulation by comparing the model outcomes with empirical data from a commercial AMS dairy farm; and (3) to apply teatcup removal settings to the simulation to predict their effect on quarter and cow milking duration and box duration in an AMS. For model development, a data set from an AMS farm with 32 robots milking over 1,500 cows was used to fit the parameters to the variables days in milk, parity, and milking interval, which were subsequently used to create a herd of cows. A second data set from 2019 from an AMS farm with 1 robot milking 60 cows that contained quarter milk flowrates (at 2-s intervals) was used to extract the parameters necessary to simulate quarter milk flowrates for a milking. We simulated a herd of cows, and each was assigned a parity, days in milk, milking interval, and milk production rate. We also simulated milk flowrates every 1 s for each quarter of each cow. We estimated quarter milking duration as the total time that flowrate was greater than 0.1 kg/min after a minimum of 1 min of milk flow. We incorporated a randomly sampled attachment time for each quarter and calculated cow milking duration as the time from the first quarter attached to the last quarter detached. We included a randomly sampled preparation time which, added to cow milking duration, represented box duration. For simulation application, we tested the effect of quarter teatcup removal settings on quarter and cow milking duration. The settings were based on absolute flowrate (0.2, 0.4, and 0.6 kg/min) or a percentage of the quarter's 30-s rolling average milk flowrate (20, 30, and 50%). We simulated over 84,000 quarter milkings and found that quarter milking duration (average 212 s) had a mean absolute percent error (MAPE) of 7.5% when compared with actual data. Simulated cow milking duration (average 415 s) had a MAPE of 8%, and box duration (average 510 s) had a MAPE of 12%. From simulation application, we determined that quarter milking duration and box duration were reduced by 19% (209 vs. 170 s) and 6.5% (512 vs. 479 s), respectively, when increasing the teatcup removal flowrate from 0.2 to 0.6 kg/min. Quarter milking duration and box duration were 7% (259 vs. 241 s) and 3% (590 vs. 573 s) longer respectively by using a teatcup removal setting of 20% of the quarter's rolling average milk flowrate, compared with 30%. Both results agree with previous research. This simulation model is useful for predicting quarter and cow milking and box duration in a group of cows and to analyze the effect of milking management practices on milking efficiency. [ABSTRACT FROM AUTHOR]

• The model obtained CO 2 outlet temperature with an absolute mean error of 1.14 K. • The heat transfer rate of fluted tube-in-tube gas cooler was generally higher. • The improvement of maximum COP could be up to 29.41% by using the fluted tube. • The COP improvement could be impaired to 6.30% at water inlet temperature of 40 °C. The utilization of fluted inner tube in tube-in-tube heat exchangers is an effective way to improve the heat transfer performance. Based on the segmented model, the performance of a fluted tube-in-tube gas cooler (FTGC) in the transcritical CO 2 heat pump water heater was studied in this paper. The simulation model was validated and adopted to numerically investigate the effects of different parameters on the heat transfer performance of the gas cooler, which was compared to the smooth tube-in-tube gas cooler (STGC) with the same geometric parameters. The results showed that the FTGC had higher heat transfer capacity in most conditions. The heat transfer rate first increased and then decreased as the CO 2 inlet pressure increased. The temperature difference at the pinch point in the FTGC was lower than that in the STGC. In the FTGC, the pinch point position was mainly influenced by the CO 2 inlet pressure and water inlet and outlet temperatures. Regarding the system COP, the improvement of maximum COP could be up to 29.41% by using the FTGC compared to STGC when the water inlet temperature was 10 °C and the water outlet temperature was 80 °C. However, when the water inlet temperature was 40 °C, the improvement of COP could be impaired to 12.98%. Through changing the designs of the FTGC with the fixed total heat transfer area, when the water inlet and outlet temperatures were 10 °C and 60 °C, the highest maximum COP could be obtained with the design used in the experiments. [ABSTRACT FROM AUTHOR]

In order to further research the dynamic characteristics of liquid air energy storage (LAES) system under typical operating conditions, a dynamic simulation model of energy release process of the 10 MW LAES system is established in this paper. The characteristic curves of expander are considered during modeling and simulation process. The dynamic changes of key parameters, such as temperature, pressure, mass flow rate, and so on, of energy storage system over time under the startup and grid connection are simulated. The sensitivity analyses of rotor speed rising rate and frequency disturbance on the key parameters are carried out. The results show that the outlet temperature and outlet pressure of 1st expander stabilized at 395.96K and 5.37 MPa, respectively, at 602s when the rotor starts up with a rising rate of 360 rpm/min. The actual rotor speed reaches the maximum value of 3010r/min at 504s, the overspeed ratio is 100.3%. During the grid connection, the outlet temperature and outlet pressure of 1st expander stabilized at 345.6K and 3.0 MPa, respectively, at 910s, and the mass flow rate of air rises from 11.25 kg/s of the no-load operation to 23.60 kg/s. In addition, the rotor speed rising rate and frequency disturbance have great influence on the key parameters of expander. The new startup scheme of changing rotor speed rising rate have been put forward to balance the relationship between maximum rotor speed and startup time. The fluctuation amplitudes of outlet temperature, outlet pressure, power and rotor speed increase with the frequency disturbance amplitude increasing. The analysis results of dynamic simulation can provide data reference for learning the dynamic characteristics of LAES system. [ABSTRACT FROM AUTHOR]

[Display omitted] • Sea lampreys attack fish, killing some and leaving marks on others. • Marks observed on survivors may not index actual attack or mortality rates. • To assess survivor bias, we simulated a single season of sea lamprey attacks. • Type A (piercing) marks were informative if lethality was constant. • Type B (non-piercing) marks were informative if pierce rates were constant. Sea lampreys attack fish, killing some and leaving marks on others. Great Lakes fishery managers rely on observed marking rates to assess the success of the sea lamprey control program and estimate sea lamprey-induced mortality of lake trout. Because marking rates are only observed on survivors of sea lamprey attacks, they may not provide a reliable index of actual attack or mortality rates. To investigate the effect of survivor bias, we developed a simulation model representing a single season (June–December) of sea lamprey attacks. Simulated attack rates varied with month and lake trout size; simulated pierce and lethality rates varied with month alone. Surveyed marking rates were represented by simulated survivors in October; true rates were calculated from all simulated lake trout (dead and alive) in December. Simulation results were subsetted to include only those within the range of marking rates actually observed in the Great Lakes. Type A (piercing) marking rates were a good index of the sea lamprey attack rate and the sea lamprey-induced mortality rate if annual lethality rates were relatively constant. Type B (non-piercing) marking rates were a good index of the sea lamprey attack rate and the sea lamprey-induced mortality rate if annual pierce rates were relatively constant. Due to the uncertainty surrounding the pierce and lethality rates, we recommend that sea lamprey abundance information be incorporated in existing lake trout statistical catch-at-age models via a functional response component relating sea lamprey feeding to lake trout abundance, if possible. [ABSTRACT FROM AUTHOR]

Renewable energy has become very prominent these days because of its sustainable and environment-friendly nature. The soil heat storage system plays an important role in the long-term storage of solar energy to ensure a consistent power supply. The experimental analysis and practical implementation of soil heat storage system are very difficult due to its large size and the simulation-based calculation is also very complex for the entire storage system. In order to reduce the system from the perspective of space and time, this paper has applied a similar function relationship for soil heat storage system and develops the traditional CFD simulation model and similar model. According to the dimensions of similar model, the corresponding experimental setup is constructed and the experimental results of long-term heat storage in the soil are compared with the calculation results of a CFD similar model. The relative error of inlet and outlet temperature difference is measured 10% and the error for soil temperature rise is below 1 °C. The proposed method has reduced the simulation and experimental workload for soil heat storage using similarity theory. Hence, the proposed method has great significance in the research domain of soil heat storage and the application of similarity theory. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to optimize the parameters of the technological process of manufacturing parts by embossing in Industry 4.0. A multifunctional queuing system in relation to production was used for the research. We took the example of a production line at the plant, which demonstrates the functionality of the technological process of production and processing of parts by embossing. We achieved the strategic goals of the research due to a complex combination of detailed studies of the parameters of the technological process by modeling. The method is implemented in the FlexSim simulation system with a real set of data. In the process of production of details, it is possible to use the equipment of various quality. Its analysis shows that the effectiveness of even the most modern technological line depends to a greater extent on the performance of its weakest element, unit or part. In particular, in the production of stamping parts the weakest element is a stamp. Research, modeling and calculation of its surfaces, in particular by the method of finite elements make it possible to identify problem areas of the stamp and strengthen them by calculating with using this method. A simulation model of a part of the production process is created and the stages of production are analyzed. We take into account that the implementation of such processes is accompanied by the formation of queues of parts or products that come from the manufacturer for further processing on the conveyor. [ABSTRACT FROM AUTHOR]

In this work, the design and development of a new variable linear power supply, using the LM317 regulator, is proposed. The originality of this power supply is related with the control of the rectifier circuit, which is based on a reference of voltage, superimposed on the output voltage. This reference is used in the control strategy to maintain a constant voltage between the input and the output voltages of the LM317 regulator. Due to this strategy, the heating losses are greatly reduced, allowing to increase the efficiency of the regulator to about 90%, and to reduce the requirements of the cooling system. Moreover, drawbacks of conventional power supplies are mitigated, where the developed variable linear power supply delivers a current of 3 A and a variable output voltage, from 1.2 V to 30 V. The LM317 regulator was modeled by its thermal equivalent structure associated with a heatsink to study the heat transfer problem. The modeling was performed on the Matlab Simulink software, and the theoretical results were validated by a set of experimental tests using the LM317 regulator. [ABSTRACT FROM AUTHOR]

Closing the yield gap of strategic crops can facilitate achieving sustainable solutions to alleviate hunger, ensure food security, and enhance nutrition. This study aimed to quantify factors affecting rice yield gap in northern Iran using experimental and survey data on yields and management practices. The CERES-Rice model, calibrated with data (2011, 2016, 2019) from two regions , was used to estimate potential yield (Y p) of different rice cultivars. Yield gaps were calculated as the difference between economic yield potential and the average yield attained by farmers. The calibration process showed that cultivar coefficients varied across rice varieties. The simulated yields (2012–2021) showed that the mean potential yields were 13362 kg ha−1 and 8818 kg ha−1 for the late and early-maturing cultivars, respectively. High temperature was the most important yield defining factor across the rice growing areas. The yield gap was 3751 kg ha−1 and 2830 kg ha−1 in the late- and early-maturing cultivars, respectively. Nitrogen fertilizer rate, number of fertilizer applications, phosphorus fertilizer rate, transplanting date, potassium fertilizer rate, and seedling age were the top factors influencing the yield gap. Among the management factors, rice fertilizer management explained about 65% of the yield variability. Together, transplanting date and seedling age explained 15.3% of the variability in rice production, while pest, disease, and weed damage accounted for 9.6%. Breaking down the yield gap into affecting factors allows growers to improve the production system by providing the best crop management according to their facilities and capabilities. This approach is essential for optimizing agricultural productivity and achieving sustainable food production goals. • Identifying yield-limiting factors is critical to improving food production. • Rice production can rise by 35–40% through improved crop management. • Effective fertilizer management was key in influencing the yield gap. • Weed damage and rice density had minimal impact on the yield gap. [ABSTRACT FROM AUTHOR]

• Escaped scattered light from multi-blade and V-groove laser dumps was analyzed. • Increasing depth of beam incidence into dump helps to suppress stray light. • V-groove with small angle can better suppress the escape of scattered light. • An optimal spacing for dump to minimize the intensity of escaping scattered light. Laser dump is an essential optical component in Thomson scattering diagnostic. Both multi-blade and V-grooved dumps can increase the ability of absorbing laser energy by using multiple surfaces to reduce the energy density on the wall surface. Still, the wall edges of the dump easily produce scattered light. The distribution and intensity of scattered light escaping from these two dumps, as well as the distribution and intensity of scattered light on the wall, are analyzed by the theory and simulation. In which an optical-mechanical simulation model of the laser dump was built. The results indicate that increasing the depth of the laser beam incident into the dump can decrease the distribution of escaping scattered light for these two dumps. When both the half-angle of V-groove and the incidence angle of beam on the entrance surface take a small amount, the V-grooved dump has an advantage of weaker escaping scattered light intensity, while there is a problem of heat accumulation at the bottom. For a fixed laser beam diameter, there is an optimal spacing for the dump to minimize the intensity of escaping scattered light. Additionally, the intensity of escaping scattered light is affected by the surface properties of dump, with low surface specular reflection resulting in low intensity. [ABSTRACT FROM AUTHOR]

• The aim of this research is to develop business intelligence simulation model with their leadership enhancement and crisis management using gaming model based on cloud network. • Here the crisis management with leadership analysis is carried out using variational recurrent Boltzmann learning model (VRBL). • The experimental analysis based on cloud network modelling in terms of execution time, network performance, overall complexity, data optimization, end-end delay. • ML offers a more accurate and efficient prediction method than standard econometric models, making it more useful. • In terms of prediction performance, the final fusion model performs better than the voting and averaging techniques. The reality of the modern, fast-paced business world is crisis. Instability in today's business environment is brought on by rapid organisational change, shifting economic situations, people issues, unanticipated technological advancements, and political ramifications. The state is unable to control this instability, which manifests as economic disruptions leading to crises. In addition to harming those who have lost their employment, the crisis that is impacting our nation and every other nation in the world also affects others who are worried about losing their work. The aim of this research is to develop business intelligence simulation model with their leadership enhancement and crisis management using gaming model based on cloud network. Here the crisis management with leadership analysis is carried out using variational recurrent Boltzmann learning model (VRBL). the experimental analysis based on cloud network modelling in terms of execution time, network performance, overall complexity, data optimization, end-end delay. ML offers a more accurate and efficient prediction method than standard econometric models, making it more useful. In terms of prediction performance, the final fusion model performs better than the voting and averaging techniques. [ABSTRACT FROM AUTHOR]

• A dynamic simulation model of a novel wind-to-heat system is built. • The energy conversion from wind to heat is explained by the model. • The model is verified within 10% average errors with the experimental results. • The heat production capacity of the system in one heating season is obtained. • For the first time match the wind-to-heat system heat production and the heat load. As a clean heating technology, the wind-to-heat system with shorter energy conversion and higher efficiency is proposed. The simulation model of the wind-to-heat system is built by combined wind turbine, drive chain and heat pump with the control strategy. The compressor torque characteristics are the key to matching the wind turbine and the compressor. The three-zone model is used to simulate the condenser and the evaporator. Compared with theoretical calculation research, the dynamic performance and the accuracy of the system can be studied and improved. The control strategy specifies the control objectives of the system at different wind speeds. Comparing the simulated heating capacity, shaft power and revolving speed with the experimental values at different wind speeds, the simulation results are verified with average errors within 10%. Considering the application scope of the system on the user side, the match between the heat production and heat load is carried out. The wind energy utilization hours, the loss of load probability and the average electric heat production are introduced as evaluation indexes. Under the conditions with or without energy storage, to ensure the maximum utilization of wind energy in the wind-to-heat system, different optimal number of villas are obtained. It can provide a reference for matching the system design and the user needs. [ABSTRACT FROM AUTHOR]

Accurately describing the soil erosion process is crucial for improving the accuracy of existing simulation models of ephemeral gully erosion. However, a laboratory experimental strategy for simulating sediment distribution along slope lengths of an ephemeral gully is lacking. This limitation greatly hinders the development of simulation models for ephemeral gully erosion. In this study, we constructed six soil flumes with 12 m in length, 0.1 m in width, and 0.5 m in depth, which were filled with cultivated loess soils. Four flow rates (5.33, 10.67, 21.33, and 42.67 × 10−3 m3 s−1 m−1), four slope gradients (5°, 10°, 15°, and 20°), and six gully lengths (2, 4, 6, 8, 10 and 12 m) were adopted to perform a series of laboratory scouring experiments. The measured sediment concentrations at the outlet ranged from 23.39 kg m−3 to 534.60 kg m−3. The trend of exponential increase in sediment concentrations along slope lengths of an ephemeral gully was similar to that observed in a rill. According to the fitting equation, the maximum sediment concentrations (A e) ranged from 358.05 kg m−3 to 910.88 kg m−3. The attenuation coefficients (B e) indicated the rate of increase in sediment load with slope length, which ranged from 0.042 m−1 to 0.185 m−1. By combining the measured sediment loads along the slope length (8 m) with the sediment transport capacity, the sediment distribution along slope lengths of an ephemeral gully could be accurately quantified. Moreover, the results confirmed that a flume with a short slope length (4/6 m) could effectively determine the sediment distribution along slope lengths at gentle slope of 5° and 10°. However, a minimum length of 8 m was advisable at steep slope of 15° and 20°. In summary, our experimental strategy provides an efficient method for determining the sediment distribution along slope lengths of an ephemeral gully. [ABSTRACT FROM AUTHOR]

Extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli (E. coli) in animals are considered a human health threat, because this type of bacteria can serve as a reservoir of antibiotic resistant genes and act as a continuous threat of the emergence of new resistant bacteria, in addition to the direct effect of making infection untreatable. Although the prevalence of ESBL producing bacteria in broilers was drastically reduced in the Netherlands, chicken meat still has the highest prevalence among meat products. Therefore, further control of the ESBL-producing E. coli in the broiler production chain is important to reduce public health risks. The main objectives of this study were to evaluate the effectiveness of intervention scenarios to reduce the transmission of ESBL-producing E. coli in the broiler production chain and to quantitatively estimate the risk to public health. In this study, we developed two different types of transmission models that described the observed time-related decline in prevalence during a production round: one with time-dependent decline in susceptibility and one with partial immunity to phylogenetic groups. Both models incorporated the environmental contamination effect between production rounds and within flocks. The parameter values, including transmission rate and recovery rate, were estimated by Approximate Bayesian computation (ABC) method using data from a longitudinal study in a Dutch organic broiler farm. We applied the models to the three production stages in the broiler production chain, beginning from the Parent Stock (PS) farms, the hatcheries, and to the broiler farms. In our models, eggs were collected from different parent stock farms and transported to the hatchery and from there to a broiler farm.The size of a flock and the number of farms were adjusted to the Dutch situation. Both models were able to describe the observed dynamics within and between the production stages equally well, with estimated ESBL-producing E. coli prevalence of 8.98% and 11.47% in broilers at slaughter and 0.12% and 0.15% in humans due to chicken consumption. Both models indicated that improving farm management to eliminate the bacteria from the environment was the most effective intervention, making this outcome robust. Although chicken meat consumption is not a major risk factor for human carriage of the bacteria according to our models, reducing the bacteria in the PS and broiler farm environment to at least one percent can further decrease the prevalence in humans. • Control of ESBL in the environment of poultry farms is a promising strategy. • Two transmission models reflecting susceptibility change and immunity difference. • Chicken meat is a minor contributor to human carriage of ESBLs. [ABSTRACT FROM AUTHOR]

Objectives: Coronavirus disease 2019 has put unprecedented pressure on healthcare systems worldwide, leading to a reduction of the available healthcare capacity. Our objective was to develop a decision model to estimate the impact of postponing semielective surgical procedures on health, to support prioritization of care from a utilitarian perspective.Methods: A cohort state-transition model was developed and applied to 43 semielective nonpediatric surgical procedures commonly performed in academic hospitals. Scenarios of delaying surgery from 2 weeks were compared with delaying up to 1 year and no surgery at all. Model parameters were based on registries, scientific literature, and the World Health Organization Global Burden of Disease study. For each surgical procedure, the model estimated the average expected disability-adjusted life-years (DALYs) per month of delay.Results: Given the best available evidence, the 2 surgical procedures associated with most DALYs owing to delay were bypass surgery for Fontaine III/IV peripheral arterial disease (0.23 DALY/month, 95% confidence interval [CI]: 0.13-0.36) and transaortic valve implantation (0.15 DALY/month, 95% CI: 0.09-0.24). The 2 surgical procedures with the least DALYs were placing a shunt for dialysis (0.01, 95% CI: 0.005-0.01) and thyroid carcinoma resection (0.01, 95% CI: 0.01-0.02).Conclusion: Expected health loss owing to surgical delay can be objectively calculated with our decision model based on best available evidence, which can guide prioritization of surgical procedures to minimize population health loss in times of scarcity. The model results should be placed in the context of different ethical perspectives and combined with capacity management tools to facilitate large-scale implementation. [ABSTRACT FROM AUTHOR]