A novel grey power-Markov model for the prediction of China's electricity consumption.

Forecasting the electricity consumption has always played an important role in the management of power system management, which requires higher forecasting technology. Therefore, based on the principle of "new information priority", combined with rolling mechanism and Markov theory, a novel grey power-Markov prediction model with time-varying parameters (RGPMM(λ,1,1)) is designed, which overcomes the inherent defects of fixed structure and poor adaptability to the changes of original data. In addition, in order to prove the validity and applicability of the prediction model, we have used the model to predict China's total electricity consumption, and have compared it with the prediction results by a series of benchmark models. The result shows that the can better adapt to the characteristics of electricity consumption data, and it also shows the advantages of the proposed forecasting model. In this paper, the proposed forecasting model is used to predict China's total electricity consumption in the next six years from 2018 to 2023, so as to provide certain reference value for power system management and distribution.

Real-Time Power Analysis of Smart Sensors Using Advanced Debugging Methods.

To achieve a good estimate of the power consumption of an embedded system, including its firmware, is a crucial step in the development of systems with a severely constrained power supply. This is especially true for cases where the device is powered by a small battery or through energy harvesting. The state-of-the-art approaches to measure or estimate the power consumption are formal methods, using power debugging tools with the real hardware or simulation based estimations. In the work at hand, a novel method to estimate the power consumption is proposed, it utilizes the sensor-in-the-loop architecture and enhancing it with a power estimation functionality. The proposed method combines the benefits of former methods, allowing for run-time analysis of the power-consumption in a reproducible way using recorded data without the need for power debugging hardware. In the experiments it is shown that, once set up, the proposed method is able to estimate the power consumption with an error of less than 1% compared to a power debugging hardware. Thus, the proposed method provides a reliable and fast way to estimate the systems power consumption.

Co-current analysis among electricity-water-carbon for the power sector in China.

China's power sector consumes large amounts of water for its cooling every year, which has increased water stress in many regions and caused the vulnerability in electricity generation. Current plans for power sector mainly focus on the clean and low-carbon development, while it is unclear how to reconcile CO2-reduction target with water-saving target. In this paper, an optimization model named NET-Power (National Energy Technology-Power) is developed to simulate the deployment of power generation technologies, and to further answer whether there is a conflict or not between water-saving target and CO2-reduction target in the power sector. The result shows that peaking carbon emissions before 2030 in the power sector may increase the water consumption by 34.85Gt. In addition, to further meeting the water constraint on the basis of peaking carbon emissions would lead to a higher carbon intensity of thermal power. These findings indicate that low-carbon transition will cause significant water-carbon contradiction, which mainly lies in nuclear power technology and dry-cooling technology. Finally, the optimal technology layout path that can meet the dual constraints of water and carbon for the power sector in China is proposed.

The initial engraftment of tumor cells is critical for the future growth pattern: a mathematical study based on simulations and animal experiments.

BACKGROUND: Xenograft mouse tumor models are used to study mechanisms of tumor growth and metastasis formation and to investigate the efficacy of different therapeutic interventions. After injection the engrafted cells form a local tumor nodule. Following an initial lag period of several days, the size of the tumor is measured periodically throughout the experiment using calipers. This method of determining tumor size is error prone because the measurement is two-dimensional (calipers do not measure tumor depth). Primary tumor growth can be described mathematically by suitable growth functions, the choice of which is not always obvious. Growth parameters provide information on tumor growth and are determined by applying nonlinear curve fitting. METHODS: We used self-generated synthetic data including random measurement errors to research the accuracy of parameter estimation based on caliper measured tumor data. Fit metrics were investigated to identify the most appropriate growth function for a given synthetic dataset. We studied the effects of measuring tumor size at different frequencies on the accuracy and precision of the estimated parameters. For curve fitting with fixed initial tumor volume, we varied this fixed initial volume during the fitting process to investigate the effect on the resulting estimated parameters. We determined the number of surviving engrafted tumor cells after injection using ex vivo bioluminescence imaging, to demonstrate the effect on experiments of incorrect assumptions about the initial tumor volume. RESULTS: To select a suitable growth function, measurement data from at least 15 animals should be considered. Tumor volume should be measured at least every three days to estimate accurate growth parameters. Daily measurement of the tumor volume is the most accurate way to improve long-term predictability of tumor growth. The initial tumor volume needs to have a fixed value in order to achieve meaningful results. An incorrect value for the initial tumor volume leads to large deviations in the resulting growth parameters. CONCLUSIONS: The actual number of cancer cells engrafting directly after subcutaneous injection is critical for future tumor growth and distinctly influences the parameters for tumor growth determined by curve fitting.

Effect of Processing on Color, Rheology and Bioactive Compounds of Different Sweet Pepper Purees.

Sweet pepper purees (red, yellow and green) were examined for FTIR (Fourier-transform infrared spectroscopy), chemical, bioactive, color and rheological parameters. FTIR technique was used to evaluate the functional groups. FTIR wave numbers are associated with the absorption bands that depicted the presence of several phytocompounds in the purees. Among the chemical parameters, water activity varied non-significantly whereas, total soluble sugars (TSS), sugars and pH increased after processing of the fruits into purees. The presence of bioactive compounds depends on the variety of sweet pepper. The red puree had significantly higher carotenoids, phenolics and antioxidant capacity followed by yellow and green pepper purees. The minimal change was observed in the color of purees during processing. The purees were subjected to different shear rate (1 to 50 s-1) to evaluate the effect on viscosity and shear stress that is desirable for its end use in different food products. All purees show the shear thinning behavior as shear rate increased. Results revealed that heat processing of sweet peppers didn't affect color, sugars, carotenoids, phenolics and antioxidant capacity to a greater extent. The finding will be helpful to manage seasonal bulk production efficiently and make them available as an ingredient in various food products.

Development and field validation of an omni-domain power-duration model.

Purpose: To validate and compare a novel model based on the critical power (CP) concept that describes the entire domain of maximal mean power (MMP) data from cyclists.Methods: An omni-domain power-duration (OmPD) model was derived whereby the rate of W' expenditure is bound by maximum sprint power and the power at prolonged durations declines from CP log-linearly. The three-parameter CP (3CP) and exponential (Exp) models were likewise extended with the log-linear decay function (Om3CP and OmExp). Each model bounds W' using a different nonconstant function, W'eff (effective W'). Models were fit to MMP data from nine cyclists who also completed four time-trials (TTs).Results: The OmPD and Om3CP residuals (4 ± 1%) were smaller than the OmExp residuals (6 ± 2%; P < 0.001). W'eff predicted by the OmPD model was stable between 120-1,800 s, whereas it varied for the Om3CP and OmExp models. TT prediction errors were not different between models (7 ± 5%, 8 ± 5%, 7 ± 6%; P = 0.914).Conclusion: The OmPD offers similar or superior goodness-of-fit and better theoretical properties compared to the other models, such that it best extends the CP concept to short-sprint and prolonged-endurance performance.

Species-area relationships of lemurs in a fragmented landscape in Madagascar.

We used species-area relationships (SARs) to investigate the effects of habitat loss on lemur biogeography. We measured species richness via visual surveys on line transects within 42 fragments of dry deciduous forest at the Ambanjabe field site in Ankarafantsika National Park, Madagascar. We measured human disturbance and habitat characteristics within 38 of the 42 fragments. We measured the distance between each fragment and the nearest settlement, continuous forest, and nearest neighboring fragment. We fit 10 candidate SAR models to the data using nonlinear least squares regression and compared them using Akaike's Information Criterion (AIC). To determine how habitat characteristics, as well as area, influenced species richness, we ran a hierarchical partitioning procedure to select which variables to include in generalized additive models (GAMs) and compared them using AIC. Contrary to expectations, we found that lemurs form convex SARs, without a "small island effect", and with the power model being the most likely SAR model. Although we found that four variables (area, survey effort, and total human disturbance, and mean tree height) independently contributed greater than 10% of the variation in lemur species richness, only area was included in the most likely model. We suggest that the power model was the most likely SAR model and our inability to detect a "small island effect" are the result of Microcebus spp. being edge tolerant and capable of dispersing through matrix, scale issues in the study design, and low γ-diversity in the landscape. However, more study is needed to determine what role human disturbance plays in influencing species richness in lemurs.

Updated estimates of the relationship between speed and road safety at the aggregate and individual levels.

Recent studies of the relationship between the speed of traffic and road safety, stated as the number of fatalities and the number of injury accidents, are reviewed and their results synthesised by means of meta-analysis. All studies were based on data fully or partly for years after 2000. Previously proposed models of the relationship between the speed of traffic and road safety, including the Power Model and an Exponential Model, are supported. Summary estimates of coefficients show that the relationship between speed and road safety remains strong. The Power Model and the Exponential Model both fit the data very well. The relationship between speed and road safety is the same at the individual driver level as at the aggregate level referring to the mean speed of traffic.

The Critical Power Model as a Potential Tool for Anti-doping.

Existing doping detection strategies rely on direct and indirect biochemical measurement methods focused on detecting banned substances, their metabolites, or biomarkers related to their use. However, the goal of doping is to improve performance, and yet evidence from performance data is not considered by these strategies. The emergence of portable sensors for measuring exercise intensities and of player tracking technologies may enable the widespread collection of performance data. How these data should be used for doping detection is an open question. Herein, we review the basis by which performance models could be used for doping detection, followed by critically reviewing the potential of the critical power (CP) model as a prototypical performance model that could be used in this regard. Performance models are mathematical representations of performance data specific to the athlete. Some models feature parameters with physiological interpretations, changes to which may provide clues regarding the specific doping method. The CP model is a simple model of the power-duration curve and features two physiologically interpretable parameters, CP and W'. We argue that the CP model could be useful for doping detection mainly based on the predictable sensitivities of its parameters to ergogenic aids and other performance-enhancing interventions. However, our argument is counterbalanced by the existence of important limitations and unresolved questions that need to be addressed before the model is used for doping detection. We conclude by providing a simple worked example showing how it could be used and propose recommendations for its implementation.

In vivo release of peptide-loaded PLGA microspheres assessed through deconvolution coupled with mechanistic approach.

In this study, a reevaluation of the in vivo release phases from long-release PLGA-based microspheres is presented, leading to a better characterization of the plasma concentrations/time profile. Microspheres were designed for intramuscular injection releasing a cyclic somatostatin analog over 70 days. Clinical study was performed in 64 healthy subjects receiving a subcutaneous dose of an immediate release solution as reference formulation and an intramuscular injection of microspheres as test formulation. The in vivo input curve was obtained by numerical deconvolution. Results showed that double Weibull function could not fit correctly the tri-phasic (burst, lag, and erosion) in vivo input profile typical for PLGA-based formulations, due to a change in the drug release trend in the terminal phase. Triple Weibull showed a significant improvement in the curve fitting, each term being assigned to one of the following phases: initial (burst/lag), erosion, and terminal phase of drug release. The existence of the additional terminal phase was confirmed by a mechanistic approach as well, which denoted that this phase was, most probably, a consequence of the release mechanism change from erosion to diffusion controlled. The same model demonstrated that the burst release was as well influenced by the polymer swelling, while currently existing theories state that the burst phase is mainly determined by the dissolution of immediately available drug substance and diffusion through surface related pores.

Traffic safety effects of new speed limits in Sweden.

The effects of speed, both positive and negative, make speed a primary target for policy action. Driving speeds affect the risk of being involved in a crash and the injury severity as well as the noise and exhaust emissions. Starting 2008, the Swedish Transport Administration performed a review of the speed limits on the national rural road network. This review resulted in major changes of the speed limits on the rural road network. It was predominantly roads with a low traffic safety standard and unsatisfactory road sides that were selected for reduced speed limits, as well as roads with a good traffic safety record being selected for an increase in speed limits. During 2008 and 2009, speed limit changed on approximately 20,500km of roads, out of which approximately 2700km were assigned an increase, and 17,800km were assigned a reduction in speed limits. The aim of this study is predominantly to describe and analyse the longterm traffic safety effect of increased, as well as, reduced speed limits, but also to analyse the changes in actual driving speeds due to the changed speed limits. Traffic safety effects are investigated by means of a before and after study with control group and the effects on actual mean speeds are measured by a sampling survey in which speed was measured at randomly selected sites before and after the speed limit changes. Results show a reduction in fatalities on rural roads with reduced speed limit from 90 to 80km/h where the number of fatalities decreased by 14 per year, while no significant changes were seen for the seriously injured. On motorways with an increased speed limit to 120km/h, the number of seriously injured increased by about 15 per year, but no significant changes were seen for the number of deaths. The number of seriously injured increased on all types of motorways, but the worst development was seen for narrow motorways (21.5m wide). For 2+1 roads (a continuous three-lane cross-section with alternating passing lanes and the two directions of travel separated by a median barrier) with decreased speed limit from 110 to 100km/h, the seriously injured decreased by about 16 per year. As regards the change of mean speeds, a decrease in speed limit with 10km/h led to a decrease of mean speeds of around 2-3km/h and an increase of the speed limit with 10km/h resulted in an increase of mean speed by 3km/h. In conclusion, the results show that in total about 17 lives per year have been saved on the road network with changed speed limits. For comparison, 397 road users were killed in total during 2008. The number of seriously injured remain in principle unchanged. It should also be noted that the results are obtained for the road network which changed the speed limits during 2008 and 2009, and it is not certain that the results can be generalised to another road network.

Changes in speed distribution: Applying aggregated safety effect models to individual vehicle speeds.

This study investigated the effect of applying two aggregated models (the Power model and the Exponential model) to individual vehicle speeds instead of mean speeds. This is of particular interest when the measure introduced affects different parts of the speed distribution differently. The aim was to examine how the estimated overall risk was affected when assuming the models are valid on an individual vehicle level. Speed data from two applications of speed measurements were used in the study: an evaluation of movable speed cameras and a national evaluation of new speed limits in Sweden. The results showed that when applied on individual vehicle speed level compared with aggregated level, there was essentially no difference between these for the Power model in the case of injury accidents. However, for fatalities the difference was greater, especially for roads with new cameras where those driving fastest reduced their speed the most. For the case with new speed limits, the individual approach estimated a somewhat smaller effect, reflecting that changes in the 15th percentile (P15) were somewhat larger than changes in P85 in this case. For the Exponential model there was also a clear, although small, difference between applying the model to mean speed changes and individual vehicle speed changes when speed cameras were used. This applied both for injury accidents and fatalities. There were also larger effects for the Exponential model than for the Power model, especially for injury accidents. In conclusion, applying the Power or Exponential model to individual vehicle speeds is an alternative that provides reasonable results in relation to the original Power and Exponential models, but more research is needed to clarify the shape of the individual risk curve. It is not surprising that the impact on severe traffic crashes was larger in situations where those driving fastest reduced their speed the most. Further investigations on use of the Power and/or the Exponential model at individual vehicle level would require more data on the individual level from a range of international studies.

Models of PaO2 response to the continuous distending pressure maneuver during high frequency oscillatory ventilation in healthy and ARDS lung model pigs.

UNLABELLED: Purpose/Aim : High-frequency oscillatory ventilation (HFOV) is a method of ventilation that theoretically achieves the goals of lung protective ventilation in acute respiratory distress syndrome (ARDS) patients. It is characterized by a rapid delivery of small tidal volumes at high frequencies oscillating around a continuous distending pressure (CDP). Optimization of CDP is not an easy task and it is titrated empirically in the clinical practice. The aim of this study is to investigate whether the level of CDP consistently affects the shape of the partial pressure of oxygen (PaO2) response to stepwise changes in CDP during HFOV of healthy and ARDS-induced pigs. MATERIALS AND METHODS: We performed two stepwise maneuvers of CDP in 14 pigs: one before and one after the lung lavage, inducing ARDS. For each CDP step performed, we fitted a segment of PaO2 curve with a one-term power model. RESULTS: PaO2 course follows shapes modeled by root, linear, quadratic, and cubic functions for values of PaO2 ≤ 110 mmHg and PaO2 ≤ 200 mmHg, before and after the lung lavage, respectively. PaO2 course follows a shape modeled exclusively by a root function for values of PaO2 > 110 mmHg and PaO2 > 200 mmHg, before and after the lung lavage, respectively. It is not possible to describe a relationship between the shape of the PaO2 course and the values of CDP. CONCLUSIONS: The PaO2 curve may give information about the level of recruitment of alveoli, but cannot be used for optimization of CDP level during HFOV in healthy and ARDS lung model pigs.

Number of leaves needed to model leaf area in jack bean plants using leaf dimensions / Número de folhas para modelar a área foliar de feijão de porco por dimensões foliares

Leaf area estimation models based on linear leaf dimensions are an important method because their application is not destructive to the leaves. For these models to be reliable, it is important that the estimation of model parameters is accurate, and for that to occur, the models must be generated using an adequate sample size (number of leaves). The objective of this study was to determine the number of leaves necessary to accurately model the leaf area of jack beans (Y), determined by digital photos, according to the width of the central leaflet (x), by a power model (Y = axb) generated through an iterative process. Accordingly, an experiment was performed in a 256 m2 area. A total of 745 leaves were randomly collected at six different crop development stages (29, 43, 57, 73, 87 and 101 days after emergence). Each leaf was comprised of a left, central and right leaflet. The width of the central leaflet (x) was measured on the 745 leaves. Leaf area (sum of the area of the left, central and right leaflets; Y) was then determined using a digital photo method. The number of leaves necessary for the estimation of the parameters a and b and the coefficient of determination (R2) of the power model were determined through resampling with replacement. The power model (Y = 4.2049x1.8215, R2 = 0.9701), based on the width of the central leaflet was determined to be adequate for estimating jack bean leaf area. Data collected from a sample of 200 leaves were determined to be sufficient for constructing an accurate power model for the leaf area of jack beans (Y) as a function of the width of the central leaflet (x), based on determinations of leaf area using digital photos.

Modelos de estimação de área foliar de plantas em função das dimensões lineares das folhas são importantes, principalmente, por não haver necessidade de destruição das folhas. Para modelos fidedignos, é importante que as estimativas de seus parâmetros sejam precisas, e, para isso, devem ser gerados a partir de um número adequado de folhas. O objetivo deste trabalho foi determinar o número de folhas necessário para modelar a área foliar de feijão de porco determinada por fotos digitais (Y) em função da largura do limbo do folíolo central da folha (x), por meio do modelo potência (Y = axb) gerado por processo iterativo. Para isso foi conduzido um experimento numa área de 256 m2, no qual, em seis períodos de desenvolvimento da cultura (29, 43, 57, 73, 87 e 101 dias após a emergência) foram coletadas, aleatoriamente, o total de 745 folhas. Cada folha é composta pelos folíolos esquerdo, central e direito. Nas 745 folhas foi mensurada a largura do limbo do folíolo central (x). A seguir, determinou-se a área foliar (soma da área dos folíolos esquerdo, central e direito) por meio do método de fotos digitais (Y). O número de folhas, necessário para a estimação dos parâmetros a e b do modelo potência e do coeficiente de determinação do modelo (R2), foi determinado por reamostragens, com reposição. Em feijão de porco, o modelo potência (Y = 4,2049x1,8215, R2 = 0,9701) da largura do limbo do folíolo central é adequado para estimar a área foliar obtida por fotos digitais. Mensurar 200 folhas é suficiente para construir modelos precisos do tipo potência, da área foliar de feijão de porco determinada por fotos digitais (Y) em função da largura do limbo do folíolo central da folha (x).

Optimal Self-Tuning PID Controller Based on Low Power Consumption for a Server Fan Cooling System.

Recently, saving the cooling power in servers by controlling the fan speed has attracted considerable attention because of the increasing demand for high-density servers. This paper presents an optimal self-tuning proportional-integral-derivative (PID) controller, combining a PID neural network (PIDNN) with fan-power-based optimization in the transient-state temperature response in the time domain, for a server fan cooling system. Because the thermal model of the cooling system is nonlinear and complex, a server mockup system simulating a 1U rack server was constructed and a fan power model was created using a third-order nonlinear curve fit to determine the cooling power consumption by the fan speed control. PIDNN with a time domain criterion is used to tune all online and optimized PID gains. The proposed controller was validated through experiments of step response when the server operated from the low to high power state. The results show that up to 14% of a server's fan cooling power can be saved if the fan control permits a slight temperature response overshoot in the electronic components, which may provide a time-saving strategy for tuning the PID controller to control the server fan speed during low fan power consumption.

A Bayesian generalized age-period-cohort power model for cancer projections.

Age-period-cohort (APC) models are the state of art in cancer projections, assessing past and recent trends and extrapolating mortality or incidence data into the future. Nordpred is a well-established software, assuming a Poisson distribution for the counts and a log-link or power-link function with fixed power; however, its predictive performance is poor for sparse data. Bayesian models with log-link function have been applied, but they can lead to extreme estimates. In this paper, we address criticisms of the aforementioned models by providing Bayesian formulations based on a power-link and develop a generalized APC power-link model, which assumes a random rather than fixed power parameter. In addition, a power model with a fixed power parameter of five was formulated in the Bayesian framework. The predictive performance of the new models was evaluated on Swiss lung cancer mortality data using model-based estimates of observed periods. Results indicated that the generalized APC power-link model provides best estimates for male and female lung cancer mortality. The gender-specific models were further applied to project lung cancer mortality in Switzerland during the periods 2009-2013 and 2014-2018.

Rationale and resources for teaching the mathematical modeling of athletic training and performance.

A number of professions rely on exercise prescription to improve health or athletic performance, including coaching, fitness/personal training, rehabilitation, and exercise physiology. It is therefore advisable that the professionals involved learn the various tools available for designing effective training programs. Mathematical modeling of athletic training and performance, which we henceforth call "performance modeling," is one such tool. Two models, the critical power (CP) model and the Banister impulse-response (IR) model, offer complementary information. The CP model describes the relationship between work rates and the durations for which an individual can sustain them during constant-work-rate or intermittent exercise. The IR model describes the dynamics by which an individual's performance capacity changes over time as a function of training. Both models elegantly abstract the underlying physiology, and both can accurately fit performance data, such that educating exercise practitioners in the science of performance modeling offers both pedagogical and practical benefits. In addition, performance modeling offers an avenue for introducing mathematical modeling skills to exercise physiology researchers. A principal limitation to the adoption of performance modeling is a lack of education. The goal of this report is therefore to encourage educators of exercise physiology practitioners and researchers to incorporate the science of performance modeling in their curricula and to serve as a resource to support this effort. The resources include a comprehensive review of the concepts associated with the development and use of the models, software to enable hands-on computer exercises, and strategies for teaching the models to different audiences.