Experimental validation of inviscid linear stability theory applied to an axisymmetric jet

We study the development of perturbations in a submerged air jet with a round cross-section and a long laminar region (five jet diameters) at a Reynolds number of 5400 by both inviscid linear stability theory and experiments. The theoretical analysis shows that there are two modes of growing axisymmetric perturbations, which are generated by three generalized inflection points of the jet's velocity profile. To validate the results of linear stability theory, we conduct experiments with controlled axisymmetric perturbations to the jet. The characteristics of growing waves are obtained by visualization, thermoanemometer measurements and correlation analysis. Experimentally measured wavelengths, growth rates and spatial distributions of velocity fluctuations for both growing modes are in good agreement with theoretical calculations. Therefore, it is demonstrated that small perturbations to the laminar jet closely follow the predictions of inviscid linear stability theory.

Power management of variable capacitors in electrical grid systems according to the criterion of mini-mum energy loss

The aim is to manage the transmitted reactive power in electrical grids using variable capacitor batteries according to the criterion of minimum energy loss under different annual reactive load schedules and different numbers of variable capacitor sections. The main theoretical relations were obtained by the methods of mathematical modelling and integral calculus using the theory of optimal control. The influence of the power and number of sections in a capacitor battery on energy losses in the grid was estimated using computational experiments. Dependencies for energy losses in a capacitor battery, as well as for reducing energy losses in the grid, were obtained. These expressions are valid for linearized load schedules. It is shown that the dependences of energy losses in a capacitor battery and the reduction of losses in the grid on the section power have inflection points and pass through a maximum. The presence of inflection points is associated with a change in the number of capacitor sections operating throughout the year. The presence of a maximum is explained by the fact that, with an increase in the power of the capacitor battery, its operating time decreases under the complete number of variable sections. It is established that the batteries of static capacitors with two variable sections can reduce energy losses when transmitting reactive power by over 90%. For three- and four-section static capacitors, the loss reduction is close to 100%. The reduction in energy losses increases when approaching maximal levels of annual reactive load. Energy losses in electrical grid systems can be reduced by capacitor batteries with no more than three or four variable sections. In most cases, this can be achieved by two-section capacitor batteries.

Stream Boundary Detection of a Hyper-Arid, Polar Region Using a U-Net Architecture: Taylor Valley, Antarctica

Convolutional neural networks (CNNs) are becoming an increasingly popular approach for classification mapping of large complex regions where manual data collection is too time consuming. Stream boundaries in hyper-arid polar regions such as the McMurdo Dry Valleys (MDVs) in Antarctica are difficult to locate because they have little hydraulic flow throughout the short summer months. This paper utilizes a U-Net CNN to map stream boundaries from lidar derived rasters in Taylor Valley located within the MDVs, covering ∼770 km2. The training dataset consists of 217 (300 × 300 m2) well-distributed tiles of manually classified stream boundaries with diverse geometries (straight, sinuous, meandering, and braided) throughout the valley. The U-Net CNN is trained on elevation, slope, lidar intensity returns, and flow accumulation rasters. These features were used for detection of stream boundaries by providing potential topographic cues such as inflection points at stream boundaries and reflective properties of streams such as linear patterns of wetted soil, water, or ice. Various combinations of these features were analyzed based on performance. The test set performance revealed that elevation and slope had the highest performance of the feature combinations. The test set performance analysis revealed that the CNN model trained with elevation independently received a precision, recall, and F1 score of 0.94±0.05, 0.95±0.04, and 0.94±0.04 respectively, while slope received 0.96±0.03, 0.93±0.04, and 0.94±0.04, respectively. The performance of the test set revealed higher stream boundary prediction accuracies along the coast, while inland performance varied. Meandering streams had the highest stream boundary prediction performance on the test set compared to the other stream geometries tested here because meandering streams are further evolved and have more distinguishable breaks in slope, indicating stream boundaries. These methods provide a novel approach for mapping stream boundaries semi-automatically in complex regions such as hyper-arid environments over larger scales than is possible for current methods.

Nonlinear models in the height description of the Rhino sunflower cultivar

ABSTRACT: Sunflower produces achenes and oil of good quality, besides serving for production of silage, forage and biodiesel. Growth modeling allows knowing the growth pattern of the crop and optimizing the management. The research characterized the growth of the Rhino sunflower cultivar using the Logistic and Gompertz models and to make considerations regarding management based on critical points. The data used come from three uniformity trials with the Rhino confectionery sunflower cultivar carried out in the experimental area of the Federal University of Santa Maria - Campus Frederico Westphalen in the 2019/2020 agricultural harvest. In the first, second and third trials 14, 12 and 10 weekly height evaluations were performed on 10 plants, respectively. The data were adjusted for the thermal time accumulated. The parameters were estimated by ordinary least square’s method using the Gauss-Newton algorithm. The fitting quality of the models to the data was measured by the adjusted coefficient of determination, Akaike information criterion, Bayesian information criterion, and through intrinsic and parametric nonlinearity. The inflection points (IP), maximum acceleration (MAP), maximum deceleration (MDP) and asymptotic deceleration (ADP) were determined. Statistical analyses were performed with Microsoft Office Excel® and R software. The models satisfactorily described the height growth curve of sunflower, providing parameters with practical interpretations. The Logistics model has the best fitting quality, being the most suitable for characterizing the growth curve. The estimated critical points provide important information for crop management. Weeds must be controlled until the MAP. Covered fertilizer applications must be carried out between the MAP and IP range. ADP is an indicator of maturity, after reaching this point, the plants can be harvested for the production of silage without loss of volume and quality.

Spatiotemporal Polyrhythm Characteristics of Public Bicycle Mobility in Urban Chronotopes Context

Cycling rhythm performance is the result of a complex interplay between active travel demand and cycling network supply. Most studies focused on bicycle flow, but little attention has been paid to cycling rhythm changes for public bicycles. Full sample data of origin–destination enables an efficient description of network-wide cycling mobility efficiency in urban public bicycle systems. In this paper, we show how the spatiotemporal characteristics of cycling speed reveal the performance of cycling rhythms. The inference method of riding speed estimation is proposed with an unknown cycling path. The significant inconsistency of docking stations in cycling rhythm was unraveled by the source–sink relationship comparison. The asymmetry of the cycling rhythm on the path is manifested as the rhythm difference among paths and bidirectional inconsistency. We found that cycling rhythm has a temporal multilayer and spatial mismatch, which shows the inflection points of the cycling rhythm where the travel behavioral preference changes and the exact road segments with different rhythms. This finding suggests that a well-designed cycling environment and occupation-residential function should be considered in active transport demand management and urban planning to help induce active travel behavior decisions.

Dependence on Film Thickness of Guest-Induced c Perpendicular Orientation in PPO Films

For poly(2,6-dimethyl-1,4-phenylene)oxide (PPO) films exhibiting nanoporous-crystalline (NC) phases, c^ orientation (i.e., crystalline polymer chain axes being preferentially perpendicular to the film plane) is obtained by crystallization of amorphous films, as induced by sorption of suitable low-molecular-mass guest molecules. The occurrence of c^ orientation is relevant for applications of NC PPO films because it markedly increases film transparency as well as guest diffusivity. Surprisingly, we show that the known crystallization procedures lead to c^ oriented thick (50–300 μm) films and to unoriented thin (£20 μm) films. This absence of crystalline phase orientation for thin films is rationalized by fast guest sorption kinetics, which avoid co-crystallization in confined spaces and hence inhibit formation of flat-on lamellae. For thick films exhibiting c^ orientation, sigmoid kinetics of guest sorption and of thickening of PPO films are observed, with inflection points associated with guest-induced film plasticization. Corresponding crystallization kinetics are linear with time and show that co-crystal growth is poorly affected by film plasticization. An additional relevant result of this study is the linear relationship between WAXD crystallinity index and DSC melting enthalpy, which allows evaluation of melting enthalpy of the NC α form of PPO (DHmo = 42 ± 2 J/g).

New Model for the COVID-19 Reported Cases and Deaths of Ghana in Accelerated Spread and Prediction of the Delayed Phase

There is an ongoing investigation on the transmission characteristics of COVID-19 with respect to country-based inflection points, nature of distribution and prediction of future trends. In this study, a new accelerated and delayed spread models for COVID-19 reported cases and deaths in Ghana were developed. Optimization techniques coupled with interpolations, least square and non-linear regression methods, to come out with an informed modeling strategy to predict the delayed spread for the case of Ghana were adopted. Derivative and tangent methods were also applied to determine inflection points for Ghana’s cases and death from COVID-19. The data used for the study covered the first 250 days of events and interventions of the pandemic in Ghana. It was realized that the distribution of the COVID-19 situation in Ghana followed an exponential distribution curve. A modification of the developed model to help optimize the error between observed and estimated values yielded an improvement in the prediction of the delayed phase. Our derived parameters revealed that transmission of the virus between phases depended on changes in the precautionary measures and peoples' behaviors. The study thus shows that Ghana passed her inflection point of reported cases on Sunday 19th July, 2020 and may currently be in the delayed phase characterized with a staggering trend where new infections similar in magnitude to previous infections may upsurge. The correlation between reported cases and deaths revealed linear dependence with positive deviation between accelerated and delayed phases. In conclusion, the study predicted the commencement of a new wave in Ghana after Wednesday October 28, 2020 with higher intensity than what was previously observed if timely impositions of interventions to minimize the effect of the second wave are not taken.

Predicting Medical Fees for Hospitalized Inpatients and the Determination of Inflection Point

Background: Taiwan’s Bureau of National Health Insurance (BNHI) implemented an inpatient DRG payment system scheduled for January 2008. Many hospital managers urgently invent initiatives to decrease the impacts of DRGs. Predicting medical fees for hospitalized inpatients every day and the corresponding inflection points (IPs) are required for investigations. The aims of this study include (1) verifying the efficacy of the exponential growth model on accumulative publications of mobile health research between 1997 and 2016 in the literature; (2) building the model of predicting medical fees for hospitalized inpatients and determining the inflection points; and (3) demonstrating visualizations of the prediction model online in use for hospital physicians.Methods: An exponential growth model was applied to determine the IP and predict the medical fees to help physicians contain the medical fees of a specific patient during hospitalization. The IP is equal to the item difficulty proven using the differential equation in calculus. An online visual display of the medically contained and predicted inpatient hospitalization was demonstrated in this study.Results: We observed (1) a model accuracy (R2 = 0.99) higher than that (R2 = 0.98) in the literature based on identical data; (2) 231 samples of medical fees for inpatients in the study module with a length of days between 6 and 20 and an IPS falling in the range between 1 and 10 (Q1=0.98, Q3=1.00); and (3) online visualization demonstration of medical fees predicted for hospital inpatients and IP determination on ogive curves.Conclusion: The exponential growth model can be applied to a clinical setting to help physicians consecutively predict medical fees for hospitalized inpatients and upgrade the level of hospital management in the future.

Inflection Points, Kinks, and Jumps: A Statistical Approach to Detecting Nonlinearities

Inflection points, kinks, and jumps identify places where the relationship between dependent and independent variables switches in some important way. Although these switch points are often mentioned in management research, their presence in the data is either ignored, or postulated ad hoc by testing arbitrarily specified functional forms (e.g., U or inverted U-shaped relationships). This is problematic if we want accurate tests for our theories. To address this issue, we provide an integrative framework for the identification of nonlinearities. Our approach constitutes a precursor step that researchers will want to conduct before deciding which estimation model may be most appropriate. We also provide instructions on how our approach can be implemented, and a replicable illustration of the procedure. Our illustrative example shows how the identification of endogenous switch points may lead to significantly different conclusions compared to those obtained when switch points are ignored or their existence is conjectured arbitrarily. This supports our claim that capturing empirically the presence of nonlinearity is important and should be included in our empirical investigations.

Analysis of the Influence of Lifestyle on Liver Dysfunction Based on NAHANES Database

ObjectiveTo find out the influence of various factors in life style on liver dysfunction, put forward reasonable suggestions on prevention of liver dysfunction.MethodsDatasets from 2017 to March 2020 NHANES (National Health and Nutrition Examination Surveys) required for the analysis were downloaded from the NHANES web site and R 4.1.1. Software was used for data analysis. Survey Design Logisitic regression was used to analyze the influence of various factors on liver dysfunction and screen the risk factors.Resultshypertension, depression, and sedentary activity are risk factors for liver dysfunction, while reducing salt in diet and vigorous recreational activities were protective factors for liver dysfunction. The inflection points of blood pressure, BMI and sedentary activity were 98.33mmHg, 30.6kg/m2, 420min, respectively.ConclusionsBlood pressure, BMI, mood and sedentary behavior are risk factors for liver dysfunction. We suggest that keeping MAP level at 70-98.33mmHg, controlling BMI < 30kg/m2, maintaining a positive attitude, and sedentary time less than 420 min per day are more conducive to reducing the risk of liver dysfunction.