Physiological Response to Short-Term Heat Stress in the Leaves of Traditional and Modern Plum (Prunus domestica L.) Cultivars

The aim of this study was to evaluate physiological responses to short-term heat stress in the leaves of traditional (Bistrica) and modern (Toptaste) plum cultivars. In this study, detached plum leaves were incubated at 25 °C (control) and 40 °C (stress). After 1 h of exposure to heat (40 °C), chlorophyll a fluorescence transients were measured, and several biochemical parameters were analyzed. Elevated temperature caused heat stress in both plum cultivars, seen as a decrease in water content (WT), but in the leaves of the cultivar Bistrica, an accumulation of proline and phenols, as well as an accumulation of photosynthetic pigments, suggest the activation of a significant response to unfavorable conditions. Conversely, in the leaves of Toptaste, a significant accumulation of malondialdehyde (MDA) and an activation of guaiacol peroxidase (GPOD), all together with a decreased soluble proteins content, indicate an inadequate response to maintaining homeostasis in the leaf metabolism. The impact of an elevated temperature on photosynthesis was significant in both plum cultivars as reflected in the decrease in performance indexes (PIABS and PItotal) and the maximum quantum yield of PSII (Fv/Fm), with significantly pronounced changes found in Toptaste. Unlike the traditional plum cultivar, Bistrica, in the modern cultivar, Toptaste, short-term heat stress increased the minimal fluorescence (F0) and absorption (ABS/RC), as well as Chl b in total chlorophylls. Additionally, the inactivation of RCs (RC/ABS) suggests that excitation energy was not trapped efficiently in the electron chain transport, which resulted in stronger dissipation (DI0/RC) and the formation of ROSs. Considering all presented results, it can be presumed that the traditional cultivar Bistrica has better tolerance to heat stress than the modern cultivar Toptaste. The cultivar, Bistrica, can be used as a basis in further plum breeding programs, as a source of tolerance for high temperature stress.

Numerical Simulation of Rockfill Materials Based on Fractal Theory

With the use of the particle flow code in two dimensions, a fractal model is established with the number of particles of different particle fractions used as the statistics to study the fractal characteristics of particle size distribution. Numerically simulated specimens obtained by four scale methods are subjected to the relative density test and the biaxial compression test to explore the influences of fractal dimension D on the macroscopic and mesomechanical properties of specimens, as well as to study the relationship between fractal dimension D and different mechanical performance indexes. Results show that the particle size distribution of each of the four groups after scale exhibits fractal characteristics, with the fractal dimension D ranging from 1.27 to 2.03. The number of fine particles in the specimen increases with the fractal dimension D, the particle aggregates become more compact, the macroscopic mechanical properties of the specimens are improved, and a linear relationship exists between the fractal dimension D and different mechanical performance indexes. A large fractal dimension D corresponds to a great mesoparticle coordination number.

Demand Based Cost Optimization of Electric Bills for Household Users

Abstract- Internet of Things (IoT) is increasingly becoming the vehicle to automate, optimize and enhance the performance of systems in the energy, environment, and health sectors. In this paper, we use Wi-Fi wrapped sensors to provide online and in realtime the current energy consumptions at a device level, in a manner to allow for automatic control of peak energy consumption at a household, factory level, and eventually at a region level, where a region can be defined as an area supported by a distinct energy source. This allows to decrease the bill by avoiding heavily and controllable loads during high tariff slice and/or peak period per household and to optimize the energy production and distribution in a given region. The proposed model relies on adaptive learning techniques to help adjust the current load, while taking into consideration the actual and real need of the consumer. The experiments used in this study makes use of current and voltage sensors, Arduino platform, and simulation system. The main performance indexes used are the control of a peak consumption level, and the minimum time needed to adjust the distribution of load in the system. The system was able to keep the maximum load at a maximum of 10 kW in less than 10 seconds of response time. The level and response time are controllable parameters.

Optimization and Characterization of Ultrasound-Assisted Pectin Extracted from Orange Waste

The concept of waste to valuable products is a hot topic with exploring ongoing worldwide to minimize food-based feedstocks. This work utilized a citric acid solution and an ultrasoundassisted to extract pectin from orange waste, a critical agroindustry byproduct. Artificial neural network and central composite design were utilized to assess the extraction of pectin using different levels of the extraction parameters and in turn to optimize the extraction process. The extraction of pectin from orange waste is found to be highly affected by pH solution and ultrasound power. The result of an artificial neural network was found to be better in terms of prediction capability and performance indexes. Fourier transform infrared spectrometry analysis confirmed the existence of functional groups in the fingerprint region of orange waste pectin. Ash and crude protein content of orange wastes are found to be low; meaning low ash and protein content contributes to better gelling ability of the pectin. The extracted pectin has a higher degree of esterification. The result of the current work highlighted that orange wastes are a good source of pectin. In addition, the extracted pectin from orange wastes can be used as a food additive as it fulfills all the standard requirements pectin for application.

Tests Research on Grouting Materials of Waste-Concrete-Powder Cement for Goaf Ground Improvement

Waste concrete powder (WCP) is proposed to replace part of the cement to seek environmentally friendly grouting materials for ground improvement in mine goaf. The optimal mixing proportion was selected based on the performance indexes of the water-separation ratio, stone rate, viscosity, setting time, and compressive strength. X-ray diffraction (XRD) and scanning electron microscopy (SEM) tests were also conducted to analyze mineralogical phases and investigate the microscopic mechanism. Test results show that the slurry prepared by the substitution rate of 70% and adding 0.05% water-reducing agent meets well the requirements of ground grouting in mine goaf. The WCP produced by grinding mainly exerts microaggregate effect in the slurry due to low activity. A lot of pores on the surface of WCP were shown by SEM which can absorb the water in the slurry and increase the stone rate. The WCP application for ground grouting in mine goaf can not only recycle WC but also provide new grouting materials for goaf ground.

Evaluation of investment funds through different performance measures

Purpose - The aim of this study is to examine the evaluation of Brazilian equity funds from different performance measures. Theoretical framework - In the literature, several indexes are available that can be used to evaluate the performance of investment funds. Design/methodology/approach - Monthly return data were collected from 1,901 Brazilian equity funds. Fund performance was estimated using four indexes: the Sharpe ratio, the Sortino ratio, Jensen’s alpha, and the Treynor ratio. Findings - The results showed that all four performance measures are positively associated. This means that there are no significant differences in the ranking of Brazilian equity funds in terms of performance. Research, Practical & Social implications - The comparison of different performance indexes contributes to the literature on the subject by providing further data for researchers to adequately define the indexes considered in studies on the performance of funds. Originality/value - This study fills a gap in the literature regarding the analysis of performance measures of investment funds. Keywords - Mutual funds. Equity funds. Performance.

Application of non-equidistant GM(1,1) model based on the fractional-order accumulation in building settlement monitoring

Non-equidistant GM(1,1) (abbreviated as NEGM) model is widely used in building settlement prediction because of its high accuracy and outstanding adaptability. To improve the building settlement prediction accuracy of the NEGM model, the fractional-order non-equidistant GM(1,1) model (abbreviated as FNEGM) is established in this study. In the modeling process of the FNEGM model, the fractional-order accumulated generating sequence is extended based on the first-order accumulated generating sequence, and the optimal parameters that increase the prediction precision of the model are obtained by using the whale optimization algorithm. The FNEGM model and the other two grey prediction models are applied to three cases, and five prediction performance indexes are used to evaluate the prediction precision of the three models. The results show that the FNEGM model is more suitable for predicting the settlement of buildings than the other two grey prediction models.

Power Performance Assessment for the Energy Storage Type of Wave Energy Converter

This paper discusses the energy matching problem between wave energy input and generator power output, in the power performance assessment for the energy storage type of wave energy converter. Under the small wave condition, the power performance of the energy storage type of wave energy converter is researched. The site test data processing method is analyzed, and the calculation method of the average conversion efficiency and the annual energy production are optimized. The results show that the optimized power performance analysis method can more accurately assess the power performance matrix of the wave energy converter, and improve the calculation accuracy of the average conversion efficiency and the annual energy production of the wave energy converter. The research results provide an effective method for more scientific and accurate evaluation of power performance indexes of the energy storage type of wave energy converters.

Forced Sliding Mode Control for Chaotic Systems Synchronization

Synchronization of chaotic systems is considered to be a common engineering problem. However, the proposed laws of synchronization control do not always provide robustness towards the parametric perturbations. The purpose of this article is to show the use of synergy-cybernetic approach for the construction of robust law for Arneodo chaotic systems synchronization. As the main method of design of robust control, the method of design of control with forced sliding mode of the synergetic control theory is considered. To illustrate the effectiveness of the proposed law it's compared in this article with the classical sliding mode control. The distinctive features of suggested robust control law are the more good compensation of parametric perturbations (better performance indexes --- the root-mean-square error, average absolute value of error) without designing perturbation observers, the ability to exclude the chattering effect, less energy-consuming and a simpler analysis of the stability of a closed-loop system. Offered approach will allow a new consideration for the design of robust control laws for chaotic systems, taking into account the ideas of directed self-organization and robust control. It can be used for synchronization other chaotic systems.Mathematics Subject Classification (2020) 93B35 · 93B52 · 93C30 · 93D21 · 34H10

UAV low-altitude obstacle detection based on the fusion of LiDAR and camera

In this paper, aiming at the flying scene of the small unmanned aerial vehicle (UAV) in the low-altitude suburban environment, we choose the sensor configuration scheme of LiDAR and visible light camera, and design the static and dynamic obstacle detection algorithms based on sensor fusion. For static obstacles such as power lines and buildings in the low-altitude environment, the way that image-assisted verification of point clouds is used to fuse the contour information of the images and the depth information of the point clouds to obtain the location and size of static obstacles. For unknown dynamic obstacles such as rotary-wing UAVs, the IMM-UKF algorithm is designed to fuse the distance measurement information of point clouds and the high precision angle measurement information of image to achieve accurate estimation of the location and velocity of the dynamic obstacles. We build an experimental platform to verify the effectiveness of the obstacle detection algorithm in actual scenes and evaluate the relevant performance indexes.