Parameter Fluctuations Research Articles

Oscillatory and negative magnetoresistance in granular nanowires of superconducting NiBi3

Local fluctuations in the superconducting order parameters in granular systems show interesting magnetotransport behavior, particularly relevant to superconducting nanowires. Kivelson and Spivak [Phys. Rev. B 45, 10490 (1992)] have shown that fluctuations in density and signs of supercurrent can lead to oscillating and negative magnetoresistance (MR). Here, we present magnetoresistance measurements of 100 nm wide NiBi3 superconducting nanowires, patterned by focused ion beam lithography, from granular NiBi3 films containing different concentrations of magnetic Ni impurities. The nanowire containing a higher concentration of Ni impurity showed oscillations in MR and simultaneously exhibited negative MR in certain temperature and field ranges. None of these effects were observed in the nanowire with nearly no Ni impurities. Unlike earlier experiments, we argue that excess magnetic Ni impurities in the nanowire realize a case of simultaneous magnitude and sign fluctuations in local order parameter, leading to MR oscillations and MR sign reversal in the same system, as discussed by Kivelson and Spivak. This result is important in the context of transport in superconducting quantum circuits.

Terahertz field-induced metastable magnetization near criticality in FePS3.

Controlling the functional properties of quantum materials with light has emerged as a frontier of condensed-matter physics, leading to the discovery of various light-induced phases of matter, such as superconductivity1, ferroelectricity2,3, magnetism4-6 and charge density waves7. However, in most cases, the photoinduced phases return to equilibrium on ultrafast timescales after the light is turned off, limiting their practical applications. Here we use intense terahertz pulses to inducea metastable magnetization with a remarkably long lifetime of more than 2.5 milliseconds in the van der Waals antiferromagnet FePS3. The metastable state becomes increasingly robust as the temperature approaches the antiferromagnetic transition point, suggesting that critical order parameter fluctuations play an important part in facilitating the extended lifetime. By combining first-principles calculations with classical Monte Carlo and spin dynamics simulations, we find that the displacement of a specific phonon mode modulates the exchange couplings in a manner that favours a ground state with finite magnetization near the Néel temperature. This analysis also clarifies how the critical fluctuations of the dominant antiferromagnetic order can amplify both the magnitude and the lifetime of the new magnetic state. Our discovery demonstrates the efficient manipulation of the magnetic ground state in layered magnets through non-thermal pathways using terahertz light and establishes regions near critical points with enhanced order parameter fluctuations as promising areas to search for metastable hidden quantum states.

Few-to-many-particle crossover of pair excitations in a superfluid

Motivated by recent advances in the creation of few-body atomic Fermi gases with attractive interactions, we study theoretically the few-to-many-particle crossover of pair excitations, which for large particle numbers evolve into a mode that describes amplitude fluctuations of the superfluid order parameter (the “Higgs” mode). Our analysis is based on the hypothesis that salient aspects of the excitation spectrum are captured by interactions between time-reversed pair states in a harmonic oscillator potential. Microscopically, this assumption leads to a Richardson-type pairing model, which is integrable and thus allows a systematic quantitative study of the few-to-many-particle crossover with only minor numerical effort. We first establish a parity effect in the ground-state energy, i.e., a spectral convexity in the energy of open-shell configurations compared to their closed-shell neighbors, which is quantified by a so-called Matveev-Larkin parameter discussed for mesoscopic superconductors, which generalizes the pairing gap to mesoscopic ensembles and which behaves quantitatively differently in a few-body and a many-body regime. The crossover point for this quantity is widely tunable as a function of interaction strength. We then compute the excitation spectrum and demonstrate that the pair excitation energy shows a minimum that deepens with increasing particle number and shifts to smaller interaction strengths, consistent with the finite-size precursor of a quantum phase transition to a superfluid state. We extract a critical finite-size scaling exponent that characterizes the decrease of the gap with increasing particle number. Published by the American Physical Society 2024

Net-shaping (Y,NSG)BCO composite superconductor into cylindrical geometry with enhanced flux pinning up to 9 T at 77 K

Abstract Fabrication of a (Y,RE)BCO superconducting compact simultaneous with improved properties is demonstrated using gelcasting of slurries into rapid prototyped precision moulds. The infiltration Growth (IG) process with NdBCO film seed was used to obtain a textured 45 mm long hollow superconducting (Y,RE)BCO cylinder, as a prototype. This involves design of a (Y,RE)2BaCuO5 preform referred to as (Y,RE)-211, into which liquid phase is infiltrated; this reacts with the preform and forms (Y,RE)Ba2Cu3O7-x. The end product aimed at is a composite of YBa2Cu3O7-x (YBCO) with 20 wt% of mixed rare earth (Nd,Sm,Gd)BCO and 0.5 wt% of WO3 nanoparticles, which are intended to cause notable enhancement in flux pinning and critical current density (J c). Uniform distribution of micron-sized (Y/RE)-211 and WO3 nanoparticles in the matrix was enabled by sol-casting process. Magnetic shielding is demonstrated at low dc fields (41 gauss). J c is found to remain nearly constant with field (B) at each temperature (T) up to 50 K, where J c reaches about 4 kA cm−2 at 8.5 T. At 77 K, J c of ∼ 4 kA cm−2 at zero field and ∼ 0.4 kA cm−2 at 8.5 T is observed. The flux pinning force density (F p) increased with the applied field, reaching a maximum at a field (B p) of 7 T to 8 T for all temperatures from 10 K to 77 K. Temperature-independent B p confirms that flux pinning is caused by structural defects that induce fluctuations in the Ginzberg-Landau parameter (k). Substitution of RE ions randomly at the Y-site in YBCO unit cells can locally create compositional fluctuations that lead to stress fields and a dense network of stacking faults and assist pinning of flux. Analysis of F p (B) by scaling laws does confirm δk pinning to be the dominant mechanism. A second peak observed in F p(B) curves at low fields, below 3 T, is attributed to additional pinning from WO3 nanoparticles and is field-dependent. Significance of the present process stems from the fact that it enables uniform distribution of second phase additions to be realized in the end product, for improved performance and it allows design and creation of components of composite ceramic superconductor in any complex shape, required for a chosen application.

A Neural Controller Design for Enhancing Stability of a Single Machine Infinite Bus Power System

This paper examines the formulation and implementation of a neuro-controller for the excitation system of synchronous generators in a Single-Machine Infinite Bus (SMIB) power system. The SMIB model is employed as a fundamental model of a power system, thereby facilitating the assessment and comparison of disparate control strategies with the objective of enhancing system stability. The goal of this study is to enhance the stability of the SMIB power system through the implementation of an Artificial Neural Network (ANN) neuro-controller, providing a comparison of its performance to that of a Power System Stabilizer (PSS) and a Proportional-Integral-Derivative (PID) controller. The proposed neuro-controller will be integrated into the generator's excitation system and will be designed to regulate the excitation voltage in response to fluctuations in the system's operational parameters. To this end, an ANN is calibrated to account for the singularity of the generator's excitation level and terminal voltage. The Levenberg-Marquardt algorithm is employed to ascertain the optimal weight coefficients for the ANN. To assess the performance of the neuro-controller, simulations were conducted using MATLAB/Simulink. The simulations encompass a comprehensive range of operational scenarios, including diverse disturbances and alterations in the reference voltage level. Subsequently, the neuro-controller's outputs are evaluated in comparison to the PSS and PID controllers, as these are the prevailing controllers used to enhance voltage regulation and transient stability in power systems. This paper presents the results of an analysis of the neuro-controller's impact on the system's robustness, voltage variation amplitude, and generator dynamic performance during faults. Simulation results demonstrate that the application of an ANN-based neuro-controller yields superior outcomes in voltage regulation and transient stability compared to the conventional controllers PSS and PID. Furthermore, the neuro-controller is distinguished by accelerated response times and enhanced precision in voltage level regulation. The neuro-controller represents a superior approach to the control of a power system, particularly in the context of SMIB, which would ultimately result in enhanced performance and stability.

Trade Globalization, Overseas Investment, and Tax Revenue Growth in Sub-Saharan Africa

Abstract The financial setbacks of the sub-Saharan African regions have necessitated this study. The study assesses the role of trade openness and foreign direct investment (FDI) in driving tax revenue growth in sub-Saharan Africa. The major parameter representing the dependent variable is tax revenue growth while the independent factors include trade openness, exports, imports, and GDP as a moderating element. The research runs from 1990 to 2022 and employs the vector error correction model (VECM), with a unit root test that yields order one, while the Johansen co-integration test shows a long-run connection for all variables. The VECM results suggest that the long-run disequilibrium is corrected at a positive rate of 8.5%. It is also noteworthy that a percentage change in trade openness would result in a 13.7% decrease in tax income, but fluctuations in all other parameters except GDP will enhance tax revenue growth in sub-Saharan Africa. The test for the impact of all criteria on tax revenue growth yields minor results; however, tax revenue growth initiatives in Sub-Saharan Africa have a negative short- term effect on FDI but a favourable long-term impact. In addition, trade openness has a negative effect on GDP and exports in the short run, while imports have a negative impact on foreign investment. The policy implications include that bilateral trade policies will need to be reviewed, with an emphasis on exports, economic growth, and tax collection schemes. In addition, the governments in sub-Saharan African regions are encouraged to enact tax policies that would engender the inflow of overseas investment.

Enhanced Accuracy in State-of-Charge Estimation for Lithium-Ion Batteries in Electric Vehicles Using Augmented Adaptive Extended Kalman Filter

Accurate assessment of state of charge (SoC) is crucial for the safety and efficiency of lithium-ion batteries used in electric vehicles (EVs). For precise SoC estimation in EV BMSs, an Augmented Adaptive Extended Kalman Filter (AAEKF) has been proposed in this research. To improve the precision of SoC estimation, AAEKF approach combines Kalman filtering methods with adaptive robust control concepts. The effectiveness of the AAEKF algorithm is shown by simulation results and confirmed by comparison with data from LiFePO4 battery research. The proposed AAEKF SoC estimation matches measurement results with errors of less than 3%. Adaptive Extended Kalman Filter (AEKF) is quite sensitive to the accuracy of the battery model, as errors in this region can lead to large estimate errors. Faster convergence to actual SoC, improved real-time responsiveness, accuracy, and resilience to disturbances and parameter fluctuations are all results of AAEKF's efficient handling of nonlinearities in battery systems, adaptation to system changes, errors (Root Mean Square Error (RMSE) and Mean Absolute Error (MAE), and overall performance. The maximum estimate error stays under 5% at various external temperatures.

A molten salt energy storage integrated with combined heat and power system: scheme design and performance analysis

To investigate the flexibility and economic characteristics of a molten salt-combined heat and power (CHP) integrated system under different heat sources, this paper proposes a design scheme for a molten salt-CHP system based on flue gas heat storage, comparing it with main steam heat storage and reheated steam heat source schemes. First, a molten salt heat release sub-loop is designed, where the steam heated by the molten salt can either compensate for heating demands or enter the low-pressure turbine for work, meeting the flexible operation requirements of the unit. Secondly, in response to fluctuations in temperature and pressure parameters of the main steam and reheated steam in the flue gas heat storage scheme, a water-spray desuperheating device is arranged. Finally, a simulation experiment based on a 350 MW CHP was conducted, and the results show that the flue gas molten salt heat storage technology significantly reduces energy loss on the boiler side. Underrated load, compared to the main steam and reheated steam heat storage schemes, the flue gas heat storage scheme has the highest boiler exergy efficiency and total energy utilization efficiency, at 55.8% and 59.1% respectively. During the thermal storage process, the coal consumption index of the flue gas heat storage scheme decreases with increasing load, while conversely, during the heat release process, it increases with the load. The peak-shaving capacity increases with the load, reaching 78.4 MWh under the 75% THA condition. In the steam extraction heating scenario, coupling with the molten salt subsystem can expand the safe heating operation range of the original unit, increasing the maximum peak shaving range by 13.9%, and increasing the maximum heating capacity by 65.4%.

Influence of Axial Flow Field Parameter Fluctuations on Performance of Scramjet Combustor

Abstract When air-breathing aircraft is flying over a wide area, the upflow of the combustor central axis will change greatly, and the flow field parameters will fluctuate along the axis. Therefore, it is necessary to carry out a study on the influence of axis flow field parameter fluctuation on combustion chamber performance, so as to provide relevant theoretical support for the combustion chamber of air-breathing aircraft in wide-area flight design. Based on the N-S gas-phase control model, combined with combustion model, turbulence model, burning rate model and mass transfer model, a numerical simulation model of flow combustion in solid fuel scramjet combustor is established. Through this model, the influence of the upflow field parameter fluctuation of the central axis on the combustor performance is carried out. The results show that for a optimized combustor configuration, different inlet air flow rates will cause the Mach number of the combustor to oscillate along the flow direction. The greater the oscillation amplitude, the greater the total pressure loss. Too high or too low inlet air flow rate will both result in Mach number oscillation in the combustor. However, selecting a suitable inlet air flow rate can significantly reduce the Mach number oscillation of combustor flow. Therefore, for different combustor configurations, appropriate inlet air flow should be designed to reduce the Mach number oscillation of the flow field in the combustor, reducing the flow loss and improving the working performance of the combustor.

Robust controller design strategies with improved performance for MSBR core

Designing controllers for power regulation of nuclear reactors is a challenging task because of its non-linear behavior, and fluctuation of system parameters over time in response to changes in power levels. Motivated by the aforementioned fact, proportional-integral (PI) controllers are designed in this manuscript to regulate the core power of the molten salt breeder reactor (MSBR) by employing the all stabilizing region and quantitative feedback theory (QFT) technique. In the first approach, the entire stability region is plotted in the (Kp,Ki)-plane. In order to ensure safe operation, the reactivity of control rods must lie in the specified range. Hence, the control effort constrained stability region (CECSR) is obtained within the all stability region to design the PI controller. A novel PI controller and a pre-filter based on gain-phase shaping on Nichols chart are also proposed. Robustness, disturbance rejection and relative stability of the system are addressed by obtaining the performance bounds on Nichols chart. Simulation results illustrate that the closed-loop system is exhibiting a noteworthy improvement in the closed loop performance over the latest reported control strategies.

Reflexive eye saccadic parameters in Parkinson's disease.

Abnormal reactive saccade, with reduced saccadic gain, impaired smooth pursuit, and unwarranted reactions are clinically used to assess people with Parkinson's disease (PwPD). However, there are inconsistent findings related to other saccade parameters such as latency and transition times. This study aimed to identify differences in the reflexive saccade parameters of early stage PwPD and aged-matched control (AMC). In this observational study, the reactive eye-gaze was recorded for 70 participants (42 PwPD) and parameters of reflexive saccades and eye-gaze fluctuations were extracted. These parameters were then statistically analyzed using the Mann-Whitney -test. Results showed that PwPD had significantly shorter latency than AMC for reflexive saccadic movement away from the center of the screen. The overshoot as a fraction of the screen width, a measure of the inaccuracy in reaching the target, was also significantly higher for PwPD. PwPD had greater horizontal and vertical eye gaze fluctuation with a steady target. The numbers of invalid saccades, i.e., when the gaze goes in the opposite direction from the target movement or is considered anticipatory, were similar for both groups; PwPD with 33.43% and AMC with 25.71%. This study shows that there are significant differences in the reflexive saccade of PwPD and AMC measured using an inexpensive eye-tracking device. The presence of invalid saccade trials, and differences between towards and away from screen center, both of which were not considered in earlier studies, may explain the discrepancies between earlier studies. The outcome of this study has the potential to be made a device that would assist neurologists in the assessment of PwPD.

Power controller design for electrolysis systems with DC/DC interface supporting fast dynamic operation: A model-based and experimental study

The ability of the electrolysis system, powered by fluctuating and intermittent renewable sources, to rapidly and accurately track power signals is crucial for energy management in renewable power-to-hydrogen (ReP2H) plants and for providing grid frequency regulation as a virtual power plant (VPP). However, there is a considerable lag (several seconds or even more than 20 s) between the changes of the stack power compared with the stack current, mainly due to the existence of the electric double-layer (EDL) effect. This characteristic hinders the further application of electrolysis systems as flexible loads in power grids. By designing a suitable power controller in the power-electronics interface directly connected to the stack to replace the traditional current controller, it is expected to improve the fast dynamic response of the stack power. This paper proposes a unified electrical equivalent circuit for alkaline water electrolysis (AWE) systems and proton exchange membrane (PEM) electrolysis system with detailed parallel Buck type DC/DC interface, which considers the EDL effect and nonlinear behaviors of electrolysis systems and is suitable for controller design. A power controller design and robust parameter tuning method without excessive current overshoot based on frequency-domain analysis is proposed. The accuracy and effectiveness of the proposed model and method are verified by the experimental test on the 2 N m3/h(10 kW) AWE system and the 1 N m3/h(5 kW) PEM electrolysis system. With the proposed power controller, the AWE and PEM electrolysis system can change the stack power within 0.266s and 0.21s respectively, meeting the requirements of energy management and frequency regulation. Additionally, the temperature stability and the sensitivity of the proposed method to parameter fluctuations in the stack and DC/DC interface are analyzed.

Optimized Energy Management Strategy for an Autonomous DC Microgrid Integrating PV/Wind/Battery/Diesel-Based Hybrid PSO-GA-LADRC Through SAPF

This study focuses on microgrid systems incorporating hybrid renewable energy sources (HRESs) with battery energy storage (BES), both essential for ensuring reliable and consistent operation in off-grid standalone systems. The proposed system includes solar energy, a wind energy source with a synchronous turbine, and BES. Hybrid particle swarm optimizer (PSO) and a genetic algorithm (GA) combined with active disturbance rejection control (ADRC) (PSO-GA-ADRC) are developed to regulate both the frequency and amplitude of the AC bus voltage via a load-side converter (LSC) under various operating conditions. This approach further enables efficient management of accessible generation and general consumption through a bidirectional battery-side converter (BSC). Additionally, the proposed method also enhances power quality across the AC link via mentoring the photovoltaic (PV) inverter to function as shunt active power filter (SAPF), providing the desired harmonic-current element to nonlinear local loads as well. Equipped with an extended state observer (ESO), the hybrid PSO-GA-ADRC provides efficient estimation of and compensation for disturbances such as modeling errors and parameter fluctuations, providing a stable control solution for interior voltage and current control loops. The positive results from hardware-in-the-loop (HIL) experimental results confirm the effectiveness and robustness of this control strategy in maintaining stable voltage and current in real-world scenarios.

Self-adjusting voxelated electrochemical three-dimensional printing of metallic microstructures

Abstract Microscale metallic structures enhanced by additive manufacturing technology have attracted extensive attention especially in microelectronics and electromechanical devices. Meniscus-confined electrodeposition (MCED) advances microscale 3D metal printing, enabling simpler fabrication of superior metallic microstructures in air without complex equipment or post-processing. However, accurately predicting growth rates with current MCED techniques remain challenging, which is essential for precise structure fabrication and preventing nozzle clogging. In this work, we present a novel approach to electrochemical 3D printing that utilizes a self-adjusting, voxelated method for fabricating metallic microstructures. Diverging from conventional voxelated printing which focuses on monitoring voxel thickness for structure control, this technique adopts a holistic strategy. It ensures each voxel’s position is in alignment with the final structure by synchronizing the micropipette’s trajectory during deposition with the intended design, thus facilitating self-regulation of voxel position and reducing errors associated with environmental fluctuations in deposition parameters. The method’s ability to print micropillars with various tilt angles, high density, and helical arrays demonstrates its refined control over the deposition process. Transmission electron microscopy analysis reveals that the deposited structures, which are fabricated through layer-by-layer (voxel) printing, contain nanotwins that are widely known to enhance the material’s mechanical and electrical properties. Correspondingly, in situ scanning electron microscopy (SEM) microcompression tests confirm this enhancement, showing these structures exhibit a compressive yield strength exceeding 1 GPa. The indentation tests provided an average hardness of 3.71 GPa, which is the highest value reported in previous work using MCED. The resistivity measured by the four-point probe method was (1.95 ± 0.01) × 10−7 Ω·m, nearly 11 times that of bulk copper. These findings demonstrate the considerable advantage of this technique in fabricating complex metallic microstructures with enhanced mechanical properties, making it suitable for advanced applications in microsensors, microelectronics, and micro-electromechanical systems.

Spatiotemporal Fluctuation in Water Quality Parameters and Correlation with Phytoplankton Community at Sambhar Salt Lake, India

Spatiotemporal Fluctuation in Water Quality Parameters and Correlation with Phytoplankton Community at Sambhar Salt Lake, India

Dynamics of Barred Coast at Different Temporal Scales (by the Example of Vistula Spit in the Baltic Sea)

According to fundamental concepts, the morphodynamic system of an accumulative sandy coast with underwater bars exhibits cyclic behavior across various time scales. This raises the question: which factor is more significant for the dynamics of a given coast—individual storms or seasonal changes in wave activity? While observations and studies addressing this issue have primarily been conducted on oceanic coasts, there is a lack of comparable data for fetch-limited areas. Monitoring of the bottom topography along the west coast of Vistula Spit (Baltic Sea) revealed a cyclic behavior in morphology, transitioning from a straightened external bar to its connection with the shore. Analysis of field measurement results indicated that seasonal variations in wave intensity do not significantly impact coastal relief. Furthermore, it was found that the complete cycle of underwater bar evolution lasts approximately two years, during which the coast profile maintains a stable shape at the stage of the straightened external bar. The identification of the primary factor influencing coastal evolution can be characterized by the Dean number (Ω), which combines wave parameters (wave height and period) with sediment fall velocity. Utilizing ERA5 wave reanalysis data, we compared the variability of Ω values on both annual and monthly scales. The analysis revealed that for the section of the coast under consideration, there is no clearly dominant evolutionary factor; rather, the coast is influenced approximately equally by individual storm events and seasonal fluctuations in wave energy. Modeling storm-induced bed profile deformations using the CROSS-PB model demonstrated that the position of the external underwater bar remains nearly constant even during intense and prolonged storms. It is concluded that under specific conditions—determined by a combination of sediment size, coastal slope, and wave regime characteristics—the coast can remain stable, exhibiting minimal response to relatively strong storms and seasonal variations in wave energy. Such coasts are characterized by an absence of a dominant evolutionary factor as indicated by fluctuations in the Dean parameter, allowing their morphodynamic cycles to span several seasons. This type of morphodynamics in coastal accumulative relief appears to be typical for conditions found in fetch-limited areas, such as regional and semi-closed seas.

Comprehensive water quality indicators modeling by environmental protection view using multi optimized weighted ensemble machine learnings

The environmental protection water quality is a critical subject in dominance of the sustainable water resources management. Accordingly, the essential indicators of water quality were considered, which are not only appropriate indicators for water quality, but they can also serve as crucial indicators for the health of water environment and ecosystems. Therefore, this study uses well-known ensemble machine learning methodologies to investigate and predict the fluctuations of water quality parameters. Optimization procedures used to assemble machine learnings were non-linear programming (NLP), genetic, gradient descent, and least square algorithms, linear programming, particle swarm optimization, Nelder-Mead optimization, and simulating annealing optimization. Using optimization procedures, the basic MLs were assembled and eight new ensemble machine learning were developed. The studied area was the South Platte River basin, USA. The primary dataset was obtained through the online database of the United States Geological Survey, which contained sampling information on river water related to 2023–2024. Then, using clean missing and outlier data preprocessing techniques, the dataset was modified. Finally, using the 10-fold cross-validation technique, the primary data was validated. The results showed that NLP significantly improved the accuracy and performance of models, achieving the best performance with R2 of 0.9836 and 0.9031 across DO and pH modelings. The modeling results indicated that the pH parameter fluctuated within the safe range. While the DO seems that tolerated in unsafe domain for aquatic ecosystems. The findings of this research could help a wide range of decision-makers.

The Discrete Grey Power Model Based on Aging Accumulation and its Application

Abstract Accumulation generation is one of the key methods to reduce the randomness of data series, which significantly enhances the predictive performance of the grey prediction model. By integrating a degenerate operator, a novel accumulating discrete grey power model is introduced, capable of substantially enhancing the accuracy of predictions. This method allows for the flexible adjustment of the accumulation coefficient in the modeling data, mitigating the fluctuations in model parameters due to data perturbations, and effectively minimizing the loss of differential information. The outcomes of practical numerical examples demonstrate that the proposed aging accumulation discrete grey power model exhibits superior performance.

INVESTIGATION OF PARAMETRIC OSCILLATORY MOVEMENTS IN THE AUTOMOTIVE SYSTEM

The aim of the study is to understand the stability of automotive systems by studying parametric oscillations. The Mathieu function is used to calculate the eigenvalues of the system, which are crucial for determining the behavior of the system over time. The results of the study reveal the resonance zone of the system and provide an algorithm for calculating the eigenvalues of Mathieu functions. The results of this study can be applied to the analysis of various transport systems to assess their stability. This knowledge can be used to improve the comfort and performance of vehicles by minimizing the impact of parametric fluctuations. The study concludes that the analysis of parametric fluctuations in automotive systems can provide valuable information about the stability of the system. For a deeper analysis, the study suggests that numerical integration should be used when the modulation depth is low. This approach will allow you to get a more accurate understanding of the management of the system.

Physicochemical and Nutritional Evaluation of Mango Purees from the Savanes District under Different Storage Conditions

Mangoes are perishable commodities subject to continuous changes which lead to post-harvest losses. Thus, developing effective conservation methods is necessary in order to reduce these losses. Main objective of this study was to evaluate the impact of storage at 4°C and 25°C on the physicochemical and nutritional properties of mango purees from 3 departments (Boundiali, Korhogo and Sinématiali) of the district of savannahs. After stabilization of the purees, the physicochemical and nutritional parameters were determined according to standardized methods. Results of the study revealed fluctuations in parameters during storage. After 4 weeks of storage at 4°C, the moisture content, pH and acidity oscillated between 82.90 ± 0.20 – 88.61 ± 0.70%, 3.50 ± 0.05 – 4.21 ± 0.02 and 6.00 ± 0.02 – 8.66 ± 0.30 meq/, respectively. 100g. As for storage at 25°C after 4 weeks, these parameters varied respectively between 82.90 ± 0.20 – 93.23 ± 0.55%, 3.21 ± 0.12 – 4.21 ± 0.02 and 6.00 ± 0.02 – 9.10 ± 0.02 meq/100g. Residual nutrient contents after 4 weeks at 4 °C were included: soluble dry extract (18 ± 0.00 – 13.33 ± 0.17 °Brix), reducing sugars (0.35 ± 0.02 – 0.89 ± 0.02 %), total sugars (0.73 ± 0.04 – 1 .19 ± 0.11 %), proteins (3.97 ± 0.15 – 5.87 ± 0.26%) and vitamin C (6.56 ± 0.09 – 11.15 ± 0.05 mg/100g). After 4 weeks of storage at 25°C, the variations were as follows: soluble dry extract (18 ± 0.00 – 11 ± 0.00 °Brix), reducing sugars (0.28 ± 0.03 – 0.89 ± 0.02%), total sugars (0.49 ± 0.01 – 1.19 ± 0.11 %), proteins (3.97 ± 0.15 – 9.40 ± 0.15%) and vitamin C (4.86 ± 0.10 – 11.15 ± 0.05 mg/100g). In view of these results, it would be desirable to keep the purees stabilized at 4°C and 25°C for respectively no more than 4 weeks and 2 weeks in order to contribute to the food security of the Ivorian population.