Search Results (297)

With the continuous expansion of data center scales worldwide, the problem of energy consumption has become increasingly prominent. To address the multi-parameter control challenge in environmental temperature regulation for large data center computer rooms, achieve precise control of hot-aisle temperatures in data centers, and reduce energy waste, this paper designs a multi-parameter model-free adaptive control (MMFAC) algorithm suitable for computer room environmental temperatures. The algorithm integrates the model-free adaptive control (MFAC) algorithm with a weight matrix to perform scaling transformations. Considering the large parameter space of the MFAC controller and the dynamic complexity of data center temperature control systems, compact-form dynamic linearization (CFDL) technology and optimization mathematical methods are used to simplify the parameter identification of the pseudo-Jacobian matrices and the calculation of control quantities for the regulation devices. Simulation experiments based on measured data from a data center show that the proposed algorithm can calculate control quantities for equipment such as air conditioners according to real-time environmental parameter measurements and drive each device based on these control quantities. Meanwhile, the algorithm can reduce errors in key parameters by adjusting the weight matrix. Comparative tests with other control algorithms show that the algorithm has faster response in temperature control and smaller control errors, verifying the effectiveness and application prospects of the algorithm in data center temperature control. Full article

To achieve energy transition, hydrogen and carboxylic acids have attracted much attention due to their cleanliness and renewability. Anaerobic fermentation technology is an effective combination of waste biomass resource utilization and renewable energy development. Therefore, the utilization of anaerobic fermentation technology is expected to achieve efficient co-production of hydrogen and carboxylic acids. However, this process is fundamentally affected by gas–liquid mass transfer kinetics, bubble behaviors, and system partial pressure. Moreover, the related studies are few and unfocused, and no systematic research has been developed yet. This review systematically summarizes and discusses the basic mathematical models used for gas–liquid mass transfer kinetics, the relationship between gas solubility and mass transfer, and the liquid-phase product composition. The review analyzes the roles of the headspace gas composition and partial pressure of the reaction system in regulating co-production. Additionally, we discuss strategies to optimize the metabolic pathways by modulating the gas composition and partial pressure. Finally, the feasibility of and prospects for the realization of hydrogen and carboxylic acid co-production in anaerobic fermentation systems are outlined. By exploring information related to gas mass transfer and system pressure, this review will surely provide an important reference for promoting cleaner production of sustainable energy. Full article

Given the growing relevance of issues of educational inclusion at an international level, educational curricula have pointed out the need to address the diversity of students in the classroom. In this article, a theoretical reflection is proposed around the Universal Design for Learning (UDL) guideline—as inclusive principles for generic teaching and learning processes—and Didactic Suitability Criteria (DSC) guideline—as specific principles for mathematical teaching and learning processes—to establish relationships and seek complementarities between both references. To this end, firstly, a document analysis of literature about UDL was conducted; secondly, UDL and DSC guidelines were contrasted, relating UDL principles and verification points to DSC components and indicators to design a first proposal of an integrated guideline between both references; and, thirdly, an expert validation was conducted with researchers familiar with DSC to adjust the guideline originally proposed. As a main result, a proposal of integration of the UDL and DSC guidelines was designed, which intends to organise the reflection of (prospective and practising) mathematics teachers on their teaching practice. This integrated proposal not only seeks to address current curricular needs, but also to delve deeper into theoretical development that contributes to refining existing tools to encourage reflection on teaching practice. Full article

Mathematical modeling and computer visualization of hazardous zones of toxic substance cloud spread that occur during different accidents at industrial enterprises located near residential areas are in high demand to support the operational planning of evacuation measures and accident response. The possible chain-like nature of fires and explosions of containers with toxic substances inside increases the importance of predicting changes in hazardous zone parameters in real time. The objective of this study is to develop algorithms for the development of a mathematical model of a hazardous zone during an explosion and fire at an enterprise. The subject of this study is a software tool created for the visualization of hazardous substance emission zones in real time, superimposed onto a development map to determine potential damage to human health and for the operational planning of evacuation measures. The proposed model takes into account variables such as the air temperature, wind speed and direction, the mass of the substance at each explosion and fire site, etc. C# and Visual Studio 2022 languages and an SQL database were used to create a software tool for visualizing the hazardous area. The testing of the calculation model and software used for the visualization of the hazardous zones of toxic substance cloud spread are presented on the basis of explosion cases involving a railway tank containing ammonia and the combustion of polyvinyl chloride at a chemical industry enterprise. The results confirmed the operability of the software and the prospects of its use in regard to the mitigation of the consequences of human-made accidents. Full article

This study explores the viral dynamics of SARS-CoV-2 infection within host cells by incorporating the pharmacological effects of andrographolide—a bioactive compound extracted from Andrographis paniculata, renowned for its antiviral, anti-inflammatory, and immunomodulatory properties. Through the application of mathematical modeling, the interactions among the virus, host cells, and immune responses are simulated to provide a comprehensive analysis of viral behavior over time. Two distinct models were employed to assess the impact of varying andrographolide dosages on viral load, target cell populations, and immune responses. One model revealed a clear dose–response relationship, whereas the other indicated that additional biological or pharmacological factors may modulate drug efficacy. Both models demonstrated stability, with basic reproductive numbers (R₀) suggesting the potential for viral propagation in the absence of effective therapeutic interventions. This study emphasizes the significance of understanding the pharmacokinetics (PK) and pharmacodynamics (PD) of andrographolide to optimize its therapeutic potential. The findings also underscore the necessity for further investigation into the compound’s absorption, distribution, metabolism, and excretion (ADME) characteristics, as well as its prospective applications in the treatment of not only COVID-19 but also other viral infections. Overall, the results lay a foundational framework for future experimental research and clinical trials aimed at refining andrographolide dosing regimens and improving patient outcomes. Full article

For the calculation of thermal processes of canned food, the original formula method of Ball is still widely used for its accuracy and safety. However, it requires the consultation of tables that Ball prepared and the relative interpolation of the data. This is due to the exponential integral function (Ei) resulting after the integration of the thermo-bacteriological and heat transfer differential equations. Mathematical modelling that replaces the Ball tables is useful for speeding up the thermal process calculations and for being prospectively implemented in process control systems. Stoforos had already proposed a simple and accurate mathematical model based on the regression of the table data. However, Stoforos’ equations do not contain the influence of the temperature difference between the steam and the cold water (m+g) when this is different from the two values of the tables (180 and 130 °F). This approximation leads, in some cases, to over-sterilization with a consequent loss of quality. To overcome these limitations, in this work a nonlinear regression of the values of the exponential integral function (Ei) has been developed. However, this is performed by using the regression on the ratio between the function and its derivative and replacing the hyperbola of the initial cooling imposed by Ball with an appropriate exponential function. The overall mean relative error, MRE, compared to Ball’s tables was less than 1%. Full article

The transition toward a renewable-based energy structure has significantly accelerated the advancement of energy storage technologies. Compressed air energy storage (CAES) is regarded as a highly promising long-duration energy storage solution due to the advantages of its large scale and long service life. However, the efficiency of conventional compressed air energy storage (CAES) systems remains limited due to the inadequate utilization of thermal energy. Isothermal compressed CAES (ICAES) technology, based on liquid pistons, can overcome the efficiency bottleneck by enabling temperature control during air compression. However, the operation of liquid pistons under high-pressure storage conditions remains a challenge because of the high compression ratio. To enhance the utilization rate of the two-stage liquid piston unit by using the synchronous operations of compression and discharge processes, this paper proposes a coordinated operation scheme. Then, a multi-stage ICAES system under constant-pressure air storage is proposed. Mathematical models and energy efficiency analysis methods of the multi-stage ICAES system are also established. Finally, the operational characteristics are analyzed in combination with the ICAES at 200 kWh. The results show that the proposed system can achieve an overall efficiency of 68.0%, under 85% and 90% efficiencies for low-pressure and linear equipment, respectively. The coordinated operation of the two-stage liquid piston unit can be further extended to multi-stage operations, demonstrating broad application prospects in ICAES systems. Full article

Arc scanning synthetic aperture radar (ArcSAR) can achieve high-resolution panoramic imaging and retrieve submillimeter-level deformation information. To monitor buildings in a city scenario, ArcSAR must be lightweight; have a high resolution, a mid-range (around a hundred meters), and low power consumption; and be cost-effective. In this study, a novel high-resolution wide-beam single-chip millimeter-wave (mmwave) ArcSAR system, together with an imaging algorithm, is presented. First, to handle the non-uniform azimuth sampling caused by motor motion, a high-accuracy angular coder is used in the system design. The coder can send the radar a hardware trigger signal when rotated to a specific angle so that uniform angular sampling can be achieved under the unstable rotation of the motor. Second, the ArcSAR’s maximum azimuth sampling angle that can avoid aliasing is deducted based on the Nyquist theorem. The mathematical relation supports the proposed ArcSAR system in acquiring data by setting the sampling angle interval. Third, the range cell migration (RCM) phenomenon is severe because mmwave radar has a wide azimuth beamwidth and a high frequency, and ArcSAR has a curved synthetic aperture. Therefore, the fourth-order RCM model based on the range-Doppler (RD) algorithm is interpreted with a uniform azimuth angle to suit the system and implemented. The proposed system uses the TI 6843 module as the radar sensor, and its azimuth beamwidth is 64°. The performance of the system and the corresponding imaging algorithm are thoroughly analyzed and validated via simulations and real data experiments. The output image covers a 360° and 180 m area at an azimuth resolution of 0.2°. The results show that the proposed system has good application prospects, and the design principles can support the improvement of current ArcSARs. Full article

In image processing, the acquisition step plays a fundamental role because it determines image quality. The present paper focuses on the issue of blur and suggests ways of assessing contrast. The logic of this work consists in evaluating the sharpness of an image by means of objective measures based on mathematical, physical, and optical justifications in connection with the human visual system. This is why the Logarithmic Image Processing (LIP) framework was chosen. The sharpness of an image is usually assessed near objects’ boundaries, which encourages the use of gradients, with some major drawbacks. Within the LIP framework, it is possible to overcome such problems using a “contour detector” tool based on the notion of Logarithmic Additive Contrast (LAC). Considering a sequence of images increasingly blurred, we show that the use of LAC enables images to be re-classified in accordance with their defocus level, demonstrating the relevance of the method. The proposed algorithm has been shown to outperform five conventional methods for assessing image sharpness. Moreover, it is the only method that is insensitive to brightness variations. Finally, various application examples are presented, like automatic autofocus control or the comparison of two blur removal algorithms applied to the same image, which particularly concerns the field of Super Resolution (SR) algorithms. Such algorithms multiply (×2, ×3, ×4) the resolution of an image using powerful tools (deep learning, neural networks) while correcting the potential defects (blur, noise) that could be generated by the resolution extension itself. We conclude with the prospects for this work, which should be part of a broader approach to estimating image quality, including sharpness and perceived contrast. Full article

This paper presents a study whose aim was to formulate a conceptual framework that allows us to understand the degree of complexity of the connections between the knowledge that a mathematics teacher can possess, based on the model of the mathematics teacher’s specialized knowledge model and the Piaget’s schemas. To this end, a literature review was carried out to analyze how these connections are made in the minds of mathematics teachers and how complex they are, identifying a deficit. Therefore, the schema structure proposed by Piaget, with its three stages of intra-, inter-, and trans-development, was considered. Based on an instrumental case study with two prospective teachers, an analysis was performed on semi-structured interviews conducted while the teachers separately discussed a lesson plan based on the understanding of multiplication and division of natural numbers, aimed at third-grade students. The results show that three types of knowledge schemas emerged among the participating teachers, with the respective types of connections between the knowledge. This shows that the connections between the knowledge of the model in teachers’ minds can vary in complexity. Full article

In recent years, the electromic approach, which is based on the ‘electrome’ concept, to the analysis of electrical activity in plants has become increasingly relevant, as it can allow the detection of early signs of stress and the classification of external factors on the basis of complex, systemic changes in electrical parameters. However, the mechanisms underlying the observed complex effects remain unresolved. This review describes the main electrical signals in plants and their influence on physiological processes and tolerance to abiotic stressors, discusses limitations of traditional methods of investigation of electrical activity, summarizes modern strategies for electrome analysis, and considers the prospect of applying mathematical modeling to interpret the electromic data. We suggest that the integration of the electromic approach and mathematical modeling can greatly enhance the ability to investigate plant electrical signaling, opening new ways for fundamental and applied research in plant electrophysiology. Full article

The Schrödinger equation, Heisenberg’s uncertainty principles, and the Boltzmann constant represent transformative scientific achievements, the impacts of which extend far beyond their original domain of physics. As we celebrate the centenary of these fundamental quantum mechanical formulations, this review examines their evolution from abstract mathematical concepts to essential tools in contemporary drug discovery and development. While these principles describe the behavior of subatomic particles and molecules at the quantum level, they have profound implications for understanding biological processes such as enzyme catalysis, receptor–ligand interactions, and drug–target binding. Quantum tunneling, a direct consequence of these principles, explains how some reactions occur despite classical energy barriers, enabling novel therapeutic approaches for previously untreatable diseases. This understanding of quantum mechanics from 100 years ago is now creating innovative approaches to drug discovery with diverse prospects, as explored in this review. However, the fact that the quantum phenomenon can be described but never understood places us in a conundrum with both philosophical and ethical implications; a prospective and inconclusive discussion of these aspects is added to ensure the incompleteness of the paradigm remains unshifted. Full article

The global transition towards clean energy sources is becoming essential to reduce reliance on conventional fuels and mitigate carbon emissions. In the future, the clean energy storage landscape, green hydrogen, and green ammonia (powered by renewable energy sources) are emerging as key players. This study explores the prospectives and feasibility of producing and storing offshore green hydrogen and green ammonia. The potential power output of Hornsea one and Hornsea two winds farms in the United Kingdom was calculated using real wind data. The usable electricity from the Hornsea one wind farm was 5.83 TWh/year, and from the Hornsea two wind farm, it was 6.44 TWh/year, harnessed to three different scenarios for the production and storage of green ammonia and green hydrogen. Scenario 1 fulfil the requirement of green hydrogen storage for flexible ammonia production but consumes more energy for green hydrogen compression. Scenario 2 does not offer any hydrogen storage which is not favourable in terms of flexibility and market demand. Scenario 3 offers both, a direct routed supply of produced hydrogen for green ammonia synthesis and a storage facility for green hydrogen storage. Detailed mathematical calculations and sensitivity analysis was performed based on the total energy available to find out the energy storage capacity in terms of the mass of green hydrogen and green ammonia produced. Sensitivity analysis in the case of scenario 3 was conducted to determine the optimal percentage of green hydrogen going to the storage facility. Based on the cost evaluation of three different presented scenarios, the levelized cost of hydrogen (LCOH) is between USD 5.30 and 5.97/kg, and the levelized cost of ammonia (LCOA) is between USD 984.16 and USD 1197.11/tonne. These prices are lower compared to the current UK market. The study finds scenario 3 as the most appropriate way in terms of compression energy savings, flexibility for the production and storage capacity that depends upon the supply and demand of these green fuels in the market, and a feasible amount of green hydrogen storage. Full article

Mathematical models and methods serve as fundamental tools for studying ice-related phenomena in the Yellow River. River ice is driven and constrained by hydrometeorological and geographical conditions, creating a complex system. Regarding the Yellow River, there are some uncertainties that manifest in unique features in this context, including ice–water–sediment mixed transport processes and the distribution of sediment both within the ice and on its surface. These distinctive characteristics are considered to different degrees across different scales. Mathematical models for Yellow River ice developed over the past few decades not only encompass models for the large-scale deterministic evolution of river ice formation and melting, but also uncertainty parameter schemes for deterministic mathematical models reflecting the Yellow River’s particular ice-related characteristics. Moreover, there are modern mathematical results quantitatively describing these characteristics with uncertainty, allowing for a better understanding of the unique ice phenomena in the Yellow River. This review summarizes (a) universal equations established according to thermodynamic and hydrodynamic principles in river ice mathematical models, as well as (b) uncertainty sources caused by the river’s characteristics, ice properties, and hydrometeorological conditions, embedded in parametric schemes reflecting the Yellow River’s ice. The intractable uncertainty-related problems in space–sky–ground telemetric image segmentation and the current status of mathematical processing methods are reviewed. In particular, the current status and difficulties faced by various mathematical models in terms of predicting the freeze-up and break-up times, the formation of ice jams and dams, and the early warning of ice disasters are presented. This review discusses the prospects related to the uncertainties in research results regarding the simulation and prediction of Yellow River ice while also exploring potential future trends in research related to mathematical methods for uncertain problems. Full article

In this study, a new edible gel of Perilla essential oil (PE)/grape seed extract (GSE)–chitosan/gelatin was prepared, and it was applied to the preservation of silver carp. By establishing a fuzzy mathematical model, using a single-factor experiment and Box–Behnken response surface optimization combined with matlab analysis, the optimum preparation conditions of composite gel films were determined: the addition of PE (p < 0.01) was 6.91 μL/mL, the addition of GSE (p < 0.05) was 0.45 mg/mL, and the addition of gelatin (p > 0.05) was 1.63%. Under these conditions, the composite gel films exhibited an excellent water vapor barrier and mechanical properties. Using Fourier-transform infrared spectroscopy (FTIR) analysis, it was found that the addition of PE enhanced or weakened the absorption peaks, indicating the molecular interaction between PE and the substrate. Scanning electron microscopy (SEM) observed that the surfaces of the composite gel films with added PE were smooth, but there were a few pores in the cross-section. X-ray diffraction (XRD) analysis showed that PE had good compatibility with other components. The fresh-keeping experiment showed that the composite gel films could significantly prolong the fresh-keeping period of grass carp. After 10 days of storage at 4 °C, compared with the blank group (without plastic wrap) and the control group (with composite gel film, no PE added), the experimental group (with composite gel films, PE added) showed better fresh-keeping effect in terms of sensory score, moisture content, pH value, TBARS value, and TVB-N value (p < 0.05). Correlation analysis further confirmed the positive effects of composite gel films on water content, pH value, TVB-N, and other quality indexes of silver carp, indicating that the composite gel films will have broad application prospects in the food preservation field. This study provides an innovative basis and theoretical basis for the development and application of natural polysaccharide/protein composite edible film, which is helpful to promote the development of green food-packaging materials. Full article