Specific Applications Research Articles

Exploring the Synergistic Effects of Biostimulant and Hydrogel Combinations on Brinjal Growth: An Assessment of Growth Parameters

Background: This study at Lovely Professional University, Phagwara, Punjab, evaluates the combined effects of hydrogel and Arka Vegetable biostimulants on brinjal (Solanum melongena L.) production. Brinjal’s high water and nutrient needs make it sensitive to water scarcity and seasonal variations. Hydrogel enhances soil moisture retention, reducing irrigation needs, while Arka Vegetable biostimulants improve plant growth and stress tolerance. Using both together aims to optimize water management and plant health, addressing key challenges in brinjal cultivation. Methods: In the study, the hydrogel was applied during the sowing stage, while Arka Vegetable Special was sprayed twice, with a 15-day interval after transplanting. The treatment designated as V2H2 (5 g/L + 1.5 kg/acre) was utilized, where ‘V’ represents concentration in grams per liter and ‘H’ denotes application rate in kilograms per acre. This treatment is aimed at optimizing vegetative growth. Various levels of Arka Vegetable Special and hydrogel application were tested to observe their effects on growth characteristics. Result: The study’s findings revealed the effectiveness of the V2H2 treatment in enhancing vegetative growth. Application of Arka Vegetable Special and hydrogel at different levels significantly improved all the studied growth characteristics. This suggests the potential of integrating biostimulants and Hydrogel practices to optimize Brinjal production, offering a sustainable solution to meet year-round vegetable demand and mitigate water scarcity challenges in agricultural systems.

Scaling Oral Assessment Authentically

The rise of AI and related threats to academic integrity in a post-pandemic academic environment where most assessments are not invigilated forces universities to revisit the question of how to conduct safe and fair assessments (Dawson, 2022). As invigilated exams and online proctoring have fallen out of favour with university administrators due to cost, space or privacy concerns, oral assessments have found renewed interest (Newell, 2023). These are effective in measuring students' knowledge whilst verifying that the responses truly belong to the student (Joughin, 1998). Though there are many established variations of oral assessment, from viva voce thesis defence to interactive orals (as widely conducted in Law and Medicine), they usually emphasise authentic live interaction between student and assessor. However, the sheer scale of some undergraduate programs (as common in Business Schools) along with the integrated nature of business curriculum requiring marking expertise from different graders makes truly interactive oral exams unfeasible. As a response, a large first-year undergraduate Business course (with student enrolments of between 500-1200 per term) at a G08 institution implemented an authentic recorded oral assessment, which mimics job interview practice. Students were recorded for a set time period while they responded to questions verbally with the resulting video and transcripts being later marked. We utilised an asynchronous, remotely invigilated oral assessment (Baird et al., 2022) for the final exam to improve academic integrity and to further embed transferable skills that is industry relevant whilst increasing student employability. The new assessment format was named ‘Live Recorded Video Exam (LRVE)’. The invigilation process for this exam was conducted on a one-on-one basis where one invigilator checked each student in their groupings. The invigilators were provided with a procedural checklist to follow to be consistent within all the groups. The process involved the invigilator calling the student into a Microsoft Teams channel, verifying the student’s identity, checking their immediate surroundings, sharing the screen of the device that the student was using, providing a password verbally for the student to access the exam questions and then to start the recording for invigilation purposes. Once the recording commenced, the invigilator would leave the meeting room and allow the student to complete the exam independently by articulating their responses. The graders had access to both the video recording as well as the captioned transcript to mark the exam and check for any student misconduct. Students were informed about the exam format through different channels from the teaching team as well as innovative student-led initiatives. They were given various opportunities to prepare throughout the term within established class structures and practice mock sessions. Out of 542 exams, none were reported for violations of academic integrity and the rate of special consideration applications was lower. This is, in part, due to potential problems being rectified during the student check-in process. Surveys conducted after the exam showed the LRVE format was well-received by markers and student representatives in part because of its flexibility, offering a complement to traditional viva voce models and demonstrating its scalability.

Simultaneous measurement of temperature and refractive index based on fiber optic Fabry–Pérot cavity in batteries

Abstract A Fabry-Pérot (FP) sensor for simultaneous measurement of refractive index and temperature of an all-fiber synchronous liquid based on the Vernier effect is proposed, special application for internal monitoring of lithium-ion battery electrolytes. The theoretical model of high sensitivity cascade Fabry-Pérot interferometer (PFPI) is established, the sensitivity amplification mechanism of PFPI is analyzed in detail, the perfect matching scheme for measuring the refractive index of the electrolyte inside the battery is designed according to the matching conditions of the optical path, and the corresponding sensors for simultaneous measurement of the temperature and the refractive index are fabricated. The experimental results show that the sensor has a maximum refractive index sensitivity of 15391.5033 nm/RIU, a good linear fit, and can effectively monitor the refractive index change of the electrolyte by 10-4 orders of magnitude during normal charging and discharging of lithium-ion batteries. Compared to traditional epoxy adhesive bonded or laser processed FP sensors, this all-fibre optic structure not only improves temperature and corrosion resistance, but also significantly reduces temperature cross-sensitivity. Its small size and excellent resistance to high temperature and corrosion ensure the sensor's excellent response and broad application prospects in monitoring the refractive index of the electrolyte in 18650 lithium-ion batteries, which provides effective technical support for monitoring the health status of batteries and detecting early safety issues.

Flexible Inverse Opal Structural Color Films with High Strength and Harsh Environment Stability.

Flexible photonic crystals (PCs) constructed by PCs and special polymers are very promising to achieve a combination of vivid structural colors, mechanical robustness, and environment stability. However, PCs that incorporate polymer binders are still susceptible to destruction and subsequent loss of structural color when subjected to significant external forces or harsh environments. Besides, because most of these polymers are highly flammable, crucial fire safety is difficult to be guaranteed in the application of these materials. In this study, we report a poly(m-phenyleneisophthalamide) inverse opal (PMIA IO) structural color film through a SiO2 PC template sacrificing method. Benefiting from the high rigid PMIA molecular structural configuration, the PMIA IO films are able to maintain their structural colors even in harsh conditions, such as large tensile stress, high and low temperatures, potent acids and bases, and ultraviolet radiation. More attractively, the PMIA IO films demonstrate excellent flame retardancy, with the limiting oxygen index (LOI) and flame retardant rating reaching 28 vol % and V0, respectively. We believe that the flexible structural color films with high strength, harsh environment stability, and flame retardancy, which are difficult for other structural color materials to possess simultaneously, have great potential for special applications in fire protection, national defense, aviation, marine, and aerospace fields.

A 3D nitrogen-rich heat-resistant supramolecular MOF with superior energetic performances assembled from Zn(II) and 5-aminotetrazole

Heat-resistant explosives are pivotal for specialized applications demanding high thermal stability, essential in both civil and military sectors, especially in extreme environments. Our study focuses on the synthesis of a 3D nitrogen-rich supramolecular energetic metal-organic framework (MOF), Zn(ATZ)2 (1), using the 5-aminotetrazole (HATZ) ligand and Zn(II) ion. Structural analysis indicates that compound 1 adopts the orthorhombic CmCm space group and possesses a robust 2D network, characterized by strong π-π packing interactions between 2D layers, offering exceptional thermal stability up to 322 °C with minimal mechanical sensitivity. The standard molar enthalpy of formation (ΔfHo) and heat of detonation (ΔHdet) for compound 1 are calculated to be 7.08 kJ/g and 7.34 kJ/g, respectively. Remarkably, the ΔfHo of compound 1 significantly exceeds those of traditional heat-resistant explosives like RDX (0.32 kJ/g), HNS (0.17 kJ/g), TNT (–0.295 kJ/g), and TATB (–0.54 kJ/g), and is also higher than those of most reported energetic MOF materials. Similarly, its ΔHdet value surpasses those of common explosives such as TNT (4.144 kJ/g), HMX (5.525 kJ/g) and RDX (5.71 kJ/g), as well as the majority of reported energetic MOFs. Compound 1 also demonstrates impressive detonation properties with a velocity (D) of 7.22 km s-1 and a pressure (P) of 21.95 GPa, outperforming many other energetic MOF materials. These superior energetic characteristics position compound 1 as a strong candidate for heat-resistant explosives, showcasing its potential for future applications in demanding environments.

Image restoration through few-mode fiber using a new comprehensive attention model

Few-mode fibers (FMF) has unique advantages in single fiber imaging (SFI) in special applications. However, the limited number of transmission modes restricts the information carriers, hence the high-quality image restoration is a major challenge. A deep learning network with new comprehensive attention, called few-mode fiber Swin Transformer (FFST), is developed based on Swin Transformer V2 to realize successful image restoration with a FMF on handwriting letters and numbers. This network is proved outperforming nine widely used convolutional neural networks or Transformer-based models with four evaluation criteria. In addition, single-fiber-multi-location (SFML) experiment is conducted to investigate the effect of different view on imaging feasibility, the result of which shows that SFML can improve the restoration quality despite one object corresponds to multiple different speckle images, indicating that multi-mapping relationships has constructive effect in single FMF imaging. This paper provides a method for imaging in very narrow cavities.

Hardening properties, water resistance and associated micro-mechanism of nano-modified calcium sulphoaluminate cement

Calcium sulphoaluminate cement (CSA) is considered a sustainable alternative to traditional Portland cement to reduce CO2 emissions. To further improve the hardening properties and water resistance of CSA and advance its extensive special engineering application, nanoparticles including nano-SiO2 (NS), nano-MgO (NM) and nano-Al2O3 (NA) were used as nano-modifiers for CSA. The effects of nanoparticles dosage on the setting time, compressive strength and water resistance of nano-modified CSA were experimentally evaluated, and the micro-mechanisms were also clarified by conducting X-ray diffraction (XRD), scanning electron microscopy (SEM) and thermogravimetric analysis (TG) tests. The results showed that incorporating nanoparticles into CSA obviously shortened the initial and final setting times. The appropriate addition of nanoparticles effectively enhanced the compressive strength of CSA, and the optimum dosages of NS, NM, and NA were respectively determined to be 0.5%, 1.0%, and 0.5%. Water immersion decreased the bonding strength of CSA, and adding nanoparticles can effectively weaken this water-induced deterioration effect. Under water immersion environment, the optimum dosages of nanoparticles would be increased to obtain the highest residual water immersion strength and minimum strength loss rate. The generation of ettringite was mainly responsible for the compressive strength and water resistance improvements of nano-modified CSA. The hydration process of nano-modified CSA was clarified and the corresponding micro-mechanism model was proposed. Furthermore, the benefits and challenges of using nano-modified CSA were also analyzed, advancing its widespread application in rapid repair of special engineering.

СОВЕРШЕНСТВОВАНИЕ СПОСОБА ПОЛУЧЕНИЯ УСНИНОВОЙ КИСЛОТЫ ИЗ РАСТИТЕЛЬНОГО СЫРЬЯ ИСЛАНДСКОГО МХА

Relevance. Contemporary pharmaceutical industry requires constant search and development of new technologies for the production of pharmacological products. At the same time, the processing of plants, which contain substances with a therapeutic effect, is a promising direction. Their use in terms of economic and therapeutic effectiveness is sometimes very beneficial. It has been proven that lichen plants contain substances that have a therapeutic effect. Organisms of the genus Cladonia, which synthesize usnic acid, among them have a special significance and application. The extraction of usnic acid from lichen biomass is carried out using various organic solvents. At the same time, it is preferable to use techniques with the lowest cost with a high quantitative yield of extractives. In addition, extracts containing bioactive substances should exhibit significant biological activity. The aim is improving the technology of extraction of usnic acid from the vegetable raw materials of Cladonia rangiferina Hoff by determining the optimal components for its extraction. Materials and methods. The material for the study is raw material of Yagel (Deer Moss)/Cladonia rangiferina Hoff. The extractive properties of the most commonly used solvents (purified water, ethyl alcohol 40, 70 and 95%) were studied, among which the most effective was identified. The content of extractive substances was determined by the gravimetric analysis method. The results of the study. According to the results of a series of experiments to study extractive capabilities, of all solvents, the maximum extractive ability of extractive substances from Cladonia rangiferina Hoff was noted for 95% ethyl alcohol (7.38%). Ethyl alcohol 70% was produced with a high extraction capacity, however, it turned out to be less effective. The conclusion was made about these methods can be used to detect biologically active substances obtained from the raw materials of Cladonia rangiferina Hoff. The obtained developments create prerequisites for the development of regulatory documentation on the procedure and position of the relevant standard or a temporary pharmacopoeia article.

A New Iterative Algorithm for Magnetic Motion Tracking

Motion analysis is of great interest to a variety of applications, such as virtual and augmented reality and medical diagnostics. Hand movement tracking systems, in particular, are used as a human–machine interface. In most cases, these systems are based on optical or acceleration/angular speed sensors. These technologies are already well researched and used in commercial systems. In special applications, it can be advantageous to use magnetic sensors to supplement an existing system or even replace the existing sensors. The core of a motion tracking system is a localization unit. The relatively complex localization algorithms present a problem in magnetic systems, leading to a relatively large computational complexity. In this paper, a new approach for pose estimation of a kinematic chain is presented. The new algorithm is based on spatially rotating magnetic dipole sources. A spatial feature is extracted from the sensor signal, the dipole direction in which the maximum magnitude value is detected at the sensor. This is introduced as the “maximum vector”. A relationship between this feature, the location vector (pointing from the magnetic source to the sensor position) and the sensor orientation is derived and subsequently exploited. By modelling the hand as a kinematic chain, the posture of the chain can be described in two ways: the knowledge about the magnetic correlations and the structure of the kinematic chain. Both are bundled in an iterative algorithm with very low complexity. The algorithm was implemented in a real-time framework and evaluated in a simulation and first laboratory tests. In tests without movement, it could be shown that there was no significant deviation between the simulated and estimated poses. In tests with periodic movements, an error in the range of 1° was found. Of particular interest here is the required computing power. This was evaluated in terms of the required computing operations and the required computing time. Initial analyses have shown that a computing time of 3 μs per joint is required on a personal computer. Lastly, the first laboratory tests basically prove the functionality of the proposed methodology.

Tools for promoting information security in the media space

The article analyzes the main tools for detecting disinformation, in particular, special applications, artificial intelligence technologies for checking content, which are used by popular social networks, such as Facebook, Instagram, etc. The capabilities of artificial intelligence systems used in Ukraine to monitor the media space and analyze a large volume of online publications are highlighted. The most important elements in combating disinformation are identified, in particular programs and projects related to the development of media literacy, the involvement of social media platforms, international cooperation, etc. Attention was drawn to the programs of the international non-profit organization IREX. The main technologies and approaches for countering disinformation and destructive propaganda are analyzed. Particular attention is paid to strengthening resistance to russian disinformation during the war and countering it in the future. The work uses a synergistic approach, which will enable the analysis of state policy directions and measures of civil society to counter disinformation and hostile propaganda. The scientific nature of the research is provided by a system of cognitive principles generally recognized in modern science, in particular, the principle of complexity and objectivity.

Split Hopkinson bar and flash X-ray characterization of ultra high performance concrete reinforced by steel fibers subjected to dynamic compression

AbstractExcellent mechanical properties of ultra high performance concrete make it suitable for use in special applications, where the material is subjected to dynamic phenomena such as impacts, explosions, or earthquakes. This paper presents a novel experimental approach that integrates a Split Hopkinson Pressure Bar with a flash X-ray system and high-speed optical imaging to investigate the dynamic behavior of steel fiber reinforced UHPC under high strain rate uni-axial compression. In-situ Flash X-ray radiography emerges as a particularly effective tool, providing clear visualization of deformation response and overcoming challenges associated with flying debris encountered in optical inspection. Moreover, computed tomography and scanning electron microscopy appear as a vital technique for analyzing micro-structure and fiber distribution and orientation. The combined approach offers a promising method to study the dynamic behavior of steel fiber reinforced ultra high performance concrete and also holds promise for analyzing more complex modes of deformation and material interactions, providing valuable insights for enhancing the design and performance of critical infrastructure subjected to dynamic loading events.

Sources and splitting of special fertilizers application in coffee crop

This study assesses special and mineral fertilizers and the splitting of fertilizer application in coffee - a crop with high nutritional requirements for full yield potential. A 4 × 3 factorial scheme was implemented with four fertilizers [mineral, mineral with polymer, organomineral with cellulosic residue (OM-CR), or sugarcane filter cake (OM-FC)] and three application times, or splits (100% at once, 50%+50%, 33.3%+33.3%+33.3%). Coffee plant height, canopy diameter, plagiotropic branch growth, leaf chlorophyll, nutrient contents in the soil and leaves, and harvest yield after fruit maturation were evaluated in two consecutive crop cycles. The results indicated that organomineral fertilizers performed similarly to other fertilizers regarding coffee leaf chlorophyll and plant height. Only one fertilizer application effectively increased canopy diameter in both crop cycles. In the first crop cycle, OM-FC and conventional mineral fertilizers were significantly better for coffee foliar N content. In contrast, in the second crop cycle, mineral-P, OM-CR, and OM-FC achieved satisfactory results with one fertilizer application, whereas conventional mineral fertilizer required three applications for superior results. There are no differences in leaf P content among different sources and frequencies of application. Still, mineral-P and OM-CR had better soil P content than the conventional mineral fertilizer. OM-CR required two applications to reach high levels of leaf K content, while other fertilizers achieved it with one application. Organomineral and protected mineral fertilizers performed similarly in both crop cycles, with two applications resulting in greater coffee yield in the second cycle, regardless of the fertilizer used.

Nonlinear control of the permanent magnet synchronous motor PMSM using input-output linearization control and sliding mode control

Today, electric machines are becoming increasingly important in all sectors (industrial drives, the automotive industry, aviation, traction systems, and agriculture, etc.). Among these machines, permanent magnet synchronous machines (PMSMs) hold a significant place in the control of industrial mechanisms, automated systems, and in the fields of renewable energy like (wind energy, solar energy, and hybrid systems, etc ). Currently, in variable speed drives, the use of PMSM, especially for low power and certain special industrial applications, is replacing DC motors and asynchronous motors because they offer higher efficiency, power factor, and torque density. Moreover, PMSM do not have an excitation circuit in the rotor, which leads to reduced maintenance demands. The control of permanent magnet synchronous machines (PMSM) presents significant challenges due to their nonlinear behavior. Classical linear controllers, such as PI, perform well with linear systems that have constant parameters. However, for nonlinear systems with varying parameters, the conventional control methods may prove insufficient and exhibit a lack of robustness. To address the issues and achieve decoupled machine control, various methods have been proposed. Nonlinear robust control techniques have been extensively explored within the domain of power electronics and drive systems. Included in these, sliding mode control and nonlinear input-output feedback linearization (IOFL). Sliding mode control (SMC) is a control technique known for its excellent dynamic performance in PMSM drives. It offers high robustness and straightforward implementation in both software and hardware. However, a significant drawback of this method is the chattering phenomenon. By the way the input/output linearization control can provide good behavior in steady and dynamic regimes and also provides good decoupling between system variables. This article presents a design of tow control laws based on sliding mode and feedback linearization controller based on input-output feedback linearization to adjust the speed of a permanent magnet synchronous motor (PMSM). To highlight the effectiveness of the designed controllers, a comparison was carried out Matlab Simulink, revealing that the feedback linearization controller outperforms the SMC.

Image segmentation for pest detection of crop leaves by improvement of regional convolutional neural network

Pest detection is important for crop cultivation. Crop leaf is the main place of pest invasion. Current technologies to detect crop pests have constraints, such as low efficiency, storage demands and limited precision. Image segmentation is a fast and efficient computer-aided detection technology. High resolution image capture solidly supports the crucial processes in discerning pests from images. Study of analytical methods help parse information in the images. In this paper, a regional convolutional neural network (R-CNN) architecture is designed in combination with the radial bisymmetric divergence (RBD) method for enhancing the efficiency of image segmentation. As a special application of RBD, the hierarchical mask (HM) is produced to endorse detection and classification of the leaf-dwelling pests, offering enhanced efficiency and reduced storage requirements. Moreover, to deal with some mislabeled data, a threshold variable is introduced to adjust a fault-tolerant mechanism into HM, to generate a novel threshold-based hierarchical mask (TbHM). Consequently, the hierarchical mask R-CNN (HM-R-CNN) model and the threshold-based hierarchical mask R-CNN (TbHM-R-CNN) model are established to detect various types of healthy and pest-invasive crop leaves to select the regional image features that are rich in pest information. Then simple linear iterative clustering (SLIC) method is incorporation to finish the image segmentation for the classification of pest invasion. The models are tuned and optimized, then validated. The most optimized modeling results are from the TbHM-R-CNN model, with the classification accuracy of 96.2%, the recall of 97.5% and the F1 score of 0.982. Additionally, the HM-R-CNN model observed appreciable results second only to the best model. These results indicate that the proposed methodologies are well-suited for training and testing a dataset of plant diseases, offering heightened accuracy in pest classification. This study revealed that the proposed methods significantly outperform the existing techniques, marking a substantial improvement over current methods.

Comparative Performance of ARIMA and ARCH Models On Time Series of Monthly Libyan Brent Oil Price

Many economic and financial time series exhibit a phenomenon known as heteroscedastic, where the variance of the series changes over time. This research study focuses on financial time series modelling, with special application to modelling the price of Libyan Brent Oil. In particular, the theory of univariate nonlinear time series analysis is explored and applied to the price Libyan of Brent Oil, spanning from January 2000 to December 2010. The data was obtained from Bullent of the Platts Market Wire of Statistics. This study aims to evaluate the performance of ARIMA as a linear model and ARCH as a nonlinear modelling data. Multiple time series models were considered for fitting the data, and the best ARIMA models were selected based on the Akaike Information Criteria (AIC). ARIMA (0, 1, 1), and ARIMA (1, 1, 0) were identified as the best models. After estimating the parameters of the selected models, model checking revealed that these models were not suitable for modeling the data, as they lacked validity according to the test of squared residuals. The goodness of fit was assessed using the AIC, and based on minimum AIC values, the best fit ARCH models were found to be ARIMA (0, 1, 1) - ARCH (1). After estimating the parameters of the selected model, a series of diagnostic and forecast accuracy tests were performed. Based on this model, a twelve-month forecast of the price of Libyan Brent crude was made.

Gassmann triples with special cycle types and applications

Gassmann triples with special cycle types and applications

Railway noise monitoring - a tool to analyse in detail the evolution of noise over time during a rolling stock renewal period

As part of the commissioning of a rail freight project, a noise monitoring system was set up to track the increase in rail freight traffic and to monitor noise over time. Noise monitoring is done by continuous measurement stations, an analysis of the classic noise exposure indexes LAeq,6-22h and LAeq,22-6h is realized, completed by an analysis of several event acoustic indexes, with a distinction between the different traffic types (Freight, regional trains). In addition, the European Regulation EU 2019/774 on the application of the technical specification for interoperability relating to the subsystem 'rolling stock - noise' to the existing freight wagons, obliges the circulation of less noisy freight trains on certain itineraries called "Quieter routes" from 8/12/2024. The projected benefit will not be limited to the nearby residents of these routes but will, by indirect consequence, enable a gradual acoustic gain on all the French rail freight routes, due to the retrofit or renewal of the existing rolling stock. The goal of the noise monitoring system is also to quantify the acoustic gains from the indirect effects of this new regulation.

Overview of Single-Subject Design in Special Education Studies

In recent years, there has been an increase in the use of single-subject design in special education research. This paper provides an insightful overview of the application of single-subject design within special education studies. The paper delves into an exploration of the fundamental concepts underlying single-subject design, its historical origins, and the wide range of purposes it serves. Furthermore, an examination of the strengths and weaknesses inherent to single-subject design is undertaken. Finally, an evaluation of withdrawal design, multiple baseline design, and alternating treatment design and their special education research application are offered. In this evaluation, the researcher specifically examines how these designs can be applied in special education research contexts. By exploring these variations, this paper provides insights into the diverse ways single-subject design can be applied to address the unique research needs and challenges in special education.

Thermally robust hierarchical nanofiber triboelectric yarns for efficient energy harvesting in firefighting E-textiles

Textile-based triboelectric nanogenerators (TENGs) face challenges in achieving high performance and fulfilling functional requirement for special applications. This paper presents the development of a high-performance, thermally robust hierarchical polyimide (PI) nanofiber triboelectric yarns with a charge-trapping interlayer for application in firefighting E-textiles. The hierarchical nanofiber yarns, comprising a stainless-steel core electrode, a PI/MXene interlayer and PI outer tribo-layer, exhibit enhanced triboelectric performance due to the charge-trapping capabilities of MXene, which preventing the recombination of triboelectric and induced charges. When the MXene content in the charge-trapping interlayer reached 1 wt%, the corresponding TENG achieved its optimal output performance, with an output voltage of 153 V and a current of 13.13 μA and a peak power density of 0.84 W/m2 under optimal conditions. It also demonstrates exceptional thermal stability, maintaining stable output at temperatures up to 400 °C. The integration of the TENG into E-textiles enables real-time monitoring of firefighters’ physical activities and location tracking, significantly enhancing their safety and operational efficiency in fire scenarios. Additionally, the TENG powers electroluminescent yarns, improving visibility in dense smoke and dust environments. This research opens new avenues for the application of smart wearable systems in high-temperature environments, providing effective strategies for ensuring the safety of firefighters in fire rescue operations.

Exploring The Potentials and Drawbacks of Hysteresis Current Controller For SRM: A Case Study Of Wind Energy Conversion System

Switched Reluctance Machines (SRMs) have drawn interest in renewable energy systems because of their special qualities and applicability. This study examines the idea of hysteresis current regulation in a wind energy conversion system with a Switched Reluctance Generator (SRG). The system is modeled in MATLAB/SIMULINK. The model is simulated and analyzed to ascertain the system’s benefits and shortcomings, focusing on reducing torque ripples in SRG. Considering most classical controllers are complicated to construct, the hysteresis current control is straightforward and effective. However, this controller's two primary shortcomings are that it produces a variable switching frequency and increases current ripples at a steady state, both enhancing acoustic noise in SRM. Lastly, the report suggests that improving controller performance should be the primary emphasis of future research in this field.