Example Of Application Research Articles

Measuring Interest: Development and Application of a Three-Dimensional Situational Interest Short Scale

<p>Situational interest is an important factor that has a great influence on learning success in both in-school and out-of-school learning situations. Although there has been extensive research on interest in its diverse forms for decades, an evaluated measurement instrument for situational interest that covers the three theoretically defined components of interest (emotional, cognitive, value-related) is still missing. Therefore, in this study, based on person-object theory of interest, a short scale was developed that can be used in a variety of learning programs independent of content or methods. In study 1, eight suitable items were selected and their structure was examined using exploratory methods. In study 2, the results of study 1 were verified using confirmatory factor analyses. Study 3 shows an example of a practical application of the newly developed scale in two different learning settings. The findings provide evidence that the scale developed here is a practical instrument to measure situational interest taking into account all its components. On the one hand, the scale can help teachers evaluate their educational programs; on the other hand, it can be used by researchers to empirically investigate the construct of interest. Thus, the scale makes an important contribution to research and practice.</p>

On the Synthesis and Structure of 'Naked' Ga(I) and In(I) Salts and the Surprising Stability of Simple Ga(I) and In(I) Salts in the Coordinating Solvents Ether and Acetonitrile.

In this work, we present the solid-state structures of solvent-free Ga[pf] and In[pf] salts ([pf]- = [Al(ORF)4]-; RF = C(CF3)3), which are very rare examples of salts with truly 'naked' metal cations. Both salts may serve as starting materials for subvalent gallium and indium chemistry with very weakly coordinating ligands providing the freedom of choice for solvents and ligands for the future. On the other hand, we report and rationalize the formation and isolation of [M(OEt2)2][pf] and [M(MeCN)2][pf] (M= Ga, In), underlining the surprising stability of these subvalent group 13 M+ ions against disproportionation. Unexpectedly, tricoordinate and carbene analogous [Ga(L)2]+ ions with the [pf]- counterion are stable in L = acetonitrile and diethyl ether at room temperature, opening up possible applications for example in organic synthesis and catalysis.

Event-Triggered Adaptive Saturated Fault-Tolerant Control for Unknown Nonlinear Systems With Full State Constraints

This paper investigates the issue of event-triggered adaptive saturated fault-tolerant control (ESFC) for uncertain nonlinear systems with time-varying full state constraints (TFSCs), actuator saturation and faults as well as unknown control direction. A bounded function with an auxiliary variable is constructed by utilizing a novel dynamics of the auxiliary system, which contributes to reducing the adverse impact of actuator saturation. Different from the previous backstepping-based event-triggered control methods such specifications by either using fuzzy approximation or by employing neural approximation techniques, this paper skillfully addresses the unknown nonlinearities, actuator saturation and faults without involving any approximation structures, and thus, we proposes the ESFC on the basis of low-complexity design framework as contributing to communication and computational resource reduction. A rigorous theoretical analysis shows that the proposed control method is an effective way to handle with the problems of actuator saturation and faults, full state constraints, and unknown system uncertainties, while simultaneously simplifying the backstepping design and avoiding the issue of explosion of complexity. The asymptotic stability of the closed-loop system is guaranteed and the Zeno behavior can be effectively removed. We present an application example of a linear motor scenario to illustrate the effectiveness of the method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Since state constraints, actuator saturation and faults, unknown mechanism model, and limited bandwidths exist extensively in practical engineering systems, which constantly degrade the operation performance of the plant. To handle these disadvantages, this paper is focus on providing simple but effective ESFC methods to ensure the asymptotic stability and enhance reliability. Compared to existing results, the presented method only uses the state signals of system without using system dynamic functions under mild conditions, which provides a theoretical basis, and has the advantages of low-complexity design, and easy implementation in practical engineering. Preliminary physical experimental comparisons demonstrate that this method is applicable to practical liner-motor platform, and achieves satisfactory control performance.

Composing MPC With LQR and Neural Network for Amortized Efficiency and Stable Control

Model predictive control (MPC) is a powerful control method that handles dynamical systems with constraints. However, solving MPC iteratively in real time, i.e., implicit MPC, remains a computational challenge. To address this, common solutions include explicit MPC and function approximation. Both methods, whenever applicable, may improve the computational efficiency of the implicit MPC by several orders of magnitude. Nevertheless, explicit MPC often requires expensive pre-computation and does not easily apply to higher-dimensional problems. Meanwhile, function approximation, although scales better with dimension, still requires pre-training on a large dataset and generally cannot guarantee to find an accurate surrogate policy, the failure of which often leads to closed-loop instability. To address these issues, we propose a triple-mode hybrid control scheme, named Memory-Augmented MPC, by combining a linear quadratic regulator, a neural network, and an MPC. From its standard form, we derive two variants of such hybrid control scheme: one customized for chaotic systems and the other for slow systems. The proposed scheme does not require pre-computation and is capable of improving the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">amortized</i> running time of the composed MPC with a well-trained neural network. In addition, the scheme maintains closed-loop stability with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">any</i> neural networks of proper input and output dimensions, alleviating the need for certifying optimality of the neural network in safety-critical applications. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article was motivated by the need to reduce the amortized cost of MPC in repetitive industrial robotic applications, where long-term operational cost is important and safety is critical. Examples of such applications include factory robotic arm manipulation and fixed-route quadcopter payload transport. Unlike explicit MPC or function approximation, our approach does not require any pre-computation or pre-training. Rather, it attains task proficiency over time by learning a surrogate neural network on the spot and by gradually replacing the costly MPC with the more efficient surrogate model so long as safety permits. Consequently, the proposed scheme incurs a learning cost during the initial phase of the deployment but usually becomes more adept on the task afterwards, leading to amortized efficiency.

İşletmelerde Stratejik Planlama ve Bütçeleme ile Finansal Modelleme Uygulama Örneği

Bu çalışmada, işletmelerin finansal tablolarının birbiri ile entegrasyonu ve böylelikle denetiminin daha kolay yapılması ve işletme yönetimine raporlanması; bu yolla gelecek dönem için alınması gereken önlemlerin önceden tespiti amaçlanmış, örnek bir uygulama yapılarak finansal modellemenin bir işletmede nasıl yapılması gerektiği üzerinde durulmuştur. Stratejik planlama doğrultusunda işletme bütçesinin yapılması, nakit akış tablosu, yatırım raporu ve raporlama tablolarının entegre edilmesi suretiyle işletme için daha verimli ve etkin kullanılabilecek ‎bir finansal modelleme ‎sistemi tasarlanıp, uygulamalı olarak anlatılmıştır. Çalışmada ilk olarak “İşletmelerde stratejik planlama” ‎kavramı ele alınıp anlatılmıştır, stratejik ‎planlama ile işletmenin GZFT/SWOT analizi ve işletmelerde bütçeleme konusuna değinilmiştir.‎ Çalışmanın amacı, işletmelerin en büyük problemi olan geleceği ön görememelerine çözüm olarak işletmelerde finansal modelleme sistemiyle gelecek dönemler için işletmenin misyon ve vizyonu doğrultusunda belirlenen hedeflerin takibinin yapılması ve yönetime rapor edilerek gerekli önlemlerin önceden alınmasını sağlamaktır. Finansal modelleme özelinde işletme bütçelerinin yönetim aracı olarak sahip olduğu potansiyel gücü göstermek de çalışmanın amaçları arasında yer almakta ve çalışmada kurgusal örnek bir uygulama çalışması yapılarak daha iyi anlaşılması sağlanmıştır.

Dispersion state analysis in hot melt extruded, highly drug-loaded 3D printing filaments applying Raman microscopy

Abstract Objectives Highly drug-loaded polymer formulations are favorable intermediates in pharmaceutical applications, for example, for the individualized production of medicines via 3D printing with the maximum flexibility regarding dose strength and drug combination in a single dosage form. However, high-disperse drug loads are challenging for the process itself and the (intermediate) product properties, making the knowledge about the dispersion state of the drug particles achieved by the production process helpful to overcome such challenges. Methods Therefore, a novel dispersion state analysis technique based on scanning Raman microscopy is proposed in the present study and applied to HPMC filaments loaded with 20 wt%, 40 wt%, and 60 wt% theophylline. The qualitative and quantitative evaluations of the scans were correlated to melt viscosities, process data, and mechanical properties of the filaments. Key findings The analyses revealed not only an increasing particle size reduction with increasing drug load and thus increasing viscosity and mechanical energy input. The particle size reduction also caused a change in the filaments’ mechanical properties from elastic ductile to rigid brittle. Furthermore, an alignment of the elongated drug particles with the frozen three-dimensional flow pattern of the extruder and not only with the extrusion direction was elucidated. Conclusions Therefore, the necessity to investigate the dispersion state further is highlighted for future studies on highly drug-loaded polymer formulations, providing a novel measuring technique applicable to challenging pharmaceutical formulations.

Optimal Opacity-Enforcing Supervisory Control of Discrete Event Systems on Choosing Cost

To ensure opacity, it is optimal to retain as many as possible occurring event sequences. Contrary to this problem, the other optimal goal is to preserve the minimal occurring event sequences. Based on the choosing cost, an optimal opacity-enforcing problem with minimal discount choosing cost is presented under two constraints in this paper. The first constraint is the opacity of the controlled system. The second is the retention of the secret to the maximum. To solve the model, two scenarios on opacity are considered. For the two scenarios, some algorithms are presented to achieve the optimal solution for the model by using the method of dynamic programming. Then, the solutions produced by the algorithms are proved to be correct by theoretical proof. Finally, some illustrations and an application example on location privacy protection for the algorithms are given.

Methodological approach to probabilistic prediction and comparison of systems operation quality under conditions of uncertainty

 Abstract. Aim. To propose a methodological approach to probabilistic forecasting and comparison of the performance of systems producing material and/or information products, to illustrate the practicality of the proposed approach with examples in various applications. Methods. Methods and models based on the methods of probability theory and system analysis, brought to implementation in national standards of system engineering, are proposed for use. Results. Models of complex systems producing material and/or information products are adapted for predicting and comparing for the same system under different operating conditions, for different systems applied to the same time period or for different time periods with the same or different duration and operating conditions. The proposed approach covers methods for assessing the relative part of the system functions performed with acceptable quality, estimating costs in the life cycle of systems, assessing the relative degree of satisfaction of stakeholders associated with quality and costs in system operation. Conclusions. The efficiency of the proposed methodological approach to probabilistic forecasting and comparison of the performance of systems of various applications under conditions of uncertainty is demonstrated. The approach can be used for system analysis and optimisation of the performance of systems producing material and/or information products, substantiation of quantitative system requirements and engineering solutions aimed at meeting the needs of stakeholders.

Insights into commonalities of a sample: A visualization framework to explore unusual subset-dataset relationships

Domain experts are driven by business needs, while data analysts develop and use various algorithms, methods, and tools, but often without domain knowledge. A major challenge for companies and organizations is to integrate data analytics in business processes and workflows. We deduce an interactive process and visualization framework to enable value creating collaboration in inter- and cross-disciplinary teams. Domain experts and data analysts are both empowered to analyze and discuss results and come to well-founded insights and implications. Inspired by a typical auditing problem, we develop and apply a visualization framework to single out unusual data in general subsets for potential further investigation. Our framework is applicable to both unusual data detected manually by domain experts or by algorithms applied by data analysts. Application examples show typical interaction, collaboration, visualization, and decision support.

Rules and Regulations regarding the Punishment for Adultery Extracted from The Book "Fatawa Al-Nawazil" by Imam Abu Al-Laith Al-Samarqandi: Examples of Applications

This study aims to gather the jurisprudential rules and regulations specific to the punishment for adultery, extracted from the book Fatawa al-Nawazil by Imam Abu al-Laith al-Samarqandi, one of the prominent figures of the Hanafi school known for his extensive jurisprudential heritage and rich works. The study intends to explain these rules and regulations, highlighting their importance and evidence for the jurist and the mufti, and providing examples of subsidiary applications and contemporary issues falling under them. To achieve the objectives of the study, which include three chapters and a conclusion, the researcher employed an inductive and analytical approach. The study yielded a set of results and recommendations, among which highlighting the significant role of Imam al-Samarqandi in the field of jurisprudential rules and regulations was prominent. He relied on these rules and regulations in legal reasoning, preference, and issuing fatwas. One of the most important recommendations is to continue researching the extraction and gathering of scattered jurisprudential rules and regulations from the book Fatawa al-Nawazil by Imam al-Samarqandi. 

First-principles investigation of structural electronic magnetic and thermodynamic properties of CdS alloyed with Co transition metal

This research work investigates the structural, electronic, and magnetic properties of Cd1–xCoxS compounds. The supercells with 16 atoms have been studied by substituting a Cd atom with a Co atom in the cubic unit cell CdS from x = 0 to x = 1 in a Zinc-Blende structure based on the first principles of spin-polarized density functional theory as implemented in the WIEN2k code. The full potential augmented plane wave method FP-LAPW (Full potential linear augmented plane wave) was used in this study to evaluate the structural properties of the compounds, the exchange–correlation term is based on the PBE-GGA (Perdew–Burke–Ernzerhof generalized gradient approximation). For other properties, such as electronic structures, densities of states, and magnetic properties, the TB-mbj GGA (Tight Binding modified Becke–Johnson) exchange potential approximation is utilized. In addition to these properties, the thermodynamic properties were added advantage to clarify their comportment as temperature variation. The analysis of the density of spin-polarized states showed the ferromagnetic character with a from x = 0.125 to x = 0.875. The calculated total magnetic moments of Cd1–xCoxS are addressed concerning the change in lattice parameters. To track the shift brought on by adding Co, we ran our calculationsfrom x = 0.125 to x = 0.875 for Cd1–xCoxS compounds. Hence, the negative energyformation indicates that our compound can be made experimentally. The material may be used for solar cell applications. In summary, our findings represent a guide for future research. The findings of this work might provide useful direction for the usage of this alloy system in a variety of device applications, For example in high-efficiency tandem solar cells, magnetic sensors, and photoconductive detector applications.

Dynamic Response of PCCP under the Rockfall Impact Based on the Continuous–Discontinuous Method: A Case Study

Rockfalls are major geological hazards threatening prestressed concrete cylinder pipes (PCCPs) in water diversion projects. To accurately assess the impact of large deformation movements of rockfalls on PCCPs, this study utilized the continuous–discontinuous method to investigate the dynamic response of a PCCP under a rockfall. The impact mode of rockfalls, the mechanical characteristics of PCCP, and the nonlinear-contact characteristics between soil and PCCP were considered in this study. The advantages of continuous and discontinuous numerical simulation methods were utilized to establish a continuous and discontinuous coupling model of “tube-soil-rock” considering the interaction of soil and structure. The impact mechanism and process of PCCP under the rockfall were investigated by simulating the rockfall process and analyzing its spatiotemporal evolution. The influence of PCCP under rockfalls with different heights and radii was studied to clarify the effects of these two parameters on the PCCP. Combined with a practical application example of large-scale water transfer projects, there is a tendency of center flattening under static load and dynamic impact load, and the PCCP part directly below the impact point is the most dangerous. This investigation provided a comprehensive understanding of the impact mechanism of the PCCPs under rockfall. The findings of this study have significant implications for the design of the protection engineering of PCCPs and ensuring the safe operation of water diversion projects.

Flexible development and evaluation of machine‐learning‐supported optimal control and estimation methods via HILO‐MPC

AbstractModel‐based optimization approaches for monitoring and control, such as model predictive control and optimal state and parameter estimation, have been used successfully for decades in many engineering applications. Models describing the dynamics, constraints, and desired performance criteria are fundamental to model‐based approaches. Thanks to recent technological advancements in digitalization, machine‐learning methods such as deep learning, and computing power, there has been an increasing interest in using machine learning methods alongside model‐based approaches for control and estimation. The number of new methods and theoretical findings using machine learning for model‐based control and optimization is increasing rapidly. However, there are no easy‐to‐use, flexible, and freely available open‐source tools that support the development and straightforward solution to these problems. This article outlines the basic ideas and principles behind an easy‐to‐use Python toolbox that allows to solve machine‐learning‐supported optimization, model predictive control, and estimation problems quickly and efficiently. The toolbox leverages state‐of‐the‐art machine learning libraries to train components used to define the problem. Machine learning can be used for a broad spectrum of problems, ranging from model predictive control for stabilization, set point tracking, path following, and trajectory tracking to moving horizon estimation and Kalman filtering. For linear systems, it enables quick generation of code for embedded model predictive control applications. HILO‐MPC is flexible and adaptable, making it especially suitable for research and fundamental development tasks. Due to its simplicity and numerous already implemented examples, it is also a powerful teaching tool. The usability is underlined, presenting a series of application examples.

Furo, Pyrano, and Pyrido[2,3‐d]Pyrimidines: A Comprehensive Review of Synthesis and Medicinal Applications

AbstractDue to their extensive applications in pharmaceuticals and natural substances, organic synthesis and heterocyclic compounds have been at the forefront of research for many years. Pyrimidine is one of the heterocyclic compounds that have various derivatives with promising biological and pharmacological properties. This review article covers the synthesis and biological effects of pyrimidine derivatives, such as pyrano[2,3‐d]pyrimidines, pyrido[2,3‐d]pyrimidines, and furo[2,3‐d]pyrimidines. The compounds discussed in this review have a wide range of biological activities. Recent advances in green chemistry have led to the development of eco‐friendly synthetic methods for producing these bioactive heterocycles. This review aims to present various synthetic methods and biological effects of these compounds and provide new opportunities for organic chemists to develop potent nitrogen‐ and oxygen‐containing heterocycles for future applications. The review highlights examples of successful syntheses and applications of pyrimidine derivatives in the fields of antibacterial, antifungal, anticancer, enzyme inhibition, and antiviral research.

Women Safety Device Using IOT

Abstract - Addressing the safety concerns of women in society is a critical issue, and the application of technology offers a promising avenue to enhance their protection. A prime example of this technological application is the deployment of a GPS-based safety mechanism. This system, specifically designed for the assistance of women, features a GPS module capable of tracking the user's location. In emergency situations, the device quickly alerts a preselected emergency contact. Users can activate the system either through a smartphone application or by pressing a dedicated button on the device itself. Through the use of satellite technology, the GPS module in the device precisely locates the user and facilitates communication, ensuring timely assistance when needed. Keywords—At mega 328, GPS, GSM Module, Wi-Fi Controller

Understanding Cu Sintering and Its Role on Corrosion Behaviour for High-Temperature Microelectronic Application

There has been a significant rise in interest from academic and industry communities on copper nano and micro-particles-based sinter pastes for harsh environment die attach. However, sintering these particles is a complex process which is affected by many parameters, such as (i) particles size, shape, and distribution, (ii) sintering temperature, pressure, environment, and (iii) organic compounds used for the paste formulation. In literature, various research groups demonstrated that sintered copper layer can achieve good electrical conductivity and high strength. In our previous research [1, 2], we explained that microscale etched flakes are also capable of shear strength &gt;30Mpa while sintering with 10 MPa bonding pressure at 275°C for just 1 minute with negligible paste cost (in comparison to silver paste). However, very limited knowledge exists on literature about corrosion behaviour in sintered copper interconnects. This, from experience in the industry with silver sintering has proven to be critical to applications. For examples in high power LED headlamp applications, minor exposure to residual Sulphur emerging from vulcanized rubber seals has been observed to cause corrosion in silver sintered interconnects. Therefore, corrosion and its impact on performance and reliability must be considered, especially for safety critical applications. For this reason, we have studied the relationship between copper sintered samples and corresponding corrosion behaviours and compared again to pure copper (conventionally produced). The corrosion resistance of the samples in salt water was assessed via various electrochemical analysis techniques and correlated with sintered microstructure. Sample produced better corrosion resistance when fabricated with higher density (less porosity). However, in case of the microscale copper flakes-based interconnects, a pitting behaviour was observed. The sintered copper paste samples showed to be nobler than commercial copper. In addition, copper oxide and its role in accelerating/preventing oxidation is also studied.

A stretchable breathable washable all-textile smart wearable keyboard

The development of comfortable and lightweight wearable devices is an emerging technological goal in human-computer interaction. Conductive textiles attract a great deal of interest as versatile materials for wearable devices. It can naturally integrate into our daily clothing, making wearable devices more comfortable and convenient. However, developing all-textile wearable devices remains an important challenge. And the wiring of wearable devices in practical applications is also a thorny issue. In this study, a novel wearable smart keyboard is proposed. Benefit from the ingenious structural design of double-faced effect functional textiles and 3D spacer textiles, the smart keyboard achieves all-textile structure and the wires can also be hidden inside the 3D spacer textile. The smart keyboard is stretchable, breathable, washable and can be integrated with daily clothing by sewing. In addition to the functions of traditional keyboards, smart keyboards also have the ability to detect tapping force which lays the foundation for future intelligent applications, such as tracking the tapping force of typewriting to enhance security.The application examples of integrating the smart keyboard into lab-coat for typewriting are demonstrated. This study shows that the novel smart keyboard has great potential in the fields of wearable devices and human-computer interface.

A Bayesian Bernoulli-Exponential joint model for binary longitudinal outcomes and informative time with applications to bladder cancer recurrence data

BackgroundA variety of methods exist for the analysis of longitudinal data, many of which are characterized with the assumption of fixed visit time points for study individuals. This, however is not always a tenable assumption. Phenomenon that alter subject visit patterns such as adverse events due to investigative treatment administered, travel or any other emergencies may result in unbalanced data and varying individual visit time points. Visit times can be considered informative, because subsequent or current subject outcomes can change or be adapted due to previous subject outcomes.MethodsIn this paper, a Bayesian Bernoulli-Exponential model for analyzing joint binary outcomes and exponentially distributed informative visit times is developed. Via statistical simulations, the influence of controlled variations in visit patterns, prior and sample size schemes on model performance is assessed. As an application example, the proposed model is applied to a Bladder Cancer Recurrence data.Results and conclusionsResults from the simulation analysis indicated that the Bayesian Bernoulli-Exponential joint model converged in stationarity, and performed relatively better for small to medium sample size scenarios with less varying time sequences regardless of the choice of prior. In larger samples, the model performed better for less varying time sequences. This model’s application to the bladder cancer data showed a statistically significant effect of prior tumor recurrence on the probability of subsequent recurrences.

A Region-Based Approach for the Operational Reliability Evaluation of Power Systems With Renewable Energy Integration

Power system operational reliability evaluation is computationally time-consuming due to the need to analyze numerous system states resulting from uncertain renewable energies and loads as well as random outages of components. This paper presents a load feasible region (LFR) approach to accelerate the process of operational reliability evaluation. The LFR of each state, which is defined as a polyhedron in the load space, can be built in advance offline. The inner points of the LFR correspond to the loads that can be satisfied under the system operational constraints. Then, the preestablished LFR can be corrected with little computing effort considering the renewable energy fluctuation during the operation phase. The optimal load shedding under each state can be obtained directly by calculating the minimum Manhattan distance to the LFR's boundary. Multiple application examples are presented to demonstrate the efficiency and scalability of the proposed region-based approach.

Observation of solar radio burst events from Mars orbit with the Shallow Radar instrument

Context. Multispacecraft and multiwavelength observations of solar eruptions, such as flares and coronal mass ejections, are essential to understanding the complex processes behind these events. The study of solar burst events in the radio frequency spectrum has relied almost exclusively on data from ground-based observations and a few dedicated heliophysics missions such as STEREO or Wind. Aims. By reanalysing existing data from the Mars Reconnaissance Orbiter (MRO) Shallow Radar (SHARAD) instrument, a Martian planetary radar sounder, we discovered the instrument was also capable of detecting solar radio bursts and that it was able to do so with unprecedented resolution for a space-based solar instrument. In this study, we aim to demonstrate the reliability and value of SHARAD as a new solar radio observatory. Methods. We characterised the sensitivity of the instrument to type III solar radio bursts through a statistical analysis of correlated observations using STEREO and Wind as references. Using 38 correlated detections, we established the conditions under which SHARAD can observe solar bursts in terms of acquisition geometry. As an example of scientific application, we also present the first analysis of type III characteristic times at high resolution beyond 1 AU. Results. A simple logistic model based purely on geometrical acquisition parameters can predict burst show versus no-show in SHARAD data with an accuracy of 79.2%, demonstrating the reliability of the instrument in detecting solar bursts and laying the foundation for using SHARAD as a solar radio observatory. The extremely high resolution of the instrument, both in temporal and frequency directions; its bandwidth; and its position in the Solar System enable SHARAD to make significant contributions to heliophysics. Notably, it could provide data on plasma processes on the site of the burst generation and along the propagation path of associated fast electron beams.