Modern Applications Research Articles

Experimental behaviour of ductile diagonal connections for rack supported warehouses

Steel racking systems are widely adopted for storage purposes: they are thin-walled structures composed of consecutive trusses, connected with beams on which the palletized goods are stored. Their geometry and structural configuration strongly depend on market and operator necessities, and, in modern applications, racks can also function as the supporting structure of the warehouse itself in the form of Rack Supported or High-Bay Warehouses. With the increase of the overall geometric dimensions and the global weight of the stored material, the seismic action becomes more relevant for the design. Along these lines, the development and experimental testing of a dedicated seismic design approach for ductile steel racks is here presented, with particular attention to Rack Supported Warehouses. This approach exploits the ductility of trusses introduced via the plastic ovalization mechanism of the diagonal-to-upright connections while a tailored capacity design is used to assure the elastic behaviour of the rest of the structure and to keep the brittle failure mechanisms at bay.

The diffusion stability of an externally driven cavitation bubble in micro-confinement

The diffusion stability of a single cavitation bubble in a spherical liquid cell surrounded by an infinite elastic solid is considered. The time-periodic pressure in the solid far away from the liquid cell is used as an external driving, which initiates bubble oscillations along with the gas diffusion process in the bubble-in-cell system. The work is based on the engineering approximation according to which the bubble growth/reduction is considered on average, assuming that during the period of the external driving the mass of gas in the bubble does not noticeably change. This theory predicts the existence of stably oscillating bubbles in confined liquid undergoing an external driving force. Three possible diffusion regimes are revealed: 1) total bubble dissolution, 2) partial bubble dissolution, and 3) partial bubble growth, where the last two regimes provide the diffusion stability in the bubble-in-cell system. The parametric study of the influence of the gas concentration dissolved in the liquid on the resulting stable bubble size is conducted. The obtained results are compared with the results for the case of the stable bubble oscillations in the pressure sound field in a bulk (infinite) liquid. The theoretical findings of the present study can be used for improvement of the modern applications of ultrasound technology.

استخدام وسائل التواصل الاجتماعي وأثرها على الأداء التنظيمي في المشاريع الصغيرة لرائدات الأعمال "مشروع CURA"

This study aimed to identify the impact of using social media on organizational performance in small projects for female entrepreneurs in the application of the CURA project. To achieve the study objectives, the quantitative approach was used, and the questionnaire was used as a tool to collect data from the intentional study sample, which consisted of 170 individuals on the CURA project. 124 questionnaires were retrieved with a response rate of 73%, and analyzed using the multiple variance test using the SPSS statistical analysis package. The results of the study concluded that there is a statistically significant positive impact of using social media on organizational performance in its dimensions (time to market - satisfaction - innovation) in the application of the CURA project. The study recommended the need to work on activating social media on the widest scale due to its great importance in communication processes and the tremendous development in modern applications, by finding specialists or specialized departments in small projects to care about social media and work to activate it in the best possible way.

Increasing the energy efficiency of an electric vehicle powered by hydrogen fuel cells

The article considers fuel cell electric vehicle energy efficiency improvement by means of traction battery remanent state of charge modern control algorithms application which based on fuzzy logic. Fuel cell vehicle traction system used as experimental setup for the study includes brushless dc motor, lithium-ion batteries pack and electronic differential approach implementation. The results of simulation modelling in MATLAB-Simulink software comparing conventional PID-controller based and fuzzy logic based controller for vehicle speed control systems are presented. Fuzzy logic controller provides an electric vehicle dynamic behavior tuning for different driving modes automatically transferring the control system to economy mode when it possible. However, the control system is able to provide fast dynamic behavior when it is required. The proposed control algorithm is tested by means of developed experimental setup. Experimental results validate conducted simulation modelling results and the proposed control algorithm. Application of the proposed fuzzy logic control algorithm to control the electric vehicle dynamic behavior allows energy efficiency improvement and driving range increase.

Analysis of Correlation Effects of Double Mutations in Enzymes: A Revised Residual-Contact Network Clique Model.

The relationship between amino acid mutations and enzyme bioactivity is a significant challenge in modern bio-industrial applications. Despite many successful designs relying on complex correlations among mutations at different enzyme sites, the underlying mechanisms of these correlations still need to be explored. In this study, we introduced a revised version of the residual-contact network clique model to investigate the additive effect of double mutations based on the mutation occurrence topology, secondary structures, and physicochemical properties. The model was applied to a set of 182 double mutations reported in three extensively studied enzymes, and it successfully identified over 90% of additive double mutations and a majority of non-additive double mutations. The calculations revealed that the mutation additivity depends intensely on the studied mutation sites' topology and physicochemical properties. For example, double mutations on irregular secondary structure regions tend to be non-additive. Our method provides valuable tools for facilitating enzyme design and optimization. The code and relevant data are available at Github.

Quantum-tunneling deep neural network for optical illusion recognition

The discovery of the quantum tunneling (QT) effect—the transmission of particles through a high potential barrier—was one of the most impressive achievements of quantum mechanics made in the 1920s. Responding to the contemporary challenges, I introduce a deep neural network (DNN) architecture that processes information using the effect of QT. I demonstrate the ability of QT-DNN to recognize optical illusions like a human. Tasking QT-DNN to simulate human perception of the Necker cube and Rubin’s vase, I provide arguments in favor of the superiority of QT-based activation functions over the activation functions optimized for modern applications in machine vision, also showing that, at the fundamental level, QT-DNN is closely related to biology-inspired DNNs and models based on the principles of quantum information processing.

Classification, military applications, and opportunities of unmanned aerial vehicles

Unmanned aerial vehicles (UAVs) are cutting-edge technologies used for military purposes world-wide at tactical, operational, and strategic levels. This study provides an overview of the history and current state of military drones, considering a global and Ecuadorian background. Then, a classification of the UAVs developed and built in Ecuador is conducted based on their endurance, altitude, and wing span to understand the national context and progress. The research also delves into the applications of UAVs in several military operations and missions, aiming to create a framework that aligns UAV capabilities with specific operational needs; this permits the identification of the challenges and opportunities the country faces. Unmanned aerial systems have changed the battlefield, and the government needs to adapt to a national strategy that incorporates this technology; this research analyzes and provides insights to improve military capabilities such as exploring modern UAV military applications, technical updates in communication, navigation, and data acquisition systems; and the integration of emerging technologies like smart materials, artificial intelligence, and electric propulsion systems. This study provides valuable insights into the Ecuadorian UAVs that enhance the country’s military operations and offer some applications and uses of this technology for national security.

A Corrugated Edged Tapered Slot Antenna with Low Cross-Polarization and Moderate Gain for Phased Array Systems

ABSTRACT This paper presents a miniaturized Vivaldi antenna with a scan volume of ± 30° designed for the 6–18 GHz tactical operational band, commonly employed in phased array systems and modern surveillance applications. The proposed antenna offers enhanced radiation characteristics, low cross polarization, broad beam width, and moderate gain. The design presented in this paper follows a step-by-step approach to achieve enhanced performance in terms of multi-octave bandwidth and compact size. Initially, a traditional Vivaldi antenna was designed and examined, with a modified feed structure. Subsequently, corrugated edges were inserted into the antenna, increasing its electrical length and resulting in good impedance matching, especially in the 6–10 GHz frequency band. A prototype model is fabricated and tested to validate its performance against the simulation results. The measured results demonstrate that the return loss (S11) remains below −10 dB across the operating frequency range, achieving a 50% bandwidth, with a gain of 3–7 dB, and improved co-cross polarization of −23 dB at 6 GHz and −26 dB at 18 GHz.

IMPLEMENTATION OF A DYNAMIC PRICING SYSTEM IN RETAIL: AN ANALYTICAL REVIEW OF THE PRACTICES OF RUSSIAN COMPANIES

Over the past few years, the conditions and nature of doing business for Russian companies have changed dramatically. The processes of procurement, logistics, product sales, accounting and other business processes are automated. The development of artificial intelligence technology and the growing volume of data are additional growth drivers for the company. Within the framework of this article, an analytical review of the practices of applying the pricing system in retail of Russian companies was conducted. The pricing process is key, which allows you to directly influence the main economic indicators of the company’s activities, since sales volume, profit, demand for products, inventories of inventory resources can be regulated by means of competent changes in prices for goods. Dynamic pricing is gaining great popularity among retailers, which leads to the expansion of patent activities in terms of software and models for automating pricing, including using machine learning. In this article, the authors reviewed some of the most popular offers on the market for the introduction of dynamic pricing systems and analyzed them, revealed the main features and identified common features of building automated dynamic pricing models. The practices of implementing dynamic pricing systems in Russian companies were also investigated. The results obtained allow us to draw conclusions about the importance of using automated pricing systems in retail in modern conditions, their capabilities and application problems.

Durable and programmable ultrafast nanophotonic matrix of spectral pixels.

Locally addressable nanophotonic devices are essential for modern applications such as light detection, optical imaging, beam steering and displays. Despite recent advances, a versatile solution with a high-speed tuning rate, long-life durability and programmability across multiple pixels remains elusive. Here we introduce a programmable nanophotonic matrix consisting of vanadium dioxide (VO2) cavities on pixelated microheaters that meets all these requirements. The indirect Joule heating of these VO2 cavities can result in pronounced spectral modulation with colour changes and ensures exceptional endurance even after a million switching cycles. Precise control over the thermal dissipation power through a SiO2 layer of an optimized thickness on Si facilitates an ultrafast modulation rate exceeding 70 kHz. We demonstrated a video-rate nanophotonic colour display by electrically addressing a matrix of 12 × 12 pixels. Furthermore, inspired by the unique pixel-level programmability with multiple intermediate states of the spectral pixels, a spatiotemporal modulation concept is introduced for spectrum detection.

Roadmap of Adversarial Machine Learning in Internet of Things-Enabled Security Systems.

Machine learning (ML) represents one of the main pillars of the current digital era, specifically in modern real-world applications. The Internet of Things (IoT) technology is foundational in developing advanced intelligent systems. The convergence of ML and IoT drives significant advancements across various domains, such as making IoT-based security systems smarter and more efficient. However, ML-based IoT systems are vulnerable to lurking attacks during the training and testing phases. An adversarial attack aims to corrupt the ML model's functionality by introducing perturbed inputs. Consequently, it can pose significant risks leading to devices' malfunction, services' interruption, and personal data misuse. This article examines the severity of adversarial attacks and accentuates the importance of designing secure and robust ML models in the IoT context. A comprehensive classification of adversarial machine learning (AML) is provided. Moreover, a systematic literature review of the latest research trends (from 2020 to 2024) of the intersection of AML and IoT-based security systems is presented. The results revealed the availability of various AML attack techniques, where the Fast Gradient Signed Method (FGSM) is the most employed. Several studies recommend the adversarial training technique to defend against such attacks. Finally, potential open issues and main research directions are highlighted for future consideration and enhancement.

Efficient Fabrication of Disordered Graphene with Improved Ion Accessibility, Ion Conductivity, and Density for High-Performance Compact Capacitive Energy Storage.

High-performance compact capacitive energy storage is vital for many modern application fields, including grid power buffers, electric vehicles, and portable electronics. However, achieving exceptional volumetric performance in supercapacitors is still challenging and requires effective fabrication of electrode films with high ion-accessible surface area and fast ion diffusion capability while simultaneously maintaining high density. Herein, a facile, efficient, and scalable method is developed for the fabrication of dense, porous, and disordered graphene through spark-induced disorderly opening of graphene stacks combined with mechanical compression. The obtained disordered graphene achieves a high density of 1.18gcm-3, sixfold enhanced ion conductivity compared to common laminar graphene, and an ultrahigh volumetric capacitance of 297Fcm-3 in ionic liquid electrolyte. The fabricated stack cells deliver a volumetric energy density of 94.2WhL-1 and a power density of 13.7kWL-1, representing a critical breakthrough in capacitive energy storage. Moreover, the proposed disordered graphene electrodes are assembled into ionogel-based all-solid-state pouch cells with high mechanical stability and multiple optional outputs, demonstrating great potential for flexible energy storage in practical applications.

Flexo-Phototronic Boosted Self-Powered Ultraviolet Detection in ZnAl:Layered Double Hydroxide Nanosheets/NiO Heterostructure.

Developing self-powered and flexible optoelectronic sensors with high responsivity and speed is crucial for modern applications, motivating continuous efforts to enhance their performance. Flexo-phototronics is a less-explored but promising technique to elevate the performance of optoelectronics. Therefore, this work addresses the potential of utilizing the flexo-phototronic effect to enhance the performance of a flexible and self-powered ultraviolet photodetector (UV PD) based on ZnAl:LDH (layered double hydroxides) nanosheets (Ns)/NiO heterostructure. The vertically oriented ZnAl:LDH Ns are synthesized via a simple method involving the immersion of a sputtered 10% Al-doped ZnO thin film in deionized water at room ambient conditions. The fabricated PD exhibits an impressive response to 365 nm UV light, with high sensitivity in the order of 103. The device's photocurrent and responsivity are significantly enhanced by the flexo-phototronic effect, attributed to the flexoelectric properties of ZnAl:LDH Ns. Specifically, applying an inhomogeneous tensile strain of 2% boosted the device responsivity by 57.1% and improved its operational speed. Furthermore, a working model revealing the altered energy-band structure is demonstrated to elucidate the flexo-phototronic-induced boost in the photoresponse. The PD also demonstrated a sustainable performance under severe bending cycles, underlining the good flexibility of the device. The results presented in this study demonstrate a self-powered and flexible UV PD and provide a viable approach to augment the performance of optoelectronics through the flexo-phototronic effect.

The Role of Cannabinoids in Advancing Cancer Treatment: Insights from Evidence-Based Medicine.

This document critically examines the role of cannabinoids in cancer care during an era marked by rapid advancements in oncology and changing perceptions on cannabis. It traces the historical context of cannabis in medicinal use, navigating its journey from widespread acceptance, subsequent criminalization, to its resurgence in modern therapeutic applications, particularly within the framework of Evidence-Based Medicine (EBM). Anchored in EBM principles, this study synthesizes current research from clinical trials, systematic reviews, and meta-analyses to evaluate the efficacy and safety of cannabinoids in oncology. The focus is on their palliative effects, considering the nuances of effectiveness, risk assessment, and challenges inherent in translating these findings into clinical guidelines. The study seeks to bridge the gap between scientific research and clinical practice, offering insights to inform future oncological therapies and symptom management strategies involving cannabinoids. The potential benefits and risks of cannabinoid use in cancer treatment are assessed to guide clinicians and researchers in developing comprehensive, evidence-based approaches to patient care.

History and Evolution of the Electroencephalogram.

This paper summarizes the history and evolution of the electroencephalogram (EEG). The EEG, used to record the electrical activity of the brain, is a pivotal tool in neuroscience and medicine. Its history and evolution reflect significant advancements in our understanding of brain function and our ability to diagnose and treat neurological conditions. This tool has revolutionized our understanding of the brain's electrical activity and is the cornerstone for the diagnosis and treatment of epilepsy and related disorders.The evolution of the EEGfrom early experimental observations to sophisticated modern applications highlights the profound progress in our ability to monitor and interpret brain activity. The EEG remains an invaluable tool in clinical and research settings, continually evolving with technological advancements to expand our understanding of the human brain. This review traces the journey of this iconic tool.

Modern Applications of Blockchain Technologies in Contemporary Times: A Systematic Review

Blockchain technology is one of the most innovative and versatile technological advancements of contemporary times, finding applications in various fields such as finance, healthcare, education, and real estate. This paper provides a systematic review of blockchain technology, its historical evolution, fundamental concepts, different types of blockchain, and its various applications. The study also explores the key characteristics of blockchain, including decentralization, transparency, and immutability, and discusses the challenges and limitations faced by the technology, such as scalability issues, security concerns, and regulatory challenges. Additionally, the paper looks into future trends and developments in blockchain technology, particularly advancements in consensus algorithms, integration with other emerging technologies, and the rise of Central Bank Digital Currencies (CBDCs) and Decentralized Finance (DeFi).

Reaching the efficiency limit of arbitrary polarization transformation with non-orthogonal metasurfaces

Polarization transformation is at the foundation of modern applications in photonics and quantum optics. Notwithstanding their applicative interests, basic theoretical and experimental efforts are still needed to exploit the full potential of polarization optics. Here, we reveal that the coherent superposition of two non-orthogonal eigen-states of Jones matrix can improve drastically the efficiency of arbitrary polarization transformation with respect to classical orthogonal polarization optics. By exploiting metasurface with stacking and twisted configuration, we have implemented a powerful configuration, termed “non-orthogonal metasurfaces”, and have experimentally demonstrated arbitrary input-output polarization modulation reaching nearly 100% transmission efficiency in a broadband and angle-insensitive manner. Additionally, we have proposed a routing methodology to project independent phase holograms with quadruplex circular polarization components. Our results outline a powerful paradigm to achieve extremely efficient polarization optics, and polarization multiplexing for communication and information encryption at microwave and optical frequencies.

Physicochemical properties of 2-amino-5-methylpyridinium 3-carboxy-4-hydroxybenzenesulfonate single crystal: An efficient material for optoelectronic applications

A novel third-order organic nonlinear optical (NLO) material with promising excellent properties in the crucial NLO application. For the first time high NLO active 2-amino-5-methylpyridinium 5-sulfosalicylic acid (2A5MP3C4H) has been rationally designed and single crystals have been grown by the slow evaporation solution growth technique (SEST). X-ray diffraction analysis revealed that 2A5MP3C4H belongs to the category of triclinic system and has a Centro symmetric space group of P1. Remarkably, the grown crystal exhibits competitive and even superior physical properties including high thermal stability and wider transparency than the standard NLO single crystal. The morphology of the as-grown 2A5MP3C4H crystal was equivalent to the theoretically produced morphology. Fourier transform infrared spectroscopy (FTIR) was used to investigate the molecular vibrations of 2A5MP3C4H. The optical characteristics of 2A5MP3C4H recorded optical transmittance spectrum reveals that the 2A5MP3C4H crystal possesses good optical transparency in the range between ultraviolet (UV) and near-infrared (NIR) regions. Intriguingly, the short cut-off edge of the grown crystal is found to be about 345 nm which is more favourable for developing modern photonic and optoelectronic devices application. The Laser Damage Threshold (LDT), were investigated to understand its effectiveness to be utilized in the area of optoelectronics and photonics. The thermal and mechanical stability of 2A5MP3C4H was tested using Thermo gravimetric Differential Thermal Analysis (TG-DTA) and Vickers hardness test. The third-order nonlinear optical properties of 2A5MP3C4H single crystals were analyzed, which involves studying the absorption coefficient and refractive index behaviour using a continuous wave laser. Additionally, the grown crystal exhibits outstanding third-order NLO response and wide LDT, which are crucial characteristics for developing practical NLO devices. There are various 2-amino-5-methylpyridine (2A5MP) derivative single crystals available in the literature. However 2A5MP3C4H crystal has not been reported earlier. So, we have carried out our researcher on this new novel crystal. Our findings consequently open a novel path for the logical design of enormous, thermally stable and NLO-active organic complexes for true NLO applications.

Roadmap on specialty optical fibers

Abstract Optical fibers, long an enabling technology for telecommunications, are proving to play a central role in a growing number of modern applications, starting from high speed broad band internet to medical surgery and entering across the entire spectrum of scientific, military, industrial and commercial applications. Specialty optical fibers either special waveguide structure or novel material composition becomes heart of all fiber based advanced photonics devices and components. This rapidly evolving field calls on the expertise and skills of a broad set of different disciplines: materials science, ceramic engineering, optics, electrical engineering, physics, polymer chemistry, and several others. This roadmap on specialty optical fibers addresses different technologies and application areas. It is constituted by fourteen contributions authored by world-leading experts, providing insight into the current state-of-the-art and the challenges their respective fields face. Some articles address the area of multimode fibers, including the nonlinear effects occurring in them. Several other articles are dedicated to doped, plastic, and soft-glass fibers. Large mode area fibers, hollow-core fibers, and nanostructured fibers are also described in different sections. The use of some of such fibers for optical amplification and to realize several kinds of optical sources - including lasers, single photon sources and supercontinuum sources - is described in some other sections. Different approaches to satisfy applications at visible, infrared and THz spectra regions are also discussed. Throughout the roadmap there is an attempt to foresee and to suggest future directions in this particularly dynamic area of optical fiber technology.

Advancing cryptography: a novel hybrid cipher design merging Feistel and SPN structures

In the dynamic field of cryptography, lightweight ciphers play a pivotal role in overcoming resource constraints in modern applications. This paper introduces a lightweight cryptographic algorithm by seamlessly merging the proven characteristics of the Feistel cipher CLEFIA with the advanced substitution-permutation network (SPN) framework of RECTANGLE for key generation. The algorithm incorporates a specially optimized feather S-box, balancing efficiency and security in both CLEFIA and RECTANGLE components. The RECTANGLE key generation, vital for the proposed lightweight technique, enhances overall cryptographic security and efficiency. Meticulous consideration of resource limitations maintains the algorithm's lightweight nature, making it well-suited for applications with restricted computational resources. To validate the efficacy of the lightweight algorithm, extensive evaluation on encrypted data is conducted using National Institute of Standards and Technology (NIST) tools, known for assessing cryptographic algorithm quality. Results reveal a high degree of randomness, indicative of robust resistance against cryptographic attacks. This manuscript provides a comprehensive examination of the lightweight algorithm, emphasizing key attributes, security enhancements, and successful integration of the optimized feather S-box. Rigorous testing, particularly NIST tool-based randomness analysis, offers empirical evidence of the algorithm's resilience against attacks, establishing its suitability for secure data encryption in resource-limited environments.<p> </p>