Standardization Efforts Research Articles

The evolution of embedded systems in automotive industry: A global review

The evolution of embedded systems in automotive industry: A global review

Reviewing advancements in privacy-enhancing technologies for big data analytics in an era of increased surveillance

In the contemporary landscape of big data analytics, privacy concerns loom large, exacerbated by escalating surveillance measures. This review delves into the advancements of privacy-enhancing technologies (PETs) amidst this era of heightened scrutiny. The review explores the evolving landscape of PETs, highlighting their pivotal role in safeguarding individual privacy while enabling meaningful data analysis. Firstly, the review elucidates the escalating surveillance environment, characterized by ubiquitous data collection practices and the proliferation of sophisticated monitoring mechanisms. Against this backdrop, the imperative for robust privacy solutions becomes evident. Subsequently, the review navigates through the array of PETs, encompassing differential privacy, homomorphic encryption, secure multi-party computation, and federated learning, among others. Each technology is scrutinized for its efficacy in mitigating privacy risks without compromising analytical utility. Furthermore, the review delineates notable applications of PETs across diverse domains, including healthcare, finance, and social media. Case studies exemplify how PETs facilitate data sharing and collaborative analysis while preserving confidentiality and compliance with regulatory frameworks. Moreover, the review examines the challenges hindering the widespread adoption of PETs, such as computational overhead, interoperability issues, and regulatory ambiguities. Strategies for overcoming these hurdles are elucidated, encompassing advancements in algorithmic efficiency, standardization efforts, and policy advocacy. The review underscores the pivotal role of PETs in reconciling the imperatives of data analytics with the imperatives of privacy protection amidst escalating surveillance. It emphasizes the necessity for interdisciplinary collaboration among researchers, policymakers, and industry stakeholders to foster the development and deployment of effective PET solutions, thereby ensuring a harmonious balance between data utility and individual privacy rights in the digital age.

Accounting for digital currencies: A review of challenges and standardization efforts

In the wake of the Fourth Industrial Revolution, the ascent of digital currencies heralds a transformative era in the global financial landscape, challenging traditional paradigms of currency, commerce, and regulation. This study delves into the emergence, integration, and implications of digital currencies within the global economy, with a particular focus on the accounting and regulatory challenges they pose. Through a meticulous examination of global adoption trends, technological advancements, and the historical evolution of digital currencies, this paper aims to dissect the multifaceted impact of these novel financial instruments on financial reporting, transparency, and regulatory frameworks. Employing a qualitative literature review strategy alongside thematic analysis, the study identifies key challenges in volatility, valuation, transaction anonymity, and the pressing need for standardized accounting practices to enhance comparability and transparency in financial reporting. The investigation extends to the scrutiny of current accounting standards, regulatory responses, and the concerted efforts towards standardization and best practices in digital currency accounting. The findings underscore a critical juncture for practitioners and regulators alike, navigating the intricate accounting landscape shaped by digital currencies. The study culminates in advocating for adaptive regulatory frameworks and standardized accounting practices, emphasizing the necessity of international collaboration and continuous research to harness the potential of digital currencies while safeguarding financial stability and integrity. Recommendations for future research and policy development are proposed to address the evolving dynamics of digital currencies, aiming to support innovation, ensure financial transparency, and maintain regulatory efficacy in the digital age.

Icephobic Coating Based on Novel SLIPS Made of Infused PTFE Fibers for Aerospace Application.

The development of slippery surfaces has been widely investigated due to their excellent icephobic properties. A distinct kind of an ice-repellent structure known as a slippery liquid-infused porous surface (SLIPS) has recently drawn attention due to its simplicity and efficacy as a passive ice-protection method. These surfaces are well known for exhibiting very low ice adhesion values (τice < 20 kPa). In this study, pure Polytetrafluoroethylene (PTFE) fibers were fabricated using the electrospinning process to produce superhydrophobic (SHS) porous coatings on samples of the aeronautical alloy AA6061-T6. Due to the high fluorine-carbon bond strength, PTFE shows high resistance and chemical inertness to almost all corrosive reagents as well as extreme hydrophobicity and high thermal stability. However, these unique properties make PTFE difficult to process. For this reason, to develop PTFE fibers, the electrospinning technique has been used by an PTFE nanoparticles (nP PTFE) dispersion with addition of a very small amount of polyethylene oxide (PEO) followed with a sintering process (380 °C for 10 min) to melt the nP PTFE together and form uniform fibers. Once the porous matrix of PTFE fibers is attached, lubricating oil is added into the micro/nanoscale structure in the SHS in place of air to create a SLIPS. The experimental results show a high-water contact angle (WCA) ≈ 150° and low roll-off angle (αroll-off) ≈ 22° for SHS porous coating and a decrease in the WCA ≈ 100° and a very low αroll-off ≈ 15° for SLIPS coating. On one hand, ice adhesion centrifuge tests were conducted for two types of icing conditions (glaze and rime) accreted in an ice wind tunnel (IWT), as well as static ice at different ice adhesion centrifuge test facilities in order to compare the results for SHS, SLIPs and reference materials. This is considered a preliminary step in standardization efforts where similar performance are obtained. On the other hand, the ice adhesion results show 65 kPa in the case of SHS and 4.2 kPa of SLIPS for static ice and <10 kPa for rime and glace ice. These results imply a significant improvement in this type of coatings due to the combined effect of fibers PTFE and silicon oil lubricant.

Refactoring a Complex Scientometric Software System to Support PostgreSQL Database Management System

The problem of software import substitution is under a great deal of attention in Russia since 2015. As a part of import substitution for a complex software system, database migration presents a considerable risk. Despite the SQL ISO standardization efforts, different implementations of SQL relational database management system are partially incompatible on the level of source codes for the schema, queries and stored procedures. Incompatibilities can manifest even at the level of query semantics. Some traits of complex scientometric software systems further complicate the migration process. Such traits include the complex data model and, consequently, the presence of non-trivial graph-traversing SQL queries which should complete fast enough to be used interactively for thousands of users simultaneously. In this paper an experience of refactoring a complex scientometric software system to support PostgreSQL database management system is presented. Our approach includes both usage and modification of the existing tools and development of the in-house software to support the refactoring process compounded with an extensive automated testing procedures.

Role of Hydroponics in Improving Water-Use Efficiency and Food Security

Hydroponic agriculture offers a soilless cultivation method that can enhance crop yields and sustainability. With decreasing arable land and water availability, hydroponics is positioned to complement conventional farming approaches to support global food security. This paper reviews the current status and future innovations in precision hydroponic technologies. Leading application crops, geographic adoption patterns, growth potential in developing countries, and technological advances are analyzed. Key challenges limiting widespread implementation are discussed, including infrastructural costs, lack of expertise, and inadequate research investments. Proposed legislation and standardization efforts in major markets are outlined. Ongoing improvements in automation, renewable energy integration, biocontrols and tailored crop varieties can further overcome limitations. The paper offers recommendations to promote hydroponics through targeted research initiatives, public incentives and localized equipment development. With appropriate regulatory support and sustained funding commitment, hydroponic systems can bolster food ecosystem resilience. The COVID-19 crisis has highlighted the interlinked risks in concentrated, centralized agriculture. More decentralized precision approaches can enhance stability. Hydroponics and vertical farming innovations can enable sustainable intensification to meet future nutritional demands. Adoption efforts to date have focused on profitable vegetable and herb markets in advanced economies, but expanding technical skills training and appropriate technologies globally would support wider implementation. With further commercial maturation and policy regulations keeping pace with innovations, hydroponics can be an integral strategy for sustainable crop production worldwide.

Habitat Utilization and Behavioral Patterns of the Endemic Sri Lankan Green Pit Viper (Craspedocephalus trigonocephalus) in the Wet Zone of Sri Lanka

Behavioral patterns and habitat utilization of the endemic Green Pit Viper (GPV) Craspedocephalus trigonocephalus were studied in the wet zone of Sri Lanka. The region, which is covered by the wet zone, has no significant dry periods and a moderately high mean annual rainfall of over 2,500 mm. Data collection occurred between April 2021 and March 2022 with a total of 260 hours of standardized sampling effort distributed throughout the collection period. The method used was an active search which consists of a visual search of up to six meters from the central line along each side of the quadrate. Quadrats were placed in habitats, taking each GPV sighting as the center of a quadrate. At each GPV-occupied quadrat, ambient temperature, body surface temperature, prey availability, perch position and perch light level were recorded. The day was divided into six-time periods as; early morning, morning, mid-day, evening, late evening, and night. Activity level was determined considering the number of GPV that could be visually observed. A total of 49 GPV were examined during the study. Focal animal sampling was conducted, and an ethogram was developed. A strong positive relationship was observed between ambient temperature (Ta) and body surface temperature (Ts) of GPVs (Pearson correlation r=0.936). The highest number of individuals preferred filtered sun light (57.14%). C. trigonocephalus mostly preferred distal position on the branches followed by middle and apical. There was a significant difference in the percentage of individuals with different behaviors [ANOVA, F=3.64, p&lt;0.05]. Behavioral pattern of GPV varied in the temporal scale during the day. During the morning time slot, C. trigonocephalus spent most of the time ambushing (16.12%) and basking (6.42%) respectively. During the mid-day they spent most of their time basking (10.57%), followed by resting (7.15%). The evening, late evening, night, and early morning slots were spent mostly on ambushing. The highest average time of 239 min was spent on ambushing behavior. Feeding behavior (9.8 min) had relatively short time on average. Results of this study indicate that C. trigonocephalus is well adapted for the utilization of its preferred habitat in the wet zone, and that, it displayed behavioral patterns that vary within temporal scales, which results in more efficient and effective utilization of resources. Therefore, this study provides important insights for conservation and management of C. trigonocephalus by critically evaluating the requirements of this species. &#x0D; Keywords: Craspedocephalus trigonocephalus, Behavior, Endemic pit viper, Wet zone

Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine.

Advancements in data acquisition and computational methods are generating a large amount of heterogeneous biomedical data from diagnostic domains such as clinical imaging, pathology, and next-generation sequencing (NGS), which help characterize individual differences in patients. However, this information needs to be available and suitable to promote and support scientific research and technological development, supporting the effective adoption of the precision medicine approach in clinical practice.Digital biobanks can catalyze this process, facilitating the sharing of curated and standardized imaging data, clinical, pathological and molecular data, crucial to enable the development of a comprehensive and personalized data-driven diagnostic approach in disease management and fostering the development of computational predictive models.This work aims to frame this perspective, first by evaluating the state of standardization of individual diagnostic domains and then by identifying challenges and proposing a possible solution towards an integrative approach that can guarantee the suitability of information that can be shared through a digital biobank.Our analysis of the state of the art shows the presence and use of reference standards in biobanks and, generally, digital repositories for each specific domain. Despite this, standardization to guarantee the integration and reproducibility of the numerical descriptors generated by each domain, e.g. radiomic, pathomic and -omic features, is still an open challenge. Based on specific use cases and scenarios, an integration model, based on the JSON format, is proposed that can help address this problem.Ultimately, this work shows how, with specific standardization and promotion efforts, the digital biobank model can become an enabling technology for the comprehensive study of diseases and the effective development of data-driven technologies at the service of precision medicine.

Biomarkers of Cartilage Composition.

Magnetic resonance imaging (MRI) has significantly advanced the understanding of osteoarthritis (OA) because it enables visualization of noncalcified tissues. Cartilage is avascular and nurtured by diffusion, so it has a very low turnover and limited capabilities of repair. Consequently, prevention of structural and detection of premorphological damage is key in maintaining cartilage health. The integrity of cartilage composition and ultrastructure determines its mechanical properties but is not accessible to morphological imaging. Therefore, various techniques of compositional MRI with and without use of intravenous contrast medium have been developed. Spin-spin relaxation time (T2) and spin-lattice relaxation time constant in rotating frame (T1rho) mapping, the most studied cartilage biomarkers, were included in the recent standardization effort by the Quantitative Imaging Biomarkers Alliance (QIBA) that aims to make compositional MRI of cartilage clinically feasible and comparable. Additional techniques that are less frequently used include ultrashort echo time with T2*, delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), glycosaminoglycan concentration by chemical exchange-dependent saturation transfer (gagCEST), sodium imaging, and diffusion-weighted MRI.

A Comprehensive Review of Hybrid Strategies and Deep Learning in Tyre Defect Detection

Abstract: This comprehensive exploration centers on the pivotal role of tyres in vehicular performance, particularly in the era of autonomous vehicles. Navigating the intricate dynamics of tyre-road interactions, the study delves into a spectrum of methodologies for effective tyre defect detection. Emphasizing the evolutionary landscape from intelligent tyres with sensor technology to the transformative impact of deep learning, the focus remains on addressing challenges such as imbalanced datasets and limited labeled samples through strategies like transfer learning and domain adaptation. Key studies include innovative approaches like Hybrid-DBN for crack detection, 3D laser scanning for low-visibility defects, and the application of Wasserstein GAN for handling imbalanced datasets. These advancements signal paradigm shifts in the field, integrating hybrid methodologies, inventive data augmentation, and domain adaptation. Real-world scenarios, including tyre tread wear detection and MEMS accelerometer-based monitoring, highlight the practical implications of these methodologies. The conclusion acknowledges persistent challenges and suggests future research directions, advocating for standardized evaluation frameworks and collaborative efforts. The synthesis of insights contributes to the maturation of tyre defect detection research, offering a guide for the development of safer and more reliable vehicles on the road.

Comparative Study: Cloud Computing

The concept of cloud computing was invented by the Internet service providers to support a large number of users and elastic services with the least number of resources. This expanding field of cloud computing has become the need of the future and is at the cutting edge. The hosting process of cloud computing has been transformed from internal IT systems to public services, from cost-effective tools to revenue generator tools, and from ISP to telecom services. This paper describes the concept, overview, services of cloud computing, issues and challenges of cloud computing as the value chain and standardization effort. Working of Cloud is the distribution of Computing services which include servers, database, networking devices, storage devices, software, analytics and intelligence-over the Internet (“the Cloud“) to offer faster revolution, cost-saving and flexible resources, and economies of scale. The purpose of cloud computing is to deliver computing services which include servers, storage, database, networking, software, analytics, intelligence, and more, over the Cloud (Internet).Overviewing at the characteristics of cloud computing there are majorly 5 characteristics : (1) large scale computing resources (2) high scalability &amp; elasticity (3)shared resource pool (virtualized and physical resource) (4)dynamic resource scheduling (5) general purpose

Performance and Efficiency Exploration of Hardware Polynomial Multipliers for Post-Quantum Lattice-Based Cryptosystems

The significant effort in the research and design of large-scale quantum computers has spurred a transition to post-quantum cryptographic primitives worldwide. The post-quantum cryptographic primitive standardization effort led by the US NIST has recently selected the asymmetric encryption primitive Kyber as its candidate for standardization and indicated NTRU, as a valid alternative if intellectual property issues are not solved. Finally, a more conservative alternative to NTRU, NTRUPrime was also considered as an alternate candidate, due to its design choices that remove the possibility for a large set of attacks preemptively. All the aforementioned asymmetric primitives provide good performances, and are prime choices to provide IoT devices with post-quantum confidentiality services. In this work, we present a comprehensive exploration of hardware designs for the computation of polynomial multiplications, the workhorse operation in all the aforementioned cryptosystems, with a thorough analysis of performance, compactness and efficiency. The presented designs cope with the differences in the arithmetics of polynomial rings employed by distinct cryptosystems, benefiting from configurations and optimizations that are applicable at synthesis time and/or run time. In this context, we target a use case scenario where long-term key pairs are used, such as the ones for VPNs (e.g., over IPSec), secure shell protocols and instant messaging applications. Our high-performance design variants exhibit figures of latency comparable to the ones needed for the execution of the symmetric cryptographic primitives also included in the Post-Quantum schemes. Notably, the performance figures of the designs proposed for NTRU and NTRU Prime surpass the ones described in the related literature.

CLSM-Guided Imaging for Quantifying Endodontic Disinfection.

Elimination of microbes in the root canal system is crucial for achieving long-term success in endodontic treatment. Further efforts in study design and standardization are needed in order to improve the validity and comparability of in vitro results on endodontic disinfection procedures, in turn improving clinical outcomes. This study optimizes two models at all steps: tooth selection, pretreatment, inoculation method (by growth or centrifugation), and confocal laser scanning microscopy (CLSM)-guided imaging of LIVE/DEAD-stained specimens. Individual anatomical conditions lead to substantial differences in penetration depth. Sclerosis grading (SCG), a classification system introduced in this study, provides information about the sclerosis status of the dentine and is helpful for careful, specific, and comparable tooth selection in in vitro studies. Sonically activated EDTA for the pretreatment of roots, inoculation of Enterococcus faecalis in an overflow model, 3-4 weeks of incubation, as well as polishing of dentine slices before staining, led to advances in the visualization of bacterial penetration and irrigation depths. In contrast, NaOCl pretreatment negatively affected performance reproducibility and should be avoided in any pretreatment. Nonsclerotized teeth (SCG0) can be used for microbial semilunar-shaped inoculation by centrifugation as a "quick-and-dirty" model for initial orientation. In conclusion, CLSM-guided imaging for quantifying endodontic infection/disinfection is a very powerful method after the fine-tuning of materials and methods.

Pediatric kidney transplantation in Europe, a clinical snapshot pilot.

Pediatric kidney transplantations are rarely performed, and there is limited knowledge about the diversity in current clinical practices across Europe. This study aims to explore the utility of clinical snapshot studies in identifying these disparities, establishing a foundation for future snapshot studies and standardization efforts. A pilot clinical snapshot study was conducted, with invitations extended to all 109 pediatric kidney transplant centres in Europe. Each participating centre provided pre-, peri-, and postoperative data concerning their most recent thirty transplantations. The primary outcomes encompassed the evaluation of disparities in donor-recipient selection, surgical techniques, post-operative drainage procedures, and immunosuppressive therapy protocols. Secondary outcomes involved the analysis of rejection rates, incidence of infections, and graft survival. The study involved 439 patients from fifteen centres (14%) in twelve countries, with varying transplant volumes (range 1-29 transplantations per year) and follow-up periods. Significant differences were found among centres in terms of donor types, cold and warm ischemia time, pre-emptive transplant rates, and kidney transplant drainage methods. The rate of living donors varied between 3% and 90% and the median duration of cold ischemia ranged was 770 min after deceased donation and 147 min after living donation. Basiliximab was the dominant induction therapy, yet steroid withdrawal varied widely. Infection, rejection, and graft survival rates also varied significantly between centres. This study revealed substantial variation in clinical practices among European centres performing pediatric kidney transplantations. These findings could serve as a stimulus for international dialogue and collaboration.

GNSS Software-Defined Radio: History, Current Developments, and Standardization Efforts

GNSS Software-Defined Radio: History, Current Developments, and Standardization Efforts

Ideal free distributions form across a regulatory boundary in the Northwest Atlantic Fisheries Organization (NAFO) Division 4X and 5Z groundfish fisheries

We used isodars, developed from the ideal free distribution (IFD), to predict the distribution of fishing effort across regulatory boundaries in the south-western Scotian Shelf’s haddock fishery. Our analysis was focused around the boundary between Northwest Atlantic Fisheries Organization’s Divisions 4X and 5Z. While effort within 4X was related to the standardized catch value and effort experienced along the 4X–5Z boundary, most effort predictions across the boundary were also accurate. Accuracy of these cross-boundary isodars suggests that a high degree of movement across the boundary meets the IFD assumption of free movement and thus, effort on one side of the boundary is related to fishing success on the other side of the boundary. Fisheries management strategies should adopt a broad view that encompasses adjacent regulatory regions to understand where vessels may choose to fish when multiple regulatory regions are accessible. In fisheries where isodars describe effort distributions across a regulatory boundary, the relative abundance of the underlying fish population could be better indicated by effort distribution among regulatory regions than by catch rates.

Multimodel approach to a support stock assessment of standardized catch and effort data: A case study of blue shark (Prionace glauca) in the Indian Ocean by the Taiwanese large-scale longline fishery

Multimodel approach to a support stock assessment of standardized catch and effort data: A case study of blue shark (Prionace glauca) in the Indian Ocean by the Taiwanese large-scale longline fishery

Initiation of Red Ginger Callus (Zingiber officinale var. rubrum Rosc.) from Various Explants

The increasing demand for red ginger (Zingiber officinale Roxb. var. rubrum Rosc.) both at the domestic and international levels has led to the need for gingerol production, a main compound of red ginger, which has various pharmacological activities. The urgency of this research is related to gingerol produced in cultivated red ginger, which often shows variability in quantity due to genetic variation and differences in geographical and environmental conditions where it is grown, so it requires gingerol standardization efforts. Through tissue culture techniques, it is possible to propagate plants in a controlled environment, ensuring genetic uniformity and minimizing variations caused by genetic factors. Red ginger raw materials that can be produced consistently, quickly, and land-efficiently with high gingerol content and pesticide-free have become an essential economic necessity. In this joint study with PT. Bintang Toedjoe, researchers intend to utilize root culture bioprocessing technology to increase gingerol production from red ginger. Root cultures have stabile genetics and growth faster; thus, these techniques imply the formation of organs or structures conducive to enhanced gingerol production. Our research has revealed successful protocols for inducing and multiplying suitable callus for organogenesis. Through the application of hormones, the best callus induction is using a combination of 3 ppm 2,4-D and 0.2 ppm BA with a callus production percentage of 67%. On the other hand, a satisfactory callus multiplication rate was used using 1 ppm 2,4-D with the most significant increase in explant area (79 mm2) by ruler alignment. Meanwhile, the rooting response was prominent at 1 ppm 2,4-D + 3 ppm BA.

Potentials of the Metaverse for Robotized Applications in Industry 4.0 and Industry 5.0

As a digital environment of interconnected virtual ecosystems driven by measured and synthesized data, the Metaverse has so far been mostly considered from its gaming perspective that closely aligns with online edutainment. Although it is still in its infancy and more research as well as standardization efforts remain to be done, the Metaverse could provide considerable advantages for smart robotized applications in the industry. Workflow efficiency, collective decision enrichment even for executives, as well as a natural, resilient, and sustainable robotized assistance for the workforce are potential advantages. Hence, the Metaverse could consolidate the connection between Industry 4.0 and Industry 5.0. This paper identifies and puts forward potential advantages of the Metaverse for robotized applications and highlights how these advantages support goals pursued by the Industry 4.0 and Industry 5.0 visions.

Quantum Computing in Cryptographic Systems

Quantum computing represents a transformative advancement in computational power, with profound implications for cryptographic systems. This paper explores the intersection of quantum computing and cryptography, examining the potential for quantum computers to both break traditional cryptographic algorithms and enable new forms of secure communication. Classical cryptographic systems, such as RSA and ECC, rely on the computational difficulty of problems like integer factorization and discrete logarithms. However, quantum algorithms, notably Shor's algorithm, can solve these problems exponentially faster than the best-known classical algorithms, posing a significant threat to the security of current cryptographic practices. This vulnerability necessitates the development and implementation of quantum-resistant algorithms to ensure data security in a post-quantum world. The paper reviews the state-of-the-art in quantum-resistant cryptographic algorithms, including lattice-based, hash-based, code-based, and multivariate polynomial cryptography. These algorithms are analyzed for their security properties, efficiency, and practicality for real-world deployment. Additionally, the paper discusses the ongoing standardization efforts led by organizations such as NIST, which are crucial for establishing widely accepted quantum-safe cryptographic protocols. Beyond the threat posed by quantum computing, this paper also highlights the potential benefits quantum computing can bring to cryptographic systems. Quantum Key Distribution (QKD) is one such advancement, offering theoretically unbreakable encryption by leveraging the principles of quantum mechanics. QKD enables secure communication channels that are immune to any computational advances, including those of quantum computers, by ensuring that any attempt at eavesdropping can be detected. The practical implementation challenges of QKD and other quantum cryptographic protocols are also addressed, including issues related to transmission distance, error rates, and integration with existing communication infrastructures. Experimental results from recent QKD trials are presented, showcasing significant progress in extending the viability of quantum-secure communication over long distances. Furthermore, the paper delves into the hybrid approaches combining classical and quantum cryptographic techniques. These approaches aim to leverage the strengths of both paradigms to enhance security and performance. For instance, hybrid protocols might use classical encryption for bulk data transfer, supplemented by quantum techniques for key exchange, thereby ensuring robust security even against future quantum adversaries. In conclusion, while quantum computing poses substantial risks to existing cryptographic systems, it also offers novel opportunities for creating highly secure communication protocols. The transition to quantum-safe cryptography is imperative to protect sensitive information in the quantum era. This paper underscores the urgency of advancing quantum-resistant cryptographic research, promoting international collaboration for standardization, and exploring innovative applications of quantum technologies in cryptography. Continued research and development in these areas are essential to stay ahead of the evolving threat landscape and harness the full potential of quantum computing for secure communications.