Revolutionary Paradigm Research Articles

Mediating effect of ambiguity tolerance in automated writing evaluation research model

In light of the advancement of generative artificial intelligence (GenAI) technology-empowered automated writing evaluation (AWE) system represents a revolutionary paradigm at the forefront of mobile assisted English learning (MAEL). Numerous empirical studies have been carried out to test the efficacy of automated writing corrective feedback in writing assistance. However, it has seldom been investigated from the cognitive stance of AWE technology enhanced embodied learning. Embodied cognitive linguistics intensifies that learning experience is enhanced in the process of conceptualizing the empirical world. Therefore, the current study explores technology characteristics and individual characteristics incorporating the psychological construct of ambiguity tolerance. Emanating from psychology, ambiguity tolerance describes people’s preponderance to manage uncertainties and unpredictable challenges in the learning process. This study utilized the partial least square structural equation modeling (PLS-SEM) method to analyze 679 valid questionnaire responses via SPSS 29 and SmartPLS 4. The results elucidated that the AWE research model incorporating the technology acceptance model (TAM model), task technology fit model (TTF model), and individual characteristics could predict the user’s adoption of AWE software in the completion of writing tasks. Moreover, ambiguity tolerance functions as an effective mediator in the GenAI technology-empowered automated writing evaluation research model. This study provides technical implications for AWE developers to design AWE software suitable for individual characteristics. Future research could combine qualitative research methods with multivariant statistical approaches to meticulously investigate the interaction of literacy cultivation and emotional intelligence in the utilization of AWE technology for academic purposes in the GenAI era.

Ethics in Crisis? A Paradigm Revolution for Ethical Research in the Social Sciences

Ethics in Crisis? A Paradigm Revolution for Ethical Research in the Social Sciences

Revolutionizing Organizational Communication in Industry 4.0: Unlocking Opportunities and Overcoming Challenges in Bangladesh

This paper examines the impact of Industry 4.0 on organizational communication, exploring the opportunities and challenges presented by this revolutionary paradigm shift. The study employs a qualitative research methodology, drawing on academic literature, case studies, and in-depth interviews with national and international organizations. By evaluating the importance of effective communication in the Internet of Things (IoT) era, the paper assesses the opportunities and identifies the challenges of Industry 4.0 in organizational communication. The study delves into the complex relationship between technology and communication, outlining best practices for implementing communication tools and artificial intelligence (AI) in Industry 4.0. Effective communication is crucial for success in Industry 4.0, as it enables individuals to collaborate effectively and share ideas, leading to improved decision-making and problem-solving. However, information overload, miscommunication, and isolation risks must be mitigated to ensure effective communication. Investing in employee training and development, establishing clear communication protocols, and balancing virtual and face-to-face communication can help organizations manage these risks effectively. Mitigating the risks associated with organizational communication in Industry 4.0 is crucial to ensure that organizations can successfully leverage the opportunities presented by this era of digitalization. Recommendations include adopting cybersecurity measures, streamlining communication processes, protecting personal information, ensuring clarity and transparency, regularly updating data security measures, and promoting inclusive communication to overcome social barriers and ensure sustainable organizational communication.

Revolutions and Law

Two broad thematic perspectives can be distinguished in the literature that broaches the revolutions–law nexus. One considers how actors’ relations to, and usages of, legal statutes and constitutional provisions affect the dynamics of revolutionary conjunctures (law in revolutions). The other examines how the dynamics and modalities of revolutionary processes affect the content of law and the configuration of the legal order (revolutions in law). Subsumed to the law in revolutions perspective are five main topics: the use of constitutional provisions as instruments of revolutionary subversion, legally framed defensive strategies, constitutional devolutions, legitimation problems, and the courts’ stances. The revolutions in law perspective encompasses reflections on the status of law in revolutionary paradigms, the impacts of revolutionary events as acts of foundation, shifting conceptions of constituent power, and the issue of continuities coexisting with ruptures. Cutting across these two perspectives are challenges and pitfalls that studies of revolutions and law can hardly ignore: the reification of analytical and descriptive categories, the confusion of normative and positive standpoints, and the reliance on unconditional claims. Studies overcome these challenges when they document and analyze the processes whereby actors engage law as they make decisions and pursue courses of action.

The Arab Revolutionary Paradigm : An Evaluative-Prospective Reading in Light of Ongoing Political and Socio-Economic Transformations Underway

تناقش هذه الدراسة احتمالية اندلاع موجة ثورية جديدة، ضمن نسق ثوري عربي مؤهل للانفجار تحت وقع عوامل سياسية واقتصادية؛ ترتبط بالإخفاقات التي نجمت عن موجة 2011، سواء من حيث فشلها في التأسيس لمسار حقيقي للإصلاح الحقوقي والديمقراطي والاقتصادي، أو من حيث نجاح النخبة السياسية التي توخت الثورات التخلص منها آنذاك في استعادة هيمنتها على السلطة السياسية قبل متم العقد الأول لهذه الثورات. وكذلك عوامل سوسيو-اقتصادية؛ تتعلق بالفشل المزمن في السياسات الاجتماعية للنظم السلطوية، والتي بقدر ما أنتجت التفاوت والاستبعاد الاجتماعي سابقا، فإن تواصل عجزها في تقويمهما والحد منهما بعد استعادتها للسلطة من جديد، خاصة بعد تفاقمهما تأثرا بتداعيات الأزمات الاقتصادية العالمية الأخيرة، والتي زادت من حدة التدهور في الأوضاع المعيشية للشعوب العربية، نتيجة اندحار فئات عريضة من طبقاتها الوسطى إلى الفقر والهشاشة والبطالة، أو أصبحت على هوامش ذلك. انتهت الدراسة إلى أن الهوة بين النظم السياسية والشعوب العربية سائرة في الاتساع، وأن التردي المسجل في الأوضاع الاجتماعية للشعوب العربية في واقعها السياسي المضطرب من شأنه أن يدفعها للثورة من جديد. وبالتالي، فالحد من الاحتقان الاجتماعي المحفز للفعل الثوري، بات يتطلب من النظم العربية التعجيل إصلاح سياسي واقتصادي وتنموي شامل. الكلمات المفتاحية: النسق الثوري العربي – الأزمات الاقتصادية والاجتماعية – تردي الأوضاع المعيشية – السلطوية – موجة ثورية جديدة.

Quantum Key Distribution In Quantum Communication

Quantum Key Distribution (QKD) stands as a revolutionary paradigm in secure communication, leveraging the principles of quantum mechanics to establish cryptographic keys with unprecedented levels of security. This paper explores the foundational concepts and key protocols of QKD, emphasizing its role in addressing the vulnerabilities associated with classical key exchange methods. The discussion covers quantum entanglement, quantum superposition, and the no-cloning theorem as the cornerstones of QKD. Furthermore, the abstract delves into the practical implementations and challenges, highlighting the potential of QKD to redefine the landscape of secure communication in an increasingly interconnected world. Key words: Quantum Key Distribution, Quantum communication, quantum entanglement, cryptographic security, no-cloning theorem, secure communication, unbreakable security, quantum technology.

Hazard regressive multipoint elitist spiral search optimization for resource efficient task scheduling in cloud computing

Cloud computing, a revolutionary paradigm, connects computing resources and users via the internet, offering services like cloud storage and on-demand computing. In this context, efficient task scheduling is crucial, aiming to minimize costs and makespan. We introduce hazard regressive multipoint elitist spiral search optimization (HRMESSO), a novel technique for efficient task scheduling with reduced time consumption. User tasks are initially received, prioritized, and optimized. Cox proportional hazard regression is applied to establish relationships between task attributes (e.g., priority level, request arrival time, file size) and task prioritization. The great deluge elitist spiral search optimization identifies optimal virtual machines, considering factors like energy, memory, and CPU availability. The spiral search employs logarithmic spirals and Jenson Shannon divergence to find global optimal virtual machines. Finally, the task assigner schedules prioritized tasks onto the identified optimal virtual machines. Experimental evaluation is conducted with different metrics such as task scheduling efficiency, makespan, throughput and energy consumption. The quantitatively compared results exhibit the HRMESSO technique provides better scheduling efficiency, lesser makespan, throughput and energy consumption.

Synergizing Nanomaterials and Artificial Intelligence in Advanced Optical Biosensors for Precision Antimicrobial Resistance Diagnosis.

Antimicrobial resistance (AMR) poses a critical global One Health concern, ensuing from unintentional and continuous exposure to antibiotics, as well as challenges in accurate contagion diagnostics. Addressing AMR requires a strategic approach that emphasizes early stage prevention through screening in clinical, environmental, farming, and livestock settings to identify nonvulnerable antimicrobial agents and the associated genes. Conventional AMR diagnostics, like antibiotic susceptibility testing, possess drawbacks, including high costs, time-consuming processes, and significant manpower requirements, underscoring the need for intelligent, prompt, and on-site diagnostic techniques. Nanoenabled artificial intelligence (AI)-supported smart optical biosensors present a potential solution by facilitating rapid point-of-care AMR detection with real-time, sensitive, and portable capabilities. This Review comprehensively explores various types of optical nanobiosensors, such as surface plasmon resonance sensors, whispering-gallery mode sensors, optical coherence tomography, interference reflection imaging sensors, surface-enhanced Raman spectroscopy, fluorescence spectroscopy, microring resonance sensors, and optical tweezer biosensors, for AMR diagnostics. By harnessing the unique advantages of these nanoenabled smart biosensors, a revolutionary paradigm shift in AMR diagnostics can be achieved, characterized by rapid results, high sensitivity, portability, and integration with Internet-of-Things (IoT) technologies. Moreover, nanoenabled optical biosensors enable personalized monitoring and on-site detection, significantly reducing turnaround time and eliminating the human resources needed for sample preservation and transportation. Their potential for holistic environmental surveillance further enhances monitoring capabilities in diverse settings, leading to improved modern-age healthcare practices and more effective management of antimicrobial treatments. Embracing these advanced diagnostic tools promises to bolster global healthcare capacity to combat AMR and safeguard One Health.

Optimizing Operating System Performance through Advanced Memory Management Techniques: A Comprehensive Study and Implementation

In the ever-evolving landscape of computing, operating system (OS) performance remains a paramount concern. Efficient memory management serves as the cornerstone of OS performance, ensuring seamless resource utilization and delivering a responsive user experience. This comprehensive study delves into the realm of advanced memory management techniques, meticulously exploring their impact on system performance and resource utilization. The study commences with a comprehensive overview of fundamental memory management concepts and techniques, laying the foundation for a deeper understanding of advanced approaches. It meticulously dissects the intricacies of paging, segmentation, and virtual memory, unraveling their underlying principles and implementation mechanisms. Venturing into the realm of advanced memory management techniques, the study delves into the intricacies of memory virtualization, a revolutionary paradigm that transcends the physical limitations of hardware memory. It elucidates the concepts of shadow page tables, copy-on-write (COW) techniques, and memory ballooning, unraveling their role in enhancing system flexibility, scalability, and isolation. To comprehensively assess the impact of advanced memory management techniques, the study employs a rigorous methodology, encompassing extensive experimentation and benchmarking. Through meticulous evaluation under diverse workloads and system configurations, the study unveils the performance gains and resource utilization benefits associated with each technique.

From Deterrence to Strategic Morality: A Proposed Paradigm Revolution Addressing the Reintroduction of Aggressive War into the Strategic Environment

From Deterrence to Strategic Morality: A Proposed Paradigm Revolution Addressing the Reintroduction of Aggressive War into the Strategic Environment

Developing a Manufacturing Industrial Brain in a Smart City: Analysis of fsQCA Based on Yiwu Knitting Industry Platform

Developing a Manufacturing Industrial Brain in a Smart City: Analysis of fsQCA Based on Yiwu Knitting Industry Platform

Abstract PO5-26-11: The Breast Cancer Research Foundation Drug Research Collaborative – A unique and innovative model for industry-funded, academically driven research to advance the field of breast cancer

Abstract The Breast Cancer Research Foundation (BCRF) is committed to preventing and curing breast cancer through groundbreaking research. In pursuit of this mission, the BCRF launched the Drug Research Collaborative (DRC) in 2016—a pioneering program designed to bridge the gap between academic investigators and access to investigational therapies, thereby fostering greater academic-driven research in breast cancer. The DRC's primary objective is to fund independent, innovative, and high-quality investigator-initiated trials (IITs) and pre-clinical/translational research projects. In conventional drug development, industry-sponsored registration trials play a crucial role, leaving limited resources and scope for exploratory and translational IITs that fall outside the industry's drug approval strategy. Additionally, industry-funded IIT research faces challenges such as reputational risks, perceived influence during internal review processes, intellectual property (IP) concerns, and logistics/program management burdens. The BCRF-DRC program addresses these challenges by issuing requests for proposals to generate creative and unbiased ideas, which are then vetted through an academic review process involving leading breast cancer experts. The most promising research projects are selected for further advancement. The BCRF-DRC program is facilitated by the BCRF research staff, providing project management, while the Translational Breast Cancer Research Consortium (TBCRC), founded by the BCRF and also supported by Susan G. Komen, supports the clinical trial aspects of the program. Since its inception, the BCRF-DRC has expanded from one to three industry partners, securing a total funding of $25 million for 15 projects, including seven clinical trials and eight pre-clinical projects. This abstract reports on the ongoing progress and outcomes achieved by these three programs. The BCRF-DRC represents a revolutionary paradigm in research funding and collaboration by harnessing the collective power of industry partners, philanthropic organizations, and academic institutions. Through this collaborative effort, the BCRF-DRC provides a unique platform for researchers to accelerate the translation of scientific discoveries into effective clinical interventions, thus making significant strides in the field of breast cancer in the coming decades. By empowering academic investigators, fostering unbiased research, and addressing the limitations of industry-funded IITs, the BCRF-DRC is revolutionizing breast cancer research and driving the development of novel interventions. This abstract highlights the transformative potential of the BCRF-DRC program and its contribution to advancing breast cancer treatments and ultimately improving patient outcomes. The success of this collaborative model serves as a testament to the power of multi-sector partnerships and the pivotal role they play in shaping the future of breast cancer research. Citation Format: Unnati Jariwala, Dorraya El-Ashry, Judy Garber, Larry Norton. The Breast Cancer Research Foundation Drug Research Collaborative – A unique and innovative model for industry-funded, academically driven research to advance the field of breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-26-11.

Enhancing X-Ray Sensitization with Multifunctional Nanoparticles.

In the progression of X-ray-based radiotherapy for the treatment of cancer, the incorporation of nanoparticles (NPs) has a transformative impact. This study investigates the potential of NPs, particularly those comprised of high atomic number elements, as radiosensitizers. This aims to optimize localized radiation doses within tumors, thereby maximizing therapeutic efficacy while preserving surrounding tissues. The multifaceted applications of NPs in radiotherapy encompass collaborative interactions with chemotherapeutic, immunotherapeutic, and targeted pharmaceuticals, along with contributions to photodynamic/photothermal therapy, imaging enhancement, and the integration of artificial intelligence technology. Despite promising preclinical outcomes, the paper acknowledges challenges in the clinical translation of these findings. The conclusion maintains an optimistic stance, emphasizing ongoing trials and technological advancements that bolster personalized treatment approaches. The paper advocates for continuous research and clinical validation, envisioning the integration of NPs as a revolutionary paradigm in cancer therapy, ultimately enhancing patient outcomes.

Proactive Response Model for App Centric Attack Recognition

Safeguarding strong security while reducing energy usage is still a top priority in the world of smartphone applications. In addition to addressing these important concerns, this work presents a revolutionary paradigm that advances attack modeling and intrusion detection in a proactive manner. Taking advantage of the novel framework of Application-based Behavioral Model Analysis (ABMA), our approach goes beyond traditional security protocols by deeply examining the complex behaviors of mobile applications. Through the smooth integration of advanced intrusion detection systems with ABMA, we present a comprehensive solution that maximizes energy efficiency while strengthening application security. We enable both users and developers to proactively prevent possible threats, including communication-based assaults, by rigorous analysis and modeling. This comprehensive strategy ushers in a new era of mobile security and energy efficiency by protecting sensitive data and user privacy while also ensuring an effective and sustainable ecology for smartphone applications.

Biofloc biosecurity: A revolutionary paradigm in augmenting aquaculture health and resilience against Aeromonashydrophila

This research embarked upon an in-depth exploration of the pioneering concept of biofloc biosecurity, assessing its instrumental role in amplifying fish growth dynamics, hematological indices, biochemical metrics, chemical body composition, and immunological defenses, both pre- and post-infection by Aeromonas hydrophila. By juxtaposing biofloc-reared Oreochromis niloticus against traditionally reared fish, intricate observations of histopathological changes and clinical symptomatology were undertaken. Employing 16S RNA, the bacterial strain Aeromonas hydrophila (ATCC 7966) was precisely identified and banked It into gene bank and given accession number (OR452335). After a preparatory period of ten weeks in the Biofloc system, O. niloticus faced a challenge with Aeromonas hydrophila. Empirical findings revealed that fish from the Biofloc cohort displayed marked advancements across all investigational parameters, before and after infection, as opposed to the control set. In the aftermath of the Aeromonas hydrophila confrontation, biofloc-acclimatized fish manifested an elevated resilience against the bacterial onslaught, displaying superior metrics in growth, hematology, biochemistry, body constitution, and immunological response. Biofloc group showed a strong immune response, particularly in terms of Lysozyme and Total Antioxidant Capacity. Additionally, there was a significant impact on Immunoglobulin and Complement 3 after infection, highlighting the group's increased immune activity. Furthermore, these fish attenuated the pernicious morphological indicators and histopathological anomalies instigated by septicemic bacteria, which otherwise inflict substantial economic detriments upon the aquaculture industry. This research underscores the immense promise biofloc biosecurity holds in bolstering the overall health and performance metrics of cultured O. niloticus.

Implementing an environment for hybrid software evaluation

Quantum computing is a revolutionary paradigm in computer science based on the principles of quantum mechanics. It has the potential to solve problems that are currently unsolvable for classical computing. Applications of quantum computing already span a variety of sectors.Ongoing enhancements to the integrated programming and development environment simplify the creation and optimization of quantum algorithms. Ultimately, the focus on supporting tools represents the starting point towards achieving quantum computing maturity, facilitating its transition from an experimental domain to a practical industry.As quantum software gains ground and relevance in various domains, it is essential to address the evaluation of hybrid systems that combine classical and quantum elements to ensure diverse quality characteristics. However, in the realm of quantum software, models, metrics, and tools are still to be established.The primary contribution of this paper is to present the first technological environment for measuring and evaluating the analyzability of hybrid software.Real-world examples of hybrid software are provided to showcase the functionality of the different tools in the environment, yielding readable and representative results for the evaluator.

Engineered Bio-Based Hydrogels for Cancer Immunotherapy.

Immunotherapy represents a revolutionary paradigm in cancer management, showcasing its potential to impede tumor metastasis and recurrence. Nonetheless, challenges including limited therapeutic efficacy and severe immune-related side effects are frequently encountered, especially in solid tumors. Hydrogels, a class of versatile materials featuring well-hydrated structures widely used in biomedicine, offer a promising platform for encapsulating and releasing small molecule drugs, biomacromolecules, and cells in a controlled manner. Immunomodulatory hydrogels present a unique capability for augmenting immune activation and mitigating systemic toxicity through encapsulation of multiple components and localized administration. Notably, hydrogels based on biopolymers have gained significant interest owing to their biocompatibility, environmental friendliness, and ease of production. This review delves into the recent advances in bio-based hydrogels in cancer immunotherapy and synergistic combinatorial approaches, highlighting their diverse applications. It is anticipated that this review will guide the rational design of hydrogels in the field of cancer immunotherapy, fostering clinical translation and ultimately benefiting patients.

Proteolysis-targeting drug delivery system (ProDDS): integrating targeted protein degradation concepts into formulation design.

Targeted protein degradation (TPD) has emerged as a revolutionary paradigm in drug discovery and development, offering a promising avenue to tackle challenging therapeutic targets. Unlike traditional drug discovery approaches that focus on inhibiting protein function, TPD aims to eliminate proteins of interest (POIs) using modular chimeric structures. This is achieved through the utilization of proteolysis-targeting chimeras (PROTACs), which redirect POIs to E3 ubiquitin ligases, rendering them for degradation by the cellular ubiquitin-proteasome system (UPS). Additionally, other TPD technologies such as lysosome-targeting chimeras (LYTACs) and autophagy-based protein degraders facilitate the transportation of proteins to endo-lysosomal or autophagy-lysosomal pathways for degradation, respectively. Despite significant growth in preclinical TPD research, many chimeras fail to progress beyond this stage in the drug development. Various factors contribute to the limited success of TPD agents, including a significant hurdle of inadequate delivery to the target site. Integrating TPD into delivery platforms could surmount the challenges of in vivo applications of TPD strategies by reshaping their pharmacokinetics and pharmacodynamic profiles. These proteolysis-targeting drug delivery systems (ProDDSs) exhibit superior delivery performance, enhanced targetability, and reduced off-tissue side effects. In this review, we will survey the latest progress in TPD-inspired drug delivery systems, highlight the importance of introducing delivery ideas or technologies to the development of protein degraders, outline design principles of protein degrader-inspired delivery systems, discuss the current challenges, and provide an outlook on future opportunities in this field.

Lightweight Secure Compression Scheme for Green IoT Applications

The Internet of Things (IoT) is a revolutionary paradigm that has gained significant prominence in recent years. It represents the interconnection of everyday objects, devices and machines to the internet, allowing them to collect, exchange and analyze data. As the number of connected objects grows exponentially, energy consumption and data security become essential challenges to ensure a sustainable development of green IoT. Data compression theory can be used as an enticing key to downsize the large amount of circulated information, since wireless communication is the prime energy consuming component in IoT devices. In addition, data encryption algorithms are crucial to protect sensitive information and ensure the integrity and confidentiality of IoT systems. Therefore, combining compression and encryption can lead to improved overall IoT system performance in terms of both power cost and data privacy. In this paper, a lightweight and secure compression approach is introduced to efficiently manage the energy expenditure and provide end-to-end security for energy constrained devices. This proposed algorithm combines the performance of LTC compression and AES encryption to securely encode collected data in IoT devices. The energy model analysis has shown that the suggested method is effective in terms of processing energy, reduces the volume of transmitted data and guarantees end-to-end information privacy.

The Healthcare IoTs as a Paradigm Shift in Healthcare Management, Patient Treatment, and Healthcare Data Processing

When it comes to hospital administration, patient care, and medical data analysis, the Healthcare Internet of Things (HIoT) is nothing short of a paradigm revolution. We dive into this new paradigm to examine its far-reaching effects and revolutionary possibilities in the healthcare system. The context is established by introducing HIoT as a game-changing development in healthcare. Using the IoT to network several devices, this model paves the way for real-time patient monitoring, streamlined inventory management, and integrated telemedicine. The healthcare industry as we know it will be transformed by HIoT as it strives to improve resource allocation, simplify operations, and provide proactive patient care. Our investigation includes a thorough appraisal of how HIoT will affect many facets of medical treatment. We use many research approaches and quality indicators for this evaluation. We may evaluate the viability and scalability of HIoT solutions by testing them in experimental settings that mimic real-world healthcare settings. To provide a precise depiction of the healthcare system, dataset environments use well maintained medical data sources. The performance and efficacy of HIoT technologies may be evaluated using measurable criteria such as sensitivity (0.94), specificity (0.89), F1-Score (0.91), ROC-AUC (0.95), and cost savings ($150,000). To determine the relative importance of each part of the HIoT ecosystem, researchers undertake ablation studies. Our findings provide a clear picture of the disruptive potential of HIoT. Better patient outcomes may be ensured via early interventions thanks to the improved accuracy (0.92), efficiency (9.2), and satisfaction (9.2) provided by the suggested HIoT technique for patient monitoring. When healthcare and telemedicine are combined, the success rate of remote consultations increases to 95%, response times decrease to 15 minutes, and more people have access to medical treatment.