Engineering Methodology Research Articles

Latin America: A hub for agrobiotechnological innovations.

Modern biotechnology is one of the last century's major advances in human science. Particularly in the agronomical field, the landscape of crop improvement technologies has witnessed a great expansion, driven by the integration of molecular and genetic engineering methodologies into the breeding toolbox. Latin America (LATAM) serves as a pioneering region in incorporating such techniques with several countries swiftly embracing these technologies. This review aims to give a comprehensive overview of the elements that influenced agrobiotech acceptance in LATAM countries and how such cases could provide support for upcoming technologies to be considered worldwide. Nearly 50 years of biotech breakthroughs have provided humankind with an impressive portfolio of tools already integrated into several life-sciences areas. The agronomical field has greatly progressed thanks to technologies derived from Genetically Modified Organisms (GMOs) and high promises are being made to also incorporate genome -editing products. LATAM's case is a prime example of how early introduction of novelties in the crop production chain can result in improved yields, paving the way for future developments to be easily integrated into the technological ecosystem of a region. The example set by LATAM can also be useful for the present gene-editing regulatory scenario. With several countries presently on the path to approving these methods in their current crop systems, basing their next steps on the southern continent's example, could represent a safe and practical pathway towards a new agronomical revolution.

The machine system as a factor of scientific and technological progress in agro-industrial complex

The article proposes a principle for forming a machine system using the object-process approach to modeling technical systems as a methodology of systems engineering. It has been shown that the central concept of a machine system is scientific and technological progress (STP): a machine system should simultaneously promote progress in the agro-industrial complex (AIC) and reflect it. The article presents a definition of a machine system, its functions, main goal, architecture, stakeholders, and external environment. A machine system is positioned as a mixed system that combines conceptual, substantive, and physical components. The conceptual part is an information product – the machine system itself, presented in the form of a computer program, website, standards, databases, on paper, etc. The physical component is a group of experts in developing a machine system. It has been shown that in a market economy, a machine system should be built not on the basis of specific brands and models of technical means, but on the basis of their types. A definition of the type was proposed based on the division of technical means characteristics into functional and non-functional. To substantiate the machine types, an approximate list of types of non-functional characteristics of agricultural machinery was formed. Diagrams of the architecture of the machine system and the development of types of agricultural machines were constructed. The architecture of the machine system is a combination of the structure of the machine system and the activities of experts in the development of the machine system, which ensures the performance of the machine system of its functions, the main ones being the systematization of agricultural machines and technologies and the formation of ideas among interested parties about the state and directions of scientific and technological progress in the agro-industrial complex.

Accelerating Evidence Synthesis in Observational Studies: Development of a Living Natural Language Processing-Assisted Intelligent Systematic Literature Review System.

Systematic literature review (SLR), a robust method to identify and summarize evidence from published sources, is considered to be a complex, time-consuming, labor-intensive, and expensive task. This study aimed to present a solution based on natural language processing (NLP) that accelerates and streamlines the SLR process for observational studies using real-world data. We followed an agile software development and iterative software engineering methodology to build a customized intelligent end-to-end living NLP-assisted solution for observational SLR tasks. Multiple machine learning-based NLP algorithms were adopted to automate article screening and data element extraction processes. The NLP prediction results can be further reviewed and verified by domain experts, following the human-in-the-loop design. The system integrates explainable articificial intelligence to provide evidence for NLP algorithms and add transparency to extracted literature data elements. The system was developed based on 3 existing SLR projects of observational studies, including the epidemiology studies of human papillomavirus-associated diseases, the disease burden of pneumococcal diseases, and cost-effectiveness studies on pneumococcal vaccines. Our Intelligent SLR Platform covers major SLR steps, including study protocol setting, literature retrieval, abstract screening, full-text screening, data element extraction from full-text articles, results summary, and data visualization. The NLP algorithms achieved accuracy scores of 0.86-0.90 on article screening tasks (framed as text classification tasks) and macroaverage F1 scores of 0.57-0.89 on data element extraction tasks (framed as named entity recognition tasks). Cutting-edge NLP algorithms expedite SLR for observational studies, thus allowing scientists to have more time to focus on the quality of data and the synthesis of evidence in observational studies. Aligning the living SLR concept, the system has the potential to update literature data and enable scientists to easily stay current with the literature related to observational studies prospectively and continuously.

Low Thermal Resistance of Diamond‐AlGaN Interfaces Achieved Using Carbide Interlayers

AbstractThis study investigates thermal transport across nanocrystalline diamond/AlGaN (aluminum gallium nitride) interfaces, crucial for enhancing thermal management in AlGaN‐based electronic devices. Chemical vapor deposition growth of diamond directly on AlGaN resulted in a disordered interface with a high thermal boundary resistance (TBR) of 20.6 m2‐KGW−1. Sputtered carbide interlayers of boron carbide (B4C), silicon carbide (SiC), and a mixture of boron carbide and silicon carbide (B4C/SiC) are employed to reduce thermal boundary resistance in diamond/AlGaN interfaces. The carbide interlayers resulted in record‐low thermal boundary resistance values of 3.4 and 3.7 m2‐KGW−1 for Al0.65Ga0.35N samples with B4C and SiC interlayers, respectively. STEM imaging of the interface reveals interlayer thicknesses between 1.7 and 2.5 nm, with an amorphous structure. Additionally, Fast‐Fourier Transform (FFT) characterization of sections of the STEM images displayed sharp crystalline fringes in the AlGaN layer, confirming it is properly protected from damage from hydrogen plasma during the diamond growth. In order to accurately measure the thermal boundary resistance we develop a hybrid technique, combining time‐domain thermoreflectance and steady‐state thermoreflectance fitting, offering superior sensitivity to buried thermal resistances. The findings underscore the efficacy of interlayer engineering in enhancing thermal transport and demonstrate the importance of innovative measurement techniques in accurately characterizing complex thermal interfaces. This study provides a foundation for future research in improving thermal properties of semiconductor devices through interface engineering and advanced measurement methodologies.

Assessment of Thermoelectric Properties of Bi2Se3: Insights from Hybrid Functional Studies, Strain Engineering, and Machine Learning Methodology

AbstractThermoelectric properties in topological insulator Bi2Se3 are explored with multifaceted strategies, i.e., hybrid functional with strain and artificial intelligence methodology. The assessment with the experimental band gap values recognizes the limitations of conventional functional and the effectiveness of screened hybrid functionals. A thorough investigation into the impact of biaxial and uniaxial strain on thermoelectric parameters uncovers distinctive behaviors in n‐type and p‐type Bi2Se3, providing insights into optimal strain conditions for improved performance. Furthermore, the studies on the role of topologically non‐trivial surface states (TNSS) in thermoelectric properties reveal that TNSS significantly dominate electronic transport. Dual scattering time approximation elucidates the segregation of thermoelectric transport contributions from bulk and surface states, highlighting the importance of controlling the relaxation time ratio for enhanced thermoelectric performance. Additionally, the prediction of thermoelectric properties using Random Forest and Neural Networks models showcase impressive agreement with density functional theory predictions across varying temperatures, offering a powerful tool for understanding complex temperature‐dependent trends in thermoelectric properties. In summary, this interdisciplinary study presents a unique approach to advancing the understanding and optimization of thermoelectric properties in Bi2Se3. It provides a comprehensive framework for tailoring material behavior for diverse thermoelectric applications.

Cyber Resilience Limitations in Space Systems Design Process: Insights from Space Designers

Space technology is integral to modern critical systems, including navigation, communication, weather, financial services, and defence. Despite its significance, space infrastructure faces unique cyber resilience challenges exacerbated by the size, isolation, cost, persistence of legacy systems, and lack of comprehensive cyber resilience engineering standards. This paper examines the engineering challenges associated with incorporating cyber resilience into space design, drawing on insights and experiences from industry experts. Through qualitative interviews with engineers, cybersecurity specialists, project managers, and testers, we identified key themes in engineering methodologies, cybersecurity awareness, and the challenges of integrating cyber resilience into space projects. Participants emphasised the importance of incorporating cybersecurity considerations from the earliest stages of design, advocating for principles such as zero-trust architecture and security by design. Our findings reveal that experts favour Model-Based Systems Engineering (MBSE) and Agile methodologies, highlighting their synergy in developing flexible and resilient systems. The study also underscores the tension between principles-based standards, which offer flexibility but can lead to inconsistent implementation, and compliance-based approaches, which provide clear measures but may struggle to adapt to evolving threats. Additionally, the research recognises significant barriers to achieving cyber resilience, including insider threats, the complexity of testing and validation, and budget constraints. Effective stakeholder engagement and innovative funding models are crucial for fostering a culture of cybersecurity awareness and investment in necessary technologies. This study highlights the need for a comprehensive cyber resilience framework that integrates diverse engineering methodologies and proactive security measures, ensuring the resilience of space infrastructure against emerging cyber threats.

Reverse engineering in medical application: literature review, proof of concept and future perspectives

Reverse engineering, a process of extracting information or knowledge from existing objects or systems, has gained significant attention in various fields, including medicine. This article presents a comprehensive literature review and a proof of concept on the application of reverse engineering in the medical field. The review particularly focuses on the reverse engineering process, available technologies, and their specific relevance to the medical domain. Various imaging techniques, such as computed tomography and magnetic resonance imaging, are discussed in respect of their integration with reverse engineering methodologies. Furthermore, the article explores the wide range of medical applications facilitated by reverse engineering, including prosthetics, implants, tissue engineering, and surgical planning. The potential of reverse engineering to enhance personalized medicine and patient-specific treatments is highlighted. A detailed proof of concept focusing on femur reconstruction is a significant component of the article. The proof of concept showcases the practical implementation of reverse engineering techniques to assist in designing and manufacturing precise custom-made implants and bone reconstruction. It emphasizes the integration of patient-specific anatomical data obtained through imaging technologies and the subsequent utilization of reverse engineering processes for anatomical reconstruction (solid modeling). Overall, this article provides an extensive overview of reverse engineering in medical applications, incorporating a literature review and a case study. The findings highlight reverse engineering’s potential to advance medical practices, improve patient outcomes, and foster personalized treatments. The review emphasizes the reverse engineering process, available technologies, and their specific relevance to the medical field, as well as their potential and effectiveness in advancing medical practices.

DevOps Adoption Guidelines, Challenges and Benefits: A Systematic Literature Review

The DevOps methodology in software engineering is currently trending and many software development organisations are adopting it to stay competitive. However, these organisations face difficulties in adopting DevOps due to a lack of common standard guidelines and methodology. We argued that guidelines across multiple platforms are needed to succeed in DevOps implementation. This paper aims to identify the benefits, challenges, and guidelines associated with DevOps adoption using a systematic literature review. The search spanned over ten digital libraries such as ACM Digital Library, ScienceDirect, EBSCOhost, SAGE Journals, Wiley Online Library, and so on. The review also included keyword searches in relevant studies i.e DevOps guidelines, DevOps and guidelines, DevOps benefits, DevOps and benefits, DevOps challenges, DevOps and challenges. Papers written in English and published from 2011 through July 2020 were considered. 33 studies passed the two-step quality assessment. Finally, the data were extracted and analysed based on the themes and research questions, revealing the benefits and challenges of DevOps adoption guidelines. The findings show that improved software delivery speed increases code quality and application quality with frequent releases. It also shows that there was no transparent scientific approach to determining the DevOps capabilities regarding the process, practice, tools, and implementations, cost implications, and insufficient knowledge of the automation process. Finally, the reviewed studies indicated that software quality increases whenever DevOps best practices are adopted. DevOps is about continuous software delivery. Previous studies have not considered the guidelines for scientifically adopting DevOps for organisations that want to migrate. The present review identified the DevOps adoption guideline model represented in a cyclic format that indicates an infinite process representing continuous integration, continuous delivery, and continuous deployment, with an understanding of benefits and challenges.

Graphene Oxide Nano-Sheets: A Novel Eco-Friendly Approach for Tissue Engineering and Antibacterial Applications in Bone Disease

Obtaining novel scaffolds on bone disease-affected cells with osteoconductivity has recently been the focus of tissue engineering methodologies. Chemical treatment and microwave radiation form a novel strategy to create graphene oxide nanosheets (Gns) that decorate carbon crystal structures. This approach is proven to be eco-friendly. Gns was characterized using "X-ray diffraction, ultraviolet, and Fourier transform infrared spectrophotometers". The XRD spectra confirmed the crystalline structure of Gns. The Gns product was analyzed using "Raman spectroscopy. Transmission electron microscopy and field-emission scanning electron microscopy" exposed few layered surfaces of Gns. The TEM images showed Gns specifically decorated with carbon nanoparticles. The evidence demonstrated the novelty of Gns as a very effective bactericidal agent, suggesting its potential as a future antibacterial agent. Different concentrations of Gns and its derivatives showed different cell viabilities toward various cell lines, demonstrating the dependency of a biocompatible environment for good attachment on MG63 cells.

Computer-aided engineering: Quantification of the heating non-uniformity and distribution of the thermal load occurring during continuous ohmic and conventional thermal food sterilization

The characterization of continuous thermal processing (CTP) is a crucial aspect in the design and selection of technologies for the production of safe products with optimal quality retention after the thermal stress. Conventional methods for CTP characterization are constrained in their capacity to comprehensively capture the complex dynamics of fluid flow through pipelines and the different heating principles that contribute to local temperature variations. These methods rely on isolated local temperature measurements, which fail to account for the intricate interactions between temperature, heat transfer phenomena and fluid dynamics. In view of the aforementioned limitations, this study presents the implementation of a computational fluid dynamic digital model as a toolbox for the characterization and comparison of a conventional heating (CH) ultra-high temperature (UHT) sterilization process and ohmic heating (OH) UHT sterilization. This serves as a tool for an extensive and accurate comparison of the two processes. The model enabled the estimation of each technology's thermal load through the F0 value, thereby providing a more comprehensive assessment than local temperature measurements alone. Furthermore, this approach accounted for the flow behavior throughout the sterilization process. This strategy demonstrated that 2.5 % of the food product is exposed to an up to 75.4 times the average thermal load, whereas for OH treatments only 0.4 % of the product was exposed up to 5.1 times the average thermal load. This is due to the volumetric heating feature of OH, which leads to a 54.7 % reduction in the cooking grade of the product. Furthermore, the computer-aided comparison revealed no statistically significant difference (p-value of 0.6) between the two technologies in their capacity to inactivate Geobacillus stearothermophilus spores in terms of thermal load. This study highlights the importance of computer-aided engineering methodologies for the technological assessment of food sterilization processes prior to industrial transfer.

Human-powered vehicles as a way to abate transport-related greenhouse gas emissions: Part 2 - A virtual prototype for emissions and performance analyses

Velomobiles, despite their potential for efficient transportation, remain relatively unknown compared to electric cars, receiving limited attention in academic research and public awareness. This paper highlights their untapped potential and underlines public interest in their adoption, provided a velomobile meeting customer requirements is available. Leveraging the Model Based System Engineering (MBSE) methodology, this work presents a structured approach to design, focusing on customer needs translation and digital prototype validation. This iterative process ensures velomobiles meet performance criteria while minimizing environmental impact. The lack of standardized testing for the energy consumption of Human-Powered Vehicles (HPVs) is addressed by proposing an analysis of consumption under diverse operating conditions, giving information on the environmental assessments. This study underscores velomobiles’ potential as a sustainable transportation solution and provides a framework for their design, validation, and optimization.

Preliminary Design of Satellite Systems through the Integration of Model-Based System Engineering and Agile Methodologies: Application to the 3ColStar Mission

This paper presents a case study on integrating Agile Systems Engineering methodologies in the preliminary design phase of satellite systems, focusing on the 3ColStar satellite mission. Through Model-Based Systems Engineering (MBSE), technical consistency was rigorously managed across various architectural documents, ensuring coherency and minimizing errors. Furthermore, the preliminary design was developed, with the implementation of the Arcadia Method, supported by the Capella modeling tool. This allowed the digitalization of the system, which was represented by models that contain requirements, architecture, and interfaces between the different parts of the system. At the same time, the preliminary design process was streamlined and completed within an accelerated time frame of 4 months, with weekly sprints driving progress based on the scrum methodology. This case study highlights the effectiveness of Agile Systems Engineering principles to improve the team communication accuracy, communication, and efficiency of satellite systems preliminary design, providing valuable insights for future missions.

Assessing the Impact of Transport Phenomena on Modeling and Optimization of Solid-State Fermentation for the Revalorization of Agro-Industrial Residues in a Wall‐Cooled Packed‐Bed Bioreactor

This work assesses the influence of transport phenomena on the growth of Yarrowia lipolytica 2.2ab (Yl2.2ab) and protease production during Solid-State Fermentation (SSF) in a bench-scale wall-cooled tubular bioreactor packed with substrate-based pellets derived from agro-industrial residues. Our engineering methodology, in a novel manner, includes: (i) developing a new pseudo-heterogeneous model, (ii) identifying and quantifying the impact of all transport phenomena on microbial kinetics, (iii) elucidating how fluid dynamics enhances heat and mass transfer processes, and hence microbial kinetics, and (iv) determining the operational and geometric parameters for optimal bioreactor performance. As main results: (i) all transport phenomena occurring within the bench-scale bioreactor are fundamental for its reliable simulation and will be essential for its scale-up, and (ii) the maximum production of proteases, 420 U kgDS‐1−1, is achieved under the following operational conditions: a tube to particle diameter ratio of 5.6, a bath temperature of 45°C, an inlet airflow rate of 1 L min−1, and inlet fluid temperature of 43 °C. Finally, the pseudo-heterogeneous model is assessed by describing SSF-based observations from the literature, appropriately predicting the performance of Yl2.2ab in a bench-scale bioreactor. These results pave the way for future exploration of Yl2.2ab in SSF within larger-scale packed-bed bioreactors.

Robust genome and cell engineering via in vitro and in situ circularized RNAs.

Circularization can improve RNA persistence, yet simple and scalable approaches to achieve this are lacking. Here we report two methods that facilitate the pursuit of circular RNAs (cRNAs): cRNAs developed via in vitro circularization using group II introns, and cRNAs developed via in-cell circularization by the ubiquitously expressed RtcB protein. We also report simple purification protocols that enable high cRNA yields (40-75%) while maintaining low immune responses. These methods and protocols facilitate a broad range of applications in stem cell engineering as well as robust genome and epigenome targeting via zinc finger proteins and CRISPR-Cas9. Notably, cRNAs bearing the encephalomyocarditis internal ribosome entry enabled robust expression and persistence compared with linear capped RNAs in cardiomyocytes and neurons, which highlights the utility of cRNAs in these non-dividing cells. We also describe genome targeting via deimmunized Cas9 delivered as cRNA and a long-range multiplexed protein engineering methodology for the combinatorial screening of deimmunized protein variants that enables compatibility between persistence of expression and immunogenicity in cRNA-delivered proteins. The cRNA toolset will aid research and the development of therapeutics.

Auto-WoodSDA: A scalable end-to-end automation framework to perform probabilistic seismic risk and recovery assessment of new residential woodframe buildings

The seismic performance of residential woodframe buildings has a widespread and lasting impact on the socioeconomic vitality of a community. To enable efficient seismic risk and resilience assessment, a comprehensive framework that is rooted in performance-based earthquake engineering (PBEE) methodology is proposed. The framework is formulated as a computational workflow which is operationalized as an automation program dubbed “Auto-WoodSDA”. The end-to-end platform is developed to perform four major tasks: (1) generate code-compliant seismic design, (2) create numerical models, (3) perform nonlinear analyses, and (4) assess earthquake-induced financial losses and functional recovery time. Given the user inputs, Auto-WoodSDA sequentially executes the four tasks without intermediate human intervention to produce seismic performance metrics such as the expected annual loss. It is presented as a ready-to-implement platform that is computationally efficient and scalable in performing large-scale seismic risk and resilience assessment. An example building from the existing literature is used to demonstrate the key features of the automation framework and verify the results. The results underscore the ability of the AutoWoodSDA computational workflow to automate the generation of reliable new code-compliant woodframe building designs, perform nonlinear analysis, and assess the earthquake-induced impacts using PBEE principles.

Semantic-based systems engineering for digitalization of space mission design

The engineering of space systems is a collaborative, iterative process that integrates various domain-specific viewpoints to represent the final system. To ensure consistency across these viewpoints, the European Space Agency (ESA) employs Model-Based System Engineering (MBSE) and Semantic-Based System Engineering (SBSE) methodologies together to improve digital continuity and interoperability across collaborative space system developments. One significant application of semantic engineering in SE is the ESA MBSE Methodology. The ESA MBSE Methodology provides a standardized approach aligned with the European Cooperation for Space Standardization (ECSS), promotes interoperability across MBSE methodologies and tools, and overcomes integration challenges. ESA MBSE Methodology is the input for the Overall Semantic Modeling for Space System Engineering (OSMoSE) which leverages interoperability in the space community. Case studies, such as the EagleEye Earth Observation mission, demonstrate practical applications, highlighting how semantic models enhance efficiency in complex space systems. This paper discusses the importance of semantics and data management in SE and presents a practical solution derived from the ESA MBSE Methodology.

Software Engineering in Health Care

Software engineering has emerged as a cornerstone in the evolution of healthcare delivery, serving as a key player in improving patient care and maximizing systemic efficiency. This paper delves into the integration of software engineering principles, methodologies, and technologies within the healthcare sector, highlighting key applications such as Electronic Health Records (EHR), telemedicine platforms, clinical decision support systems, and medical imaging software. Through an exploration of challenges, opportunities, future trends, and case studies illustrating successful implementations, this study underscores the critical importance of software engineering in shaping the future of providing healthcare and enhancing patient results. By tackling current issues, seizing opportunities, and embracing future trends, Software engineering's revolutionary potential can be used by the healthcare industry to improve patient care and operational efficiency.

(Invited) Material Engineering for the GAA and Post-GAA Transistors and Interconnects

Feature scaling in advanced CMOS technology has been slowing down starting at 10 nm node and is expected to stop completely in the next few years. Nevertheless, transistor density scaling is continuing at a Moore’s law pace, driven by DTCO and 3D IC.Transistor dimensions and minimum metal pitch are expected to be massaged down only by 10% to 20% during the next decade. However, both the transistor and the interconnect will continue to evolve and improve both in performance and in variability.Currently, the industry is transitioning from FinFET technology to GAA (Gate All-Around) technology. The next transition, from GAA to the NMOS and PMOS GAA transistors stacked on top of each other (often referred to as CFET (Complementary Field Effect Transistor)) is expected in 8 to 10 years from now.The main methodology for GAA and CFET transistor engineering comes down to bandstructure engineering, where material composition, shape and thickness of different layers, and mechanical stress are engineered to tailor a bandstructure of the channel that maximizes on-state driving strength and minimizes off-state leakage and variability. The key methodology for bandstructure engineering is ab-initio analysis of transistor components and then transfer of the obtained bandstructure to transistor scale analysis to characterize its behavior.For the interconnect engineering, the tight metal pitches and increasingly tall and narrow vias dictate transition from copper to alternative metals, with a preference for the metals that can be etched and selectively grown. The key methodology for interconnect engineering is ab-initio analysis of electron scattering at the interfaces and grain boundaries. The scattering is then converted into interconnect resistance that defines speed and power consumption of the advanced CMOS circuits.This work introduces the concepts of transistor band structure engineering and interconnect scattering engineering and provides illustrations of these methodologies applied to GAA and post-GAA technologies.

Correlation between tooth decay and insulin resistance in normal weight males prompts a role for myo-inositol as a regenerative factor in dentistry and oral surgery: a feasibility study.

In an era of precision and stratified medicine, homogeneity in population-based cohorts, stringent causative entry, and pattern analysis of datasets are key elements to investigate medical treatments. Adhering to these principles, we collected in vivo and in vitro data pointing to an insulin-sensitizing/insulin-mimetic effect of myo-inositol (MYO) relevant to cell regeneration in dentistry and oral surgery. Confirmation of this possibility was obtained by in silico analysis of the relation between in vivo and in vitro results (the so-called bed-to-benchside reverse translational approach). Fourteen subjects over the 266 screened were young adult, normal weight, euglycemic, sedentary males having normal appetite, free diet, with a regular three-times-a-day eating schedule, standard dental hygiene, and negligible malocclusion/enamel defects. Occlusal caries were detected by fluorescence videoscanning, whereas body composition and energy balance were estimated with plicometry, predictive equations, and handgrip. Statistically significant correlations (Pearson r coefficient) were found between the number of occlusal caries and anthropometric indexes predicting insulin resistance (IR) in relation to the abdominal/visceral fat mass, fat-free mass, muscular strength, and energy expenditure adjusted to the fat and muscle stores. This indicated a role for IR in affecting dentin reparative processes. Consistently, in vitro administration of MYO to HUVEC and Swiss NIH3T3 cells in concentrations corresponding to those administered in vivo to reduce IR resulted in statistically significant cell replication (ANOVA/Turkey tests), suggesting that MYO has the potential to counteract inhibitory effects of IR on dental vascular and stromal cells turnover. Finally, in in silico experiments, quantitative evaluation (WOE and information value) of a bioinformatic Clinical Outcome Pathway confirmed that in vitro trophic effects of MYO could be transferred in vivo with high predictability, providing robust credence of its efficacy for oral health. Our reverse bed-to-benchside data indicate that MYO might antagonize the detrimental effects of IR on tooth decay. This provides feasibility for clinical studies on MYO as a regenerative factor in dentistry and oral surgery, including dysmetabolic/aging conditions, bone reconstruction in oral destructive/necrotic disorders, dental implants, and for empowering the efficacy of a number of tissue engineering methodologies in dentistry and oral surgery.

Demonstration of quality evaluation for MDA-based web engineering methodologies using quality evaluation framework – WSDMDA case study

Demonstration of quality evaluation for MDA-based web engineering methodologies using quality evaluation framework – WSDMDA case study