Complete Roadmap Research Articles

Mental illness detection through harvesting social media: a comprehensive literature review.

Mental illness is a common disease that at its extremes leads to personal and societal suffering. A complicated multi-factorial disease, mental illness is influenced by a number of socioeconomic and clinical factors, including individual risk factors. Traditionally, approaches relying on personal interviews and filling out questionnaires have been employed to diagnose mental illness; however, these manual procedures have been found to be frequently prone to errors and unable to reliably identify individuals with mental illness. Fortunately, people with mental illnesses frequently express their ailments on social media, making it possible to more precisely identify mental disease by harvesting their social media posts. This study offers a thorough analysis of how to identify mental illnesses (more specifically, depression) from users' social media data. Along with the explanation of data acquisition, preprocessing, feature extraction, and classification techniques, the most recent published literature is presented to give the readers a thorough understanding of the subject. Since, in the recent past, the majority of the relevant scientific community has focused on using machine learning (ML) and deep learning (DL) models to identify mental illness, so the review also focuses on these techniques and along with their detail, their critical analysis is presented. More than 100 DL, ML, and natural language processing (NLP) based models developed for mental illness in the recent past have been reviewed, and their technical contributions and strengths are discussed. There exist multiple review studies, however, discussing extensive recent literature along with the complete road map on how to design a mental illness detection system using social media data and ML and DL classification methods is limited. The review also includes detail on how a dataset may be acquired from social media platforms, how it is preprocessed, and features are extracted from it to employ for mental illness detection. Hence, we anticipate that this review will help readers learn more and give them a comprehensive road map for identifying mental illnesses using users' social media data.

Inclusive Teaching Competency for Successful Implementation of Inclusive Education

Inclusive education is a transformative approach aimed at providing equitable opportunities for all learners, regardless of their backgrounds, abilities, or differences. Successful implementation of inclusive education necessitates educators to possess a multifaceted set of competencies tailored to address the diverse needs of learners. This paper proposes a holistic framework for cultivating inclusive teaching competency, encompassing five key themes: Knowledge of Diverse Learners, Creating an Inclusive Classroom Climate, Pedagogical Strategies Knowledge, Collaboration & Communication, and Evaluation and Monitoring. Knowledge of Diverse Learners underscores the importance of educators understanding the unique backgrounds, abilities, and learning styles of each student. By recognizing and appreciating diversity, educators can effectively tailor their instruction to meet individual needs. Creating an Inclusive classroom climate involves fostering a welcoming and supportive environment where all students feel valued, respected, and empowered to participate actively in the learning process. Pedagogical Strategies Knowledge involves arming educators with a toolbox of inclusive teaching methods, including tailored instruction, Universal Design for Learning (UDL), and culturally sensitive teaching practices. These tools enable educators to effectively address the varied learning needs of their students, fostering an environment where every individual can engage with and benefit from the educational process. Collaboration & Communication highlight the crucial significance of unified efforts among educators, students, families, and community members in cultivating inclusivity and conquering educational challenges as a cohesive unit. Evaluation and Monitoring are essential for assessing the effectiveness of inclusive practices and making data-informed decisions to enhance student outcomes. By bringing together these five important ideas, this framework gives teachers a complete roadmap to improve how they teach inclusively. It's like a detailed guidebook that helps educators become better at including all students in their classrooms and making sure inclusive education works well for everyone involved.

Producing methane from dry municipal solid wastes: A complete roadmap and the influence of char catalyst

The lack of standardized products is a key hindrance to the widespread commercialization of municipal solid wastes (MSW) pyrolysis technology. In this paper, a cost-effective roadmap employing pyro-gasification and methanation processes is developed, with CH4-rich gas as the target product. In this roadmap, a two-stage catalytic conversion of “MSW → syngas → CH4-rich gas” was realized using MSW char, a by-product of the pyrolysis process as the catalyst/catalyst carrier. The results showed that, in the pyro-gasification stage, a syngas yield of 1.3 L/gMSW could be obtained at 800 °C and a steam-to-MSW mass ratio of 0.4, with a H2 fraction reaching 56.6 vol%. The effective conversion of MSW to syngas was attributed to the superior catalytic activity of the MSW char. By comparing the catalytic activity and structural characteristics of the chars produced from various waste components, it could be determined that the high catalytic activity of the char required both active minerals derived from contaminated plastics and residue, and an appropriate proportion of carbon matrix from the biomass components in MSW. The gasified MSW char (G-MSWC), co-produced with the syngas, served as a carrier for the subsequent methanation catalyst. Due to the activation effect of steam during the syngas production stage, the pore structure of G-MSWC was improved and its defect density also increased. Consequently, G-MSWC demonstrated enhanced Ni–C interaction, facilitating the methanation activity. The final product from the methanation stage achieved a CH4 concentration of 52.9 vol%, and a CH4 yield of 11.25 mol/kgMSW. The above findings demonstrate the feasibility of the complete roadmap from MSW to CH4 and provide valuable guidance for decentralized MSW management based on pyrolysis technology.

Designing Organizational Evolution Model in Hospitals Affiliated with Bushehr University of Medical Sciences

Background: The desire to survive is inherent in any organization; in the private sector, profit, and in the public sector, people's satisfaction is the guarantee of survival. Taking into account the ever-increasing changes and developments, achieving this goal, requires the adoption of a suitable strategy such as the evolution of an organization that, along with patient-centeredness and service quality, encourages government employees to gain the satisfaction of citizens. The main goal of this research is to design organizational evolution in hospitals affiliated with Bushehr University of Medical Sciences.
 Methods:. This research was carried out qualitatively using grounded theory. To collect data, semi-structured interviews were used and data analysis was done using Strauss and Corbin method and the paradigm model. Purposive sampling was carried out based on which14 interviews conducted with professors of the scientific board of universities and experts working in government hospitals.
 Results: The results of the data obtained from the interviews during the process of open, central ,and selective coding led to the creation of grounded theory in the field of organizational evolution in hospitals affiliated with Bushehr University of Medical Sciences. The model designed in this research included 43 sub-categories in the form of 6 main categories of causal, contextual, interventional, central phenomenon, consequences, and strategies.
 Conclusion: This research can be a complete road map for hospital managers to move towards an evolutionary organization by providing causal, contextual, and intervening conditions, strategies, and consequences of the central phenomenon of organizational evolutionism. Furthermore, this research will help to better understand this phenomenon.

Horizontal network collaboration by entrepreneurial ventures: a supply chain finance perspective

PurposeThe present paper aims at understanding how horizontal network collaborations between small and medium enterprises (SMEs) can be designed and implemented to take advantage of a supply chain finance (SCF) perspective.Design/methodology/approachThis study presents an SCF literature background identifying four literature gaps, and in response to them it adopts an action research approach. The empirical analysis is developed on a network-case study: a horizontal collaboration project between small businesses of the Italian wine industry and their supply chains.FindingsSMEs can play an active role in developing – in terms of design and implementation – their collaborative networks by taking advantage of an SCF perspective for themselves, and their customers, based on the reorganization of relationships interface processes. Taking this perspective can be a concrete and crucial way to sustain the development of SMEs and their supply chains in an actual competitive context.Research limitations/implicationsThe paper identifies the theoretical gaps in the literature, suggests new research areas that deserve to be more deeply investigated and connects case-related results to the key concepts. The empirical part presents a real case application that proposes a complete roadmap for managers and practitioners who wish to experience similar projects.Practical implicationsThis network-case study storyline, presenting an overview of ten years of meetings, with related purposes, is suggesting a roadmap for design and implementation of horizontal network as managerial implications. These kinds of active research projects, with a collaborative mixed team of academics and practitioners, and involving a multilayer group of participants, are positive examples for closing the bridge between companies and academia, which enhance this network of small businesses active in trying to improve their competitiveness working together.Originality/valueThe value of the paper is to embrace a supply chain-oriented perspective for an SME, independent of the financial system and based on inventory flow management. Very little literature focuses on inventory-based research within the SCF framework, designed for real implementation in horizontal network collaboration by entrepreneurial ventures.

Graphene nanoparticles as data generating digital materials in industry 4.0

One of the potential applications of 2D materials is to enhance multi-functionality of structures and components used in aerospace, automotive, civil and defense industries. These multi-functional attributes include sensing, energy storage, EMI shielding and property enhancement. In this article, we have explored the potential of using graphene and its variants as data generating sensory elements in Industry 4.0. We have presented a complete roadmap to cover three emerging technologies i.e. advance materials, artificial intelligence and block-chain technology. The utility of 2D materials such as graphene nanoparticles is yet to be explored as an interface for digitalization of a modern smart factory i.e. “factory-of-the-future”. In this article, we have explored how 2D material enhanced composites can act as an interface between physical and cyber spaces. An overview of employing graphene-based smart embedded sensors at various stages of composites manufacturing processes and their application in real-time structural health monitoring is presented. The technical challenges associated with interfacing graphene-based sensing networks with digital space are discussed. Additionally, an overview of the integration of associated tools such as artificial intelligence, machine learning and block-chain technology with graphene-based devices and structures is also presented.

A Complete Roadmap of Analytical Quality by Design in Various Analytical Techniques

Background: For the development of robust analytical methods, Analytical-Qualityby- Design (AQbD)-based testing methods have been found to be more suited than other one factorial approaches. By creating a Method Operable Design Space, this strategy selects the optimal method conditions using the appropriate Design of Experiments. Objective: To impart knowledge to the researchers producing methods using this technique, this review seeks to provide an overview of the Analytical Quality-by-Design technique, experimental designs used, and a survey on methods developed using this technique in various analytical instruments. Method: The following parts must typically be accomplished for the method to be developed utilizing the Analytical Quality by Design technique: analytical target profile, scouting and risk assessment, experimental runs, selection of Method Operable Design Region, robustness testing, and validation. To optimize the risk parameters, suitable designs for the experiment were chosen based on the number of variables that needed to be optimized. Conclusion: By establishing a relationship between the high-risk factors and target profiles utilizing multidimensional design space, robustness and other critical quality attributes in techniques were attained with a minimum of experimental runs, analytical time, and energy. So, it stands to reason that the Analytical Quality by Design technique will soon be widely used and highly advantageous in several industries.

Field experiments in marketing research: a systematic methodological review

PurposeThe purpose of this study is to present a systematic methodological review of the application of field experiments in the domain of marketing research. By performing this study, the authors seek to offer necessary advice and suggestions to marketing scholars interested in the application of field experiments and to promote the adoption of field experiments as a preferred methodological choice among scholars in this domain.Design/methodology/approachA total of 315 field experiments published in the ten leading marketing journals in the past five decades were analyzed in this systematic methodological review. This study examines various aspects of field experiments, including the research profile of existing research, different trends and topics related to field experiments, choice of research questions, methods of observations, unobtrusive data collection, types of interventions and outcome variables.FindingsThis study identified various trends and topics, categories of manipulations, types of limitations and important considerations in designing field experiments and offered necessary advice on the future of field experiments in marketing research.Research limitations/implicationsThis study provides a complete roadmap for future marketing scholars to adopt field studies in their research plans. The systematic summary of limitations and the checklist will be helpful for the researchers to design and execute field studies more effectively and efficiently.Practical implicationsThis review study offers a complete roadmap for marketing scholars who are interested in adopting field experiments in their research projects. The discussion of trends and topics, manipulations, limitations, design considerations and checklist items for field experiments offers relevant insights to marketing scholars and may help them design and execute field experiments more effectively and efficiently.Originality/valueTo the best of the authors’ knowledge, this study is the first of its kind to provide a comprehensive methodological review of field experiments published in leading marketing journals throughout the past five decades. This study makes novel and unique contributions to both theory and literature on field experiments in the marketing discipline.

Recent Advancement on Microbe‐Assisted Biohydrogen Production

The requirement for an ecologically sustainable coverage of energy demand is the need of the present day. The major global concern for clean, green, and sustainable energy with environmental protection is rapidly gaining momentum among researchers around the world that leads to the search for alternative energy sources for the transportation and industrial sectors. Among all energy sources, hydrogen generation and utilization have become a promising option as a transportation fuel. Hydrogen is considered as the potential energy source for the future and is therefore also called the fuel of the future. Hydrogen is not only used as fuel source in automobile engines, but also implemented in fuel cells technology. Compared to other fossil-based fuels, hydrogen has a wide array of advantages with more net calorific value. The production of biohydrogen is a global focus to mitigate the wide use of fossil fuels for sustainability. Sustainable production of hydrogen is demanded worldwide due to a wide range of applications for the provision of energy and fuels in various sectors. The biological method, utilizing microbial communities, is recognized as the most promising option for biohydrogen production, as it is an environment-friendly process utilizing renewable waste biomass under acceptable operating conditions. This special issue features articles about hydrogen production in all aspects including algal cells, thermochemical and biochemical methods. Hydrogen production from food waste by biochemical and thermochemical methods is critically described. A complete road map regarding hydrogen-producing cellular machineries, the mechanism of catalysis, and the role of modern genetic engineering for enhancing hydrogen production are also discussed. The potential of different algal cells and their mechanisms are critically explained in this issue. The role of nanotechnology to enhance the rate of hydrogen production from biomass is presented in this issue. Additionally, metabolic pathways such as biophotolysis, photofermentation, and dark fermentation were discussed for biohydrogen production. Therefore, this special issue focuses on recent advancements and approaches on microbe-assisted biohydrogen production by biotechnological interventions like metabolic engineering of microorganisms towards biohydrogen production, fermentation technologies for hydrogen along with nanotechnology application. Dr. Prakash Kumar Sarangi College of Agriculture, Central Agricultural University, Imphal, India Prakash Kumar Sarangi

Technoeconomic assessment of an FTTH network investment in the Greek telecommunications market

Recent years have seen an increasing need for higher broadband connections, fueled by novel applications including fifth generation wireless networks (5G). The European Commission is working on achieving specific milestones regarding the development of next generation networks. Many EU countries have opted to adopt a gradual migration path towards the Fiber-to-the-Home (FTTH) technology in view of the high costs of implementation. The Fiber-to-the-Cabinet (FTTC) architecture, combined with very-high-bit-rate digital subscriber line 2 (VDSL2) and vectoring noise cancellation techniques may therefore provide a viable short-term basis solution. Techno-economic modeling and assessment is vital at the initial stages of the development of a telecommunication network investment project involving high capital expenditures for the infrastructure. The present work provides a techno-economic model in order to assess the prospects of such a network upgrade project from a financial perspective, following a three-way migration path. The three stages are: the implementation of the FTTC architecture with VDSL2 vectoring technology, the upgrade to FTTC with G.Fast and finally the migration to FTTH. The analysis is implemented over a suburb of the city of Athens, Greece. Different scenarios are evaluated, predicting profits even from the first years following the investment. The analysis includes the estimation of the degree of market penetration, analytical cost calculations for the implementation and operation of the network and the evaluation of crucial financial indicators, regarding the prospects of the investment in vectoring services. The study can serve as a complete road-map and can be applied in similar upgrade scenarios. The most important outcome of the analysis is that the profits resulted from each upgrade will finance the next step.

Vitamin E synthesis and response in plants.

Vitamin E, also known as tocochromanol, is a lipid-soluble antioxidant that can only be produced by photosynthetic organisms in nature. Vitamin E is not only essential in human diets, but also required for plant environment adaptions. To synthesize vitamin E, specific prenyl groups needs to be incorporated with homogentisate as the first step of reaction. After decades of studies, an almost complete roadmap has been revealed for tocochromanol biosynthesis pathway. However, chlorophyll-derived prenyl precursors for synthesizing tocochromanols are still a mystery. In recent years, by employing forward genetic screening and genome-wide-association approaches, significant achievements were acquired in studying vitamin E. In this review, by summarizing the recent progresses in vitamin E, we provide to date the most updated whole view of vitamin E biosynthesis pathway. Also, we discussed about the role of vitamin E in plants stress response and its potential as signaling molecules.

Comprehensive study of the light charged Higgs boson in the type-I two-Higgs-doublet model

In the type-I two-Higgs-doublet model, existing theoretical and experimental constraints still permit the light charged Higgs boson with a mass below the top quark mass. We present a complete roadmap for the light charged Higgs boson at the LHC through the comprehensive phenomenology study, focusing on the normal scenario where the lighter \textit{CP}-even Higgs boson is the observed Higgs boson. In type-I, it is challenging to simultaneously accommodate the light mass of the charged Higgs boson and the constraints from theory, electroweak precision data, Higgs data, $b\to s \gamma$, and direct search bounds. Consequently, the parameter space is extremely curtailed, which predicts somewhat definite phenomenological signatures. We find that the mass of the pseudoscalar Higgs boson, $M_A$, is the most crucial factor in the phenomenology of the charged Higgs boson. If $M_A$ is light, the charged Higgs boson decays mainly into $A W^\pm$. When $M_A$ is above the $A W^\pm$ threshold, the dominant decay mode is into $ \tau^\pm \nu$. Over the whole viable parameter space, we study all the possible production and decay modes of charged Higgs bosons at the LHC, and suggest three efficient channels: (i) $pp \to H^+ H^-\to [\tau \nu] [\tau \nu]$; (ii) $pp \to HA/HH/AA \to H^\pm W^\mp H^\pm W^\mp \to [\tau \nu] [\tau \nu] W W$; (iii) $pp \to H^+ H^-\to [b \bar b W ] [b \bar b W ] $. Based on the sophisticated signal-background analyses including detector simulation, we showed that the significance of the first final state is large, that of the second one is marginal around three, but the third one suffers from huge $t\bar t$ related backgrounds.

A combined hole position error correction method for automated drilling of large-span aerospace assembly structures

PurposeAerospace assembly demands high drilling position accuracy for fastener holes. Hole position error correction is a key issue to meet the required hole position accuracy. This paper aims to propose a combined hole position error correction method to achieve high positioning accuracy.Design/methodology/approachThe bilinear interpolation surface function based on the shape of the aerospace structure is capable of dealing with position error of non-gravity deformation. A gravity deformation model is developed based on mechanics theory to efficiently correct deformation error caused by gravity. Moreover, three solution strategies of the average, least-squares and genetic optimization algorithms are used to solve the coefficients in the gravity deformation model to further improve position accuracy and efficiency.FindingsExperimental validation shows that the combined position error correction method proposed in this paper significantly reduces the position errors of fastener holes from 1.106 to 0.123 mm. The total position error is reduced by 43.49% compared with the traditional mechanics theory method.Research limitations/implicationsThe position error correlation method could reach an accuracy of millimeter or submillimeter scale, which may not satisfy higher precision.Practical implicationsThe proposed position error correction method has been integrated into the automatic drilling machine to ensure the drilling position accuracy.Social implicationsThe proposed position error method could promote the wide application of automatic drilling and riveting machining system in aerospace industry.Originality/valueA combined position error correction method and the complete roadmap for error compensation are proposed. The position accuracy of fastener holes is reduced stably below 0.2 mm, which can fulfill the requirements of aero-structural assembly.

Progressive steps and catalytic cycles in methanol-to-hydrocarbons reaction over acidic zeolites

Understanding the complete reaction network and mechanism of methanol-to-hydrocarbons remains a key challenge in the field of zeolite catalysis and C1 chemistry. Inspired by the identification of the reactive surface methoxy species on solid acids, several direct mechanisms associated with the formation of the first C-C bond in methanol conversion have been recently disclosed. Identifying the stepwise involvement of the initial intermediates containing the first C-C bond in the whole reaction process of methanol-to-hydrocarbons conversion becomes possible and attractive for the further development of this important reaction. Herein, several initial unsaturated aldehydes/ketones containing the C-C bond are identified via complementary spectroscopic techniques. With the combination of kinetic and spectroscopic analyses, a complete roadmap of the zeolite-catalyzed methanol-to-hydrocarbons conversion from the initial C-C bonds to the hydrocarbon pool species via the oxygen-containing unsaturated intermediates is clearly illustrated. With the participation of both Brønsted and Lewis acid sites in H-ZSM-5 zeolite, an initial aldol-cycle is proposed, which can be closely connected to the well-known dual-cycle mechanism in the methanol-to-hydrocarbons conversion.

WITHDRAWN: An extensive survey on signed, unsigned truncated multiplier

Abstract This work confers a widespread survey on the recent developments in Signed, Unsigned Truncated Multiplier, considering various aspects such as modeling, simulation tools and applications especially in signal processing and image processing, highlighting the future directions. Applications such as audio and signal processing, SDR and so on, based on the signal processing and image processing in the recent years of development of technology can function with high efficacy in performance and greatly compactable in terms of area. There could be more signal noises and fluctuations in the digital signal processing applications which use all types of gadgets. Besides, these applications occupy larger areas in VLSI implementation due to the arithmetic operation of Adders and Multiplier design. This survey paper gives a complete roadmap to design an efficient truncated multiplier which can be useful for both signed and unsigned operations. Finally provides a complete roadmap for truncated multiplier for signal processing applications.

Analysis of Energy Retrofit Assessment Methodologies in Buildings by European Research Projects

Abstract Energy retrofit of existing buildings is one of the main keys to achieve European Union’s decarbonising objectives defined in the European Green Deal. In order to proceed into them, European policy has been adapted and several research projects are developed. The aim of this paper is to analyse the assessment methodology of the research projects, setting up the overview of the assessed fields and the criteria followed to perform and evaluate each project. As working methodology, 18 projects have been studied, firstly characterising by the main parameters and afterwards analysing the assessment followed by each one. This analysis is decomposed into five parameters: the assessment scope, reflecting the fields covered by the project’s assessment; data source, the nature of the data; verification, use of data verification strategies; and implementation of life cycle thinking in the assessment methodology. The research shows that although the projects have their bases in the EU energetic targets they also cover a wider scope, assessing many fields and combining many sources of data. However, despite the large knowledge already defined by many projects, there is a lack of global and complete roadmap to be followed.

Thermal management in TSV based 3D IC Integration: A survey

Three Dimensional IC (3D IC) integration is one of the emerging technology which suits CMOS applications by stacking various IC layers vertically. In 3D IC, IC Layers are interconnected electrically using Through Silicon Vias (TSV’s) and mechanically by Cu–Cu bonding. The major drawbacks in 3D IC structures are thermal issues between layers and noise coupling between TSV-to-substrate and TSV-to-TSV which leads significantly on the overall system performance. This paper presents an extensive survey on one of the major issue in 3D based IC integration technique called thermal issues between the layers and how the researchers have tried to overcome the problems by introducing various materials which are suitable for elimination of hotspot, by introducing spreaders among the layers. This extensive survey work shows the complete roadmap for the thermal management in future IC Integration.

Biological pretreatment of biomass to decrease energy consumption in mechanical defiberization process

It is critical to develop sustainable, effective, and innovative technologies for society, particularly for processing of biomass, so that the green/ sustainable advantages can be extended to the final products. This review examined two-step biological-mechanical defiberization of lignocellulosic biomass to produce fibers. Two biological pretreatment methods of fungi and enzymes were mainly introduced, with particular focus on the energy consumption. Potential application methods, advantages, disadvantages, process economics, and future prospects of two biological pretreatment methods were considered to derive a complete road map for the proposed process. With the help of biological pretreatment, the mechanical pulping production could not only improve the paper strength, but also decrease energy consumption at about 40%. This process fits well with the green/sustainable strategy to produce lignocellulosic fibers with reasonable quality while having minimal environmental impact.

An extensive survey on reduction of noise coupling in TSV based 3D IC integration

3D Integration technology is probably the best methodologies among others which suits CMOS applications with in various layers of devices are stacked with high thickness interconnects between the layers. In 3D IC structure electrical and thermal models are introduced for the interface between Through-Silicon-Via’s (TSV’s). TSV’s can be used to enable the 3-D platform; however this TSV’s will represent additional concerns. TSV-to-substrate and TSV-to-TSV noise coupling is assessed inside the 3-D IC’s. A vertical TSV’s design is proposed to reduce the area per TSV, capacitive coupling and effective inductance as compared with the other classical design patterns. TSV’s and substrate noise coupling is one of the major drawbacks in 3D IC. Some of the researchers have tried to overcome the problems in TSV based 3D IC due to noise coupling using different models, materials and different circuit techniques. This paper shows the complete road map for the noise coupling reduction in future IC integration.

Four Decades of Research on the Open-Shop Scheduling Problem to Minimize the Make-span

One of the basic scheduling problems, the open-shop scheduling problem has a broad range of applications across different sectors. The problem concerns scheduling a set of jobs, each of which has a set of operations, on a set of different machines. Each machine can process at most one operation at a time and the job processing order on the machines is immaterial, i.e., it has no implication for the scheduling outcome. The aim is to determine a schedule, i.e., the completion times of the operations processed on the machines, such that a performance criterion is optimized. While research on the problem dates back to the 1970s, there have been reviving interests in the computational complexity of variants of the problem and solution methodologies in the past few years. Aiming to provide a complete road map for future research on the open-shop scheduling problem, we present an up-to-date and comprehensive review of studies on the problem that focuses on minimizing the make-span, and discuss potential research opportunities.