The authors built their analysis on a structured review of 57 peer-reviewed studies, integrating three established theoretical lenses: the Triple Helix Model, which describes the interplay of universities, industry, and government; the National Innovation Systems framework, which treats innovation as the product of interconnected institutions; and Governance Theory, which focuses on how relationships among actors are coordinated and steered. By weaving these perspectives together, the team set out to identify what distinguishes transitional settings from mature innovation systems such as those in Western Europe or North America. Their conclusion is that conventional models of university-industry collaboration, which typically assume well-functioning institutions as a starting condition, simply do not travel well to post-conflict and post-authoritarian environments. In those contexts, the institutions themselves are part of the problem.

The evidence assembled in the review points to a cluster of mutually reinforcing barriers. Weak institutional coordination means that universities, firms, and public agencies often operate in silos, with no effective body aligning their priorities. Fragmented policy frameworks leave research and innovation initiatives scattered across ministries and programs without coherent strategy. Limited mutual trust between academics and business leaders discourages the long-term commitments that joint research and development requires. Insufficient university autonomy and research capacity prevent institutions from acting as reliable partners, while misaligned incentives—where academic careers reward publications rather than applied outcomes, and firms demand short-term returns—undermine the willingness to cooperate on either side. Beneath all of this lie historically embedded institutional legacies that continue to shape behavior long after formal political transitions have occurred.

What makes these findings technically significant is the way the authors reframe the problem. Rather than treating governance as a fixed backdrop, they propose understanding it as a dynamic process: a sequence of institutional coordination, trust-building, policy alignment, and progressive consolidation of relationships among universities, industry, and government. In this view, institutional fragility and historical legacies are not obstacles to be overcome before collaboration can begin, but integral dimensions of the collaboration process itself. This context-sensitive collaborative governance perspective extends the Triple Helix and innovation-system approaches by foregrounding the mechanisms required for university-industry relationships to emerge, stabilize, and generate sustainable research and development outcomes in environments where those relationships have never functioned smoothly.

Kosovo and Albania serve as the study’s illustrative contexts, and their profiles are instructive for a much wider set of countries. Both are economies in transition, shaped by post-conflict or authoritarian legacies, with higher education sectors that have expanded rapidly but often without commensurate investment in research infrastructure or institutional autonomy. Firms in both countries tend to be small and medium-sized enterprises with limited internal research capacity, which means they have much to gain from academic partnerships but few resources to initiate them. Public institutions, meanwhile, frequently lack the coordination capacity to broker and sustain such partnerships. The result is an innovation ecosystem in which every actor has reasons to collaborate but no reliable framework for doing so—a situation the authors argue is characteristic of transitional economies more broadly.

The conceptual contribution of the paper lies in connecting previously fragmented strands of literature. Work on institutional governance, innovation systems, and university-industry relations has largely developed in parallel, with each field addressing a piece of the puzzle. By bringing them together, Nuka and colleagues establish a conceptual foundation for future empirical investigation in Kosovo, Albania, and comparable transition economies. This matters because empirical research in such settings has often imported frameworks designed for mature systems, producing findings that misdiagnose local realities. A framework that explicitly accounts for institutional fragility allows researchers to ask more precise questions: not merely whether collaboration exists, but what governance conditions enable it to emerge and endure.

The practical implications are equally concrete. For policymakers, the study argues for more coherent policies that align research, innovation, and industrial strategies rather than leaving them dispersed across agencies. For universities, it highlights the need for institutional capacity-building and greater autonomy so that academic institutions can act as credible, responsive partners. For industry stakeholders, it points toward trust-based partnerships built on realistic expectations and aligned priorities rather than one-off transactions. The authors emphasize that these interventions are interdependent: policy coherence without trust-building produces paper frameworks, while trust without institutional capacity produces fragile pilot projects that collapse when key individuals move on. Sustainable collaboration, in their account, requires progress on all fronts simultaneously.

The study also situates university-industry collaboration within the broader agenda of sustainable development, positioning well-governed research partnerships as a mechanism for advancing Sustainable Development Goals 4, 8, 9, and 17—covering quality education, decent work and economic growth, industry, innovation and infrastructure, and partnerships for the goals. This framing reflects a growing recognition that innovation-led development in emerging economies cannot be achieved by universities or firms alone. When collaboration functions, it channels academic knowledge into productive capacity, creates demand-driven research agendas, and builds the absorptive capacity that allows economies to adopt and adapt new technologies. When it fails, the result is a persistent gap between what universities produce and what economies need, reinforcing dependence on imported knowledge and limiting local innovation.

For the international research community, the paper offers a caution against one-size-fits-all innovation policy. Donor programs and national strategies alike have often assumed that establishing technology transfer offices, incubators, or matching funds will automatically generate collaboration, mirroring models that succeeded in mature systems. The Kosovo and Albania evidence suggests that such instruments underperform when the underlying governance relationships are absent. The authors’ framework implies that interventions should be sequenced and designed to build coordination capacity, trust, and aligned incentives first, creating the conditions in which conventional collaboration tools can then take root. As transition economies worldwide—from the Western Balkans to Central Asia—seek to convert expanding higher education systems into engines of innovation, this study provides both a diagnostic lens and a roadmap, arguing that the quality of governance relationships, not the mere presence of universities, firms, and public institutions, determines whether research and development collaboration can flourish and endure.

Subject of Research: Governance of university-industry R&D collaboration for innovation in transition economies

Article Title: Governance of university industry research and development collaboration for innovation in transition economies

Article References: Nuka, D., Troshani, I., & Mijo, K. C. (2026). Governance of university industry research and development collaboration for innovation in transition economies. Discover Sustainability. https://doi.org/10.1007/s43621-026-04736-y

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04736-y

Keywords: university-industry collaboration, R&D governance, transition economies, innovation systems, Triple Helix model, Kosovo, Albania, institutional trust, sustainable development goals, research policy, Governance, university

The National Commercialization and Translation Institute, or NCTI, is a two-year pilot program specifically tailored to support late-stage federally funded technology companies. Unlike earlier-stage programs that focus on initial concept validation, NCTI targets firms that have already progressed beyond the initial research and development phases. These companies possess validated technologies but often struggle with the final, critical steps required to achieve commercial success. By focusing on this specific segment of the innovation pipeline, the initiative aims to reduce the attrition rate of deep-tech startups that fail to reach the marketplace despite having robust scientific foundations.

The program is led by Ivan Garibay, a UCF Professor of Industrial Engineering and Management Systems and the principal investigator for NCTI. Garibay brings over two decades of expertise in modeling and simulating complex systems that integrate social, technological, and economic factors. His previous role as the Office of Research’s director of technology and innovation at UCF provided him with unique insights into the mechanics of translating laboratory developments into real-world innovations. Garibay emphasizes that NCTI is designed to complement existing federal programs rather than duplicate them, creating a coordinated continuum of support that manages the handoffs from customer discovery to full commercialization.

Support for the initiative extends well beyond the university walls, drawing from a diverse network of more than 30 organizations across industry, academia, and national laboratories. Major industry leaders such as Samsung, Siemens, Lockheed Martin, and L3Harris have submitted letters of support, signaling a strong private-sector interest in accelerating the commercialization of advanced technologies. Academic and research institutions including UC Berkeley, Oak Ridge National Laboratory, Pacific Northwest National Laboratory, and Sandia National Laboratory are also key partners. This broad coalition reflects the national scope of the project and its potential to influence the broader innovation ecosystem by connecting disparate stakeholders in a unified framework.

Michael Georgiopoulos, dean of UCF’s College of Engineering and Computer Science, serves as a co-principal investigator, bringing expertise in electrical and computer engineering, machine learning, and neural networks. Georgiopoulos has previously led NSF-supported efforts focused on strengthening STEM education and student success, which helps fuel the talent pipeline necessary for future innovation. He views NCTI as a unique opportunity to leverage UCF’s prior experience with Technology, Innovation, and Partnership programs to assemble a national network of entrepreneurs, venture capitalists, and subject matter experts. This collaborative approach is intended to help deep-tech companies with proven technologies achieve the market impact their innovations are destined to deliver.

Thomas O’Neal, a professor of industrial engineering and management systems, has been instrumental in building UCF’s commercialization infrastructure since the 1990s. He founded the UCF Business Incubation Program in 1999, which has recently been ranked as the top traditional business incubator in the country by Time magazine. O’Neal also co-leads UCF’s NSF Innovation-Corps program, which launched in 2014 and provides researchers with a structured customer-discovery process. This process helps scientists and engineers evaluate market demand and make informed go or no-go decisions about pursuing commercialization, ensuring that resources are directed toward technologies with genuine market potential.

The initiative also benefits from the expertise of Ron Piccolo, UCF Galloway Professor of Management and co-principal investigator of NCTI. Piccolo leads the Florida Semiconductor Engine, an NSF-funded initiative focused on translating and commercializing promising technologies in the semiconductor domain. His involvement connects NCTI to a broader network of NSF Engines spanning critical technology areas such as energy, quantum computing, and critical materials. Piccolo notes that identifying why some technologies succeed while others fail is central to the institute’s research, with key factors including sufficient capital investment, clarity on customer need, and the discipline to execute business plans effectively.

NCTI will support a select group of NSF-funded small businesses, specifically those in Phase II and Phase IIB of the Small Business Innovation Research and Small Business Technology Transfer programs. These companies operate in deep technology fields such as artificial intelligence, biotechnology, and quantum computing. The support provided includes funding, mentoring, and curated introductions to customers, investors, and industry partners. Each company receives individualized support that begins with diagnostic triage and culminates in a comprehensive commercialization plan. This tailored approach ensures that each firm receives the specific resources and guidance necessary to navigate the unique challenges of their respective technology sectors.

The research component of NCTI will examine how different combinations of support, including capital investment, mentorship, training, and market validation, most effectively accelerate commercialization. By studying the outcomes of these interventions, the institute aims to generate data-driven insights that can inform future federal policy and commercialization strategies. This empirical approach is crucial for understanding the specific mechanisms that drive successful transitions from laboratory to marketplace. The findings will help identify which interventions have the intended impact, allowing for more efficient allocation of resources in the future.

As the initiative launches, it represents a significant step forward in the national effort to enhance the commercialization ecosystem for deep-tech companies. By leveraging UCF’s proven model and a broad network of partners, NCTI aims to reduce the friction that often prevents promising technologies from reaching their full potential. The program’s focus on late-stage companies addresses a critical gap in the innovation pipeline, ensuring that validated technologies are not left to stall in the final stages of development. This coordinated approach to commercialization has the potential to accelerate the delivery of transformative technologies to the market, benefiting both the economy and society at large.

Subject of Research: National Commercialization and Translation Institute (NCTI) initiative led by UCF

Article Title: University of Central Florida-led $20M NSF initiative scales tech-driven business growth at national level

Article References: University of Central Florida-led $20M NSF initiative scales tech-driven business growth at national level. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: technology commercialization, National Science Foundation, University of Central Florida, deep tech, innovation ecosystem, small business support, research translation, business incubation, federal funding, market validation, University, Central

The methodological approach adopted in the study follows the well-established logic of instrument development in the social sciences. An instrumental design was implemented, moving through phases of item development, scale construction, and final evaluation. What distinguishes a rigorous validation study from a casual questionnaire effort is the sequence of checks applied at each stage. The researchers began with cognitive interviews conducted with a small group of participants, a step that allows item writers to discover how respondents actually interpret the wording of questions. Cognitive interviewing is particularly valuable when measuring experiences that may be shaped by cultural context, because a phrase that seems neutral to a researcher may carry different connotations for a first-generation student navigating unfamiliar institutional norms.

Following the pre-pilot phase, the analytic sample of 502 participants was deliberately split to serve two complementary purposes in psychometric analysis. Exploratory factor analysis, conducted with 200 responses, is used when researchers do not yet know how items will cluster together. It allows the underlying dimensions of the instrument to emerge from patterns of covariation among responses. Confirmatory factor analysis, performed on the remaining 302 responses, then tests whether the structure suggested by the exploratory phase holds in an independent sample. This two-stage separation is considered good practice because validating a scale on the same data used to generate its structure tends to produce overly optimistic estimates of fit. By holding out a separate confirmation sample, the study provides a more honest appraisal of whether the subscales correspond to stable dimensions of first-generation students’ experiences.

The final instrument comprises 25 items organized into theoretically meaningful subfactors. The emphasis on theory in this phrasing matters. A scale whose items group together only by statistical accident offers little guidance to future users, whereas subscales that map onto coherent domains of experience can be interpreted, compared, and tracked over time. The multidimensional framing is itself a contribution, because much of the earlier research on first-generation students examined isolated characteristics rather than the constellation of factors that together influence whether students remain in education. Dimensions such as family support, academic integration, financial strain, and institutional belonging interact with one another, and a scale that captures several of these simultaneously allows researchers to study their relationships rather than treating each in isolation.

Reliability and validity are the twin criteria by which any psychometric instrument is judged, and the study reports adequate performance for several subfactors alongside more limited results for others. This candid reporting is scientifically important. In scale development, it is common for some domains to cohere more readily than others, particularly when the construct being measured is complex or when respondents’ experiences within a domain vary widely. A subscale with weaker reliability may still prove useful as a starting point for refinement, and transparency about which domains performed well allows future researchers to prioritize improvements rather than discovering the weaknesses independently. The reported internal structure within each domain, even where performance was uneven, establishes a foundation on which subsequent versions of the instrument can be built.

The context in which the validation took place deserves attention. Data collection occurred during the first semester of Chile’s 2025 academic year, between March and August, using a cross-sectional design. Cross-sectional studies capture a snapshot of the population at a single point in time, which is well suited to establishing whether an instrument functions coherently but cannot by itself demonstrate how experiences change across a student’s academic trajectory. The transition to university, which the scale is designed to assess, is a period of substantial flux, and longitudinal applications of the instrument in future research could reveal how the measured dimensions evolve as students move through their programs. Such applications would also allow researchers to test whether scores on particular subscales predict outcomes such as persistence, academic performance, or wellbeing.

The rationale for developing a regionally grounded instrument rests on a body of evidence showing that first-generation students in Latin America share some characteristics with peers in the Global North while differing in others. As elsewhere, these students tend to achieve lower grades, face greater risk of dropping out, and encounter more difficulty financing their studies. Their families often have limited familiarity with the ways universities operate, which constrains the guidance they can provide during admission processes and beyond. However, access to higher education in Latin America depends to a greater degree on economic capital than in many Global North countries, where admission to prestigious programs is not as tightly linked to parental professional status. In some Latin American systems, students whose parents are not professionals are less likely to be admitted to selective institutions, making admission procedures themselves a significant source of exclusion. A measurement tool developed in one region cannot simply be transplanted to another without testing whether its assumptions hold.

Within families, the literature points to distinctive dynamics that a contextualized scale can begin to capture. Mothers have been documented as playing a particularly influential role in shaping the educational aspirations of first-generation students, supporting the choice of institution, and accompanying their children through admission. At the same time, the arrival of a first university student in a family can generate internal tensions, particularly when the student must leave the family home or when the demands of academic life conflict with family expectations. These relational dimensions of the first-generation experience are often invisible in administrative data, which capture enrollment and completion but not the social negotiations that surround them. An instrument that includes such domains acknowledges that student experience extends beyond the classroom.

The definition of a first-generation student adopted in the research also carries methodological weight. Students are typically classified as first-generation when their parents or guardians hold non-professional qualifications. Notably, having a sibling who attends or has attended university does not remove a student from this category, because the sibling belongs to the same generation. This clarification prevents a common source of inconsistency across studies, in which definitions vary in ways that make findings difficult to compare. Harmonized definitions are a prerequisite for the comparative research agenda that the authors envision, in which the scale could be used to study first-generation students across different Latin American countries with confidence that the same construct is being measured.

The study acknowledges an important limitation: reliance on purposive, non-probabilistic samples. Such samples are efficient for instrument development because they reach the target population directly, but they limit the generalizability of findings to the broader population of first-generation students. The recommended path forward, implementing stratified sampling, would draw participants in proportion to their representation in defined strata such as institution type, region, or demographic characteristics. Stratified designs strengthen both the representativeness of results and the ability to make comparisons between groups, which is essential if the scale is to inform policy at national or regional levels rather than remaining valid only for the specific populations from which the original samples were drawn.

The timing of this research situates it within a period in which first-generation students have faced compounding pressures. Over the past decade, digital transformation, episodes of social unrest, and the COVID-19 pandemic have reshaped the conditions under which students pursue their degrees. Disruptions to in-person instruction tend to fall hardest on students who lack quiet study spaces, reliable connectivity, or family members who can advise them on navigating institutional systems. Understanding how these pressures distribute across the student population requires measurement tools sensitive to the specific circumstances of first-generation students, and the validated subscales offer one such tool for researchers and practitioners working in the post-pandemic university.

Beyond its immediate findings, the study contributes to a broader conversation about how educational research can support socially responsive institutions. The authors position the scale as a robust starting point for advancing research and practice, with the potential to inform more inclusive policies as further evidence accumulates. This framing reflects a realistic view of instrument development as an iterative enterprise. A first validated version does not settle all questions, but it converts a domain of experience that was previously studied only through qualitative accounts or ad hoc measures into something that can be assessed systematically, compared across contexts, and monitored over time. For universities enrolling large proportions of first-generation students, such measurement capacity is a precondition for evaluating whether support programs achieve their intended effects.

The open-access publication of the work, appearing in the Journal of New Approaches in Educational Research, also facilitates uptake by practitioners and researchers throughout the region who may lack access to subscription-based literature. Widespread availability is particularly consequential for measurement instruments, whose value grows with each additional independent validation. As other research teams apply the subscales in their own contexts, evidence will accumulate about which domains perform consistently and which require adaptation, moving the field closer to the comparative, multidimensional understanding of first-generation students’ experiences that prior scholarship has identified as lacking.

In sum, the development and validation of this scale addresses a documented gap in Latin American educational research, where first-generation students have only recently been studied as a distinct phenomenon. By combining careful item development, cognitive testing, and a split-sample psychometric strategy, the study establishes a foundation for measuring a multidimensional construct within the region. Its limitations, including non-probabilistic sampling and uneven performance across subfactors, are clearly stated and point directly toward the next stages of research. For the students whose experiences the instrument is designed to capture, the ultimate significance lies in whether better measurement translates into better-targeted support, and the study provides the methodological groundwork on which such improvements can be built.

Subject of Research: Development and validation of subscales for assessing first-generation university students’ experiences

Article Title: Development and validation of subscales for assessing first-generation university students’ experiences

Article References: Flanagan-Bórquez, A., Soriano-Soriano, G., Jiménez-Quinteros, P., Carvajal-Araneda, K., & Escalante-Barrios, E. (2026). Development and validation of subscales for assessing first-generation university students’ experiences. Journal of New Approaches in Educational Research, 15(1), Article 23. https://doi.org/10.1007/s44322-026-00070-3

Image Credits: AI Generated

DOI: 10.1007/s44322-026-00070-3

Keywords: Development, validation, subscales, assessing, first-generation, university, students, experiences, scientific research

Mechanical forces operating within and between cells orchestrate a myriad of biological functions and pathologies. Cells constantly generate and experience forces as they adhere, migrate, divide, and remodel their surrounding environment. In cancer, for instance, malignant cells invade neighboring tissues by physically squeezing through the dense cellular matrix. Until now, it has been challenging to directly quantify these pico- to nanonewton-scale forces within live cell environments due to limitations in existing techniques. The implementation of these microlasers offers a new paradigm—using optical signals rather than conventional mechanical or fluorescent markers—to measure forces with high spatial and temporal precision.

The microlasers capitalize on whispering gallery mode phenomena, where light circulates along the inner circumference of a spherical cavity, effectively trapped by continuous total internal reflection. This circulating light amplifies coherently to form a laser when the cavity incorporates a gain medium, in this case, fluorescent dye integrated into a flexible elastomer bead. The key innovation lies in balancing the mechanical softness of the material—allowing deformation under forces exerted by cells—with a sufficiently high refractive index to sustain laser action. Achieving this required identifying a commercially available elastomer optimized for both flexibility and optical performance, a challenge given that materials with high refractive indices tend to be rigid.

When external forces are applied to these microbeads, the shape and internal strain of the bead change, which in turn shifts the spectral properties of the laser emission. By monitoring these shifts, researchers can quantitatively correlate changes in laser wavelength and mode width with precise force magnitudes up to around 50 nanonewtons. Such sensitivity neatly matches the biomechanical range pertinent to intercellular forces, enabling direct biophysical insights without perturbing the natural cellular milieu. Moreover, this laser-based sensing does not require direct imaging, an advantage in dense tissue contexts where optical access is limited or where fluorescence-based probes suffer from photobleaching and background noise.

Unlike prior efforts that relied on liquid droplet lasers, which are often too soft and unstable for biological force measurements, these elastomer-based microlasers exhibit robust mechanical stability with Young’s modulus values comparable to living cells. This mechanical compatibility facilitates cellular internalization—the beads can be readily taken up by cells via endocytosis without disrupting normal physiology. Long-term stability in cell culture conditions was verified, confirming that the microlasers maintain lasing performance over several days, a vital attribute for longitudinal force monitoring in dynamic biological processes.

The research team employed an atomic force microscope as a calibration tool to mechanically manipulate single microbeads and simultaneously record their laser emission spectra. This meticulous calibration enabled them to construct precise force-to-optical signal maps. The microlasers demonstrated multimodal lasing thresholds as low as 2 nanojoules, underscoring their high optical efficiency. Notably, the spectral mode widths broadened proportionally with applied force, providing an additional parameter for refining force quantification.

These versatile microlasers herald a new class of biosensors that can be tailored to varying biomechanical sensitivities by adjusting the elastomer’s stiffness and dye concentration. In future iterations, the team envisions applications beyond cellular biomechanics, including probing contractile forces in muscle and heart tissues. The ability to measure forces deep within tissues, where conventional imaging modalities are impractical, could revolutionize mechanobiology and biomedical diagnostics by delivering spatially resolved force maps in vivo.

Apart from the immediate technological breakthrough, this innovation also underscores the vital synergy between materials science and biophotonics. Designing a soft yet optically capable lasing medium required navigating trade-offs between mechanical deformability and optical confinement, a balance rarely achieved in prior microlaser work. The highly reproducible fabrication process, enhanced by size uniformity and chemical stability, ensures that these microlasers can be mass-produced and tailored for diverse biological investigations.

Looking ahead, ongoing research is focused on enhancing the long-term photostability and reproducibility of the microbeads, crucial for clinical and experimental deployment. By standardizing fabrication parameters and exploring alternative dye chemistries, the researchers aim to mitigate variability and extend the operational lifespan of these biosensors under physiological conditions. Such improvements will empower continuous monitoring of biomechanical fluctuations during complex biological events like tissue regeneration and cancer invasion.

In essence, this pioneering work paves the way for integrating optical microlasers as minimally invasive biomechanical probes within living systems. By transforming mechanical stress into easily measurable optical signals, these whispering gallery mode microbeads could unlock unprecedented understanding of the physical forces that shape life at the microscopic scale. As mechanobiology continues to emerge as a crucial frontier in biomedical science, innovations like these microlasers will be indispensable tools in the quest to decipher the language of cellular forces.

Subject of Research: Biomechanical force sensing in living cells using elastomer-based whispering gallery mode microlasers.

Article Title: Elastomer-based whispering gallery mode microlasers with low Young’s modulus for biosensing applications.

News Publication Date: Information not provided.

Web References: https://doi.org/10.1364/OME.600106

References: M. Bayrak, D. Ripp, J. S. Hill, M. Schubert. “Elastomer-based whispering gallery mode microlasers with low Young’s modulus for biosensing applications,” Optical Materials Express 16, 1440-1453 (2026).

Image Credits: Marcel Schubert, University of Cologne

Keywords: Microlasers, whispering gallery mode, elastomer, biosensing, cellular force measurement, biomechanical sensing, photonics, fluorescent dye, nanonewton forces, cell mechanics, mechanobiology.