Innovative Solutions Research Articles

How marketing and sales use digital tools for innovation ideation

With the widespread practice of using digital tools to work from home (WFH), it is not clear how this impacts innovation. While some scholars argue that digital tools limit the spontaneous conversations that are essential for innovation, others consider them the solution for innovation in a hybrid work environment. We suggest that the current confusion about the impact of digital tools on innovation is due to researchers (a) treating innovation as a homogeneous activity, rather than focusing on specific innovation activities, and (b) ignoring the nature of specific jobs of employees participating in this process. This study explores how marketing and sales professionals use digital tools during innovation ideation. The findings show that various digital tools are used for idea generation, assessment, and development. During each of these stages, marketing and sales personnel use a different mix of digital tools – serving different purposes – and face different challenges. Study findings contribute to our understanding of how digital tools impact innovation and help managers to improve innovation ideation in hybrid work environments.

Enhanced biopolymer composites through micro-integrated lignin and anhydride modified nonwoven bast fiber

The growing need for sustainable materials in various industries has driven research towards eco-friendly biopolymer composites. In this study, lignin microfillers were integrated into PHBV/modified bast fiber matrices, offering a promising solution for sustainable material innovation with improved performance and functionality. Nonwoven bast fiber mats were initially treated with propionic, succinic, and maleic anhydrides, evaluated through weight gain analysis, chemical characterization, thermal stability, and wettability assessments. These modified bast fibers were then reinforced with poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) biopolymer at 30 % loading using specialized molding techniques. The resulting biocomposites were subjected to comprehensive characterization, including moisture related properties, mechanical strength, thermal behavior, and fracturographical properties. In a final stage, lignin microparticles (LMPs) as biofillers were integrated at 1 %, 3 %, 5 %, and 7 % concentrations to enhance biocomposite properties. Experimental findings highlighted succinylated bast fibers as offering the greatest improvements in mechanical strength, thermal stability, and morphological integrity among the modified fibers. At an optimal 5 % lignin microfiller content, the biocomposites exhibited superior wettability and improved stiffness. However, excessive lignin loading led to particle agglomeration, diminishing overall performance. Fracturographical analysis provided insights into the fracture behavior of the biocomposites, highlighting the cohesive and interfacial characteristics of the materials under stress conditions. This research highlights the efficacy of sequential modification strategies in developing high-performance sustainable materials tailored for diverse industrial applications.

Progressing towards personalised medicine: the Genomic Data Infrastructure (GDI) project

Abstract Funded by the European Commission under the Digital Europe Programme and through co-funding from participating Member States, the European Genomic Data Infrastructure (GDI) aims to support the 1+Million Genome initiative for establishing an effective data infrastructure for genomic data. GDI has the potential to fill the gap between genomic research and clinical practice, promoting the implementation of data-driven precision medicine in Europe with the harmonisation of genomic and related phenotypic and clinical data across adhering countries. Launched in November 2022, the GDI project is a collaborative effort involving partners from 20 European countries, divided into 8 Work Packages across three Pillars. GDI is structured with the development of a framework (Pillar I Long-term sustainability) and the necessary tools (Pillar II 1+MG infrastructure deployment), with the implementations of use cases (Pillar III Application and innovation solution) to support research and innovation, integrate findings into the clinic and healthcare, and improve public health measures. In the first 2 years, we completed the starter kit which we are currently testing with real data. Over the subsequent years, the GDI project aims to provide a federated and sustainable infrastructure for facilitating research that use genomic data. Through authorized secure access, clinicians and researchers can leverage genomic insights for faster and more precise clinical decision-making, diagnosis, and treatments. The GDI project represents a significant opportunity to improve healthcare outcomes and public health measures by leveraging the potential of genomics. By providing secure access to extensive genomic datasets combined with phenotyped data, the infrastructure sets the foundation for international partnerships in personalized medicine. Ultimately, this initiative holds the promise of advancing medical understanding, enhancing patient care, and fostering economic growth across Europe. Key messages • GDI drives personalised medicine via international collaboration, building a sustainable infrastructure. Harmonizing data accelerates innovation, improving outcomes and fostering growth in Europe. • GDI aims to revolutionize healthcare by collecting and harmonizing genomic and clinical data in Europe. It facilitates faster and more precise decisions and treatments, improving healthcare outcomes.

Circular Economy Models in Renewable Energy: Technological Innovations and Business Viability

The transitions from fossil-based energy to renewable energy are deeply connected with circular economy solutions for business development and innovation. This paper aims to evaluate to what extent innovation in renewable energy can be used to advance circular economy strategies, with emphasis on the business aspect. Using a combination of qualitative and quantitative analysis, the research analyzes case contributions of a number of RES projects that apply CE principles. It also focuses on the main issues which specialists encounter while implementing these models and considers their economic feasibility. The results show that circular economy principles present renewable energy firms with tremendous potential for enhancing resource use efficiency and financial performance. This research provides practical recommendations aimed at the stakeholders in terms of constructing a more sustainable energy system. In doing so this research adds novelty by identifying the technological factors as advocates for implementing circular economy models to support business outcomes within the renewable energy industry.

Precision Genome Editing Techniques in Gene Therapy: Current State and Future Prospects.

Precision genome editing is a rapidly evolving field in gene therapy, allowing for the precise modification of genetic material. The CRISPR and Cas systems, particularly the CRISPRCas9 system, have revolutionized genetic research and therapeutic development by enabling precise changes like single-nucleotide substitutions, insertions, and deletions. This technology has the potential to correct disease-causing mutations at their source, allowing for the treatment of various genetic diseases. Programmable nucleases like CRISPR-Cas9, transcription activator-like effector nucleases (TALENs), and zinc finger nucleases (ZFNs) can be used to restore normal gene function, paving the way for novel therapeutic interventions. However, challenges, such as off-target effects, unintended modifications, and ethical concerns surrounding germline editing, require careful consideration and mitigation strategies. Researchers are exploring innovative solutions, such as enhanced nucleases, refined delivery methods, and improved bioinformatics tools for predicting and minimizing off-target effects. The prospects of precision genome editing in gene therapy are promising, with continued research and innovation expected to refine existing techniques and uncover new therapeutic applications.

Application of Nanocomposites and Nanoparticles in Treating Neurodegenerative Disorders.

Neurodegenerative diseases represent a formidable global health challenge, affecting millions and imposing substantial burdens on healthcare systems worldwide. Conditions, like Alzheimer's, Parkinson's, and Huntington's diseases, among others, share common characteristics, such as neuronal loss, misfolded protein aggregation, and nervous system dysfunction. One of the major obstacles in treating these diseases is the presence of the blood-brain barrier, limiting the delivery of therapeutic agents to the central nervous system. Nanotechnology offers promising solutions to overcome these challenges. In Alzheimer's disease, NPs loaded with various compounds have shown remarkable promise in preventing amyloid-beta (Aβ) aggregation and reducing neurotoxicity. Parkinson's disease benefits from improved dopamine delivery and neuroprotection. Huntington's disease poses its own set of challenges, but nanotechnology continues to offer innovative solutions. The promising developments in nanoparticle-based interventions for neurodegenerative diseases, like amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS), have offered new avenues for effective treatment. Nanotechnology represents a promising frontier in biomedical research, offering tailored solutions to the complex challenges posed by neurodegenerative diseases. While much progress has been made, ongoing research is essential to optimize nanomaterial designs, improve targeting, and ensure biocompatibility and safety. Nanomaterials possess unique properties that make them excellent candidates for targeted drug delivery and neuroprotection. They can effectively bypass the blood-brain barrier, opening doors to precise drug delivery strategies. This review explores the extensive research on nanoparticles (NPs) and nanocomposites in diagnosing and treating neurodegenerative disorders. These nanomaterials exhibit exceptional abilities to target neurodegenerative processes and halt disease progression.

Innovative technologies of rail transport used by the Armed Forces of the Republic of Poland

Innovation in rail transport has a wide range of applications, which includes customer contact, train moni-toring with modern internet-connected sensors and data analysis, as well as the use of artificial intelli-gence for route optimization, customer service management and vehicle maintenance. The presented is-sues constitute a research niche in the field of the use of innovations in military rail transport, which en-courages research in this area. The article describes innovative technologies of rail transport used by the Armed Forces of the Republic of Poland. The subject of the research included in the article are the latest innovations in the field of rail transport technology and the analysis of their benefits and potential use by the Polish Armed Forces. These include: intelligent control systems, infrastructure maintenance, innova-tive designs of trains and wagons. The aim of the article is to identify the advantages of innovative tech-nologies and their potential application in the Polish Armed Forces. In order to achieve the objectives of the article outlined in this way, it is necessary to answer the following research questions: What innovative technologies of rail transport are used by the Polish Armed Forces? What are the prospects for the devel-opment of innovative rail transport technologies for defence purposes in Poland? What innovative solu-tions concerning the railway infrastructure in Poland could improve the safety of movements of troops by rail? The research hypothesis was adopted in the article: Innovative solutions in rail transport used by the Polish Armed Forces will effectively support the implementation of transports in the movement and transport subsystem (M&T). In order to verify the hypothesis, the following research methods were used: theoretical methods (analysis, synthesis, abstraction, inference, generalization) and the method of expert interview with representatives of the movement and transport subsystem. The presented approach allowed to analyse the problem from different perspectives, which makes it possible to conduct detailed research on this important and current issue.

Current State, Challenges, and Solutions for Innovation and Entrepreneurship among College Students in the Context of the "Double First-rate" Policy

It has been a pattern that understudies pursue innovation development rivalries or begin their own organizations after graduation, since the "Twofold First-rate" strategy, for example developing "twofold first-evaluated" colleges, has been carried out and the government has consistently energized instruction on understudies' development and business venture. A review has been led to explore business as usual of understudies' advancement and business of Tianjin College through different ways, for example, contextual investigation and field work, surveys and meetings, coming to a end that understudies need adequate information towards development and business and that colleges ought to further develop understudies' useful and complete abilities. The paper resolves the issues with the parts of stage development, strategy backing and brand exercises with the examination of explicit cases “Abstract” is a necessary section in a research paper. It may be constructed by gathering main points (summary) from each section of the research paper.

Towards Entrepreneurial Campus Sustainability: Integrating Artificial Intelligence for Resource Allocation in Business Management

This research delves into the utilization of artificial intelligence (AI) within the framework of campus resource allocation, with a primary focus on enhancing business management practices and fostering entrepreneurial sustainability within educational institutions. Through an innovative amalgamation of AI technology and SmartPLS methodology, the study constructs a comprehensive analytical framework aimed at tackling the multifaceted challenges inherent in resource allocation within campus environments. The findings underscore the transformative potential of AI integration in optimizing resource utilization, identifying efficiency gains, and nurturing entrepreneurial endeavors. This paper distinguishes itself from existing studies by presenting a novel approach that emphasizes the unique contributions of AI-driven solutions in both methodological innovation and practical application. By harnessing SmartPLS alongside AI, the research facilitates more accurate resource demand forecasting and enables adaptive decision-making processes, thereby contributing to the Sustainable Development Goals (SDGs), particularly in promoting quality education and sustainable management practices. The study also provides a detailed technical implementation of AI algorithms, offering valuable insights into their development and application within campus settings. The broader implications for the educational sector are explored, considering the scalability and adaptability of the proposed solutions in various educational contexts. Furthermore, the research contributes to theoretical advancements by pioneering the integration of AI and SmartPLS in campus management research, offering a fresh perspective on economic, environmental, and social impact assessments of AI-driven solutions.

Crowdsourcing solutions for innovation: An evolutionary examination of participant behavior strategy

AbstractDespite numerous enterprises embracing crowdsourcing to access several innovative solutions, the prevalence of information asymmetry among different participants has led to an increase in the submission of low‐quality solutions and payment disputes. To improve the efficiency of crowdsourcing solutions for innovation, this study aims to employ an evolutionary game model to capture the dynamic interaction and decision‐making process of the requesters, platforms, and solvers. Initially, we dissect the relevant factors influencing the behavioral decisions of participants to construct a tripartite evolutionary game model. Subsequently, we analyze five potential evolutionarily stable strategies and conditions. Ultimately, we simulate the dynamic evolution of participant decision‐making behavior and the sensitivity of related parameters. The simulation results depict that the initial selection probabilities of populations bear no correlation to the system stability, which only influences the time required to reach equilibrium. The participant's behaviors are affected by price, loss, penalty, compensation, cost, and reputation recognition. Reward and punishment mechanisms help effectively mitigate the emergence of free‐riding and collusion. These findings provide important implications for the sustainable development of crowdsourcing solutions for innovation.

When R&D Becomes a Firm’s Liability: The External Shocks and Adoption of Digital Innovation Solution

When R&D Becomes a Firm’s Liability: The External Shocks and Adoption of Digital Innovation Solution

Degradation-Risk-Inspired Optimization of the Antifungal Oxazolinyl Aniline Lead by a Fusion of Triazole with Nicotinamide.

The discovery of readily available and easily modifiable new models is a crucial and practical solution for agrochemical innovation. Antifungal function-oriented fusion of triazole with the prevalidated lead (R)-LE001 affords a novel framework with a broad and enhanced antifungal spectrum. Characterized by the easy accessibility and adjustability of [1,2,4]triazolo[4,3-a]pyridine, modular fine-tuning provided a set of unprecedented leads (e.g., Z23, Z25, Z26, etc.) with superior antifungal potentials than the positive control boscalid. Candidate Z23 exhibited a more promising antifungal activity against Sclerotinia sclerotiorum, Botrytis cinerea, and Phytophthora capsici with EC50 values of 0.7, 0.6, and 0.5 μM, respectively. This candidate could effectively control boscalid-resistant B. cinerea strains and also exhibit good vivo efficacy in controlling gray mold. Noteworthily, both the SDH-inhibition and the efficiency against Oomycete P. capsici are quite distinct from that of the positive control boscalid. A molecular docking simulation also differentiates Z23 from boscalid. These findings highlight the potential of [1,2,4]triazolo[4,3-a]pyridine amide as a novel antifungal model.

Insights on Quercetin Therapeutic Potential for Neurodegenerative Diseases and its Nano-technological Perspectives.

The neurodegeneration process begins in conjunction with the aging of the neurons. It manifests in different parts of the brain as Aβ plaques, neurofibrillary tangles, Lewy bodies, Pick bodies, and other structures, which leads to progressive loss or death of neurons. Quercetin (QC) is a flavonoid compound found in fruits, tea, and other edible plants have antioxidant effects that have been studied from subcellular compartments to tissue levels in the brain. Also, quercetin has been reported to possess a neuroprotective role by decreasing oxidative stress-induced neuronal cell damage. The use of QC for neurodegenerative therapy, the existence of the blood-brain barrier (BBB) remains a significant barrier to improving the clinical effectiveness of the drug, so finding an innovative solution to develop simultaneous BBB-crossing ability of drugs for treating neurodegenerative disorders and improving neurological outcomes is crucial. The nanoparticle formulation of QC is considered beneficial and useful for its delivery through this route for the treatment of neurodegenerative diseases seems necessary. Increased QC accumulation in the brain tissue and more significant improvements in tissue and cellular levels are among the benefits of QC-involved nanostructures.

From manure to megawatts: Navigating the sustainable innovation solution through biogas production from livestock waste for harnessing green energy for green economy

This article aims to provide a systematic review of the literature on animal biomass and biogas plants through an analysis of externalities and benefits in economic, social, and environmental terms. In recent years, the spread of biogas plants has played an important role, especially in rural areas, generating benefits not only for the individual farm but for entire communities, contributing to the reduction of energy poverty and, at the same time, promoting the production of energy and organic manure. In light of the findings, the study argues that: (a) more public subsidies are needed; (b) the deployment of an appropriate policy mix would encourage the spread of small and medium-sized plants, with a reduction in road transport; and (c) targeted and diversified investments are needed on a geographic-by-geographic basis.

Green Road is open: Economic Pathway with a carbon price escalator

The paper develops the concept of “Economic Pathways” (EPs), which characterizes theory-based scenarios for an economy that strives for decarbonization by the middle of the century. The theoretical framework derives closed-form analytical solutions for consumption, innovation, emissions, and population. The EPs differ in the stringency of assumed policies and associated income and emission development. Unlike the well-known “Shared Socioeconomic Pathways”, they allow the inclusion of important causalities between the economy and the environment and thereby considerably narrow down the scope of likely future developments. The quantitative part serves to illustrate the long-term consequences of climate policy. I show that deep decarbonization only moderately delays economic development, but requires increasing escalation of the carbon price. The paper argues that the adoption of more stringent climate policies becomes more likely as the phase-out of fossil fuels increases. The “Green Road” is not only feasible but also attractive and realistic.

Cyber-physical recreation of six DOF industrial robot arm

AbstractThe Cyber-Physical and Vehicle Manufacturing Laboratory, a model Industry 4.0 laboratory, is applying new innovative solutions to improve the quality of education. As part of this, a digital twin of the lab was designed and built, where users can practice. In the virtual space, it is possible to apply the known robot motion types, and the tool centre and wrist speed have been measured virtually. Robot control tasks can be performed “offline” using parameters. This information can then be transferred to the actual physical robot unit. The stable diffusion 1.5 deep learning model generates 2D geometric shapes for trajectory, allowing users to perform unique tasks during education. The Google Colab cloud-based service was used to teach our rendered-type dataset. For the 3D simulation frame, we used V-REP, which was developed on a desktop PC equipped with an Intel Core i5 7600K processor, Nvidia GTX1070 VGA with 8 GB of DDR5 VRAM, and 64 GB of DDR4 memory modules. The following material describes an existing industrial six-axis robot arm and its implementation, which can be controlled and programmed while performing virtual measurements after integrating into a Cyber-Physical system and using deep learning techniques.

Development of Wi-Fi based Moving Target Tracking System for Precise Shooting

In modern times where analysis of foot traffic is essential for effective resources management and security, moving target systems that use Wi-Fi-based movement counter offers an innovation solution. This paper summarizes the fundamental idea, the methodology as well as the potential uses of the system. The proposed system makes use of the widespread characteristic of Wi-Fi networks to detect and track the movement of moving targets within a given area. With a thorough analysis of Wi-Fi signals generated by tablets, smartphones or any other wireless-enabled device carried by people, the proposed system is capable of accurately counting and recording the movements of individuals in real-time. The system operates passively by eliminating the requirement for sensors or manually counting. Furthermore, it captures live data, which allows rapid making of decisions regarding security, crowd management and resource allocation. Potential possibilities for applications of the wireless moving target counter are diverse. For retail environments they can help enhance the store's layout and personnel according to peak times for traffic as well as popular pathways. Moving target counters that use Wi-Fi provides a high-end yet easy option for precise and instant pedestrian analysis. The potential for it to transform the management of crowds and improve security across a variety of settings is a powerful device for today's environments.

Exploring Design Principles for STEAM Learning Activities Development by Science and Technology Teachers

This study explored the design principles of science, technology, engineering, arts, and mathematics (STEAM) learning activities developed by science and technology teachers for classroom practice. Through a qualitative approach, interpretive paradigm, and design-based research, 12 Bachelor of Education honours degree students were conveniently sampled. Data were collected by means of reflections and development of learning materials through the analysis, design, development, implementation, and evaluation (ADDIE) model. The study followed the design-based research stages of needs analysis, development, testing, and reflection to produce design principles, and it was underpinned by the learning theory of constructionism. The findings showcase the design principles to include design thinking, finding solutions for learning problems, creativity, and innovation applied to instructional design. The study recommends the use of design thinking pedagogies in developing teacher knowledge on STEAM classroom practice.

Winning with mētis: embodied virtues in sport practice, from Odysseus to Maradona

ABSTRACT The Greek word mētis (μῆτις) traditionally refers to a particular form of wily intelligence associated with the arts of deception (dolos) and the knowledge of tricks (kerdē), subterfuges, and traps. Mētis evokes innovative and ground-breaking solutions, based on the capability to understand, anticipate, and possibly violate the others’ expectations. Most importantly, mētis presupposes practical wisdom, or prudence (phrόnesis), a dispositional quality that underpins all the virtues that deserve to be cultivated by sportspersons and that is pivotal to perfect sportspersons’ moral character. Not only is prudence required to apply mētis profitably for winning a game, but it is also indispensable to perform consistently with the game’s norms—cognizant of sport values. This analysis of mētis is key to illuminate the embodied dimension of tactical and moral reasoning in contemporary sport practice. In this paper, we first argue that the strategic effectiveness of mētis proves that not only sensorimotor control but also higher forms of intelligence, like strategic reasoning, are embodied and inform skilful performance; second, we argue that relying on mētis is necessary not only to interpret the rules of the game in one’s own favor but also to respect the shared values that these rules uphold in the sport practice.

Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges.

The Radiological Society of North America (RSNA) has held artificial intelligence competitions to tackle real-world medical imaging problems at least annually since 2017. This article examines the challenges and processes involved in organizing these competitions, with a specific emphasis on the creation and curation of high-quality datasets. The collection of diverse and representative medical imaging data involves dealing with issues of patient privacy and data security. Furthermore, ensuring quality and consistency in data, which includes expert labeling and accounting for various patient and imaging characteristics, necessitates substantial planning and resources. Overcoming these obstacles requires meticulous project management and adherence to strict timelines. The article also highlights the potential of crowdsourced annotation to progress medical imaging research. Through the RSNA competitions, an effective global engagement has been realized, resulting in innovative solutions to complex medical imaging problems, thus potentially transforming health care by enhancing diagnostic accuracy and patient outcomes. Keywords: Use of AI in Education, Artificial Intelligence © RSNA, 2024.