Perspectives For Applications Research Articles

Fuzzy Hybrid Meta-optimized Learning-based Medical Image Segmentation System for Enhanced Diagnosis

This medical image segmentation plays a fundamental role in the diagnosis of diseases related to the correct identification of internal structures and pathological regions in different imaging modalities. The conventional fuzzy-based segmentation approaches, though quite useful, still have some drawbacks regarding handling uncertainty, parameter optimization, and high accuracy of segmentation with diverse datasets. Because of these facts, it generally leads to poor segmentations, which can give less reliability to the clinical decisions. In addition, the paper is going to propose a model, FTra-UNet, with advanced segmentation of medical images by incorporating fuzzy logic and transformer-based deep learning. The model would take complete leverage of the strengths of FIS concerning the handling of uncertainties in segmentation. Besides, it integrates SSHOp optimization technique to fine-tune the weights learned by the model to ensure improvement in adaptability and precision. These integrated techniques ensure faster convergence rates and higher accuracy of segmentation compared to state-of-the-art traditional methods. The proposed FTra-UNet is tested on BRATS, CT lung, and dermoscopy image datasets and ensures exceptional results in segmentation accuracy, precision, and robustness. Experimental results confirm that FTra-UNet yields consistent, reliable segmentation outcomes from a practical clinical application perspective. The architecture and implementation of the model, with the uncertainty handled by FIS and the learning parameters optimization handled by the SSHOp method, increase the power of this model in segmenting medical images.

Bottom-Up Metasurfaces for Biotechnological Applications.

Metasurfaces are the 2D counterparts of metamaterials, and their development is accelerating rapidly in the past years. This progress enables the creation of devices capable of uniquely manipulating light, with applications ranging from optical communications to remote biosensing. Metasurfaces are engineered by rational assembly of subwavelength elements, defined as meta-atoms, giving rise to unique physical properties arising from the collective behavior of meta-atoms. These meta-atoms are typically organized using effective, reproducible, and precise nanofabrication methods that require a lot of effort to achieve scalable and cost-effective metasurfaces. In contrast, bottom-up methods based on colloidal nanoparticles (NPs) have developed in the last decade as a fascinating alternative for accelerating the technological spread of metasurfaces. The present review takes stock of recent advances in the fabrication and applications of hybrid metasurfaces prepared by bottom-up methods, resulting in disordered metasurfaces. In particular, metasurfaces prepared with plasmonic NPs are emphasized for their multifold applications, which are discussed from a biotechnology perspective. However, some examples of organized metasurfaces prepared by merging bottom-up and top-down approaches are also described. Finally, leveraging the historical disordered metasurface evolution, the review draws new perspectives for random metasurface design and applications.

Artificial Intelligence in Natural Product Drug Discovery: Current Applications and Future Perspectives.

Drug discovery, a multifaceted process from compound identification to regulatory approval, historically plagued by inefficiencies and time lags due to limited data utilization, now faces urgent demands for accelerated lead compound identification. Innovations in biological data and computational chemistry have spurred a shift from trial-and-error methods to holistic approaches to medicinal chemistry. Computational techniques, particularly artificial intelligence (AI), notably machine learning (ML) and deep learning (DL), have revolutionized drug development, enhancing data analysis and predictive modeling. Natural products (NPs) have long served as rich sources of biologically active compounds, with many successful drugs originating from them. Advances in information science expanded NP-related databases, enabling deeper exploration with AI. Integrating AI into NP drug discovery promises accelerated discoveries, leveraging AI's analytical prowess, including generative AI for data synthesis. This perspective illuminates AI's current landscape in NP drug discovery, addressing strengths, limitations, and future trajectories to advance this vital research domain.

The Orthopaedic Trauma Fellowship Application Process: An Analysis of the Applicant Experience

Background: Several studies have analyzed the fellowship application process from the perspective of the program director and few have analyzed the application process from the perspective of the applicant. There is no study that analyzes orthopaedic trauma fellowship applicant perspectives on the application process to fellowship. Methods: An anonymous electronic survey was distributed via the Orthopaedic Trauma Association directory to all current orthopaedic trauma surgery fellows and attending physicians one year post-fellowship in the United States who completed fellowship in 2021-2022 and 2022-2023. The survey contained a total of 24 questions: 10 questions regarding demographics and accomplishments, 13 questions regarding interview statistics, preferences and expenses, and a set of questions concerning how applicants formed impressions of programs. Results: 47/180 surgeons (26.11%) completed the survey. 37 (78.7%) were male. There was no associations between sex, USMLE Step 1, Step 2, or AOA status and number of interviews (R<0.20). There was a moderate correlation between the number of applications and number of interviews (R=0.68). Respondents valued faculty interaction (average scoring of 3.91 out of 4) and case volume/complexity (3.83 out of 4) the most. Research was the least valued program factor (2.19 out of 4). The average cost of applying to fellowship was $3331.84. Conclusions: Orthopaedic trauma fellowship applicants value case volume/complexity and faculty interaction the most and least value research. The financial burden of applying to fellowship is significant with most applicants spending over $3000. This study provides insight into factors that applicants value; which may lead to improved applicant satisfaction and reduced financial burden.

Trends in Urology Residency Applications: Results from The American Urological Association Medical Student Survey from 2022 to 2024.

To provide a comprehensive overview of the American Urological Association (AUA) Medical Student Surveys and includes data 2022, 2023 and 2024. Data collected through surveys distributed prior to match day and were distributed to all medical students who submitted a rank list for urology residency. Questions consisted of various topics including applicant demographics, application metrics, and experiences with preference signals and virtual interviews. 440 (79%), 428 (84%), and 387 (77%) applicants participated in surveys for the years 2022, 2023, and 2024, respectively. Applicants continue to participate in research at a high level. Additionally, USMLE Step 2 Clinical Knowledge scores gained prominence following the transition of USMLE Step 1 to pass/fail. Preference signals were well-received, and large volume signaling may have prompted applicants to apply to fewer programs. Virtual interviews were favored for cost-effectiveness and perceived equity benefits, however, applicants expressed a preference for in-person interactions. There have been dynamic shifts in urology residency applications from the applicant perspective from 2022 to 2024. This may be influenced by changing evaluation metrics as well as the adoption of preference signals and virtual interviews. The findings highlight the need for ongoing feedback and transparency to ensure equitable practices for both applicants and residency programs during this evolution.

Exploring the therapeutic potential of lupeol: A review of its mechanisms, clinical applications, and advances in bioavailability enhancement.

Lupeol, a naturally occurring triterpenoid, has garnered significant attention for its diverse range of biological activities and potential therapeutic applications. This comprehensive review delves into the various aspects of lupeol, including its sources, extraction methods, chemical characteristics, pharmacokinetics, safety evaluation, mechanisms of action, and applications in disease treatment. We highlight the compound's unique carbon skeleton and its role in inflammation regulation, antioxidant activity, and broad-spectrum antimicrobial effects. The review also underscores lupeol's potential in cancer therapy, cardiovascular protection, metabolic disease management, and wound healing. Furthermore, we discuss the challenges and future perspectives of lupeol's clinical application, emphasizing the need for further research to improve its bioavailability and explore its full therapeutic potential. The review concludes by recognizing the significance of lupeol in drug development and healthcare, with expectations for future breakthroughs in medical applications.

Valorization of waste biomass towards biochar production – Characterization and perspectives for sustainable applications in Serbia

Valorization of waste biomass towards biochar production – Characterization and perspectives for sustainable applications in Serbia

An overview of advancements in biomass pyrolysis modeling: Applications, challenges, and future perspectives in rotary reactors

An overview of advancements in biomass pyrolysis modeling: Applications, challenges, and future perspectives in rotary reactors

Enhancing spectral imaging with multi-condition image fusion

Spectral Imaging techniques such as Laser-induced Breakdown Spectroscopy (LIBS) and Raman Spectroscopy (RS) enable the localized acquisition of spectral data, providing insights into the presence, quantity, and spatial distribution of chemical elements or molecules within a sample. This significantly expands the accessible information compared to conventional imaging approaches such as machine vision. However, despite its potential, spectral imaging also faces specific challenges depending on the limitations of the spectroscopy technique used, such as signal saturation, matrix interferences, fluorescence, or background emission. To address these challenges, this work explores the potential of using techniques from conventional RGB imaging to enhance the dynamic range of spectral imaging. Drawing inspiration from multi-exposure fusion techniques, we propose an algorithm that calculates a global weight map using exposure and contrast metrics. This map is then used to merge datasets acquired with the same technique under distinct acquisition conditions. With case studies focused on LIBS and Raman Imaging, we demonstrate the potential of our approach to enhance the quality of spectral data, mitigating the impact of the aforementioned limitations. Results show a consistent improvement in overall contrast and peak signal-to-noise ratios of the merged images compared to single-condition images. Additionally, from the application perspective, we also discuss the impact of our approach on sample classification problems. The results indicate that LIBS-based classification of Li-bearing minerals (with Raman serving as the ground truth), is significantly improved when using merged images, reinforcing the advantages of the proposed solution for practical applications.

Deciphering the Origin of Higher Shell Coordination on Single Iron Catalysts for Resilient Modulating Persulfate Oxidation Into Singlet Oxygen Pathway

AbstractPrecise manipulation of coordination structure of single‐atom sites and establishment of schematic microenvironment‐oxidation pathway relations remain significant challenges in Fenton‐like chemistry. Herein, incorporating sulfur heteroatoms into the higher coordination shell of FeN4 structure (Fe‐NSC) exhibited a volcano trend of p‐hydroxybenzoic acid oxidation, aligning with the number and positions of sulfur dopant. Specifically, higher shell S coordination with moderate electronegativity and larger atomic radii triggers long‐range electronic interactions, which provoke Fe 3d orbital splitting and spin electron rearrangement, resulting in a spin crossover with orbital states dxy2 dyz1 dxz2 dz21. As a result, the partial filling of eg and t2 g orbitals and moderate σ/π antibonding states between 3d and 2p atomic states optimized the adsorption–desorption behaviors of the key oxygenated intermediates from peroxymonosulfate activation. Thus, the optimal binding configuration weakens the Fe─O bonding and accelerates PMS dissociation to yield C‐S‐N4Fe‐O*, which subsequently couples to form 1O2 with nearly 100% selectivity. The Fe‐NSC‐functionalized membrane exhibited outstanding long‐term reusability in a continuous flow reactor which further validated practical application perspective. This study provides insight at both atomic and electronic levels for rational design of spin‐polarized catalysts and its functions in fine‐tuning oxidation pathways in environmental catalysis.

Coronary CT Angiography in the Emergency Department: State of the Art and Future Perspectives

About 5% of annual access to emergency departments (EDs) and up to 25–30% of hospital admissions involve patients with symptoms suggestive of acute coronary syndrome (ACS). The process of evaluating and treating these patients is highly challenging for clinicians because failing to correctly identify an ACS can result in fatal or life-threatening consequences. However, about 50–60% of these patients who are admitted to the hospital because of chest pain are found to have no ACS. Coronary computed tomographic angiography (CCTA) has emerged as a proposed new frontline test for managing acute chest pain in the ED, particularly for patients with low-to-intermediate risk. This narrative review explores the potential of adopting an early CCTA-based approach in the ED, its significance in the era of high-sensitivity troponins, its application to high-risk patients and its prognostic value concerning atherosclerotic burden and high-risk plaque features. Additionally, we address clinical and technical issues related to CCTA use for triaging acute chest pain in the ED, as well as the role of functional testing. Finally, we aim to provide insight into future perspectives for the clinical application of CCTA in the ED.

Silver Nanoparticles as Antimicrobial Agents in Veterinary Medicine: Current Applications and Future Perspectives

Silver nanoparticles (AgNPs) have gained significant attention in veterinary medicine due to their antimicrobial properties and potential therapeutic applications. Silver has long been recognized for its ability to combat a wide range of pathogens, and when engineered at the nanoscale, silver’s surface area and reactivity are greatly enhanced, making it highly effective against bacteria, viruses, and fungi. This narrative review aimed to summarize the evidence on the antimicrobial properties of AgNPs and their current and potential clinical applications in veterinary medicine. The antimicrobial action of AgNPs involves several mechanisms, including, among others, the release of silver ions, disruption of cell membranes and envelopes, induction of oxidative stress, inhibition of pathogens’ replication, and DNA damage. Their size, shape, surface charge, and concentration influence their efficacy against bacteria, viruses, and fungi. As a result, the use of AgNPs has been explored in animals for infection prevention and treatment in some areas, such as wound care, coating of surgical implants, animal reproduction, and airway infections. They have also shown promise in preventing biofilm formation, a major challenge in treating chronic bacterial infections. Additionally, AgNPs have been studied for their potential use in animal feed as a supplement to enhance animal health and growth. Research suggested that AgNPs could stimulate immune responses and improve the gut microbiota of livestock, potentially reducing the need for antibiotics in animal husbandry. Despite their promising applications, further research is necessary to fully understand the safety, efficacy, and long-term effects of AgNPs on animals, humans, and the environment.

Toward the Construction of Affective Brain-Computer Interface: A Systematic Review

Electroencephalogram(EEG)-based affective computing aims to recognize the emotional state, which is the core technology of affective brain-computer interface(aBCI). This concept encompasses aspects of physiological computing, human-computer interaction(HCI), mental health care, and brain-computer interfaces(BCI), presenting significant theoretical and practical value. However, the field reached a bottleneck stage due to EEG individual difference issues, causing various challenges to achieve a fundamental aBCI. In this review, we collected some representative works from 2019 to 2023. Combining the historical exploration process and research approaches of EEG-based emotion recognition, a comprehensive understand of current research status was conducted. Furthermore, we analyzed the main obstacles for emotion recognition modeling. To construct a reasonable aBCI, we envisioned the working scenarios, developmental stages, and key impact factors based on the existing EEG physiology knowledge. From the practical application perspective, we evaluated the theoretical significance, implementation difficulty, and real-world limitations of different approaches. By synthesizing the merits and drawbacks of various techniques, we proposed a theoretically feasible aBCI framework under the restrictions of real-world application scenarios. Finally, we suggested several research topics that have not been thoroughly investigated to broaden the research scope and accelerate the development of aBCIs.

Advances in Programmable Control of Ostwald Ripening for Tailoring Material Properties: Challenges, Applications, and Future Perspectives.

During the past decade, enlightened by the better understanding of the mechanism of Ostwald ripening (OR), programmable control of OR process have gained popularity in the fields from nanocrystals to bulk materials in virtue of its important on regulating the structural and chem-physical properties. In this perspective, we systematically summarize the up-to date advanced applications of OR process involved in nanomaterials and bulk material properties. The potential challenges and perspectives for further research are highlighted. We envision that such research directions will be a base for future work and have a bright future especially for material science.

Alloreactive-free CAR-VST therapy: a step forward in long-term tumor control in viral context.

CAR-T cell therapy has revolutionized immunotherapy but its allogeneic application, using various strategies, faces significant challenges including graft-versus-host disease and graft rejection. Recent advances using Virus Specific T cells to generate CAR-VST have demonstrated potential for enhanced persistence and antitumor efficacy, positioning CAR-VSTs as a promising alternative to conventional CAR-T cells in an allogeneic setting. This review provides a comprehensive overview of CAR-VST development, emphasizing strategies to mitigate immunogenicity, such as using a specialized TCR, and approaches to improve therapeutic persistence against host immune responses. In this review, we discuss the production methods of CAR-VSTs and explore optimization strategies to enhance their functionality, activation profiles, memory persistence, and exhaustion resistance. Emphasis is placed on their unique dual specificity for both antitumor and antiviral responses, along with an in-depth examination of preclinical and clinical outcomes. We highlight how these advances contribute to the efficacy and durability of CAR-VSTs in therapeutic settings, offering new perspectives for broad clinical applications. By focusing on the key mechanisms that enable CAR-VSTs to address autologous CAR-T cell challenges, this review highlights their potential as a promising strategy for developing effective allogeneic CAR-T therapies.

Perspective on Flexible Organic Solar Cells for Self-Powered Wearable Applications.

The growing advancement of wearable technologies and sophisticated sensors has driven the need for environmentally friendly and reliable energy sources with robust mechanical stability. Flexible organic solar cells (OSCs) have become promising substitutes for traditional energy solutions thanks to their remarkable mechanical flexibility and high power conversion efficiency (PCE). These unique properties allow flexible OSCs to seamlessly integrate with diverse devices and substrates, making them an excellent choice for powering various electronic devices by efficiently harvesting solar energy. This review summarizes recent achievements in flexible OSCs from the perspective of self-powered wearable applications. It discusses advancements in materials, including substrates and transparent electrodes, evaluates performance criteria, and compares the PCEs of flexible OSCs to their rigid counterparts. Subsequently, novel applications of flexible OSCs in self-powered wearable applications are explored. Finally, a summary and perspectives on the current challenges and obstacles facing flexible OSCs and their applications in self-powered wearables are provided, aiming to inspire further research toward practical implementations.

THE ROLE OF RELATIONSHIP MARKETING IN CONSUMER PURCHASE DECISION: AN EXPLORATORY STUDY

Objective: This study seeks to investigate the function of relationship marketing in consumer purchasing decisions. Theoretical Framework: As a result of the significant changes witnessed in the last millennium at the global level in all spheres of life, perhaps the most prominent is the shift from the planned economy to the market economy, as well as the pressures of intense competition, the emergence of globalization, the information and technology revolution, the rise in levels of foreign investment, and the enormous increase in the number and types of products, services, and brands. It significantly influenced the decisions of consumers. Method: Our study consists of a qualitative setting; thus, we have utilized the depth method, which helped us clarify the relation between consumer purchase decisions and relationship marketing from the perspective of both the consumer and the company, using semi-structured and unstructured interviews. Results and Discussion: The results indicate that the foundation for achieving growth and sustainability in the markets is to attract the greatest number of customers possible, to strive for their satisfaction and gain loyalty, to work on establishing permanent partnership relationships with all customers, and to treat each customer as if it were its market division. Research Implications: From a managerial application perspective, an understanding of consumers' expectations of their relationships with sellers would assist marketers in establishing, enhancing, and maintaining these relationships. Marketers need to identify how they can use customer data to improve customer relationships. Permission from customers can provide marketers with the privilege of contacting customers; information such as customer needs makes possible the customization of products and services; and data about the initiation and growth of customer relationships help to ensure effective and timely feedback. Marketers can informally survey their customers by asking about the relevance of various services, or they can formally survey their customers to gain more in-depth customer-specific information. Originality/Value: The findings provide insight into consumers' motivations and attitudes with regard to relationship marketing and suggest a way forward for further research. In particular, a number of ways in which mobile phone companies might seek to encourage consumers to consider value-added service propositions more seriously and become less solely price-sensitive are proposed.

Plasma Optimization as a Novel Tool to Explore Plant-Microbe Interactions in Climate Smart Agriculture.

Plasma treatment has emerged as a promising tool for manipulating plant microbiomes and metabolites. This review explores the diverse applications and effects of plasma on these biological systems. It is hypothesized that plasma treatment will not induce substantial changes in the composition of plant microbiomes or the concentration of plant metabolites. We delve into the mechanisms by which plasma can regulate microbial communities, enhance antimicrobial activity, and recruit beneficial microbes to mitigate stress. Furthermore, we discuss the optimization of plasma parameters for effective microbiome interaction and the role of plasmids in plant-microbe interactions. By characterizing plasmidome responses to plasma exposure and investigating transcriptional and metabolomic shifts, we provide insights into the potential of plasma as a tool for engineering beneficial plant-microbe interactions. The review presented herein demonstrates that plasma treatment induces substantial changes in both microbial community composition and metabolite levels, thereby refuting our initial hypothesis. Finally, we integrate plasmidome, transcriptome, and metabolome data to develop a comprehensive understanding of plasma's effects on plant biology and explore future perspectives for agricultural applications.

Differences in the influence of virtual influencers on different consumer groups

This paper uses quantitative research methods to explore the differences in the impact of virtual influencers on different consumer groups in the context of technological integration and innovation. The study uses DBSCAN clustering technology to segment consumers and combines social media behavior analysis with purchase records to collect data to identify differences in consumer behavior under the influence of virtual influencers. Consumers’ emotional resonance and brand awareness information about virtual influencers are extracted through sentiment analysis technology. The study finds that there are significant differences in the influence of virtual influencers on different consumer groups, especially in high-potential purchase groups, where the influence of virtual influencers is strong but short-lived. This paper further explores the deep integration of virtual influencer technology with new generation information technologies such as 5G and artificial intelligence, and emphasizes the importance of such technological integration in enhancing the endogenous and empowering capabilities of virtual influencers. The research results show that technological integration and innovation can not only promote the development of virtual influencers, but also provide new technical support for infrastructure construction, especially in the fields of smart cities and industrial production. This paper provides a new theoretical perspective for the market application of virtual influencers and provides practical support for the application of virtual technology in infrastructure construction.

Vegetable Oil Fractionation: Technological Methods, Applications, and Future Perspectives

Vegetable Oil Fractionation: Technological Methods, Applications, and Future Perspectives