Search Results (4,744)

Background: Robot-assisted surgery has become increasingly used across multiple specialties; however, its integration into aesthetic plastic surgery remains limited. Individualized patient requirements, such as concealed scar placement, superficial soft tissue dissection, and patient-specific docking angles, are major challenges to its adoption, unlike in other specialties. This review aimed to evaluate the current use of robotic systems in plastic surgery, with a particular focus on aesthetic procedures, operative outcomes, and existing technological limitations. Methods: Multiple databases, including PubMed, Scopus, and Google Scholar, were extensively searched to identify studies published between 2011 and 2026. Data on robotic platforms, operative duration, rehabilitation outcomes, and aesthetic indications were extracted and analyzed. Robotic systems such as da Vinci, Symani, MUSA, and ARTAS demonstrated feasibility across reconstructive subspecialties. However, their clinical application remains limited, as purely aesthetic procedures are rare, highlighting a significant lack of standardized docking methods and dedicated instruments. Results: The data show that robotic platforms offer great advantages, such as precision and minimally invasive access; however, their high costs, bulky instrumentation, and limited docking methods represent barriers to their adoption in aesthetic surgery. Conclusions: Robot-assisted aesthetic plastic surgery remains in the early stage of development. Further research is required to establish reproducible docking standards and expand its clinical indications. Advancements in single-port systems, artificial intelligence integration, and surgeon training will facilitate broader clinical implementation. Full article

Firewall policy misconfigurations remain a major source of security vulnerabilities in modern networks, particularly as firewall rule sets grow in size and complexity. Such misconfigurations, commonly referred to as firewall anomalies, can lead to unintended access control behavior and undermine network security. In this paper, we propose a formal logic rule-based framework for the systematic detection and investigation of firewall anomalies, supported by knowledge graph-based visualization. First-order logic (FOL) is employed to precisely model firewall rules and to define major anomaly types, including shadowing, redundancy, correlation, generalization, and irrelevance, in both single and distributed firewall environments. The proposed framework introduces explicit and comprehensive logical definitions for each anomaly type, enabling deterministic, interpretable, and complete detection of rule conflicts and overlaps. Complex anomalies, particularly correlation and generalization, are systematically decomposed into well-defined logical cases to facilitate the accurate identification of subtle, order-dependent interactions among firewall rules. To enhance usability and analysis, firewall rules and detected anomalies are represented using Neo4j knowledge graphs, providing intuitive visual insights into rule relationships and anomaly causes. The effectiveness of the proposed approach is validated using a real operational backbone network dataset collected from Stanford University’s campus network. Experimental results demonstrate the framework’s ability to accurately detect both simple and complex firewall anomalies under realistic network conditions. To further validate the proposed logic rules, a machine learning-based evaluation was conducted. The findings confirm their effectiveness in accurately characterizing firewall anomalies. Unlike machine learning or heuristic-based methods, the proposed approach does not require training data and guarantees formal correctness and explainability. These features make it a robust and practical solution for firewall policy verification and network security management. Full article

Candida albicans is a ubiquitous commensal fungus that may be lethal once it gains access to the bloodstream, following a breach in protective barriers such as skin or gut lining. Intravenous injection of C. albicans (4.5 × 10⁴ yeasts/gm of mouse) leads reproducibly to systemic infection with a median survival of about 75 h. We studied the effects of two human innate immune effectors on the course of systemic infections. The soluble human pentraxin serum amyloid P component (hSAP) retards death in murine disseminated candidiasis. In contrast, another soluble pentraxin, human C-reactive protein (hCRP), hastens death. To examine the pathological basis for these differences, necropsies were performed, and the right kidney was removed for study. Candidiasis caused abundant collagen deposition (the precursor to fibrosis) and loss of contrast between the kidney medulla and cortex. Daily administration of subcutaneous hSAP following the intravenous injection of C. albicans preserved the discrete histological difference between cortex and medulla and lessened host collagen deposition. Yeasts and hyphae within abscesses were decorated with hSAP. Contrastingly, kidneys from animals administered C. albicans and hCRP showed extensive collagen deposition and loss of the boundary between the cortex and the medulla of the kidney. hCRP did not bind to fungi but bound to damaged tissue surrounding abscesses, leading to a more destructive infection with loss of tissue. Staining cells with antibodies to CD45 (to detect T-lymphocytes, myelocytes, monocytes, and macrophages) and antibodies to Ly-6G (neutrophils, and granulocytes) showed that hSAP retarded infiltration of inflammatory cells into diseased areas. The results are consistent with the hypothesis that early administration of hSAP represses the migration of inflammatory cells, dampens the production of collagen by fibroblasts, and dampens the overall immune response of the host to infection. In doing so, hSAP prolonged life, whereas hCRP facilitated the infectious process and hastened death. Full article

This study examines the effects of a three-month pedagogical intervention that integrated artificial intelligence (AI), social media, and web-based tools to strengthen digital literacy, creativity, and cultural participation among secondary education students in Ecuador. The intervention was theoretically grounded in perspectives of inclusive digital education and Universal Design for Learning (UDL), emphasizing participation, accessibility, and collaborative knowledge construction. The intervention involved 61 students supported by 31 university facilitators and was developed under a mixed-methods action research design with a pre–post (quasi-experimental) approach. Pre- and post-test surveys were administered to assess changes in digital competencies and creativity, while semi-structured interviews explored students’ perceptions of creative expression and their engagement with the cultural and technological ecosystem. Quantitative results showed statistically significant improvements in digital literacy and creativity (p < 0.001), while qualitative findings evidenced increased student empowerment, critical awareness of algorithms, and active cultural participation. The integration of AI and social media promoted an inclusive, student-centered learning environment that enhanced autonomy, reflective thinking, and media engagement. These results suggest that hybrid and culturally contextualized AI-mediated interventions may foster 21st-century competencies, strengthen digital equity, and promote creative agency in educational contexts of the Global South, particularly within emerging digital learning environments in Ecuador. Full article

Background: During the flu season, there is an increase in absenteeism due to illness, a drop in productivity, and a greater risk of the virus spreading among workers. Thus, the Italian Ministry of Health recommends vaccination for essential service workers. The University of Salerno, in collaboration with the local health authority of Salerno, offers free vaccination to its employees. Methods: A public health methodology for seasonal influenza vaccination in the workplace is presented—specifically in the university setting—with the aim of identifying individual, contextual, and organizational elements of the model that have promoted vaccination uptake. An ad hoc questionnaire was used (October–December 2025) to survey 399 academic employees, investigating seasonal influenza vaccination in the following aspects: recent personal experiences, motivations, vaccination experiences at university, sources of information, considerations regarding national and local vaccination campaigns, and level of vaccine confidence (VCI). Results: Seasonal influenza vaccination at the University is appreciated for its compatibility with working hours (66.1%), the availability of a platform that allows flexible booking (56.9%), the perception of safety in the environment (31.6%), the fact that the vaccine is free (17.4%), and the involvement of office/laboratory colleagues (5%). Participants appreciate the model and would apply it to other vaccinations at the University and in other institutional settings. A significant relationship (F = 7.24; df = 1; p < 0.05) exists between confidence in the vaccine and the sense of security experienced when receiving the vaccine in the workplace. Data analysis was performed using the IBM SPSS v.28 software. Conclusions: The model proposed can be applied to other institutional contexts, simplifying and facilitating access to vaccines by implementing vaccination campaigns tailored to specific work environments. Full article

The increasing demand for advanced diagnostic technologies has positioned biosensor platforms as powerful alternatives to conventional analytical methods. Among them, lateral flow platforms (LFPs) are widely used for their speed, simplicity, and low cost. However, their limited sensitivity and lack of quantitative precision have spurred the development of enhanced systems incorporating electrochemical detection. Electrochemical biosensors offer significant advantages, including high sensitivity, excellent selectivity, and ease of miniaturization, which make them especially suitable for point-of-care testing (POCT). To address the limitations of traditional colorimetric LFPs, several strategies have been employed, such as the incorporation of nanomaterials, enzymatic amplification, and signal-enhancing labels. A particularly promising innovation is the direct integration of electrodes into LFPs, enabling real-time electrochemical readouts and enhanced analytical accuracy. Despite their potential, challenges persist, including manufacturing complexity, a lack of standardized protocols, and difficulties in scaling production for widespread adoption. Continued progress in developing hybrid platforms that combine lateral flow technology with electrochemical detection is crucial for expanding diagnostic applications in healthcare, environmental monitoring, and food safety. This work explores recent advances in electrochemical LFPs, reviewing current methodologies while discussing their advantages, limitations, and the future directions necessary to facilitate broader implementation and improve global diagnostic accessibility. Full article

Background: Care for knee osteoarthritis (KOA) is frequently fragmented, and pathway-level decisions within Physical Medicine and Rehabilitation (PM&R) are influenced by local organizations. The objective of this study was to identify areas of agreement and disagreement among PM&R experts and to translate these into a clinically interpretable, function-oriented care pathway for knee osteoarthritis (KOA) within rehabilitation services. Methods: A two-round Real-Time Delphi study was conducted using the SmartDelphi web platform. A steering committee of five PM&R physicians developed a 37-item questionnaire covering referral/access, functional and outcome assessment, conservative management, escalation/referral thresholds, and follow-up/discharge. Round 1 was online (SERMEF osteoarthritis working group; 46 invited, 40 completed; 87.0%) with responses collected until 30 April 2025. Round 2 was an in-person, facilitated validation round on 30 May 2025 at the SERMEF Congress (A Coruña; 85 invited, 70 completed; 82.4%). Items were rated on a 6-point Likert scale; consensus strength was defined by interquartile range (IQR): strong (0–1) vs. weak (≥2). No patient-level data were collected; participant characteristics were comparable across rounds, suggesting consensus refinement reflected deliberation rather than panel shifts over time. Results: Consensus supported a longitudinal, function-first pathway that was structured into five phases: entry/referral to PM&R; comprehensive functional assessment using a minimum outcomes dataset (pain VAS/NRS, WOMAC function, quality-of-life scale); multimodal conservative rehabilitation combining exercise/physiotherapy, education/self-management support, and indicated oral/topical therapies; reassessment-guided escalation in non-responders, reserving interventional PM&R techniques, multidisciplinary musculoskeletal pain-unit management, or orthopedic evaluation for persistent pain and/or functional limitation; and longitudinal monitoring with defined discharge criteria. Conclusions: SERMEF PM&R experts converged on an implementation-oriented, outcomes-driven KOA itinerary centred on functioning, conservative multimodal care, structured reassessment, and explicit discharge planning. Full article

Peru’s recent national mental health (MH) reforms aim to decentralise care and expand access to MH services for rural populations by integrating services into primary healthcare through the expansion of Community Mental Health Centres (CMHCs). Evidence on the implementation of these reforms at the local level remains limited. This qualitative study aimed to (i) describe the structure and implementation framework of MH services, (ii) analyse local understandings of MH; and (iii) examine pathways to care and identify barriers and facilitators to MH service implementation from both the supply (service providers) and demand (users and community members) perspectives. MH services were mapped across three provinces of northern Peru using a review of national MH policies, 2 focus group discussions, and 31 semi-structured interviews. Data were analysed thematically to explore local understandings of MH, pathways to care, and health system barriers. Local understandings of MH are shaped by cultural beliefs, social norms, and economic conditions, with many individuals experiencing distress initially relying on family networks or traditional healers. Stigma and expectations of a quick recovery hinder engagement with formal services. While the expansion of CMHCs has improved geographical access to specialised care in rural areas through proximity and being patient-centred, the implementation of respectful provider interactions remains uneven. Weak referral pathways and limited coordination between primary care centres and CMHCs frequently shift the responsibility for navigating care onto users and their families. Family involvement and culturally sensitive practices foster trust and support continued engagement. Persistent challenges include the limited capacity of service providers, high staff turnover, and the follow-up mechanisms, stigma, and tensions between cultural and biomedical understandings of MH. Peru’s expansion of CMHCs represents a significant health system reform to improve equitable access for rural populations. To sustain these gains, it will be necessary to strengthen workforce stability, clarify referral processes, and integrate culturally responsive approaches within primary care systems, offering lessons for similar resource-constrained contexts. Full article

Background/Objectives: Protein kinases play a crucial role in cancer initiation, progression, and therapeutic resistance by regulating signalling pathways involved in tumour growth and survival. Consequently, they represent major targets in anticancer drug discovery. Among heterocyclic scaffolds explored in kinase inhibitor design, benzimidazole has emerged as a privileged structure due to its strong hydrogen-bonding capability and structural resemblance to purine moieties. Triazole motifs are also widely incorporated into bioactive molecules because of their metabolic stability, favourable electronic properties, and ability to establish key interactions within kinase active sites. This review aims to summarise and critically discuss benzimidazole- and triazole-based kinase inhibitors, both as individual scaffolds and as hybrid systems, with emphasis on their kinase targets and multitarget potential. Methods: The relevant literature was surveyed from major scientific databases focusing on studies describing the synthesis, biological evaluation, and molecular modelling of benzimidazole- and triazole-containing kinase inhibitors. Results: Numerous studies demonstrate that both benzimidazole and triazole scaffolds exhibit significant kinase inhibitory activity against oncogenic targets, including EGFR, cyclin-dependent kinases (CDKs), and components of the PI3K/Akt/mTOR signalling pathway. Hybrid molecules combining these pharmacophores frequently enhance binding interactions and facilitate the development of multitarget kinase inhibitors. Structure–activity relationship trends indicate that pharmacophore accessibility, substitution patterns, and linker architecture influence inhibitory potency and selectivity. Conclusions: Overall, benzimidazole- and triazole-based scaffolds represent promising platforms for developing next-generation multitarget anticancer agents and provide valuable insights for the rational design of improved kinase inhibitors. Full article

Educational robotics (ER) and robotics competitions offer an effective context for developing STEM (Science, Technology, Engineering, and Mathematics) competencies, technical skills, and soft skills in engineering degrees. However, current platforms reveal a pedagogical and technical gap: closed commercial systems restrict access to hardware, while open solutions frequently lack a robust and structured architecture for educational settings. Moreover, in both cases, many platforms do not achieve the hardware requirements of the most demanding competitions. To address this issue, the present article presents the design, implementation, and validation of EASYbot, a modular open-hardware robotics platform based on Arduino. The system integrates a microcontroller, a dual USB–battery power supply, high-performance motor power stages, and a plug-and-play interface for input/output and communication peripherals, enabling its use in several competition categories such as mini-sumo or maze robots. The platform is complemented by a state-based programming model and supports libraries that facilitate a learning assessment. The platform provides a scalable ecosystem, enabling students to progress from initial prototyping to optimised hardware control. The validation process encompasses a range of assessments, including technical tests, usability, and adoption evaluation through surveys. Full article

Background: In reverse shoulder arthroplasty (RSA), preservation of the subscapularis (SSC) has gained attention because of its biomechanical and functional significance. However, when SSC preservation is attempted using the conventional deltopectoral (DP) approach, glenoid visualization and instrument access may be limited. The purpose of this Technical Note is to describe a modified deltopectoral exposure technique, hereafter referred to as the Margin-Shifted, Yawing, Subscapularis-Sparing, and Transitioned Lateralized Deltopectoral (MYST–LDP) approach, and to assess its feasibility in primary RSA. Methods: The MYST–LDP approach incorporates a laterally shifted incision apex, a proximally oriented curved arc (“yawing”) toward the acromion, complete preservation of the subscapularis, and a distally transitioned limb aligned with the anterior humeral axis. We describe the surgical technique and our initial experience in three consecutive primary RSA cases performed using an inlay implant system to minimize humeral lateralization and allow focused assessment of exposure geometry. Results: In all cases, the SSC was preserved without conversion to a standard DP exposure. Adequate glenoid visualization was achieved using three retractors without excessive soft-tissue tension, allowing controlled glenoid preparation and component implantation without additional exposure or conversion. No approach-related intraoperative complications were observed. Conclusions: The MYST–LDP approach is a feasible modification of the deltopectoral exposure that preserves both SSC and the deltoid while facilitating glenoid visualization and instrument alignment. This technique represents an ergonomic and tissue-preserving option within the familiar DP framework for surgeons performing SSC-preserving RSA. Further comparative and quantitative studies are warranted to determine its clinical value. Full article

Background/Objectives: Pterygoid implant placement represents a valuable alternative to conventional bone grafting procedures in the rehabilitation of the atrophic posterior maxilla; however, the procedure remains technically demanding because of limited visibility, difficult access, complex pterygomaxillary anatomy, and the need for precise angulation and distal bicortical anchorage. Although digital guidance has increasingly been applied in implant dentistry, a clearly described workflow integrating automatic segmentation, selective virtual trimming of the posterior maxillary anatomy, and direct three-dimensional planning for static-guided pterygoid implant placement remains insufficiently detailed in the literature. The aim of this report was to describe and illustrate such a workflow in a proof-of-concept clinical application. Methods: This work was designed as a methodological proof-of-concept with a single clinical illustration. A CBCT dataset was imported into BlueSkyPlan, where automatic segmentation was used to generate three-dimensional models of the maxilla, teeth, and pterygoid process. The segmented volumes were then selectively trimmed to expose the relevant pterygomaxillary anatomy and to support direct three-dimensional planning of the implant axis in the rendered model. A static surgical guide with combined tooth and mucosal support was subsequently designed, positioned on a printed jaw model derived from the intraoral scan, and assessed by CBCT-based internal verification. Results: In this proof-of-concept application, the workflow enabled three-dimensional visualization of the pterygomaxillary trajectory, supported implant axis planning in the rendered model, and facilitated guide design and radiographic verification of the planned trajectory. The verification step provided an internal methodological consistency check between the planned implant axis and the drill-guided direction visible on CBCT. Conclusions: The present report describes a segmentation-assisted three-dimensional planning workflow for static-guided pterygoid implant placement in a single proof-of-concept clinical application. The workflow should be interpreted as a methodological illustration rather than a quantitative validation study. Further investigations are required to evaluate accuracy, inter-operator reproducibility, and broader clinical applicability. Full article

Southwest China harbors the world’s richest germplasm resources of Tartary buckwheat (Fagopyrum tataricum). However, their effective utilization is severely constrained by poor management and narrow genetic diversity. Developing a core collection is a key strategy for overcoming these bottlenecks and facilitates the efficient conservation and utilization of germplasm resources. Therefore, we aimed to assess the genetic diversity and population structure of a Tartary buckwheat germplasm collection from Yunnan Province and adjacent regions to establish a core collection. Whole-genome resequencing and phenotyping of four key agronomic traits were performed on 313 Tartary buckwheat accessions. Population genetic structure, differentiation, and diversity parameters were analyzed using single-nucleotide polymorphism (SNP) data. We obtained 3,433,676 high-quality SNP markers. The 313 accessions were classified into four ancestral populations and three phylogenetic groups, which revealed the complex patterns of genetic differentiation and gene flow. Phenotypic traits exhibited high genetic diversity, with wide variation ranges in key agronomic traits such as plant height, stem diameter, and branching characteristics, highlighting the richness of the germplasm resources. By integrating the phenotypic and SNP data, we constructed a core collection (Core-Merge) comprising 105 accessions (33.55% of the original collection). Core-Merge showed no significant differences in phenotypic traits compared to the original collection, exhibited a similar distribution in principal coordinate analysis, and demonstrated low kinship among individuals. The collection established in this study, Core-Merge, captures the maximum phenotypic and genotypic variability present in the original germplasm. The core germplasm collection provides a valuable foundation for the efficient conservation of, genetic research on, and molecular breeding of Tartary buckwheat. Full article

Skin cancer is caused by aberrant cells that proliferate uncontrollably after unrepaired DNA damage results in mutations in the epidermis. The majority of skin cancer is caused by high UV exposure from the sun, tanning beds, or sunlamps. Due to sociocultural hurdles, limited access to specialized dermatological care, and low public knowledge, many nations, including India, have higher mortality rates and late-stage presentations. The unequal distribution of specialized dermatological treatments, particularly in rural and underdeveloped areas, makes detection and treatment more difficult. For skin cancer, one of the most prevalent malignancies with a high death rate, early detection is crucial. This study gathered 1200 dermoscopic images from two clinics in Himachal Pradesh in order to solve these problems. In order to automatically classify dermoscopic clinical images into melanoma and non-melanoma skin cancer categories, this study compares VGG16 with ResNet-50. Preprocessing, lesion segmentation, and classification are all part of the suggested approach. A collection of 1200 dermoscopic images with clinical annotations was used to improve the models. ResNet-50 outperformed VGG16 in tests, with 93% accuracy and 96% AUC-ROC as opposed to 89% and 94%, respectively. These results emphasize how crucial model selection and preprocessing are to diagnostic performance. Ensemble methods, multi-class classification, explainability integration, and clinical validation will be investigated in order to facilitate the implementation of AI-assisted dermatological diagnostic tools. Full article

The development of effective Intrusion Detection Systems (IDS) for Internet of Things (IoT) environments is constrained by the absence of realistic, large-scale datasets, particularly for the Message Queuing Telemetry Transport (MQTT) protocol, which is prevalent in industrial IoT. Existing datasets are frequently limited in scope, imbalanced, or do not capture MQTT-specific attack patterns, thereby impeding the training of accurate machine learning models. To address this gap, the extensible Message Queuing Telemetry Transport (eMQTT) Traffic Generator is introduced as a modular platform capable of simulating both legitimate MQTT communication and targeted denial-of-service (DoS) attacks. The framework features a scalable and reproducible architecture that incorporates protocol-aware attack modeling, automated traffic labeling, and direct export of datasets suitable for machine learning applications. The system produces standardized, configurable, repeatable, and publicly accessible datasets, thereby facilitating reproducible research and scalable experimentation. Experimental validation demonstrates that the simulated traffic aligns with established DoS behavior models. Two high-volume datasets were generated: one representing normal MQTT traffic and another emulating CONNECT-flooding attacks. Machine learning classifiers trained on these datasets exhibited strong performance, with gradient boosting models achieving over 95% accuracy in distinguishing benign from malicious traffic. This work offers a practical solution to the scarcity of datasets in IoT security research. By providing a controlled, extensible, and reproducible traffic-generation platform alongside validated datasets, eMQTT enables systematic experimentation, supports the advancement of IDS solutions, and enhances MQTT security for critical IoT infrastructures. Full article