Search Results (6,034)

Auditory Brain–Computer Interfaces (BCIs) constitute the vital intervention for profound sensorineural hearing loss where the auditory nerve is compromised, yet their clinical efficacy remains restricted by substantial biological bottlenecks and limited spectral resolution. This review critically examines the evolutionary paradigm of auditory restoration, tracing the transition from static physical replacement to dynamic biological symbiosis. We systematically analyze physiological barriers across cochlear, brainstem, and cortical levels, elucidating how rigid interfaces provoke chronic tissue responses and why linear encoding protocols fail in distorted central tonotopy. The article synthesizes emerging methodologies in material science, demonstrating how soft, bio-integrated electronics and biomimetic topologies effectively address mechanical impedance mismatches. Furthermore, the trajectory of neural encoding is evaluated, highlighting the paradigm shift from traditional envelope extraction to deep learning-driven non-linear mapping and adaptive closed-loop neuromodulation. Finally, the potential of high-resolution modulation techniques, including optogenetics and sonogenetics, alongside AI-facilitated intent perception for active listening, is assessed. It is concluded that future neuroprostheses must evolve into symbiotic systems capable of seamlessly integrating with neural plasticity to enable high-fidelity cognitive reconstruction. Full article

This study examines the perceived impact of sensory and interactive architectural design in inclusive learning environments on the sensory–emotional responses and behavioral–academic outcomes of children with neurodevelopmental disorders—namely Autism Spectrum Disorder, Down Syndrome, and Attention-Deficit/Hyperactivity Disorder—during early childhood within the Egyptian educational context. Adopting a perception-based, non-causal analytical perspective, a descriptive–analytical, survey-based design was implemented using a validated questionnaire developed from an architectural–educational conceptual framework grounded in relevant literature. The study involved (N = 202) parents, teachers, therapists, and caregivers who evaluated the perceived influence of environmental design elements on children’s sensory responses, behavior, social interaction, and academic performance, based on observational and experiential assessments rather than objective environmental performance measurements. The results indicated high perceived impacts on sensory–emotional responses (84.8%) and behavioral–academic outcomes (82.0%). Movement–spatial attributes showed the strongest influence, followed by balanced natural lighting, calming colors, natural materials, and low-noise acoustic conditions, while natural elements and sensory gardens played a regulatory role in supporting emotional stability and social interaction. The study concludes that sensory- and emotionally responsive architectural design, when understood as a supportive component of the educational experience rather than an independent causal factor, and integrated with appropriate pedagogical practices, contributes to inclusive learning environments accommodating neurodevelopmental diversity, while informing the development of an applied, evidence-informed architectural design framework that translates perceptual–correlational findings into structured and operational design guidelines adaptable to the Egyptian educational context. Full article

Chrysomya megacephala is a synanthropic fly with a high potential to act as a mechanical vector of pathogenic bacteria, surpassing Musca domestica in both bacterial load and diversity. Native to Asia and Africa, it has become a cosmopolitan species, successfully adapting to a wide range of environments, including natural ecosystems. In Colombia, studies on its role as a vector are limited and have largely relied on traditional culturing methods. This study aimed to characterize the pathogenic bacterial microbiota associated with C. megacephala using 16S rRNA gene sequencing in urban, rural, and forest settings of a coastal tourist city. Flies were collected using Van Someren Rydon traps with attractants and sterile materials. Bacterial identification was performed through Oxford Nanopore MinION sequencing (Manufactured by Oxford Nanopore Technologies, Oxford, UK). A total of 49 bacterial species were identified, with urban environments showing the highest taxonomic richness. The forest environment was characterized by a highly dominant community structure, led by Vagococcus carniphilus. Notably, 20 bacterial species of public health relevance were detected, including Clostridium botulinum, Clostridium perfringens, Ignatzschineria ureiclastica, Escherichia coli, and Streptococcus agalactiae. These findings indicate that bacterial community composition varies by environment and underscore the potential role of C. megacephala as a mechanical vector, highlighting the importance of surveillance for its public health implications. Full article

“Smart” nanoparticles are often presented as the vanguard of precision cancer therapy, defined by engineered abilities to sense predefined stimuli, enhance targeting, and control therapeutic release. Yet this notion of smartness remains largely material-centric and only partially reflects how nanomedicines behave in vivo. Cells exposed to nanoparticles are not passive recipients of engineered functions; they actively interpret these perturbations through integrated stress-response, metabolic, transcriptional, and innate immune programs. These cell-state trajectories can determine efficacy, tolerance, resistance, or toxicity, and can do so independently of uptake, biodistribution, or triggerable release efficiency. Accordingly, evaluation strategies that prioritize delivery metrics and limited a priori molecular markers may misestimate functional performance and durability. This Perspective proposes a cell-aware reframing in which smartness is defined by biological controllability: the capacity of a nanoparticle system to elicit predictable, mechanistically interpretable, and therapeutically favorable cell-state trajectories across relevant malignant and non-malignant compartments. A practical path forward is to integrate time-resolved functional profiling into benchmarking using compact response signatures that report stress buffering, immune activation or suppression, and the emergence of tolerant states. A practical path forward is to integrate time-resolved functional profiling into benchmarking using compact response signatures that report stress buffering, immune activation or suppression, and the emergence of tolerant states. Here, biological controllability refers to the ability of a nanoparticle system to reproducibly steer integrated cellular stress, metabolic, and immune programs toward predefined therapeutic endpoints while minimizing adaptive escape across heterogeneous compartments. Full article

Human information processing is often considered vision-dominant. However, perception is multisensory and shaped by interactions among sensory modalities as well as by top-down processes that integrate prior knowledge and context. Research demonstrates that these mechanisms influence early neural processing and enrich perception beyond purely bottom-up input. For individuals who are blind, this adaptability allows for the effective acquisition of information through alternative sensory channels, provided that accessibility systems are in place. A central challenge is the limited access to written materials, including text, numerical data, and music notation. Assistive technologies such as speech synthesis and Braille have become key solutions. This contribution focuses on Braille, discussing issues of organization, standardization, and technical design. It also introduces the project “Braille Display Screen Based on Long-Wave Infrared Radiation,” which seeks to create a passive Braille display as an alternative to conventional actuator-based devices. Full article

For decades, zirconia- and ceramic-based materials have dominated dental crown fabrication due to their durability and aesthetic appeal. However, a fundamental shift is occurring as polymeric alternatives emerge with notable advantages: better adhesive bonding, versatile aesthetics, lower costs, and a lighter weight. The advances in polymer chemistry and additive manufacturing have significantly impacted prosthodontics, allowing the rapid creation of highly customized, patient-specific restorations with a precision previously impossible (achieved through advanced Computer-Aided Design software and standardized 3D-printing equipment) with traditional methods. This review provides a detailed analysis of 3D-printed polymeric dental crowns from various angles. It explores the materials science behind different polymers, compares manufacturing methods, and evaluates the mechanical performance and biocompatibility. Despite the progress, polymeric materials still fall short of matching the mechanical properties of advanced ceramics, especially in compressive strength and wear resistance. Moreover, there is limited long-term clinical data over five to ten years. The lack of standardized testing protocols complicates cross-study comparisons, and the regulatory pathways for patient-specific 3D-printed devices are still developing, creating uncertainty for manufacturers and clinicians. The future prospective looks promising in many ways such as innovations like four-dimensional printing, where materials respond dynamically to environmental stimuli, which could enable crowns that adapt to changing oral conditions. Nanocomposites with functionalized nanoparticles might enhance mechanical properties while maintaining printability. AI-driven design optimization could automate and improve the crown morphology, occlusal contacts, and fit. Incorporating bioactive materials could turn crowns into active therapeutic devices that promote remineralization and combat bacterial colonization. This review summarizes the current knowledge, highlights the key gaps, and suggests steps toward establishing polymeric 3D-printed crowns as viable long-term alternatives capable of competing with or surpassing traditional ceramic options. Full article

As critical end-effectors enabling the practical deployment of marine robotic systems, soft hands face persistent challenges including multi-finger asynchronization, unbalanced force distribution, and insufficient anti-disturbance robustness, compounded by constraints from soft material nonlinearity and harsh marine environmental disturbances. To address these limitations, this paper proposes a dexterous grasping method integrating coupled dynamical systems and adaptive force planning control, designed to enhance operational reliability in complex marine environments. An intermediate dynamic layer is embedded to ensure precise multi-finger synchronization, a hybrid force planning algorithm balances force uniformity and constraint satisfaction, and an adaptive controller synergizes with a Neo-Hookean model to compensate for nonlinear deviations. Simulations and physical experiments demonstrate that the method delivers excellent grasping stability and accuracy for uneven mass distribution targets such as cylinders and spheres, while balancing synchronization precision, constraint compliance, and anti-disturbance capability. Compared with the traditional coupled dynamical systems (DSs), the constraint violation is reduced by up to 18.2%, the friction force is increased by 4.0%, and the force distribution uniformity is improved by approximately 5.1%.Compared with the particle swarm optimization (PSO) strategy, the constraint violation is reduced by up to 50.5%, the friction force is increased by 40.9%, and the force distribution uniformity is also improved by about 5.1%. This work fills a key gap in balancing multiple performance metrics for marine soft hands, providing a reliable technical solution to accelerate the real-world deployment of marine robotic systems. Full article

Background: Artificial intelligence (AI) is increasingly integrated into healthcare systems worldwide, including mental health services. While AI holds promise for improving efficiency and addressing workforce shortages, its role in psychiatry remains complex due to the central importance of empathy, clinical judgment, and ethical responsibility. Understanding clinicians’ perceptions is essential for guiding responsible AI implementation, particularly in culturally specific settings such as Saudi Arabia. Material and Methods: A cross-sectional survey was conducted among psychiatrists and family medicine physicians in Saudi Arabia between October and December 2025. The survey questionnaire was adapted from previously published instruments to assess perceptions of AI’s impact on mental health professions, the likelihood that AI could fully replace clinicians in ten core psychiatric tasks, expected timelines for replacement, and views on the balance between AI’s benefits and risks. Descriptive statistics, subgroup comparisons, and multivariable linear regression were used to analyze factors associated with higher perceived AI replacement likelihood. Results: A total of 100 physicians participated (mean age, 43.3 ± 8.9 years; 47% female). Most respondents anticipated that AI would lead to slight (45.0%) or substantial (43.0%) changes in professional roles. Perceptions varied by task: administrative tasks were most replaceable (clinical documentation, 4.03 ± 0.95; 79% likely), diagnostic/assessment tasks showed mixed perceptions (40–58%), high-risk diagnostics (suicidal/homicidal thoughts) were largely resistant (2.73–2.82; 8–30%), and relational tasks including empathetic care were least replaceable (24% likely). Physicians currently using AI tools reported significantly higher AI replacement likelihood scores, a finding that remained significant after adjustment. Overall, 64.0% of participants believed that the benefits of AI in mental health care outweighed its potential risks. Conclusions: Mental health professionals in Saudi Arabia largely view AI as a supportive tool rather than a replacement for clinicians. Clear boundaries remain around tasks requiring empathy and ethical judgment. These findings underscore the need for culturally sensitive, clinician-led, and ethically grounded AI integration strategies that strengthen, rather than undermine, the human foundations of mental health care. Full article

The overall objective of the study was to propose the application of the IRA principles and the WWP model in the Tejemujeres Cooperative, with the aim of strengthening its production and management system without compromising its social identity. To this end, a mixed descriptive and explanatory methodology was used. Surveys were conducted among the organization’s 110 members, and focus groups were conducted with internal and external stakeholders, in addition to a review of documents and bibliographic sources. This revealed structural limitations in the production system, such as a shortage of raw materials, low innovation, marketing difficulties, and limited technical training. However, the perception of economic sustainability remained positive, thanks to the social and cultural cohesion of the cooperative. Likewise, most of the members expressed openness to incorporating IRA principles and the WWP model, highlighting training, active participation in decision-making, strengthening internal governance, and creating commercial networks as priorities. In conclusion, it was determined that Tejemujeres’ main strength lies in its community identity and human capital, rather than in traditional economic indicators. The proposed theoretical frameworks were found to be relevant and adaptable to the context of the organization. Finally, a hybrid strategy is proposed that combines the participatory flexibility of the WWP model with the methodological rigor of the IRA principles, which will enable the cooperative to consolidate an innovative, sustainable, and culturally legitimate production system. Full article

This paper presents the design and industrial implementation of an adaptive discrete control system for a rotary dryer operating in potash fertilizer production. The drying process is characterized by high inertia, multivariable interactions, transport delay, and non-stationary behavior resulting from variations in raw material properties and external disturbances, which significantly reduce the effectiveness of conventional fixed-parameter controllers. A discrete-time mathematical model of the rotary drying process was developed using industrial experimental data collected from a full-scale production plant. The process was modeled as a coupled 2 × 2 multivariable system with pronounced time-delay effects in the main control channels. System identification was carried out using statistical and frequency-domain methods to capture the dominant dynamic characteristics required for controller synthesis. Based on the identified model, an adaptive discrete controller with online parameter adjustment was developed to regulate outlet moisture content and exhaust gas temperature. Simulation and industrial results confirmed stable operation under varying conditions, improved regulation accuracy, enhanced process stability, and an average production efficiency increase of approximately 1.8%, accompanied by reduced fuel consumption. Full article

Reconfigurable logic is crucial for future adaptive computing, but is challenging to realize with conventional complementary metal-oxide-semiconductor technology due to the limited field-effect characteristics of the fundamental silicon devices. Two-dimensional materials offer a promising platform, yet enhancing their functional versatility requires novel operational mechanisms. Here, we demonstrate a single WSe₂/h-BN/graphene heterojunction capable of dynamically switching between distinct logic functions—XNOR and IMP (implication gate or “IF-THEN” gate)—simply by modulating the drain-source voltage. At a low bias of 0.3 V, the carrier distribution is governed by capacitive coupling, realizing an XNOR gate. Increasing the bias to 3 V activates Fowler–Nordheim tunneling between the graphene floating gate and the drain, enabling IMP logic operation. The interplay and voltage-induced transition between these two physical mechanisms underpin the device’s multifunctional capability. This work introduces a novel operational strategy for two-dimensional material-based reconfigurable logic, providing a pathway toward compact, adaptive hardware for post-CMOS computing. Full article

Background/Objectives: Interbody fusion cages provide both structural support and a biologically favorable environment for osseointegration. Through recent decades, cage design and biomaterial selection have evolved to more adapted implants in different concept philosophies. Based on this development, the objective of this work was to develop a systematic review of the state of the art regarding spine interbody cage concepts on the market and anticipate future directions in cage design. Methods: A systematic review following PRISMA 2020 guidelines was conducted in three databases of reference, Scopus, PubMed and Mendeley, in September 2025, considering results from between 2015 and the present using the following keywords: spine, interbody, cage and concept. A revision of the first results was performed, and duplicate entries were excluded, as well as papers without a firm relevance for cage design concepts. Results: This search resulted in 76 selected papers and different design concepts and clinical outputs, and after a duplicate analysis, just 40 papers were selected. The material properties may play an important role in the characteristics of the implant and critically influence load-sharing and bone ingrowth. Surface modifications, including texturing, porosity engineering, and osteoconductive coatings, have been introduced to enhance cellular adhesion and fusion rates. It was observed through the research performed that the main problems are related to micromobility, implant displacement and stress shielding effects in adjacent vertebras. Conclusions: Among the different evolutions observed in cages through the years, design changes played an important role in adapting each case. Knowing that the design could be strongly influenced by the surgical approach used (anterior, posterior, transforaminal or lateral) and bone quality, it is also possible to find, nowadays, different options for different needs that are only accessible due to the technological advances in additive manufacturing, which allowed the development of patient-specific implants. Full article

To meet the demand for refined laundry care in intelligent washing machines and address the low accuracy, poor robustness, and lack of physical interpretability of existing material recognition technologies, a recognition method integrating physical prior knowledge is proposed. Based on a physical experimental platform for drum washing machines, mechanical vibration signals from a three-axis acceleration sensor and motor electromagnetic signals are collected synchronously, a dataset consisting of soft and hard loads is constructed, and time-domain alignment of heterogeneous signals is realized using adaptive pooling technology. Combined with the mechatronic coupling mechanism in the loosening, deviation detection, and weighing stages of washing machines, a Physics-Aware Dual-Stream Multi-Scale Temporal Convolutional Network (PSA-DSMS-TCN) is designed. The network extracts mechanical and electromagnetic features in parallel through a dual-stream structure, expands the receptive field using multi-scale dilated convolution, and introduces an operating condition-gated attention mechanism to achieve dynamic feature fusion. The results of 5-fold cross-validation show that the model achieves an average recognition accuracy of 94.05%, with consistent performance enhancement and substantial practical robustness. The results demonstrate that the PSA-DSMS-TCN effectively improves the precision of material prediction while maintaining lightweight characteristics, providing reliable technical support for the intelligent matching of laundry care parameters. Full article

Erosion is widely encountered in circulating fluidized bed (CFB) boilers. Investigations into erosion mechanisms and mitigation strategies are essential for improving the operational reliability and reducing economic losses. This paper presents a bibliometric analysis and review of recent progress in erosion-related studies for CFB boilers, identifying three main research hotspots: CFD-based erosion prediction from flow dynamics, anti-wear coatings from materials science that consider chemical corrosion, and boiler design adaptations for biomass. Building upon classical studies on solid particle erosion mechanisms and accounting for the high-temperature and reactive chemical environments characteristic of CFB boilers, the erosion mechanisms in CFB boilers are systematically summarized. It is revealed that particle flow parameters dominate the erosion process, coupled with chemical corrosion. Subsequently, the application of computational fluid dynamics (CFD) methods to erosion prediction and mitigation in CFB boilers is reviewed, and the characteristics of various anti-wear techniques are discussed. It is found that CFD can serve as an effective tool for the design of anti-wear techniques; however, the design must account not only for erosion resistance but also for the resulting impacts on boiler heat transfer and thermal inertia. Finally, perspectives and future research directions for erosion studies in CFB boilers are outlined. Full article

This study investigates the application of the Pure Random Orthogonal Search (PROS) method, introduced in the literature in 2021, for approximating force and displacement measurement data obtained from rock specimen testing, using granite as a case study. The primary objective is to simplify the data approximation procedure and improve the accuracy of experimental data analysis by reducing the influence of subjective factors within a predefined protocol. The research focuses on determining the maximum value of the tangent modulus of elasticity during the pre-peak deformation stage of granite specimens under uniaxial compression. The study employs methods of mathematical modeling of rock mechanical behavior and experimental data analysis. To approximate the experimental data, a modified two-parameter S-curve equation is proposed. The optimal parameter values are determined using the PROS method, which reduces the problem to solving a two-dimensional objective function minimization task. The dimensionality of this optimization problem remains independent of the number of experimental data points, thereby enhancing computational efficiency. A systematic computational procedure is developed for the automated calculation of the approximating equation’s parameters and the determination of the maximum tangent modulus of elasticity. In the context of challenges associated with accurately measuring displacements using conventional testing machines, a numerical correction procedure is proposed and implemented to account for the compliance of the loading system. The results of the study are consistent with both the literature-reported experimental data and the data obtained in this work. The methodology and findings can be adapted for analyzing the properties of concrete as an artificial analog of natural rock materials. Full article