Search Results (224)

Recent advancements in data collection technologies, data science, and speech processing have fueled significant interest in the computational analysis of biological sounds. This enhanced analytical capability shows promise for improved understanding and detection of various pathological conditions, extending beyond traditional speech analysis to encompass other forms of acoustic data. A particularly promising and rapidly evolving area is the application of deep learning techniques for the detection and analysis of diverse pathologies, including respiratory, cardiac, and neurological disorders, through sound processing. This paper provides a comprehensive review of the current state-of-the-art in using deep learning for pathology detection via analysis of biological sounds. It highlights key successes achieved in the field, identifies existing challenges and limitations, and discusses potential future research directions. This review aims to serve as a valuable resource for researchers and clinicians working in this interdisciplinary domain. Full article

Deep margin elevation (DME) is a widely adopted technique for managing subgingival cervical proximal margins by repositioning them to a supragingival location. This approach enhances access, visibility, and control in these anatomically challenging areas. This narrative review aimed to evaluate current evidence on the indications, materials, clinical protocols, and outcomes of DME. A structured search was conducted in PubMed, the Cochrane Library and Scopus up to February 2025, using keywords such as “deep margin elevation”, “proximal box elevation” and “subgingival margin.” Clinical studies, in vitro investigations, relevant reviews and reports in English were included. A total of 59 articles were selected based on eligibility criteria. The hypothesis was that DME can serve as a reliable alternative to surgical crown lengthening in appropriate cases. A variety of materials have been investigated for use as the intermediate layer, with composite resins of varying viscosities and filler compositions being preferred due to their favorable long-term mechanical properties. DME may reduce the need for surgical intervention while maintaining periodontal health; however further randomized clinical trials are needed to clarify the material selection, establish long-term outcomes, and standardize clinical protocols. Understanding the indications, limitations, and protocol of DME is critical for achieving biologically sound and predictably functional restorations. Full article

Common ragweed (Ambrosia artemisiifolia L.) has been identified as one of the most harmful invasive weed species in Europe due to its allergenic pollen and competitive growth in diverse habitats. In the first part of this review [Common Ragweed—Ambrosia artemisiifolia L.: A Review with Special Regards to the Latest Results in Biology and Ecology], its biological characteristics and ecological behavior were described in detail. In the current paper, control strategies are summarized, focusing on integrated weed management adapted to the specific habitat where the species causes damage—arable land, semi-natural vegetation, urban areas, or along linear infrastructures. A range of management methods is reviewed, including agrotechnical, mechanical, physical, thermal, biological, and chemical approaches. Particular attention is given to the spread of herbicide resistance and the need for diversified, habitat-specific interventions. Among biological control options, the potential of Ophraella communa LeSage, a leaf beetle native to North America, is highlighted. Furthermore, innovative technologies such as UAV-assisted weed mapping, site-specific herbicide application, and autonomous weeding robots are discussed as environmentally sustainable tools. The role of legal regulations and pollen monitoring networks—particularly those implemented in Hungary—is also emphasized. By combining traditional and advanced methods within a coordinated framework, effective and ecologically sound ragweed control can be achieved. Full article

Recent advances in passive acoustic monitoring (PAM) have markedly improved the ability to study marine soundscapes by enabling long-term, non-invasive monitoring of biological sounds across large spatial and temporal scales. Among aquatic organisms, fish are primary contributors to biophony, producing sounds associated with feeding, reproduction, and social behavior. However, the majority of previous research has focused on individual vocalizations, with limited attention to collective acoustic phenomena such as fish choruses. This study quantitatively analyzes choruses produced by the small yellow croaker (Larimichthys polyactis), an ecologically and commercially important species in the Northwest Pacific Ocean. Using power spectral density (PSD) analysis, we examined long-term underwater recordings from a sea cage containing approximately 2000 adult small yellow croakers. The choruses were centered around ~600 Hz and exhibited sound pressure levels 15–20 dB higher at night than during the day. These findings highlight the ecological relevance of fish choruses and support their potential use as indicators of biological activity. This study lays the foundation for incorporating fish choruses into soundscape-based PAM frameworks to enhance biodiversity and habitat monitoring. Full article

An innovative approach is explored to reconnect urban populations with nature through the integration of technology and artistic expression. In a case study of London’s Canary Wharf, environmental sensor data of sound and visual art were analyzed to create new pathways for human–plant interaction. By transforming plant biological data into accessible artistic experiences, interdisciplinary methods spanning environmental science, plant biology, and artistic practice can enhance ecological awareness and engagement. The synthesized approach in this study offers promising solutions for addressing the growing disconnect between urban communities and their natural environment. Full article

Medical phantoms are essential to imaging calibration, clinician training, and the validation of therapeutic procedures. However, most ultrasound phantoms prioritize acoustic realism while neglecting the viscoelastic and anisotropic properties of fibrous soft tissues. This gap limits their effectiveness in modeling realistic biomechanical behavior, especially in wave-based diagnostics and therapeutic ultrasound. Current materials like gelatine and agarose fall short in reproducing the complex interplay between the solid and fluid components found in biological tissues. To address this, we developed a soft, anisotropic composite whose dynamic mechanical properties resemble fibrous biological tissues such as skin and skeletal muscle. This material enables wave propagation and vibration studies in controllably anisotropic media, which are rare and highly valuable. We demonstrate the tunability of damping and stiffness aligned with fiber orientation, providing a versatile platform for modeling soft-tissue dynamics and validating biomechanical simulations. The phantoms achieved Young’s moduli of 7.16–11.04 MPa for skin and 0.494–1.743 MPa for muscles, shear wave speeds of 1.51–5.93 m/s, longitudinal wave speeds of 1086–1127 m/s, and sound absorption coefficients of 0.13–0.76 dB/cm/MHz, with storage, loss, and complex moduli reaching 1.035–6.652 kPa, 0.1831–0.8546 kPa, and 2.138–10.82 kPa. These values reveal anisotropic response patterns analogous to native tissues. This novel natural fibrous composite system affords sustainable, low-cost ultrasound phantoms that support both mechanical fidelity and acoustic realism. Our approach offers a route to next-gen tissue-mimicking phantoms for elastography, wave propagation studies, and dynamic calibration across diverse clinical and research applications. Full article

Blind source separation (BSS) of underwater acoustic mixed signals aims to improve signal clarity by separating noise components from aliased underwater signal sources. This enhancement directly increases target detection accuracy in underwater acoustic perception systems, particularly in scenarios involving multi-vessel interference or biological sound coexistence. Deep learning-based BSS methods have gained wide attention for their superior nonlinear modeling capabilities. However, existing approaches in underwater acoustic scenarios still face two key challenges: limited feature discrimination and inadequate robustness against non-stationary noise. To overcome these limitations, we propose a novel Robust Cross-Band Network (RCBNet) for the BSS of underwater acoustic mixed signals. To address insufficient feature discrimination, we decompose mixed signals into sub-bands aligned with ship noise harmonics. For intra-band modeling, we apply a parallel gating mechanism that strengthens long-range dependency learning so as to enhance robustness against non-stationary noise. For inter-band modeling, we design a bidirectional-frequency RNN to capture the global dependency relationships of the same signal across sub-bands. Our experiment demonstrates that RCBNet achieves a 0.779 dB improvement in the SDR compared to the advanced model. Additionally, the anti-noise experiment demonstrates that RCBNet exhibits satisfactory robustness across varying noise environments. Full article

The welfare of animals in zoos has come under increasing scrutiny as public awareness grows around the biological needs of captive species. It is also becoming clear that promoting positive welfare experiences upholds population management and conservation aims. This paper re-evaluates current welfare frameworks in zoological institutions, advocating for evidence-based practices, multi-dimensional welfare metrics, and greater emphasis on species-specific needs, as well as the importance of input-based approaches to assess the welfare of zoo animals. By evaluating the limitations of current welfare practices (e.g., a lack of species-specific assessment protocols or sound husbandry evidence to base measures on) and presenting potential areas for improvement, this paper identifies ways that sound baselines for meaningful zoo animal welfare outputs can be created. Although current welfare policies from large zoo membership organisations stipulate assessment of welfare outputs as key to improving animal welfare standards, such outputs can only be positive if inputs are species-specific and relevant to the animals being housed. Practices such as the use of environmental enrichment (for example) need to be further refined to ensure they provide meaningful outputs (for the individuals) from the inputs that create them. Understanding the animal’s needs to ensure that the goal of enrichment is clear benefits both the animal who is provided with the enrichment and the human caregivers as husbandry and management becomes easier. A focus on welfare outputs is commendable and (especially when considering emotional outputs) is indeed a gold standard to aim for, yet we must not lose sight of striving for improvements to housing, husbandry, and species-specific care. Without such fundamental support from correct inputs, outputs are unlikely to be truly (or meaningfully) positive. Therefore, consistent re-examination of inputs is required to make sure they uphold an individual’s attainment of good welfare. Full article

Despite the formal protection of many natural areas, the problem of noise pollution poses a serious challenge to the preservation of their ecological integrity and biodiversity. Traffic noise generated by vehicle traffic on public roads disrupts natural biological processes, negatively affecting animals and the quality of the audiosphere. This research aimed to assess the acoustic impact of the public road network crossing the Roztocze National Park (RPN, Poland) and to characterize noise propagation as a factor polluting the environment and disrupting the functioning of natural forest ecosystems. The equivalent sound pressure level (L_Aeq) was measured at different distances from four public roads crossing the park. A terrain analysis was also taken into account to determine the impact of height differences on sound propagation. To enhance the acoustic analysis, recordings of environmental sounds were made, and their components, including both natural and anthropogenic sounds, were identified. It was found that traffic noise dominated natural sounds at distances 250 m from roads. The results obtained indicate the need for an integrated approach to protected area management, including noise monitoring, the implementation of noise protection regulations, and environmental education. Full article

In the era of artificial intelligence, the demand for rapid and efficient data processing is growing, and traditional computing architectures are increasingly struggling to meet these needs. Against this backdrop, memristor devices, capable of mimicking the computational functions of brain neural networks, have emerged as key components in neuromorphic systems. Despite this, memristors still face many challenges in biomimetic functionality and circuit integration. In this context, a starch–glycerol-based hydrogel memristor was developed using starch as the dielectric material. The starch–glycerol–water mixture employed in this study has been widely recognized in literature as a physically cross-linked hydrogel system with a three-dimensional network, and both high water content and mechanical flexibility. This memristor demonstrates a high current switching ratio and stable threshold voltage, showing great potential in mimicking the activity of biological neurons. The device possesses the functionality of auditory neurons, not only achieving artificial spiking neuron discharge but also accomplishing the spatiotemporal summation of input information. In addition, we demonstrate the application capabilities of this artificial auditory neuron in gain modulation and in the synchronization detection of sound signals, further highlighting its potential in neuromorphic engineering applications. These results suggest that starch-based hydrogel memristors offer a promising platform for the construction of bio-inspired auditory neuron circuits and flexible neuromorphic systems. Full article

Humanoid soccer robots operate in dynamic, unpredictable, and often partially observable settings. Effective teamwork, sound decision-making, and real-time collaboration are critical to competitive performance. In this paper, a biologically inspired swarm-intelligence framework for humanoid soccer is proposed, comprising (1) a low-overhead communication User Datagram Protocol (UDP) optimized for minimal bandwidth and graceful degradation under packet loss; (2) an Ant Colony Optimization (ACO)-based decentralized role allocation mechanism that dynamically assigns attackers, midfielders, and defenders based on real-time pheromone trails and local fitness metrics; (3) a Reynolds’ flocking-based formation control scheme, modulated by role-specific weighting to ensure fluid transitions between offensive and defensive formations; and (4) an adaptive behavior layer integrating lightweight reinforcement signals and proactive failure-recovery strategies to maintain cohesion under robot dropouts. Simulations demonstrate a 25–40% increase in goals scored and an 8–10% boost in average ball possession compared to centralized baselines. Full article

The use of insect sex pheromones as an alternative technology for pest control in agriculture and forestry offers a promising solution. The development of a novel technology for the biological production of pheromones through yeast fermentation significantly lowers production costs, enabling the adoption of sustainable pest control practices in field crops, a strategy previously reserved for high-value crops. Over three years of monitoring and mating disruption trials in Greek cotton fields, focusing on the cotton bollworm Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae), it was confirmed that yeast-derived pheromones exhibit equal efficacy compared to their chemically synthesized counterparts. For the mating disruption of H. armigera, a biodegradable, flowable, and paraffin-based matrix was developed. The matrix adheres to plants, protects the labile pheromone molecules (Z)-11-hexadecenal and (Z)-9-hexadecenal, and controls their gradual release into the environment. These biodegradable polymer blobs act as non-retrievable dispensers and can be deployed manually or via unmanned aerial vehicles (UAVs), ensuring efficient and accurate application. This precise, time-efficient, and economically sound technology aligns with European Commission initiatives, such as the Green Deal’s Farm to Fork Strategy and the Biodiversity Strategy, contributing to food sustainability while respecting biodiversity. Full article

Flexible wearable electronics face critical challenges in achieving reliable physiological monitoring, particularly due to the trade-off between sensitivity and durability in flexible electrodes, compounded by mechanical modulus mismatch with biological tissues. To address these limitations, we develop an anti-freezing ionic hydrogel through a chitosan/acrylamide/LiCl system engineered via the solution post-treatment strategy. The optimized hydrogel exhibits exceptional ionic conductivity (24.1 mS/cm at 25 °C) and excellent cryogenic tolerance. Leveraging these attributes, we construct a gel-based triboelectric nanogenerator (G-TENG) that demonstrates ultrahigh sensitivity (1.56 V/kPa) under low pressure. The device enables the precise capture of subtle vibrations at a frequency of 1088 Hz with a signal-to-noise ratio of 16.27 dB and demonstrates operational stability (>16,000 cycles), successfully differentiating complex physiological activities including swallowing, coughing, and phonation. Through machine learning-assisted analysis, the system achieves 96.56% recognition accuracy for five words and demonstrates good signal recognition ability in different ambient sound scenarios. This work provides a paradigm for designing environmentally adaptive wearable sensors through interfacial modulus engineering and ion transport optimization. Full article

Urban green spaces are critical yet understudied areas where anthropogenic and biological sounds interact. This study investigates how vegetation structure mediates the acoustic partitioning of urban soundscapes and informs sustainable forestry management. Through the principal component analysis (PCA) of 1–11 kHz frequency bands, we identified anthropogenic sounds (1–2 kHz) and biological sounds (2–11 kHz). Within bio-acoustic communities, PCA further revealed three positively correlated sub-clusters (2–4 kHz, 5–6 kHz, and 6–11 kHz), suggesting cooperative niche partitioning among avian, amphibian, and insect vocalizations. Linear mixed models highlighted vegetation’s dual role: mature tree stands (explaining 19.9% variance) and complex vertical structures (leaf-height diversity: 12.2%) significantly enhanced biological soundscapes (R²m = 0.43) while suppressing anthropogenic noise through canopy stratification (32.3% variance explained). Based on our findings, we suggest that an acoustic data-driven framework—comprising (1) the preservation of mature stands with multi-layered canopies to enhance bioacoustic resilience, (2) strategic planting of mid-story vegetation to disrupt low-frequency noise propagation, and (3) real-time soundscape monitoring to balance biophony and anthropophony allocation—can contribute to promoting sustainable urban forestry management. Full article

Bowel sounds, produced by intestinal peristalsis, are essential for diagnosing gastrointestinal disorders. However, acquiring and analyzing bowel sounds is challenging due to their unpredictable nature and individual variability. Biological tissues can affect bowel sounds during propagation, resulting in varying degrees of signal attenuation between the sound source and the transducer. This study aims to develop a numerical model of bowel sound propagation in the abdominal cavity, focusing on the impact of different biological layers on signal attenuation. Validation of the model demonstrated strong consistency between simulated and actual bowel sound signals, confirming the model’s accuracy and reliability. The model accounted for adipose tissue thickness, ranging from 5 to 20 mm across individuals, while muscle and skin thicknesses remained constant. Results indicated that signal attenuation increases with both the propagation distance and adipose tissue thickness. These findings provide insights into how tissue layers influence bowel sound propagation, offering a theoretical foundation for developing personalized and precise monitoring devices. Full article