Search Results (527)

Fe³⁺-incorporated hydrogels are particularly valuable for wearable devices due to their tunable mechanical properties and ionic conductivity. However, conventional immersion-based fabrication fundamentally limits hydrogel performance because of heterogeneous ion distribution, ionic leaching, and scalability limitations. To overcome these challenges, we report a novel one-pot strategy where controlled amounts of Fe³⁺ are directly added to polyacrylamide-sodium acrylate (PAM-SA) precursor solutions, ensuring homogeneous ion distribution. Combining this with Photoinduced Electron/Energy Transfer Reversible Addition–Fragmentation Chain Transfer (PET-RAFT) polymerization enables efficient hydrogel fabrication under open-vessel conditions, improving its scalability. Fe³⁺ concentration achieves unprecedented modulation of mechanical properties: Young’s modulus (10 to 150 kPa), toughness (0.26 to 2.3 MJ/m³), and strain at break (800% to 2500%). The hydrogels also exhibit excellent compressibility (90% strain recovery), energy dissipation (>90% dissipation efficiency at optimal Fe³⁺ levels), and universal adhesion to diverse surfaces (plastic, metal, PTFE, and cardboard). Finally, these Fe³⁺-incorporated hydrogels demonstrated high effectiveness as strain sensors for monitoring finger/elbow movements, with gauge factors dependent on composition. This work provides a scalable, oxygen-tolerant route to tunable hydrogels for advanced wearable devices. Full article

The recent discovery of TIGR-Tas (Tandem Interspaced Guide RNA-Targeting Systems) marks a major advance in the field of genome editing, introducing a new class of compact, programmable DNA-targeting systems that function independently of traditional CRISPR-Cas pathways. TIGR-Tas effectors use a novel dual-spacer guide RNA (tigRNA) to recognize both strands of target DNA without requiring a protospacer adjacent motif (PAM). These Tas proteins introduce double-stranded DNA cuts with characteristic 8-nucleotide 3′ overhangs and are significantly smaller than Cas9, offering delivery advantages for in vivo editing. Structural analyses reveal homology to box C/D snoRNP proteins, suggesting a previously unrecognized evolutionary lineage of RNA-guided nucleases. This review positions TIGR-Tas at the forefront of a new wave of RNA-programmable genome-editing technologies. In parallel, I provide comparative insight into the diverse and increasingly modular CRISPR-Cas systems, including Cas9, Cas12, Cas13, and emerging effectors like Cas3, Cas10, CasΦ, and Cas14. While the CRISPR-Cas universe has revolutionized molecular biology, TIGR-Tas systems open a complementary and potentially more versatile path for programmable genome manipulation. I discuss mechanistic distinctions, evolutionary implications, and potential applications in human cells, synthetic biology, and therapeutic genome engineering. 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

Growing concern over anthropogenic underwater noise, highlighted by initiatives like the Marine Strategy Framework Directive (MSFD) and its Technical Group on Underwater Noise (TG Noise), emphasizes regions like the Western Black Sea, where increasing activities threaten marine habitats. This region is experiencing rapid growth in maritime traffic and resource exploitation, which is intensifying concerns over the noise impacts on its unique marine habitats. While machine learning offers promising solutions, a research gap persists in comprehensively evaluating diverse ML models within an integrated framework for complex underwater acoustic data, particularly concerning real-world data limitations like class imbalance. This paper addresses this by presenting a multi-faceted framework using passive acoustic monitoring (PAM) data from fixed locations (50–100 m depth). Acoustic data are processed using advanced signal processing (broadband Sound Pressure Level (SPL), Power Spectral Density (PSD)) for feature extraction (Mel-spectrograms for deep learning; PSD statistical moments for classical/unsupervised ML). The framework evaluates Convolutional Neural Networks (CNNs), Random Forest, and Support Vector Machines (SVMs) for noise event classification, alongside Gaussian Mixture Models (GMMs) for anomaly detection. Our results demonstrate that the CNN achieved the highest classification accuracy of 0.9359, significantly outperforming Random Forest (0.8494) and SVM (0.8397) on the test dataset. These findings emphasize the capability of deep learning in automatically extracting discriminative features, highlighting its potential for enhanced automated underwater acoustic monitoring. Full article

Accelerometry-based physical activity monitors (PAMs) are a useful tool to collect objective measurements of physical activity and movement. Recently, there has been an increased utilization of PAMs in companion animal chronic pain research. However, a general lack of understanding of PAMs contributes to challenges and misconceptions around the interpretation and utility of these data. Commercially available devices differ in how they acquire, process, report, and, in some cases, interpret data. Furthermore, various factors relating to the subject, such as age, body condition, and species, clearly influence PAM data, and on top of this, understanding the biological meaning of PAM data is in its relative infancy. This review examines the principles of PAM technology and the technical and biological considerations when applying PAMs to companion animal chronic pain research, in particular osteoarthritis pain research. It also provides an overview of applications of these devices in veterinary chronic pain research thus far, and the potential of these devices in future studies. Full article

Accurate identification of non-food crops underpins food security by clarifying land-use dynamics, promoting sustainable farming, and guiding efficient resource allocation. Proper identification and management maintain the balance between food and non-food cropping, a prerequisite for ecological sustainability and a healthy agricultural economy. Distinguishing large-scale non-food crops—such as oilseed rape, tea, and cotton—remains challenging because their canopy reflectance spectra are similar. This study proposes a novel phenology-aware Vision Transformer Model (PVM) for accurate, large-scale non-food crop classification. PVM incorporates a Phenology-Aware Module (PAM) that fuses multi-source remote-sensing time series with crop-growth calendars. The study area is Hunan Province, China. We collected Sentinel-1 SAR and Sentinel-2 optical imagery (2021–2022) and corresponding ground-truth samples of non-food crops. The model uses a Vision Transformer (ViT) backbone integrated with PAM. PAM dynamically adjusts temporal attention using encoded phenological cues, enabling the network to focus on key growth stages. A parallel Multi-Task Attention Fusion (MTAF) mechanism adaptively combines Sentinel-1 and Sentinel-2 time-series data. The fusion exploits sensor complementarity and mitigates cloud-induced data gaps. The fused spatiotemporal features feed a Transformer-based decoder that performs multi-class semantic segmentation. On the Hunan dataset, PVM achieved an F1-score of 74.84% and an IoU of 61.38%, outperforming MTAF-TST and 2D-U-Net + CLSTM baselines. Cross-regional validation on the Canadian Cropland Dataset confirmed the model’s generalizability, with an F1-score of 71.93% and an IoU of 55.94%. Ablation experiments verified the contribution of each module. Adding PAM raised IoU by 8.3%, whereas including MTAF improved recall by 8.91%. Overall, PVM effectively integrates phenological knowledge with multi-source imagery, delivering accurate and scalable non-food crop classification. Full article

Phosphorus Adsorption Media (PAM) is an emerging technology used to remove phosphorus from water and has the advantage of minimal operation and maintenance support when compared to biological and chemical treatments. Although the capacity of PAM has been researched, the understanding of important design parameters for PAM is lacking. Therefore, this study focused on determining critical design parameters for PAM, such as hydraulic loading, Empty Bed Contact Time (EBCT), and its impact on the media’s capacity. In addition, the regeneration potential of PAM and the mathematical model for predicting the exhaustion of PAM are discussed to provide a practice tool for designing PAM. The results indicate that hydraulic loadings do not show a strong effect on PAM performance, as there are no significant differences between hydraulic loadings of 0.05, 0.12, and 0.22 mL/min/cm². This study also showed that the higher EBCT (190 min) has higher removal rates than the lower EBCT (60 and 90 min). This indicated that EBCT is a critical design parameter for PAM. Laboratory studies demonstrating the regeneration of exhausted media by washing with a caustic solution have been conducted, and a qualitative study showed that exhausted media can be used in hydroponics. Batch testing showed that over 99% of the sorbed phosphorus was eliminated after six cycles of the regeneration process. Full article

Pneumatic artificial muscles (PAMs) consist of an elastomeric bladder wrapped in a Kevlar braid. When inflated, PAMs expand radially and contract axially, producing large axial forces. PAMs are often utilized for their high specific work and specific power, as well as their ability to produce large axial displacements. Although the axial behavior of PAMs is well studied, the radial behavior has remained underutilized and is poorly understood. Modeling was performed using a force balance approach to capture the effects that bladder strain and applied axial load have on the anchoring force. Radial expansion testing was performed to validate the model. Force due to anchoring was recorded using force transducers attached to sections of aluminum pipe using an MTS servo-hydraulic testing machine. Data from the test were compared to the predicted anchoring force. Radial expansion in large-diameter (over 50.8 mm) PAMs was then used in worm-like robots to create anchoring forces that allow for a peristaltic wave, which creates locomotion through acrylic pipes. By radially expanding, the PAM presses itself into the pipe, creating an anchor point. The previously anchored PAM then deflates, which propels the robot forward. Modeling of the radial expansion forces and anchoring was necessary to determine the pressurization required for proper anchoring before slipping occurs due to the combined robot and payload weight. Full article

Background/Objectives: Preventive health behaviors are key to disease prevention and health system sustainability; however, population-level factors remain understudied in multilingual regions. South Tyrol, an autonomous multilingual province in Northern Italy, provides a unique setting to examine how sociodemographic and linguistic factors shape preventive behaviors. Methods: A stratified, population-representative survey of 2090 adults (aged ≥18 years) was conducted in South Tyrol in 2024. Preventive behavior was assessed using the validated 16-item Good Health Practices Scale (GHP-16). Key predictors included age, sex, education, living situation, language group, employment in the health/social sector, health literacy (HLS-EU-Q16), patient activation (PAM-10), and the mistrust of professional health information. Weighted statistics and multivariable linear regression were used to identify associations. Results: The GHP-16 scores varied significantly across sociodemographic and psychosocial strata. Female sex, older age, higher education, higher patient activation, and sufficient health literacy were independently associated with greater engagement in preventive behaviors. Patient activation showed the strongest graded effect (β = 1.739). The mistrust of health professionals was inversely associated with behavior (β = –0.050, 95% CI: –0.090 to –0.009). Italian speakers reported higher GHP-16 scores than German speakers (β = 0.377), even after adjusting for covariates. Item-level analysis revealed small but consistent differences, particularly in information-seeking and vaccination behavior. Conclusions: Preventive behaviors in South Tyrol are shaped by demographic, psychosocial, and linguistic factors. Patient activation and health literacy are key modifiable predictors, whereas language group differences suggest structural and trust-related disparities that require tailored public health strategies in multilingual settings. Full article

Polymer brushes (PBs) are transformative surface-modifying nanostructures, yet their synthesis via controlled methods like copper-mediated surface-initiated atom-transfer radical polymerization (Cu⁰-SI-ATRP) faces reproducibility challenges due to a lack of understanding of parameter interdependencies. This study systematically evaluates the Cu⁰-SI-ATRP process for polyacrylamide brushes (PAM-PBs), aiming to clarify key parameters that influence the synthesis process. This evaluation followed a step-by-step characterization that tracked molecular changes through infrared spectroscopy (IR) and surface development by contact angle (CA) through two different mixing methods: ultrasonic mixing and process simplification (Method A) and following literature-based parameters (Method B). Both methods, consisting of surface activation, 3-aminopropyltriethoxysilane (APTES) deposition, bromoisobutyryl bromide (BiBB) anchoring, and polymerization, were analyzed by varying parameters like concentration, temperature, and time. Results showed ultrasonication during surface activation enhanced siloxane (1139→1115 cm⁻¹) and amine (1531 cm⁻¹) group availability while reducing APTES concentration to 1 Vol% without drying sufficed for BiBB anchoring. BiBB exhibited insensitivity to concentration but benefited from premixing, evidenced by sharp C–Br (~1170 cm⁻¹) and methyl (3000–2800 cm⁻¹) bands. Additionally, it was observed that PAM-PBs improved with Method A, which had reduced variance in polymer fingerprint regions compared to Method B. Adding to the above, CA measurements gave complementary step-by-step information along the modifications of the surface, revealing distinct wettability behaviors between bulk PAM and synthesized PAM-PBs (from 51° to 37°). As such, this work identifies key parameter influence (e.g., mixing, BiBB concentration), simplifies steps (drying omission, lower APTES concentration), and demonstrates a step-by-step, systematic parameter decoupling that reduces variability. In essence, this detailed parameter analysis addresses the PAM-PBs synthesis process with better reproducibility than the previously reported synthesis method and achieves the identification of characteristic behaviors across the step-by-step process without the imperative need for higher-cost characterizations. Full article

Recent studies have indicated that microplastics (MPs) may accumulate in the human body, potentially posing health risks. This preliminary study aimed to investigate the effect of a food supplement (FS: 0.8 g of chitosan derived from Procambarus clarkii, PCC) on the fecal excretion of MPs (20–500 µm size) following ingestion of a standardized meal (SM). Ten healthy volunteers (non-smokers, non-drinkers, non-drug users) participated in a two-phase, crossover design conducted one week apart. In both phases, participants consumed an SM after overnight fasting, and fecal samples were collected the following morning (7–10 am). Phase 1 served as baseline (no PCC), while in Phase 2, PCC was administered immediately before the SM. Sixteen types of MPs were analyzed. A modest increase (5%) in fecal mass was observed after PCC intake. MP counts were 356 in the SM, 656 ± 110 in Phase 1 feces, and 965 ± 165 in Phase 2 feces. The excretion of nine MPs—PA, PAN, PAM, PE, PES, PET, PP, PS, and RA—was enhanced by PCC. These preliminary findings suggest that PCC promotes the fecal elimination of MPs. Further controlled studies are needed to validate these results and assess their potential relevance for dietary interventions. Full article

Treatment with endocrine therapy (ET) in combination with CDK4/6 inhibitors has improved the outcome of patients with hormone receptor (HR)+/HER2- advanced breast cancer (ABC), but most patients eventually experience disease progression. Since the PI3K-AKT-mTOR (PAM), estrogen receptor (ER), and cyclin-dependent kinase (CDK) pathways are interdependent drivers of HR+/HER2- breast cancer (BC), the simultaneous inhibition of these pathways is expected to enhance anti-tumor control. Here we investigated the molecular and cellular effects of gedatolisib, a multi-target kinase inhibitor of the PAM pathway currently being evaluated in Phase 3 clinical trials, combined with fulvestrant and/or palbociclib in BC cell models. We found that the gedatolisib/fulvestrant/palbociclib triplet inhibited BC cell growth significantly more than the single agents or the palbociclib/fulvestrant doublet, both in vitro and vivo. Specifically, the triplet combination counteracted adaptive responses associated with single drug treatment, such as the reactivation of the CDK-RB-E2F pathway after palbociclib treatment, and inhibited multiple cellular functions, such as cell cycle progression, cell survival, protein synthesis, and glucose metabolism. The triplet combination was effective in treatment-naïve BC cell lines as well as in cell lines adapted to palbociclib and/or fulvestrant, regardless of PIK3CA/PTEN genetic alterations. Our findings provide a mechanistic rationale for conducting clinical studies evaluating gedatolisib in combination with CDK4/6 inhibitors and ET in HR+/HER2- ABC. Full article

Underwater wireless communications face significant challenges due to high attenuation, turbulence, and water turbidity. Traditional methods like acoustic and radio frequency (RF) communication suffer from low data rates (<100 kbps), high latency (>1 s), and limited transmission distances (<10 km).Visible Light Communication (VLC) emerges as a promising alternative, offering high-speed data transmission (up to 5 Gbps), low latency (<1 ms), and immunity to electromagnetic interference. This paper provides an in-depth review of underwater VLC, covering fundamental principles, environmental factors (scattering, absorption), and dynamic water properties. We analyze modulation techniques, including adaptive and hybrid schemes (QAM-OFDM achieving 4.92 Gbps over 1.5 m), and demonstrate their superiority over conventional methods. Practical applications—underwater exploration, autonomous vehicle control, and environmental monitoring—are discussed alongside security challenges. Key findings highlight UVLC’s ability to overcome traditional limitations, with experimental results showing 500 Mbps over 150 m using PAM4 modulation. Future research directions include integrating quantum communication and Reconfigurable Intelligent Surfaces (RISs) to further enhance performance, with simulations projecting 40% improved spectral efficiency in turbulent conditions. Full article

In the field of enhanced oil recovery (EOR), particularly for water control in high-temperature reservoirs, there is a critical need for effective in-depth water shutoff and conformance control technologies. Polymer-based in situ-cross-linked gels are extensively employed for enhanced oil recovery (EOR), yet their short gelation time under high-temperature reservoir conditions (e.g., >120 °C) limits effective in-depth water shutoff and conformance control. To address this, we developed a hydrogel system via the in situ cross-linking of polyacrylamide (PAM) with phenolic resin (PR), reinforced by silica sol (SS) nanoparticles. We employed a variety of research methods, including bottle tests, viscosity and rheology measurements, scanning electron microscopy (SEM) scanning, density functional theory (DFT) calculations, differential scanning calorimetry (DSC) measurements, quartz crystal microbalance with dissipation (QCM-D) measurement, contact angle (CA) measurement, injectivity and temporary plugging performance evaluations, etc. The composite gel exhibits an exceptional gelation period of 72 h at 130 °C, surpassing conventional systems by more than 4.5 times in terms of duration. The gelation rate remains almost unchanged with the introduction of SS, due to the highly pre-dispersed silica nanoparticles that provide exceptional colloidal stability and the system’s pH changing slightly throughout the gelation process. DFT and SEM results reveal that synergistic interactions between organic (PAM-PR networks) and inorganic (SS) components create a stacked hybrid network, enhancing both mechanical strength and thermal stability. A core flooding experiment demonstrates that the gel system achieves 92.4% plugging efficiency. The tailored nanocomposite allows for the precise management of gelation kinetics and microstructure formation, effectively addressing water control and enhancing the plugging effect in high-temperature reservoirs. These findings advance the mechanistic understanding of organic–inorganic hybrid gel systems and provide a framework for developing next-generation EOR technologies under extreme reservoir conditions. Full article

Anti-washout admixtures (AWAs) are a unique component of underwater non-dispersive concrete (UNDC), which gives the concrete the ability to remain undispersed in water. On some special occasions, freshly mixed underwater non-dispersive concrete is exposed to the erosion of moving water, and conventional acrylamide-based AWAs are only suitable for static water or the water flow rate is small. In this study, the inorganic component nanosilica (NS) is modified, treated, and copolymerized with the organic components acrylamide (AM) and acrylic acid (AA) to form an inorganic–organic hybrid polymer with a hyperbranched structure, which changes the linear structure of the original polyacrylamide molecule, and we optimize the synthesis process. The polymers are characterized at the microscopic level and their compatibility with polycarboxylic acid water-reducing agents (SP) is investigated. In addition, the polymers are compared and evaluated with commonly used PAM in terms of their working performance. The experimental results indicated that under specific process conditions, polymers endow cement mortar with good resistance to water erosion. At the same time, the polymers’ three-dimensional network structure is prominent, with good compatibility with SP and better anti-dispersity. The microstructure of the cement paste with added polymers is dense and flat, but its flowability and setting time are slightly worse. This study provides a new development direction for the development of AWAs under a dynamic water environment, which has specific engineering significance. Full article