Search Results (1,625)

Accurate prediction of the rocking and sliding response of free-standing rigid blocks under seismic excitation remains challenging, particularly in regimes where rocking and sliding are strongly coupled and motion mode transitions occur. This study presents a modified semi-analytical framework and an optimized Finite Element Method (FEM) approach to investigate the nonlinear dynamics of rigid rectangular blocks subjected to initial angular displacements, assuming Coulomb friction and near-inelastic impacts. The proposed semi-analytical formulation explicitly captures the coupling between rocking and sliding motions, enabling systematic identification of rest, rocking, sliding, rocking–sliding, and free-flight response modes. Benchmark comparisons with Veeraraghavan’s classical model show overall agreement in limiting cases but reveal notable differences in intermediate regimes, where motion mode transitions are highly sensitive to friction coefficient and slenderness ratio. These discrepancies arise from the ability of the present formulation to resolve transitional rocking–sliding behavior that is not fully represented in uncoupled or limiting-case assumptions. Complementary FEM simulations employing both rigid and deformable body representations further elucidate the role of contact modeling and energy dissipation. While rigid-body FEM models offer computational efficiency, they exhibit localized penetration and residual bouncing due to contact enforcement limitations. In contrast, deformable FEM models more closely approximate near-inelastic collision behavior and dissipate impact energy more effectively, albeit at higher computational cost. The combined semi-analytical and FEM results provide a robust framework for interpreting motion mode transitions, quantifying contact and penetration effects, and defining the applicability limits of simplified rigid-body models. These findings offer practical guidance for selecting appropriate modeling strategies for seismic response assessment of free-standing rigid blocks. Full article

The flexible positioning platform is a critical structural component in the ultra-high acceleration macro–micro motion platform, enabling precise positioning across multiple scales. However, under high-frequency start–stop cycles and prolonged multi-condition operation, it is prone to fatigue damage induced by random vibrations, which poses a threat to system reliability. This study proposes a method for evaluating and optimizing the platform’s performance under random vibration based on power spectral density (PSD) analysis. In accordance with the IEC 60068-2-64 standard, representative load spectra from Tables A.8 and A.6 were selected as excitation inputs. Frequency-domain analyses of stress, strain, and displacement were conducted using ANSYS Workbench 2022R1 in conjunction with the nCode platform, incorporating the Gaussian three-sigma probability interval. The results reveal that stress and deformation are highly concentrated in the hinge region, indicating a structural vulnerability. Fatigue life predictions were carried out using the Dirlik method and Miner’s linear damage rule under various PSD loading conditions. The findings demonstrate that hinge stiffness is a key factor influencing vibration resistance and service life. This research provides theoretical support for the design optimization of flexible structures operating in complex random vibration environments. Full article

To address challenges such as small target size, high density, severe occlusion, complex background interference, and edge device computational constraints, a lightweight model, GAFNet, is proposed based on YOLO11n, optimized for rice pest detection in field environments. To improve feature perception, we propose the Global Attention Fusion and Spatial Pyramid Pooling (GAM-SPP) module, which captures global context and aggregates multi-scale features. Building on this, we introduce the C3-Efficient Feature Selection Attention (C3-EFSA) module, which refines feature representation by combining depthwise separable convolutions (DWConv) with lightweight channel attention to enhance background discrimination. The model’s detection head, Enhanced Ghost Detect (EGDetect), integrates Enhanced Ghost Convolution (EGConv), Squeeze-and-Excitation (SE), and Sigmoid-Weighted Linear Unit (SiLU) activation, which reduces redundancy. Additionally, we propose the Focal-Enhanced Complete-IoU (FECIoU) loss function, incorporating stability and hard-sample weighting for improved localization. Compared to YOLO11n, GAFNet improves Precision, Recall, and mean Average Precision (mAP) by 3.5%, 4.2%, and 1.6%, respectively, while reducing parameters and computation by 5% and 21%. GAFNet can deploy on edge devices, providing farmers with instant pest alerts. Further, GAFNet is evaluated on the AgroPest-12 dataset, demonstrating enhanced generalization and robustness across diverse pest detection scenarios. Overall, GAFNet provides an efficient, reliable, and sustainable solution for early pest detection, precision pesticide application, and eco-friendly pest control, advancing the future of smart agriculture. Full article

Highly accurate quantitative detection of heavy metals is crucial for preventing environmental pollution and safeguarding public health. To address the demand for sensitive and specific detection of Cu²⁺ ions, we have developed carbon dots using a simple hydrothermal process. The synthesized carbon dots are highly stable in aqueous media, environmentally friendly, and exhibit strong blue photoluminescence at 440 nm when excited at 352 nm, with a quantum yield of 5.73%. Additionally, the size distribution of the carbon dots ranges from 2.0 to 20 nm, and they feature excitation-dependent emission. They retain consistent optical properties across a wide pH range and under high ionic strength. The photoluminescent probes are selectively quenched by Cu²⁺ ions, with no interference observed from other metal cations such as Ag⁺, Ca²⁺, Cr³⁺, Fe²⁺, Fe³⁺, Hg²⁺, K⁺, Mg²⁺, Sn²⁺, Pb²⁺, Sr²⁺, and Zn²⁺. The emission of carbon dots exhibits a strong linear correlation with Cu²⁺ concentration in the range of 0–14 μM via a static quenching mechanism, with a detection limit (LOD) of 4.77 μM in water. The proposed carbon dot sensor is low cost and has been successfully tested for detecting Cu²⁺ ions in general water samples collected from rivers in Taiwan. Full article

Background/Objectives: Glucose Transporter 1 Deficiency Syndrome (GLUT1-DS) is a neurodevelopmental disorder caused by mutations in the gene encoding glucose transporter 1 (GLUT1), which leads to impaired glucose transport into the brain and is characterized by drug-resistant epilepsy. Limited glucose supply disrupts neuronal and astrocytic energy homeostasis, but how hypometabolism translates into network hyperexcitability remains poorly understood. Here, we used induced pluripotent stem cells (iPSCs)-derived brain organoids to examine how reduced metabolic substrate availability shapes epileptiform dynamics in human neuronal circuits from GLUT1-DS. Methods: Brain organoids were generated from a healthy donor or a GLUT1-DS patient and interfaced with multielectrode arrays (MEA) for recording of neuronal activity. A unified Python (v3.10)-based analytical pipeline was developed to quantify spikes, bursts, and power spectral density (PSD) across frequency bands of neuronal activity. Organoids were challenged with reduced glucose, pentylenetetrazol (PTZ), potassium chloride (KCl), and tetrodotoxin (TTX) to assess metabolic and pharmacological modulation of excitability. Results: GLUT1-DS organoids exhibited elevated baseline hyperexcitability compared to healthy control, characterized by increased spike rates, prolonged bursts, increased spikes per burst, and elevated PSD. Reduced glucose availability further amplified these features selectively in GLUT1-DS. Conclusions: Human brain organoids reproduce the pathological coupling between hypometabolism and hyperexcitability in GLUT1-DS. Our platform provides a mechanistic model and quantification tool for evaluating metabolic and anti-epileptic therapeutic strategies. Full article

Bladder cancer (BC) represents a major global health issue with high recurrence and significant mortality rates in cases of advanced disease. Currently, the development of molecular profiling, liquid biopsy technologies, and artificial intelligence (AI) software has resulted in unprecedented opportunities to improve diagnosis, prognostic assessment, and treatment selection. Recent multicenter studies have identified emerging metabolomic, proteomic, and genomic biomarkers with high sensitivity and specificity that may help replace or complement invasive approaches. AI-driven models that combine multi-omics datasets with radiomics and clinical parameters have demonstrated improved accuracy for predicting both therapeutic response and long-term outcomes, compared to standard approaches for risk stratification. Additionally, the incremental clinical usefulness of liquid biopsy platforms has been demonstrated for the monitoring of non-muscle-invasive bladder cancer and minimal disease detection. As these innovations converge, they herald the advent of a new era of personalized management of urothelial carcinoma; however, broad-based clinical implementation will require large-scale validation, standardization, regulatory harmonization, and economic analyses. Background: Bladder cancer continues to be a global health problem, particularly in the advanced disease setting where treatment options are limited, and mortality remains high. The exciting advances in precision medicine, including breakthrough molecular profiling techniques, liquid biopsy, and opportunities to apply AI to interpret these molecular data, hold unprecedented promise in improving the accuracy of diagnosis, prognostic stratification, and therapeutic decision-making. Full article

Background: The rostral ventromedial medulla (RVM) is a central hub of the descending pain modulatory system, yet the inhibitory circuits that regulate its activity during neuropathic pain remain poorly defined. The zona incerta (ZI), a predominantly GABAergic nucleus in the subthalamic region, has been implicated in nociceptive modulation, but its functional connection to the RVM has not been established. Methods: A chronic constriction injury (CCI) model was used to induce neuropathic pain. Neuronal activation and circuit connectivity were examined using anatomical tracing and activity mapping. Optogenetic and chemogenetic approaches were employed to selectively manipulate ZI-derived GABAergic projections to the RVM, and mechanical sensitivity was assessed using behavioral assays. Results: CCI selectively activated ZI neurons on the ipsilateral side of nerve injury (p = 0.0452), which projected to the ipsilateral RVM. Optogenetic activation of ZI-derived terminals in the RVM significantly alleviated CCI-induced mechanical allodynia (p = 0.0038), whereas optogenetic inhibition exacerbated pain behaviors (p = 0.0183). Consistently, chemogenetic excitation of ZI–RVM neurons attenuated hypersensitivity (p < 0.0001), while chemogenetic silencing had the opposite effect (p = 0.0015). Conclusions: These findings reveal a novel diencephalic-to-brainstem inhibitory pathway that exerts dynamic control over RVM-mediated descending modulation of neuropathic pain. Full article

Three Schiff base fluorescent probes 3a–3c with N-heterocyclic structure were designed and synthesized by using the reaction of 4-diethylaminosalicylaldehyde with different N-heterocyclic amines, such as 2-aminobenzimidazole, 2-aminobenzothiazole, and 2-amino-6-methylpyridine. Compound 3a exhibited excellent selectivity towards Hg²⁺, with a detection limit of 3.21 × 10⁻⁷ M and a response time of only 30 s. It could be used as a fluorescent probe for detecting Hg²⁺. Meanwhile, compounds 3b and 3c exhibited excellent selectivity towards Zn²⁺, with detection limits of 1.61 × 10⁻⁷ M and 2.03 × 10⁻⁷ M, respectively, and response times of only 30 s. They could serve as fluorescent probes for detecting Zn²⁺. Using probe 3a for Hg²⁺ as an example, the detecting mechanism was further elucidated through ¹H NMR, ESI-MS testing, and DFT calculation analysis. For compound 3a, the coordination stoichiometry between compound 3a and Hg²⁺ was verified to be 1:1 through a Job’s plot. After coordination with Hg²⁺, the molecular rigidity of compound 3a was enhanced, which inhibited the non-radiative decay process and led to the closure of the excited-state intramolecular proton transfer (ESIPT) effect. At the same time, the fluorescence intensity was significantly increased through the chelation-enhanced fluorescence (CHEF) mechanism, which was confirmed by density functional theory (DFT) calculations. In addition, compounds 3a–3c were successfully applied in practical water samples and test strips for the detection of Hg²⁺/Zn²⁺. Full article

Symmetry and asymmetry jointly govern the dynamics and surface integrity of thin-wall AA7075 end milling. In this work, a symmetry-aware simulation and experimental framework is developed to connect process parameters with milling forces, dynamic response, surface quality, and through-thickness residual stress. A mechanistic milling-force model is first established for multi-tooth end milling, where the periodically repeated tooth-order excitation provides a nominally symmetric load pattern along the tool path. The predicted forces are then used as input for finite-element modal and harmonic-response analysis of a thin-walled component, revealing how symmetric and anti-symmetric mode shapes interact with the tooth-order excitation to generate locally amplified, asymmetric vibration of the compliant wall. Orthogonal and single-factor milling experiments on AA7075 thin-wall specimens are performed to calibrate and validate the force model, and to quantify the influence of feed per tooth, axial depth of cut, spindle speed, and radial width of cut on deformation, surface roughness, and geometric accuracy. Finally, a thermo-mechanically coupled finite-element model is employed to evaluate the residual-stress field, showing a characteristic pattern in which an initially symmetric thermal–mechanical loading produces depth-wise symmetry breaking between tensile surface layers and compressive subsurface zones. The proposed symmetry-aware framework, which combines milling-force theory, finite-element simulation, and systematic experiments, provides practical guidance for selecting parameter windows that suppress vibration, control residual stress, and improve the machining quality of thin-wall AA7075 components. Full article

Background: Rhythmic sensory stimulation, including structured musical interventions, has gained renewed interest as a non-pharmacological strategy that may modulate cortical excitability and network stability in focal epilepsy. Although several small studies have reported changes in seizure frequency or epileptiform activity during rhythmic or music exposure, the underlying mechanisms and translational relevance remain insufficiently synthesized. Objective: This narrative review summarizes clinical evidence on music-based and rhythmic sensory interventions in focal epilepsy, outlines plausible neurophysiological mechanisms related to neural entrainment and large-scale network regulation, and discusses emerging opportunities for digital delivery of rhythmic protocols in everyday self-management. Methods: A structured search of recent clinical, neurophysiological, and rehabilitation literature was performed with emphasis on rhythmic auditory, tactile, and multimodal stimulation in epilepsy or related conditions. Additional theoretical and translational sources addressing oscillatory dynamics, entrainment, timing networks, and patient-centered digital tools were reviewed to establish a mechanistic framework. Results: Existing studies—although limited by small cohorts and heterogeneous methodology—suggest that certain rhythmic structures, including specific musical compositions, may transiently modulate cortical synchronization, reduce epileptiform discharges, or alleviate seizure-related symptoms in selected patients. Evidence from neurologic music therapy and rhythmic stimulation in other neurological disorders further supports the concept that externally delivered rhythms can influence timing networks, attentional control, and interhemispheric coordination. Advances in mobile health platforms enable structured rhythmic exercises to be delivered and monitored in real-world settings. Conclusions: Music-based and rhythmic sensory interventions represent a promising but underexplored adjunctive approach for focal epilepsy. Their effectiveness likely depends on individual network characteristics and on the structure of the applied rhythm. Digital integration may enhance personalization and adherence. Rigorous clinical trials and mechanistic studies are required to define optimal parameters, identify responders, and clarify the role of rhythmic stimulation within modern epilepsy care. Full article

A heavy-duty vibrating screen with excitation sources is a mining vibrating machine synchronized by two eccentric rotors, exhibiting typical coupled dynamic behavior. Aiming at the coupling dynamic behavior of dual excitation sources based on the nonlinear vibration of a heavy-duty mining screen, theoretical research and experimental analysis of coupling synchronization are carried out, and the dynamic reasons for the dual excitation sources to achieve vibration synchronization are discussed. Based on nonlinear vibration theory, electromechanical coupling nonlinear dynamics equations for a dual excitation source vibrating screen are established in this paper, and the coupled dynamics factors of the two eccentric rotors are analyzed. The impact of coupling strength on the equilibrium state of the nonlinear vibration system is discussed, and the evolution process of the synchronous motion of the two eccentric rotors is further investigated, revealing the causal relationship by which the dual excitation sources achieve synchronization due to coupled dynamics behavior. The results show that the coupling effect of the multi-exciter is based on the nonlinear vibration of the vibration system, and the motion characteristics and motion mode of the exciter will change, and, finally, a coupled synchronous motion state will be reached. The research results can provide ideas for the mechanical structure design of heavy-duty mining screens excited by multiple excitation sources and can provide a theoretical basis and application reference for the selection of structural parameters of this kind of mining machinery. Full article

Background/Objectives: Boron-dipyrromethene (BODIPY) derivatives are a superior class of fluorophores prized for their exceptional photostability and tunable photophysical properties. While ideal for imaging, their translation to photodynamic therapy (PDT) has been hampered by excitation in the visible range, leading to poor tissue penetration. To overcome this, intense research has focused on developing near-infrared (NIR)-absorbing BODIPY photosensitizers (PS). This review aims to systematically summarize the hierarchical design strategies, from molecular engineering to advanced nanoplatform construction, that underpin the recent progress of NIR-BODIPY PS in therapeutic applications. Methods: We conducted a comprehensive literature review using PubMed, Scopus, and Web of Science databases. The search focused on keywords such as “BODIPY”, “aza-BODIPY”, “near-infrared”, “photodynamic therapy”, “photothermal therapy”, “nanocarriers”, “hypoxia”, “immuno-phototherapy”, and “antibacterial.” This review analyzes key studies describing molecular design, chemical modification strategies (e.g., heavy-atom effect, π-extension), nanoplatform formulation, and therapeutic applications in vitro and in vivo. Results: Our analysis reveals a clear progression in design complexity. At the molecular level, we summarize strategies to enhance selectivity, including active targeting, designing “smart” PS responsive to the tumor microenvironment (TME) (e.g., hypoxia or low pH), and precise subcellular localization (e.g., mitochondria, lysosomes). We then detail the core chemical strategies for achieving NIR absorption and high singlet oxygen yield, including π-extension, the internal heavy-atom effect, and heavy-atom-free mechanisms (e.g., dimerization). The main body of the review categorizes the evolution of advanced theranostic nanoplatforms, including targeted systems, stimuli-responsive ‘smart’ systems, photo-immunotherapy (PIT) platforms inducing immunogenic cell death (ICD), hypoxia-overcoming systems, and synergistic chemo-phototherapy carriers. Finally, we highlight emerging applications beyond oncology, focusing on the use of NIR-BODIPY PS for antibacterial therapy and biofilm eradication. Conclusions: NIR-BODIPY photosensitizers are a highly versatile and powerful class of theranostic agents. The field is rapidly moving from simple molecules to sophisticated, multifunctional nanoplatforms designed to overcome key clinical hurdles like hypoxia, poor selectivity, and drug resistance. While challenges in scalability and clinical translation remain, the rational design strategies and expanding applications, including in infectious diseases, confirm that NIR-BODIPY derivatives will be foundational to the next generation of precision photomedicine. Full article

Transcranial focused ultrasound stimulation (tFUS), an emerging non-invasive neuromodulation technique, has garnered growing attention owing to its high spatial resolution and precise targeting capability for deep brain structures. A body of evidence demonstrates that tFUS can effectively modulate neural activity in specific brain regions, inducing excitatory or inhibitory effects, and it is an important means to reshape neural functions. Ultrasound parameters are crucial in determining the transcranial ultrasound modulation effects. However, there is still controversy over which parameters can regulate neural excitability or inhibition, and there are significant differences in the parameters used in previous studies, which have limited the clinical application of transcranial ultrasound to some extent. Therefore, a systematic clarification of parameter–effect relationships is urgently needed to enable qualitative and quantitative understanding of ultrasound-induced neuromodulation, which is essential for achieving reliable and reproducible outcomes. This paper intends to review the effects of different tFUS parameters and their combinations on the excitability and inhibition of brain neural activities as well as the possible mechanisms. By integrating recent findings from both animal models and human clinical studies, we also discuss critical safety issues related to tFUS, aiming to provide a theoretical basis for future transcranial focused ultrasound modulation treatments for various neurological diseases such as stroke, Parkinson’s disease, dementia, epilepsy, pain disorders, and disorders of consciousness while providing reference value for selecting tFUS treatment regimens. Full article

To address the challenges of system failures and equipment damage caused by excitation inrush currents and overvoltages during no-load energization of high-speed locomotive transformers, a simulation model was developed utilizing PSCAD electromagnetic transient simulation software. This study establishes a no-load switching simulation model for rolling stock transformers within PSCAD, analyzing variations in overvoltage and excitation inrush current amplitudes across different phase angles. Additionally, it compares excitation inrush current amplitudes under varying residual magnetism conditions. A phase-selective control strategy is proposed, integrating the hysteresis characteristics of the transformer core. The model’s accuracy is validated against empirical data obtained from a city train. Employing the Jiles–Atherton hysteresis model, the residual magnetism of the transformer core is quantified. Based on measured data, a relationship curve between switching phase and residual magnetism is fitted, enabling calculation of the optimal closing angle through the phase selection procedure. This approach effectively mitigates overvoltage and excitation inrush current hazards, thereby enhancing the operational safety of the train system. Full article

Aim: To propose a standardized clinical protocol for cone-specific neuromodulation that classifies therapeutic filters for selective stimulation of S-, M-, and L-cones and translates optical and safety parameters into condition-specific frameworks for amblyopia, strabismus, and ADHD. Methods: Previously characterized spectral filters were re-evaluated using published transmittance and cone-excitation data to identify a reduced set of monochromatic and combined options with meaningful cone bias. These were integrated with $\alpha$-opic metrology, international photobiological and flicker standards, and condition-specific neurophysiological evidence to define reproducible ranges for wavelength, corneal illuminance, exposure timing, temporal modulation, and safety verification. Results: The protocol consolidates eleven monochromatic and six combined filters into operational classes mapped onto mechanistic profiles for amblyopia, esotropia, exotropia, vertical deviations, and exploratory ADHD applications. All time frames and applications are presented as methodological anchors rather than efficacy claims. Conclusions: This work provides a structured, safety-anchored framework intended to guide protocol design and comparability in future cone-specific neuromodulation trials; therapeutic benefit must be demonstrated in prospective clinical studies. Full article