Search Results (502)

Real-time fatigue classification on resource-constrained edge devices faces three unresolved computational challenges: just-in-time compilation latency spikes that violate the 50 ms inference budget, statistical moment features insensitive to temporal complexity signatures of fatigue, and binary anomaly outputs insufficient for actionable coaching decisions. A synthetic IMU dataset (9 subjects, 540,000 samples, 6 channels at 100 Hz) was generated as a reproducible computational benchmark, with fatigue signatures calibrated to published biomechanical effect sizes (sample entropy $d=+0.77$; permutation entropy $d=+0.38$). We present Safari (Stochastic Adaptive Fitness-Aware Real-time Inference), an end-to-end computational pipeline integrating: a dual-pathway entropy triplet (SampEn, PermEn, SpEn) replacing statistical moments; 16 pre-compiled polyhedral anchor kernels eliminating JIT latency; $O\left({(\Delta W)}^2\right)$-bounded runtime interpolation; subject-specific MaxEnt free-energy anomaly scoring; and a Banister fitness–fatigue adaptive threshold. Safari achieves AUC-ROC = 0.9820 (Monte Carlo 95% CI: 0.9726–0.9886), F1 = 0.8835, four-state accuracy = 83.3%, and worst-case latency = 7.2 ms on a Raspberry Pi 4. Entropy features achieve 1.55× higher discriminability than statistical moments. Safari is a computational framework for real-time fatigue monitoring, contributing a reproducible algorithmic benchmark for edge AI in movement analysis, with real-athlete validation as the recommended next step. Full article

Melanin pigments protect human tissues from ultraviolet and visible radiation, yet their phototoxic potential increases with oxidative degradation. This computational study investigates how the oxidation state influences the first excited states of eu- and pheomelanin using molecular models of varying complexity (monomers to tetramers, both covalently and non-covalently bonded). First, vertical and adiabatic electronic transitions were computed, and supramolecular interactions were characterized with the ETS-NOCV method. In eumelanin, oxidation drastically lowers the first triplet-state (T₁) energies (from above 230 kJ/mol) to levels comparable to retinal carotenoids (≤66 kJ/mol), emphasizing its role in triplet quenching rather than singlet oxygen generation. Pheomelanin showed greater heterogeneity in the values of the first triplet state, staying mostly above the eumelanin T₁ energies. However, selected pheomelanin structures also exhibited relatively low triplet energies, particularly oxidized benzothiazole (BZox) and trichochromes, and although their T₁ energetics remained higher than those calculated for oxidized eumelanin, they were still sufficiently low to suggest a potential ability to quench singlet oxygen. Furthermore, supramolecular analysis reveals that eumelanin aggregates are moderately stabilized by both π-π stacking and hydrogen bonding, whereas pheomelanin aggregates are dominated by dense hydrogen-bond networks. Full article

In this work, we report an example of tuning the photophysical properties of a polypyridine ruthenium(II) complex via the coordination of a second cation. A new ruthenium(II) complex contains a thiacrown-ether fragment that allows selective binding of additional metal cations (Ba²⁺, Cd²⁺, Pb²⁺), leading to pronounced changes in the optical and electronic properties of the bimetallic system. Spectroscopic and electrochemical studies reveal that the monoruthenium precursor displays dual excitation pathways involving either intraligand charge transfer (ILCT) or triplet metal-to-ligand charge transfer (³MLCT) excited states. Upon coordination of a second metal ion, the ILCT channel is suppressed, and only the ³MLCT state remains emissive, resulting in a significant increase in phosphorescence quantum yields (up to 22.6% in degassed solutions) for the bimetallic derivative. Time-resolved emission studies confirm the conversion from biexponential to monoexponential luminescence decay upon complexation. Electrochemical analysis and density functional theory (DFT) calculations support the hypothesis that cation binding alters the electron density distribution within the chromophore, stabilizing the MLCT pathway. These results demonstrate that incorporation of a second cation provides an effective strategy to control excited-state dynamics in ruthenium complexes, offering opportunities for the rational design of photosensitizers and photofunctional materials. Full article

Thiopurines are efficient triplet-state photosensitisers; however, the practical application of canonical derivatives such as 6-thioguanine (6TG) and 6-thioguanosine (6TGuo) is limited by competing deactivation pathways that reduce the fraction of triplet states available for productive interaction with molecular oxygen. In this work, we investigated how structural modification of the thiopurine scaffold through introducing of an additional five-membered etheno ring affects triplet-state energetics, deactivation pathways, and singlet oxygen sensitisation. The photophysical properties of four tricyclic thiopurine analogues—9-thio-1,N²-ethenoguanine (TEGua), 9-thio-1,N²-ethenoguanosine (TEGuo), 6-methyl-9-thio-1,N²-ethenoguanine (6MeTEGua), and 6-methyl-9-thio-1,N²-ethenoguanosine (6MeTEGuo)—were investigated using steady-state spectroscopy, low-temperature phosphorescence, nanosecond transient absorption spectroscopy, and direct detection of singlet oxygen phosphorescence. All investigated compounds exhibited efficient intersystem crossing and microsecond-lived triplet states. Compared with canonical thiopurines, the tricyclic analogues displayed lower triplet-state energies and significantly enhanced singlet oxygen generation. Quantum yields of singlet oxygen sensitisation reached ~0.56 in acetonitrile, approximately twofold higher than those observed for 6TG and 6TGuo under identical conditions. Analysis of triplet-state deactivation pathways showed that the enhanced photosensitising efficiency does not result from increased triplet formation, but from more effective use of the triplet-state population for energy transfer to molecular oxygen leading to singlet oxygen formation. These findings demonstrate that structural modification of the thiopurine scaffold enables control over triplet-state reactivity and provides a strategy for designing improved thiopurine-based photosensitisers for photodynamic therapy applications (PDT). Full article

Three new heteroleptic copper(I) complexes of the form [Cu(N,N)(XantPhos)]PF₆ were synthesized and characterized, where N,N refers to phenyl-substituted imidazo[4,5-f][1,10]phenanthroline. All complexes were obtained as yellow powders in yields ranging 82–95% and were fully characterized by NMR spectroscopy, FT-IR, and mass spectrometry. The complexes were also redox-optically characterized. Their absorption profiles display a lower-energy metal-to-ligand charge-transfer (MLCT) band at approximately 412 nm. In solution, weak dual emission is observed, combining ligand-centered and MLCT contributions, with oxygen-dependent quenching supporting the presence of triplet character in the latter. Temperature- and solvent-dependent studies reveal thermally coupled emissive states, in which a relaxed ³MLCT state dominates at low temperatures. In the solid state, intense orange-to-red emission arises from restricted molecular motion and stabilized ³MLCT states, with C3 showing the highest efficiency. Additionally, aggregation-induced emission (AIE) is observed in solvent mixtures. These results suggest that remote substitution can influence the excited-state dynamics and aggregation-driven emission in Cu(I) complexes. Full article

Transition metal complexes that can serve as photosensitizers (PSs) have attracted considerable scientific interest owing to their potential applications in photodynamic therapy (PDT), triplet-triplet annihilation for energy upconversion (TTA UC), photocatalysis, and time-resolved bioimaging techniques. In many of these applications, the efficiency of intermolecular triplet-triplet energy transfer (TTET) between the photosensitizer and acceptor is largely determined by the triplet excited-state lifetime of the photosensitizer. One of the most efficient strategies for extending the triplet lifetimes of transition metal complexes is the incorporation of organic chromophores possessing long-lived intraligand (³IL) excited states into the coordination sphere of transition metal complexes. Polycyclic aromatic hydrocarbons, particularly anthracene- and pyrene-based chromophores, have emerged as especially attractive building blocks for this purpose. The current contribution highlights the role of pyrene and anthracene groups in controlling the photophysical properties of cyclometalated iridium(III) metal complexes, with an emphasis on their applications as photosensitizers. Particular attention is devoted to elucidating the relationships between molecular structure and excited-state properties. A detailed discussion of these relationships has been performed for three classes of cyclometalated iridium(III) complexes: (1) charge-neutral Ir(III) complexes including pyrene and anthracene motifs, (2) cationic bis-cyclometalated iridium(III) complexes bearing pyrene-functionalized ligands, and (3) cationic mono- and bis-cyclometalated iridium(III) complexes bearing anthracene-functionalized ligands. Full article

Classifying encrypted sensor traffic is critical for the security and management of Internet of Things networks, particularly in Mobile Edge Computing (MEC) environments. Existing methods often require extensive task-specific labeled data to adapt to emerging traffic categories and may also fail to distinguish intrinsic traffic behaviors from patterns introduced by shared communication libraries, which can degrade classification accuracy under distribution shifts. To address these issues, we propose CDTF, a contrastive dual-task framework for transferable and few-shot traffic representation learning. CDTF adopts a hybrid pre-training strategy that jointly optimizes supervised triplet pretraining (STP) and self-supervised dynamic burst masking (DBM). STP uses base-class labels as structural anchors to explicitly constrain distance relationships by aligning intra-class samples and separating inter-class samples, thereby mitigating interference from shared network components. DBM models global semantic structures and enhances the robustness of traffic representations against network noise and distribution shifts. By learning discriminative and contextual representations in a shared embedding space via these two tasks, CDTF can rapidly adapt to novel categories through lightweight fine-tuning, thereby substantially reducing the reliance on large-scale fine-grained supervision in downstream tasks. Experimental results across seven public and two custom datasets, across diverse environments, show that the proposed framework outperforms state-of-the-art methods. Under the few-shot setting, CDTF improves Precision by 4.61 percentage points over the strongest baseline, with statistical significance confirmed by a paired t-test ($p<0.05$). Full article

We report the synthesis and characterization of the photophysical characterization of a series of rhodamine (Rho)–perylenebisimide (PBI) electron donor–acceptor dyad/triads containing flexible alkyl spacers (ethylene or hexylene chains). Steady-state absorption and emission, femtosecond and nanosecond transient absorption (fs-TA and ns-TA), cyclic voltammetry, triplet–triplet energy transfer (TTET) experiments and DFT/TD-DFT calculations were combined to elucidate the excited-state dynamics. fs-TA spectral study indicates fast decay of the S₁ state and formation of the ³PBI state (0.32–663 ps), which is supported by the ns-TA spectra. The localized PBI triplet (³PBI*) exhibits unusually long lifetimes (up to 272 μs) as determined by the TTET experiment. No long-lived charge-separated (CS) state was observed. While a Förster resonance energy transfer (FRET) probably occurs between PBI and the open-ring rhodamine, a photo-induced electron transfer is proposed to be responsible for the quenching of the fluorescence of the PBI moiety. Full article

High-performance full-color displays and white lighting require stable and efficient red, green, and blue emitters; however, they are often limited by wide bandgaps, imbalanced carrier injection/transport, complex device structures, and high material costs. To address these challenges, we designed and synthesized a multifunctional deep-blue molecule (PPI-F-PO) integrating a phenanthroimidazole moiety, a 9,9-diphenylfluorene unit, and a phosphine oxide group. The twisted structure of fluorene, featuring a sp³-hybridized carbon, effectively suppresses conjugation extension and aggregation-caused quenching, whereas the electron-withdrawing phosphine oxide group enhances electron transport. Consequently, it exhibits good thermal stability, high solid-state photoluminescence quantum yield (58.8%), and high triplet energy (E_T = 2.54 eV). Non-doped blue OLEDs based on this emitter achieve a maximum external quantum efficiency (EQE) of 2.52% with deep-blue CIE coordinates of (0.16, 0.06). Moreover, using this material as a host, green and orange-red phosphorescent OLEDs exhibit maximum EQEs of 15.4% and 9.7%, respectively, along with low efficiency roll-off. This work demonstrates that a bipolar deep-blue emitter with high triplet energy can act both as a high-efficiency standalone emitter and as a universal host for lower-energy phosphors, thereby simplifying device architecture and reducing material costs for full-color OLEDs. Full article

Network intrusion detection systems play a vital role in protecting networks by detecting malicious network traffic which can then be investigated by a cybersecurity operations centre. State-of-the-art approaches utilise supervised machine learning methods to train a classification model to recognise known cyberattacks; however, these models require a large labelled dataset to train and show poor performance when trained on smaller datasets. In an attempt to address this shortcoming, anomaly detection models learn the distribution of benign traffic and flag non-conforming traffic as malicious. While these methods do not require malicious examples to train, they suffer from high false-positive rates rendering them impractical. As a result, networks may be particularly vulnerable when there are insufficient labelled instances of a specific attack class to train an effective classifier. This often occurs in newly established networks or when previously unseen types of attacks emerge. To address this challenge, this work proposes the use of a triplet network, utilising online triplet mining and a KNN classifier, which is able to perform few-shot classification, enabling effective intrusion detection after being trained on a limited number of malicious examples. Various online triplet mining algorithms were explored and model design choices, such as the inference algorithm and optimised distance metrics, were compared and evaluated through a series of ablation studies. The final model was compared against other state-of-the-art approaches in few-shot binary and multiclass classification, where the proposed approach was found to be competitive with existing methods when trained on as little as 10 malicious samples of each class. Full article

Antimicrobial resistance (AMR) is emerging as one of the most serious global health problems, necessitating the urgent development of alternative approaches to pathogen control. The present study describes the synthesis and characterization of a novel iodinated BODIPY derivative (BODIPY5), designed as a highly efficient photosensitizer for antimicrobial photodynamic inactivation (aPDI). The molecular design of the compound involves the introduction of two iodine atoms into the BODIPY5 core, which induces a “heavy atom effect”, accelerates the intersystem transition from the singlet to the triplet state, and leads to increased generation of singlet oxygen upon irradiation with visible light. Photophysical measurements show a significant fluorescence quenching of BODIPY5 compared to its unsubstituted counterpart, which is a direct indicator of increased photodynamic activity. The compound’s antimicrobial efficacy was tested in a homogeneous medium and after immobilization on cotton textiles via physical adsorption. In solution, BODIPY5 nearly eliminated the model bacterial strains B. cereus and P. aeruginosa at a low concentration of 10 µg/mL under light, with cell viability below 1%. The functionalized cotton fabric exhibits pronounced self-disinfection properties, retaining high photodynamic activity against the Gram-negative pathogen P. aeruginosa. Scanning electron microscopy results confirm extensive morphological damage and loss of structural integrity in bacterial cells on the treated textile following irradiation. The non-specific mechanism of action, which generates reactive oxygen species (¹O₂) in situ, prevents the development of bacterial resistance and makes the developed material a promising candidate for use in hospital environments, including antibacterial clothing and protective equipment. Full article

BODIPY derivatives are promising scaffolds for triplet photosensitizers because of their strong absorption and tunable absorption range, but their dominant fluorescence decay and weak spin–orbit coupling hinder efficient intersystem crossing (ISC). Here, we report iodine-substituted BODIPY photosensitizers bearing anthracene, pyrene, and perylene units (BI-Ant, BI-Pyr, and BI-Per), designed to combine the heavy-atom effect with the spin–orbit charge-transfer ISC (SOCT-ISC) process. Spectroscopic and computational analyses revealed charge-transfer character and efficient triplet formation in all three compounds. Transient absorption measurements showed that BI-Ant and BI-Pyr undergo an ISC process to BODIPY-centered triplet state, whereas BI-Per exhibits intermediate strong charge-transfer-state evolution and the fastest ISC process. Solvent-dependent results further indicate that charge-transfer-state stabilization accelerates ISC process, supporting an additional SOCT contribution. These findings provide an effective strategy for developing highly efficient metal-free triplet photosensitizers. Full article

The photophysical processes and photochemical reactions of 1,4-di(azastyryl)benzene (1) derivative {[(E,E)-1](ClO₄)₂} were investigated by absorption, luminescence, and laser kinetic spectroscopy in the water solution. The observed photo processes include dimerization, E-Z isomerization, and intersystem crossing to the triplet state, as well as the complexation [(E,E)-1](ClO₄)₂ with cucurbit[7]uril (CB[7]). The [(E,E)-1](ClO₄)₂ dye dimerization was shown to be energetically more favorable in the excited state than in the ground state. The reversible photoinduced migration of the dye dication in the CB[7] cavity takes place as a result of partial exit of the [(E,E)-1]²⁺ from the cavity and its subsequent conversion to the (E,Z)-isomer in the excited state, which undergoes conversion to the initial complex of {[(E,E)-1]@CB[7]}²⁺ after returning to the ground state. This photoprocess is of interest in relation to the scientific problem of designing photocontrolled supramolecular machines. Full article

High-voltage bushings, the fault-prone key electrical components of transformers, are critical for real-time and high-accuracy fault monitoring and management. Intelligent fault detection via infrared images is plagued by low classification accuracy due to massive interference from similar tubular objects and small target characteristics. This study proposes a lightweight deep learning model, MTrip–YOLO, an improved YOLO11n integrated with Mamba-2 (Structured State Space Duality, SSD) and Triplet Attention, to achieve efficient fault monitoring in complex backgrounds. The training and validation dataset comprises open-source images, on-site data from a substation, and field-collected infrared images, categorized into four types: normal bushings, poor contact, oil shortage, and high dielectric loss faults. Mamba-2 captures the long-range global context of infrared features with its linear-complexity long-range modeling capability to enhance feature extraction, while Triplet Attention suppresses complex background radiation noise through cross-dimensional interaction without dimensionality reduction, enabling the model to focus on small targets and accurately classify bushings from morphologically similar strip-shaped objects. Experimental results show that MTrip–YOLO achieves a top mAP50 of 91.6% and a minimal parameter count of 1.9 M, outperforming Faster R-CNN, RT-DETR, and YOLO26n across all evaluated metrics and being potentially suitable for edge deployment on UAV-mounted or handheld infrared platforms, pending hardware validation on embedded computing devices. Ablation experiments verify the independent contributions of Mamba-2 (0.8027% mAP50 improvement) and Triplet Attention (0.89327% mAP50 improvement), with a synergistic effect from their combination. MTrip–YOLO provides a potential edge-deployable solution for high-voltage bushing fault monitoring, offering important application value for the intelligent operation and maintenance of substations. Full article

To deal with the high standards, strong restrictions, and high repeatability that are inside State Grid small-scale infrastructure projects, this research puts forward a norm-driven generative design method, which conquers the low efficiency, compliance dangers, and semantic breakage that are usual in manual modeling. Taking standards such as Q/GDW 11382.3-2015 as the knowledge origin, we construct an ALBERT-BiLSTM-CRF semantic parsing model and change natural-language clauses into executable design restrictions via normative text pre-processing, BIO sequence marking, and rule triplet mapping. Therefore, model training and assessment produce Accuracy, Precision, Recall, and F1 of 98.05%, 95.49%, 95.88%, and 95.59% separately, with 100% precision for logical comparison and conjunction labels; thus, this provides a steady semantic base for the rule base. At the component level, a three-part coding plan and unit module collection are built based on OmniClass and GB/T 51269, which makes semantic consistency and traceability between components and space functions possible. At the system level, a continuous work process is carried out through the Revit API, which covers scheme making, automatic arrangement, and deliverable output. Hence, validation on a real case in a digital operation center for the power system shows that the design time for the third-floor administrative office area was cut from about 20 h to around 4 h, and the first-time solution met all code restrictions, which improves efficiency and compliance in a significant way. The results point out that norm-driven generative design can supply deployable automation and high-quality outputs for small-scale power infrastructure, which provides a sustainable database for digital twins and smart O&M. Full article