Overlap Of Spectra Research Articles

Empirical Modal Decomposition Combined with Deep Learning for Photoacoustic Spectroscopy Detection of Mixture Gas Concentrations.

In photoacoustic spectroscopy based multicomponent gas analysis, the overlap of the absorption spectra among different gases can affect the measurement accuracy of gas concentrations. We report a multicomponent gas analysis method based on empirical modal decomposition (EMD), convolutional neural networks (CNN), and long short-term memory (LSTM) networks that can extract the exact concentrations of mixed gases from the overlapping wavelength-modulated spectroscopy with second harmonic (WMS-2f) detection. The WMS-2f signals of 25 different concentration combinations of acetylene-ammonia mixtures are detected using a single distributed feedback laser (DFB) at 1531.5 nm. The acetylene concentrations range from 2.5 to 7.5 ppm and the ammonia concentrations from 12.5 to 37.5 ppm. The data set is enhanced by cyclic shifting and adding Gaussian noise. The classification accuracy of the test set reaches 99.89% after tuning. The mean absolute errors of the five additional sets of data measured under different conditions are 0.092 ppm for acetylene and 1.902 ppm for ammonia, within the above concentration ranges.

An extended substrate spectrum of the proton organic cation antiporter and relation to other cation transporters.

Most central nervous system (CNS) active drugs are organic cations, which need carrier proteins for efficient transfer through the blood-brain barrier (BBB). A genetically still unidentified proton organic cation (H+/OC) antiporter is found in several tissues, including endothelial cells of the BBB. We characterized the substrate spectrum of the H+/OC antiporter and the overlap in substrate spectrum with OCTN1, OCTN2 or OCT3 by screening 87 potential substrates for transport activity. Based on high antiport rates, 45 of the tested substances were substrates of the H+/OC antiporter. They included antidepressants (like tranylcypromine or nortriptyline), antipsychotics (like levomepromazine) and local anaesthetics. Concentration-dependent transport was confirmed for 38 of the substrates. Transport uptake depending on a pH gradient across the cell membrane confirmed that 43 drugs were indeed substrates of the H+/OC antiporter. However, the patterns of pH dependence differed between the substrates, possibly indicating different modes of transport or the existence of multiple antiporter proteins. The substrate overlap between the H+/OC antiporter and OCTN1, OCTN2 or OCT3 was minimal, indicating that the latter three are not the proteins underlying the H+/OC antiporter activity. Overall, about 50% of positively charged drugs may be substrates of the antiporter, which may be the most important membrane transport protein for many drugs.

Simultaneous Detection of Clenbuterol and Higenamine in Urine Samples Using Interference-Free SERS Tags Combined with Magnetic Separation.

Sports doping remains a significant challenge in competitive sports. Given that urine analysis is the standard for detecting doping, developing rapid, sensitive, accurate, and high-throughput methods for stimulant detection in urine is crucial. Surface-enhanced Raman scattering (SERS) tag-based immunoassays have emerged as powerful analytical tools known for their high sensitivity and specificity, holding particular promise for stimulant detection in urine samples. However, both the Raman signals of typical SERS tags and sample matrices are within the Raman fingerprint region (<1800 cm-1), which could lead to spectrum overlap, potentially reducing detection accuracy and sensitivity. By recognizing this, we designed a competitive immunoassay that integrates two types of zero-background SERS tags and magnetic separation. These innovative SERS tags exhibit distinctive Raman peaks within the Raman-silent region (1800-2800 cm-1), effectively mitigating potential spectrum overlap with background sample signals. Moreover, magnetic separation not only enhances operational simplicity but also improves the system's anti-interference capability. Using clenbuterol (CL) and higenamine (HM) as model targets, the SERS-based competitive immunoassay demonstrated sensitive detection of individual CL or HM standards, with limits of detection (LODs) of 0.87 and 0.71 pg/mL, respectively. In multiplex mode, CL and HM can be simultaneously detected with LODs of 1.0 and 0.81 pg/mL, respectively. Furthermore, the recovery rates in urine samples ranged from 83 to 116% (relative standard deviation, RSD ≤ 6.4%) for CL and from 82 to 103% (RSD ≤ 5.1%) for HM, further confirming the reliability of the SERS-based immunoassay for practical applications.

Suppression of cross-interference in the absorption spectra of gas mixtures

In the quantitative analysis of mixed gases by tunable diode laser absorption spectroscopy, the overlapping of absorption spectra and mutual interference of multi-component gases can lead to problems of large measurement errors and low analysis accuracy. In this paper, an improved firefly algorithm is proposed and applied to the support vector machine regression model to solve this problem. The specific method includes introducing an adaptive step size to balance the local and global searches and using the gradient descent method to accelerate the parameter optimization process so as to improve the model’s generalization ability and prediction accuracy. The experimental results show that the maximum errors of the improved algorithm in the prediction of CH4 and CO gas concentrations are no more than 0.0443 % and 2 ppm, with coefficients of determination, R2, of 0.9994 and 0.99815. The promising results obtained by the system provide theoretical support for the realization of high-precision detection of multicomponent gases with a single source of light, and also demonstrate the high efficiency and feasibility of the method in practical detection.

Nailfold Video-Capillaroscopy in Sarcoidosis: New Perspectives and Challenges.

Nailfold video-capillaroscopy (NVC) is a non-invasive cost-effective technique involving the microscopic examination of small blood vessels of the distal nailfold with a magnification device. It provides valuable information regarding the microcirculation including anomalies such as tortuous or dilated capillaries, hemorrhages, and avascular areas, which can characterize connective tissue diseases. The utility of NVC in the diagnosis and monitoring of systemic sclerosis (SSc) has been investigated in numerous studies allowing the distinction of the specific microvascular pattern of scleroderma from different conditions other than scleroderma (non-scleroderma pattern). Sarcoidosis (SA) is a systemic inflammatory disease that can affect various organs, including the lungs, skin, and lymph nodes. The purpose of our review was to evaluate the current state of the art in the use of NVC in the diagnosis of SA, to understand the indications for its use and any consequent advantages in the management of the disease in different settings in terms of benefits for patients. We searched for the key terms "sarcoidosis" and "video-capillaroscopy" in a computerized search of Pub-Med, extending the search back in time without setting limits. We provided a critical overview of the literature, based on a precise evaluation. After our analysis, we examined the six yielded works looking for answers to our questions. Few studies have evaluated that microcirculation is often compromised in SA, with alterations in blood flow and consequent tissue damage. Basing on highlighted findings, NVC appears to be a useful tool in the initial evaluation of sarcoidosis patients. Furthermore, capillaroscopy is useful in the evaluation of the coexistence of sarcoidosis and scleroderma spectrum disorder or overlap syndromes. In conclusions, no specific pattern has been described for sarcoidosis, and further re-search is needed to fully understand the implications of nailfold capillaroscopy find-ings in this disease and to establish standardized guidelines for its use in clinical practice.

Modeling of a Single-Band-Ratiometric Sensor Based on Lattice Positive Thermal Expansion in Eu3+-Activated Halide Perovskite Cs2NaEuCl6.

Recently, single-band ratiometric (SBR) thermometry has emerged as an innovative approach to traditional fluorescence thermometry, overcoming uncertainties associated with emission spectrum overlap or scattering while maintaining high spatial resolution and remote monitoring. This paper presents a novel Cs2NaEuCl6 perovskite prepared through a slow-cooling solution method. Additionally, it proposes a temperature sensor model that relies on the thermal quenching of charge-transfer state absorption. Mechanical studies highlight the role of lattice positive thermal expansion in affecting Eu3+ emission. Conversely, a significant emission enhancement is observed upon excitation corresponding to both the ground state and excited state absorption. The distinct luminescent behavior of this Eu3+-activated halide perovskite model makes it suitable for developing a highly sensitive SBR-type sensor with a relative sensitivity (Sr) exceeding 1.5% K-1 and temperature resolution (𝛿T) below 1 K at room temperature. Furthermore, it demonstrates the thermal stability during multiple heating-cooling cycles. Finally, the practical applicability of the proposed SBR model is demonstrated by employing a self-manufactured film sensor that enables precise real-time temperature detection for electronic components. The work is regarded as a significant stride toward the development of cutting-edge and exquisitely sensitive thermometers based on lanthanide-based halide double perovskites.

A Framework of Multi-View Machine Learning for Biological Spectral Unmixing of Fluorophores with Overlapping Excitation and Emission Spectra.

The accuracy in assigning fluorophore identity and abundance, termed spectral unmixing, in biological fluorescence microscopy images remains challenging due to the unavoidable and significant overlap in emission spectra among fluorophores. In conventional laser scanning confocal spectral microscopy, fluorophore information is acquired by recording emission spectra with a single combination of discrete excitation wavelengths. As a matter of fact, organic fluorophores have not only unique emission spectral signatures but also have unique and characteristic excitation spectra. In this paper, we propose a generalized multi-view machine learning approach, which makes use of both excitation and emission spectra to greatly improve the accuracy in differentiating multiple highly overlapping fluorophores in a single image. By recording emission spectra of the same field with multiple combinations of excitation wavelengths, we obtain data representing these different views of the underlying fluorophore distribution in the sample. We then propose a framework of multi-view machine learning methods, which allows us to flexibly incorporate noise information and abundance constraints, to extract the spectral signatures of fluorophores from their reference images and to efficiently recover their corresponding abundances in unknown mixed images. Numerical experiments on simulated image data demonstrate the method's efficacy in improving accuracy, allowing for the discrimination of 100 fluorophores with highly overlapping spectra. Furthermore, validation on images of mixtures of fluorescently labeled E. coli demonstrates the power of the proposed multi-view strategy in discriminating fluorophores with spectral overlap in real biological images.

Pathogenetic significance of long non-coding RNAs in the development of thoracic and abdominal aortic aneurysms

Aortic aneurysm (AA) is a life-threatening condition with high prevalence and risk of severe complications. The aim of this review was to summarize the data on the role of long non-coding RNAs (lncRNAs) in the development of aortic aneurysms of various locations. Over a less than decade of lncRNA studies in AA, using experimental and bioinformatic approaches, scientists have obtained the data confirming the involvement of these molecules in metabolic pathways and pathogenetic mechanisms critical for the development of aneurysms. Regardless of the location of the pathological process (thoracic or abdominal aorta), changes in the expression levels of various lncRNAs in the tissue of the affected vessels have been established. The consistency of changes in the expression level of lncRNA, mRNA and microRNA in aortic tissues during AA development has been recorded. Also, a number of regulatory networks those are pathogenetically significant for biochemical pathways and cellular processes have been identified, in which lncRNAs act as the competing endogenous RNAs (ceRNA networks). Moreover, on the one hand, the same lncRNA can be involved in different ceRNA networks and regulate different biochemical and cellular events; on the other hand, the same pathological process is controlled by different lncRNAs. Despite some similarities in pathogenesis and the overlap of the lncRNA spectrum, identical ceRNA networks have not been described for abdominal and thoracic aortic aneurysms. Interactions between lncRNA and protein molecules, including those involved in epigenetic processes at other levels, have also been identified as potentially relevant to the pathogenesis of aortic aneurysm. For some lncRNAs, correlations of the expression level with clinically significant aortic features and biochemical findings AA were observed. The identification of regulatory RNAs that are functionally significant for aneurysm development is important for clarification of the disease pathogenesis and will also provide a basis for early diagnosis and development of new preventive and therapeutic drugs.

1,1,2,2-Tetra(4-carboxylphenyl)ethylene-Based Metal-Organic Gel as Aggregation-Induced Electrochemiluminescence Emitter for the Detection of Aflatoxin B1 Based on Nanosurface Energy Transfer.

In this Letter, a sensitive DNA sensing platform was developed using an indium-ion-coordinated 1,1,2,2-tetra(4-carboxylphenyl)ethylene (TPE) metal-organic gel (In-MOG) as an aggregation-induced electrochemiluminescence (AIECL) emitter and nanosurface energy transfer (NSET) as an efficient quenching strategy for detecting aflatoxin B1 (AFB1), the most dangerous food toxin. The coordination occurred in indium ions, and carboxyl groups restricted the internal rotation and vibration of TPE molecules, forcing them to release photons via radiative transitions. The quenchers of microfluidic-produced gold nanoparticles were embedded in a long-tailed triangular DNA structure, where the quenching phenomenon aligned with the theory of ECL-NSET under the overlap of spectra and appropriate donor-acceptor spacing. The proposed analytical method showed a sensitive ECL response to AFB1 in the wide concentration range of 0.50-200.00 ng/mL with a limit of detection of 0.17 ng/mL. Experimental results confirmed that constraining luminescent molecules using coordination and bonding to trigger the AIECL phenomenon was a promising method to prepare signal labels for the trace detection of food toxins.

Colorimetric and ECL dual-mode aptasensor for smartphone-based onsite sensitive detection of aflatoxin B1 in combination with ZnO@MWCNTs/g-C3N4 nanosheets and CuO@CuPt nanocomposites

The development of dual-mode strategies with superior sensitivity and accuracy have garnered increasing attention for researchers in Aflatoxin B1 (AFB1) analysis. Herein, a colorimetric-electrochemiluminescence (ECL) dual-mode biosensor was constructed for onsite and ultrasensitive determination of AFB1. The multi-wall carbon nanotubes (MWCNTs) were integrated with the ZnO metal organic frameworks (MOFs) to accelerate the electron transfer and boost the ECL intensity of g-C3N4 nanoemitters. Through the aptamer-based DNA sandwich assay, the CuO@CuPt nanocomposites were introduced onto the electrode and acted as the dual functional signal nanoprobes. Due to the good spectrum overlap between the CuO@CuPt nanoprobes and g-C3N4 nanosheets, ECL signal could be efficiently quenched. Additionally, the CuO@CuPt nanoprobes show superior catalytic properties towards the TMB and H2O2 colorimetric reactions, and an obvious color alteration from colorless to blue can be observed using the smartphone. Under optimized conditions, a sensitive and accurate dual-mode analysis of the AFB1 was accomplished with the colorimetric detection limit of 3.26 fg/mL and ECL detection limit of 0.971 fg/mL (S/N = 3). This study combines innovative nanomaterial properties of ZnO@MWCNTs, g-C3N4 and CuO@CuPt for ultrasensitive dual-mode detection, which offers new opportunities for the innovative engineering of the dual-mode sensors and demonstrates significant potential in food safety analysis.

Resonance energy transfer aided detection of nitroaromatics in aqueous medium by a luminescent Mn based metal-organic framework

A light brown needle-like crystal of Mn-based metal–organic framework (MOF); [Mn2.5(µ3-OH)(DTDB)2], (DTDB = 2,2′-dithiodibenzoate), compound 1, was synthesized using hydrothermal technique. Compound 1 was systematically characterized by single-crystal X-ray diffraction (SCXRD), powder X-ray diffraction (PXRD), and infrared spectroscopy (IR). Photoluminescence study of compound 1 in an aqueous medium showed intense blue emission centred at 395 nm upon excitation at 310 nm. This emissive property of compound 1 was utilized for selective and sensitive detection of 2,4,6- trinitrophenol (TNP), 2,4- dinitrophenol (DNP) and 4-nitrophenol (NP) in the aqueous medium through luminescence quenching mechanism. As indicated by the good overlap of the absorption spectra of the analytes and the emission spectrum of the compound 1, and manifested as the reduction in luminescence lifetimes, it can be concluded that the resonance energy transfer is the most significant factor for the selective detection of aromatic nitro-phenol compounds. The resonance energy transfer requires the proximity of the donor and acceptor, which was achieved by the molecular level interactions between the ‘S’ atom of the DTDB ligand and phenolic –OH groups of the nitrophenols through non-covalent type interactions like hydrogen bonding and dipolar type interactions. Detection limits for TNP, DNP, and NP with the values of 208 ppb, 156 ppb, and 556 ppb, respectively, were obtained in an aqueous medium. The studies indicate that compound 1 could be helpful for detecting nitrophenol derivatives in water.

Intermolecular FRET Pairs as An Approach to Visualize Specific Enzyme Activity in Model Biomembranes and Living Cells

Herein, we propose an analytical approach based on intermolecular fluorescent resonant energy transfer (FRET) pairs for the visualization of specific enzyme activity in model biomembranes and in living cells. Cell visualizations with fluorescent confocal laser microscopy usually rely on fluorescent probes, such as Fluorescein isothiocyanate (FITC), Alexa488, Tetramethylrhodamine isothiocyanate (TRITC) and many others. However, for more specific tasks, such as the detection of certain enzymatic activity inside the living cell, the toolbox is quite limited. In the case of enzyme-hydrolases for example, the choice is limited to organic molecules comprising a fluorescent dye (typically, 4-methylumbelliferone (MUmb) or 7-amino-4-methylcoumarin (AMC) derivatives) and a fluorescence quencher, bound via an enzyme-sensitive linker—so that when the linker is degraded, the fluorescent signal increases. Unfortunately, both MUmb and AMC are quenched and have a relatively low quantum yield in cells, and their excitation and emission ranges overlap with that of intracellular fluorophores, often producing a strong background noise. R6G, on the other hand, has excellent quantum yield apart from intracellular fluorophores, but there are no efficient quenchers that could be chemically linked to R6G. Herein, we show that R6G is able to form intermolecular FRET pairs with MUmb or AMC, with the latter serving as fluorescence donors. This yields a combination of R6G’s excellent fluorescence properties with a possibility to use an enzyme-sensitive linker in MUTMAC or AMC derivatives. This phenomenon was initially discovered in a model system, reversed micelles, where the donor, the acceptor, and the enzyme are forced to be in close proximity to each other, so that proximity could serve as an explanation for the intermolecular FRET effect. Surprisingly enough, the phenomenon has been reproduced in living cells. Moreover, we were able to create working intermolecular donor–acceptor FRET pairs for several different enzymes, including chymotrypsin, phosphatase, and asparaginase. This appears counterintuitive, as besides the overlap of the emission spectra of the donor and the absorption spectra of the acceptor, there are other criteria for the FRET effect, including the convergence of two fluorophores at a distance of about 1–10 nm, and the orientation of their dipoles at a certain angle, which is difficult to imagine in a bulk system like a living cell. We hypothesize that FRET-enabling donor–acceptor interaction may be taking place at the inner surface of the lipid bilayer, to which both donor and acceptor molecules would likely have an affinity. This hypothesis would require a more detailed investigation. Therefore, we have shown that the method suggested has good potential in the visualization of enzyme functioning inside living cells, which is often a challenging task. Shifting of the fluorescence signal to the long-wavelength region would increase the signal selectivity, making it easily distinguishable from autofluorescence.

Green micellar factorial design optimized first derivative synchronous spectrofluorimetric method for tripelennamine and diphenhydramine determination in pharmaceutical gel.

A green micellar synchronous spectrofluorimetric method was developed and validated for simultaneous determination of tripelennamine hydrochloride and diphenhydramine in bulk and combined pharmaceutical formulation. Synchronous fluorescence of tripelennamine hydrochloride and diphenhydramine was determined using Δλ = 60 nm. The first derivative of synchronous fluorescence was computed to resolve overlap in the synchronous fluorescence spectra. Tripelennamine hydrochloride was quantified at 375 nm, whereas diphenhydramine was quantified at 293 nm; each is the zero-crossing point of the other. As diphenhydramine exhibited weak native fluorescence, micelle enhancement upon incorporation of sodium dodecyl sulfate was considered. Two-level full factorial design was carried out to optimize experimental parameters. Optimum conditions involved using SDS (2% w/v) along with Teorell and Stenhagen buffer (pH9). The method was found to be linear over the range 0.2-4.5 and 0.2-5μg/mL for tripelennamine and diphenhydramine, respectively, with limits of detection 0.211 and 0.159 μg/mL. The method was successfully applied for simultaneous determination of tripelennamine hydrochloride and diphenhydramine in laboratory-prepared gel containing all possible excipients with mean percent recoveries ±SD 100.59 ±0.79 and 98.99 ±0.98 for tripelennamine hydrochloride and diphenhydramine, respectively. The proposed method was proved to be eco-friendly using different greenness assessment tools.

ESIPT-associated fluorescent property and AIE characteristic of multifunctional nanoprobe DPNAP

The DPNAP is a multifunctional nanoprobe designed for selective illumination of fungi and targeted antimicrobial applications. By introducing hydroxyl groups into the DPNAP, the aggregation-induced emission (AIE) characteristic can be obtained. However, its optical properties and underlying theoretical mechanisms are not fully understood. In this work, we explored the stable DPNAP configurations by constructing the potential energy surfaces and elucidated the mechanism of the proton transfer reaction. Our findings indicate that proton transfer occurs through a stepwise reaction with energy barriers of < 10 kcal/mol, owing to the variation in hydrogen-bonding strength as revealed by hydrogen-bond parameters and infrared vibrational analyses. The theoretical fluorescence peak (λcal = 541 nm) based on the optimized structures is consistent with the experimental peak (λexp = 500 nm). The experimental single-fluorescence band is attributed to the overlap of emission spectra of normal structure and single- and double-proton transfer isomers. Moreover, the hydroxyl-induced AIE mechanism is attributed to increased molecular planarity and restricted intramolecular charge transfer in the aggregate state. Understanding of the AIE characteristic and ESIPT mechanism is of fundamental importance in molecular electronics and photonics, and is also beneficial to the development of novel biomedical materials.

60‐4: Minimal Efficiency Degradation and Elevated Radiometric Power Density of Ultraviolet‐A Micro‐LED with Homoepitaxial Structure

As display technology continues to advance, UVA micro‐LEDs are becoming increasingly important in a variety of display and beyond‐display applications. In this study, we investigate the optoelectronic characteristics of UVA micro‐LEDs based on a homogeneously epitaxial structure on freestanding gallium nitride (GaN) substrates. The device exhibits a central wavelength of 390 nm, positioned at the overlap of UVA and visible light spectra. It demonstrates an impressively low ideality factor of 1.49 at 2.86 V and a series resistance of 9.88 O beyond 3 V. Optically, our device shows virtually no wavelength shift across a wide current density range of 0.1‐1000 A/cm2, indicating exceptional optical stability and color accuracy. The emitted light is typical purple, reaching an expansive color gamut of 115.3% of Rec.2020. Furthermore, the GaN‐on‐GaN structure, with its superior crystal structure and heat dissipation properties, results in a very low droop ratio in EQE. This ensures sustained highpower output at high current densities, showcasing great potential in applications such as 3D printing, maskless photolithography, and fluorescence tagging.

Hazardous 2,4,6-Trinitrophenol (TNP) Detection in Water by Amine and Azine Functionalized Metal-Organic Framework.

A Zn(II)-based metal-organic framework (MOF) decorated with amine and azine functionalities, TMU-17-NH2 (formulated as [Zn(H2ata)(L)].2DMF; L = 1,4-bis(4-pyridyl)-2,3-diaza-2,3-butadiene and H2ata = 2-aminoterephthalic acid) has been successfully synthesized via a solvothermal method. According to crystallographic studies, the synthesized TMU-17-NH2 has three dimensional cuboidal structure with the pore surface decorated with free amine (-NH2) and azine (= N-N =) functional groups. The photoluminescence investigations proved that the synthesized MOF can be effectively utilized for selective detection of 2,4,6-trinitrophenol (TNP) in water with an apparent turn-off quenching response. Its limits of detection (LOD) for TNP was 9.4ppb and competitive nitro explosive testing confirmed its higher selectivity towards TNP (over other nitro explosives). Calculations based on density functional theory (DFT) and spectrum overlap were utilized to evaluate the sensing mechanisms. This MOF-based fluorescence sensing technique for TNP had a high sensitivity (Ksv = 3.26 × 104M-1).

Lateral Heterostructure Formed by Highly Thermally Conductive Fluorinated Graphene for Efficient Device Thermal Management.

The continued miniaturization of chips demands highly thermally conductive materials and effective thermal management strategies. Particularly, the high-field transport of the devices built with 2D materials is limited by self-heating. Here a systematic control of heat flow in single-side fluorinated graphene (FG) with varying degrees of fluorination is reported, revealing a superior room-temperature thermal conductivity as high as 128W m-1 K-1. Monolayer graphene/FG lateral heterostructures with seamless junctions are approached for device fabrication. Efficient in-plane heat removal paths from graphene channel to side FG are created, contributing significant reduction of the channel peak temperature and improvement in the current-carrying capability and power density. Molecular dynamics simulations indicate that the interfacial thermal conductance of the heterostructure is facilitated by the high degree of overlap in the phonon vibrational spectra. The findings offer novel design insights for efficient heat dissipation in micro- and nanoelectronic devices.

Reinforcement Learning for FDA-MIMO Radar Power Allocation in Congested Spectral Environments

This paper studies the coexistence problem of frequency diverse array multiple-input multiple-output (FDA-MIMO) radar and communication systems. The communication system and radar share the same frequency band, and the overlap of the frequency spectrum will interfere with each other's performance, which constitutes a dynamic non-cooperative coexistence problem. We model the FDA-MIMO radar interference suppression process as a Markov decision process (MDP). The interference signals received by FDA-MIMO radar are generated by the communication system, including constant interference, frequency-hopping interference, and intermittent interference. FDA-MIMO radar realizes flexible transmission waveform spectrum control through transmission power allocation. Reinforcement learning (RL) is applied to obtain the optimal power allocation strategy of FDA-MIMO radar, and it is compared with the Sense and Avoid (SSA) algorithm. The simulation results show that the FDA-MIMO radar power allocation method based on reinforcement learning can effectively suppress the communication system's interference and improve the radar's signal-to-interference-and-noise ratio (SINR) and range resolution.

Porphyrin-BODIPY Dyad: Enhancing Photodynamic Inactivation via Antenna Effect.

A porphyrin-BODIPY dyad (P-BDP) was obtained through covalent bonding, featuring a two-segment design comprising a light-harvesting antenna system connected to an energy acceptor unit. The absorption spectrum of P-BDP resulted from an overlap of the individual spectra of its constituent parts, with the fluorescence emission of the BODIPY unit experiencing significant quenching (96 %) due to the presence of the porphyrin unit. Spectroscopic, computational, and redox investigations revealed a competition between photoinduced energy and electron transfer processes. The dyad demonstrated the capability to sensitize both singlet molecular oxygen and superoxide radical anions. Additionally, P-BDP effectively induced the photooxidation of L-tryptophan. In suspensions of Staphylococcus aureus cells, the dyad led to a reduction of over 3.5 log (99.99 %) in cell survival following 30 min of irradiation with green light. Photodynamic inactivation caused by P-BDP was also extended to the individual bacterium level, focusing on bacterial cells adhered to a surface. This dyad successfully achieved the total elimination of the bacteria upon 20 min of irradiation. Therefore, P-BDP presents an interesting photosensitizing structure that takes advantage of the light-harvesting antenna properties of the BODIPY unit combined with porphyrin, offering potential to enhance photoinactivation of bacteria.

SoundCount: Sound Counting from Raw Audio with Dyadic Decomposition Neural Network

In this paper, we study an underexplored, yet important and challenging problem: counting the number of distinct sounds in raw audio characterized by a high degree of polyphonicity. We do so by systematically proposing a novel end-to-end trainable neural network~(which we call DyDecNet, consisting of a dyadic decomposition front-end and backbone network), and quantifying the difficulty level of counting depending on sound polyphonicity. The dyadic decomposition front-end progressively decomposes the raw waveform dyadically along the frequency axis to obtain time-frequency representation in multi-stage, coarse-to-fine manner. Each intermediate waveform convolved by a parent filter is further processed by a pair of child filters that evenly split the parent filter's carried frequency response, with the higher-half child filter encoding the detail and lower-half child filter encoding the approximation. We further introduce an energy gain normalization to normalize sound loudness variance and spectrum overlap, and apply it to each intermediate parent waveform before feeding it to the two child filters. To better quantify sound counting difficulty level, we further design three polyphony-aware metrics: polyphony ratio, max polyphony and mean polyphony. We test DyDecNet on various datasets to show its superiority, and we further show dyadic decomposition network can be used as a general front-end to tackle other acoustic tasks.