Synthesis of histidine, serine and folic acid-functionalized and boron and iron-doped graphene quantum dot with excellent optical behavior and peroxidase-like activity for colorimetric and fluorescence detection of H2O2 in food.

Low fluorescence under visible light excitation and catalytic activity limit many applications of graphene quantum dots in optical detection, biosensing, catalysis and biomedical. The paper reports design and synthesis of histidine, serine and folic acid-functionalized and boron and iron-doped graphene quantum dot (Fe/B-GQD-HSF). The Fe/B-GQD-HSF shows excellent fluorescence behavior and peroxidase-like activity. Excitation of 330 nm ultraviolet light produces the strongest blue fluorescence and excitation of 480 nm visible light produces the strongest yellow fluorescence. The specific activity reaches 92.67 U g-1, which is higher than that of other graphene quantum dots. The Fe/B-GQD-HSF can catalyze oxidation of 3,3',5,5'-tetramethylbenzidine with H2O2 to form blue compound. Based on this, it was used for colorimetric and fluorescence detection of H2O2. The absorbance at 652 nm linearly increases with the increase of H2O2 concentration between 0.5 and 100 µM with detection limit of 0.43 µM. The fluorescence signal linearly decreases with the increase of H2O2 concentration between 0.05 and 100 µM with detection limit of 0.035 µM. The analytical method has been satisfactorily applied in detection of H2O2 in food. The study also paves one way for design and synthesis of functional graphene quantum dots with ideal fluorescence behavior and catalytic activity.

Optical Micro/Nanofiber Enabled Multiaxial Force Sensor for Tactile Visualization and Human-Machine Interface.

Tactile sensors with capability of multiaxial force perception play a vital role in robotics and human-machine interfaces. Flexible optical waveguide sensors have been an emerging paradigm in tactile sensing due to their high sensitivity, fast response, and antielectromagnetic interference. Herein, a flexible multiaxial force sensor enabled by U-shaped optical micro/nanofibers (MNFs) is reported. The MNF is embedded within an elastomer film topped with a dome-shaped protrusion. When the protrusion is subjected to vector forces, the embedded MNF undergoes anisotropic deformations, yielding time-resolved variations in light transmission. Detection of both normal and shear forces is achieved with sensitivities reaching 50.7 dB N-1 (14% kPa-1) and 82.2 dB N-1 (21% kPa-1), respectively. Notably, the structural asymmetry of the MNF induces asymmetrical optical modes, granting the sensor directional responses to four-directional shear forces. As proof-of-concept applications, tactile visualizations for texture and relief pattern recognition are realized with a spatial resolution of 160 µm. Moreover, a dual U-shaped MNF configuration is demonstrated as a human-machine interface for cursor manipulation. This work represents a step towards advanced multiaxial tactile sensing.

An easier life to come for mosquito researchers: field-testing across Italy supports VECTRACK system for automatic counting, identification and absolute density estimation of Aedes albopictus and Culex pipiens adults.

BACKGROUND: Disease-vector mosquito monitoring is an essential prerequisite to optimize control interventions and evidence-based risk predictions. However, conventional entomological monitoring methods are labor- and time-consuming and do not allow high temporal/spatial resolution. In 2022, a novel system coupling an optical sensor with machine learning technologies (VECTRACK) proved effective in counting and identifying Aedes albopictus and Culex pipiens adult females and males. Here, we carried out the first extensive field evaluation of the VECTRACK system to assess: (i) whether the catching capacity of a commercial BG-Mosquitaire trap (BGM) for adult mosquito equipped with VECTRACK (BGM + VECT) was affected by the sensor; (ii) the accuracy of the VECTRACK algorithm in correctly classifying the target mosquito species genus and sex; (iii) Ae. albopictus capture rate of BGM with or without VECTRACK. METHODS: The same experimental design was implemented in four areas in northern (Bergamo and Padua districts), central (Rome) and southern (Procida Island, Naples) Italy. In each area, three types of traps-one BGM, one BGM + VECT and the combination of four sticky traps (STs)-were rotated each 48 h in three different sites. Each sampling scheme was replicated three times/area. Collected mosquitoes were counted and identified by both the VECTRACK algorithm and operator-mediated morphological examination. The performance of the VECTRACK system was assessed by generalized linear mixed and linear regression models. Aedes albopictus capture rates of BGMs were calculated based on the known capture rate of ST. RESULTS: A total of 3829 mosquitoes (90.2% Ae. albopictus) were captured in 18 collection-days/trap/site. BGM and BGM + VECT showed a similar performance in collecting target mosquitoes. Results show high correlation between visual and automatic identification methods (Spearman Ae. albopictus: females = 0.97; males = 0.89; P < 0.0001) and low count errors. Moreover, the results allowed quantifying the heterogeneous effectiveness associated with different trap types in collecting Ae. albopictus and predicting estimates of its absolute density. CONCLUSIONS: Obtained results strongly support the VECTRACK system as a powerful tool for mosquito monitoring and research, and its applicability over a range of ecological conditions, accounting for its high potential for continuous monitoring with minimal human effort.

Can microplastic contamination affect the wing morphology and wingbeat frequency of Aedes aegypti (Diptera: Culicidae) mosquitoes?

Microplastics (MPs) are increasingly widespread in the environment, which raises questions about their potential effects at different biological levels. It is essential to assess the impacts on biodiversity, and it is also crucial to understand whether the presence of MPs can interfere with the biological traits of species of relevance in public health. Considering that the life-history traits of mosquitoes, such as size and the wingbeat frequency (WBF), are related to its vector competence, here, we study the effects of 106 particles L-1 (as expected concentration of MPs on the environment, using the polyethylene type) on WBF, as well as wing morphology, testing the Culicidae species found across all continents, Aedes aegypti, as an indicator. Results show that larvae survival and development were not affected by the tested concentration of MP. Geometric morphometrics showed some asymmetry in female mosquito wings, which were also smaller for individuals reared in MP suspension. As for WBF, results did not indicate any significant differences between females. Male mosquitoes, however, showed alterations in WBF and wing morphology, suggesting possible sex-specific reactions to microplastic exposure. Also, the combination of morphological parameters analyzed as covariates (wing centroid size and body weight) did not significantly affect WBF for both female and male mosquitoes. Overall, this study shows an inaugural investigation of the effects of MP on wing size and WBF on Ae. aegypti, shedding light on these parameters tested for a current pollution issue and its impact on a virus vector.

Investigation of the Robust Integration of Distributed Fibre Optic Sensors in Structural Concrete Components.

In recent times, the value of data has grown. This tendency is also observeable in the construction industry, where research and digitalisation are increasingly oriented towards the collection, processing and analysis of different types of data. In addition to planning data, measurement data is a main focus. fibre optic measurements offer a highly precise and comprehensive approach to data collection. It is, however, important to note that this technology is still in research regarding concrete structures. This paper presents two methods of integrating filigree sensors into concrete structures. The first approach entails wrapping a fibre around a tendon duct and analysing the installation and associated measurements. The second method involves bonding polyimide and acrylate-coated fibres with 2K epoxy and cyanoacrylate in the grooves of rebars, exposing them to chemical environments. The resulting measurement data is evaluated qualitatively and quantitatively to ascertain its resilience to environmental factors. These developed criteria are consolidated in a decision matrix. Fibre-adhesive combinations necessitate protection from chemical and mechanical influences. The limitations of the solutions are pointed out, and alternative options are proposed.

Single Crystal Ruddlesden-Popper and Dion-Jacobson Metal Halide Perovskites for Visible Light Photodetectors: Present Status and Future Perspectives.

2D metal halide perovskites (MHPs), mainly the studied Ruddlesden-Popper (RP) and Dion-Jacobson (DJ) phases, have gained enormous popularity as optoelectronic materials owing to their self-assembled multiple quantum well structures, tunable semiconducting properties, and improved structural stability compared to their bulk 3D counterparts. The performance of polycrystalline thin film devices is limited due to the formation of defects and trap states. However, as studied so far, single crystal-based devices can provide a better platform to improve device performance and investigate their fundamental properties more reliably. This Review provides the first comprehensive report on the emerging field of RP and DJ perovskite single crystals and their use in visible light photodetectors of varied device configurations. This Review structurally summarizes the 2D MHP single crystal growth methods and the parameters that control the crystal growth process. In addition, the characterization techniques used to investigate their crystal properties are discussed. The review further provides detailed insights into the working mechanisms as well as the operational performance of 2D MHP single crystal photodetector devices. In the end, to outline the present status and future directions, this Review provides a forward-looking perspective concerning the technical challenges and bottlenecks associated with the developing field of RP and DJ perovskite single crystals. Therefore, this timely review will provide a detailed overview of the fast-growing field of 2D MHP single crystal-based photodetectors as well as ignite new concepts for a wide range of applications including solar cells, photocatalysts, solar H2 production, neuromorphic bioelectronics, memory devices, etc.

Computational insights into the underlying mechanism of zinc ion-specificity of the fluorescent probe, BDA-1.

Ion specificity is crucial for developing fluorescence probes. Using a recently reported optical sensor (BDA-1) of Zn2+ as a representative, we carried out extensive quantum chemical calculations on its photophysical properties using density function theory. According to the calculated optimized geometries, excitation energies and transition oscillator strengths, the weak fluorescence of BDA-1 observed in experiments is attributed to the suppression of fluorescence emission by efficient internal conversion, rather than the previously proposed photoinduced electron transfer (PET) mechanism. With the addition of Zn2+ or Cd2+ ions, the tetradentate chelates [M:BDA-1-H+]+ (M=Zn, Cd) are produced. According to frontier molecular orbital and interfragment charge transfer analyses of these complexes, PET is preferentially confirmed to occur upon photo-excitation. Notably, as one coordination bond in the excited [Cd:BDA-1-H+]+ complex is significantly weakened in comparison to that of [Zn:BDA-1-H+]+, their molecular orbital compositions in the S1 state are completely different. As a result, absorption and radiation transitions of [Zn:BDA-1-H+]+ both have considerable oscillator strength, while fluorescence radiation from the excited [Cd:BDA-1-H+]+ is doubly suppressed. This difference causes that the fluorescence intensity of BDA-1 is sensitive to the addition of metal ions, and exhibits the zinc ion-specificity.

Reconfigurable Optical Sensor for Metal-Ion-Mediated Label-Free Recognition of Different Biomolecular Targets.

Reconfiguration of chemical sensors, intended as the capacity of the sensor to adapt to novel operational scenarios, e.g., new target analytes, is potentially game changing and would enable rapid and cost-effective reaction to dynamic changes occurring at healthcare, environmental, and industrial levels. Yet, it is still a challenge, and rare examples of sensor reconfiguration have been reported to date. Here, we report on a reconfigurable label-free optical sensor leveraging the versatile immobilization of metal ions through a chelating agent on a nanostructured porous silica (PSiO2) optical transducer for the detection of different biomolecules. First, we show the reversible grafting of different metal ions on the PSiO2 surface, namely, Ni2+, Cu2+, Zn2+, and Fe3+, which can mediate the interaction with different biomolecules and be switched under mild conditions. Then, we demonstrate reconfiguration of the sensor at two levels: 1) switching of the metal ions on the PSiO2 surface from Cu2+ to Zn2+ and testing the ability of Cu2+-functionalized and Zn2+-reconfigured devices for the sensing of the dipeptide carnosine (CAR), leveraging the well-known chelating ability of CAR toward divalent metal ions; and 2) reconfiguration of the Cu2+-functionalized PSiO2 sensor for a different target analyte, namely, the nucleotide adenosine triphosphate (ATP), switching Cu2+ with Fe3+ ions to exploit the interaction with ATP through phosphate groups. The Cu2+-functionalized and Zn2+-reconfigured sensors show effective sensing performance in CAR detection, also evaluated in tissue samples from murine brain, and so does the Fe3+-reconfigured sensor toward ATP, thus demonstrating effective reconfiguration of the sensor with the proposed surface chemistry.

An emerging assay for rapid diagnosis of live Salmonella Typhimurium by exploiting aqueous/liquid crystal interface.

The rapid and accurate identification of live pathogens with high proliferative ability is in great demand to mitigate foodborne infection outbreaks. Herein, we have developed an ultrasensitive image-based aptasensing array to directly detect live Salmonella typhimurium (S.T) cells. This method relies on the long-range orientation of surfactant-decorated liquid crystals (LCs) and the superiority of aptamers (aptST). The self-assembling of hydrophobic surfactant tails leads to a perpendicular/vertical ordered film at the aqueous/LC interface and signal-off response. The addition of aptST perturbed LCs' ordering into a planar/tilted state at the aqueous phase due to electrostatic interactions between the surfactant with the aptST, and a signal-on response. Following the conformational switch of aptST in the presence of live S. typhimurium, a relative reversing signal-off response was observed upon the target concentration. This aptasensor could promptly confirm the presence of S. typhimurium without intricate DNA-extraction or pre-enrichment stats over a linear range of 1-1.1 × 106 CFU/mL and a detection limit of 1.2 CFU/mL within ∼30 min. These results were successfully validated using molecular and culture-based methods in spiked-milk samples, with a 92.61-104.61 % recovery value. Meanwhile, the flexibility of this portable sensing platform allows for its development and adoption for the precise detection of various pathogens in food and the environment.

Chromoionophoric molecular probe infused bimodal porous polymer rostrum as solid-state ocular sensor for the selective and expeditious optical sensing of ultra-trace toxic mercury ions.

This study presents a distinctive solid-state naked-eye colorimetric sensing approach by encapsulating a chromoionophoric probe onto a hybrid macro-/meso-pore polymer scaffold for fast and selective sensing of ultra-trace Hg(II). The customized structural/surface properties of the poly(VPy-co-TM) monolith are attained by specific proportions of 2-vinylpyridine (VPy), trimethylolpropane trimethacrylate (TM), and pore-tuning solvents. The interconnected porous network of poly(VPy-co-TM), inherent superior surface area and porosity, is captivating for the homogeneous/voluminous incorporation of probe molecules, i.e., 7-((4-methoxyphenyl)diazenyl)quinoline-8-ol (MPDQ), for the target-specific colorimetric detection. The structural morphology, surface topography, and phase characteristics of the bare poly(VPy-co-TM) monolith and MPDQ@poly(VPy-co-TM) sensor are examined using HR-TEM-SAED (High-Resolution Transmission Electron Microscopy - Selected Area Electron Diffraction), FE-SEM-EDAX (Field Emission Scanning Electron Microscopy - Energy Dispersive X-ray Spectroscopy), XPS (X-ray Photoelectron Spectroscopy), p-XRD (Powder X-Ray Diffraction), FT-IR (Fourier Transform Infrared Spectroscopy), UV-Vis-DRS (Ultraviolet-Visible Diffuse Reflectance Spectroscopy), and BET/BJH (Brunauer-Emmett-Teller / Barrett-Joyner-Halenda) analysis. The distinctive properties of the sensor reveal a constrained geometrical orientation of the MPDQ probe onto the long-range continuous monolithic network of meso-/-macropore template, enabling selective interaction with Hg(II) with peculiar color transfiguration from pale yellow to deep brown. The sensor demonstrates a linear spectral-color alliance in the 0-200 ppb concentration range for Hg(II), with quantification and detection limits of 0.63 and 0.19 ppb. The sensor efficacy is verified using certified contaminated water and tobacco samples, with excellent reusability, reliability, and reproducibility of ≥ 99.23 % (RSD ≤1.89 %) and ≥ 99.19 % (RSD ≤1.94 %) of Hg(II), respectively.

Elevating nanomaterial optical sensor arrays through the integration of advanced machine learning techniques for enhancing visual inspection of food quality and safety.

Food quality and safety problems caused by inefficient control in the food chain have significant implications for human health, social stability, and economic progress and optical sensor arrays (OSAs) can effectively address these challenges. This review aims to summarize the recent applications of nanomaterials-based OSA for food quality and safety visual monitoring, including colourimetric sensor array (CSA) and fluorescent sensor array (FSA). First, the fundamental properties of various advanced nanomaterials, mainly including metal nanoparticles (MNPs) and nanoclusters (MNCs), quantum dots (QDs), upconversion nanoparticles (UCNPs), and others, were described. Besides, the diverse machine learning (ML) and deep learning (DL) methods of high-dimensional data obtained from the responses between different sensing elements and analytes were presented. Moreover, the recent and representative applications in pesticide residues, heavy metal ions, bacterial contamination, antioxidants, flavor matters, and food freshness detection were comprehensively summarized. Finally, the challenges and future perspectives for nanomaterials-based OSAs are discussed. It is believed that with the advancements in artificial intelligence (AI) techniques and integrated technology, nanomaterials-based OSAs are expected to be an intelligent, effective, and rapid tool for food quality assessment and safety control.

Ppb-Level Ammonia Sensor for Exhaled Breath Diagnosis Based on UV-DOAS Combined with Spectral Reconstruction Fitting Neural Network.

Ammonia (NH3) in exhaled breath (EB) has been a biomarker for kidney function, and accurate measurement of NH3 is essential for early screening of kidney disease. In this work, we report an optical sensor that combines ultraviolet differential optical absorption spectroscopy (UV-DOAS) and spectral reconstruction fitting neural network (SRFNN) for detecting NH3 in EB. UV-DOAS is introduced to eliminate interference from slow change absorption in the EB spectrum while spectral reconstruction fitting is proposed for the first time to map the original spectra onto the sine function spectra by the principle of least absolute deviations. The sine function spectra are then fitted by the least-squares method to eliminate noise signals and the interference of exhaled nitric oxide. Finally, the neural network is built to enable the detection of NH3 in EB at parts per billion (ppb) level. The laboratory results show that the detection range is 9.50-12425.82 ppb, the mean absolute percentage error (MAPE) is 0.83%, and the detection accuracy is 0.42%. Experimental results prove that the sensor can detect breath NH3 and identify EB in simulated patients and healthy people. Our sensor will serve as a new and effective system for detecting breath NH3 with high accuracy and stability in the medical field.

A novel spectrofluorimetric method using optical sensor Eu3+-ACAC as a highly selective photo probe to determine Pregabalin in biological samples and pharmaceutical form.

A novel spectrofluorimetric method with high selectivity and sensitivity was created to determine Pregabalin (PG) in pharmaceutical form, human serum, and urine. This method relies on detecting quenching in the intensity of luminescence of the europium acetylacetone complex (Eu3+-ACAC) at emission wavelength λem = 616 nm, which results from interaction with various concentrations of PG after excitation at λex = 395 nm and pH 6.5 in dimethylformamide (DMF). The calibration curve was generated using concentrations ranging from 7.6 × 10-8 to 6.3 × 10-6 mol/L. The plot showed a high correlation coefficient (r2) of 0.994 with a detection limit (LOD) of 2.81 × 10-8 mol/L and a quantification limit (LOQ) of 8.5 × 10-8 mol/L. The remarkable luminescence intensity quenching of the Eu3+-ACAC by ranged concentrations of PG was effectively employed as a photo probe to determine PG in marketable form and different body fluids. Spectroscopic characterization, such as absorption and emission spectra, confirmed the obtained sensor. The improved method is verified using a range of characteristics, such as accuracy, precision, selectivity, linearity, and robustness.

Portable point-of-care surface enhanced Raman scattering spectroscopy for the quantification of glutathione in whole blood microsamples.

Glutathione (GSH) is a non-protein tripeptide thiol that plays a prominent role in oxidative stress defense. GSH concentration is particularly critical in the neonatal period, especially for premature newborns that face increased susceptibility to oxidative stress. Monitoring GSH levels provides valuable insights into newborn health, helping to tailor care to their specific needs. The aim of this study was the development of a sensor specifically targeted for its use in neonatology, enabling GSH determination in only 2 µL of whole blood. The newly developed sensing system simplifies sample processing, addressing a critical need in clinical applications. Unlike current methods that demand fast pre-processing of relatively large sample volumes, expensive equipment, and skilled personnel, the developed approach streamlines the analytical process. By using 2 µL of whole blood, a single syringe filter for sample treatment, a deuterated internal standard (IS) for signal normalization, and Surface Enhanced Raman Scattering (SERS) spectroscopy with a silver colloid substrate for GSH detection, the set-up's characteristics are compatible with point-of-care applications. The analytical procedure was validated and applied to diverse populations including healthy adults (N = 63) and newborns (N = 35), yielding GSH concentration values ranging from 0.6 to 1.8 and 0.8-2.1 mM, respectively. This new optical sensor offers a quick and cost-effective solution to support the assessment of GSH levels in newborns that can greatly benefit not only neonatal care, but also the study of adult populations for health monitoring.

An Optical Sensor for Measuring Displacement between Parallel Surfaces.

An optoelectronic sensor was developed to measure the in-plane displacement between two parallel surfaces. This sensor used a photodetector, which was placed on one of the parallel surfaces, to measure the intensity of the red (R), green (G), blue (B), and white/clear (C) light spectra of a broad-spectrum light that was reflected off a color grid on the opposing surface. The in-plane displacement between these two surfaces caused a change in the reflected RGB and C light intensity, allowing the prediction of the displacement direction and magnitude by using a polynomial regression prediction algorithm to convert the RGB and C light intensity to in-plane displacement. Results from benchtop experiments showed that the sensor can achieve accurate displacement predictions with a coefficient of determination R2 > 0.97, a root mean squared error (RMSE) < 0.3 mm, and a mean absolute error (MAE) < 0.36 mm. By measuring the in-plane displacement between two surfaces, this sensor can be applied to measure the shear of a flexible layer, such as a shoe's insole or the lining of a limb prosthesis. This sensor would allow slippage detection in wearable devices such as orthotics, prostheses, and footwear to quantify the overfitting or underfitting of these devices.

SiNx/SiO2-Based Fabry-Perot Interferometer on Sapphire for Near-UV Optical Gas Sensing of Formaldehyde in Air.

Fabry-Perot interferometers (FPIs), comprising foundry-compatible dielectric thin films on sapphire wafer substrates, were investigated for possible use in chemical sensing. Specifically, structures comprising two vertically stacked distributed Bragg reflectors (DBRs), with the lower DBR between a sapphire substrate and a silicon-oxide (SiO2) resonator layer and the other DBR on top of this resonator layer, were investigated for operation in the near-ultraviolet (near-UV) range. The DBRs are composed of a stack of nitride-rich silicon-nitride (SiNx) layers for the higher index and SiO2 layers for the lower index. An exemplary application would be formaldehyde detection at sub-ppm concentrations in air, using UV absorption spectroscopy in the 300-360 nm band, while providing spectral selectivity against the main interfering gases, notably NO2 and O3. Although SiNx thin films are conventionally used only for visible and near-infrared optical wavelengths (above 450 nm) because of high absorbance at lower wavelengths, this work shows that nitride-rich SiNx is suitable for near-UV wavelengths. The interplay between spectral absorbance, transmittance and reflectance in a FPI is presented in a comparative study between one FPI design using stoichiometric material (Si3N4) and two designs based on N-rich compositions, SiN1.39 and SiN1.49. Spectral measurements confirm that if the design accounts for phase penetration depth, sufficient performance can be achieved with the SiN1.49-based FPI design for gas absorption spectroscopy in near-UV, with peak transmission at 330 nm of 64%, a free spectral range (FSR) of 20 nm and a full-width half-magnitude spectral resolution (FWHM) of 2 nm.

Nanoplasmonic sensors for extracellular vesicles and bacterial membrane vesicles.

Extracellular vesicles (EVs) are promising tools for the early diagnosis of diseases, and bacterial membrane vesicles (MVs) are especially important in health and environment monitoring. However, detecting EVs or bacterial MVs presents significant challenges for the clinical translation of EV-based diagnostics. In this Review, we provide a comprehensive discussion on the basics of nanoplasmonic sensing and emphasize recent developments in nanoplasmonics-based optical sensors to effectively identify EVs or bacterial MVs. We explore various nanoplasmonic sensors tailored for EV or bacterial MV detection, emphasizing the application of localized surface plasmon resonance through gold nanoparticles and their multimers. Additionally, we highlight advanced EV detection techniques based on surface plasmon polaritons using plasmonic thin film and nanopatterned structures. Furthermore, we evaluate the improved detection capability of surface-enhanced Raman spectroscopy in identifying and classifying these vesicles, aided by plasmonic nanostructures. Nanoplasmonic sensing techniques have remarkable precision and sensitivity, making them a potential tool for accurate EV detection in clinical applications, facilitating point-of-care molecular diagnostics. Finally, we summarize the challenges associated with nanoplasmonic EV or bacterial MV sensors and offer insights into potential future directions for this evolving field.

Particulate matter forecast and prediction in Curitiba using machine learning.

Introduction: Air quality is directly affected by pollutant emission from vehicles, especially in large cities and metropolitan areas or when there is no compliance check for vehicle emission standards. Particulate Matter (PM) is one of the pollutants emitted from fuel burning in internal combustion engines and remains suspended in the atmosphere, causing respiratory and cardiovascular health problems to the population. In this study, we analyzed the interaction between vehicular emissions, meteorological variables, and particulate matter concentrations in the lower atmosphere, presenting methods for predicting and forecasting PM2.5. Methods: Meteorological and vehicle flow data from the city of Curitiba, Brazil, and particulate matter concentration data from optical sensors installed in the city between 2020 and 2022 were organized in hourly and daily averages. Prediction and forecasting were based on two machine learning models: Random Forest (RF) and Long Short-Term Memory (LSTM) neural network. The baseline model for prediction was chosen as the Multiple Linear Regression (MLR) model, and for forecast, we used the naive estimation as baseline. Results: RF showed that on hourly and daily prediction scales, the planetary boundary layer height was the most important variable, followed by wind gust and wind velocity in hourly or daily cases, respectively. The highest PM prediction accuracy (99.37%) was found using the RF model on a daily scale. For forecasting, the highest accuracy was 99.71% using the LSTM model for 1-h forecast horizon with 5 h of previous data used as input variables. Discussion: The RF and LSTM models were able to improve prediction and forecasting compared with MLR and Naive, respectively. The LSTM was trained with data corresponding to the period of the COVID-19 pandemic (2020 and 2021) and was able to forecast the concentration of PM2.5 in 2022, in which the data show that there was greater circulation of vehicles and higher peaks in the concentration of PM2.5. Our results can help the physical understanding of factors influencing pollutant dispersion from vehicle emissions at the lower atmosphere in urban environment. This study supports the formulation of new government policies to mitigate the impact of vehicle emissions in large cities.

Recent Advances in Organic Small-Molecule Fluorescent Probes for the Detection of Zinc Ions (Zn2+).

Zinc(II) ions (Zn2g) play crucial roles in the growth, propagation, and metabolism of animals, plants, and humans. Abnormal concentrations of Zn2+ in the environment and living organisms pose potential risks to environmental protection and human health. Therefore, it is imperative to develop rapid, reliable and in-situ detection methods for Zn2+ in both environmental and biological contexts. Furthermore, effective analytical methods are required for diagnosing diseases and understanding physiological metabolic mechanisms associated with Zn2+ concentration levels. Organic small-molecule fluorescent probes offer advantages such as fast, reliable, convenient, non-destructive detection capabilities and have significant application potential in Zn2+ detection and bioimaging; thus garnering extensive attention. Over the past two years alone, various organic small-molecule probes for Zn2+ based on different detection mechanisms and fluorophores have been rapidly developed. However, these probes still exhibit several limitations that need further resolution. In light of this context, we provide a comprehensive summary of the detection mechanisms, performance characteristics, and application scope of Zn2+ fluorescence probes since year 2022 while highlighting their advantages. We also propose solutions to address existing issues with these probes and outline future directions for their advancement. This review aims to serve as a valuable reference source offering insights into the development of advanced organic small-molecule-based fluorescence probes specifically designed for detecting Zn2+.

High-Performance Refractive Index and Temperature Sensing Based on Toroidal Dipole in All-Dielectric Metasurface.

This article shows an all-dielectric metasurface consisting of "H"-shaped silicon disks with tilted splitting gaps, which can detect the temperature and refractive index (RI). By introducing asymmetry parameters that excite the quasi-BIC, there are three distinct Fano resonances with nearly 100% modulation depth, and the maximal quality factor (Q-factor) is over 104. The predominant roles of different electromagnetic excitations in three distinct modes are demonstrated through near-field analysis and multipole decomposition. A numerical analysis of resonance response based on different refractive indices reveals a RI sensitivity of 262 nm/RIU and figure of merit (FOM) of 2183 RIU-1. This sensor can detect temperature fluctuations with a temperature sensitivity of 59.5 pm/k. The proposed metasurface provides a novel method to induce powerful TD resonances and offers possibilities for the design of high-performance sensors.