Search Results (23)

Belle II is a particle physics experiment working at an high luminosity collider within a hard irradiation environment. The Time-Of-Propagation detector, aimed at the charged particle identification, surrounds the Belle II tracking detector on the barrel part. This detector is composed by 16 modules, each module contains a finely fused silica bar, coupled to microchannel plate photomultiplier tube (MCP-PMT) photo-detectors and readout by high-speed electronics. The MCP-PMT lifetime at the nominal collider luminosity is about one year, this is due to the high photon background degrading the quantum efficiency of the photocathode. An alternative to these MCP-PMTs is multi-pixel photon counters (MPPC), known as silicon photomultipliers (SiPM). The SiPMs, in comparison to MCP-PMTs, have a lower cost, higher photon detection efficiency and are unaffected by the presence of a magnetic field, but also have a higher dark count rate that rapidly increases with the integrated neutron flux. The dark count rate can be mitigated by annealing the damaged devices and/or operating them at low temperatures. We tested SiPMs, with different dimensions and pixel sizes from different producers, to study their time resolution (the main constraint that has to satisfy the photon detector) and to understand their behavior and tolerance to radiation. For these studies we irradiated the devices to radiation up to $5\times {10}^{11}1$ MeV neutrons equivalent (neq) per cm² fluences; we also started studying the effect of annealing on dark count rates. We performed several measurements on these devices, on top of the dark count rate, at different conditions in terms of overvoltage and temperatures. These measurements are: IV-curves, amplitude spectra, time resolution. For the last two measurements we illuminated the devices with a picosecond pulsed laser at very low intensities (with a number of detected photons up to about twenty). We present results mainly on two types of SiPMs. A new SiPM prototype developed in collaboration with FBK with the aim of improving radiation hardness, is expected to be delivered in September 2025. Full article

Coastal cities and low-lying areas are increasingly vulnerable, and accurate data is needed to identify where interventions are most required. We compared 53 cities affected by a 1 m increase in land levels and a 2 m rise in sea levels. The geographical scope of this study covered selected coastal cities in Europe and northern Africa. Data were sourced from the European Environment Agency (EEA) in the form of prepared datasets, which were further processed for analysis. Statistical methods were applied to compare the extent of urban flooding under two sea level rise scenarios—1 m and 2 m—by calculating the percentage of affected urban areas. To assess social vulnerability, the analysis included several variables: MAPF65 (Mean Area Potentially Flooded for people aged 65 and older, indicating elderly exposure), Age (the percentage of the population aged 65+ in each city), MAPF (Mean Area Potentially Flooded, representing the average share of urban area at risk of flooding), and Unemployment Ratio (the percentage of unemployed individuals living in the areas potentially affected by sea level rise). We utilized t-tests to analyze the means of two datasets, yielding a mean difference of 2.9536. Both parametric and bootstrap confidence intervals included zero, and the p-values from the t-tests (0.289 and 0.289) indicated no statistically significant difference between the means. The Bayes factor (0.178) provided substantial evidence supporting equal means, while Cohen’s D (0.099) indicated a very small effect size. Ceuta’s flooding value (502.8) was identified as a significant outlier (p < 0.05), indicating high flood risk. A Grubbs’ test confirmed Ceuta as a significant outlier. A Wilcoxon test highlighted significant deviations between the medians, with a p << 0.001, demonstrating systematic discrepancies tied to flood frequency and sea level anomalies. These findings illuminated critical disparities in flooding trends across specific locations, offering essential insights for urban planning and mitigation strategies in cities vulnerable to rising sea levels and extreme weather patterns. Information on coastal flooding provides awareness of how rising sea levels affect at-risk areas. Examining factors such as MAPF and population data enables the detection of the most threatened zones and supports targeted action. These perceptions are essential for strengthening climate resilience, improving emergency planning, and directing resources where they are needed most. Full article

Small-scale inshore fisheries significantly contribute to the total landing volumes and have an important role in Vietnamese socioeconomic development, food security, livelihoods, and social well-being. The setnet fishery has been used throughout coastal communities of Vietnam for many decades. Being a passive fishing gear, the catch efficiency of setnet depends on various conditions such as fish density, season, oceanography, environment, and others. However, very little information exists about the relationship between catch rates and national conditions. Recognizing this research gap, this study examined the effect of temporal and environmental conditions on the catch rates of the narrow-barred Spanish mackerel (Scomberomorus commerson) setnet fishery using long-term data from 2005 to 2016. Overall, the catch of narrow-barred Spanish mackerel decreased over the course of the study. The generalized additive model (GAM) showed that catch rates were significantly affected by sea surface temperature (SST), which peaked at 27 °C. After this temperature point, the catch rates significantly decreased. Temporal variables also contributed to the catch variation. The setnet caught the highest yield in April and May, and more fish were caught during periods of low nightlight intensity than during high illuminated periods. Our study contributes to the understanding of critical factors affecting the catch rates of valuable species, which helps to determine the optimal fishing process of the setnet fishery within the shifting of marine heatwaves. Full article

Passive radar has become very popular in recent years because it is usually undetectable, and countermeasures used to prevent its functioning are complex and, in general, easily identified. Terrestrial digital video broadcasting (DVB-T) is commonly used as an opportunistic illumination signal because of its large range and widespread deployment, both of which make it applicable to almost all scenarios. This paper presents the design of a compact and robust receiver for passive radar that uses a low number of antenna while achieving high accuracy. In order to do this, we use an iterative algorithm to refine the initial estimations based on time-domain channel information to converge to the true estimations. This is especially effective when the signal-to-noise-ratio (SNR) at the receiver is moderate and/or there are several reflections in the environment that may introduce some error into schemes that perform the angle of arrival or time of arrival for the estimation. The algorithm proposed herein is able to accurately estimate the position of a target with a low SNR. Full article

Training in team sports such as soccer requires advanced technical and tactical skills for effective decision-making, particularly when executing a shot. This study validates an innovative instrument, a training platform (TP), designed to measure and enhance decision-making in dual-task scenarios. The TP aims to improve visual–motor reactions in multitask environments that simulate real game conditions. Equipped with an LED panel, main circuitry, ball sensor, and targets, the TP challenges players to kick the ball in response to the illumination of the final LED array on the panel while hitting a designated target. The study evaluated three parameters: reaction time (RT), ball speed (BS) and accuracy. To validate the TP against a gold standard (GS), we conducted correlation analyses. The results exhibited very strong correlations for both RT (r = 0.997) and BS (r = 0.994). The mean differences between TP and GS measurements were 13 ± 15 ms for RT and 0.1 ± 0.5 km/h for BS. Bland–Altman plots revealed trend lines obtained by a simple linear regression of r = −0.507, p = 0.307 for RT and r = 0.134, p = 0.077 for BS. The TP effectively simulates game scenarios, offering advantages such as low-cost components, installation flexibility, test variability, instant feedback, and integration of physical and cognitive components of sports performance. Full article

With the acceleration of population aging, the elderly driving safety issue is increasingly prominent. Method: With the crash data of Pennsylvania from 2010 to 2019, this study exclusively discusses features of single-vehicle hit-fixed-object crashes (SVHFOCs), one of the most common and deadliest crash types for elderly drivers. Results: Firstly, we demonstrate that elderly drivers are much more likely to be injured and killed than young drivers in SVHFOCs by checking crash consequences. The descriptive analysis indicates that elderly drivers have very different crash features from young drivers. They are found to drive with more caution in many aspects, such as more low-speed local travels, fewer illegal behaviors, fewer nighttime travels, etc. Then, a logistic regression model is built to find the factors significantly influencing the severity of SVHFOCs from driver, vehicle, roadway, and environment. The estimation results indicate that female sex, not wearing a seatbelt, DUI, rural area, and SUV involvement tend to be associated with more severe SVHFOCs. Additionally, illumination, weather, and road type could also significantly affect crash severity. Especially, SVHFOCs in adverse weather, in dark conditions, and at intersections are found to be less severe, which implies that elderly drivers might drive more carefully in complex environments. Practical Applications: These findings are expected to provide new insights for agencies in formulating customized measures to prevent elderly drivers from being involved in SVHFOCs. Full article

A label-free biosensor based on a tunable MEMS metamaterial structure is proposed in this paper. The adopted structure is a one-dimensional array of metamaterial gratings with movable and fixed fingers. The moving unit of the optical detection system is a component of the MEMS structure, driven by the surface stress effect. Thus, these suspended optical nanoribbons can be moved and change the grating pattern by the biological bonds that happened on the modified cantilever surface. Such structural variations lead to significant changes in the optical response of the metamaterial system under illuminating angled light and subsequently shift its resonance wavelength spectrum. As a result, the proposed biosensor shows appropriate analytical characteristics, including the mechanical sensitivity of S_m = 11.55 μm/Nm⁻¹, the optical sensitivity of S_o = Δλ/Δd = 0.7 translated to S_o = Δλ/Δσ = 8.08 μm/Nm⁻¹, and the quality factor of Q = 102.7. Also, considering the importance of multi-biomarker detection, a specific design of the proposed topology has been introduced as an array for identifying different biomolecules. Based on the conducted modeling and analyses, the presented device poses the capability of detecting multiple biomarkers of disease at very low concentrations with proper precision in fluidic environments, offering a suitable bio-platform for lab-on-chip structures. Full article

The defining attribute of self-excited motion is its capability to extract energy from a stable environment and regulate it autonomously, making it an extremely promising innovation for microdevices, autonomous robotics, sensor technologies, and energy generation. Based on the concept of an automobile, we propose a light-fueled self-propulsion of liquid crystal elastomer-engined automobiles in zero-energy mode. This system utilizes a wheel comprising a liquid crystal elastomer (LCE) turntable as an engine, a wheel with conventional material and a linkage. The dynamic behavior of the self-propulsion automobile under steady illumination is analyzed by integrating a nonlinear theoretical model with an established photothermally responsive LCE model. We performed the analysis using the fourth-order Runge–Kutta method. The numerical findings demonstrate the presence of two separate motion patterns in the automobile system: a static pattern and a self-propulsion pattern. The correlation between the energy input and energy dissipation from damping is essential to sustain the repetitive motion of the system. This study delves deeper into the crucial requirements for initiating self-propulsion and examines the effect of critical system parameters on the motion of the system. The proposed system with zero-energy mode motions has the advantage of a simple structural design, easy control, low friction and stable kinematics, and it is very promising for many future uses, including energy harvesting, monitoring, soft robotics, medical devices, and micro- and nano-devices. Full article

Titanium dioxide (TiO₂) nanoparticles (NPs) are the subject of numerous studies and controversies on the risks they could pose to the environment and human health. When in contact with biological tissues, NPs can sometimes be challenging to precisely localize within subcellular structures (typically around 0.1 µm) when they exist as isolated NPs, particularly when using the SIMS approach. Indeed, the chemical signals produced by isolated NPs are very low, so they can be confused with background signals. This was the motivation behind our development of a new strategy for correlating TEM/SIMS to detect TiO₂ NPs in close proximity to cutaneous corneocytes. For this purpose, we initially developed a new tool for TEM and SIMS image registration based on a non-rigid image-deformation-enabling image overlay. Combining SIMS and TEM data through this overlay enhances NP localization’s precision. Secondly, we developed an algorithm based on the statistical analysis of multiplane SIMS images to denoise them. As a result, background noise was reduced, illuminating the low yet specific signals from isolated NPs. Finally, this new correlative approach enables the precise 3D localization of isolated NPs within the analyzed volume. We consider this method a breakthrough for subcellular-scale NP localization. Full article

Fire accidents threaten public safety. One of the greatest challenges during fire rescue is that firefighters need to find objects as quickly as possible in an environment with strong flame luminosity and dense smoke. This paper reports an optical method, called violet illumination, coupled with deep learning, to significantly increase the effectiveness in searching for and identifying rescue targets during a fire. With a relatively simple optical system, broadband flame luminosity can be spectrally filtered out from the scattering signal of the object. The application of deep learning algorithms can further and significantly enhance the effectiveness of object search and identification. The work shows that this novel optics–deep learning combined method can improve the object identification accuracy from 7.0% with the naked eye to 83.1%. A processing speed of 10 frames per second can also be achieved on a single CPU. These results indicate that the optical method coupled with machine learning algorithms can potentially be a very useful technique for object searching in fire rescue, especially considering the emergence of low-cost, powerful, compact violet light sources and the rapid development of machine learning methods. Potential designs for practical systems are also discussed. Full article

Formamidine lead iodide (FAPbI₃) perovskite material is very suitable for solar photovoltaic devices because of its ideal low band gap, theoretically high efficiency, and wide range of solar spectral absorption, coupled with its good thermal stability. A two-step spin coating method could control the crystallization process of formamidine lead iodide perovskite films better, resulting in more easily repeatable high-quality films. However, it is still difficult to avoid the formation of halide I-vacancy during the preparation of films, which will affect device performance and stability. In this paper, we added small molecular formamidine formate (FAHCOO) into the PbI₂ precursor solution. Due to the high binding energy between HCOO⁻ and I-vacancy, film defects caused by I-vacancies could be passivated. A molecular exchange process could be introduced in the two-step method with the addition of FAHCOO. The exchange process could delay the crystallization process in perovskite films and make them transform more fully; thus, ultimately improving the crystallization quality of the films. In addition, by adding FAHCOO to the PbI₂ precursor solution, a small number of FAPbI₃ can be pre-generated as templates. These templates could induce the growth of specific crystal planes of FAPbI₃ in the second step reaction; thereby, improving the crystallinity of FAPbI₃ films. The FAPbI₃ of devices with optimized FAHCOO show a champion power conversion efficiency (PCE) of 19.04%, apparently higher than that of the controlled devices without FAHCOO (16.69%). For working stability tests under AM 1.5G illumination in an air environment, PSCs with FAHCOO showed nearly 100% of their initial efficiency after a 4100 s tracking test, while the original control device dropped to about 94%. Full article

The release of mercury into the environment has adverse effects on humans and aquatic species, even at very low concentrations. Pyrene and its derivatives have interesting fluorescence properties that can be utilized for mercury (Hg²⁺) ion sensing. Herein, we reported the highly selective pyrene-functionalized silica nanoparticles (Pyr-NH@SiO₂ NPs) for chemosensing mercury (Hg²⁺) ions in a seawater sample. The Pyr-NH@SiO₂ NPs were synthesized via a two-step protocol. First, a modified Stöber method was adopted to generate amino-functionalized silica nanoparticles (NH₂@SiO₂ NPs). Second, 1-pyrenecarboxylic acid was coupled to NH₂@SiO₂ NPs using a peptide coupling reaction. As-synthesized NH₂@SiO₂ NPs and Pyr-NH@SiO₂ NPs were thoroughly investigated by ¹H-NMR, FTIR, XRD, FESEM, EDS, TGA, and BET surface area analysis. The fluorescent properties were examined in deionized water under UV-light illumination. Finally, the developed Pyr-NH@SiO₂ NPs were tested as a chemosensor for Hg²⁺ ions detection in a broad concentration range (0–50 ppm) via photoluminescence (PL) spectroscopy. The chemosensor can selectively detect Hg²⁺ ions in the presence of ubiquitous ions (Na⁺, K⁺, Ca²⁺, Mg²⁺, Ba²⁺, Ag⁺, and seawater samples). The quenching of fluorescence properties with Hg²⁺ ions (LOD: 10 ppb) indicates that Pyr-NH@SiO₂ NPs can be effectively utilized as a promising chemosensor for mercury ion detection in seawater environments. Full article

Landing an unmanned aerial vehicle (UAV) autonomously and safely is a challenging task. Although the existing approaches have resolved the problem of precise landing by identifying a specific landing marker using the UAV’s onboard vision system, the vast majority of these works are conducted in either daytime or well-illuminated laboratory environments. In contrast, very few researchers have investigated the possibility of landing in low-illumination conditions by employing various active light sources to lighten the markers. In this paper, a novel vision system design is proposed to tackle UAV landing in outdoor extreme low-illumination environments without the need to apply an active light source to the marker. We use a model-based enhancement scheme to improve the quality and brightness of the onboard captured images, then present a hierarchical-based method consisting of a decision tree with an associated light-weight convolutional neural network (CNN) for coarse-to-fine landing marker localization, where the key information of the marker is extracted and reserved for post-processing, such as pose estimation and landing control. Extensive evaluations have been conducted to demonstrate the robustness, accuracy, and real-time performance of the proposed vision system. Field experiments across a variety of outdoor nighttime scenarios with an average luminance of 5 lx at the marker locations have proven the feasibility and practicability of the system. Full article

Human recognition in indoor environments occurs both during the day and at night. During the day, human recognition encounters performance degradation owing to a blur generated when a camera captures a person’s image. However, when images are captured at night with a camera, it is difficult to obtain perfect images of a person without light, and the input images are very noisy owing to the properties of camera sensors in low-illumination environments. Studies have been conducted in the past on face recognition in low-illumination environments; however, there is lack of research on face- and body-based human recognition in very low illumination environments. To solve these problems, this study proposes a modified enlighten generative adversarial network (modified EnlightenGAN) in which a very low illumination image is converted to a normal illumination image, and the matching scores of deep convolutional neural network (CNN) features of the face and body in the converted image are combined with a score-level fusion for recognition. The two types of databases used in this study are the Dongguk face and body database version 3 (DFB-DB3) and the ChokePoint open dataset. The results of the experiment conducted using the two databases show that the human verification accuracy (equal error rate (ERR)) and identification accuracy (rank 1 genuine acceptance rate (GAR)) of the proposed method were 7.291% and 92.67% for DFB-DB3 and 10.59% and 87.78% for the ChokePoint dataset, respectively. Accordingly, the performance of the proposed method was better than the previous methods. Full article

The physiology and behavior of most life at or near the Earth’s surface has evolved over billions of years to be attuned with our planet’s natural light–dark cycle of day and night. However, over a relatively short time span, humans have disrupted this natural cycle of illumination with the introduction and now widespread proliferation of artificial light at night (ALAN). Growing research in a broad range of fields, such as ecology, the environment, human health, public safety, economy, and society, increasingly shows that ALAN is taking a profound toll on our world. Much of our current understanding of light pollution comes from datasets generated by remote sensing, primarily from two missions, the Operational Linescan System (OLS) instrument of the now-declassified Defense Meteorological Satellite Program (DMSP) of the U.S. Department of Defense and its follow-on platform, the Day-Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on board the Suomi National Polar-Orbiting Partnership satellite. Although they have both proved invaluable for ALAN research, sensing of nighttime lights was not the primary design objective for either the DMSP-OLS or VIIRS-DNB instruments; thus, they have some critical limitations. Being broadband sensors, both the DMSP-OLS and VIIRS-DNB instruments suffer from a lack of spectral information. Additionally, their spatial resolutions are too low for many ALAN research applications, though the VIIRS-DNB instrument is much improved over the DMSP-OLS in this regard, as well as in terms of dynamic range and quantization. Further, the very late local time of VIIRS-DNB observations potentially misses the true picture of ALAN. We reviewed both current literature and guiding advice from ALAN experts, aggregated from a diverse range of disciplines and Science Goals, to derive recommendations for a mission to expand knowledge of ALAN in areas that are not adequately addressed with currently existing orbital missions. We propose a stand-alone mission focused on understanding light pollution and its effects on our planet. Here we review the science cases and the subsequent mission recommendations for NITESat (Nighttime Imaging of Terrestrial Environments Satellite), a dedicated ALAN observing mission. Full article