Search Results (155)

Heavy rainfall events, characterized by extreme downpours that exceed 100 mm per day, pose an intensifying hazard to the densely settled valleys of the western Himalaya; however, their coupling with expanding urban land cover remains under-quantified. This study mapped the spatiotemporal exposure of built-up areas to heavy-day rainfall (HDR) across Jammu, Kashmir, and Ladakh and the adjoining areas by integrating daily Climate Hazards Group InfraRed Precipitation with Stations product (CHIRPS) precipitation (0.05°) with Global Human Settlement Layer (GHSL) built-up fractions within the Google Earth Engine (GEE). Given the limited sub-hourly observations, a daily threshold of ≥100 mm was adopted as a proxy for HDR, with sensitivity evaluated at alternative thresholds. The results showed that HDR is strongly clustered along the Kashmir Valley and the Pir Panjal flank, as demonstrated by the mean annual count of threshold-exceeding pixels increasing from 12 yr⁻¹ (2000–2010) to 18 yr⁻¹ (2011–2020), with two pixel-scale hotspots recurring southwest of Srinagar and near Baramulla regions. The cumulative high-intensity areas covered 31,555.26 km², whereas 37,897.04 km² of adjacent terrain registered no HDR events. Within this hazard belt, the exposed built-up area increased from 45 km² in 2000 to 72 km² in 2020, totaling 828 km². The years with the most expansive rainfall footprints, 344 km² (2010), 520 km² (2012), and 650 km² (2014), coincided with heavy Western Disturbances (WDs) and locally vigorous convection, producing the largest exposure increments. We also performed a forecast using a univariate long short-term memory (LSTM), outperforming Autoregressive Integrated Moving Average (ARIMA) and linear baselines on a 2017–2020 holdout (Root Mean Square Error, RMSE 0.82 km²; measure of errors, MAE 0.65 km²; R² 0.89), projecting the annual built-up area intersecting HDR to increase from ~320 km² (2021) to ~420 km² (2030); 95% prediction intervals widened from ±6 to ±11 km² and remained above the historical median (~70 km²). In the absence of a long-term increase in total annual precipitation, the projected rise most likely reflects continued urban encroachment into recurrent high-intensity zones. The resulting spatial masks and exposure trajectories provide operational evidence to guide zoning, drainage design, and early warning protocols in the region. Full article

Background/Objectives: Neurocognitive disorders (NCDs) encompass a spectrum of conditions that significantly impact cognitive domains, including attention, memory, and language. Mild NCD, increasingly prevalent with aging, represents an early stage of these disorders, characterized by cognitive deficits that do not interfere with daily functioning. Non-pharmacological therapies, especially cognitive stimulation, are widely recommended to preserve cognitive function of older adults. This study aimed to evaluate the effectiveness of a 12-week individual cognitive stimulation (iCS) program on cognitive performance, mood, and prefrontal cortex activation in older adults with mild NCD using a single-blind, randomized, parallel two-arm RCT. Methods: A sample of 36 older adults were selected from a central region of Portugal. The intervention group (n = 18) received 24 iCS sessions, twice weekly for 12 weeks. The control group (n = 18) completed their regularly scheduled activities. Outcomes included global cognitive function, executive functioning, and mood. All participants were assessed at baseline and after the intervention. Functional near infra-red spectroscopy (fNIRS) was also collected to measure prefrontal cortex activity at both time points in the intervention group. Results: The intervention group showed a significant improvement in global cognition and executive functions, and reduced depressive symptomatology compared to the control group. fNIRS data revealed enhanced activation and functional efficiency in the lateral prefrontal cortex following the iCS program. Adherence and degree of collaboration to the intervention were very high. Conclusions: These findings suggest that iCS is an effective approach to improving cognitive function and mood in mildly cognitively impaired older adults. Full article

Background: This study aimed to investigate the neurocardiovascular responses during an Active Stand (AS) test, utilizing both pre-processed and raw signals, to predict adverse health outcomes including orthostatic intolerance (OI) during the AS, and future falls and mortality. Methods: A total of 2794 participants from The Irish Longitudinal Study on Ageing (TILDA) were included. Continuous cardiovascular (heart rate (HR), systolic (sBP), and diastolic (dBP) blood pressure) and near infra-red spectroscopy-based neurovascular (tissue saturation index (TSI), oxygenated hemoglobin (O₂Hb), and deoxygenated hemoglobin (HHb)) signals were analyzed using Statistical Parametric Mapping (SPM) to identify significant group differences across health outcomes. Results: The results demonstrated that raw (unprocessed) signals, particularly O₂Hb and sBP/dBP, were more effective in capturing significant physiological differences associated with mortality and OI compared to pre-processed signals. Specifically, for OI, raw sBP and dBP captured significant changes across the entire test, whereas pre-processed signals showed intermittent significance. TSI captured OI only in its pre-processed form, at approximately 10 s post-stand. For mortality, raw O₂Hb was effective throughout the AS test. No significant differences were observed in either pre-processed or raw signals related to falls, suggesting that fall risk may require a multifactorial assessment beyond neurocardiovascular responses. Conclusions: These findings highlight the potential utility of raw signal analysis in improving risk stratification for OI and mortality, with further studies needed to validate these findings and refine predictive models for clinical applications. This study underscores the importance of retaining raw data for certain physiological assessments and provides a foundation for future work in developing machine-learning models for early health outcome detection. Full article

The deterioration of stone materials due to atmospheric factors is a growing global concern, affecting the integrity and preservation of numerous UNESCO World Heritage Sites around the world. This study provides an estimate of the long-term impact of the climate on the degradation of carbonate stone materials in the UNESCO site of Matera, in southern Italy. Focusing on Gravina calcarenite, a lithotype susceptible to weathering, the research integrates satellite-derived precipitation data from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) with a dose-response model. The method involves the calibration of CHIRPS precipitation records against ground-based meteorological data, and the use of year-specific recession coefficients K_y dynamically computed as a function of atmospheric CO₂ concentration and temperature. These coefficients were applied within a Lipfert-based equation to estimate annual surface recession from 1981 to 2040 (near future). The results reveal a continuous increase in surface degradation over time, with the cumulative material loss reaching approximately 0.75 mm by 2040. These findings underscore the relevance of climate-responsive models in estimating stone decay and provide a critical basis for adaptive conservation planning. Incorporating future climate projections into risk assessments is essential for the sustainable preservation of carbonate-based cultural heritage exposed to atmospheric and hydrological stressors. Full article

Accurate detection of textile composition is a major challenge for textile reuse/recycling. This paper investigates the feasibility of identification of textile materials using a Near Infra-Red (NIR) camera. A transportable metric has been defined which could be capable of identification and distinction between cotton and polyester. The NIR camera provides a single data value in the form of the “intensity” of the exposed light at each pixel across its 2D pixel array. The feasibility of textile material identification was investigated using a combination of various statistical methods to evaluate the output images from the NIR camera when a bandpass filter was attached to the camera’s lens. A repeatable and stable metric was identified and was shown to be independent of both the camera’s exposure setting and the physical illumination spread over the textiles. The average value of the identified metric for the most suitable bandpass filter was found to be 0.68 for cotton, with a maximum deviation of 2%, and 1.0 for polyester, with a maximum deviation of 1%. It was further shown that carbon black dye, a known challenge in the industry, was easily detectable by the system, and, using the proposed technique in this paper, areas that are not covered by carbon black dye can be identified and analysed. Full article

This work presents two pre-processing patches to automatically correct the residual local misalignment of datasets acquired by very/extremely high resolution (VHR/EHR) satellite multispectral (MS) scanners, one for, e.g., GeoEye-1 and Pléiades, featuring two separate instruments for MS and panchromatic (Pan) data, the other for WorldView-2/3 featuring three instruments, two of which are visible and near-infra-red (VNIR) MS scanners. The misalignment arises because the two/three instruments onboard GeoEye-1 / WorldView-2 (four onboard WorldView-3) share the same optics and, thus, cannot have parallel optical axes. Consequently, they image the same swath area from different positions along the orbit. Local height changes (hills, buildings, trees, etc.) originate local shifts among corresponding points in the datasets. The latter would be accurately aligned only if the digital elevation surface model were known with sufficient spatial resolution, which is hardly feasible everywhere because of the extremely high resolution, with Pan pixels of less than 0.5 m. The refined co-registration is achieved by injecting the residue of the multivariate linear regression of each scanner towards lowpass-filtered Pan. Experiments with two and three instruments show that an almost perfect alignment is achieved. MS pansharpening is also shown to greatly benefit from the improved alignment. The proposed alignment procedures are real-time, fully automated, and do not require any additional or ancillary information, but rely uniquely on the unimodality of the MS and Pan sensors. Full article

Aflatoxins are carcinogenic mycotoxins that may contaminate many crops and more especially maize. To protect consumers from these contaminants, many countries set up low regulatory thresholds of few µg/kg. The control of food requires time-consuming analysis for which sampling is a key step. It would therefore of key sanitary and economic relevance to develop rapid, sensitive and accurate methods that could even be applied on line at harvest, to identify batches to be excluded as soon as possible. In this study, we analyzed more than 500 maize samples taken at harvest during 3 years for their aflatoxin contamination using HPLC-MS. Among them, only 7% were contaminated but sometimes at levels largely exceeding European regulations. We demonstrate that Near InfraRed Spectroscopy (NIRS) could be of great help to classify cereal samples according to their level of aflatoxin contamination (below or higher than E.U. regulation). To build the model, all AF contaminated samples as well as an equivalent number of AF free samples were used. NIRS performance was not sufficient to quantify the toxins with adequate precision. However, its ability to discriminate naturally contaminated maize samples according to their level of contamination with aflatoxins in relation to European regulations using a quadratic PCA-DA model was excellent. Accuracy of the model was 97.4% for aflatoxin B1 and 100% for total aflatoxins. Full article

The global, near-real-time monitoring of volcano thermal activity has become feasible through thermal infrared sensors on various satellite platforms, which enable accurate estimations of volcanic emissions. Specifically, these sensors facilitate reliable estimation of Volcanic Radiative Power (VRP), representing the heat radiated during volcanic activity. A critical factor influencing VRP estimates is the identification of hotspots in satellite imagery, typically based on intensity. Different satellite sensors employ unique algorithms due to their distinct characteristics. Integrating data from multiple satellite sources, each with different spatial and spectral resolutions, offers a more comprehensive analysis than using individual data sources alone. We introduce an innovative Remote Sensing Data Fusion (RSDF) algorithm, developed within a Cloud Computing environment that provides scalable, on-demand computing resources and services via the internet, to monitor VRP locally using data from various multispectral satellite sensors: the polar-orbiting Moderate Resolution Imaging Spectroradiometer (MODIS), the Sea and Land Surface Temperature Radiometer (SLSTR), and the Visible Infrared Imaging Radiometer Suite (VIIRS), along with the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI). We describe and demonstrate the operation of this algorithm through the analysis of recent eruptive activities at the Etna and Stromboli volcanoes. The RSDF algorithm, leveraging both spatial and intensity features, demonstrates heightened sensitivity in detecting high-temperature volcanic features, thereby improving VRP monitoring compared to conventional pre-processed products available online. The overall accuracy increased significantly, with the omission rate dropping from 75.5% to 3.7% and the false detection rate decreasing from 11.0% to 4.3%. The proposed multi-sensor approach markedly enhances the ability to monitor and analyze volcanic activity. Full article

A hand-held NIR spectrophotometric method was developed, validated, and applied for the determination of tadalafil in tablets. The aim of our work was to develop analytical methods based on vibrational techniques using low-cost portable equipment. Based on different chemometric modeling, we attempted to validate the method, which gave encouraging results from the principal component analysis (PCA), DD-SIMCA, and PLS modeling. Following this, we optimized the method using an appropriate experiment plan. For validation, we used the total error approach with acceptance limits set at ±10% with a risk level of 5%. The method showed that it was possible to perform both qualitative and quantitative analysis of pharmaceutical products using low-cost portable NIR systems with chemometric tools. The developed approach enabled the completion of the first step in implementing an NIR method for quality control of tadalafil-based drugs in the DRC. Validation difficulties of the PLS method resulted from the lack of information about inter-day serial variations of spectral responses. It would be interesting to extend the study to a larger calibration interval in order to correct uncertainties that may result from the variability observed under different conditions and to verify robustness. These are the limitations of this work, but the results are nevertheless very encouraging. Full article

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, deployed on multiple satellites including the Suomi National Polar-orbiting Partnership (S-NPP), National Oceanic and Atmospheric Administration 20 (NOAA-20), NOAA-21, Joint Polar Satellite System (JPSS-3), and JPSS-4 spacecraft, with launches in 2011, 2017, 2022, 2032, and 2027, respectively, has polarization sensitivity that affects the at-aperture radiometric Sensor Data Record (SDR) calibration in the Visible Near InfraRed (VNIR) spectral region. These SDRs are key inputs into the VIIRS atmospheric, land, and water Environmental Data Records (EDRs) that are integral to weather and climate applications. If the polarization sensitivity of the VIIRS instrument is left uncorrected, EDR quality will degrade, causing diminished quality of weather and climate data. Pre-launch characterization of the instrument’s polarization sensitivity was performed to mitigate this on-orbit calibration effect and improve the quality of the EDRs. Specialized ground test equipment, built specifically for the VIIRS instrument, enabled high-fidelity characterization of the instrument’s polarization performance. This paper will discuss the polarization sensitivity characterization test approach, methodology, and results for the JPSS-3 and -4 builds. This includes a description of the ground test equipment, instrument requirements, and how the testing was executed and analyzed. A comparison of the polarization sensitivity results of the on-orbit S-NPP, NOAA-20, and -21 instruments with the JPSS-3 and -4 VIIRS instruments will be discussed as well. Full article

The application of diffusive and reflective polyethylene (PE) films as greenhouse coverings in arid climates presents an opportunity to improve the microclimate of the greenhouse and achieve consistent light distribution within the crop canopy. Nevertheless, there is still a lack of understanding regarding the properties of these covers and their impact on the microclimate and the growth parameters of crops. This study aimed to assess the impact of different covers on the diffusion of beam radiation during transmission, microclimatic parameters, and growth parameters of cucumbers in each of the greenhouses they covered. In the study, three PE covers were evaluated: a reflective cover (RC), a diffusive film (DC), and a locally produced cover (LPC) as the control treatment. The covers were installed on three identical, single-span, evaporatively cooled greenhouses named GH1/LPC, GH2/RC, and GH3/DC, which were utilized for cultivating cucumber crops. The results indicated that the diffusive nature of the tested films increased the ratio of diffuse to global solar radiation (D/G) from 0.22 outside the greenhouses to 0.49, 0.42, and 0.41 inside GH1/LPC, GH3/DC, and GH2/RC, respectively. Similarly, the ratio of diffuse to direct beam radiation (D/B) showed an increase, with values of 0.95, 0.70, and 0.68 inside GH1/LPC, GH3/DC, and GH2/RC, respectively, compared to the outside value of 0.28. The DC used in GH3 showed a favorable microclimate by reducing the air temperature and improving the relative humidity. Accordingly, the vegetative growth of the cucumbers was significantly improved in GH3/DC, reflected in increases in their biomass, followed by GH2/RC and GH1/LPC. The highest crop yield (p ≤ 0.05) of 12.3 kg/m² was achieved in GH3/DC, followed by 10.2 kg/m² in GH2/RC and 10.1 kg/m² in GH1/LPC. Interestingly, the LPC not only stood out as a low-cost option but also displayed excellent diffusive–radiative properties, and demonstrated reasonable growth development and productivity for the cucumber crops. Consequently, the LPC emerges as a practical and cost-effective greenhouse covering material for crop production in arid climates. Full article

Digital health tracking is a source of valuable insights for public health research and consumer health technology. The brain is the most complex organ, containing information about psychophysical and physiological biomarkers that correlate with health. Specifically, recent developments in electroencephalogram (EEG), functional near-infra-red spectroscopy (fNIRS), and photoplethysmography (PPG) technologies have allowed the development of devices that can remotely monitor changes in brain activity. The inclusion criteria for the papers in this review encompassed studies on self-applied, remote, non-invasive neuroimaging techniques (EEG, fNIRS, or PPG) within healthcare applications. A total of 23 papers were reviewed, comprising 17 on using EEGs for remote monitoring and 6 on neurofeedback interventions, while no papers were found related to fNIRS and PPG. This review reveals that previous studies have leveraged mobile EEG devices for remote monitoring across the mental health, neurological, and sleep domains, as well as for delivering neurofeedback interventions. With headsets and ear-EEG devices being the most common, studies found mobile devices feasible for implementation in study protocols while providing reliable signal quality. Moderate to substantial agreement overall between remote and clinical-grade EEGs was found using statistical tests. The results highlight the promise of portable brain-imaging devices with regard to continuously evaluating patients in natural settings, though further validation and usability enhancements are needed as this technology develops. Full article

Near-infrared spectroscopy (NIRS) during repeated limb occlusions is a noninvasive tool for assessing muscle oxidative capacity. However, the method’s reliability and validity remain under investigation. This study aimed to determine the reliability of the NIRS-derived mitochondrial power of the musculus vastus lateralis and its correlation with whole-body (cycling) aerobic power ($\dot{\mathrm{V}}$O₂ peak). Eleven healthy active men (28 ± 10 y) twice (2 days apart) underwent repeated arterial occlusions to induce changes in muscle oxygen delivery after 15 s of electrical muscle stimulation. The muscle oxygen consumption (m$\dot{\mathrm{V}}$O₂) recovery time and rate (k) constants were calculated from the NIRS O₂Hb signal. We assessed the reliability (coefficient of variation and intraclass coefficient of correlation [ICC]) and equivalency (t-test) between visits. The results showed high reproducibility for the m$\dot{\mathrm{V}}$O₂ recovery time constant (ICC = 0.859) and moderate reproducibility for the k value (ICC = 0.674), with no significant differences between visits (p > 0.05). NIRS-derived k did not correlate with the $\dot{\mathrm{V}}$O₂ peak relative to body mass (r = 0.441, p = 0.17) or the absolute $\dot{\mathrm{V}}$O₂ peak (r = 0.366, p = 0.26). In conclusion, NIRS provides a reproducible estimate of muscle mitochondrial power, which, however, was not correlated with whole-body aerobic capacity in the current study, suggesting that even if somewhat overlapping, not the same set of factors underpin these distinct indices of aerobic capacity at the different (peripheral and whole-body systemic) levels. Full article

The vestibular system plays a fundamental role in body orientation, posture control, and spatial and body motion perception, as well as in gaze and eye movements. We aimed to review the current knowledge regarding the location of the cortical and subcortical areas, implicated in the processing of vestibular stimuli. The search was performed in PubMed and Scopus. We focused on studies reporting on vestibular manifestations after electrical cortical stimulation. A total of 16 studies were finally included. Two main types of vestibular responses were elicited, including vertigo and perception of body movement. The latter could be either rotatory or translational. Electrical stimulation of the temporal structures elicited mainly vertigo, while stimulation of the parietal lobe was associated with perceptions of body movement. Stimulation of the occipital lobe produced vertigo with visual manifestations. There was evidence that the vestibular responses became more robust with increasing current intensity. Low-frequency stimulation proved to be more effective than high-frequency in eliciting vestibular responses. Numerous non-vestibular responses were recorded after stimulation of the vestibular cortex, including somatosensory, viscero-sensory, and emotional manifestations. Newer imaging modalities such as functional MRI (fMRI), Positron Emission Tomography (PET), SPECT, and near infra-red spectroscopy (NIRS) can provide useful information regarding localization of the vestibular cortex. Full article

Due to their appealing colors, gem quality tourmalines, particularly the blue to green Cu- and Mn-bearing Li-tourmalines known as the Paraíba type, have been of significant interest since their discovery at the end of 1980s. At the same time, the demand of other similar colored tourmalines increased. Most Paraíba-type tourmalines belong to the elbaite species; however, liddicoatite gems can also be found. Recognizing and classifying various tourmaline species, especially these valued Paraíba-type tourmalines, are important for geologists, mineralogists, mineral collectors, and gemologists. This study explores the application of Raman spectroscopy in random crystal orientations to distinguish between the elbaite and liddicoatite tourmaline species. Raman spectra were collected from faceted blue to green Li-tourmalines alongside chemical analysis using EDXRF (Energy Dispersive X-ray Fluorescence), UV-Vis-NIR (Ultraviolet-Visible-Near InfraRed Spectroscopy), and PL (Photoluminescence spectroscopy) to provide comprehensive characterization. The results show that Raman spectroscopy, particularly in the OH stretching region, is a useful tool for differentiating elbaite from liddicoatite, and this identification remains consistent regardless of crystal orientation. The fingerprint region in the Raman spectra, on the other hand, is orientation-dependent and can only differentiate the two species when detected in specific orientations. Furthermore, Paraíba-type tourmalines can be identified by visible-near infrared (Vis-NIR) spectroscopy, although not by Raman spectroscopy. Full article