Infrared spectroscopy is an effective method for the determination of compositions and concentrations of liquids, with advantages of fast response, no-sampling, flexible in use and is able for on-line monitoring. However, for trace substances in drinking water, such as nitrates and heavy metals, infrared spectroscopy is not sensitive enough for the quantitative and qualitative measurement. In this study, we improved the sensitivity of infrared spectroscopy for nitrite determination by developing an ion-exchange-enhanced diffuse reflectance spectroscopy, which consist of an accessory based on ion-exchange resin for enrichment and a FTIR spectrometer for measurement. Using this method, the limit of detection for nitrate is 1.7 mg/L, which is enough for drinking water sensing. We also verified the quantitative measurement ability of the method. Furthermore, the limit of detection and quantitative measuring range could be adjusted by changing the mass of resin and adsorption time. This study demonstrated the method can be used to detect trace nitrites in drinking water, can be applied in the field, and is sensitive, rapid, and inexpensive with a wide dynamic range.

Over the past 30 years, the use of field spectroscopy has risen in importance in remote sensing studies for the characterization of the surface reflectance of materials in situ within a broad range of applications. Potential uses range from measurements of individual targets of interest (e.g. vegetation, soils, validation targets etc.), to characterizing the contributions of different materials within larger spatially-mixed areas as would be representative of the spatial resolution captured by a sensor pixel (UAV to satellite scale). As such, it is essential that a complete and rigorous assessment of both the data-acquisition procedures, and the suitability of the derived data product be carried out. The measured energy from solar-reflected range spectroradiometers is influenced by the viewing and illumination geometries and the illumination conditions which vary due to changes in solar position and atmospheric conditions. By applying corrections, the estimated absolute reflectance (Rabs) of targets can be calculated. This property is independent of illumination intensity or conditions and is the metric commonly suggested to be used to compare spectra even when data are collected by different sensors or acquired under different conditions. By standardizing the process of estimated Rabs, as is provided in the described toolkit, consistency and repeatability in processing are ensured and the otherwise labor intensive and error-prone processing steps are streamlined. The resultant end data product (Rabs) represents our best current effort to generate consistent and comparable ground spectra which have been corrected for viewing and illumination geometries as well as other factors such as the individual characteristics of the reference panel used during acquisition.

High purity TiO2 and CuO powders were synthesized by the Pechini method, an inexpensive and easy-to-implement procedure to synthetize metal oxides. The variables of synthesis were the ethylene glycol:citric acid molar ratio and the pH. High reproducibility of the anatase and tenorite phase was obtained for all synthesis routes. The degree of purity of the powders was confirmed by XRD, FTIR, UV-vis absorption and XPS spectra. SEM and TEM images revealed the powders are composed by micrometer grains that can have a spherical shape (only in the TiO2) or formed by a non-compacted nanocrystalline conglomerate. FTIR spectra only vibrational modes associated to the TiO2 or CuO with a nanoparticle behavior. UV-vis absorption spectra revealed the values of maximum absorbance percentage of both systems are reached in the ultraviolet region, with percentages above 83 % throughout the entire visible light spectrum for the CuO system, a relevant result for solar cell applications. Finally, XPS experiments allow the observation of the valence bands and the calculation of the energy bands of all oxides.

Near-infrared spectroscopy (NIRS) has become a key modality in medical imaging, finding application in both brain and breast imaging. This paper discusses the current trends in NIRS for brain and breast imaging, exploring advances in multi-modal integration with modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Challenges related to spatial resolution, depth sensitivity, and the impact of extracerebral tissues on signal specificity are examined. In addition, ongoing efforts to enhance hemodynamic measurements’ quantitative accuracy. Challenges, including limited spatial resolution and tissue heterogeneity, are discussed. The discussion extends to diffuse optical tomography and ongoing instrumentation development, clinical trials and studies validating NIRS diagnostic efficacy in breast imaging. The paper emphasizes the need for standardization, integration into routine clinical practice, and motivates for future work.

The qualitative analysis of nanodiamonds by FTIR spectrometry as photoacoustic (PAS), diffuse-reflectance (DRIFT), and attenuated total reflection (ATR) modalities was evaluated for rapid and nondestructive analysis and comparison of nanodiamonds. The spectra reproducibility and signal-gathering depth was compared. The assignment of characteristic bands showed that only six groups of bands were present in spectra of all the modalities with appropriate sensitivity: 1760 (C=O stretch, isolated carboxyl groups); 1640–1632 (H–O–H bend, liquid water); 1400–1370 (non-carboxyl C–O–H in-plane bend and CH2 deformation); 1103 (non-carboxyl C–O stretch); 1060 (in-plane C–H bend, non-aromatic hydrocarbons and carbohydrates); and 940 cm–1 (out-of-plane carboxyl C–O–H bend). DRIFT provides the maximum number of bands and is capable of measuring hydrogen-bonded bands and CHX groups. ATR provides the good sensitivity for water and C–H/C–C bands in the range 2000–400 cm–1. PAS-FTIR reveals less bands than DRIFT but more intense bands than ATR-FTIR and shows the maximum sensitivity for absorption bands that do not appear in ATR-IR spectra and are expedient for supporting either DRIFT or PAS along with depth-profiling. Thus, all three modalities are required for full characterization of nanodiamonds surface functional groups.

Antimony (Sb) has gained significance as a critical raw material (CRM) within the European Union (EU) due to its strategic importance in various industrial sectors, particularly in the textile industry for flame retardants and as a component of Sb-based semiconductor materials. Moreover, Sb is emerging as a potential alternative for anodes used in lithium-ion batteries, a key element in the Energy transition. This study focused on exploring the feasibility of identifying and quantifying Sb mineralizations through the spectral signature of soils using reflectance spectroscopy, a non-invasive remote sensing technique, and by employing deep learning algorithms such as Convolutional Neural Networks (CNNs). Common signal preprocessing techniques were applied to the spectral data, and the soils were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Despite achieving high R-squared values, the study faces a significant challenge of generalization of the model to new data. Despite the limitations, this study provides valuable insights into potential strategies for future research in this field.

A fast and effective determination method of different species of vegetable seeds oil is vital in the plant oil industry. The near-infrared reflectance spectroscopy (NIRS) method was developed in this study to massively analyze the oil and moisture contents of Camellia gauchowensis Chang and C. semiserrata Chi seeds kernels. In the prediction models of NIRS, the levels of accuracy obtained were sufficient for C. gauchowensis Chang and C. semiserrata Chi, the correlation coefficient of which oil were 0.983 and 0.962, respectively, while which of moisture were 0.937 and 0.907, respectively. The near infrared spectrum of crush seeds kernels was more precise compared to intact kernels. Based on the calibration models of the two Camellia species, the NIRS predictive oil contents of C. gauchowensis Chang and C. semiserrata Chi seeds kernels were 48.71 ± 8.94% and 31.71 ± 7.39%, respectively, and the NIRS predictive moisture contents were 4.39 ± 1.08% and 3.49 ± 0.71%, respectively. Compared with the traditional chemical measurement, the rapid, precise measurement of oil and moisture of C. gauchowensis Chang and C. semiserrata Chi seeds kernels can be actualized by NIRS method.

Non-invasive heart rate (HR) monitoring is important in clinical settings as it plays a critical role in diagnosing a range of health conditions and assessing well-being. Presently, the gold standards for HR measurement are all based on sensors which require skin contact. Apart from inconvenience, contact sensors have proven problematic in certain scenarios – they cannot be used when mechanical isolation of the patient is imperative (burn victims, patients with shaky hands and feet), cause skin damage to premature babies in the ICU and increase the risk of spreading infections. Non-contact HR monitoring using a camera has been recently shown to be a viable alternative. It is now possible to record cardiac-synchronous blood volume variations from facial videos of human subjects under ambient lighting. These variations produce corresponding changes in skin reflectance which can be extracted as a raw reflectance photoplethysmography (rPPG) signal and processed to reveal HR. In this project, an algorithmic framework for webcam-based HR detection was successfully implemented in MATLAB. The investigation was based on 100 self-captured videos (dark-skinned subject) and 48 videos (from 12 subjects, all but one fair-skinned) obtained from COHFACE – an online database of facial videos and corresponding physiological signals. While the performance metrics (mean error, SNR) of the rPPG signals obtained from the self-captured videos were poor (best case mean error of 22%), they were good enough to demonstrate the success of the implementation. The poor results were primarily imputed to skin tone as rPPG SNR is known to be particularly low for dark tones. The results of the COHFACE videos were far superior, with mean error ranging from 3% to 15% (among 8 different rPPG signals) and 0% to 9% under ambient and dedicated lighting, respectively. This investigation sets the foundation for future research directed at optimizing rPPG performance metrics for dark-skinned subjects.

Hyperspectral reflectance imaging is an emerging method for rapid non-invasive quantitative screening of plant traits. This method is essential for high-throughput phenotyping and hence for accelerated breeding of crop plants as well as for precision agriculture practices. However, extraction of sensible information from reflectance images is hindered by the complexity of plant optical properties, especially when they are measured in the field. We propose using reflectance indices (Plant Senescence Reflectance Index, PSRI; Anthocyanin Reflectance Index, ARI; and spectral deconvolution) previously developed for remote sensing of vegetation and point-based reflectometers to infer the spatially resolved information on plant development and biochemical composition using ripening apple fruit as the model. Specifically, the proposed approach enables capturing data on distribution of chlorophylls and primary carotenoids as well as secondary carotenoids (both linked with fruit ripening and leaf senescence during plant development) as well as the information on spatial distribution of anthocyanins (known as stress pigments) over the plant surface. We argue that the proposed approach would enrich the phenotype assessments made on the base of reflectance image analysis with valuable information on plant physiological condition, stress acclimation state, and the progression of the plant development.

Modern agriculture demands for comprehensive information about the plant itself. Conventional chemistry-based analytical methods - due to their low throughput and high associated cost - are no longer capable of providing these data. In recent years, remote reflectance-based characterization has developed as one of the most promising solutions for rapid assessments for plant attributes. However, in many cases, expensive equipment is required because accurate quantifications need assessment of the full reflectance spectrum. We examined the versatility of visible colour sensors as reflectance measuring devices for biological / biochemical quantifications on sweet basil (Ocimum basilicum). Our results indicate for the wide potential of spectral colour sensors for quantitative determination of leaf phenolic compounds, flavonoids in particular, and non-invasive plant phenotyping in agricultural applications by low-cost sensors.

Oil floating on the sea surface can be detected by both passive and active methods using the ultraviolet-to-microwave spectrum, whereas oil immersed below the sea surface can signal its presence only in visible light. This paper presents an optical model of a sea area deeply polluted by an oil suspension (10 ppm) located in a layer (thickness 5 m) separated from the sea surface by a clear layer (thickness 1 m). The impact of wavelength and state of the sea surface on reflectance changes is shown based on the results of Monte Carlo ray tracing. A two-wavelength index of reflectance is proposed to detect oil suspended in the water column (645-469 nm).

The scale and accessibility of passive global surveillance have rapidly increased over time. This provides an opportunity to calibrate the performance of models, algorithms, and reflectance ratios between remote sensing devices. Here we test the sensitivity and specificity of Eucalypt chlorophyll-a reflectance ratio (ECARR) and Eucalypt chlorophyll-b reflectance ratio (ECBRR) to remotely identify eucalypt vegetation in Queensland, Australia. We compare reflectance ratio values from Sentinel-2 and Planet imagery across four sites of known vegetation composition. All imagery was transformed to reflectance values and Planet imagery was additionally scaled to harmonize across Planet Scenes. ECARR can identify eucalypt vegetation remotely with high sensitivity, but shows low specificity and is impacted by the density of the vegetation. ECBRR reflectance ratios show similar sensitivity and specificity when identifying eucalypt vegetation but with values an order of magnitude smaller than ECARR. We find that ECARR was better at identifying eucalypt vegetation in the Sentinel-2 imagery than Planet imagery. ECARR can serve as a general chlorophyll indicator but is not a specific index to identify Eucalyptus vegetation with certainty.

Background: Diffuse large B-cell lymphoma is the most common type of non-Hodgkin's lymphoma. Due to the variety of clinical manifestations, accurate diagnosis can be challenging. Here, we present a case of DLBCL that was initially misdiagnosed as a hematoma, highlighting the importance of considering malignancy in the setting of non-responsive soft tissue swelling. Methods: A 76-year-old man presented to the emergency department with right periorbital swelling and ecchymosis. The symptoms first appeared after an injury and did not resolve spontaneously. The patient was taking warfarin for atrial fibrillation. A facial bone CT revealed a large irregular homogeneous mass. An extraconal hematoma was suspected based on clinical history and radiologic findings. Incision and drainage were performed, resulting in evacuation of old blood. Despite continued drainage, the patient's symptoms worsened. A comparison with the previous CT revealed an increase in the size of the lesion. As a result, a surgical excisional biopsy was performed. Results: Biopsy of the mass showed a diffuse infiltrate of lymphocytes around the tissue. The diagnosis of diffuse large B-cell lymphoma was confirmed pathologically. The patient was referred to hematology for further management. Conclusions: DLBCL is a rare disease associated with a poor prognosis. Due to the previous injury and the use of anticoagulants, the patient was initially misdiagnosed as having a hematoma. This delayed the prompt diagnosis and affected the timing of treatment initiation. We must be aware that a malignant mass is a potential cause of unresponsive soft tissue swelling.

Wastewater (WW) analysis is a critical step in various operations such as control of a WW treatment facility, and speeding-up the analysis of WW quality can significantly improve such operations. This work demonstrates the capability of neural network (NN) regression models to estimate WW characteristic properties such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammonia (NH3-N), total dissolved substances (TDS), total alkalinity (TA), and total hardness (TH) by training on WW spectral reflectance in the visible to near-infrared spectrum (400nm-2000nm). The dataset contains samples of spectral reflectance intensity, which were the inputs, and the WW parameter levels (BOD, COD, NH3-N, TDS, TA, and TH), which were the outputs. Various NN model configurations were evaluated in terms of regression model fitness. The mean-absolute-error (MAE) was used as the metric for training and testing the NN models, and the coefficient of determination (R2) between the model predictions and true values was also computed to measure how well the NN models predict the true values. With online spectral measurements, the trained neural network model can provide non-contact and real-time estimation of WW quality at minimum estimation error.

A series of experiments were conducted to measure and quantify the yield, dry matter content, sugars content and nitrates content of grass intended for ensilement. These experiments took place in the East Midlands of Ireland during the Spring, Summer and Autumn of 2019. A bespoke sensor rig was constructed; included in this rig was a hyperspectral radiometer that measured a broad spectrum of reflected natural light from a circular spot approximately 1.2 metres in area. Grass inside a 50cm square quadrat was manually collected from the centre of the circular spot for ground truth estimation of the grass qualities. Up to 25 spots were recorded and sampled each day. The radiometer readings for each spot were automatically recorded onto a laptop that controlled the sensor rig, and ground truth measurements were made either on site or within 24 hours in a wet chemistry laboratory. The collected data was used to build Partial Least Squares Regression (PLSR) predictive models of grass qualities from the hyperspectral dataset and it was found that substantial relationships exist between the spectral reflectance from the grass and yield (r2 = 0.62), dry matter % (r2 = 0.54), sugar content (r2 = 0.54) and nitrates (r2 = 0.50). This shows that hyperspectral reflectance data contains substantial information about key grass qualities and can form part of a broader holistic data driven approach to provide accurate and rapid predictions to farmers, agronomists and agricultural contractors.

Reflected light carries ample information about biochemical composition, tissue architecture, and physiological condition of plants. Recent technical progress brought about affordable imaging hyperspectrometers (IH) providing spatially resolved spectral data on plants. The extraction of sensible information from hyperspectral reflectance images is difficult due to inherent complexity of plant tissue and canopy optics, especially when recorded by IH under ambient sunlight. We aimed at obtaining a deeper insight into plant optics as perceived by IH since there is a high demand for algorithms for fruit harvesting and grading systems equipped with computer vision and robotic systems capable of working in orchard. We report on the characteristic changes in hyperspectral reflectance accompanying the accumulation of anthocyanins in healthy fruit, pigment breakdown during sunscald and phytopathogen attacks. The measurements made outdoors with a snapshot IH were compared with traditional “point” reflectance measured with a conventional spectrophotometer under controlled illumination conditions. Most of the spectral features and patterns of plant reflectance were evident in the IH-derived reflectance images. As a step forward, a novel index for highlighting tissue damages on the background of the anthocyanin absorption, BRI-M = (1/Rorange – 1/Rred + 1/RNIR), is suggested. Difficulties of the interpretation of fruit hyperspectral reflectance images recorded in situ are discussed with possible implications for plant physiology and precision horticulture practices.

Surface treatments of metals based on laser marking technology is an important application in a wide range of industrial fields. By specific combinations of laser processing parameters, the modified surface leads to different textures with specific roughness and colored appearance. Most of current works are focused on the modification of color tonality of flat surfaces, or the development of specific topography features, but the combination of both processes is not usually evaluated, mainly due to the complexity to control the optical properties on rough surfaces. This research presents an analysis of the influence of the micro-geometrical characteristics of periodic patterned laser tracks on the chromaticity and reflectance of Ti6Al4V substrates. The samples were irradiated with an infrared nanosecond pulsed laser under air atmosphere, taking as control parameter the scan speed of the beam. A roughness evaluation, microscopic inspection, absorption and chromaticity examination were conducted. Although micro-crack growth was detected in isolated case (10 mm/s), the possibility of adjusting the result color were demonstrated by controlling the thermal affected zone thickness of the textures. Results of rough/colored combined textures allow opening new perspectives in industrial design, particularly in aesthetic applications with special properties.

Diffuse cavernous hemangioma of the rectum (DCHR) is a rare benign lesion of vascular malformation. According to previous studies, the most reported major symptoms of DCHR are recurrent painless rectal bleeding or iron deficiency anemia[1][2][3][4][5][6]. We present a case of an 8Y11M boy who was diagnosed with DCHR by MRI. The patient underwent Laparoscopic-assisted transanal distal sigmoidectomy and sigmoido-anal anastomosis（Laparoscopic Swenson Procedure）, and recovered well. After the operation, the child had short-term fecal incontinence and loose stools, which returned to normal after half a year. Regardless of age and symptoms, early and correct diagnosis and treatment of DCHR and postoperative restoration of normal anal function are necessary. Laparoscopic Swenson procedure may be a good option for the treatment of DCHR.

We compared two approaches to non-invasive proximal sensing of the early changes in fresh-cut lettuce leaf quality: hyperspectral imaging and imaging PAM-fluorometry of chlorophyll contained in the leaves. The assessments made by the imaging techniques were confronted with the quality assessments made by traditional biochemical assays: relative water content and foliar pigment (chlorophyll and carotenoid) composition. The hyperspectral imaging-based approach provided the highest sensitivity to the decline of fresh-cut lettuce leaf quality taking place within 24 h from cutting. Using of the imaging PAM was complicated by (i) weak correlation of the spatial distribution pattern of the Qy parameter with the actual physiological condition of the plant object and (ii) its high degree of heterogeneity. Accordingly, the imaging PAM-based approach was sensitive only to the manifestations of leaf quality degradation only at advanced stages of the process. Sealing the leaves in the polyethylene bags slowed down the leaf quality degradation at the initial stages (< 3 days) but promoted its rate at more advanced stages, likely due to build-up of ethylene in the bags. An approach was developed to the processing of hyperspectral data for non-invasive monitoring of the lettuce leaves with a potential for implementation in greenhouses and packinghouses.

Forests are critical in regulating the world’s climate and they maintain overall Earth’s energy balance. The variability in forest canopy structure, topography and underneath vegetation background condition creates uncertainty in the estimation and modelling of Earth’s surface radiation particularly for boreal regions in high latitude. We studied seasonal variation in surface reflectance with respect to land cover classes, canopy structures, and topography in a boreal region of Alaska by fusing together Landsat 8 surface reflectance and LiDAR-derived canopy matrices. Our study shows that canopy structure and topography interplay and influence surface reflectance in a complex way particularly during the snow season. Topographic aspect and elevation control vegetation growth, type and structure. The southern slope is featured with more deciduous and taller trees having greater rugosity than the northern slope. Higher elevation is associated with taller trees for both vegetation types, particularly in the southern slope. In general, surface reflectance shows similar relationships with canopy cover, height and rugosity, mainly due to close relationships between these parameters. Surface reflectance decreases with canopy cover, tree height, and rugosity especially for evergreen forest. Deciduous forest shows larger variability of surface reflectance, particularly in March, mainly due to the mixing effect of snow and vegetation. The relationship between vegetation structure and surface reflectance is greatly impacted by topography. The negative relationship between elevation and surface reflectance may be due to taller and denser vegetation distribution in higher elevation. Surface reflectance in the southern slope is slightly larger than the northern slope for both deciduous and evergreen forest. The shadow effect from topography and tree crowns on surface reflectance play a different role for deciduous and evergreen forests. For deciduous forest, topographic shadow effect on surface reflectance is stronger than from tree shadowing in all seasons. For evergreen forest, shadow effects from topography and tree crowns on surface reflectance are both equally dominant, however tree shadow effect is more significant in March than in May and August. The generalized additive models (GAM) based on non-linear relationships between response (surface reflectance) and predictor (canopy structures and topography) variables confirms such observations. Our study not only provides accurate quantification of surface radiation budget but also helps in parametrization of climate change models.

Runaway electrons (RAEs) generation in high-pressure gases is an important physical phenomenon that influences significantly discharge shapes and properties of initiated plasma. The diffuse discharges formed due to RAEs in air and other gases at atmospheric pressure find wide application. In the present review, theoretical and experimental results that explain the reason for the RAEs occurrence at high pressures are analyzed and recommendations are given on the implementation of conditions under which the runaway electron beam (RAEB) with the highest current can be obtained at atmospheric pressure. Experimental results were obtained using subnanosecond, nanosecond, and submicrosecond generators, including those specially developed for runaway electron generation. The RAEB were recorded by oscilloscopes and collectors with picosecond time resolution. To describe theoretically the phenomenon of continuous electron acceleration, the method of physical kinetics has been used based on the Boltzmann kinetic equation that takes into account the minimum but sufficient number of elementary processes, including shock gas ionization and elastic electron scattering. Results of modeling allowed the main factors to be established that control the RAE appearance, the most important of which is electron scattering on neutral atoms and/or molecules. Theoretical modeling has allowed the influence of various parameters (including the voltage, pressure, gas type, and geometrical characteristics of the discharge gap) to be taken into account. The results of research presented here allow the RAEs accelerators with desirable parameters to be developed and the possibility of obtaining diffuse discharges to be accessed under various conditions. The review consists of the Introduction, 5 Sections, the Conclusion, and the References.

Diffuse optical tomography (DOT) is a medical imaging procedure using light to measure the geometric and working properties of cells, for instance, oxygen consumption, water content, and fat percentage in the tissue by performing three-dimensional visualization of the tissue. This paper aims to explain the theory behind diffuse optical tomography imaging and how the technology works. The paper explains how photon migration techniques based on diffusion theory can be used to image the optical properties of tissue. There are several reasons why near-infrared (NIR) imaging is the most effective method in terms of recovering optical parameters quantitatively in the near-infrared region. The author discusses the methods in detail. This research also presents various advantages, practical uses, and potential problems that have been related to DOT in this work. There is also a brief discussion of current research developments in medical imaging using near-infrared wavelengths, and what the future holds for that area.

The High-Resolution Computed Tomography (HRCT) detection and diagnosis of diffuse lung disease is primarily based on the recognition of a limited number of specific abnormal findings, pattern combinations or their distributions, as well as anamnesis and clinical information. Since texture recognition has a very high accuracy percentage if a complex network approach is used, this paper aims to implement such a technique customized for diffuse interstitial lung diseases (DILD). The proposed procedure translates HRCT lung imaging into complex networks by taking samples containing a secondary lobule, converting them into complex networks and analyzing them in 3 dimensions: emphysema, ground glass opacity and consolidation. This method was evaluated on a 60 patient lot and the results show a clear quantifiable difference between healthy and affected lungs. By deconstructing the image on three pathological axes, the method offers an objective way to quantify DILD details which, so far, have only been analyzed subjectively.

Globally, rice is one of the most important staple food crops. The most significant metric for evaluating the rice growth and productivity is the Leaf Area Index (LAI), which can be effectively monitored using remote sensing data. Hyperspectral remote sensing provides contiguous bands at narrow wavelengths for mapping LAI at various rice phenological stages and it is functionally related to canopy spectral reflectance. Hyperspectral signatures for different phases of rice crop growth was recorded using Airborne Visible Near-Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) along with corresponding ground based observations. Ground based hyperspectral canopy spectral reflectance measurements was recorded with FieldSpec 3 Hi-Res spectroradiometer (ASD Inc., USA; spectral range: 350-2500 nm) and LAI data from 132 farmer’s fields in Southern India. Among 29 hyperspectral vegetation indices tested, eight were found promising for mapping rice LAI at various phenological stages. Among all the growth stages, elongation stage was the most accurately estimated using vegetation indices that exhibited significant correlation with the airborne hyperspectral reflectance. The validation of hyperspectral vegetation indices revealed that the best fit model for estimating rice LAI was mND705 (red-edge, blue and NIR bands) at seedling and elongation, SAVI (red and NIR bands) at tillering and WDRVI (red and NIR bands) at booting stage.

: Our study aim to test the influence of RGB reflectance and chlorophyll content on grain fill and grain yield of 15 durum wheat cultivars sown under semi-arid conditions. the evolution of chlorophyll content during three stages showed a stability during the heading stage, the chlorophyll content begins at this degradation during grain filling. Boutaleb genotype which was the best yielding genotype was characterized by low values ​​of RGB reflectance and high values ​​of majority of grain filling parameters and thousand kernels weight. Grain filling follows a sigmoid curve. Chlorophyll content was positively correlated with reflectance under the green band and negatively with both Red and Blue bands. A positive correlation was recorded between thousand kernel weight and grain yield, maximum grain dry weight and grain filling duration. The duration of the grain filling was positively influenced by the maximum dry weight of the grain and negatively by the grain filling ratio, the grain filling ratio was positively affected by reflectance at blue band. The principal component analysis separated the cultivars considered into 3 principal components, the absorption/reflectance component, the profitability component and the component of grain filling rate to which the local landrace Boutaleb belongs in terms of grain yield.

Diffuse large B cell lymphoma (DLBCL), the most frequent type of non-Hodgkin lymphoma in adulthood, remains challenging clinical issues. Despite enhanced remission rates can be achieved, there are one-third of patients who will not respond to current treatment or will relapse with resistant disease, necessitating ongoing efforts on effective treatment strategies and agents. The vacuole H+-ATPase inhibitor bafilomycin A1 is broadly used to block late stage of autophagy flux at high concentration. In this study, we show that, to our surprise, bafilomycin A1 effectively inhibited and killed DLBCL cells at nanomolar concentrations (5nM). Bafilomycin A1 targeted cell cycle regulators cyclin D1 and cyclin E2 to induce cell cycle arrest in G0/G1 phase. Meanwhile, it induced caspase-dependent apoptosis with concomitant cleaved caspase-3 and Parp. Furthermore, we found that bafilomycin A1 inhibited autophagy flux at both early and late stages of the autophagy flux through activating ERK and mammalian target of rapamycin signaling, as well as by inhibiting the degradation of autolysosomes. We speculated that bafilomycin A1 as autophagy inhibitor might enhance the effect of DLBCL chemotherapeutic drug rituximab. Accordingly, our results provided evidence that the combination of bafilomycin A1 with rituximab enhanced the inhibition of DLBCL cells notably. Taken together, our data suggest that bafilomycin A1 may be a promising candidate drug in the therapy of diffuse large B cell lymphoma.

The agricultural sector is currently confronting multifaceted challenges such as an increased food demand, a slow adoption of sustainable farming, a need for climate-resilient food systems, resource inequity, and protection of the small-scale farmers’ practices, all issues integral to food security and environmental health. Remote sensing technologies can assist precision agriculture to effectively address these complex problems, by providing farmers with a high-resolution lens. The use of vegetation indices (VIs) is an essential component of remote sensing, which combine the variability of spectral reflectance value (derived from remote sensing data) with the growth stage of crops. Currently a wide array of VIs is available that could be used to provide a classification and an evaluation of the state and health of crops. However precisely this high number leads to difficulties in selecting the best VI and combination of VIs for a specific objective. Without a thorough documentation and analysis of appropriate VIs, users might be confronted with difficulties in using remote sensing data or even with a very low accuracy of the results. Thus, the objective of this review is to conduct a critical analysis of the existing state of the art on the most important features related to the effective use of VIs for the discrimination and monitoring of the most important agricultural crops (wheat, corn, sunflower, soybean, rape, potatoes, and forage crops), grasslands and meadows. This data could be highly useful for all the stakeholders involved in agricultural activities (from farmers, researchers up to institutions dealing with the centralization and monitoring of agricultural crops).

To understand forest dynamics under today’s changing environmental conditions, it is important to analyze the state of forests at large scales. Forest inventories are not available for all regions, so it is important to use other additional sources of information, e.g. remote sensing observations. Increasingly, remotely sensed data based on optical instruments and airborne LIDAR are becoming widely available for forests. There is great potential in analyzing these measurements and gaining an understanding of forests state. In this work, we combine the new generation radiative transfer model mScope with the individual-based forest model FORMIND to generate reflectance spectra for forests. Combining the two models allows us to account for species diversity at different height layers in the forest. We compare the generated reflectances for forest stands in Finland, in the region of North Karelia, with Sentinel-2 measurements. We investigate which level of forest representation gives the best results. For the majority of the forest stands, we generated good reflectances with all levels forest representation compared to the measured reflectance. Good correlations were also found for the vegetation indices (especially NDVI with R²=0.62). This work provides a forward modelling tool for relating forest reflectance to forest characteristics. With this tool it is possible to generate a large set of forest stands with corresponding reflectances. This opens the possibility to understand how reflectance is related to succession and different forest conditions.

Abstract: The calibrator is one of the most important factors in the calibration of various laser 3D scanning instruments. The requirements for diffuse reflection surface are specially emphasized in many national standards. In this study, the spherical calibrator and plane calibrator compara-tive measurement experiments were carried out. The black ceramic standard sphere, white ce-ramic standard sphere, metal standard sphere, metal standard plane and white ceramic standard plane were used to test the laser 3D scanner. In the spherical calibrators comparative measure-ment experiments, the results indicated that the RMS of the white ceramic spherical calibrator with reflectance about 60% is 10 times that of the metal spherical calibrator with the reflectance of about 15%, and the RMS of the black ceramic spherical calibrator with reflectance of about 11% is of the same order as the metal spherical calibrator. In the plane calibrators comparative measurement experiments, the RMS of flatness measurement is 0.077 mm for metal plane cali-brator with reflectance of 15%, and 2.915 mm for ceramic plane calibrator with reflectance of 60%. The results show that when the optimal measurement distance and incident angle are selected, the reflectance of the calibrator has a great effect on the measurement results, regardless of the outlines or profiles. Based on the experiments, it is recommended to use the spherical calibrator or the standard plane with reflectance of around 18% as the standard, which can obtain the rea-sonable results. In addition, it is necessary to clearly provide the material category and surface reflectance information of the standard when calibrating the scanner according to the measure-ment standard.

ZnO has many technological applications which largely depend on its properties that can be tuned by controlled synthesis. Ideally, the most convenient ZnO synthesis is carried out at room temperature in aqueous solvent. However, the correct temperature values are often loosely defined. In the current paper we performed synthesis of ZnO in aqueous solvent, by varying reaction and drying temperature by 10°C steps and monitored the synthesis products primarily by XRD. We found out that a simple direct synthesis of ZnO, without additional surfactant, pumping of freezing, required both a reaction (TP) and a drying (TD) temperature of 40°C. Higher temperatures also afford ZnO, but lowering any of the TP or TD below the threshold value results either in the achievement of Zn(OH)2 or in a mixture of Zn(OH)2/ZnO. A more detailed Rietveld analysis of the ZnO samples reveals a density variation with the synthesis temperature and an increase of the nanoparticles average size also verified by SEM images. The optical properties of ZnO obtained by UV-Vis reflectance spectroscopy indicate a red shift of the band gap by ~0.1 eV.

In order to understand the response mechanism between plant stress, physiological indicators and hyperspectral indices, pot experiments were conducted on Suaeda salsa seedlings collected from a coastal wetland area to reveal the effects of salt stress on the physiological indicators and reflectance spectra of Suaeda salsa at the canopy and leaf level. The Suaeda salsa seedlings were exposed to seven salt treatments of different concentrations (0 mmol/L (control), 50 mmol/L, 100 mmol/L, 200 mmol/L, 300 mmol/L, 400 mmol/L, and 600 mmol/L) in natural conditions. The physiological indicators of plant height, fresh weight, dry weight, leaf succulence, chlorophyll content, and carotenoid content were measured, in addition to the reflectance spectra of Suaeda salsa at both the canopy and leaf level. Firstly, the effects of salt stress on the physiological indicators and reflectance spectra were analyzed by the qualitative and quantitative methods. Then, physiological indicators sensitive to salt stress were further retrieved. Afterwards hyperspectral indices such as a/b and ((a-b)/(a+b) ) sensitive to salt stress were also extracted by one-way analysis of variance (ANOVA) and Student-Newman-Keuls (S-N-K) comparison test. Our results showed that plant height, root length, leaf succulence, biomass, Chl-a, and Chl-b were sensitive to salt stress, while carotenoids (Car) and relative water content on the root were not significantly affected by salt stress. At the salt concentration of 200 mmol/L, plant height, biomass, relative water content, leaf succulence peaked. With enhanced salt stress, physiological indicators decreased. The first-order derivative spectral reflectance has the highest correlation with salt stress, compared to the control. The spectral index most sensitive to the salt stress at the canopy level is (D₉₀₃−D₈₅₁)/(D₉₀₃+D₈₅₁), for which the multiple determination coefficient (r²) is 0.9216. While the most sensitive spectral index to the salt stress is (D₄₄₂−D₆₆₇)/(D₄₄₂+D₆₆₇) at the leaf level, for which the r² is −0.898. In summary, the results indicated that there exists the quantitative relationship between the physiological indicators and spectra reflectance under salt stress and hyperspectral plant indices can effectively estimate the degree of salt stress. The inconsistency between the diagnostic hyperspectral plant indices at the canopy and leaf levels may be caused by the observation conditions, canopy structure.

Diffuse midline gliomas are among the deadliest human cancers and have had little progress in treatment in the last 50 years. Cell cultures of these tumors have been developed recently, but it is unknown the degree to which such cultures retain the characteristics of the source tumors. DNA methylation profiling offers a powerful tool to look at genome-wide epigenetic changes that are biologically meaningful and can help assess the similarity of cultured tumor cells to their in vivo progenitors. Paraffinized diagnostic tissue from three diffuse intrinsic pontine gliomas with H3 K27M mutations was compared with subsequent passages of neurosphere cell cultures from those tumors. Each cell line was passaged 3-4 times and analyzed with DNA methylation arrays and standard algorithms that provided comparison of diagnostic classification and cluster analysis. All samples tested maintained high classifier scores and clustered within the reference group of H3 K27M-mutant diffuse midline gliomas. There was a gain of 1q in all cell lines, with two cell lines initially manifesting the gain of 1q only during culture. In vitro cell cultures of H3 K27M-mutant gliomas maintain high degrees of similarity in DNA methylation profiles to their source tumor, confirming their fidelity even with some chromosomal changes.

Breast cancer is a global health concern, necessitating continuous advancements in diagnostic medical imaging technologies for early detection and improvement of treatment. This paper presents an overview of the past, present and future of breast cancer imaging using light and some results from the current studies. The paper specifically presents the role of Diffuse Optical Tomography (DOT) in breast cancer imaging. Conventional methods, such as X-ray mammography, face limitations. Diffuse Optical Tomography, a non-invasive light-based imaging modality can provide quantitative descriptive and architectural information about breast tissue. The paper discusses the key challenges and recent developments in breast cancer imaging using DOT to overcome some key challenges. This paper aims to contribute to the understanding of the evolving technological landscape in breast cancer imaging using light for improving early detection and patient outcomes.

Diffuse large B-cell lymphoma (DLBCL) is an aggressive and biologically heterogeneous disease. Approximately 40% of patients with DLBCL will experience disease relapse or will be refractory to first line chemoimmunotherapy. In recent years there have been several new therapeutic agents approved for the treatment of relapsed/refractory (R/R) DLBCL. These agents include anti-CD19 chimeric antigen receptor T-cell therapies (CAR T-cells) and monoclonal antibodies as polatuzumab and tafasitamab. Nevertheless, despite the high efficacy of all these new therapies, there are still patients who do not respond or relapse, representing an unmet clinical need. This review describes new promising therapies that are under investigation to treat R/R DLBCL.

The optical properties and physiology of biological tissue, as well as how near-infrared (NIR) light interacts with the tissue, both play a significant role in interpreting the tissue probing optical measurements, and in solving the inverse problem of near-infrared spectroscopy (NIRS)-based medical imaging modalities such as diffuse optical tomography and functional near-infrared spectroscopy. This paper discusses the optical properties of tissue, specifically in the NIR wavelength range, which influence NIRS measurements in NIRS-based medical imaging. There is an easy-to-understand explanation given in this paper of the NIR light-tissue interaction phenomenon. The mathematical explanation, the processes involved in the interaction, and the rationale for a few approximations are described. Various types of chromophores present in the tissue, their composition in the tissue, and how these chromophores overall affect the scattering and absorption of NIR light are presented. The absorption spectra of these chromophores are shown. Finally, the paper concludes with the author’s perspective on two NIRS-based medical imaging modalities, diffuse optical tomography, and functional near-infrared spectroscopy.

Reconstructing a 3D model of a scene from a set of multiple views poses a significant challenge in the field of computer vision. The advent of NeRF has marked a major breakthrough in this domain. However, there is a need to extend the capabilities of the NeRF model to enable editing tasks such as relighting and deformation, as well as to enhance its training efficiency. Neural reflectance fields introduce the concept of the reflectance equation into the NeRF framework to achieve relighting of the NeRF model. We leverage the TensoRF approach, which incorporates tensor decomposition and employs multiple tensors to store features, to expedite the training process of the NeRF model. Our novel method, called StensorR, combines the reflectance equation and tensor decomposition within the radiation field model framework. Differing from previous approaches, we employ a single tensor to store scene features and render the surface color of our scene using a simplified reflectance equation. This approach accelerates model convergence and enables relighting of the NeRF model. Experimental results demonstrate that our method achieves a 50% faster convergence rate compared to existing relighting radiation field models, while successfully enabling relighting and improving the quality of synthesized images from new viewpoints.

In the Mediterranean area, vegetation dynamics and phenology analyzed over a long time can have an important role in highlighting changes in land use and cover as well as the effect of climate change. Over the last 30 years, remote sensing has played an essential role in bringing about these changes thanks to many types of observations and techniques. Satellite images are to be considered an important tool to grasp these dynamics and evaluate them in an inexpensive and multidisciplinary way thanks to Landsat and Sentinel satellite constellations. The integration of these tools holds a dual potential: on one hand, allowing to obtain longer historical series of reflectance data, while on the other hand, making data available with a higher frequency even within a specific timeframe. The study aims to conduct a comprehensive cross-comparison analysis of long-time series pixel values in the Mediterranean regions. For this scope comparisons between Landsat-7 (ETM+), Landsat-8 (OLI), and Sentinel-2 (MSI) satellite sensors were conducted based on surface reflectance products. We evaluated these differences using Ordinary Least Squares (OLS) and Major Axis linear regression (RMA) analysis on points extracted from over 15,000 images across the Mediterranean basin area from 2017 to 2020. Minor but consistent differences were noted, necessitating the formulation of suitable adjustment equations to better align Sentinel-2 reflectance values with those of Landsat-7 or Landsat-8. The results of the analysis are compared with the most used harmonization coefficients proposed in the literature, revealing significant differences. The root mean square deviation, the mean difference and the orthogonal distance regression (ODR) slope show an improvement of the parameters for both models used (OLS and RMA) in this study. The discrepancies in reflectance values lead to corresponding variations in the estimation of biophysical parameters, such as NDVI, showing an increase in the ODR slope of 0.3. Despite differences in spatial, spectral, and temporal characteristics, we demonstrate that integration of these datasets is feasible through the application of band-wise regression corrections for a sensitive and heterogeneous area like those of the Mediterranean basin area.

Primary bone lymphoma of the scapula is a rare tumor that usually causes local pain. Presented patient suffered for two years from paresthesia, tingling, numbness, and edema of the little and ring finger. The 45-year-old man underwent several radiological and neurological assessments of the palm, elbow and neck prior to radiographs revealing the tumor of the left shoulder. Once diffuse large B cell lymphoma was confirmed, immunochemotherapy with rituximab, cyclophosphamide, doxorubicin, vincristine, and methylprednisolone (R-CHOP) started. The treatment was accompanied by antiviral treatment with lamivudine due to positive hepatitis B virus serology and with bisphosphonate treatment for the prevention of bone resorption. Once immunochemotherapy was finished, the treatment was supplemented by radiotherapy of the shoulder. After more than three years of accomplishing remission, the patient had an ischemic stroke manifesting with right-sided hemiparesis. Following the physical therapy, the patient is currently in the process of evaluation for thrombophilia, as well as further cardiac assessment due to the positive transcranial Doppler bubble test setting high suspicion for the presence of patent foramen ovale.

Neonatal diffuse cutaneous mastocytosis (NDCM) is defined as the infiltration of the epidermis by a clonal proliferation of mast cells, observed at birth, without initial signs of systemic involvement. The typical driver mutation is located in the KIT gene. We report a rare case of a boy, born at term, presenting already at birth with generalized subcutaneous nodules, on the face, scalp, trunk, back, hands, and feet. The spleen, liver and inflammatory markers were normal at birth. Tryptase was significantly elevated. Bone marrow biopsy showed no mast cell involvement at age 2 months. A punch biopsy at age 2 months revealed CD117-positive cells diffusely infiltrating the skin, with subsequent DNA NGS sequencing for the formalin fixed paraffin embedded tissue (FFPE) identifying the pathogenic NM_000222.3:c.1504_1509dup; p.(Ala502_Tyr503dup) variant in the KIT gene previously associated with cutaneous mastocytosis. At 2 years follow-up, he had splenomegaly and multiple cervical, and inguinal adenopathy while the skin nodules persisted especially on the scalp with accompanying pruritus. He received oral and local sodium cromoglycate, oral antihistamines, antibiotic cream for skin infection, and iron supplementation, however compliance to treatment was relatively low. The prognosis is difficult to predict, as he developed systemic involvement, failure to thrive and mild psychomotor delay. A case aggregation of NDCM reported in the literature was performed to provide a comprehensive overview of this rare pathology, to better understand the prognosis. NDCM is a life-threatening disease with severe complications. Almost half had severe complications, such as mast hepatosplenomegaly, adenopathy, bacterial infections, mast cell leukaemia, and systemic involvement.

Treating relapsed and refractory diffuse large B-cell lymphoma is still challenging for clinicians, but the available CAR-T and bispecific antibodies revolutionized therapy. Autologous stem cell transplantation was the most effective treatment modality previously. The authors report data from a single center over ten years. The retrospective study included 116 patients. There were 53 relapsed, 39 primary refractory cases, 19 had CNS involvement, and 5 received primary consolidation transplants. The median duration of follow-up was 46 months. The median event-free survival was 75 months, and the median overall survival was 105 months for all cases. Five-year overall survival was 59%, and event-free survival was 54%. Pretreatment prognostic factors at diagnosis had no effect on the outcome of transplantation. The authors found no difference between survival in relapsed or refractory cases, and the number of salvage lines or the germinal center / activated B-cell type also did not influence the results. Complete metabolic response before transplant confirmed by 18FDG PET/CT strongly affected survival. The pretransplant creatinine and CRP levels significantly influenced the long-term outcome. The number of stem cells infused did not affect survival, but engraftment within nine days did result in better survival. These data support the finding that the response to salvage therapy did select a better prognostic group who may still benefit from autologous transplantation.

Immune checkpoints are a set of molecules dysregulated in several human and canine cancers and aberrations of the PD-1/PD-L1 axis are often correlated with a worse prognosis. To gain insight into the role of immune checkpoints in canine diffuse large B-cell lymphoma (cDLBCL), we investigated PD-L1, PD-1 and CD8A expression by RNAscope. Results were correlated with several clinico-pathological features, including treatment, Ki67 index and outcome. A total of 33 dogs treated with CHOP (n=12) or CHOP plus APAVAC (n= 21) were included. PD-L1 signal was diffusely distributed among neoplastic cells, whereas PD-1 and CD8A were localized in tumor infiltrating lymphocytes. However, PD-1 mRNA was also retrieved in tumor cells. An association between PD-L1 and PD-1 scores was identified and a higher risk of relapse and lymphoma-related death was found in dogs treated with chemotherapy alone and dogs with higher PD-L1 and PD-1 scores. The correlation between PD-L1 and PD-1 is in line with the mechanism of immune checkpoints in cancers, where neoplastic cells overexpress PD-L1 that, in turn, binds PD-1 receptors in activated TIL. We also found that Ki67 index was significantly increased in dogs with the highest PD-L1 and PD-1 scores, indirectly suggesting a role in promoting tumor proliferation. Finally, even if the biological consequence of PD-1+ tumor cells is unknown, our findings suggest that PD-1 intrinsic expression in cDLBCL might contribute to tumor growth escaping adaptive immunity.

Several studies have shown that changes in incoming solar radiation and variations of the diffuse fraction can significantly modify the vegetation carbon uptake. Hence, monitoring the incoming solar radiation at large scale and with high temporal frequency is crucial for this reason along with many others. The EUMETSAT Satellite Application Facility for Land Surface Analysis (LSA SAF) operationally disseminates in near real time estimates of the downwelling shortwave radiation at the surface since 2005. This product is derived from observations provided by the SEVIRI instrument onboard the Meteosat Second Generation series of geostationary satellites, which covers Europe, Africa, the Middle East, and part of South America. However, near real time generation of the diffuse fraction at the surface level has only recently been initiated. The main difficulty towards achieving this goal was the general lack of accurate information on the aerosol particles in the atmosphere. This limitation is nowadays less important thanks to the improvements in atmospheric numerical models. This study presents an upgrade of the LSA-SAF operational retrieval method, which provides the simultaneous estimation of the incoming solar radiation and its diffuse fraction from satellite every 15 minutes. The upgrade includes a comprehensive representation of the influence of aerosols based on physical approximations of the radiative transfer within an atmosphere-surface associated medium. This article explains the retrieval method, discusses its limitations and differences with the previous method, and details the characteristics of the output products. A companion article will focus on the evaluation of the products against independent measurements of solar radiation. Finally, the access to the source code is provided through an open access platform in order to share with the community the expertise on the satellite retrieval of this variable.

The design is described of a readily useable technology for routine paddock-scale soil porosity estimation. The method is non-contact (proximal) and typically from sensors mounted on a small farm vehicle around 1 m above the soil surface. Challenges arise from the need to have a compact low-power rigid structure and to allow for pasture cover and surface roughness. The high-frequency regime for acoustic reflections from a porous material is a function of the porosity , the tortuosity , and the angle of incidence . There is no dependence on frequency, so measurements must be conducted at two or more angles of incidence in order to obtain two or more equations in the unknown soil properties and . A system requiring a single transmitter/receiver pair to be moved from one angle to another is not viable for rapid sampling. Therefore, the design includes at least two transmitter/reflector pairs placed at identical distances from the ground so that they would respond identically to power reflected from a perfectly reflecting surface. A single 25 kHz frequency is a compromise which allows for the frequency-dependent signal loss from a natural rough agricultural soil surface. Multiple-transmitter and multiple-microphone arrays are described which give a good signal to noise ratio while maintaining a compact system design. The resulting arrays have a diameter of 100 mm. Pulsed ultrasound is used so that the reflected sound can be separated from sound travelling directly through the air horizontally from transmitter to receiver. The average porosity estimated for soil samples in the laboratory and in the field is found to be within around 0.04 of the porosity measured independently. This level of variation is consistent with uncertainties in setting the angle of incidence, although assumptions made in modelling the interaction of ultrasound with the rough surface no doubt also contribute.

Cavitation resulting from underwater explosions in compressible multiphase or multicomp-onent flows presents significant challenges due to the dynamic nature of shock-cavitation-structure interactions, as well as the complex and discontinuous nature of the involved interfaces. Achieving accurate resolution of interfaces between different phases or components, in the presence of shocks, cavitating regions, and structural interactions, is crucial for modeling such problems. Furthermore, pressure convergence in simulations involving shock-cavitation-structure interactions requires accurate algorithms. In this research paper, we employ the diffuse interface method, also known as the interface capturing scheme, to investigate cavitation in various underwater explosion test cases near different surfaces; free surface and a rigid surface. The simulations are conducted using the Unstructured Compressible Navier-Stokes (UCNS3D) finite volume framework employing central-weighted essentially non-oscillatory (CWENO) reconstruction schemes, utilising the five-equation diffuse interface family of methods. Quantitative comparisons are made between the performance of both models. Additionally, we examine the effects of cavitation as a secondary loading source on structures, and evaluate the ability of the CWENO schemes to accurately capture and resolve material interfaces between fluids with minimal numerical dissipation or smearing. The results are compared with existing high-order methods and experimental data, where possible, to demonstrate the robustness of the CWENO schemes in simulating cavitation bubble dynamics, as well as their limitations within the current implementation of interface capturing.

Traumatic brain injury (TBI) affects millions of people annually, however, our knowledge of the diffuse pathologies associated with TBI is limited. As diffuse pathologies, including axonal injury and neuroinflammatory changes, are difficult to visualize in the clinical population, animal models are used. In the current study we used the central fluid percussion injury (CFPI) model in a micro pig to study the potential scalability of these diffuse pathologies in a gyrencephalic brain of a species with inflammatory systems very similar to humans. We found that both axonal injury and microglia activation within the thalamus and corpus callosum are positively correlated to the weight-normalized pressure pulse, while subtle changes in blood gas and mean arterial blood pressure are not. We also found that the majority of tissue generated up to 10 years previously is viable for immunofluorescent labeling after long-term refrigeration storage. This study indicates that a micro pig CFPI model could allow for specific investigations of various degree of diffuse pathological burdens following TBI.

Diffuse optical tomography (DOT) is an optical medical imaging method that can assess the structural properties of tissues and their functional characteristics, such as hemoglobin concentration, water content, as well as lipid concentration, via three-dimensional image reconstruction. This paper presents the theoretical basis and working principle of diffuse optical tomography. The paper explains how the optical properties of tissue can be imaged by photon migration techniques based on diffusion theory. The author presents the reasoning for near-infrared (NIR) imaging as the most effective technique in terms of quantitative recovery of spectroscopic optical parameters. This work also listed various advantages, applications, and challenges of DOT. The paper also briefly discusses current progress in near-infrared medical imaging and its future direction.

Diffuse large B-cell lymphoma (DLBCL) is the most common haematological malignancy in humans and dogs. Several studies disclosed some similarities between the two species, including the constitutive activation of NF- κB pathway as a fundamental underlying pathogenetic mecha-nism. In humans, downregulation of IL-1R8 is implicated in DLBCL development, but its role in dogs has not been explored so far. To gain insight into the pathogenesis of this tumor in dogs, we evaluated the mRNA and protein expression of IL-1R8 in 12 hyperplastic lymph nodes ob-tained from dogs not bearing tumors and from 50 dogs with DLBCL. Moreover, we analysed through qRT-PCR the expression of TLR7, TLR9, MYC, and p52 genes that are known to be in-volved in the IL-1R8 regulatory network. IL-1R8 and p52 were downregulated in DLBCLs com-pared to control lymph nodes (p<0.001), while a higher expression of TLR7, TLR9 and MYC was observed in tumors (p<0.01). Immunohistochemistry confirmed gene expression results, reveal-ing a significantly lower IL-1R8 staining score in DLBCLs compared to control lymph nodes (p<0.0001). Taken together, these results suggest that IL-1R8 downregulation may represent one of the mechanisms driving DLBCL pathogenesis in dogs, mainly through dysregulation of the Toll-like/Interleukin receptors signalling cascade and the aberrant activation of classical NF-κB pathway.

EIT-MESHER (https://github.com/EIT-team/Mesher) is C++ software, based on the CGAL library, which generates high quality Finite Element Model tetrahedral meshes from binary masks of 3D volume segmentations. Originally developed for biomedical applications in Electrical Impedance Tomography (EIT) to address the need for custom, non-linear refinement in certain areas (e.g. around electrodes), EIT-MESHER can also be used in other fields where custom FEM refinement is required, such as Diffuse Optical Tomography (DOT).

The distribution of Mexican Magnolia species´ occur under restricted climatic conditions. As many other tree species from the tropical montane cloud forests (TMCF), Magnolia species appear to be sensitive to drought. Through the use of dendrochronological techniques, this study aims to determine the climate influence on the vessel traits of M. vovidesii and M. schiedeana which are endangered tree species that are endemic to the Sierra Madre Oriental in eastern Mexico. Because most of the tree species in TMCFs are sensitive to climate fluctuations, it is necessary to investigate the differences in the climatic adaptability of the vessel architecture of these trees. This could allow us to further understand the potential peril of climate change on TMCFs. We compared vessel frequency, length and diameter in drought and non–drought years in two Mexican Magnolia species. We used tree–rings width and vessel traits to assess the drought effects on Magnolias’ diffuse–porous wood back to the year 1929. We obtained independent chronologies for M. vovidesii with a span of 75 years (1941–2016), while for M. schiedeana we obtained a span of 319 years (1697–2016). We found that temperature and precipitation are strongly associated with differences in tree–ring width (TRW) between drought and non–drought years. Our results showed anatomical differences in vessel trait response between these two Magnolia species to climatic variation. We suggest that our approach of combining dendroclimatic and anatomical techniques is a powerful tool to analyse anatomic wood plasticity to climatic variation in Magnolia species.

Cork oak tree (Quercus suber L.) symbolises Montado landscape in Portugal and is a central element in the country's social and economic history. In recent decades, the loss of thousands of cork oaks has been reported, revealing the ongoing decline of these agro-forestry ecosystems. This emblematic tree of the Mediterranean Basin is host to the soil-born root pathogen Phytophthora cinnamomi, an active cork oak decline driver. In this framework, the early diagnosis of trees infected by the oomycete by non-invasive methods should contribute to the sustainable management of cork oak ecosystems and motivated this work. Using leaf reflectance spectroscopy it was possible to distinguish plants inoculated with P. cinnamomi from non-inoculated plants in a long course assay and to argue about the factors contributing to this differentiation. Spectral acquisitions in the visible-near infrared (400–1100 nm) were performed at 63, 78, 91, 126 and 248 days after inoculation (DAI), on the abaxial and adaxial faces of the leaves, and the spectral data was arranged in a three-way array of samples × wavelengths × days. The separation of the two plant groups were attributed to variations in water content (4v (O−H)) and/or a shift in the red edge and to structural modifications in the epidermal layer and/or the mesophyll of the leaves observed in the visible range. These spectral signatures can assist in the field identification of cork oaks that are interacting with P. cinnamomi.

There is a growing need for an area-wide knowledge of SOC contents in agricultural soils at field scale for food security, monitoring long-term changes related to soil health and climate change. In Germany, large-scale SOC maps are mostly available with a spatial resolution of 250 m to 1 km2. The nationwide availability of both digital elevation models at various spatial resolutions and multi-temporal satellite imagery enables the derivation of multi-scale terrain attributes and Landsat-based multi-temporal soil reflectance composites (SRC) as explanatory variables. On the example of an Bavarian test of about 8000 km2, the scale-specific dependencies between the representativeness of 220 soil samples and different aggregation levels of the explanatory variables were analyzed for their scale-specific predictive power. The aggregation levels were generated by applying a region-growing segmentation procedure, the SOC content prediction was realized by the Random Forest algorithm. In doing so, established approaches of (geographic) object-based image analysis (GEOBIA) and machine learning were combined. The modeling results revealed scale-specific differences. Compared to terrain attributes, the use of SRC parameters lead to a significant model improvement at large field-related scale levels. The joint use of both terrain attributes and SRC parameters resulted in further model improvements. The best modeling variant is characterized by an accuracy of R2=0.84 and RMSE=1.99.

The optical response of bulk germanium sulfide (GeS) is investigated systematically using different polarization-resolved experimental techniques, such as photoluminescence (PL), reflectance contrast (RC), and Raman scattering (RS). It is shown that while the low-temperature (T=5 K) optical band-gap absorption is governed by a single resonance related to the neutral exciton, the corresponding emission is dominated by the disorder/impurity- and/or phonon-assisted recombination processes. Both the RC and PL spectra are found to be linearly polarized along the armchair direction. The low and room (T=300 K) temperature RS spectra consist of six Raman peaks identified with the help of Density Fuctional Theory (DFT) calculations: Ag1, Ag2, Ag3, Ag4, B1g1, and B1g2, which polarization properties are studied under four different excitation energies. We found that the polarization orientations of the Ag2 and Ag4 modes under specific excitation energy can be useful tools to determine the GeS crystallographic directions: armchair and zigzag.

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma and a heterogeneous disease characterized by mature B-cell neoplasms. The standard immunochemotherapy for DLBCL is R-CHOP, which includes rituximab, cyclophosphamide, doxoru-bicin, vincristine, and prednisone. Up to 30-40% of patients with DLBCL either exhibit primary refractory disease to standard treatment or experience relapse after the initial response. A 72-year-old man diagnosed with DLBCL involving chromosomal translocations t(1;22)(q21;q11.2) and t(6;18)(p25;q21) showed primary refractory disease after the fourth cycle of R-CHOP. The patient ultimately experienced cardiac involvement by the lymphoma and received salvage chemotherapy. He passed away about 15 months away after the diagnosis of DLBCL. We conducted fluorescence in situ hybridization (FISH) for further analysis of the chromosomal translocations. The breakpoint of chromosome 1q21 was located at a distance of around 151 Mb from the telomeric end of chromosome 1p. The breakpoint in chromosome 22q11 contains the immunoglobulin lambda locus. Furthermore, the breakpoint of chromosome 6p was in the telomeric region of chromosome 6p21. The breakpoint of chromosome 18q21 contains BCL2. This case report presents the first documented co-occurrence of chromosomal translocations t(1;22)(q21;q11.2) and t(6;18)(p25;q21) in a patient with DLBCL. These chromosomal translocations may indicate a worse clinical outcome.

Febrile neutropenia (FN) is a major concern in patients undergoing chemotherapy for diffuse large B-cell lymphoma (DLBCL); however, the overall risk of FN is difficult to assess. This study aimed to develop a model for predicting the occurrence of FN in patients with DLBCL. In this multicenter, retrospective, observational analysis, a multivariate logistic regression model was used to analyze the association between FN incidence and pretreatment clinical factors. We included adult inpatients and outpatients (aged ≥ 18 years) diagnosed with DLBCL who were treated with chemotherapy. The study examined 246 patients. Considering FN occurring during the first cycle of chemotherapy as the primary outcome, a predictive model with a total score of 5 points was constructed as follows: 1 point each for viral hepatitis, extranodal involvement, and a high level of soluble interleukin-2 receptor and 2 points for lymphopenia. The area under the receiver operating characteristic curve of this model was 0.844 (95% confidence interval: 0.777–0.911). Our predictive model can assess the risk of FN before patients with DLBCL start chemotherapy, leading to better outcomes.

The most common type of non-Hodgkin lymphoma in adults is diffuse large B-cell (DLBCL). There is a historical unmet need for more effective therapies in the 2nd and 3rd line setting. Emerging immunochemotherapies have shown activity in small studies of heavily pre-treated patients with prolonged remissions achieved in some patients. Anti-CD19 CAR (chimeric antigen receptor) T cells are potentially curative in the 3rd line and beyond setting and are under investigation in earlier lines of therapy.1 Antibody-drug conjugates (ADC’s) such as polatuzumab vedotin targeting the pan-B-cell marker CD79b has proven effectiveness in multiply-relapsed DLBCL patients. Tafasitamab (MOR208) is an anti-CD19 monoclonal antibody producing prolonged remissions when combined with Lenalidomide in patients who were not candidates for salvage chemotherapy or autologous stem cell transplant. Selinexor, an oral, small-molecule selective inhibitor of XPO1-mediated nuclear export (SINE), demonstrated prolonged activity against heavily-pretreated DLBCL without cumulative toxicity and is being investigated as part of an oral, chemotherapy-free regimen for relapsed aggressive lymphoma. This article reviews current strategies and novel therapies for relapsed/refractory DLBCL.

This work shows a correlation between light reflectance, absorption, and morphologies of series of (1-x) BM–x PT, (x = 0.0, 0.02, 0.04, 0.08, 0.12, 0.16, 0.24) ceramics composite. The (1-x) BM–x PT showed features of a black mirror with a low optical energy gap. The measured Vis-NIR diffused reflectance enabled the calculation of the energy gap using the modified Kubelka-Munk function. The estimated energy gap was lower than 1.5 eV related to low reflectance in the Vis-NIR range. Moreover, obtained histograms of grains, using scanning electron microscope, enabled the correlation between grains size and amount of lead titanate. We deduced from the ceramics surface morphology that marked porosity also induced reflectivity of low magnitude. We correlated the magnitude of the energy gap with phases of the BM-PT composite and with the electrical conductivity activation energy reported in the literature. Our results findings opened prospect studied materials for optical applications.

High-resolution laboratory-based thermal infrared spectroscopy is an up-and-coming tool in the field of geological remote sensing. Its spatial resolution allows for detailed analyses at centimeter to sub-millimeter scale. However, this increase in resolution creates challenges with sample characteristics such as grain size, surface roughness and porosity that can influence the spectral signature. This research explores the effect of rock sample surface preparation on the TIR spectral signatures. We applied three surface preparation methods (split, saw and polish) to determine how the resulting differences in surface roughness affects both the spectral shape as well as the spectral contrast. The selected samples are a pure quartz sandstone, a quartz sandstone containing a small percentage of kaolinite, and an intermediate-grained gabbro. To avoid instrument or measurement type biases we conducted measurements on three TIR instruments, resulting in directional hemispherical reflectance spectra, emissivity spectra and bi-directional reflectance images. Surface imaging and analyses were performed with scanning electron microscopy and profilometer measurements. We demonstrate that surface preparation affects the TIR spectral signatures influencing both the spectral contrast as well as the spectral shape. The results show that polished surfaces predominantly display a high spectral contrast while the sawed and split surfaces display up to 25% lower reflectance values. Furthermore, the sawed and split surfaces display spectral signature shape differences at specific wavelengths, which we link to mineral transmission features, surface orientation effects and multiple reflections in fine-grained minerals. Hence, the influence of rock surface preparation should be taken in consideration to avoid an inaccurate geological interpretation.

Diffuse optical tomography (DOT) technology enables a differentiation between oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the sensory and motor cerebral gyri, resulting in greater sensitivity for cerebral activation compared to functional magnetic resonance imaging (fMRI). Here, we introduce a novel approach where functional regions of interest (ROIs) are created based on the specific signal behavior observed in DOT measurements, in contrast to the conventional use of structural-ROIs obtained from anatomical information. The generation of cerebral activation maps involves using the general linear model (GLM) to compare the outcomes obtained from both the functional and structural ROI approaches. DOT-derived maps are then compared with maps derived from fMRI datasets considered the gold standard for assessing functional brain activity. The results obtained demonstrate the effectiveness of employing functional ROIs to improve the spatial location of functional activations in the sensory and motor cerebral gyri by leveraging the neural synchronization data provided by DOT. Furthermore, this methodology simplifies data processing in animal models, where anatomical differences compared to the human head can pose challenges. By incorporating functional ROIs prior to GLM application, this study offers enhancements to DOT analysis techniques and broadens its applicability in both human and animal models.

The concept of gray-zone lymphoma (GZL) has been progressively refined since its in-troduction in the literature in 1998. For several years, it was applied to a rather broad spectrum of conditions, posing the problem of the differential diagnosis between any type of Hodgkin lymphoma (HL) and diffuse large B-cell lymphoma, with special reference to primary mediasti-nal forms (PMBL). Officially recognized as a provisional entity in the 4th and revised 4th editions of the WHO Classification of Tumour of Haematopoietic and Lymphoid Tissues with the term “B-cell lymphoma unclassifiable with features intermediate between diffuse large B-cell lym-phoma and classical Hodgkin lymphoma”, it was limited to tumours, which showed either morphologic features reminiscent of classical HL (CHL) but carrying a complete B-cell pheno-type or conversely provided with a PMBL morphology but revealing CHL phenotypic charac-teristics. The definition of GZL has been further revised in the recently published International Lymphoma Classification and 5th Edition of the WHO Classification of Haemato-lymphoid Tu-mours, which have limited it to mediastinal neoplasms based on emerging molecular evidences. The aim of this review is to critically discuss the issue of GZL, also in the light of the suboptimal response to current therapies.

The presented results of simulations take into account the optical parameters of the selected sea region (from literature data on the southern Baltic Sea) and two optically extreme types of crude oil (from historical data) which exist in the form of a highly diluted oil-in-water emulsion (10 ppm). The spectral index was analyzed based on the results of modelling the radiance reflectance distribution for almost an entire hemisphere of the sky (zenith angle from 0 to 80o). The spectral index was selected and is universal for all optically different types of oil (wavelengths 650 and 412 nm). The possibility of detecting pollution in the conditions of the wavy sea surface (as a result of wind of up to 10 m/s) was studied. It has been also shown that if the viewing direction is close to a direction perpendicular to the sea surface, observations aimed at determining the spectral index are less effective than observation under the zenith angle of incidence of sunlight for all azimuths excluding the direction of sunlight specular reflection.

This study is aimed at demonstrating application of vegetation spectral techniques for detection and monitoring of impact of oil spills on vegetation. Vegetation spectral reflectance from Landsat 8 data were used in the calculation of five vegetation indices (normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), adjusted resistant vegetation index 2 (ARVI2), green-infrared index (G/NIR) and green-shortwave infrared (G/SWIR) from the spill sites (SS) and non-spill (NSS) sites in 2013 (pre-oil spill), 2014 (oil spill date) and 2015 (post-oil spill) for statistical comparison. The result shows that NDVI, SAVI, ARVI2, G/NIR and G/SWIR indicated certain level difference between vegetation condition at the SS and the NSS were significant with p-value <0.5 in December 2013. In December 2014 vegetation conditions indicated higher level of significant difference between the vegetation at the SS and NSS as follows where NDVI, SAVI and ARVI2 with p-value 0.005, G/NIR - p-value 0.01 and GSWIR p-value 0.05. Similarly, in January 2015 a very significant difference with p-value <0.005. Three indices NDVI, ARVI2 and G/NIR indicated highly significant difference in vegetation conditions with p-value <0.005 between December 2013 and December 2014 at the same sites. Post—spill analysis show that NDVI and ARVI2 indicated low level of significance difference p-value <0.05 suggesting subtle change in vegetation conditions between December 2014 and January 2015. This technique is essential for real time detection, response and monitoring of oil spills from pipelines for mitigation of pollution at the affected sites in the mangrove forest.

Soluble CD163 (sCD163) functions as a scavenger receptor for haptoglobin-hemoglobin complexes, and is mostly expressed by monocytes and macrophages. The level of soluble CD163 has been used to determine macrophage activation. Our goal was to determine whether the loading of M2 CD163 positive tumor-associated macrophages (TAMs) through the secretion of sCD163 affects overall survival in patients with DLBCL and eventually discriminates subgroups of patients with different prognosis. sCD163 levels were measured in 40 frozen serum samples from patients diagnosed with DLBCL and 30 healthy individuals (HI) using an enzyme-linked immunosorbent assay (ELISA). Statistical analyses were performed using SPSS version 28. The results showed that patients who achieved complete response after standard-of-care immuno-chemotherapy and were alive and disease-free after 12 months of follow-up, but had elevated sCD163 levels (above median) at diagnosis, presented a significantly worse overall survival compared to those with initial serum sCD163 levels below median (p=0.03). Consequently, serum sCD163 level in DLBCL patients may constitute a marker of long-term response to chemo-immunotherapy.

Diffuse intrinsic pontine glioma (DIPG) is recognized as a pediatric brainstem cancer with a 0% survival rate. On a molecular basis, DIPG commonly results from mutations in histone H3, specifically a mutation in the H3K27M gene, that promotes tumorigenesis and results in presentation of this fatal brainstem tumor. DIPG is challenging to treat, as surgical intervention is inefficacious due to the location where the glioma resides. To date, traditional treatments such as radiation, chemotherapy, and immunotherapy have not increased survival rates and have only been successful at relieving symptoms. Future therapeutic approaches such as proton beam radiation, Chimeric Antigen Receptor T Cell (CAR-T) immunotherapy, and alternative epigenetic pharmaceuticals are under investigation for potential benefits. Various clinical trials have also explored these treatment procedures to discover potential increases in survival rates in both animal and human studies. In this review, we will evaluate the pathology and molecular characteristics of DIPG, the current and future approaches to DIPG treatment; and, lastly, we will discuss clinical trials that have been completed to develop successful treatment options.

Pseudo-nitzschia spp. blooms are a recurrent problem in many coastal areas globally imposing some significant threats to the health of human, ecosystems and economy. Monitoring programmes have been established, where feasible, to mitigate the impacts caused by Pseudo-nitzschia spp. and other harmful algae blooms. The detection of such blooms from satellite data could really provide timely information on emerging risks but the development of taxa-specific algorithms from available multispectral data is still challenged by coupled optical properties with other taxa and water constituents, availability of ground data and generalisation capabilities of algorithms. Here, we developed a new set of algorithms (PNOI) for the detection and monitoring of Pseudo-nitzschia spp. blooms over the Galician coast (NW Iberian Peninsula) from Sentinel-3 OLCI reflectances using support vector machine (SVM). Our algorithm was trained and tested with reflectance data from 260 OLCI images and 4607 Pseudo-nitzschia spp. match up data points, of which 2171 were of high quality. The performance of no bloom/bloom model in the independent test set was robust, showing values of 0.80, 0.72 and 0.79 for area under the curve (AUC), sensitivity and specificity, respectively. Similar results were obtained by our below detection limit/presence model. We also present different model thresholds based on optimisation of true skill statistic (TSS) and F1-score. PNOI outperforms linear models, while its relationship with in-situ chlorophyll-a concentrations is weak demonstrating poor correlation with the phytoplankton abundance. We showcase the importance of PNOI algorithm and OLCI sensor for monitoring the bloom evolution between the weekly ground sampling and during periods of ground data absence, such as due to Covid-19.

To enhance the mechanical properties (i.e. strength and elongation) of the face-centered cubic (fcc) α-phase in the Au-Cu-Al system, this study focused on the introduction of the martensite phase (doubled B19 (DB19) crystal structure of Au2CuAl) via the manipulation of alloy compositions. Fundamental evaluations, such as microstructure observations, phase identifications, thermal analysis, tensile behavior examinations, and reflectance analysis have been conducted. The presence of fcc annealing twins was both observed in the optical microscope (OM) and the scanning electron microscope (SEM) images. Both the strength and elongation of the alloys were greatly promoted while the DB19 martensite phase was introduced into the alloys. Amongst all the prepared specimens, the 47Au41Cu12Al and the 44Au44Cu12Al alloys performed the optimized mechanical properties. The enhancement of strength and ductility in these 2 alloys was achieved while the stress plateau was observed during the tensile deformation. A plot of the ultimate tensile strength (UTS) against fracture strain was constructed to illustrate the effects of the introduction of the DB19 martensite phase on the mechanical properties of the alloys. Regardless of the manipulation of the alloy compositions and the introduction of the DB19 martensite phase, the reflectance stayed almost identical to pure Au.

This paper presents an overview of tomography and different tomographic imaging modalities. The goal of this paper is to provide an understanding of various imaging modalities; in particular, how the imaging is performed, working principles, and applications. It was not intended to provide the in-depth mathematical principles of these imaging modalities, rather this paper focuses on providing the knowledge in an easy-to-grasp manner for the readers' benefit. Imaging modalities are categorized based on the physics behind image generation. First, the paper explains the general tomography principle. Then explains Ultrasound Imaging, Electrical Impedance Tomography, Computed Tomography, Magnetic Resonance Imaging (MRI), Photoacoustic Tomography (PAT), and Positron Emission Tomography (PET). In the end, the paper provides the fundamentals and review of two relatively new imagining modalities, Diffuse Optical Tomography (DOT) and functional Near-infrared Spectroscopy (fNIRS).

Diffuse intrinsic pontine gliomas (DIPGs) account for ~15% of pediatric brain tumors, which invariably present with poor survival regardless of treatment mode. Several seminal studies have revealed that 80% of DIPGs harbor H3K27M mutation coded by HIST1H3B, HIST1H3C and H3F3A genes. The H3K27M mutation has broad effects on gene expression and is considered a tumor driver. Determination of the effects of H3K27M on posttranslational histone modifications and gene regulations in DIPG is critical for identifying effective therapeutic targets. Advanced animal models play critical roles in translating these cutting-edge findings into clinical trial development. Here, we review current molecular research progress associated with DIPG. We also summarize DIPG animal models, highlighting novel genomic engineered mouse models (GEMMs) and innovative humanized DIPG mouse models. These models will pave the way towards personalized precision medicine for the treatment of DIPGs.

Geo-information about the spectral variability of the water-leaving radiance is the key to the validation of satellite and in situ measurements and the development of regional algorithms. In this study, using cluster analysis, five trends were identified that are characteristic of various phenomena in the northwestern part of the Black Sea (summer and winter blooms, turbid waters, river runoff). Typical values of the remote sensing reflectance coefficient are calculated for each case. Additionally, the standard values of the color indices for each cluster are calculated. It is shown that the ratio of the color index CI(412/443 nm) is slightly variable and equals 0.8±0.07.This can be a reference point for recovering incorrect (negative) satellite Rrs(λ) values in the shortwave region. In a similar way, the color index was calculated according to the MODIS and VIRS data, it was shown that on days with a turbid atmosphere (high AOT values), the standard deviation of the color index is 30%. For days with a clear atmosphere, the color index is close to the in situ results.

Solar reflective index (SRI) is one of the important parameters in the analysis of a building’s energetic and thermal performance, especially for “cool” reflective paints or coatings. However, there exists less information on the typical performance of the cool materials exposed for long term in the Middle East and more specifically in the United Arab Emirates (UAE). In this study, we determined values of reflectance, emittance, solar reflective index (SRI), and color difference, for three different high SRI white paints exposed naturally on low and high sloped racks for three years. After 3 years, reflectance values of exposed paint panels significantly decreased with an increased color difference in comparison with original unexposed paint surfaces. Emissivity of the paint changed very little for all of the exposed samples, but SRI, determined from both the reflectance and emittance, was reduced from between 95 and 110 to between 60 and 90 after three years. This appeared to be related to exposure to high temperatures, UV radiation, and adhesion of airborne contaminants in conjunction with low precipitation. Macroscopically, panels exposed on a low slope were the most discolored with the greatest presence of dust infusion and reduction in increase in surface temperatures which was demonstrated through thermal imaging. Such natural weathering research study is necessary for the development of standard exposure tests and determination of various control elements to increase the durability of cool materials in hot and arid climatic conditions of UAE.

Survivors of severe brain injury may require care in a neurointensive care unit (neuro-ICU), where the brain is vulnerable to secondary brain injury. Thus, there is a need for noninvasive, bedside, continuous cerebral blood flow monitoring approaches in the neuro-ICU. Our goal is to address this need through combined measurements of EEG and functional optical spectroscopy (EEG-Optical) instrumentation and analysis to provide a complementary fusion of data about brain activity and function. The present case demonstrates in a patient with traumatic brain injury, noninvasive cerebral blood flow transients can be recorded that correlate with gold-standard invasive measurements and with the frequency content changes in the EEG data during clinical care.

Diffuse large B cell lymphoma (DLBCL) is curable with chemoimmunotherapy in ~65% of patients. One of the hallmarks of the pathogenesis and resistance to therapy in DLBCL is inhibition of apoptosis, which allows malignant cells to survive and acquire further alterations. Inhibition of apoptosis can be the result of genetic events inhibiting the intrinsic or extrinsic apoptotic pathways, as well as their modulators, such as the inhibitor of apoptosis proteins, P53, and components of the NF-kB pathway. Mechanisms of dysregulation include upregulation of anti-apoptotic proteins and downregulation of pro-apoptotic proteins via point mutations, amplifications, deletions, translocations, and influences of other proteins. Understanding the factors contributing to resistance to apoptosis in DLBCL is crucial in order to be able to develop targeted therapies that could improve outcomes by restoring apoptosis in malignant cells. This review describes the genetic events inhibiting apoptosis in DLBCL, provides a perspective of their interactions in lymphomagenesis, and discuss their implication for the future of DLBCL therapy.

The accurate prediction of the solar Diffuse Fraction (DF), sometimes called the Diffuse Ratio, is an important topic for solar energy research. In the present study, the current state of Diffuse Irradiance research is discussed and then three robust, Machine Learning (ML) models, are examined using a large dataset (almost 8 years) of hourly readings from Almeria, Spain. The ML models used herein, are a hybrid Adaptive Network-based Fuzzy Inference System (ANFIS), a single Multi-Layer Perceptron (MLP) and a hybrid Multi-Layer Perceptron-Grey Wolf Optimizer (MLP-GWO). These models were evaluated for their predictive precision, using various Solar and Diffuse Fraction (DF) irradiance data, from Spain. The results were then evaluated using two frequently used evaluation criteria, the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE). The results showed that the MLP-GWO model, followed by the ANFIS model, provided a higher performance, in both the training and the testing procedures.

This paper discusses a cross-disciplinary, international collaboration aimed at researching a series of 15th century choir books at the abbey of San Giorgio Maggiore on the homonymous island in Venice. Produced for the abbey itself, the books have never left the island during their 500-years history, thereby allowing a unique opportunity to analyse historic artefacts, which have undergone little modification over time. Prompted by ongoing cataloguing work on the manuscripts, a week-long analytical campaign using a combination of non-invasive analytical methods used in portable configuration allowed the comprehensive characterisation of ten volumes. The manuscripts’ palette and painting techniques were analysed using near-infrared imaging, reflectance spectroscopy in the UV-vis-NIR range, Raman spectroscopy, X-ray fluorescence mapping and digital microscopy. The paper will discuss the challenges linked to the fragility and the large dimensions of the volumes as well as the most interesting results of the investigation. These include the detection of unusual painting materials such as bismuth ink, as well as the discovery of a less homogeneous palette than originally expected, which prompted a partial revision of the attribution of the decoration in one of the volumes to a single artist.

In ore regions impacted by mining and metal smelting emissions, distinguishing between geogenic anoma-lies and anthropogenic contamination poses a significant challenge. In a study from two areas with different mining histories in the Ore Mountains, Czech Republic, we demonstrate that targeted sampling of topsoils and subsoils respecting local geology and correct soil data treatment respecting soil textural variability effects are indispensable to correctly construct and interpret geochemical maps and identify anthropogenic contam-ination by As, Cu, Pb, and Zn. The list of analysed elements must include both potentially toxic and lithogenic elements, otherwise natural controls of soil composition cannot be deciphered. By using empirical cumulative distribution functions, we found that local backgrounds for As/Fe and Pb/Ti are significantly naturally ele-vated (5.7 to 9.8 times and 2.1 to 2.7 times higher, respectively) compared to the global averages. We con-structed geochemical maps with topsoil minus subsoil concentrations to show the main directions of spreading anthropogenic contamination. The anthropogenic diffuse contamination contribution was calcu-lated (1.12·10-4 and 1.42·10-4 for As/Fe and 16.5·10-4 and 16.2·10-4 for Pb/Ti, respectively), which corresponds to topsoil enrichment by ca. 15 and 14 mg kg-1 for As and ca. 35 and 42 mg kg-1 for Pb in the two study areas. Our study thus provided the first published quantitative estimates of geogenic and anthropogenic contribution to this well-known montane area. The obtained estimates were comparable to the results obtained previously from the local peat archives. The approach we used is efficient in deciphering natural and anthropogenic controls of PTEs in geochemically complicated areas.

Diffuse interstitial lung diseases (DILD) are a heterogeneous group of over 200 entities, some with dramatical evolution and poor prognostic. Because of their overlapping clinical, physiopathological and imagistic nature, successful management requires early detection and proper progression evaluation. This paper tests a complex networks (CN) algorithm for imagistic aided diagnosis fitness for the possibility of achieving relevant and novel DILD management data. 65 DILD and 31 normal high resolution computer tomography (HRCT) scans were selected and analyzed with the CN model. The algorithm is showcased in two case reports and then statistical analysis on the entire lot shows that a CN algorithm quantifies progression evaluation with a very fine accuracy, surpassing functional parameters’ variations. The CN algorithm can also be successfully used for early detection, mainly on the ground glass opacity Hounsfield Units band of the scan.

All empirical water column correction methods have consistently been reported to require existing depth sounding data for the purpose of calibrating a simple depth retrieval model; they yield poor results over very bright or very dark bottoms. In contrast, we set out to (i) use only the relative radiance data in the image along with published data, and several new assumptions, (ii) in order to specify and operate the simplified radiative transfer equation (RTE), (iii) for the purpose of retrieving both the satellite derived bathymetry (SDB) and the water column corrected spectral reflectance over shallow seabeds. Sea truth regressions show that SDB depths retrieved by the method only need tide correction. Therefore it shall be demonstrated that, under such new assumptions, there is no need (i) for formal atmospheric correction, (ii) nor for conversion of relative radiance into calibrated reflectance , (iii) nor for existing depth sounding data, to specify the simplified RTE and produce both SDB and spectral water column corrected radiance ready for bottom typing. Moreover, the use of the panchromatic band for that purpose is introduced. Altogether, we named this process the Self-Calibrated Supervised Spectral Shallow-sea Modeler (4SM). This approach requires a trained practitioner, though, to produce its results within hours of downloading the raw image. The ideal raw image should be a “near-nadir” view, exhibit homogeneous atmosphere and water column, include some coverage of optically deep waters and bare land, and lend itself to quality removal of haze, atmospheric adjacency effect, and sun/sky glint.

ABSTRACT Two years after first patients approached the emergency rooms of hospitals in Wuhan becouse of respiratory distress,thousend of SARS-CoV-2 infected persons continue to die every day worldwide.SARS-CoV-2-infected patients undergo a process of dehydration and malnutrition before they develop respiratory problems and approach the emergency room of a hospital.This is,in many cases, the consequence of high fever which causes massive loss of fluids. In addition loss of appetite, is responsible for the deficit of protein intake.Most of the virus-infected patients admitted to the emergency room are therefore hypovolemic and hypoproteinemic and suffer of respiratory distress accompanied by ground grass opacities at CT-scan of the lungs.Critically ill patients are treated following the guidelines for treatment of septic shock but with „conservative“ fluid replacement and administration of diuretics to assure sufficient hourly urine production. The combination of conservative fluid administration with reduced protein content in the enterally administered diet, together with administration of diuretics, has severe hemodynamic consequenses in mostly aged,dehydrated,critically ill patients. Many of them will develop acute kidney injury in the next 24 hours.In most of the cases, patients continue to loose weight by loosing skeletal muscle mass. Ischemic damage in the lung capillaries is responsible for the acute respiratory distreass syndrome (ARDS) and for the hallmark of autoptic findings,diffuse alveolar damage (DAD) characterized by hyaline membrane formation,fluid invasion of the alveoli recruitment of some inflammatory cells and progressive arrest of blood flow in the pulmonary vessels.The consequence is progressive congestion , increase of lung weight and progressive hypoxia (progressive severity of ARDS).Sequestration of blood in the lungs worsen hypovolemia and ischemia in different organs.This is most probably responsible for recruitment of inflammatory cells and for persistance of elevated serum levels of positive acute-phase markers and of hypoalbuminemia. Autoptic studies have been performed mostly in patients who died in the ICU after SARS-CoV-2-infection because of progessive ARDS.In those patients, tubulus epithelium necrosis in the kidney is a frequent finding as it has been the case in the first SARS-CoV-1 pandemic.In the death certification charts, many times weeks after first symptoms have started ,cardiac arrest is the cause of death after respitatory insufficiency.Replacement therapy with sufficient amount of fluid and albumin should be part of the early individualized life-saving supportive measures avoiding mechanical ventilation.

The transmission of light is one of the key optical processes in the terrestrial environment (the atmosphere and underlying surfaces). The dependence of light transmittance on the illumination/observation conditions and optical properties of the atmosphere–underlying system can be studied using the integro-differential radiative transfer equation. However, for numerous applications a set of analytical equations is needed to describe the transmitted light intensity and flux. In this paper, we describe various analytical techniques to study light transmittance through light scattering and absorbing media. A physical significance and improved mathematical accuracy of approximations are provided using the analytical models for the diffusion exponent, average cosine of the light field, spherical and plane albedos. The accuracy of various approximations is studied using exact radiative transfer calculations with various scattering phase functions, single-scattering albedos, observational conditions, and optical depths.

Different notions of entropy can be identified in different communities: (i) the thermodynamic sense, (ii) the information sense, (iii) the statistical sense, (iv) the disorder sense, and (v) the homogeneity sense. Especially the “disorder sense” and the “homogeneity sense” relate to and require the notion of space and time. One of the few prominent examples relating entropy to geometry and to space is the Bekenstein-Hawking entropy of a Black Hole. Although being developed for the description of a physics object—a black hole—having a mass, a momentum, a temperature, a charge etc. absolutely no information about these attributes of this object can eventually be found in the final formula. In contrast, the Bekenstein-Hawking entropy in its dimensionless form is a positive quantity only comprising geometric attributes like an area A—which is the area of the event horizon of the black hole-, a length L_P—which is the Planck length - and a factor ¼. A purely geometric approach towards this formula will be presented. The approach is based on a continuous 3D extension of the Heaviside function, with this extension drawing on the phase-field concept of diffuse interfaces. Entropy enters into the local, statistical description of contrast respectively gradient distributions in the transition region of the extended Heaviside function definition. The structure of the Bekenstein-Hawking formula eventually is derived for a geometric sphere based on mere geometric-statistic considerations.