Rough Estimate Research Articles

Fabrication of thin inorganic temperature-sensitive paint using ball milling and its temporal response delay

Temperature-sensitive paint (TSP) is widely used to measure the temperature distribution. A TSP is advantageous in terms of cost and spatiotemporal resolution. However, regardless of its thickness, a finite thickness introduces errors. An important issue regarding the thickness of the TSP is the temporal response delay. In this study, a thin TSP was fabricated using ball milling, and TSPs with a thickness <2 µm could be produced. However, the phosphorescence intensity decreased drastically after ball milling. A special system was designed to measure the temporal response delay caused by the TSP layer. A high-resolution measurement technique (210 kHz and 1.05 µm/pixel) was employed. Time delays were defined and calculated using both experimental and numerical approaches. Numerical simulations were conducted using the experimental data and the thermal properties of ZnO:Zn and epoxy, given that the thermal properties of TSP are unknown. From the time delay, it was found that the thermal diffusivity of the TSP was between those of ZnO:Zn and epoxy, and this result was considered reasonable. Although this study provides only a rough estimation of the thermal diffusivity of TSPs, it reveals a relationship between the time delay and thermal diffusivity, opening up the possibility of calculating the thermal diffusivity from the time delay. Our results can help advance the application of TSPs for temperature measurements in highly dynamic environments.

Performance of fishery carbon sink of oyster aquaculture (mainly Crassostrea hongkongensis) in Guangxi, China: A long-term (2003–2022) analysis

Fishery carbon sink (FCS) is a concept of promoting the absorption of carbon dioxide (CO2) by ocean through enhancing the biological process in fishery resources, and then removing carbon from water body through harvesting aquatic fishery resources. Among marine organisms, bivalves are one of the seafood with high potential in developing FCS. Although the FCS of China bivalve aquaculture has been estimated, these studies were rough estimation without specified contribution of different bivalve species. In this context, based on 20 years data, this study was conducted to evaluate the FCS performance of oyster, especially Crassostrea hongkongensis (accounted for 30% of oyster production in China) farmed in Guangxi, China. The results of this study revealed that the oyster aquaculture plays an increasing role in FCS, especially in 2010 and onward. The oyster aquaculture industry in Guangxi removed about 0.05 million tons (average) of carbon from the sea every year through FCS, and is expected to remove more than 0.07 million tons of carbon from the sea in future. The results of this study not only can fill in the knowledge gap on the FCS of oyster aquaculture in Guangxi, China, but also can provide a guideline to study the FCS of other bivalve species in different regions.

An Experimental Study on Nodular Iron Machined Surfaces Utilizing a Capable 2D Finite Element Model for Precise Surface Roughness Estimation

Nodular iron plays a crucial role in various industries, especially in large-scale applications such as gearboxes. Ensuring that nodular iron remains free from oil leakage and that contact surfaces are properly aligned is essential, given its operational requirements. Achieving flat contact faces through precise machining is therefore of utmost importance. As surface roughness and flatness are closely linked, it is vital to investigate the machining process parameters involved. This study focuses on addressing surface quality issues with EN-GJS-600-3 cast iron by optimizing machining parameters. CMM measurements were utilized to analyze the relationship between surface roughness and flatness, with a surface profile used to assess flatness. Furthermore, a new 2D surface roughness estimation method (2D-SRET) was created and tested with experimental data in order to improve the precision of assessing the discrete flat surface machining procedure.

Time-difference reassigned transform with application to time difference of arrival for impulsive signal

Time difference of arrival (TDOA) is essential in localization, communication, and navigation. Under ambient noise interference, the impulsive signal is transmitted over a long distance and reaches the sensor with a low signal-to-noise ratio (SNR). Aiming to achieve a precise time delay estimation in scenarios with low SNR, this paper extends the time-reassigned extracting transform (TRET) theory to TDOA and proposes a time difference rearrangement extracting transform (TDRT) algorithm. The implementation process of the proposed algorithm comprises three steps. Initially, a rough two-dimensional time delay estimation is obtained by calculating the partial derivative of the short-time cross-power spectrum with respect to the frequency variable. Secondly, a rearrangement operation separates the signal's time-frequency (TF) points from the noise. Thirdly, a refined TDOA estimation is obtained by inverse Fourier transforming TF points extracted from the time-delay energy ridge. Simulation results show that the TDRT algorithm is effective in time delay estimation. Furthermore, experimental results prove that the performance of the TDRT algorithm outperforms comparable algorithms in low SNR environments.

Estimating the parameters of competitive Langmuir adsorption isotherms from measured responses to rectangular pulse injections exploiting equilibrium theory

Knowledge of adsorption isotherms is essential for the design and optimization of chromatographic separation processes. Since the experimental determination of these thermodynamic functions is a complicated and time consuming task, there is a need to develop methods which are fast and easy to apply. An attractive group of methods is based on neglecting in the analysis of measured dynamic elution profiles all kinetic effects. These methods assume the validity of an isotherm model equation and exploit the possibility to solve analytically the column mass balance equations of the equilibrium model. If just the dispersive part of an elution profile is, the method is known as “elution by characteristic point” (ECP). The ECP method has been applied successfully to analyse column effluent profiles of single component dissolved in a mobile phase. This work extends the ECP method to analyse just the shapes of elution profiles recorded after injecting samples that contain two key components to be separated. The extended ECP method requires recording only one overloaded elution profile for the two-component mixture and offers a fast and efficient way to estimate isotherm model parameters. The method is in particular attractive if there is limited access to the pure components, as for example in cases of enantiomers. The underlying theory is presented and applied for the case that the adsorption equilibria can be described satisfactorily by the classical competitive Langmuir model. Core of the theory are the available analytical equations describing the outlet concentration profiles of the two solutes for the equilibrium controlled case the. Considering a case study, it is shown that the extended ECP method can be applied successfully for columns characterized by 2500 or more theoretical plates. However, the method can be useful also for columns with lower efficiency. It provides then a rough estimation regarding the isotherm courses.

Impedance phase-dependent correction factor for a tonehole model

The upper and lower end corrections of an open tonehole in a woodwind instrument are often accommodated by adding them to the physical thickness of the wall to create an effective thickness used in calculating the impedance of the tonehole. A rough estimate of the correction often used is 1.5 time the tonehole radius (1.5b), while other more rigorous treatments yield values in this vicinity. These values are usually independent of frequency or are constrained to a range of geometric tonehole and bore dimensions. The data from this study showed a strong and significant frequency dependency that produced a large range of correction values between about 0.5b and 1.5b. This variation correlated with the phase of the impedance of the highest open tonehole, and generally increased with increasing sounding frequency. This paper will discuss the conditions under which the measurements were made and how the correction factors were obtained, and will propose how the observed frequency dependence can be incorporated into the correction factor through the phases of the impedances of the open toneholes.

Frequency estimation of underwater acoustic targets based on improved FRI method

The line spectrum information of a ship’s radiated noise signal is often regarded as an important feature used to distinguish between targets. In this paper, an improved FRI (finite rate of innovation) method is proposed to estimate the low-frequency line spectra of the radiated noise from underwater acoustic passive targets under the condition of finite sampling points. First, a preliminary rough estimation of the frequency is performed using the Fourier transform. Then, the multichannel signal data are iteratively fitted based on the polynomial-ratio form model. The optimal estimation results are finally determined based on the residuals between the data and the model in the fitting process. Simulation experiments prove that compared with the original FRI algorithm, the method proposed in this paper can estimate line spectral frequency more efficiently under the condition of low signal-to-noise ratio (SNR), and can achieve fast convergence with shorter operation time. The experimental data processing results prove that the method can realize high-precision extraction of line spectrum information of ship noise.

Diffuse interstellar bands in Gaia DR3 RVS spectra

Diffuse interstellar bands (DIBs) are weak and broad interstellar absorption features in astronomical spectra that originate from unknown molecules. To measure DIBs in spectra of late-type stars more accurately and more efficiently, we developed a random forest model to isolate the DIB features from the stellar components. We applied this method to 780 thousand spectra collected by the Gaia Radial Velocity Spectrometer (RVS) that were published in the third data release (DR3). After subtracting the stellar components, we modeled the DIB at 8621 Å (λ8621) with a Gaussian function and the DIB around 8648 Å (λ8648) with a Lorentzian function. After quality control, we selected 7619 reliable measurements for DIB λ8621. The equivalent width (EW) of DIB λ8621 presented a moderate linear correlation with dust reddening, which was consistent with our previous measurements in Gaia DR3 and the newly focused product release. The rest-frame wavelength of DIB λ8621 was updated as λ0 = 8623.141 ± 0.030 Å in vacuum, corresponding to 8620.766 Å in air, which was determined by 77 DIB measurements toward the Galactic anticenter. The mean uncertainty of the fit central wave-length of these 77 measurements is 0.256 Å. With the peak-finding method and a coarse analysis, DIB λ8621 was found to correlate better with the neutral hydrogen than with the molecular hydrogen (represented by 12CO J = (1−0) emission). We also obtained 179 reliable measurements of DIB λ8648 in the RVS spectra of individual stars for the first time, further confirming this very broad DIB feature. Its EW and central wavelength presented a linear relation with those of DIB λ8621. A rough estimation of λ0 for DIB λ8648 was 8646.31 Å in vacuum, corresponding to 8643.93 Å in air, assuming that the carriers of λ8621 and λ8648 are comoving. Finally, we confirmed the impact of stellar residuals on the DIB measurements in Gaia DR3, which led to a distortion of the DIB profile and a shift of the center (≲0.5 Å), but the EW was consistent with our new measurements. With our measurements and analyses, we propose that the approach based on machine learning can be widely applied to measure DIBs in numerous spectra from spectroscopic surveys.

Temporal change of seafloor scattering and its dependence on environmental parameters in shallow-water sandy sites

In the ocean, the performance of active sonar systems used for object detection and seafloor characterization can be affected when the acoustic properties of the seafloor change due to near-bottom hydrodynamics and biological activity. Determining the dominant environmental mechanisms and corresponding time scales that regulate seafloor scattering will increase our understanding of the performance of these remote-sensing applications. To this end, a high-frequency active acoustic system (operating at 38 kHz, 70 kHz and 200 kHz), a wave-sensing CTD, and a stereo camera were deployed on the seafloor in a series of experiments lasting from two weeks to five months. Seafloor scattering measurements were obtained in two shallow water locations in New Hampshire, USA: a wave-dominated site and a tidal current dominated site. Daily and weekly trends in mean scattered levels and the mechanisms causing their temporal variability are discussed. The temporal change in scattering as a function of angle is compared to the small-slope approximation model where seafloor roughness estimates were obtained using stereophotogrammetry.

Two new genera and species of the valvatiform hydrobiid snails (Caenogastropoda: Truncatelloidea: Hydrobiidae) from Morocco.

Stygobiont and crenobiont minute gastropods representing the family Hydrobiidae (Caenogastropoda: Truncatelloidea), characterized by the valvatoid low-spired shell, were collected from one spring and four wells in Bouregreg region, NW Morocco. The shells were photographed and measured; shell biometry is illustrated with principal component analysis. Penes were illustrated and described. Mitochondrial cytochrome oxidase subunit 1 (COI) and 16S rRNA, as well as nuclear 18S rRNA sequences were used to infer the phylogeny. The snails represented two genera, both new to science. Their closest relatives were taxa from the Iberian Peninsula, the rough molecular estimate of the time of divergence between these Moroccan and Iberian genera coincided with the Pliocene Flooding, which restored the Strait of Gibraltar to connect the Mediterranean Basin with Atlantic Ocean.

Quantification of losses in bent waveguides within DBR-RW laser diodes emitting at 785 nm

An experimental study of straight and bent distributed Bragg reflector (DBR) ridge waveguide (RW) lasers and Fabry–Pérot (FP) RW lasers emitting at 785 nm is presented. To determine the losses introduced by the bent waveguides within DBR-RW lasers, different laser designs were manufactured and characterized. The bent waveguides investigated here within DBR-RW laser diodes are sine-shaped S-bends. S-bends with three different lateral offsets are manufactured. The experimental characterization of FP lasers and the straight DBR-RW lasers with different coatings at the rear facet enables a rough estimation of the losses caused by the DBR grating and the determination of the DBR reflectivity. Furthermore, additional losses in the bent DBR-RW lasers caused by the S-bend (i.e. radiation and scattering losses) are quantified by comparing them to the straight DBR-RW lasers. Within the active resonator, the S-bend losses amount to α Bend = 0.6 cm−1 (α Bend = 0.5 dB) for the smallest manufactured lateral S-bend offset H = 40 μm. For both straight and bent DBR-RW lasers spectrally narrow single-mode emission is obtained. A lateral beam width of 3.8 μm (using second moments) and a lateral far-field angle of about 18° and 19.5° (using second moments) for the straight and S-bend DBR-RW are measured, respectively. This gives a lateral beam propagation ratio of 1.2 and 1.3 (using second moments) for straight and S-bend DBR-RW, respectively. The radiation loss in dependency of the lateral S-bend offset is simulated and compared to experimentally estimated S-bend losses for bent DBR-RW lasers (H = 40 μm, H = 60 μm and H = 70 μm).

Parameter Inference of a State-of-the-Art Physical Afterglow Model for GRB 190114C

A state-of-the-art semi-analytic gamma-ray burst (GRB) afterglow model with synchrotron self-Compton (SSC) emission has been applied for the first time for parameter inference using real GRB data. We analyzed the famous GRB 190114C as a case study. GRB 190114C, characterized by its long duration and high luminosity, was observed by many ground-based and orbiting telescopes spanning a wide range of electromagnetic wavelengths, from radio to GeV gamma rays. We used two advanced algorithms for inference: a nested sampling algorithm called UltraNest and an MCMC algorithm emcee. Evoking the standard afterglow model, the inference result and the best-fit values lead to an initial bulk Lorentz factor (a rough estimate of Γ=526), which aligns with the values often seen in GRBs identified by the Fermi-LAT instrument. Similarly to the best-fit values of other studies in the literature, the derived values of microphysical parameters, the circumburst density, and the kinetic efficiency are consistent with those found after modeling the multi-wavelength observations in GRB 190114C. We show that the SSC from the forward-shock region can only describe the highest-energy photons above a few GeVs.

Detection of normal and abnormal brain tumor MRI images using machine learning approaches

&lt;p&gt;Without image processing, the modern technological world we live in today would be completely different. Different applications can be found in many different areas, including as medicine, remote sensing, computer vision, and more. Brain tumours occur because of the abnormal growth of brain tissue. Therefore, it is crucial to surgically remove the tumor’s component that has spread throughout the brain. The creation of images of the human body’s internal organs and structures depends on numerous factors, one of which is the use of Magnetic Resonance Imaging (MRI), one of the many medical imaging techniques. Segmenting images is a challenging task in the modern medical field. The tumor’s location and sizes can be detected with more accuracy with the help of a segmentation performed on MRI slices. In this paper, we propose the Adaptive Convex Region Contour (ACRC) algorithm, a novel method for achieving such requirements. Here, we use the Support Vector Machine, often known as SVM, to identify slices and determine whether they are normal or abnormal. Once the SVM results are in, the off-kilter slices will be included into the analysis. Since the human body already has a complex anatomy in 3D. It’s disappointing because MRI slices can only provide images in a plain, 2D plane. Because of its 3D structure, the tumor’s actual shape cannot be detected from a surface image. This means that the transformation from 2D to 3D is important, as it provides necessary data to the surgeons doing the operation. The Rapid Mode Image Matching (RMIM) algorithm should be used when constructing a 3D reconstruction model. Immediately after the 3D model is completed being created, a rough estimate of the tumor’s original volume is generated. The methodological consideration was conducted in the simulated MATLAB software. It was determined from the data that the proposed method is better to the current establishment methodologies in terms of accuracy. &lt;strong&gt;Objective:&lt;/strong&gt; This paper aims to address the need for accurate segmentation of brain tumors in Magnetic Resonance Imaging (MRI) slices. The primary research question revolves around developing a novel segmentation method, the Adaptive Convex Region Contour (ACRC) algorithm, to improve the precision of tumor detection by incorporating a Support Vector Machine (SVM) for identifying abnormal slices.&lt;strong&gt; &lt;/strong&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The proposed approach involves utilizing the SVM to classify MRI slices as either normal or abnormal. The abnormal slices, detected by SVM, are subjected to further analysis. To overcome the limitation of MRI producing 2D images for the inherently 3D human anatomy, a transformation from 2D to 3D is crucial. The Rapid Mode Image Matching (RMIM) algorithm is adopted to construct a 3D reconstruction model of the brain and its tumor. This model allows surgeons to obtain a more accurate understanding of the tumor’s actual 3D shape. &lt;strong&gt;Results: &lt;/strong&gt;The methodology was implemented and evaluated using simulated MATLAB software. The results demonstrate that the proposed ACRC algorithm, combined with SVM-based abnormal slice identification and subsequent 3D reconstruction using RMIM, outperforms existing methodologies in terms of accuracy. The 3D reconstruction provides valuable insights into the tumor’s shape, aiding surgical planning. &lt;strong&gt;Conclusions: &lt;/strong&gt;In conclusion, the research contributes to the field of medical image processing by presenting a comprehensive approach for brain tumor segmentation and 3D reconstruction. The ACRC algorithm, in conjunction with SVM and RMIM, enhances the accuracy of tumor detection and provides critical 3D information for surgical procedures. This advancement holds the potential to improve the efficacy of brain tumor surgeries, underscoring the significance of innovative image processing techniques in modern medical applications.&lt;/p&gt;

Estimation of the subsurface electromagnetic velocity distribution from diffraction hyperbolas by means of a novel automated picking procedure: Theory and application to glaciological ground-penetrating radar data sets

We have developed an auto-picking algorithm that is designed to automatically detect subsurface diffractors within ground-penetrating radar (GPR) data sets, to accurately track the hyperbolic diffractions originating from the identified scatterers, and to recover the subsurface electromagnetic (EM) velocity distribution, among other possible analyses. Our procedure presents several advantages with respect to other commonly applied diffraction tracking techniques because it can be applied with minimal signal preprocessing, thus making it more versatile and adaptable to local conditions; it requires only limited input from the interpreter in the form of a few thresholds for the tracking parameters, thus making the results more objective; and it does not involve pretraining as opposed to machine-learning algorithms, thus removing the need to gather a large and comprehensive image database of all possible subsurface situations, which would not necessarily be limited to only examples of diffractions. The presented algorithm starts by identifying those signals that are likely to belong to diffraction apexes, which are then used as initial seeds by the auto-tracking process. The horizontal search window used during the auto-tracking process is locally adapted through a rough preliminary estimate of the size of each diffraction. In addition, multiple seeds within the same apex can produce several acceptable hyperbolas tracking the same diffraction phase. The algorithm thus selects the best-fitting ones by assessing several signal attributes while also removing redundant hyperbolas and the expected false positives. The algorithm is applied to two glaciological GPR profiles, and it is able to accurately track the vast majority of the recorded diffractions, with very few false positives and negatives. This produces a statistically sound EM velocity distribution, which was used to assess the state of the surveyed alpine glacier.

The genetic and environmental variance of radial increment in Scots pine of south-eastern Baltic provenances in response to weather extremes

Intensification of weather anomalies, particularly those related to temperature in warming winters and moisture availability, have been identified as the major emerging climatic threats to forest ecosystems in the hemiboreal zone. Considering the large-scale nature of the threats, assisted migration and tree breeding appear as the most promising means for mitigating the climatic risks. However, for successful implementation of such means, information on the genetic control over the weather sensitivity of trees is needed. Local genetic adaptations of populations occur to maximize competitiveness and survival, while the differences in phenotypic plasticity, implying varying genotype by environmental interactions, can be utilized for the acquisition of locally targeted reproductive material. To gain initial (rough) estimates of genetic control and phenotypic plasticity of growth responses to weather anomalies, a set of seven native eastern Baltic provenances differing by productivity in five trials in Latvia and northern Germany were studied. Tree-ring widths were measured for 10–15 trees per provenance per trial. Relative growth changes and pointer year values were calculated to link changes in increment with weather anomalies and to estimate heritability on an annual basis by the methods of quantitative genetics. During the analysed period (1987–2017), four to seven trial- and provenance-specific pointer years (common relative growth changes) were estimated, which were mainly triggered by co-occurring anomalies in moisture availability and winter thermal regime. This implied resilience of the studied trees to singular weather anomalies, suggesting their adaptability. Furthermore, the heritability estimates peaked one to two years after the pointer years, implying that growth recovery and hence resilience rather than resistance was genetically controlled. Still, local variability of pointer years and heritability estimates portrayed explicit phenotypic plasticity of responses, implying the potential for breeding to locally improve weather tolerance of growth. Keywords: Pinus sylvestris; local adaptation; phenotypic plasticity; growth recovery; tree-ring width; pointer years

Mountain Streambed Roughness and Flood Extent Estimation from Imagery Using the Segment Anything Model (SAM)

Machine learning models facilitate the search for non-linear relationships when modeling hydrological processes, but they are equally effective for automation at the data preparation stage. The tasks for which automation was analyzed consisted of estimating changes in the roughness coefficient of a mountain streambed and the extent of floods from images. The Segment Anything Model (SAM) developed in 2023 by Meta was used for this purpose. Images from many years from the Wielka Puszcza mountain stream located in the Polish Carpathians were used as the only input data. The model was not additionally trained for the described tasks. The SAM can be run in several modes, but the two most appropriate were used in this study. The first one is available in the form of a web application, while the second one is available in the form of a Jupyter notebook run in the Google Colab environment. Both methods do not require specialized knowledge and can be used by virtually any hydrologist. In the roughness estimation task, the average Intersection over Union (IoU) ranges from 0.55 for grass to 0.82 for shrubs/trees. Ultimately, it was possible to estimate the roughness coefficient of the mountain streambed between 0.027 and 0.059 based solely on image data. In the task of estimation of the flood extent, when selecting appropriate images, one can expect IoU at the level of at least 0.94, which seems to be an excellent result considering that the SAM is a general-purpose segmentation model. It can therefore be concluded that the SAM can be a useful tool for a hydrologist.

Microscopic moisture localisation in unsaturated materials using nuclear magnetic resonance relaxometry

Due to the detrimental effects of moisture in the built environment, there is a continuous interest in non-destructive experimental techniques that quantify and/or localise moisture in materials. Most existing experimental techniques, however, typically focus on macroscopic moisture contents in samples rather than the microscopic distribution of water in the individual pores of building materials. For the latter, a popular method such as X-ray computed tomography is not readily applicable, due to the gap between its spatial resolution limit and the typical pore sizes of building materials. Nuclear magnetic resonance (NMR) relaxometry is capable of measuring water in pores of both the nanometer and micrometer scale and is therefore an interesting possibility. While most NMR research focusses on water-saturated materials or overall moisture contents, this study determines the size distributions of the water islands in unsaturated materials with NMR, and compares results to X-ray computed tomography (XCT) images and pore network model (PNM) simulations. Results on unsaturated materials show that NMR focusses on the biggest water islands (i.e. in capillary filled pores) and disregards the hydrogen nuclei in smaller water islands (i.e. stored in pore corners). NMR relaxometry is therefore only adept at providing very rough estimates of the size of water-filled pores, especially since post-processing of the NMR experiments to obtain these water island size distributions involves a lot of uncertainty.

AirSUM - Structure from Motion supported stock unearthing Method: Erosion modeling in Viennese vineyards

Soil mobilization is particularly high in viticulture. In Austria and especially in Vienna, soil protection measures are frequently implemented without the vintners knowing how high their erosion rates are and where in particular they can introduce additional measures. New, highly accurate and cost-efficient methods for erosion estimation are expected to improve this situation.A relatively fast and low-cost option is the stock unearthing method (SUM), which provides a rough estimation of erosion based on biomarkers, but neglects the inter-row area. The improved stock unearthing method (ISUM) approach uses additional measurement points in this area and therefore delivers more accurate erosion volumes. Additionally, the use of Structure from Motion (SfM) DEMs provides respectable results on small plots in vineyards. This study combines and evaluates the unmanned aerial vehicle (UAV) SfM approach with the SUM. This results in a millimeter scale resolution and can be applied to larger study areas. The combination of SUM and SfM forms the new airSUM approach that provides a more accurate representation of the recent relief, rendering interpolation techniques unnecessary, reproducing visible runoff patterns, and enhancing erosion volume estimations. The use of airSUM enabled the detection of 32.7 ± 17.5 m3 (avg. of ∼ 84.1 ± 45 t ha−1 yr−1) soil erosion on an area of 700 m2 in a period of 8 years. Erosion hotspots could be modeled mainly in the wheel tracks with depths of up to 20.5 cm parallel to the slope and correspond excellently with field observations. This is partly due to the compaction of the surface, but mainly due to the preferential runoff and erosion. The identification of the erosion hot spots, runoff breaches and consequent runoff concentration allows the precise allocation of mitigation funds to reduce overland flow and erosion.

Insight into the dynamics of a long-runout mass movement using single-grain feldspar luminescence in the Pokhara Valley, Nepal

Abstract. Mass movements play an important role in landscape evolution of high mountain areas such as the Himalayas. Yet, establishing numerical age control and reconstructing transport dynamics of past events is challenging. To fill this research gap, we bring luminescence dating to the test in an extremely challenging environment: the Pokhara Valley in Nepal. This is challenging for two reasons: (i) the optically stimulated luminescence (OSL) sensitivity of quartz, typically the mineral of choice for dating sediments younger than 100 ka, is poor, and (ii) highly rapid and turbid conditions during mass movement transport hamper sufficient OSL signal resetting prior to deposition, which eventually results in age overestimation. Here, we first assess the applicability of single-grain feldspar dating of medieval mass movement deposits catastrophically emplaced in the Pokhara Valley. Second, we exploit the poor bleaching mechanisms to get insight into the sediment dynamics of this paleo-mass movement through bleaching proxies. The Pokhara Valley is a unique setting for our case study, considering the availability of an extensive independent radiocarbon dataset as a geochronological benchmark. Single-grain infrared stimulated luminescence (IRSL) signals were measured at 50 ∘C (IRSL-50) and post-infrared infrared stimulated luminescence signals at 150 ∘C (pIRIR-150). Our results show that the IRSL-50 signal is better bleached than the pIRIR-150 signal. A bootstrapped minimum age model (bMAM) is applied to retrieve the youngest subpopulation to estimate the paleodose. However, burial ages calculated with this paleodose overestimate the radiocarbon ages by an average factor of ∼23 (IRSL-50) and ∼72 (pIRIR-150), showing that dating of the Pokhara Formation with a single-grain approach was not successful for most samples. Some samples, however, only slightly overestimate the true emplacement age and thus could be used for a rough age estimation. Large inheritances in combination with the scatter in the single-grain dose distributions show that the sediments have been transported under extremely limited light exposure prior to deposition, which is consistent with the highly turbid nature of the sediment-laden flood and debris flows depositing the Pokhara gravels. To investigate the sediment transport dynamics in more detail, we studied three bleaching proxies: the percentage of grains in saturation 2D0 criteria, the percentage of best-bleached grains (2σ range of bMAM-De) and the overdispersion (OD). None of the three bleaching proxies indicate a spatial relationship with runout distance of the mass movement deposits. We interpret this as evidence for the lack of bleaching during transport, which reflects the catastrophic nature of the event. While not providing reliable burial ages of the Pokhara mass movement deposits, single-grain feldspar dating can potentially be used as an age range finder method. Our approach shows the potential of luminescence techniques to provide insights in sediment transport dynamics of extreme and rare mass movement events in mountainous regions.

On the self-assessment of ocular status and of visual functions by senior students at Russian medical universities (anonymous survey results)

BACKGROUND: Visual impairment is a worldwide problem for the humanity in general, including students.&#x0D; AIM: to conduct a rough estimate of the visual system status in senior medical students at Russian universities taking a training according to General Medicine educational program 31.05.01 (specialty) and having completed the ophthalmology course.&#x0D; MATERIALS AND METHODS: an online anonymous survey of students from five universities in various cities of the country was conducted using an original interactive questionnaire. Answers were received from 549 respondents, predominantly women (n = 425, 77.4%), mean age 22.4 ± 0,06 years.&#x0D; RESULTS: Only 42.7% of students rated their vision as “excellent” or “good.” The most common refractive error according to the survey participants’ self-assessment was myopia, which was reported by 56.1% of them, while 21.9% of respondents reported that they did not know their clinical refraction; 25.5% of students confirmed the presence of astigmatism. 56.9% of respondents use optical correction, glasses being the most popular option. 76.7% of the respondents had their vision testing, and 64.5% visited an ophthalmologist within the last year. Any other concomitant ocular condition (refractive errors excluded) was reported by 4.9% of students (most frequently various types of vitreoretinal pathology, dry eye syndrome, and strabismus were mentioned). 57.9% of respondents believe their vision to have worsened over the past few years, and excessive visual stress was considered the leading cause, reported by 57.2% of the study participants. The respondents rated the importance of having a good vision at 9.25 ± 0.06 points on an arbitrary scale from 1 (minimum) to 10 (maximum) points.&#x0D; CONCLUSIONS: Senior students at Russian medical universities highly appreciate the importance of good vision, while more than half of respondents have visual impairments, use optical correction, and also believe that their vision continues to deteriorate. Insufficient awareness of some students about their vision and gaps in ophthalmological knowledge were revealed.