Reflectance Values Research Articles

The Laser Scanner Technique: A Tool for Determining Shear Strength Parameters of Rock Mass Discontinuities

When evaluating the shear strength of rock mass discontinuities, certain challenges arise due to the difficulty in quantifying the roughness characteristics of surfaces and the strength of asperities. Recent research has focused on enhancing techniques for assessing these characteristics and exploring the application of laser scanning to aid in evaluating discontinuity features. The analysis of reflectivity values (I) obtained through a laser scanner survey presents an efficient method for assessing mechanical characteristics, such as joint compressive strength (JCS). Reflectivity measurements demonstrate correlations with Schmidt hammer rebound values (r). The laser scanner technique would enable the measurement of JCS without the direct application of the Schmidt hammer on rocks in areas where rebound values (r) measurements are unavailable. The use of a laser scanner allows for the acquisition of high-precision geometrical information concerning the 3D roughness and anisotropy of rock surfaces. In this study, an innovative technique was introduced that utilizes laser scanner data from six previous experimental surveys conducted on rock formations in Southern Italy. This technique facilitates the evaluation of roughness profiles, considering potential variations along kinematically admissible sliding directions, allowing for the estimation of the Joint Roughness Coefficient (JRC). This new methodology aids in evaluating the parameters of Barton’s equation to determine the strength characteristics of rock mass discontinuities.

Turning Night into Day: The Creation and Validation of Synthetic Nighttime Visible Imagery Using the Visible Infrared Imaging Radiometer Suite (VIIRS) Day–Night Band (DNB) and Machine Learning

Abstract Meteorological satellite imagery is a critical asset for observing and forecasting weather phenomena. The Joint Polar Satellite System (JPSS) Visible Infrared Imaging Radiometer Suite (VIIRS) Day–Night Band (DNB) sensor collects measurements from moonlight, airglow, and artificial lights. DNB radiances are then manipulated and scaled with a focus on digital display. DNB imagery performance is tied to the lunar cycle, with the best performance during the full moon and the worst with the new moon. We propose using feed-forward neural network models to transform brightness temperatures and wavelength differences in the infrared spectrum to a pseudo-lunar reflectance value based on lunar reflectance values derived from observed DNB radiances. JPSS NOAA-20 and Suomi National Polar-Orbiting Partnership (SNPP) satellite data over the North Pacific Ocean at night for full moon periods from December 2018 to November 2020 were used to design the models. The pseudo-lunar reflectance values are quantitatively compared to DNB lunar reflectance, providing the first-ever lunar reflectance baseline metrics. The resulting imagery product, Machine Learning Nighttime Visible Imagery (ML-NVI), is qualitatively compared to DNB lunar reflectance and infrared imagery across the lunar cycle. The imagery goal is not only to improve upon the consistent performance of DNB imagery products across the lunar cycle, but ultimately to lay the foundation for transitioning the algorithm to geostationary sensors, making global continuous nighttime imagery possible. ML-NVI demonstrates its ability to provide DNB-derived imagery with consistent contrast and representation of clouds across the full lunar cycle for nighttime cloud detection. Significance Statement This study explores the creation and evaluation of a feed-forward neural network to generate synthetic lunar reflectance values and imagery from VIIRS infrared channels. The model creates lunar reflectance values typical of full moon scenes, enabling quantifiable comparisons for nighttime imagery evaluations. Additionally, it creates imagery that highlights low clouds better than its infrared counterparts. Results indicate the ability to create visually consistent nighttime visible imagery across the full lunar cycle for the improved nighttime detection of low clouds. Wavelengths chosen are available on both polar and geostationary satellite sensors to support the utilization of the algorithm on multiple sensor platforms for improved temporal resolution and greater simultaneous geographic coverage over polar orbiters alone.

A global forest burn severity dataset from Landsat imagery (2003–2016)

Abstract. Forest fires, while destructive and dangerous, are important to the functioning and renewal of ecosystems. Over the past 2 decades, large-scale, severe forest fires have become more frequent globally, and the risk is expected to increase as fire weather and drought conditions intensify. To improve quantification of the intensity and extent of forest fire damage, we have developed a 30 m resolution global forest burn severity (GFBS) dataset of the degree of biomass consumed by fires from 2003 to 2016. To develop this dataset, we used the Global Fire Atlas product to determine when and where forest fires occurred during that period and then we overlaid the available Landsat surface reflectance products to obtain pre-fire and post-fire normalized burn ratios (NBRs) for each burned pixel, designating the difference between them as dNBR and the relative difference as RdNBR. We compared the GFBS dataset against the Canada Landsat Burned Severity (CanLaBS) product, showing better agreement than the existing Moderate Resolution Imaging Spectrometer (MODIS)-based global burn severity dataset (MOdis burn SEVerity, MOSEV) in representing the distribution of forest burn severity over Canada. Using the in situ burn severity category data available for the 2013 wildfires in southeastern Australia, we demonstrated that GFBS could provide burn severity estimation with clearer differentiation between the high-severity and moderate-/low-severity classes, while such differentiation among the in situ burn severity classes is not captured in the MOSEV product. Using the CONUS-wide composite burn index (CBI) as a ground truth, we showed that dNBR from GFBS was more strongly correlated with CBI (r=0.63) than dNBR from MOSEV (r=0.28). RdNBR from GFBS also exhibited better agreement with CBI (r=0.56) than RdNBR from MOSEV (r=0.20). On a global scale, while the dNBR and RdNBR spatial patterns extracted by GFBS are similar to those of MOSEV, MOSEV tends to provide higher burn severity levels than GFBS. We attribute this difference to variations in reflectance values and the different spatial resolutions of the two satellites. The GFBS dataset provides a more precise and reliable assessment of burn severity than existing available datasets. These enhancements are crucial for understanding the ecological impacts of forest fires and for informing management and recovery efforts in affected regions worldwide. The GFBS dataset is freely accessible at https://doi.org/10.5281/zenodo.10037629 (He et al., 2023).

Petroleum system assessment of the Beni Suef Basin, Western Desert, Egypt

Within the northwestern Desert of Egypt, the Beni Suef Basin is one of the most significant hydrocarbon basins. After over 50 years of exploration and production, the main challenge today is to locate new areas that are prolific to oil and gas production. The study aims to identify potential drilling locations by integrating geochemical methods, 1D and 2D basin modelling, well log analysis, seismic interpretation, and hydrocarbon migration pathways. Results show that the Lower Kharita shale contain both oil and gas generating kerogen with generating potential that ranges from fair to very good. The source rocks within the Lower Kharita are mature (main oil window) and have a transformation ratio of up to 60% based on 1D basin modeling. The modelled 2D vitrinite reflectance map showed that hydrocarbon generation occurred at depths greater than 10850 ft (3306 m) with vitrinite reflectance values greater than 0.65% in both the northern and southern parts of the Beni Suef Field. Two main reservoirs were studied. The lower Bahariya and upper Kharita reservoirs are composed of well to moderately sorted sandstone. The subsurface structural maps, reservoirs, source, and charge modeling maps have been constructed to show the migration pathways and accumulation areas. There are three accumulation areas identified. The first accumulation area is located in the high structure up-dip section of the major normal fault, and migration direction is from northwest. The second and third accumulation areas are located in the low structure and down-dip from the normal fault, with migration of hydrocarbons from southeast. The latter two areas should be tested by drilling in the future.

Investigation of Structural, Electronic, and Optical Characteristics of a Novel Perovskite Halide, Mg3AsCl3, for Electronic Applications

In the present research article, the structural, electronic, and optical characteristics of a novel perovskite halide, Mg3AsCl3, for a broad range of applications are thoroughly investigated. The characteristics of Mg3AsCl3 perovskite are investigated via the use of the generalized gradient approximation (GGA), Perdew–Burke–Ernzerhof and Heyd–Scuseria–Ernzerhof (HSE06) functionals, which are employed in conjunction with the linear combination of atomic orbital calculator. The structural, electrical, and optical characteristics of the material are investigated using density‐functional theory. In this study of the electronic characteristics, it is found that Mg3AsCl3 exhibits an indirect energy bandgap of 2.49 eV with GGA and 3.54 eV with HSE06. The complex band structure exhibits characteristics that indicate the presence of evanescent waves, which are characterized by a layer separation of 5 Å. The report in this research presents reflectivity values of 0.06328 and 0.02971 with GGA and HSE06 functionals, respectively. The reported values of the extinction coefficient are 3.36487 × 10−5 and 2.07389 × 10−5 calculated with GGA and HSE06 functionals. The value reported for the real dielectric function Re[ε] is 2.79625 with GGA and 2.00658 with HSE06. Overall, in these findings, an overview is given that Mg3AsCl3 holds potential as a candidate for use in a wide range of electronic device applications.

Optimization of Reservoir Water Quality Parameters Retrieval and Treatment Using Remote Sensing and Artificial Neural Networks

Inland water bodies are critical ecosystems that serve several functions including the provision of freshwater, regulation of climate and hydrological flows, and pollution control. Therefore, effective monitoring and management of these water resources is critical for sustainable water supply systems. This study evaluated the possible use of satellite data to estimate water quality parameters (WQPs) in an inland water body. The study also used artificial neural network (ANN) models in addition to the satellite data to determine the optimum coagulant dose for water treatment. The use of earth observations and machine learning methods has not been done extensively in developing countries, specifically, in water quality monitoring and management. The study utilized empirical multivariate regression modelling (EMRM) of the spectral reflectances from satellite data for the retrieval of Chla-a, Turbidity, and total suspended solids (TSS) concentrations in an inland water body. Using MLP-ANN modelling, the extracted spectral reflectance values from the selected sampling points in the reservoir were used as model inputs for the prediction of treated WQPs. A second MLP-ANN model was developed to predict the optimum coagulant dose required for raw water treatment. The R2 values achieved with AN model 1 were 0.81, 0.76, and 0.81 respectively for TSS, turbidity, and Chl-a, and 0.99 for the optimum coagulant dose. The study concluded that spectral reflectance from medium resolution satellite data products can be used to estimate WQPs from inland water bodies. Further, the ANN models demonstrate that extracted water quality data from satellite images can be used to inform ANN models for water quality predictions, and for the optimization of water treatment plant operations.

Near-infrared reflective coatings based on red-brown Ce1-xPrxO2 pigments

Red-brown Ce1-xPrxO2 pigments have high reflectance values over the entire NIR range, which recommend their use as NIR-reflective (cool) pigments. Ce0.99Pr0.01O2 pigment had the highest proportion of red and the lowest proportion of yellow (CIEL*/a*/b* = 60.1/19.7/13.1), corroborated with a total solar reflectance of 54.1 %. The pigments based on Ce1-xPrxO2 showed excellent behavior both in coloring an aqueous acrylic paint applied onto a metal substrate and a transparent glaze applied on a ceramic tile. The tile glazed with the Ce0.99Pr0.01O2 pigment had a significantly higher total solar reflectance (TSR = 45.0 %) than a commercial reference ceramic tile (TSR = 24.2 %), whilst the color of the two was comparable. In the case of metal substrates, the maximum temperature measured on the surface of the acrylic coating based on Ce1-xPrxO2 (54.0 °C) having a total solar reflectance of 51.4 %, was almost 10 °C lower than the temperature measured on the surface of the reference coating (63.7 °C), having a total solar reflectance of 35.7 %. These results demonstrate the extraordinary potential of Ce1-xPrxO2-based pigments to prevent overheating of metal/ceramic surfaces exposed to NIR radiation including, but not limited to, roofing applications.

A Power Combiner–Splitter Based on a Rat-Race Coupler for an IQ Mixer in Synthetic Aperture Radar Applications

Synthetic aperture radar (SAR) is a powerful tool in remote sensing applications that can produce high-resolution images and operate in any weather condition. It is composed of many RF components, such as the IQ mixer, which mixes the base chirp signal (IF) with the carrier signal (LO) and increases the bandwidth of the transmitted signal to twice the maximum frequency of the base chirp signal, reducing the workload of Programmable Field Gate Arrays (FPGA) and increasing the resolution of the SAR system. This research proposes a power combiner–splitter design that will be used as a supporting component to construct the IQ mixer in SAR applications based on a rat-race coupler. The measurement results show that the coupler has good S-parameter values. S11, S22, and S33 have a low reflection value below −17 dB, S13 has a high isolation value below −22 dB, and S21 and S31 have a low attenuation value below −4 dB with amplitude unbalance below 0.1 dB and phase unbalance below 1∘. The 150 MHz requirement bandwidth for the RF signal is also achieved.

Assessment of apple soluble sugar content by hyperspectral vegetation indexes

Soluble sugar content in apple fruit is a crucial internal quality factor. Rapid and accurate estimation of soluble sugar content in apple fruit is helpful to predicting maturity. However, few studies have used an approach of hyperspectral vegetation indexes for monitoring apple soluble sugar content from ground-based handheld hyperspectral data. This study systematically analyzed the performance of hyperspectral vegetation indexes of apple in estimating the soluble sugar content. The visible and near infrared spectral of apple samples were measured by using a hyperspectral equipment, with the wavelength of 350–2500 nm. Eleven early-ripening apple varieties were collected from orchards located in five provinces of China, and the sugar content of each apple fruit sample was measured using laboratory methods. Two-band combination method was used to identify the effective spectral index. Results showed that the newly developed two-band ratio spectral index R833/R834 (Rλ is the reflectance value at wavelength λ) was recommended as the optimal index for monitoring early-ripening apple soluble sugar content, generated the coefficients of determination, root mean square error (RMSE) and residual prediction deviation (RPD) values between the measured and predicted values of 0.73%, 0.72%, and 1.38%, respectively. Result indicated that the newly developed two-band index R833/R834 can be used to nondestructively determine apple fruit soluble sugar content. The findings can provide insight into the relationship between the optical properties of apple fruit at different wavelengths and soluble sugar content.

Zvěstovite-(Fe), Ag6(Ag4Fe2)As4S13, a new member of the tetrahedrite group from the Ulatayskoe Ag–Cu–Co occurrence, eastern Siberia, Russia

Abstract. The new mineral zvěstovite-(Fe), ideally Ag6(Ag4Fe2)As4S13, has been found in the small abandoned Ulatayskoe Ag–Cu–Co occurrence, Ovyurskiy District, Tuva Republic, eastern Siberia, Russia. It occurs as anhedral grains, up to 1 × 0.4 mm in size but usually much smaller, closely intergrown with native silver, in Mg-bearing siderite–quartz gangue. Other associated minerals include acanthite, cobaltite, As-rich members of the tetrahedrite group (kenoargentotennantite-(Fe), tennantite-(Zn), zvěstovite-(Zn)), gersdorffite, jalpaite, krutovite, löllingite, pearceite, safflorite, skutterudite, Br-bearing chlorargyrite, malachite, and muscovite. Zvěstovite-(Fe) is iron black and opaque and has a black streak and metallic lustre. It is brittle and has a conchoidal fracture. No cleavage or parting is observed. The Vickers micro-indentation hardness (Vickers hardness number, VHN; 25 g load) is 169 kg mm−2 (range of 149–187 kg mm−2, n=4), corresponding to a Mohs hardness of 3–3.5. The calculated density is 4.979 g cm−3. In reflected light, zvěstovite-(Fe) is light grey with a greenish tint and isotropic. Internal reflections are ubiquitous and deep red in colour. The reflectance values for wavelengths recommended by the Commission on Ore Mineralogy of the International Mineralogical Association are (R, %): 32.5 (470 nm), 31.1 (546 nm), 30.1 (589 nm), and 28.8 (650 nm). The chemical composition (wt %, electron microprobe data, mean of eight spot analyses) is as follows: Cu 1.81, Ag 56.02, Fe 4.60, Zn 0.01, As 13.85, Sb 2.63, S 21.50, total 100.42. The empirical formula, calculated on the basis of 16 atoms per formula unit, is Ag9.93Cu0.54Fe1.58As3.54Sb0.41S12.83. Zvěstovite-(Fe) is cubic and has a space group of I4‾3m, with a=10.8601(3), V=1280.86(11) Å3, and Z=2. The strongest lines of the X-ray powder diffraction pattern (d, Å (I, %) hkl) are 7.68 (11) 110, 3.136 (100) 222, 2.717 (12) 400, 1.984 (8) 521, 1.921 (23) 440, and 1.638 (11) 622. The crystal structure of zvěstovite-(Fe) was refined to R1=0.0551 for 400 unique reflections with Fo>4σ (Fo). The possible ordering of the split M(2) sites is discussed. The new mineral is the Fe isotype of zvěstovite-(Zn). Both these minerals form the zvěstovite series within the tetrahedrite group.

Conformal Antireflective Multilayers for High‐Numerical‐Aperture Deep‐Ultraviolet Lenses

AbstractPrecise surface reflectance control at specific deep‐ultraviolet (DUV) wavelengths across wide angles is crucial for semiconductor inspection and lithography tools. The inherent challenges in designing DUV antireflective multilayers stem from limited transparent materials and the resultant fabrication complexity owing to numerous interfaces. Here, wide‐angle antireflective multilayers finely tuned to 248 nm designed using an active learning scheme is presented. The active learning scheme employing factorization machines (FM) identifies the optimal configurations for binary‐material‐based multilayers (AlF3/LaF3, AlF3/MgF2, and AlF3/Al2O3) with varying index contrasts, achieving minimal figure‐of‐merit (i.e., average angular reflectance) values at predetermined total thicknesses. High‐index‐contrast AlF3/Al2O3 multilayers are fabricated via atomic layer deposition, thus enabling the conformal coating of high‐numerical‐aperture (NA) lenses with atomic precision. An optimized AlF3/Al2O3 tri‐layer with a total thickness of 180 nm results in an average (0°–45°) reflectance of 0.4% on a CaF2 planar substrate and 0.6% on a CaF2 convex lens (NA = 0.47), similar to the performance of an ideal single‐layer coating requiring a practically unavailable refractive index. Phasor analysis, which considers only first‐order reflections between adjacent layers, supports the benefits of high‐index‐contrast binary materials and the use of the FM‐based active learning scheme in antireflective multilayer design.

Synthesizing Jakarta City’s Local Wisdom: Reimagining Sidewalks with an Emotional Design and Sustainability Approach

The research objective was to design sidewalks as walking facilities and public spaces, considering comfort, safety, cleanliness, and functionality for Jakarta’s residents. The city of Jakarta, as a megapolitan center, hosted various societal activities. The high mobility of Jakarta’s population led to busy sidewalk activities, especially walking, regulated by the Director General of Highways’ guidelines. Walking could help reduce pollution, with Jakarta having the worst pollution in 2023. The research problem, based on 360-degree Google Maps images of sidewalks, was that sidewalks serve not only as footpaths but also as public gathering spaces. The qualitative research method examined digital data on sidewalk use in Jakarta (west, central, south, east, and north). The design process incorporated emotional design (visceral, behavioral, reflective) and three dimensions of sustainability (The Overlapping Spheres Model of Triple Bottom Line/TBL). The result is a 3D sidewalk model using emotional and sustainability design approaches. Synthesis of emotional design interprets visceral (sensory), behavioral (habits), and reflective (values) levels. Synthesis of sustainability includes environmental, social, and economic dimensions, focusing on air quality, water management, and energy efficiency. Social and economic aspects aim to meet Jakarta residents’ basic needs. Ultimately, these recommendations aim to make cities and neighborhoods inclusive, safe, resilient, and sustainable. However, the research is limited to design recommendations without direct implementation. Further research or implementation is needed to address these challenges and ensure Jakarta residents’ future well-being.

Petrology and association of rare earth elements in magmatically altered high-ash coal of Indian origin

The extraction of valuables from waste has gained momentum. Thermal influence alters both the organic and inorganic components of coal. Insufficient knowledge on the association of rare earth elements (REEs) with the parent matrix of thermally altered high-ash coals (63% ash) limits the potential for such coals being utilized for isolation of valuables. In this study, we analyzed the distribution and occurrence modes of REEs within a magmatically altered high-ash coal via nine-step sequential extraction, combining Tessier and BCR methods. The total concentration of REEs in the coal sample, on whole coal basis, was found to be 820 ppm, which is significantly higher than the world average. Major mineral oxides were deduced to be those of Si, Fe, Al, Ca, Mg, and Ti. Sequential extraction confirmed that about 66% of HREE and 25% of LREE were included in the residual fraction. LREEs were concluded to be primarily in ionic form, whereas HREEs were speculated to be associated with the TiO2 phase. XRD analyses showed that thermal alteration affected the dolomite phase specifically, which selectively got removed where carbonate-bound elements were assessed. Petrographic analysis supported the magmatic influence and demonstrated the presence of mosaic structures and pores containing unfused vitrinite, with a reflectance value of 3.6. To summarize, the present study pertaining to delineation of association of valuables in high-ash heat-altered coals from an Eastern coalfield in India can potentially open up new avenues for utilizing such coals, which are otherwise considered waste.

Geotechnologie stosowane w konstrukcjach antropomorficznych: Wykorzystanie georadaru do wykrywania problemów strukturalnych, przyczyn i skutków - studium przypadku w Coimbrze w Portugalii

One of the recurrent problems in civil construction concerns the wear and deterioration of structures due to their use over time. There should be a plan for monitoring the structures to assess and quantify anomalies, which will allow the minimization and rehabilitation measures to be carried out in advance. This study aimed to use geotechnologies, specifically the Ground Probing Radar (GPR), to identify and quantify the damage caused using a swimming pool inserted in a structure built on a residential property. The methodology comprised the use of georradar Sensors & Software PulseEKKO GPR for data acquisition. The data were processed in the software EKKO Project considering the following parameters: 1- Grain/Filter: Dewow + SEC2 Gain (Attenuation:10.00 Start Gain:4.00 Maximum Gain: 950). Seven acquisition profiles were performed: 3 on the East side, 2 on the South side, and 2 on the West side of the pool, with a spacing between 0.8 m. From the visualization of the processed radargrams, and the slices elaborated for each profile with a color palette corresponding to the obtained reflectance values, it was possible to identify the underlying structures of the pavement of the edge of the pool such as beams, beam frames, slope, interior space of the support structure and, most importantly, the degree of subsoil materials alteration, depth, and dispersion of water infiltrations. On the East side, the pool is inserted into the rock formation; it is possible to identify up to 1 m depth of the water infiltration and dispersion. To the West and South, the pool is supported by a built-up structure; underneath there is a hall and the engine room. In these places, the infiltration and dispersion of water were identified until approximately 0.7 m depth, as well as the existing structures and their condition. The 0.7 m corresponds to the thickness of the existing slab and beams. Based on these results, an intervention plan was prepared for the rehabilitation of the deterioration of the materials and the minimization of water percolation through the waterproofing of the pool's surrounding areas.

Real-time Neural Appearance Models

We present a complete system for real-time rendering of scenes with complex appearance previously reserved for offline use. This is achieved with a combination of algorithmic and system level innovations. Our appearance model utilizes learned hierarchical textures that are interpreted using neural decoders, which produce reflectance values and importance-sampled directions. To best utilize the modeling capacity of the decoders, we equip the decoders with two graphics priors. The first prior—transformation of directions into learned shading frames—facilitates accurate reconstruction of mesoscale effects. The second prior—a microfacet sampling distribution—allows the neural decoder to perform importance sampling efficiently. The resulting appearance model supports anisotropic sampling and level-of-detail rendering, and allows baking deeply layered material graphs into a compact unified neural representation. By exposing hardware accelerated tensor operations to ray tracing shaders, we show that it is possible to inline and execute the neural decoders efficiently inside a real-time path tracer. We analyze scalability with increasing number of neural materials and propose to improve performance using code optimized for coherent and divergent execution. Our neural material shaders can be over an order of magnitude faster than non-neural layered materials. This opens up the door for using film-quality visuals in real-time applications such as games and live previews.

Energy optimization for Façade retrofit design of residential buildings in hot climates using advanced materials

Global warming has adversely affected the building sector in many countries. Energy retrofit strategies for existing buildings have been developed to combat this issue, including advanced facade system coatings. This study examines how advanced coatings such as PCMs, thermochromics, and cool materials can be effectively used to enhance the thermal behavior and energy performance of existing facades in hot climates. It aims to suggest the optimal combinations of such materials for the façade retrofit design of a typical low-rise residential building in hot climates. Using optimization, Design Builder software is utilized to assess the thermal behavior and energy performance of a combination of advanced materials used. The results revealed that the arrangement of exterior wall layers, thickness and placement of thermal insulation, and the material used in the façade outer layer have a significant effect on the annual energy consumption. Applying coatings with high reflective values as an outer layer of facades can reduce monthly surface temperatures by 2.62 °C in summer and annual cooling loads by 13.78 %. Using PCM coating as an inner layer of the façade improves indoor temperatures by 1.83 °C during different seasons and decreases annual cooling demands by 13.23 %. Finally, the optimal combination of such materials for the energy retrofit design of a typical residential building with three conventional façades has been defined.

Insights on the regional thermal evolution from semianthracite petrology of the Fengfeng coalfield, China

Igneous intrusions induce alterations in coal and minerals. Alteration degree depends upon the in-situ coal rank and maceral composition, the intrusion temperature, heat source proximity, and intrusion size. In the Permo-Carboniferous Fengfeng coalfield, coal rank increases over some 50 km distance south to north from high volatile bituminous coal to anthracite. The coal seams were commonly intruded, and the regional elevation of rank was augmented by Jurassic-Cretaceous igneous intrusions, not just burial coalification. The petrographic examination of a semianthracite from the Dashucun mine in the north of the Fengfeng coalfield shows development of coke microstructure and increased reflectance approaching the dike in the No. 2 Seam. Based on 11 samples at 50-cm horizontal intervals, random vitrinite reflectance value (Rr) declines from 5.41% at the contact to the background value of 2.05% at 5-m distance from the contact. Towards the dike, vitrinite anisotropy increases and the microtexture shows development of circular, coarse mosaic, and ribbon anisotropic coke textures and devolatilization vacuoles. Natural coke textures respond to an estimated temperature > 570 °C at the intrusion/coal contact. However, the occurrence of coke structures within a semianthracite reveals a local and regional thermal evolution. Coke textures suggest that coal rank was high volatile A bituminous coal at the time of intrusion. This has implications for burial history, heating, and subsidence rates. Assuming a paleogeothermal gradient of 40 °C/km, high volatile A bituminous coal (1% Rr) would have been buried to 3 km at the time of the Jurassic intrusion. The intrusion metamorphosed high volatile bituminous coal to natural coke and subsequent larger-scale regional metamorphism then metamorphosed the coal to semianthracite.

Pressure effect on the structural, electronic, elastic, thermodynamic and optical properties of LiZnZ (Z = N, P, and As) Li-based half-Heusler

ABSTRACT Using first-principle calculations based on the density functional theory, we investigated the pressure effect on the structural, electrical, elastic, thermodynamic,electronic and optical properties of Li-based half-Heusler compounds LiZnZ (Z = N, P, and As). We found that the most stable structural phase is the α-phase at 0 GPa for all studied compounds. The obtained lattice parameters at 0 GPa align with existing experimental and theoretical findings for all compounds. The negative values of cohesive and formation energies of LiZnZ indicate that the studied compounds are chemically stable. Band structure calculations confirm the semiconductor behavior of all studied compounds. The calculated elastic and thermodynamic properties show that these compounds are mechanically and thermodynamically stable. The reflectivity values, which are approximately 39%, 54%, and 57% for LiZnN, LiZnP, and LiZnAs, respectively, suggest that the semiconductors LiZnZ are well-suited for optoelectronic applications.

Prospective of Management and Supervision in Latin American Education

Purpose: Reflect on the approach to topics such as educational supervision, educational management, the importance of these aspects and the guidelines that currently govern this type of processes, likewise the importance lies in demonstrating the importance of this process in current education ensuring that children and young people in all countries have quality education. Methodology: The methodology of the article is based on the reflective qualitative method. Sánchez Silva (2005) defines it as follows: “The reflective tradition privileges values, norms and creates patterns of behavior that favor an analytical and critical attitude aimed at reviewing and evaluating ideas, assumptions, theories and conventional methods” (p.116). Furthermore, according to Edmund Husserl (cited by Menéndez, 2012), reflection is fundamental in phenomenology, being one of its main tasks to analyze experiences in an organized way. Results and Conclusions: Raise awareness about the importance of assigning suitable people to these positions, ensuring that they fulfill the responsibilities they acquire and also training teachers and directors in everything that educational supervision brings with it so that they can take decisive and participatory roles. since all types of opinions must provide significant elements. Furthermore, within the general guidelines in current education, it must be taken into account that this is an instrument of public policy that is based on the general law of the system, generating in turn a motivation and a direct relationship of the topics discussed since the The main element is the teacher, thus generating the necessary changes to provide students with quality education. Implications: This research provides implications for educational and government policies to continue strengthening Educational Supervision and Management policies in Latin America. Originality/value: This research offers novelty by reflecting on how public policies impact educational supervision and management in Latin American institutions.

Mapping the Dynamics of Mangrove Density in Alas Purwo National Park using the ARVI Index

This study aims to compare the sensor/Top-of-Atmospheric (TOA) reflectance correction method and surface reflectance correction in the ARVI (Atmospherically Resistant Vegetation Index) vegetation index transformation application. The resulting comparison of the two has a correlation that is not much different, sensor reflectance correction (R = 0.9723) and surface reflectance correction (R = 0.9781) are both able to represent mangrove forest canopy density well. The model accuracy resulting from the surface reflectance correction RMSE 1.408 and MAPE 0.48%, is higher than that of the sensor correction (TOA) which has an RMSE value of 2.184 and MAPE 1.34%. For advanced remote sensing analysis, it is better to perform radiometric correction of surface reflectance because the reflectance value used for analysis is the true reflectance value. The condition of mangroves in Grajagan Bay in Alas Purwo National Park is very well preserved, this is shown by the mangrove canopy density >50% increased by 49.11 Ha in a period of 7 years from 2016 to 2023.