Miracle-dz/UniFAR-FTUs huggingface dataset:
Determining Peak Altitude on Maps, Books and Cartographic Materials: Multidisciplinary Implications

Mountain peaks and their altitude have been of interest to researchers across disciplines. Measurement methods and techniques have changed and developed over the years, leading to more accurate measurements and, consequently, more accurate determination of peak altitudes. This research transpired due to the frequency of misstatements found in existing sources including books, maps, guidebooks and the Internet. Such inaccuracies have the potential to create controversy, especially among peak-baggers in pursuit of climbing the highest summits. The Polish Sudetes Mountains were selected for this study; 24 summits in the 14 mesoregions were measured. Measurements were obtained employing the global navigation satellite system (GNSS) and light detection and ranging (LiDAR), both modern and highly precise techniques. Moreover, to determine the accuracy of measurements, several of the summits were measured using a mobile phone as an additional method. We compare GNSS vs. LiDAR and verify the level of confidence of peak heights obtained by automatic methods from LiDAR data alone. The GNSS receiver results showed a discrepancy of approximately 10 m compared with other information sources examined. Findings indicate that the heights of peaks presented in cartographic materials are inaccurate, especially in lesser-known mountain ranges. Furthermore, among all the mountain ranges examined, the results demonstrated that five of the summits were no longer classed as the highest, potentially impacting tourist perceptions and subsequent visitation. Overall, due to the topographical relief characteristics and varying vegetation cover of mountains, we argue that the re-measuring procedure should comprise two steps: (1) develop high-resolution digital elevation models (DEMs) based on LiDAR; (2) assumed heights should be measured using precise GNSS receivers. Unfortunately, due to the time constraints and the prohibitive costs of GNSS, LiDAR continues to be the most common source of new altitude data.
Application of Combining YOLO Models and 3D GPR Images in Road Detection and Maintenance

Improving the detection efficiency and maintenance benefits is one of the greatest challenges in road testing and maintenance. To address this problem, this paper presents a method for combining the you only look once (YOLO) series with 3D ground-penetrating radar (GPR) images to recognize the internal defects in asphalt pavement and compares the effectiveness of traditional detection and GPR detection by evaluating the maintenance benefits. First, traditional detection is conducted to survey and summarize the surface conditions of tested roads, which are missing the internal information. Therefore, GPR detection is implemented to acquire the images of concealed defects. Then, the YOLOv5 model with the most even performance of the six selected models is applied to achieve the rapid identification of road defects. Finally, the benefits evaluation of maintenance programs based on these two detection methods is conducted from economic and environmental perspectives. The results demonstrate that the economic scores are improved and the maintenance cost is reduced by $49,398/km based on GPR detection; the energy consumption and carbon emissions are reduced by 792,106 MJ/km (16.94%) and 56,289 kg/km (16.91%), respectively, all of which indicates the effectiveness of 3D GPR in pavement detection and maintenance.
Mission-Long Recalibrated Science Quality Suomi NPP VIIRS Radiometric Dataset Using Advanced Algorithms for Time Series Studies

Suomi NPP has been successfully operating since its launch on 28 October 2011. As one of the major payloads, along with microwave and infrared sounders (Advanced Technology Microwave Sounder (ATMS), Cross-track Infrared Sounder (CrIS)), and ozone mapping/profiling (OMPS) instruments, the Visible Infrared Imaging Radiometer Suite (VIIRS) has performed for well beyond its mission design life. Its data have been used for a variety of applications for nearly 30 environmental data products, including global imagery twice daily with 375 and 750 m resolutions, clouds, aerosol, cryosphere, ocean color and sea-surface temperature, a number of land products (vegetation, land-cover, fire and others), and geophysical and social economic studies with nightlights. During the early days of VIIRS operational calibration and data production, there were inconsistencies in both algorithms and calibration inputs, for several reasons. While these inconsistencies have less impact on nowcasting and near real-time applications, they introduce challenges for time series analysis due to calibration artifacts. To address this issue, we developed a comprehensive algorithm, and recalibrated and reprocessed the Suomi NPP VIIRS radiometric data that have been produced since the launch. In the recalibration, we resolved inconsistencies in the processing algorithms, terrain correction, straylight correction, and anomalies in the thermal bands. To improve the stability of the reflective solar bands, we developed a Kalman filtering model to incorporate onboard solar, lunar, desert site, inter-satellite calibration, and a deep convective cloud calibration methodology. We further developed and implemented the Solar Diffuser Surface Roughness Rayleigh Scattering model to account for the sensor responsivity degradation in the near infrared bands. The recalibrated dataset was validated using vicarious sites and alternative methods, and compared with independent processing from other organizations. The recalibrated radiometric dataset (namely, the level 1b or sensor data records) also incorporates a bias correction for the reflective solar bands, which not only addresses known calibration biases, but also allows alternative calibrations to be applied if so desired. The recalibrated data have been proven to be of high quality, with much improved stability (better than 0.3%) and accuracy (by up to 2%). The recalibrated radiance data are now available from 2012 to 2020 for users and will eventually be archived on the NOAA CLASS database.
Assimilation of Multi-Source Precipitation Data over Southeast China Using a Nonparametric Framework

The accuracy of the rain distribution could be enhanced by assimilating the remotely sensed and gauge-based precipitation data. In this study, a new nonparametric general regression (NGR) framework was proposed to assimilate satelliteand gauge-based rainfall data over southeast China (SEC). The assimilated rainfall data in Meiyu and Typhoon seasons, in different months, as well as during rainfall events with various rainfall intensities were evaluated to assess the performance of this proposed framework. In rainy season (Meiyu and Typhoon seasons), the proposed method obtained the estimates with smaller total absolute deviations than those of the other satellite products (i.e., 3B42RT and 3B42V7). In general, the NGR framework outperformed the original satellites generally on root-mean-square error (RMSE) and mean absolute error (MAE), especially on NashSutcliffe coefficient of efficiency (NSE). At monthly scale, the performance of assimilated data by NGR was better than those of satellite-based products in most months, by exhibiting larger correlation coefficients (CC) in 6 months, smaller RMSE and MAE in at least 9 months and larger NSE in 9 months, respectively. Moreover, the estimates from NGR have been proven to perform better than the two satellite-based products with respect to the simulation of the gauge observations under different rainfall scenarios (i.e., light rain, moderate rain and heavy rain).
Automated Mapping for Long-Term Analysis of Shifting Cultivation in Northeast India

Assessment of the spatio-temporal dynamics of shifting cultivation is important to understand the opportunities for land restoration. The past studies on shifting cultivation mapping of North-East (NE) India lack systematic assessment techniques. We have developed a decision tree-based multi-step threshold (DTMT) method for consistent and long-term mapping of shifting cultivation using Landsat data from 1975 to 2018. Widely used vegetation indices such as normalized difference vegetation index (NDVI), Normalized Burn Ratio (NBR) and its relative difference NBR (RdNBR) were integrated with the suitable thresholds in the classification, which yielded overall accuracy above 85%. A significant decrease in total shifting cultivation area was observed with an overall reduction of 75% from 1975–1976 to 2017–2018. The methodology presented in this study is reproducible with minimal inputs and can be useful to map similar changes by optimizing the index threshold values to accommodate relative differences for other landscapes. Furthermore, the crop-suitability maps generated by incorporating climate and soil factors prioritizes suitable land use of shifting cultivation plots. The Google Earth Engine (GEE) platform was employed for automatic mapping of the shifting cultivation areas at desired time intervals for facilitating seamless dissemination of the map products. Besides the novel DTMT method, the shifting cultivation and crop-suitability maps generated in this study, can aid in sustainable land management.
Development of a Parcel-Level Land Boundary Extraction Algorithm for Aerial Imagery of Regularly Arranged Agricultural Areas

The boundary extraction of an object from remote sensing imagery has been an important issue in the field of research. The automation of farmland boundary extraction is particularly in demand for rapid updates of the digital farm maps in Korea. This study aimed to develop a boundary extraction algorithm by systematically reconstructing a series of computational and mathematical methods, including the Suzuki85 algorithm, Canny edge detection, and Hough transform. Since most irregular farmlands in Korea have been consolidated into large rectangular arrangements for agricultural productivity, the boundary between two adjacent land parcels was assumed to be a straight line. The developed algorithm was applied over six different study sites to evaluate its performance at the boundary level and sectional area level. The correctness, completeness, and quality of the extracted boundaries were approximately 80.7%, 79.7%, and 67.0%, at the boundary level, and 89.7%, 90.0%, and 81.6%, at the area-based level, respectively. These performances are comparable with the results of previous studies on similar subjects; thus, this algorithm can be used for land parcel boundary extraction. The developed algorithm tended to subdivide land parcels for distinctive features, such as greenhouse structures or isolated irregular land parcels within the land blocks. The developed algorithm is currently applicable only to regularly arranged land parcels, and further study coupled with a decision tree or artificial intelligence may allow for boundary extraction from irregularly shaped land parcels.
The role of adenosine triphosphate in human granulosa-luteal cells

Adenosine triphosphate (ATP) is released from cells such as platelets and co-released with neurotransmitter granules from autonomic nerves by exocytosis. Extracellular ATP binds to a G protein-coupled P2 purinoceptor that activates phospholipase C and phosphatidylinositol hydrolysis, generating diacylglycerol and inositol 1,4,5-trisphosphate, which stimulate protein kinase C (PKC) and cytosolic calcium mobilization, respectively. Autonomic nerves have been shown to innervate the ovary and may be involved in regulating steroidogenesis. It is tempting to speculate that the co-released ATP from autonomic nerve endings in the ovary may play a role in regulating ovarian function. A series of experiments has been performed in this study to examine (1) the expression and regulation of P2U purinergic receptor (P2UR) in human granulosa-luteal cells (hGLCs), (2) the role of PKC in ATP-induced calcium oscillations, (3) the action and mechanism of antigonadotropic effect of ATP on hGLCs, (4) the functional role of extracellular ATP in the ovary, and (5) the effect of ATP on the activation of the mitogen-activated protein kinase (MAPK) signaling pathway and its physiological role in hGLCs. This study demonstrated for the first time the expression of P2UR mRNA in hGLCs, and the regulation of P2UR mRNA by hCG, cAMP and forskolin. The P2UR was functional in hGLCs, since activation of the P2UR by ATP or UTP resulted in rapid and transient mobilization of cytosolic calcium at the single cell level. It appears that PKC may have dual actions by providing positive forward actions as well as negative feedback in controlling various signaling steps. As shown in this
Spent-fuel special-studies progress report: probable mechanisms for oxidation and dissolution of single-crystal UO/sub 2/ surfaces

Due to the complexity of the structural, microstructural and compositional characteristics of spent fuel, basic leaching and dissolution mechanisms were studied with UO/sub 2/ matrix material, specifically with single-crystal UO/sub 2/, to isolate individual contributory factors. The effects of oxidation and oxidation-dissolution were investigated in different oxidation conditions, such as in air, oxygenated solutions and deionized water containing H/sub 2/O/sub 2/. In addition, the effects of temperature on dissolution of UO/sub 2/ were studied in autoclaves at 75 and 150/sup 0/C. Also, oxidation and dissolution measurements were investigated via electrochemical methods to determine if those techniques could be applied to the characterization of leaching and dissolution of spent fuel in a hot cell. Finally, the effects of radiation were explored since the radiolysis of water may create a localized oxidizing condition at or near the spent fuel-solution interface, even in neutral or reducing conditions as commonly found in deep geological environments. The oxidation and oxidation-dissolution mechanisms for UO/sub 2/ are proposed as follows: The UO/sub 2/ surface is first oxidized in solution to form a UO/sub 2+x/ surface layer several angstroms thick. This oxidized surface has a high dissolution rate since the UO/sub 2+x/ reacts with the dissolved O/sub 2/,more » or H/sub 2/O/sub 2/, to form uranyl complex ions in a U(VI) state. As the uranyl ions exceed the solubility limits in solution, they become hydrolyzed to form solid deposits and suspended particles of UO/sub 3/ hydrates. The thickness and porosity of the deposited UO/sub 3/ hydrate surface-film is dependent on temperature, pH and deposition time. A long-term dissolution rate is then determined by the nature of the surface film, such as porosity, solubility and mechanical properties. « less
Effect of Vacancy on Electronic Properties of MX2 (M = Mo, W and X = S, Se) Monolayers

Two-dimensional transition metal dichalcogenides (TMDs), an emerging class of layered materials with promising optoelectronic properties, have become one of the most intensely studied nanomaterials for nanoelectronic and photonics applications. In this work, we studied the electronic properties of defective monolayer TMDs such as WS2, WSe2, and MoS2 by using first principle calculations based on density functional theory. We focused primarily on the effects of chalcogen vacancies on the electronic characteristics. We calculated their band structure, the density of states, effective mass, and mobility. Our first-principle calculations reveal that chalcogen vacancies induce non-zero density of states within the band gap. Hence, we found a significant decrease in the band gap when we introduced single chalcogen vacancies. For instance, the band gap of WS2 reduced from 1.8 eV to 0.79 eV. These defects modify the shape of the conduction and valence band and hence the notable increase in effective mass resulting in a decrease in mobility. The findings of this study provide an insight of defect engineering for modifying electronic properties, enhancing device performance, and enabling unique functionalities.
Virtual Machine Monitor-based Hiding Method for Access to Debug Registers

To secure a guest operating system running on a virtual machine (VM), a monitoring method using hardware breakpoints by a virtual machine monitor is required. However, debug registers are visible to guest operating systems; thus, malicious programs on a guest operating system can detect or disable the monitoring method. This paper presents a method to hide access to debug registers from programs running on a VM. Our proposed method detects programs’ access to debug registers and disguises the access as having succeeded. The register’s actual value is not visible or modifiable to programs, so the monitoring method is hidden. This paper presents the basic design and evaluation results of our method.
Study on Different Strategies to Solve the Problem of Addition and Subtraction: FMRI Combined with ACT-R

Addition calculation and subtraction calculation are the most basic and common arithmetic operations. Different computational equations use different strategies, and the range and intensity of brain regions are also different. The research on cognitive processing strategies of addition calculation and subtraction calculation is helpful to explore the brain activity regularity of different cognitive processing strategies of human brain, provide reference for the further development of artificial intelligence and computer intelligence, and put forward cognitive model to realize the research on it when it is difficult to obtain a certain cognitive task data.
Modeling of an AC Plasma Torch—Part I: Electrical Parameters and Flow Temperature

A numerical study of airflow in a single-phase ac plasma torch is presented. The values of electrical current being considered are up to 10-A rms, and the ac frequency is 50 Hz. The electric and gas-dynamic parameters of the plasma torch are efficiently simulated using the model based on the Navier–Stokes equations for compressible medium and the reduced Maxwell equations. The difference in the behavior of parameters in the channel and jet is demonstrated and discussed. The effect of decreasing the observed maximum value of the flow temperature with decreasing the flow rate is shown. An explanation of this effect and an analysis of the gas-dynamic patterns of cold flow and flow with the ac discharge are presented in the following article of the series.
How to Retain Players through Dynamic Quality Adjustment in Video Games

Subscription model is one of the two commonly-used business models in the video game industry. It has been applied by some famous games such as the World of Warcraft, and EVE. Thus, how to retain players and make them willing to renew their contracts is a critical and long-running quest for game operators. Relying on characteristics of video games, we present a stylized dynamic programming model to help video game operators decide what quality level they should provide in different periods to retain players. With the assumption that both players’ memory of past service experience and network externalities can affect the resubscription decision-making process of players under the condition of profit maximization, we use a Q-learning algorithm to simulate the decision-making process off-line. We show that the game quality levels will converge to steady state no matter what the initial game quality is. However, the convergence path would be longer when the initial game quality is low. Then, we demonstrate that the trend of perceived quality indicates a "high-low-high" pattern when players overestimate initial game quality. The results also reveal that if network externality intensity is high, it is negative for game operators to lift game quality.
Ultra-Sonication Assisted Synthesis of 2D SnS2 Nanoflakes for Room-Temperature No Gas Detection

Tin disulfide belongs to the class of layered materials and has drawn attention because of its unique surface properties. In this report, synthetically prepared bulk precursor has been used to fabricate 2D layered hexagonal SnS2 flakes by using liquid exfoliation technique. It was evident from structural and morphological characterization that the exfoliation produces aggregated flakes of SnS2. The prepared 2D SnS2 based sensor has shown a response toward NO gas at room temperature, whereas the bulk SnS2 based device doesn’t respond to any analyte. The device employing exfoliated SnS2 flakes as sensing layer responds to NO in the concentration range of 500 ppb (20.61%) to 2.75 ppm (163.32%). Moreover, the sensor offers highly stable and repeatable performance with little drift. This study implements an efficient route for nanoflakes synthesis from bulk layered SnS2 by the liquid exfoliation and the result of sensing test can stimulate in the production of high performance NO gas sensors.
Comparative Analysis of Generative Adversarial Networks and their Variants

Generative Adversarial Networks (GAN) [1] is a generative modeling approach with a potential to learn high dimensional, complex real data distribution. In particular, they don’t depend on any assumptions about the conveyance and can produce real-like examples from inert space in a simple manner. This powerful property drives GAN [1] to be applied to different applications, for example, picture blend, picture quality altering, picture interpretation, space variation and other scholarly fields. While great outcomes have been approved by visual assessment, a few quantitative rules have developed as of late. In this paper, we aim to discuss the operations and objective functions of variants of GAN [1] but do not comprehend GAN [1] deeply or who wish to view GAN from various perspectives. In addition, we present the comparison of evaluation of the images generated from variants of GAN like DCGAN, FCC-GAN and more.
Model Predictive Control of Permanent Magnet Synchronous Motors in the Overmodulation Region Including Six-Step Operation

This paper proposes a model predictive control scheme with a higher-level open-loop torque control and an underlying continuous-control-set model predictive current control (CCS-MPCC) combined with a space vector modulation and an integrated harmonic reference generator (HRG) for permanent magnet synchronous motors (PMSMs), which is able to utilize the DC-link voltage of a two-level inverter to its maximum during transient and steady-state conditions. By formulating the CCS-MPCC as a quadratic program with the voltage hexagon as inequality constraints, the MPCC's typical dynamic response can be achieved during transient operation. When the overmodulation region is reached, additional current harmonics are induced by the voltage constraints, causing a deterioration of the controller's performance. To overcome this problem a HRG is introduced, which calculates at each sampling instant a reference current that contains these harmonics by solving a boundary value problem, using an overmodulation method under the assumption of steady state.Hence, the HRG performs a model-based current reference trajectory prediction ensuring that the CCS-MPCC can enter the overmodulation region. This allows highest control dynamics even at the voltage constraint while ensuring a seamless transition from linear modulation to overmodulation and six-step operation. The method presented here is able to operate in the entire speed range including standstill. Thus, it is not necessary to switch between different controller frameworks for the constant-torque and constant-power regions. Extensive simulative and experimental investigations for a highly utilized PMSM with significant (cross-)saturation effects prove the viability of the proposed control methodology.