Miracle-dz/UniFAR-FTUs huggingface dataset:
Progress in Computational Methods for Representing Geographic Concepts

Over the last ten years, a subfield of GIScience has been recognized that addresses the linkage between human thought regarding geographic space and the mechanisms of implementing these in computational models. This research area has developed an identity through a series of successful international conferences and the establishment of a journal. It has also been complemented through community activities such as international standardization efforts and GIS interoperability. Historically, much of the advancement in computational methods has occurred at—or close to—the implementation level, as exemplified by the attention on the development of spatial access methods. Significant progress has been made at the levels of spatial data models and spatial query languages, although we note the lack of a comprehensive theoretical framework comparable to the relational data model in databases management systems. The difficult problems that need future research efforts are at the highly abstract level of capturing semantics of geographic information. A cognitive motivation is most promising as it shapes the focus on the users' needs and points of view, rather than on efficiency as in the case of a bottom-up system design. We also identify the need for new research in fields, models of qualitative spatial information, temporal aspects, knowledge discovery, and the integration of GIS with database management systems.
Effects of satellite data resolution on measuring the space/time variations of surfaces and clouds

Abstract The correlated distributions of satellite-measured visible and infrared radiances, caused by spatial and temporal variations in clouds and surfaces, have been found to be characteristic of the major climate regimes and can be described by the attributes of bidimensional and monodimensional histograms and time-composite images. Most of the variability of both the surfaces and clouds is found to occur at scales larger than the minimum resolved by satellite imagery. Since satellite imaging data sets are difficult to analyse because of their large volumes, many studies reduce the volume by various sampling or averaging schemes. The effects of data resolution and sampling on the radiance histogram statistics and on the time-composite image characteristics are examined. In particular, the sampling strategy used by the International Satellite Cloud Climatology Project is tested. This sampling strategy is found to preserve the statistics of smaller cloud variations for most regions, with the exception of.
A Numerical Study on Impact of Taiwan Island Surface Heat Flux on Super Typhoon Haitang (2005)

Three to four tropical cyclones (TCs) by average usually impact Taiwan every year. This study, using the Developmental Tested Center (DTC) version of the Hurricane WRF (HWRF) model, examines the effects of Taiwan’s island surface heat fluxes on typhoon structure, intensity, track, and its rainfall over the island. The numerical simulation successfully reproduced the structure and intensity of super Typhoon Haitang. The model, especially, reproduced the looped path and landfall at nearly the right position. Sensitive experiments indicated that Taiwan’s surface heat fluxes have significant influence on the super Typhoon Haitang. Compared to sensible heat (SH) fluxes, latent heat (LH) is the dominant factor affecting the intensity and rainfall, but they showed opposite effects on intensity and rainfall. LH (SH) flux of Taiwan Island intensified (weakened) Typhoon Haitang’s intensity and structure by transferring more energy from (to) surface. However, only LH played a major role in the looped path before the landfall of the Typhoon Haitang.
Modelos para la prevención de bancarrotas empresariales utilizados por el sector empresarial costarricense (Models for company bankruptcy prevention used by the Costa Rican business sector)

El presente articulo ofrece un analisis delos modelos para la prevencion de bancarrotamas citados en la literatura, entre los cualesestan: modelo Z score de Altman, modelo deOhlson, modelo de Beaver, modelo de arbolesde decision y modelo DuPont. Ademas, incluyeun estudio de los modelos utilizados por elsector empresarial costarricense, en el cual seevidencia el desconocimiento sobre el tema,ya que la mayoria de empresas investigadasno utiliza o conoce ningun modelo con lacapacidad de prevenir las bancarrotas. En esesentido, las herramientas mas utilizadas son lasrazones financieras, control sobre el presupuestoy, en algunos casos, el esquema integral derentabilidad (Dupont). AbtractThis article presents an analysis of themodels for bankruptcy prevention mostcited in literature, that is, the Z-score modelby Altman, the Ohlson 0-score, the Beavermethod, the Decision Tree model and theDuPont method. It also includes a study ofmodels used by the Costa Rican businesssector that shows a complete lack of awarenessof the subject, since most of it does not know oruse any model for bankruptcy prevention. Tothis end, financial ratios, budget control andin some cases the DuPont integral profitabilitymethods are the ones most used.
Mantle Melting and Basalt Extraction by Equilibrium Porous Flow

The chemical composition of mid-ocean ridge basalt, the most prevalent magma type on the planet, reflects the melt's continuous reequilibration with the surrounding mantle during porous flow. Models of basalt extraction that account for the observed uranium-series disequilibria on the Juan de Fuca ridge constrain both the abundance of melt beneath ridges (0.1 to 0.2 percent) and the style of mantle melting. Unlike models that incorporate near-fractional melts (dynamic melting), mixing of equilibrium porous flow melts derived from heterogeneous source materials quantitatively explains the uranium-series observations.
THE INFLUENCE OF SLOPE AND RAIN INTENSITY ON RUNOFF AND INFILTRATION / L'influence de l'inclinaison de terrain et de l'intensité de pluie sur l'écoulement et l'infiltration

Abstract The design and construction of a special-purpose laboratory catchment and rainfall simulator is described. The equipment consists of a soil catchment area that can be inclined at various angles. Additional instrumentation then measures the flow of water across the surface of, and through, the soil bed. Precipitation is provided by a unit that simulates rainfall at particular rates with uniform distribution. The equipment was used to examine infiltration, runoff and other hydrological properties of a number of soils under different rainfall intensities and with different catchment slopes. Correlations were obtained for these variables.
A minimal cost function method for optimizing the age‐Depth relation of deep‐sea sediment cores

The question of an optimal age-depth relation for deep-sea sediment cores has been raised frequently. The data from such cores (e.g., δ18O values) are used to test the astronomical theory of ice ages as established by Milankovitch in 1938. In this work, we use a minimal cost function approach to find simultaneously an optimal age-depth relation and a linear model that optimally links solar insolation or other model input with global ice volume. Thus a general tool for the calibration of deep-sea cores to arbitrary tuning targets is presented. In this inverse modeling type approach, an objective function is minimized that penalizes: (1) the deviation of the data from the theoretical linear model (whose transfer function can be computed analytically for a given age-depth relation) and (2) the violation of a set of plausible assumptions about the model, the data and the obtained correction of a first guess age-depth function. These assumptions have been suggested before but are now quantified and incorporated explicitly into the objective function as penalty terms. We formulate an optimization problem that is solved numerically by conjugate gradient type methods. Using this direct approach, we obtain high coherences in the Milankovitch frequency bands (over 90%). Not only the data time series but also the the derived correction to a first guess linear age-depth function (and therefore the sedimentation rate) itself contains significant energy in a broad frequency band around 100 kyr. The use of a sedimentation rate which varies continuously on ice age time scales results in a shift of energy from 100 kyr in the original data spectrum to 41, 23, and 19 kyr in the spectrum of the corrected data. However, a large proportion of the data variance remains unexplained, particularly in the 100 kyr frequency band, where there is no significant input by orbital forcing. The presented method is applied to a real sediment core and to the SPECMAP stack, and results are compared with those obtained in earlier investigations.
Detection, Structure, and Origin of Extreme Anomalies in a Western Atlantic Oceanographic Section

Abstract Ten anomalous water parcels were detected in the water column of a western Atlantic oceanographic section (0–5550 m; 70°W; 23–33°N). The parcels had extreme properties lying either two standard deviations from historical mean values, or estimated origins lying 2000 km from the oceanographic section. Detection, structure, and origin of the parcels were determined from analyses on isobaric and isopycnal surfaces using eight kinds of measurements temperature, salinity, oxygen, light scattering, silicate, phosphate, nitrate, and tritium. The parcels originated from seven of the major water masses comprising the North Atlantic Ocean. As observed along the oceanographic section the parcels had the following average (range) characteristics vertical pressure extent = 650 db (100–150 db); horizontal extent = 130 km (30–260 km); and distance to origin = 2300 km (400–5200 km). A population density equaling approximately one parcel per 100 km was obtained as the number of parcels (10) divided by the length o.
Identification of Linear Models for the Dynamics of a Hovering Quadrotor

Accurate dynamic modeling of helicopter aeromechanics is becoming increasingly important, as progressively stringent requirements are being imposed on rotorcraft control systems. System identification plays an important role as an effective approach to the problem of deriving or fine tuning mathematical models for purposes such as handling qualities assessment and control system design. In this paper, the problem of deriving continuous-time models for the dynamics of a small-scale quadrotor helicopter is considered. More precisely, the continuous-time predictor-based subspace identification approach is adopted and the results obtained in an experimental study are presented and discussed.
Comparisons of aerosol optical depth and surface shortwave irradiance and their effect on the aerosol surface radiative forcing estimation

[1] Column aerosol optical depth (AOD) and surface shortwave irradiance (SSI) measurements relevant to computation of the aerosol surface radiative forcing (ΔF) and forcing efficiency (β) were taken as part of Aerosol Characterization Experiment-Asia (ACE-Asia) at the Gosan surface site in Korea in April 2001. We compare the AOD and SSI derived from three different types of Sun photometers and three sets of radiometers. We also estimate the ΔF and β using two methods and quantify the observational uncertainties of these parameters. A comparison of the AOD at 500 nm shows that the three Sun photometers generally agreed within 0.014 (mean), 0.0142 (bias), and 0.0298 (root mean square) for coincident observations. Over the course of the comparison, the mean differences between the SSI measurements were 1.6, 11.7, and 10.1 Wm−2 for direct, diffuse and global irradiances, respectively. However, for both the AOD and the SSI comparisons, relatively high instantaneous differences between the instruments were apparent on days with heavy dust at the surface. The mean β and associated deviations, which were estimated by the combinations of different instrument-derived AODs and SSIs, for simultaneous observation data at a 60° solar zenith angle are −79.50 ± 3.92 and −82.57 ± 5.70 Wm−2/τ500 for globalshaded (sum of direct and diffuse irradiances) and globalunshaded (measured by the unshaded pyranometer) irradiances, respectively. The uncertainties in β associated with uncertainties in the AOD and SSI (in parentheses) for globalshaded and globalunshaded irradiance are about 8.6% and 3.2% (10.7%), respectively. A 2% difference between the measured global irradiances for a given 9 days was translated into an uncertainty of 19% in ΔF. This difference in ΔF between instruments caused a 14% deviation in β.
A statistical analysis of death rates in Italy for the years 2015-2020 and a comparison with the casualties reported for the COVID-19 pandemic

We analyze the data about casualties in Italy in the period 01/01/2015 to 30/09/2020 released by the Italian National Institute of Statistics (ISTAT). The data exhibit a clear sinusoidal behavior, whose fit allows for a robust subtraction of the baseline trend of casualties in Italy, with a surplus of mortality in correspondence to the flu epidemics in winter and to the hottest periods in summer. While these peaks are symmetric in shape, the peak in coincidence with the COVID-19 pandemics is asymmetric and more pronounced. We fit the former with a Gaussian function and the latter with a Gompertz function, in order to quantify number of casualties, the duration and the position of all causes of excess deaths. The overall quality of the fit to the data turns out to be very good. We discuss the trend of casualties in Italy by different classes of ages and for the different genders. We finally compare the data-subtracted casualties as reported by ISTAT with those reported by the Italian Department for Civil Protection (DPC) relative to the deaths directly attributed to COVID-19, and we discuss the differences.
Neural bases of reading fluency: A systematic review and meta-analysis

Reading fluency, the ability to read quickly and accurately, is a critical marker of successful reading and is notoriously difficult to improve in reading disabled populations. Despite its importance to functional literacy, fluency is a relatively under-studied aspect of reading, and the neural correlates of reading fluency are not well understood. Here, we review the literature of the neural correlates of reading fluency and rapid automatized naming (RAN), a task that is robustly related to reading speed. In a qualitative review of the neuroimaging literature, we evaluated structural and functional MRI studies of reading fluency in readers ranging in skill levels. This was followed by a quantitative activation likelihood estimate (ALE) meta-analysis of fMRI studies of reading fluency and RAN measures. We anticipated that reading speed, relative to untimed reading and reading-related tasks, would harness ventral reading pathways that are thought to enable the fast, visual recognition of words. The qualitative review showed that speeded reading taps the entire canonical reading network. The meta-analysis, which focused on in-scanner reading fluency measures, indicated a stronger role of the ventral reading pathway in fluent reading. Both reviews identified regions outside the canonical reading network that contribute to reading fluency, such as the bilateral insula and superior parietal lobule. We suggest that fluent reading engages both domain-specific reading pathways as well as domain-general regions that support overall task performance and discuss future avenues of research to expand our understanding of the neural bases of fluent reading.
Gradient boosted decision trees reveal 1 nuances of auditory discrimination 2 behaviour 3

10 Perceptual constancy remains an elusive feature to measure in psychophysical animal studies due to the intractability of correlating trial parameters to trial outcomes and response times. Moreover, the nonlinear nature of our data constrains the potential that traditional statistical models have to elucidate the sensory and non-sensory factors that ultimately shape animal performance. In this study, we present an implementation of gradient-boosted regression and decision trees, a machine learning method, to gain insights into animal behavioural data. We implement this computational modelling method on a task in which 5 ferrets were trained to recognize a target word (”instruments”) against a stream of 54 other English non-target word tokens. To test perceptual constance to pitch, we manipulated the mean fundamental frequency (F0) of each trial across the whole series of word tokens (inter-trial F0 roving) or between word tokens (intra-trial F0 roving). We implemented Shapley Additive Explanations and permutation importance for model explainability to determine which factors were significant in our gradient-boosted regression and decision tree model performance. We found that, despite high performance on both intra-trial F0 roved and inter-trial F0 roved task paradigms, F0s that our subjects were introduced to after their initial control F0 period increased the rate of false alarms, and an F0 difference between the target word and the preceding non-target word caused slower reaction times. We also found a subset of non-target distractor words that increased the rate of false alarms and that shared spectrotemporal properties with the target word. Together, our results demonstrate that ferrets, like humans, are capable of showing tolerance to changes in pitch when discriminating complex sounds and that they rely on pitch as a cue to link sounds together over time. Finally, we illustrate the utility of gradient-boosted decision trees to gain insights into behavioural datasets.
Research on the control strategy of PMSM under neutral point supply topology

This article proposes a novel neutral point supply topology for three-phase permanent magnet synchronous motor (PMSM) drive system, which integrates drive function and boost function in a single circuit. Firstly, a new coordinate transformation equation is derived, which leads to the mathematical model of the PMSM with neutral point. Secondly, the mathematical model of the neutral point supply topology is derived to analyze the operating principle of the equivalent DC/DC converter. Then, the control strategy of the system is subsequently designed. Finally, simulation is utilized to verify the correctness of the theoretical analysis and the effectiveness of the proposed control strategy. The simulation results show that the proposed system can maintain a stable step-up of the bus voltage, achieve accurate follow-up of the $dq$-axis currents, and output stable electromagnetic torque. The system provides a promising solution for high-efficiency and compact motor drive systems.
Gamification in Live Streaming Platform: A Systematic Literature Review

Gamification uses game design techniques, game thinking, and game mechanics to enhance non-game context. Gamification usually refers to applications and processes outside of games that encourage people to adopt or influence how they use them. The Authors' goal in taking this topic is to tell some aspects of using the gamification system. Of the 210 journals the Authors found in making this article, there were 24 articles that the Authors made the primary reference in making this scientific article. The Authors use a Systematic literature Review with three research questions: What elements are used in Live Streaming gamification? What media is suitable for live-streaming Gamification? What are the impacts of using Gamification in live streaming? From the amount of data, the authors found in various references; the authors found a conclusion that readers can use; in fact, Author believes that this gamification system is more profitable for the marketing, entertainment, and live streaming sectors.
Few-Shot Learning for Smart Manufacturing: Tool Wear Prediction Using Out-of-Domain Data Based on Meta-Learning

Tool wear has a significant impact on many fields of the machining process, consisting of tool life, quality of the workpiece, and machining efficiency. Over the past few years, although numerous data-driven models have been proposed to accurately predict tool wear, they usually require abundant historical data. Meanwhile, predicting tool wear with limited historical data under various cutting conditions, especially with large variations is still a challenge due to the domain shift problem. To fill the research gap, this paper proposes a novel model-agnostic domain generalization (MADG) technique to effectively predict tool wear with small data under various cutting conditions. Through iterative training on randomly constructed subtasks, MADG can provide promising initial parameters for models to generalize among domains. Experimental results on NASA Ame milling data prove the validity and practicability of this technique.
Jitter Noise Impact on Analog Spiking Neural Networks: STDP Limitations

Accurate spike timing of neurons is essential for the temporal learning rules in Spiking Neural Networks (SNNs), such as the spike-timing dependent plasticity (STDP). Implementing these rules in analog SNNs presents a challenge as it would require a reliable spike timing of analog neurons. This paper investigates the impact of jitter noise on the spike timing of various analog neuron models, and highlights trade-offs in training neurons using spike timing. Post-layout simulation results reveal that noise-induced period jitter significantly affects spike occurrence time. Its values are three orders of magnitude higher than the precise spike timing required for an accurate synaptic weight updates. Moreover, the spike timing becomes a random variable with a σ/µ that exceeds 76%. This study shows that the spiking frequency is a more reliable measure of neuronal activity, as it achieves a σ/µ of only 0.2%.
Folded, Articulated Manipulator with Inflatable Skin Enabling Bending and Extension Using a Tension Cutoff Mechanism

Robots providing safe services in the same space as humans are popular owing to the aging population. Inflatable structures are suitable for robots that assume physical contact with humans because they enable changes in rigidity according to internal pressurization. However, systems that provide support to relatively heavy objects, such as humans, warrant safety concerns. We introduce a wire bending system with a tension cutoff mechanism that can simultaneously bend and extend with minimal driving force. The system can be installed on an articulated skeleton used to design an inflatable arm. Our research team developed an inflatable arm with both soft and rigid mechanisms by incorporating a folded articulated skeleton into a membrane structure. We verified that the arm could be actively wound around an object without damaging the object using the conventional machine. However, simultaneous bending and extension were not achieved. Therefore, we constructed a wire-bending system in which the driving force of the bending is transmitted only to the necessary point by installing a tension cutoff mechanism in the articulated skeleton. As a result, The simultaneous bending and extension of the inflatable arm were achieved mechanically, and the functionality was successfully improved. This mechanism can be applied to wire-driven articulated manipulators and machines using rotating wires.