Miracle-dz/UniFAR-FTUs huggingface dataset:
Off-Line Handwritten Chinese Character Recognition by Radical Decomposition

Off-line handwritten Chinese character recognition is a very hard pattern recognition problem of considerable practical importance. Two popular approaches are to extract features holistically from the character image or to decompose characters structurally into component parts—most usually strokes. Here, we take the novel approach of decomposing into radicals based on image information (i.e., without first decomposing into strokes). Active shape modeling is applied and developed into active radical modeling. In training, 60 examples of each radical are represented by ‘landmark’ points, labeled semi-automatically, with radicals in different characteristic positions treated as distinctly different radicals. Kernel principal component analysis then captures the main (non-linear) variations around the mean radical. In recognition, the dynamic tunneling algorithm is used to search for optimal shape parameters in terms of chamfer distance minimization. Considering character composition as a Markov process in which up to four radicals are combined in some assumed sequential order, we can recognize complete, hierarchically-composed characters using the Viterbi algorithm. This gives a character recognition rate of 93.5% characters correct (writer-independent) on a test set of 430,800 characters from 2,154 character classes composed from 200 radical categories, comparable to the best reported results in the literature. Although the initial semi-automatic landmark labeling is time consuming, the decomposition approach is theoretically well-motivated and allows the different sources of variability in Chinese handwriting to be handled separately and by the most appropriate means—either learned from example data or incorporated as prior knowledge. Hence, high generalization ability is obtained from small amounts of training data and only simple prior knowledge need be incorporated, so promising robust recognition performance. As such, there is very considerable potential for further development and improvement in the direction of larger character sets and less constrained writing conditions.
Analisis Kinerja Perbankan Syariah Di Indonesia Dengan Pendekatan Maqoshid Indeks (Periode 2009-2011)

Maqoshid index is one of the alternatives in measuring the performance of Islamic banking, Islamic banking which assessed aspects attainment of goals sharia. In this research the author tried to assess the performance of Islamic banking in Indonesia with maqoshid index approach. This research uses descriptive quantitative methodology to the entire study population of Islamic banking in Indonesia, while the sample is that Islamic banking has published an annual report 3 year. This research using purposive sampling method. From the results of the research with maqoshid index approach, in 2009 and 2010 BMI become Islamic bank which the best performance with best ratio value are 13.67% and 13,64 whereas in 2011 BSM became the best performance Islamic Bank with the best value ratio of 13.85%. Keywords: Measurement, Islamic banking, maqoshid index.
Passive Sonar Detection and Classification Based on Demon-Lofar Analysis and Neural Network Algorithms

This paper focuses on an experimental study that used passive sonar sensors as the primary information source for the submerged target in order to identify, classify, and recognize naval targets. Surface vessels and submarine generate a specific sound either by propulsion systems, auxiliary equipment or blades of their propellers, producing information known as the "acoustic signature" that is unique to each type of target. Consequently, the analysis and classification of targets depend on the processing of the frequencies produced by these vibrations (sound). utilizing the TPWS (Two-Pass-Split Windows) filter, this work aims to develop a novel technique for target identification and classification utilizing passive sonars. This technique involves processing the target's signal in the time-frequency domain. subsequently, in order to improve the frequency lines of the target noise and decrease the background noise, a TPSW algorithm is implemented in the frequency domain. By integrating narrowband and broadband analysis as inputs of an artificial intelligence model that can classify a target into one of the categories given in the training phase, the target has finally been classified. Our findings demonstrated that the suggested approach is dependent upon the size of the target noise data collection and the noise-to-effective-signal ratio.
Finite element analysis of undrained stability of cantilever flood walls

In this study, new undrained stability solutions of cantilever flood walls in clay were proposed and solved by finite element analysis with a two-dimensional plane strain condition. The analysis considered flood walls in homogeneous and non-homogeneous clay layers, where the latter corresponded to a linear increase in shear strength with depth. Two parametric studies were performed for embedded length ratios and dimensionless strength gradients. Results were summarised in the form of design charts for stability number, normalised maximum shear force and normalised maximum bending moment as a function of those two parameters. Closed-form solutions were proposed for a convenient and accurate evaluation of undrained stability of flood walls in practice, and their applications were demonstrated through a back analysis of a case study.
Soil catenas in archeological landscapes

Soil catenas crossing various archeological objects (ramparts, ancient settlements, burial mounds, etc.) with an age of 360-1800 years have been studied in the subzones of dark chestnut soils and typical, ordinary, and southern chernozems in the East European Plain. It is found that topography-induced variations in the thickness of zonal soil types are not always distinct. Often, the thickness of soil profiles does not depend on the slope gradient. In this context, it is supposed that the rate of the formation of humus horizons on slopes exceeds that on leveled surfaces. A comparative analysis of the thickness of humus horizons along soil catenas offers excellent possibilities for the determination of the rates of erosion and pedogenesis. The methodology of quantitative assessment of the potential rate of soil formation on slopes is suggested.
State scope of practice restrictions and nurse practitioner practice in nursing homes: 2012–2019

Abstract Increased engagement of nurse practitioners (NPs) has been recommended as a way to address care delivery challenges in settings that struggle to attract physicians, such as primary care and rural areas. Nursing homes also face such physician shortages. We evaluated the role of state scope of practice regulations on NP practice in nursing homes in 2012–2019. Using linear probability models, we estimated the proportion of NP-delivered visits to patients in nursing homes as a function of state scope of practice regulations. Control variables included county demographic, socioeconomic, and health care workforce characteristics; state fixed effects; and year indicators. The proportion of nursing home visits conducted by NPs increased from 24% in 2012 to 42% in 2019. Expanded scope of practice regulation was associated with a greater proportion and total volume of nursing home visits conducted by NPs in counties with at least 1 NP visit. These relationships were concentrated among short-stay patients in urban counties. Removing scope of practice restrictions on NPs may address clinician shortages in nursing homes in urban areas where NPs already practice in nursing homes. However, improving access to advanced clinician care for long-term care residents and for patients in rural locations may require additional interventions and resources.
Atmosphere‐ocean‐ice interactions in the Amundsen Sea Embayment, West Antarctica

Over recent decades outlet glaciers of the Amundsen Sea Embayment (ASE), West Antarctica, have accelerated, thinned, and retreated, and are now contributing approximately 10% to global sea level rise. All the ASE glaciers flow into ice shelves, and it is the thinning of these since the 1970s, and their ungrounding from “pinning points” that is widely held to be responsible for triggering the glaciers' decline. These changes have been linked to the inflow of warm Circumpolar Deep Water (CPDW) onto the ASE's continental shelf. CPDW delivery is highly variable and is closely related to the regional atmospheric circulation. The ASE is south of the Amundsen Sea Low (ASL), which has a large variability and which has deepened in recent decades. The ASL is influenced by the phase of the Southern Annular Mode, along with tropical climate variability. It is not currently possible to simulate such complex atmosphere‐ocean‐ice interactions in models, hampering prediction of future change. The current retreat could mark the beginning of an unstable phase of the ASE glaciers that, if continued, will result in collapse of the West Antarctic Ice Sheet, but numerical ice sheet models currently lack the predictive power to answer this question. It is equally possible that the recent retreat will be short‐lived and that the ASE will find a new stable state. Progress is hindered by incomplete knowledge of bed topography in the vicinity of the grounding line. Furthermore, a number of key processes are still missing or poorly represented in models of ice‐flow.
Realization and analysis of real-time precise point positioning based on SSR broadcast ephemeris corrections

The acquisition approach of real-time precise satellite orbit and clock products based on State Space Representation(SSR)corrections to broadcast ephemeris was analyzed in the paper.The generated real-time satellite orbit and clock products were further evaluated.Based on the Real-time Precise Point Positioning(RTPPP)model with broadcast ephemeris corrections,real-time static and kinematic PPP were realized using real-time SSR corrections through NTRI Pstreams disseminated by IGS analysis centers first,and then the accuracies of real-time static and kinematic PPP were also evaluated.Experimental results showed that the RMS of differences between real-time products and IGS final products could be about 4cm~7cm for satellite orbits and better than 0.3ns for satellite clocks.The accuracy of static RTPPP could reach 2cm level in the horizontal component and 4cm level in the up component when the observation session length is more than 6hours.The accuracy of 24-hour daily solution of static RTPPP could be better than 2cm in the horizontal and vertical components.The accuracy of kinematic RTPPP could reach centimeter level.Its convergence time to sub-decimeter could be almost the same as that taken by post-processing PPP with ambiguity unfixed.
SENSITIVITY ANALYSIS OF SO 2 EMISSIONS TO AEROSOL SULFATE OVER EAST ASIA BY CMAQ-DDM

In East Asia, its air quality has been dramatically changing due to the new policy of Chinese government in air pollution regulation. In our previous study, we found the variability in the fine-mode (submicron) aerosol optical depth (AOD) over the oceans adjacent to East Asia increased (4-8 %/yr) to a peak around 2005-2006 and subsequently decreased (4-7 %/yr) during 2000-2010, as revealed based on MODIS aerosol sensor and CMAQ modeling analysis. Such fluctuations in AOD are thought to reflect the widespread installation of fuel-gas desulfurization (FGD) devices in coal-fired power plants in China because aerosol sulfate is a major determinant of the AOD in East Asia [Itahashi et al., 2011]. Under the above mentioned background, it is necessary to clarify the source-receptor relationships of emissions from each country to the impact of chemical concentrations over East Asia. In this work, we investigate the sensitivity of SO2 emissions to aerosol sulfate based on the Decoupled Direct Method (DDM) implemented in CMAQ version 4.7. 1.
On the source of the 8 May 1939 Azores earthquake – tsunami observations and numerical modelling

ABSTRACT On 8 May 1939, an earthquake (Ms7.1) occurred near the Azores archipelago, with an epicentre located close to the western end of the Gloria fault. Previous studies present different epicentre locations spreading over a large area, and two different types of focal mechanisms. Given these uncertainties, the interpretation of the seismological information in a complex tectonic environment between the Gloria Fault and the Terceira Ridge is a matter of debate. The event caused a small tsunami recorded in the Azores Islands. In this study, we use the tsunami observations and tsunami numerical modelling to select the earthquake fault rupture that best fits the tsunami observations. We consider the different focal mechanism solutions, perform tsunami numerical modelling, and compute synthetic tsunami waveforms at the tide gauge locations. We find that an earthquake caused by a low-angle dipping fault with dominant strike–slip movement generates a tsunami that reproduces well the record at Ponta Delgada tide gauge. Finally, in areas where earthquakes are rare, the study of ancient earthquakes must use all information available, namely tsunami observations and mareograph data.
Proactive Caching for Vehicular Multi-View 3D Video Streaming via Deep Reinforcement Learning

This paper investigates the problem of proactive caching for multi-view 3D videos in the fifth generation (5G) networks. We establish a mathematical model for this problem, and point out that it is difficult to solve the problem with traditional dynamic programming, then we propose a deep reinforcement learning approach to solve it. First, we model the proactive caching system for multi-view 3D videos as a Markov decision process jointing views selection and local memory allocation. Then, we present an actor-critic, model-free algorithm based on the deep deterministic policy gradient to find effective proactive caching policy. Since the action space is affected by the system state, we embed dynamic k-Nearest Neighbor algorithm into actor-critic algorithm to implement the deep reinforcement learning algorithm working in an action space of variable size. Finally, the numerical results are given to demonstrate that the proposed solution can effectively maintain high-quality user experience for high-mobility 5G users moving among small cells. We also investigate the impact of configuration of critical parameters on the performance of the algorithm.
MICROS

Por más de una década, las calles de Santiago se tiñeron de un centellante color amarillo. La proliferación incesante de números de tres dígitos, exóticos nombres, dedicatorias de amor, improvisados altares religiosos, crípticos mensajes, luces de cabaret, peluches colgantes, focos rotos y topones estructuraron un rudimentario ecosistema que con los años se transformó en un objeto de culto irrebatible. Entre el desorden permanente, la pedestre decoración o la calidez del chofer y sus pasajeros, las micros se ganaron un espacio dentro del inconsciente colectivo nacional, hijas ilegitimas de una discreta tecnología y fanatismos diversos; posiblemente sin proponérselo, fueron el símbolo que mejor encarnó la trastienda sociocultural post-dictadura: una sumatoria de buenas intenciones amarradas con alambra. Amadas y odiadas por partes iguales hoy se despiden de las calles de Santiago y de nuestras vidas.
Dayia shirleyi Alvarez and Racheboeuf, 1986, un brachiopode silurien dans les «Schistes de Mondrepuis» à Muno, sud de la Belgique

A Muno, au bord nord de l'Anticlinorium de Givonne, de nombreuses Dayia shirleyi ALVAREZ & RACHEBOEUF, 1986 proviennent de la partie inferieure des «Schistes de Mondrepuis» surmontant le «Poudingue de Fepin», base du Gedinnien. La presence de ce brachiopode signifie que la partie inferieure du Gedinnien inferieur a Muno est d'âge silurien (pridolien)
Ethnobotanical study of plants used in the treatment of respiratory diseases in a population bordering the forest of Izarène

Context: Ethnobotanical surveys among users of medicinal plants have allowed us to inventory the medicinal species used and to safeguard the maximum of information acquired by the local population in traditional phytotherapy. Aims: To contribute to a better knowledge of the medicinal plants used in the treatment of respiratory diseases, an ethnobotanical study was carried out among the population bordering the Izarène forest. Methods: Using 480 questionnaire sheets, ethnobotanical field surveys were conducted during two campaigns (2013 to 2015). The determination of the different survey media was carried out using stratified probability sampling techniques. The ethnobotanical data were analyzed through the calculation of quantitative indices, such as Relative Frequency of Citation (RFC), Family Importance Value index (FIV), Fidelity Level (FL), Informant Consensus Factor (ICF) and Use-Value of the Plant Part (PPV). Results: Analysis of the results revealed 40 plant species, which fall into 19 botanical families. The Lamiaceae family was the most represented (14 species, FIV = 0.076). The highest Relative Citation Frequency (RFC) (0.22) was recorded for Mentha pulegium. Concerning the diseases treated, asthma had the highest ICF (0.95). The leaf was considered the most used part of the plant (PPV = 0.34), and most of the remedies were prepared as decoctions. Conclusions: The results obtained could constitute a basis for further studies for the valorization of medicinal plants used against respiratory diseases through biological and phytochemical studies of the inventoried plants.
Effects of empirical versus model-based reflectance calibration on automated analysis of imaging spectrometer data: a case study from the Drum Mountains, Utah

Data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) have been calibrated to surface reflectance using an empirical method and an atmospheric model-based method. Single spectra extracted from both calibrated data sets for locations with known mineralogy compared favorably with laboratory and field spectral measurements of samples from the same locations. Generally, spectral features were somewhat subdued in data calibrated using the model-based method when compared with those calibrated using the empirical method. Automated feature extraction and expert system analysis techniques have been successfully applied to both data sets to produce similar endmember probability images and spectral endmember libraries. Linear spectral unmixing procedures applied to both calibrated data sets produced similar image maps. These comparisons demonstrated the utility of the model-based approach for atmospherically correcting imaging spectrometer data prior to extraction of scientific information. The results indicated that imaging spectrometer data can be calibrated and analyzed without a priori knowledge of the remote target.
Analysis of signs and symptoms of SARS-CoV-2 virus infection considering different waves using Machine Learning

In March 2020, the World Health Organization declared a world pandemic of COVID-19, which can manifest in humans as a consequence of virus infection of SARS-CoV-2. On this context, this work uses Data Mining and Machine Learning techniques or the infection diagnosis. A methodology was created to facilitate this task and can be applied in any outbreak or pandemic wave. Besides generating diagnosis models based only on signals and symptoms, the method can evaluate if there are differences in signals and symptoms between waves (or outbreaks) through explainable techniques of the machine learning models. Another aspect is identifying possible quality differences between exams, for example, Rapid Test (RT) and Reverse Transcription-Polymerase Chain Reaction (RT-PCR). The case study in this work is based on data from patients who sought care at Piquet Carneiro Polyclinic of the State University of Rio de Janeiro. In this work, the results obtained with the tests were used to diagnose symptomatic infection of the SARS-CoV-2 virus, based on related signals and symptoms, and the date of the initial of these signals and symptoms. Using the Random Forrest model, it was possible to achieve the result of up to 76% sensitivity, 86% specificity, and 79% accuracy in the results of tests in one contagion wave of the SARS-CoV-2 virus. Moreover, differences were found in signals and symptoms between contagion waves, in addition to the observation that exams RT-PCR and RT Antigen tests are more reliable than RT antibody test.
Liver Intrinsic Function Evaluation (LIFE): Multi-parametric Liver Function Profiles of Patients Undergoing Hepatectomy

For a range of liver malignancies, the only curative treatment option may be hepatectomy, which may have fatal complications. Therefore, an unbiased pre-operative risk assessment is vital, however, at present the assessment is typically based on global liver function only. Magnetic resonance imaging (MRI) modalities have the possibility to aid this assessment, by introducing additional characterization of liver parenchymal, such as non-invasive quantification of steatosis, fibrosis, and uptake function, both for global and regional assessment. To this cause, we here present a prospective observation study (LIFE), in which patients underwent extensive MR-examinations both before and after resective-surgery. A total of 13 patients undergoing hepatectomy underwent a pre- (n=13) and post (m=5) multi-modal MRI examination (within 3-5 days of the surgery) (Fig. 1B). The multimodal MR-examination included DCE, 3D-MRE, fat fraction measurements (PDFF by MRS, 6PD). Using these measurements, we also construct individual patient profiles by including conventional functional, and volumetric measurements, into a multi-parametric space. As a proof of concept, the areas of each profile, denoted multiparametric profile area (MPA, and aMPA) were calculated, to create a measurement comprising information from all modalities. At a group-level, no clear pattern emerged of MPA or aMPA between groups with different ex-tent of resection. In contrast, on a case-by-case basis, several parameters contributed to high individual MPA or aMPA-values, suggesting tissue abnormalities. With respect to regional DCE measurements, i.e., relative enhancement at 20 minutes, a clear variation between function in segments, within and between the individuals, was observed. In this combined pre- and post-observational case-based study ranging from very extensive (i) liver surgery to minor (ii), or none (iii), we aimed to describe how a multi-modal MRI examination before hepatectomy could yield valuable information for the pre-operative assessment, with a particular focus on a Couinaud-segmental level. The use of a multi-modal approach allows for a broad spectral characterization of several aspects of the remnant tissue. However, the effectiveness and clinical benefit of each parameter, and how to further optimize an abbreviated clinical MR-protocol needs to be confirmed.