Miracle-dz/UniFAR-FTUs huggingface dataset:
Recognizing Semantic Concepts of Spoken Arabic Utterances using Genetic Technology

Genetic algorithms (GA) are a family of computational models inspired by evolution. GA mainly designed to solve optimization problems which can be thought of as searching through a large number of candidates for the best one that can be found. In this paper we present a genetic model to solve the problem of recognizing deep semantic concepts from spoken Arabic utterances. The aim of this algorithm is to automatically generate the grammar that recognizes each concept in the domain of discourse. This grammar is used to extract the observed concepts from the utterance. An experiment has been conducted to measure the performance of our approach. The results were promising and assured the ability of this approach in identifying the concepts of Arabic utterances taken from the travel and tourism domain.
Land evaluation for agricultural land use planning in the Gawar plain, Cameroon

Land evaluation is part of the process of land use planning. The identification of suitable forms of land use provides the building blocks for land-use planning. It is concerned with predicting land performance over time according to specific types of use and is required to guide strategic land use decisions. Many agricultural regions in Cameroon lack agricultural land use plans. The objectives of this study were to: evaluate the suitability of different soil types for rainfed upland crop production; produce land suitability maps for groundnut, maize, cotton and sorghum, correlate indigenous land evaluation with FAO land suitability evaluation (LSE) and propose management strategies for improved upland crop production in the Gawar plains. Representative profiles were described and soil samples collected for each horizon for routine soil analysis. Based on the land utilization types considered, the following land qualities were evaluated: climate (c), wetness (w), soil physical conditions (s) fertility (f), salinity and alkalinity (n) and topography (t). The output of the LSE was compared with an indigenous land evaluation. Generally, the soils of Gawar plain were moderately suitable (S3) for all the crops evaluated, with soil fertility and physical constraints mostly implicated for the moderate suitability. The most suitable (S2) class was obtained on alluvial (Lougéré) soils and ferruginous (Walouwol) soils (for groundnut and sorghum). Farmers have an understanding of the effect of soil type on land suitability for different crops, but their judgment of land suitability for crops was one class lower than that obtained with the FAO framework of land suitability evaluation. The close matching of indigenous and scientific land evaluation systems indicates that scientific land evaluation and farmers’ classification of suitable soils are based on the same principles. There is an opportunity to boost arable crop production in Gawar plain through improved soil fertility management options developed for major soils or indigenous soil classes and also to promote integrated farming system.
Dry Mass Yield and Bromatological Composition of the Forage of Cynodon dactylon cv. Vaquero Submitted to Crescent Doses of Nitrogen, Applied as Swine Waste

The present had as its objective to evaluate the response of dry mass total yield, and bromatological composition of the forage, submitted to different nitrogen doses, applied as swine waste in the pasture of Cynodon dactylon cv. ‘Vaquero’. The study was developed during the period of November 2017 until March 2018, in the experimental area of the ‘Pontificia Universidade Catolica do Parana’, campus Toledo, located in the western region of Parana, under latitude 24o43′13″ S and longitude 53o47′01″ W. The experimental design adopted was of randomized blocks with six treatments (0, 50, 100, 150, 200 and 250 kg ha-1) constituted by crescent doses of nitrogen as swine waste, with five replicates, totalizing 30 experimental plots. It was studied the dry mass yield (kg ha-1), crude protein (CP), dry mass (DM), neutral detergent fiber (NDF), acid detergent fiber (ADF), insoluble nitrogen in neutral detergent (NDIN), insoluble nitrogen in acid detergent (ADIN), lignin, ether extract (EE) and mineral matter (MM). It was verified that the N doses influenced in the dry mass yield of the forage, because it reached a productivity of 4520.57 kg ha-1 in the dry mass. The highest crude protein content of ‘Vaquero’ was obtained with the dose of 250 kg ha-1 of nitrogen, in which was observed a content of 13.72 g kg-1 of CP in the dry mass. The different nitrogen doses, applied as swine waste in the pasture of grass ‘Vaquero’, have an influence in the bromatological composition and in the dry mass yield, causing an increase in the forage contents of crude protein (CP), dry mass (DM), ether extract (EE), in forage produced under four cutting periods. The increase in the nitrogen doses improves the nutritional quality of grass ‘Vaquero’, once it causes decreases in the NDF and ADF content and increases in the CP and DM content.
THE PROJECTIVE SYMMETRY GROUP OF A FINITE FRAME

We deﬁne the projective symmetry group of a ﬁnite sequence of vectors (a frame) in a natural way as a group of permutations on the vectors (or their indices). This deﬁnition ensures that the projective symmetry group is the same for a frame and its complement. We give an algorithm for computing the projective symmetry group from a small set of projective invariants when the underlying ﬁeld is a subﬁeld of C which is closed under conjugation. This algorithm is applied in a number of examples including equiangular lines (in particular SICs), MUBs, and harmonic frames.
Bulletin of the Geological Society of Greece

Based on the results of our studies for the tidal triggering effect on the seismicity of the Hellenic area, we consider the confidence level of earthquake occurrence tidal period accordance p as an index of tectonic stress criticality for earthquake occurrence. In this paper, by the occasion of the recent catastrophic earthquake of Nepal, we investigate the variation of the index p for the South Himalaia Fault area. The preliminary results indicate positive correlation of the index p with seismicity, for all the tidal periods. We suggest that this compliance parameter p may be used as an additional element for the seismic risk assessment.
Cd-contaminated solution treatment by activated and non- activated beech charcoal

Biochar obtained from pyrolysis of vegetable waste has been recognized to possess adsorbent capacity. Furthermore, it represents an economic and environmentally sustainable alternative to commercial adsorbents because, being a waste product, its use allows to avoid industrial activities for adsorbent production as well as to reduce the amount of waste to be disposed of. In this paper, the biochar produced by pyrolysis of beech has been investigated as a potential adsorbent for remediation of cadmium-contaminated groundwater. So far, beech charcoal has been mainly used as a soil amendment and only few experiences have been reported about its use as an adsorbent medium. The present experimental activity started with a series of analyses to obtain the main physical-chemical characteristics of charcoal. Adsorption kinetics and isotherms through batch experiments were then determined. Furthermore, breakthrough curves were obtained through column experiments. The same tests were repeated using the beech charcoal after modification through the addition of specific bacterial strains able to produce a reactive monolayer biofilm. The results showed that bio-activated charcoal has enhanced adsorption capacity for cadmium-contaminated solution. Therefore, charcoal and bio-activated charcoal may be considered valid options as adsorbents for the remediation of solution contaminated by cadmium.
The effect of pelvic floor muscle exercises on sexual function in women with multiple sclerosis: a pre – post intervention clinical trial

1 Reproductive Health Promotion Research Center, School of Nursing and Midwifery, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran 2 Faculty of Nursing and Midwifery, Menopause Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran 3 Comprehensive Rehabilitation Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran 4 Department of Statistics and Epidemiology, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
Dronecaps: Recognition Of Human Actions In Drone Videos Using Capsule Networks With Binary Volume Comparisons

Understanding human actions from videos captured by drones is a challenging task in computer vision due to the unfamiliar viewpoints of individuals and changes in their size due to the camera’s location and motion. This work proposes DroneCaps, a capsule network architecture for multi-label human action recognition (HAR) in videos captured by drones. DroneCaps uses features computed by 3D convolution neural networks plus a new set of features computed by a novel Binary Volume Comparison layer. All these features, in conjunction with the learning power of CapsNets, allow understanding and abstracting the different viewpoints and poses of the depicted individuals very efficiently, thus improving multi-label HAR. The evaluation of the DroneCaps architecture’s performance for multi-label classification shows that it outperforms state-of-the-art methods on the Okutama-Action dataset.
Adaptive Cruise Control Strategy Design with Optimized Active Braking Control Algorithm

The braking quality is considered as the most important performance of the adaptive control system that influences the vehicle safety and ride comfort remarkably. This research is aimed at designing an adaptive cruise control (ACC) system based on active braking algorithm using hierarchical control. Taking into account the vehicle with safety and comfort, the upper decision-making controller is designed based on model predictive control algorithm. Throttle controller and braking controller are designed with feedforward and feedback algorithms as the bottom controller, where the braking controller is designed based on the hydraulic braking model. The whole model is simulated collaboratively with Amesim, Carsim, and Simulink. By comparison with the full deceleration model, the results show that the proposed algorithm can not only make the vehicle maintain a safe distance under the premise of following the target vehicle ahead effectively but also provide favorable driving comfort.
Modélisation numérique régionale de l’impact des éoliennes offshore sur l’hydrodynamique et le transport sédimentaire

using two approaches. The ﬁrst method takes into account monopiles directly in the mesh as dry cells and the second one uses a sub-grid parameterization method by adding drag force term in momentum equations and source terms in k-(cid:15) turbulence model equations. Comparisons between the results obtained by the diﬀerent approaches are carried out. As expected, both show impacts on the circulation, with formation of a wake downstream, ﬂow deceleration in front of the pile, and ﬂow acceleration at the side edges. Near-bed erosion occurs in locations where current speeds increase due to the monopile presence, leading to an increase of suspended sediment concentration.
Stable Carbon and Oxygen Isotopes as Environmental Indicators of the Late Pleistocene in El Arenoso, Sonora, Northwest Mexico

Víctor Adrían PÉREZ-CRESPO*, Tamara CRUZ-Y-CRUZ, Alejandro TERRAZAS-MATA, Pedro MORALES-PUENTE, Martha BENAVENTE, Edith CIENFUEGOS-ALVARADO, Francisco J. OTERO Institute of Geology, National Autonomous University of Mexico, Coyoacán, Mexico Postdoctoral Scholarship Program at UNAM, Institute of Anthropological Research, Coyoacán, Mexico Institute of Anthropological Research, National Autonomous University of Mexico, Coyoacán, Mexico National Laboratory of Geochemistry and Mineralogy (LANGEM), Mexico City, Mexico Laboratory of Prehistory and Human Evolution, Institute of Anthropological Research, National Autonomous University of Mexico, Coyoacán, Mexico
Treating me with Respect: How Visitor's Perceptions of Interpersonal Injustice Affect Their Emotional Response and Social Media Testimonial

The purpose of this study was to investigate how interactional injustice affects customers' emotional responses and the impact of such responses on word-of-mouth recommendations on social media. Specifically, this research develops and tests a theoretical model that connects issues (interactive injustice and sentiment) in scenic area service processing with opinion sharing events (electronic word of mouth) in social networks. A survey asked visitors who have experience in service processing in scenic spots and who also belong to social media users. The survey produced 244 valid answers. The results of this study show that perceived interactional injustice affects visitors' electronic word of mouth through the emotions generated by the service. Just world belief plays a moderating role in the relationship between interactive injustice and emotional response. This study provides strategic advice to tourism practitioners by linking the services of scenic areas with visitors' understanding of interactive injustice, emotions and perspectives on social media.
Understanding Association Between Logged Vehicle Data and Vehicle Marketing Parameters: Using Clustering and Rule-Based Machine Learning

Trucks are designed, configured and marketed for various working environments. There lies a concern whether trucks are used as intended by the manufacturer, as usage may impact the longevity, efficiency and productivity of the trucks. In this paper we propose a framework that aims to extract costumers' vehicle behaviours from Logged Vehicle Data (LVD) in order to evaluate whether they align with vehicle configurations, so-called Global Transport Application (GTA) parameters. Gaussian mixture model (GMM)s are employed to cluster and classify various vehicle behaviors from the LVD. Rule-based machine learning (RBML) was applied on the clusters to examine whether vehicle behaviors follow the GTA configuration. Particularly, we propose an approach based on studying associations that is able to extract insights on whether the trucks are used as intended. Experimental results shown that while for the vast majority of the trucks' behaviors seemingly follows their GTA configuration, there are also interesting outliers that warrant further analysis.
A Research of AHP Approach in Evaluating Sustainable Tourism Development

Sustainable tourism development is a key factor for tourism destination development, and evaluating the sustainable tourism development level can reflect the current situation, existing problems and deficiencies of tourism destinations. Based on constructing the evaluation index system of sustainable tourism development from four aspects, they are sustainability of tourism resources, economic feasibility, social acceptability and environmental rationality, this work applied AHP method to calculate the weight of each index, and takes Luojiang District, Deyang, Sichuan Province, China as research area. On the basis of data collection and collation, the sustainable tourism development level of Luojiang District between 2002 and 2016 was evaluated, the results show that from 2002 to 2016, the sustainable tourism development level of Luojiang District showed an overall upward trend, and can be divided into four stages: the first is the preparation stage of 2002-2011, the second is the preliminary stage of 2012-2013, the third is the basic stage of 2014-2015 and the fourth is the sustainable stage from 2016.
Applying Artificial Intelligence to Survival Prediction of Hepatocellular Carcinoma Patients

Cancer, a disease that has gradually attracted attention in the world now, it has even become one of the main causes of death. Among them, liver cancer occurs in the liver or deadly tumors starting from the liver. According to the World Cancer Report (2014), the liver cancer is primary the cancer that the occurrence of 6% ranked second highest, and the death rate is 9% ranked sixth. So the liver cancer has become the target of academic research and discussion. If we can find out the key factors that affect the death of liver cancer when identifying liver cancer, it can improve the survival prediction of patients with liver cancer, and it will bring more effective treatment and confidence to the disease. In this paper, we chose a data that a real clinically diagnosed HCC patient was collected from a University of Coimbra and Coimbra Hospital in Portugal, and we separated the data into testing and training to predict the death of HCC and find out the key factors from the prediction model. The prediction model includes Decision Tree (DT), Support vector machine (SVM), and Logistic Regression (LR). The results of this paper showed that the G-means of the three modeling methods are 0.76 (LR), 0.72 (DT), and 0.68 (SVM). The best performance is logistic regression (LR), and find out the key factors that affect the survival rate of HCC include Aspartate transaminase (U / L), Age at diagnosis, and Alkaline phosphatase (U / L).
Inversion Framework: Reasoning about Inversion by Conditional Term Rewriting Systems

We introduce a language-independent framework for reasoning about program inverters by conditional term rewriting systems. These systems can model the three fundamental forms of inversion, i.e., full, partial and semi-inversion, in declarative languages. The correctness of the generic inversion algorithm introduced in this contribution is proven for all well-behaved rule inverters, and we demonstrate that this class of inverters encompasses several of the inversion algorithms published throughout the past years. This new generic approach enables us to establish fundamental properties, e.g., orthogonality, for entire classes of well-behaved full inverters, partial inverters and semi-inverters regardless of their particular local rule inverters. We study known inverters as well as classes of inverters that yield left-to-right deterministic systems; left-to-right determinism is a desirable property, e.g., for functional programs; however, at the same time it is not generally a property of inverted systems. This generic approach enables a more systematic design of program inverters and fills a gap in our knowledge of program inversion.
Notes on James River Chlorophyll Simulator and CFD validation

This project is to develop tools that will enable the estimation of false positive and false negative error rates for the procedure in place for assessing the numerical chlorophyll criteria in the tidal James River. The key tool is a computer simulation that creates chlorophyll data with spatial and temporal patterns that are typical of observed chlorophyll in the James River. This simulation makes it possible to create data on a dense spatial and temporal grid that covers an entire river segment for a three year assessment period. The state of this simulated data is known to be compliant or non-compliant with the numerical criteria. To test for an assessment error, a subset of data are sampled from the simulation with the same spatial and temporal frequency as ship-board sampling of the James River. The full assessment procedure is applied to this sub-sample of simulated data and the result of the assessment is compared to the known state of the simulation. If the assessment finds a result of non-compliance when it is known that the simulated data are compliant, this is a false positive error. If the assessment finds compliance when the known state is non-compliant, this is a false negative error. The rates for these errors are estimated by repeatedly sampling the simulated data and tabulating the results of the assessments. The proportion of errors observed in these repeated assessments estimates the error rate.
Relative Hyperlactatemia in the Emergency Department

Objective: The clinical interpretation of lactate ≤ 2.00 mmol/L in emergency department (ED) patients is not well-characterized. This study aims to determine the optimal cutoff value for lactate within the reference range that predicts in-hospital mortality among ED patients. Methods: This was a retrospective study of adult patients presenting to a tertiary ED with an initial serum lactate level of <2.00 mmol/L. The primary outcome was in-hospital mortality. Youden's index was utilized to determine the optimal threshold that predicts mortality. Patients above the threshold were labeled as having relative hyperlactatemia. Results: During the study period, 1,638 patients were included. The mean age was 66.9 ± 18.6 years, 47.1% of the population were female, and the most prevalent comorbidity was hypertension (56.7%). The mean lactate level at presentation was 1.5 ± 0.3 mmol/L. In-hospital mortality was 3.8% in the overall population, and 16.2% were admitted to the ICU. A lactate level of 1.33 mmol/L was found to be the optimal cutoff that best discriminates between survivors and non-survivors. Relative hyperlactatemia was an independent predictor of in-hospital mortality (OR 1.78 C1.18–4.03; p = 0.02). Finally, relative hyperlactatemia was associated with increased mortality in patients without hypertension (4.7 vs. 1.1%; p = 0.008), as well as patients without diabetes or COPD. Conclusion: The optimal cutoff of initial serum lactate that discriminates between survivors and non-survivors in the ED is 1.33 mmol/L. Relative hyperlactatemia is associated with increased mortality in emergency department patients, and this interaction seems to be more important in healthy patients.
Left Ventricular Hypertrabeculation Is Not Associated With Cardiovascular Morbity or Mortality: Insights From the Eurocmr Registry

Aim: Left ventricular non-compaction (LVNC) is perceived as a rare high-risk cardiomyopathy characterized by excess left ventricular (LV) trabeculation. However, there is increasing evidence contesting the clinical significance of LV hyper-trabeculation and the existence of LVNC as a distinct cardiomyopathy. The aim of this study is to assess the association of LV trabeculation extent with cardiovascular morbidity and all-cause mortality in patients undergoing clinical cardiac magnetic resonance (CMR) scans across 57 European centers from the EuroCMR registry. Methods and Results: We studied 822 randomly selected cases from the EuroCMR registry. Image acquisition was according to international guidelines. We manually segmented images for LV chamber quantification and measurement of LV trabeculation (as per Petersen criteria). We report the association between LV trabeculation extent and important cardiovascular morbidities (stroke, atrial fibrillation, heart failure) and all-cause mortality prospectively recorded over 404 ± 82 days of follow-up. Maximal non-compaction to compaction ratio (NC/C) was mean (standard deviation) 1.81 ± 0.67, from these, 17% were above the threshold for hyper-trabeculation (NC/C > 2.3). LV trabeculation extent was not associated with increased risk of the defined outcomes (morbidities, mortality, LV CMR indices) in the whole cohort, or in sub-analyses of individuals without ischaemic heart disease, or those with NC/C > 2.3. Conclusion: Among 882 patients undergoing clinical CMR, excess LV trabeculation was not associated with a range of important cardiovascular morbidities or all-cause mortality over ~12 months of prospective follow-up. These findings suggest that LV hyper-trabeculation alone is not an indicator for worse cardiovascular prognosis.