Miracle-dz/UniFAR-FTUs huggingface dataset:
HYDROGEOLOGICAL MAPPING IN THE SEMI-ARID ENVIRONMENT OF EASTERN JORDAN USING AIRBORNE MULTIPOLARIZED RADAR IMAGES

This study focuses on the information content of HH, VV, VH and HV polarized airborne SAR data to evaluate which of these polarizations is more appropriate to facilitate mapping of lineaments and detailed drainage of wadis. It is known that a good knowledge of surficial lineaments and drainage network can help to locate wells and surface water retention dams used for groundwater recharge. The study area is located near the village of Azraq in the semi-arid environment of Eastern Jordan. In Jordan, water availability is a very acute problem as the demand is increasing and reserves are decreasing. A large amount of the water has always been obtained from deep wells but now, the rate of pumping exceeds the rate of replenishment. Additionally, the salinity is getting to a level where it is unsuitable for consumption. The area receives an average of 50 mm of rain a year mostly between October and March. Natural vegetation is very scarce and survives only in the temporary river channels. Since vegetation is very scarce, the water is rapidly evacuated and recharge of the underground water table is minimal. The area has a flat topography with slight depression enabling drainage during the “rainy” season. We use a set of airborne Synthetic Aperture Radar (SAR) images of Eastern Jordan obtained from a survey flown in 1993, as part of the Canada Centre for Remote Sensing’s GlobeSAR-1 project. All images were analyzed in order to enhance a maximum of hydrogeological information. Results show that the crossed polarizations images (HV or VH) and to a lesser extent, the HH like polarization images show a good contrast and enough details to permit hydrographic network mapping in the wadi (dry river beds) where a minimum of vegetation is available. The VV polarization is not as sensitive to vegetation presence but permits a better positioning of the wadi banks and is useful to map roughness variations within playas.
Specifications of thermal waters and their classification on the base of neural network method: Examples from Simav geothermal area, Western Turkey

Western Turkey is one of the best known geothermal fields in Turkey. There are numerous geothermal energy plants (for example Kizildere, Nazilli, Hidirbeyli, Balcova, Tuzla) in Aegean region, Western Turkey. Simav geothermal field is located within the Aegean Graben System in Western Anatolia. Rock units in the study area are mainly the formation of Menderes Massive. The Simav geothermal waters were divided into four types: (1) Eynal, (2) Citgol, (3) geothermal water and (4) cold water. In this study, we aimed to introduce a method for classifying waters in the study area using some parameters such as temperature, pH, electrical conductivity and major ions by means of Artificial Neural Network (ANN) method. The data at hand obtained from wells indicate that the drilled water can be used for drinking and irrigation, the data also reveals that the ground water flows towards the desiccated lake. The cold water analysis gave high CO3+HCO3, Ca, Mg ion values, and low NH4, NO3, Fe, NO2, Al and Mn ion values. On the other hand, the hot water analysis indicate that a cation trend of Na+K>Ca>Mg and an anion trend of HCO3+CO3>SO4>Cl. While preparing the training data set in ANN method, for input, T (°C), EC (mS), pH, Na (mg/l), K (mg/l), Ca (mg/l), Mg (mg/l), CO3 (mg/l), HCO3 (mg/l), Cl (mg/l) and SO4 (mg/l) values of 50 water samples from the study area were used. Four output values were used. In each output value, the known water was represented by 1 and others by 0. A test data set of 15 samples in which the T, EC, pH, Na, K, Ca, Mg, CO3, HCO3, Cl and SO4 values are known but their group are unknown was prepared. And these input values were run in ANN model in order to see how the waters were grouped. The advantages of artificial neural networks can be exploited to solve this problem. The most common ANN architecture is Multilayered Perceptrons, which was used in this study. For this solution, the first artificial neural network model using Extended Delta-Bar-Delta (EDBD) algorithm has been successfully implemented. Mean Square Error result of these model obtained by EDBD algorithm is 1.3x10–3. These results show that the group in which the waters in the study area fall can be determined with high accuracy by using some parameters of water such as the ion content of water. Key words: Geothermal waters, chemistry, hydrology, Artificial Neural Network (ANN), Simav, Turkey.
Collaborative rule generation: An ensemble learning approach

Due to the vast and rapid increase in data, data mining has become an increasingly important tool for the purpose of knowledge discovery in order to prevent the presence of rich data but poor knowledge. Data mining tasks can be undertaken in two ways, namely, manual walkthrough of data and use of machine learning approaches. Due to the presence of big data, machine learning has thus become a powerful tool to do data mining in intelligent ways. A popular approach of machine learning is inductive learning, which can be used to generate a rule set (a set of rules) using a particular algorithm. Inductive learning can involve a single base algorithm learning from a single data set following a standard learning approach. In this approach, the learning algorithm can generate a single rule set such as decision trees. On the other hand, the inductive learning can also involve a single base algorithm learning from multiple data sets following an ensemble learning approach. In this approach, the learning algorithm can generate multiple rule sets such as random forests. The latter approach is usually designed to reduce overfitting of models that usually arises when the former approach is adopted. In this context, the ensemble learning approach usually enables the improvement of the overall accuracy in prediction. The aim of this paper is to introduce a new approach of ensemble learning called Collaborative Rule Generation. In the new approach, the inductive learning involves multiple base algorithms learning from a single data set to generate a single rule set, which aims to enable each rule to have a higher quality. This paper also includes an experimental study validating the Collaborative Rule Generation approach and discusses the results in both quantitative and qualitative ways.
A study of candidate marine target impact craters in Arabia Terra, Mars

Abstract– Previous workers have proposed that a northern ocean existed early during Martian geologic history and the shorelines of that ocean would coincide roughly with the crustal dichotomy that divides the smooth, northern lowlands with the cratered, southern highlands. Arabia Terra is a region on Mars that straddles the crustal dichotomy, and several proposed shorelines are located in the area. Shallow marine impact craters on Mars likely would exhibit features like those on Earth, including characteristic morphological features that are distinctly different from that of craters formed on land. Common attributes of terrestrial marine impact craters include features of wet mass movement such as gravity slumps and debris flows; radial gullies leading into the crater depression; resurge deposits and blocks of dislocated materials; crater rim collapse or breaching of the crater wall; a central peak terrace or peak ring terrace; and subdued topography (an indicator of both age and possible flood inundation immediately following impact). In this article, these features have been used to evaluate craters on Mars as to a possible marine origin. This study used a simple quantification system to approximately judge and rank shallow marine impact crater candidates based on features observed in terrestrial analogs. Based on the quantification system, 77 potential shallow marine impact craters were found within an area bounded by 20°N and 40°N as well as 20°W and 20°E. Nine exemplary candidates were ranked with total scores of 70% or more. In a second, smaller study area, impact craters of approximately similar size and age were evaluated as a comparison and average total scores are 35%, indicating that there is some morphological difference between craters inside and outside the proposed shorelines. Results of this type of study are useful in helping to develop a general means of classification and characterization of potential marine craters.
Quantitative methods for comparing featural representations

The basic representational hypothesis in phonology is that segments are coded using a universal set of discrete features. We propose a method for quantitatively measuring how well such features align with arbitrary segment representations. We assess articulatory, spectral, and phonotactic representations of English consonants. Our procedure constructs a concrete representation of a feature in terms of the pairs it distinguishes, and can be extended to any pair of representations to test the consistency of one with the individual dimensions of the other. We validate the method on our phonetic representations and then show that major natural classes are not well represented in the surface phonotactics.
Ubiquitous learning analytics in the context of real-world language learning

This paper describes a method of the visualization and analysis for mining useful learning logs from numerous learning experiences that learners have accumulated in the real world as the ubiquitous learning logs. Ubiquitous Learning Log (ULL) is defined as a digital record of what learners have learned in the daily life using ubiquitous technologies. It allows learners to log their learning experiences with photos, audios, videos, location, RFID tag and sensor data, and to share and reuse ULL with others. By constructing real-world corpora which comprise of accumulated ULLs with information such as what, when, where, and how learners have learned in the real world and by analyzing them, we can support learners to learn more effectively. The proposed system will predict their future learning opportunities including their learning patterns and trends by analyzing their past ULLs. The prediction is made possible both by network analysis based on ULL information such as learners, knowledge, place and time and by learners' self-analysis using time-map. By predicting what they tend to learn next in their learning paths, it provides them with more learning opportunities. Accumulated data are so big and the relationships among the data are so complicated that it is difficult to grasp how closely the ULLs are related each other. Therefore, this paper proposes a system to help learners to grasp relationships among learners, knowledge, place and time, using network graphs and network analysis.
Incidence, Predictors, and Clinical Outcomes of New-Onset Diabetes Mellitus after Percutaneous Coronary Intervention with Drug-Eluting Stent

We investigated the incidence, predictors, and long-term clinical outcomes of new-onset diabetes mellitus (DM) after percutaneous coronary intervention (PCI) with drug-eluting stent (DES). A total of 6,048 patients treated with DES were retrospectively reviewed and divided into three groups: 1) known DM (n = 2,365; fasting glucose > 126 mg/dL, glycated hemoglobin > 6.5%, already receiving DM treatment, or previous history of DM at the time of PCI); 2) non-DM (n = 3,247; no history of DM, no laboratory findings suggestive of DM at PCI, and no occurrence of DM during follow-up); and 3) new-onset DM (n = 436; non-DM features at PCI and occurrence of DM during follow-up). Among 3,683 non-DM patients, 436 (11.8%) patients were diagnosed with new-onset DM at 3.4 ± 1.9 years after PCI. Independent predictors for new-onset DM were high-intensity statin therapy, high body mass index (BMI), and high level of fasting glucose and triglycerides. The 8-year cumulative rate of major adverse cardiac events (a composite of cardiovascular death, myocardial infarction, stent thrombosis, or any revascularization) in the new-onset DM group was 19.5%, which was similar to 20.5% in the non-DM group (P = 0.467), but lower than 25.0% in the known DM group (P = 0.003). In conclusion, the incidence of new-onset DM after PCI with DES was not low. High-intensity statin therapy, high BMI, and high level of fasting glucose and triglycerides were independent predictors for new-onset DM. Long-term clinical outcomes of patients with new-onset DM after PCI were similar to those of patients without DM.
A compact compliant actuator (CompAct™) with variable physical damping

The new areas of technical exploitation of robotics systems has recently set new trends for the robotic actuation by demanding more versatile systems which can cope with unpredictable interactions within not well defined environments and work in close vicinity with the human. Following these trends, this work presents the development of a new actuation system with embodied characteristics such as passive compliance and variable physical damping. Compared to the other existing compliant linear or rotary actuators the proposed CompAct unit has the ability to regulate the oscillations induced by the introduction of the compliance by means of a variable physical damping actuator (VPDA) unit. Apart from facilitating the control the VPDA unit can assist in managing the energy transfer from/to the compliant module. The mechatronics, model and control scheme of the CompAct are analysed. The overall system is evaluated with experimental trials performed using a prototype unit. Preliminary results are presented to show that the unit and the proposed control scheme are capable of regulating the impedance components (stiffness and damping) within a wide range and with good fidelity.
Origin of C2-C5 dicarboxylic acids in the European atmosphere inferred from year-round aerosol study conducted at a west-east transect

[1] An atmospheric study of C 2 -C 5 dicarboxylic acids was conducted over two years at seven sites located from the Azores to eastern continental European sites. The lowest concentrations of total C 2 -C 5 diacids are observed at the Azores (Portugal) and at 4360 m elevation in the Alps (∼50 ng m -3 ), and the highest (400 ng m -3 ) are observed at the rural K-puszta site (Hungary). Quasi-absent at surface sites, the seasonal cycle of total diacids is characterized by a pronounced summer maximum at elevated sites, the highest summer level (510 ng m -3 ) being observed at the forested mountain site of Schauinsland (Germany). Whatever site and season, oxalic acid is always the most abundant diacid with a relative abundance higher than 60%. The climatology of C 2 -C 5 diacids in Europe is discussed versus environmental conditions at sites (marine/ continental, rural/forested, boundary layer/free troposphere, and winter/summer). Observations are used to discuss the possible sources of C 2 -C 5 diacids, with special emphasis on their primary versus secondary and natural versus anthropogenic origin. At surface sites in winter, fast secondary productions in wood burning plumes in addition to secondary production from volatile organic carbon (VOC) species emitted by vehicles seem to be important contributors. In summer the impact of anthropogenic sources is weakened and biogenic emissions from vegetation (unsaturated fatty acids, isoprene, oxygenated VOCs, and eventually monoterpenes) likely represent major precursors of diacids. At the Azores, diacids are not only related to long-range transport from continents but also to marine biogenic emissions from phytoplankton, particularly in summer.
YOLO-SPD: Tiny objects localization on remote sensing based on You Only Look Once and Space-to-Depth Convolution

Detecting tiny objects in remote sensing images presents a significant challenge, especially moving vehicles or ships smaller than $32 \times 32$ pixels. This paper uses Space-to-depth Convolution (SPD-Conv), an architecture design to increase feature extraction of tiny objects. Additionally, the proposed network adopts four detection heads to enhance the tiny object bounding boxes. Compared to the baseline model the proposed network increases by 14.3% of Average Precision at 50% intersection over union (AP50).
Evaluation of Dynamic Weight Threshold Algorithm for WIM Operations using Simulation

In the past decades, states have utilized weigh-in-motion (WIM) technology to reduce delay and increase enforcement of overweight vehicles. Usually a threshold value is used to filter and sort the trucks by weight. If the WIM reading of a truck is over the threshold, the truck would be sent to a static scale for further inspection. To fully utilize the WIM technology and enhance the operational efficiency at WIM sites, the authors devised a dynamic weight threshold (DWT) algorithm. The threshold value is increased when the queue at the weigh station is long so as to avoid the closure of the weigh station while still catch the worst weight limit offenders. The threshold value is lowered when the queue at the station is short to maximize the number of trucks inspected. This paper focuses on the evaluation of the design and operations of the dynamic weight threshold algorithm. A microscopic simulation model based on a real-world ramp WIM weigh station site was first developed and calibrated. Subsequently the dynamic threshold adjustment strategy was modeled and tested. The results show that under a wide range of conditions DWT algorithm always outperforms the traditional static threshold operations. Under heavy demand conditions, DWT catches 16 times more overweight trucks than the static operations while keeping the average delay per truck at only 30% of the delay under static operations. In other words, DWT is both more effective in weight enforcement and more efficient for traffic flow.
Early versus Delayed Therapy of Advanced Gastric Cancer Patients - Does It Make a Difference?

Background: Nearly 50% of gastric cancer patients are diagnosed with advanced gastric cancer (AGC). Therapy is palliative but results in ill effects. The median overall survival (OS) of AGC patients is often <12 months. It is unclear if the early initiation of therapy in all AGC patients is beneficial. Methods: A retrospective analysis of AGC patients in our database was carried out. The patients were divided into two groups: asymptomatic or symptomatic. We sought to assess whether the delay of systemic therapy was harmful in asymptomatic patients. Results: A total of 135 patients were analyzed. Most patients were symptomatic (68%), males (67%), and had low ECOG scores (0-1; 85%). In univariate analyses, ECOG performance status 0 (p = 0.005), delayed initiation of therapy (p = 0.03), and lack of symptoms (p = 0.03) were associated with a longer OS. The multivariate model for OS identified only ECOG performance status as an independent prognosticator of longer OS (p = 0.02). Asymptomatic patients who had delayed (≥4 weeks) systemic therapy had an OS rate of 77% at 1 year compared to 58% for patients treated within 4 weeks (p = 0.47). Conclusion: Symptomatic AGC patients had a poor outcome compared to asymptomatic AGC patients. Treatment delay in asymptomatic patients had no detrimental effect on OS, suggesting that the timing of therapy can be based on patient selection.
Authoring Large Hypermedia Documents with IGD

SUMMARY The IGD (Interactive Graphical Documents) hypermedia system was designed to make possible interactive presentations that can be explored by and customized for individual users. We describe IGD’s authoring facilities through an annotated excerpt from an editing session, emphasizing how the system’s document model and user interface help support the creation of large documents. Although we feel that IGD successfully addressed some of the issues of scale, experience with the system has convinced us that it is wrong to cast many of the problems of authoring large hypertexts as ones that can be solved by implementing editors of sufficient scope and sophistication. We believe that hypertext design systems based on direct editing of documents inherit many of the bottlenecks associated with the conventional document authoring process. These problems are compounded by the added intellectual burden of designing a connective structure of keyworded links. We contrast the reality of the author-centered, editor-based approach to document design and layout, exemplified by IGD, with the promise of a knowledge-based, automated alternative, and discuss why we feel that many of the facilities provided by IGD will still be useful even if presentations can be created entirely automatically.
Storm depth‐area relations from digitized radar returns

The point-derived precipitation frequency values depicted on maps must be converted to areal values for engineering and design work. Sparsity of data for quantifying this relation will be overcome as the National Weather Service implements its program to digitize radar return at its primary radar sites. A prototype project converts digitized radar data to precipitation. By averaging precipitation thus derived over discrete area sizes, depth-area reduction curves are derived. While the data sample is presently very limited, this prototype can be applied to the expected accumulation of data from the future National Weather Service operational program.
Effects of chronic administration of sibutramine on body weight, food intake and motor activity in neonatally monosodium glutamate-treated obese female rats: relationship of antiobesity effect with monoamines.

When the hypothalamic ventromedial nucleus and arcuate nucleus were destroyed in rats by treatment with monosodium glutamate in the neonatal stage, increase in the Lee index (body weight 1/3/body length) and in retroperitoneal fat as well as decreases in spontaneous motor activity, food consumption and growth hormone secretion function associated with hypothalamic low body length obesity (monosodium glutamate-treated obesity; MSG-OB) were observed as these rats grew. Treatment with sibutramine at 3 and 10 mg/kg p.o. once a day continuously for 14 days improved these parameters, and the degree of improvement was dose related. The plasma lipid values in MSG-OB rats, which were the same as those in normal rats, were decreased by consecutive administration of sibutramine. Levels of hypothalamic monoamines (MAs) such as norepinephrine, 5-HT (serotonin) and dopamine and their metabolites DOPAC, HVA and 5-HIAA were decreased in MSG-OB rats, and further decrease in them, though slight, was observed with consecutive daily administration of sibutramine, probably as a result of the feedback attributable to an increase in MA in synapses caused by inhibition of MA uptake by sibutramine. These results suggest that sibutramine can activate the MA nervous system by MA uptake inhibition in regions of the brain such as the lateral hypothalamic area and the paraventricular nucleus, which control food intake and sympathetic nerve activity, and the nigrostriatal area related to the extrapyramidal motor system, and thereby exhibit anti-obesity effects in the MSG-OB rat.