Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of DUACS Sentinel-3A Altimetry Data in the Coastal Band of the European Seas: Comparison with Tide Gauge Measurements

The quality of the Data Unification and Altimeter Combination System (DUACS) Sentinel-3A altimeter data in the coastal area of the European seas is investigated through a comparison with in situ tide gauge measurements. The comparison was also conducted using altimetry data from Jason-3 for inter-comparison purposes. We found that Sentinel-3A improved the root mean square differences (RMSD) by 13% with respect to the Jason-3 mission. In addition, the variance in the differences between the two datasets was reduced by 25%. To explain the improved capture of Sea Level Anomaly by Sentinel-3A in the coastal band, the impact of the measurement noise on the synthetic aperture radar altimeter, the distance to the coast, and Long Wave Error correction applied on altimetry data were checked. The results confirmed that the synthetic aperture radar altimeter instrument onboard the Sentinel-3A mission better solves the signal in the coastal band. Moreover, the Long Wave Error processing contributes to reduce the errors in altimetry, enhancing the consistency between the altimeter and in situ datasets.
Development of an Automated Visibility Analysis Framework for Pavement Markings Based on the Deep Learning Approach

Pavement markings play a critical role in reducing crashes and improving safety on public roads. As road pavements age, maintenance work for safety purposes becomes critical. However, inspecting all pavement markings at the right time is very challenging due to the lack of available human resources. This study was conducted to develop an automated condition analysis framework for pavement markings using machine learning technology. The proposed framework consists of three modules: a data processing module, a pavement marking detection module, and a visibility analysis module. The framework was validated through a case study of pavement markings training data sets in the U.S. It was found that the detection model of the framework was very precise, which means most of the identified pavement markings were correctly classified. In addition, in the proposed framework, visibility was confirmed as an important factor of driver safety and maintenance, and visibility standards for pavement markings were defined.
Data Fusion Using a Multi-Sensor Sparse-Based Clustering Algorithm

The increasing amount of information acquired by imaging sensors in Earth Sciences results in the availability of a multitude of complementary data (e.g., spectral, spatial, elevation) for monitoring of the Earth’s surface. Many studies were devoted to investigating the usage of multi-sensor data sets in the performance of supervised learning-based approaches at various tasks (i.e., classification and regression) while unsupervised learning-based approaches have received less attention. In this paper, we propose a new approach to fuse multiple data sets from imaging sensors using a multi-sensor sparse-based clustering algorithm (Multi-SSC). A technique for the extraction of spatial features (i.e., morphological profiles (MPs) and invariant attribute profiles (IAPs)) is applied to high spatial-resolution data to derive the spatial and contextual information. This information is then fused with spectrally rich data such as multi- or hyperspectral data. In order to fuse multi-sensor data sets a hierarchical sparse subspace clustering approach is employed. More specifically, a lasso-based binary algorithm is used to fuse the spectral and spatial information prior to automatic clustering. The proposed framework ensures that the generated clustering map is smooth and preserves the spatial structures of the scene. In order to evaluate the generalization capability of the proposed approach, we investigate its performance not only on diverse scenes but also on different sensors and data types. The first two data sets are geological data sets, which consist of hyperspectral and RGB data. The third data set is the well-known benchmark Trento data set, including hyperspectral and LiDAR data. Experimental results indicate that this novel multi-sensor clustering algorithm can provide an accurate clustering map compared to the state-of-the-art sparse subspace-based clustering algorithms.
Hydrogen as a Donor in Zinc Oxide

Hydrogen is found to diffuse into and increase the conductivity of single ZnO crystals. The diffusion rates have been obtained, as well as the temperature and pressure dependencies of the quantity of hydrogen in the crystal. This quantity is found to be influenced by the electrons already in the crystal. It is thought likely that hydroxyl groups are formed from the hydrogen and oxide ions. The donor center has an ionization energy of 0.04 ev.
Estimation of the RP-HPLC Lipophilicity Parameters Log K', and Log KW, A Comparison with the Hydrophobicity Index ϕ0 †

Abstract Chromatographic retention parameters k' and kW were determined by RP-HPLC for a set of standard non-congeneric compounds and the correlation with log Po/W established. Then, log Po/W was calculated for a series of antimicrobial hydrazides, as a test set. A comparison of the chromatographic parameters log k' and log KW with the hydrophobicity index ϕ0 were also made. It seems that for the study compounds, log KW describes the partitioning better than the parameter ϕ0. †Work presented at the International Symposium on Lipophilicity and Toxicology, Lausanne, Switzerland, 21–24 March, 1995.
Lane Detection for Driverless Vehicle: A Survey

Under the intelligent transportation system, the driving of unmanned vehicles depends on lane keeping. Lane keeping technology, as one of the core technologies of smart cars and an important guarantee of driving safety, has gradually attracted public attention. In actual driving, the detection of lane is the core of its control thought, and there are many methods. Lane detection is regarded as the core requirement for the development of each intelligent transportation system. The extracted lane information can be used in a variety of intelligent applications to avoid collisions with other vehicles. In our work, we mainly study the lane detection from the two mainstream methods of traditional image processing and deep learning, summarize the main functions and existing problems of the two methods, and look forward to the direction worth studying in the future.
The Kapustin-Li formula and the evaluation of (closed) sl(N)-foams

This notes intended to supplement a talk given by the author at the Institut de Mathématiques de Jussieu Université Paris 7 in January 2010. The purpose of the talk was to give an explanation of the use of Kapustin-Li formula in the evaluation of the closed foams used in the construction of the sl(N)-link homology. This notes contains material from the author’s PhD thesis [17] as well as the explanation and the proof of some facts about the Kapustin-Li formula that were omitted from [11].
EM Injection Vs. Modern CPU Fault Characterization And AES Differential Fault Analysis

Recently, several Fault Attacks (FAs) targeting modern Central Processing Units (CPUs) have emerged. These attacks are studied from a practical point of view and, due to the modern CPUs complexity, the underlying fault effect is usually unknown. In this article, we focus on the characterization of a perturbation (the fault model) on a modern CPU. For that, we explain an approach to characterize the fault model on modern CPU from the assembly instruction level to the micro-architectural level. This fault model helps at determining which micro-architecture elements are disrupted and how. The fault model determination aims at ﬁnding original attack paths and design efﬁcient countermeasures. To confront our approach to real modern CPUs, we apply our approach on a Raspberry Pi 3 CPU on which the determined fault model is reused to corrupt an AES implementation.
Perspective-Taking for Policy-Making: An Analysis of Canadian Cross-border Shopping

ISSN: 0971-1023 | NMIMS Management Review Volume XXXIV | Issue 2 | August 2017 ISSN: 0971-1023 | NMIMS Management Review Volume XXXIV | Issue 2 | August 2017 Perspective-Taking for Policy-Making: An Analysis of Canadian Cross-border Shopping Perspective-Taking for Policy-Making: An Analysis of Canadian Cross-border Shopping Abstract Research plays an essential role in policy analysis and is a significant tool used to identify and prioritize alternatives for intervention. Yet public policy problems have a reputation for being complex because one problem (i.e. shopping behavior) can be viewed as part of a larger set of issues (i.e. trade policies, tax policy, border security, monetary policy, etc.). Accordingly, policy makers need research tools that allow them to understand how the system works. This research demonstrates a method for developing systems-level conceptual frameworks to support policy decision-making. Using archival techniques used by historical researchers in journalism, a 26-year period of news coverage of the cross-border shopping phenomenon in Canada has been conducted. Content assessment and content analysis methods are used to compare levels of topic visibility over time, exposing important changes in the landscape of cross-border shopping. The case study demonstrates how to use media coverage to develop integrative frameworks to organize issue topics, positions and policy options. Impl icat ions for pub l i c po l i cy mak ing and implementation are discussed along with study limitations and opportunities for future research.
Motor competence and social function in children with autism spectrum disorder

Motor and social competence are delayed in children with autism spectrum disorder (ASD). Social interaction and functional physical capacity play an important role for developing peer relationships in school settings such as gym, playground, and classroom. Research on the delayed motor competence in relationship to poor social interaction in children with ASD is limited. The purpose of the study was to examine motor competence and social skills functioning in children with ASD. A sample of 23 children diagnosed with ASD participated in the study. Bruininks-Oseretsky Test of Motor Proficiency-II (BOT-2) was used to examine children’s motor competence and Autism Social Skill Profile (ASSP) survey was given to parents to assess children’s social skills functioning. The descriptive analysis revealed that 87% of the children with ASD were classified as below average or well below average category in BOT-2 suggesting the children with ASD were delayed in motor competence. In addition, 52% of the children were ranked at or below 50th percentile on the ASSP indicating that they had poor social skill functioning. A significant positive correlation was found between BOT-2 and ASSP revealed that children with ASD who performed poorly in BOT-2 also scored low in ASSP. These findings suggest that including fine and gross motor skills in the treatment interventions for children with ASD may improve their health-related wellbeing and maintain positive socialization.
Relationship between plasma concentrations of estradiol-17β and progesterone and the distribution of epithelial and inflammatory cells in the external opening of the river buffaloes’ uterine cervix during the gestational period

Changes in the distribution of the epithelial and inflammatory cells in the external opening of the uterine cervix in river buffaloes at three different occasions during the gestation period were investigated by light microscopic evaluation of mucus smears prepared by wet swab sampling and Giemsa-stained. Forty five pregnant river buffaloes that were in the first (n=15), second (n=15) and third (n=15) approximately equal parts of their gestation period were sampled twice concurrently by individual wet swabs from the external opening of the uterine cervix. Five smears were prepared from each sample. Immediately after mucus sampling, blood samples were obtained from the jugular vein of each animal, centrifuged immediately and stored at -20 oC to assay the plasma levels of estradiol-17β and progesterone. The results showed that changes in the percentage of the vacuolated and non-vacuolated epithelial cells, lymphocytes, eosinophils, and basophils were not statistically significant between the groups, which suggests that as the pregnancy progressed, changes in the blood levels of estradiol-17β and progesterone had little or no effect on the distribution of these cells in the region, but changes in the percentage of neutrophils were statistically significant between the groups. It was also found that changes in the percentage of macrophages between the second and third trimesters of the gestation period were not significant, but the difference between the first and the other trimesters was statistically significant. It was concluded that the percentages of neutrophils and macrophages increase significantly as the plasma concentrations of progesterone decrease during the gestation.
HOW TO MANAGE LEARNING TENSIONS IN COOPETITION? THE ROLE OF INFORMATION SYSTEMS

We examine how firms implement specific tools to manage learning tensions in a coopetitive setting. Considering information as a key resource for firms, coopetitors balance between sharing information for the success of the project and protecting information to sustain their competitive advantage. Setting our analysis at an operational level, we stress on the central role of information systems in the management of learning tensions. Drawing from an in-depth case study in the European space industry, we contribute to the existing literature on the management of coopetition by offering a more empirical vision of the issues met by coopetitors. More precisely, we draw lessons on the design of the coopetitive IS at different levels. First, we analyze the structure of the IS and its position within the organization of the partners. We then define the information to be shared in a coopetitive agreement and finally model the structure of a coopetitive information system.
SERVQUAL Reliability and Validity: A Pilot Study to Evaluate Patients' Satisfaction in the Jordanian Hospitals

[Abstract] Like developed nations, the developing world strives for assuring high standards of healthcare services. To meet this demand, healthcare providers have begun their quest for services improvement using process re-engineering. This paper is a part of major research and documents the finding of a cross-sectional pilot study conducted in Jordan to check the reliability and validity of a patient satisfaction model, SERVQUAL. The study covers a sample of 50 patients who have visited the Emergency Department, ED, of hospitals in Amman and Irbid, Jordan. The pilot study also determines the different dimensions of the service quality in Jordanian hospitals and evaluates the service quality from the patients’ perspective. The study concluded that, overall, the SERVQUAL questioner is reliable but not valid. The sub-scale of the questioner does not possess adequate reliability, except responsiveness for the perceived service quality. The study recommends modifying the number of dimensions in SERVQUAL before implementing it on a larger scale and using a shorter instrument.
A survey on ECG Beat Classification

: ECG is used for identifying various diseases present in the heart. For curing these diseases, the first step is to classify the ECG beats. The computer based machine learning techniques are not only used for classifying the ECG beats but also increases the doctor’s efficiency which further improves the diagnostic accuracy. Thus, in this paper the review of ECG beat classification is presented. It is concluded that after detecting the irregularities present in the heart by using ECG beat classification methods, the better healthcare services can be provided. An accurate ECG beat classification is quite challenging task which provides useful information for detecting the heart diseases as well as helping the doctors for providing best diagnosis.
Comparison of the efficiency of methods and selective agars for enumerating Vibrio parahaemolyticus in shrimps

Vibrio parahaemolyticus is a major food borne pathogen that causes rejection of tiger shrimps (Penaeus monodon) consignments at the export market. It was artificially inoculated into tiger shrimps and recovery was evaluated by using nine standard procedures incorporating most probable number (MPN) method or direct plating and four selective agars. The enrichment step in alkaline salt peptone water (ASPW) and 20 h direct plating on thiosulfate citrate bile salts sucrose (TCBS) agar gave the highest recovery (76.9%) of V. parahaemolyticus in shrimps and followed by primary and secondary enrichment steps in alkaline peptone water (APW) using MPN method (71.5%). V. parahaemolyticus was not recovered in salt polymyxin broth (SPB) using either direct plating or MPN. Three tube MPN method using enrichment media ASPW and APW gave recoveries of 64.2% and 62.1% respectively. The enrichment in glucose salt teepol broth (GSTB) using MPN method resulted in 57.9% recovery whereas it was 24.7% in saline glucose sodium dodecyl sulphate peptone water (GST). The recovery in GST using direct plating was 50.4%. ASPW and APW with double enrichment steps are recommended as the most superior enrichments for enumeration of V. parahaemolyticus in tiger shrimps using direct plating and MPN method respectively. The differences observed among four selective media namely TCBS, triphenyl tetrazolium soya tryptone agar (TSAT), sodium dodecyl sulphate polymyxin sucrose agar (SDS) and CHROM agar Vibrio (CV) for enumerating V. parahaemolyticus were not significant (p>0.05).
Groundwater Geochemistry of Nile Delta-Desert Interface l.Isotope Hydrology

Sustenance and environmental protection of groundwater supply is of major concern in the integral environmental development in the arid to sub-arid regions in the Nile basin. Isotope data (O, H and H) of groundwater in the west of the Nile Delta indicates the contribution of palaeo groundwater component (in the range 0.1 0.8 with means of 0.39 and 0.52 for Tahrir and Khatatbah, respectively) along with subrecent recharge from the delta aquifer and recent recharge from irrigation conveyance canals in desert. Isotope mixing model (developed as Two-input Table using ExcelTM spreadsheat on Apple MacintoshTM) is proposed to explain the apparent discrepancies in groundwater isotopic composition of Khatatbah and Tahrir areas assuming the contribution of two isotopically different palaeo-poles with two isotopically similar main delta groundwater poles. About 0.30%c 8O depletion per 10 km downstream is detected and low northward groundwater recharge is suggested along 75 km of the Western Strip of Rosetta Nile. Higher sub-recent recharge from the main Delta aquifer is believed to take place in Khatatbah than Tahrir whereas the last is believed to be replenished at present from the irrigation/ drainage network and irrigated fields with higher pollution risk for groundwater system in Tahrir. Behira aquifer is exposed to northern marine intrusion. Lowering of the piezometric level is to be expected in the newly exploited desertic areas under overpumping. Palaeo-hydrology of the studied region requires intensive isotopic monitoring to further delineate fossil/ renewable groundwater relations for rational environmental water management in the region.
MOTIVES FOR SHARING IN SOCIAL NETWORKS ETHAN LIGON AND LAURA SCHECHTER

What motivates people in rural villages to share? Using variants of dictator games we measure two preference-related motives for sharing (benevolence and directed altruism), and two incentive-related motives (sanctions and reciprocity). Most sharing in the experiment can be explained by benevolence, but variation in sharing is explained more equally by the two classes of motives. Finally, variation in sharing within the experiment is correlated with observed ‘real-world’ gift-giving, while other motives measured in the experiment don’t seem to be useful in predicting behavior outside the experiment. JEL codes: C92, C93, D03, D64, D85, O17.
ANALYSIS OF AN INTENSE OUTBREAK OF SAHARAN DUST IN THE APULIA REGION: COMPARISON BETWEEN THE WRF-CHEM MODEL AND MULTI-PLATFORM EXPERIMENTAL DATA

In this study, the Weather Research and Forecasting model with online coupled chemistry (WRF-Chem) is applied to simulate an intense Saharan dust outbreak event that took place over the Southern Italy in March 2016. The WRF model is found to reproduce well the synoptic meteorological conditions driving the dust outbreak: an omegalike pressure configuration associated with a weak cyclogenesis in the Iberian Peninsula. At the end of the simulated period the merging of two minima produce a large depression in the Peninsular Italy. The model performances in reproducing the atmospheric desert dust load is evaluated using a multi-platform observational dataset of aerosol and desert dust properties, including optical properties from satellite and ground-based sun-photometers, plus in-situ particulate matter mass concentration (PM) data. This comparison allows us to investigate the model ability in reproducing both the horizontal and the vertical displacement of the dust plume, and its evolution in time. The preliminary comparison with satellite (MODIS-AQUA) and sunphotometers (AERONET) showed that the model is able to reproduce well the horizontal field of the aerosol optical depth (AOD) and its evolution in time. The routinely measurements of ARPA-Puglia revealed the intense dust outbreak with peak PM10 value larger than 300 μg/m during march 23. On the other side, the model-measurements comparison for PM10 shows a good temporal matching. The model-to-measurements comparisons allows the evaluation and the tuning of physics-based emission scheme that is part of the WRF-Chem package release.
Synthesis and characterization of diethynylmethanobuckminsterfullerene, a building block for macrocyclic and polymeric carbon allotropes

Diethynylmethanobuckminsterfullerene has been prepared by reaction of the lithium salt of 1,5-bis(trimethylsilyl)-1,4-pentadiyn-3-one (p-toluenesulfonyl) hydrazone with C{sub 60} followed by desilylation. The derivative was structurally characterized by NMR, IR, UV-vis, and CI-TQMS spectroscopies.
Properties of ibuprofen ion-selective electrodes based on the ion pair complex of tetraoctylammonium cation

Ibuprofen membrane electrodes based on different plasticizers: diisobutyl phthalate (DIBP), o-nitrophenyloctyl ether (o-NPOE), dioctyl sebacate (DOS) and tetraoctylammonium 2-(4-isobutylphenyl)propionate were prepared. All electrodes show: a near Nernstian slope of characteristic (58.3–60.9 mV decade−1) in the measurement range (10−4–10−1 mol L−1), limit of detection (5.0×10−5 mol L−1), really long lifetime (12 months), dependence of the electrode potential on pH (5.5–9.0), reproducibility of potential (0.6–1.2 mV) and selectivity coefficients in relation to some organic and inorganic anions. The electrodes were applied for the determination of ibuprofen in tablets by the calibration curve method and the standard addition method.