Miracle-dz/UniFAR-FTUs huggingface dataset:
DISEASE DIAGNOSIS FROM ECG SIGNALS BASED ON OPTIMIZING INDEPENDENT COMPONENT ANALYSIS USING GENETIC ALGORITHM

The examination of the ECG can benefit in diagnosing the greater part of the heart illness. The electrocardiogram (ECG) gives all data about electrical action of the heart. Changes in the typical beat of a human heart may bring about various cardiovascular arrhythmias, which might be quickly deadly or make hopeless harm to heart managed over drawn out stretches of time. The capacity to automatically recognize arrhythmias, for example, diabetics and blood pressure from ECG chronicles is critical for clinical analysis and treatment. The fundamental goal is to think of a straightforward strategy having less computational time without bargaining with the proficiency. This paper proposes an improved strategy for the arrhythmia classification and extraction of parameters from the ECG signal which is utilized for information gathering and classification framework. Principal component analysis (PCA) is utilized to diminish dimensionality of electrocardiogram (ECG) information proceeding for performing Independent component analysis (ICA). A recently proposed PCA change estimator by the author has been connected for distinguishing true, actual and false peaks of ECG information files. In this paper, it is felt that the capacity of ICA is also checked for parameterization of ECG signals, which is essential on occasion. Independent components (ICs) of appropriately parameterized ECG signals are more promptly interpretable than the estimations themselves, or their ICs. The original ECG recordings and the samples are organized by statistical measures to evaluate the noise statistics of ECG signals and discover the recreation errors. The capacity of ICA is clarified by finding the true, false and actual peaks of private hospital database ECG files. The preprocessed dataset is then classified utilizing machine learning algorithm named Genetic algorithm. The GA is qualified in improving the weights of the ICA, The genetic algorithm is used as a co-training algorithm for enhancing the connection weights values and minimizing the error value to least possible value. This method has demonstrated a decent outcome and a decent execution. Utilizing AI in examining the ECG signal has sparing time, quicker, and straightforward in diagnosing the illness.
Secondary sulphate aerosols and cirrus clouds detection with SEVIRI during Nabro volcano eruption

ABSTRACT Secondary sulphate aerosols (SSAs) and cirrus clouds in the upper troposphere–lower stratosphere (UTLS) are two key atmospheric constituents that can modulate the Earth’s radiative balance. In this article, we present a new preliminary detection algorithm for UTLS SSAs with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) geostationary instrument. This algorithm is used in combination with a well-established existing clouds classification algorithm, to provide, in perspective, a combined tool to better characterize the aerosol–cirrus interactions at the regional scale and at very high temporal resolution, thus potentially contributing to the understanding of the SSAs’ direct–indirect impact on the Earth’s radiative balance. This new combined tool is tested on the Nabro volcano eruption of June–July 2011, which is known to have emitted a great amount of SSA gaseous precursors in the UTLS and to have interacted with the peculiar Asian monsoon dynamics during summer 2011. Although volcanic aerosol–cirrus interactions are not analysed in details at this stage, this work demonstrates that this can be carried out with SEVIRI by introducing a new dedicated SSA product. First results of the new SSA detection algorithm are encouraging towards the use of this combined product.
Experimental study of the ballast in situ sediment acoustic measurement system in South China Sea

ABSTRACT The mechanical structure, the function modules, the working principles, and a sea trial of the newly developed ballast in situ sediment acoustic measurement system are reported in this study. The system relies on its own weight to insert transducers into seafloor sediments and can accurately measure the penetration depth using a specially designed mechanism. The system comprises of an underwater position monitoring and working status judgment module and has two operation modes: self-contained measurement and real-time visualization. The designed maximum working water depth of the system is 3,000 m, and the maximum measured depth of seafloor sediment is 0.8 m. The system has one transmitting transducer with the transmitting frequency band of 20–35 kHz and three receiving transducers. The in situ acoustic measurement system was tested at 15 stations in the northern South China Sea, and repeated measurements in seawater demonstrated good working performance. Comparison with predictions from empirical equations indicated that the measured speed of sound and attenuation fell within the predicted range and that the in situ measured data were reliable.
Dimensions of Internet Science

Internet Science is a new and exciting interdisciplinary field. Its purpose is the conduct of empirical studies which examine the Internet as both an instrument for, and an object of, scientific investigation. This book is the first comprehensive collection of contributions to Internet Science appearing in English, written by highly respected experts from seven different countries. All contributions were subject to a double peer review process. Dimensions of Internet Science consists of twenty contributions, covering the following topics: Issues in Net-based Survey Research, Psychological Web Experiments and Web Questionnaire Studies, Online Communication Research and E-Commerce, Knowledge Acquisition and Learning with the Net, Studying Perception on the Net.
Relation Between Arctic Moisture Flux and Tropical Temperature Biases in CMIP5 Simulations and Its Fingerprint in RCP8.5 Projections

Arctic moisture intrusions have played an important role in warming the Arctic over the past few decades. A prior study found that Coupled Model Intercomparison Project Phase 5 (CMIP5) models exhibit large regional biases in the moisture flux across 70°N. It is shown here that the systematic misrepresentation of the moisture flux is related to the models' overprediction of zonal wavenumber k = 2 contribution and underprediction of k = 1 contribution to the flux. Models with a warmer tropical upper troposphere and El‐Niño‐like tropical surface temperature tend to simulate stronger k = 2 flux, while k = 1 flux is uncorrelated with tropical upper tropospheric temperature and is associated with La‐Niña‐like surface temperature. The models also overpredict the transient eddy moisture flux while underpredicting the stationary eddy flux. Moreover, future projections in Representative Concentration Pathway 8.5 (RCP8.5) simulations show trends in moisture flux that is consistent with biases in historical simulations, suggesting that these CMIP5 projections reflect the same error(s) that cause the model biases.
Bullying y cyberbullying: prevalencia en adolescentes y jóvenes de Cantabria

El estudio tuvo como objetivo identificar la prevalencia del bullying y cyberbullying en adolescentes y jovenes de la Comunidad Autonoma de Cantabria. Este estudio se llevo a cabo con 1.322 participantes entre 12 y 20 anos, 673 mujeres (50,9%) y 649 varones (49,1%). Los participantes cursan Educacion Secundaria Obligatoria (ESO), Bachillerato, y el 1er Curso Formativo de Grado Medio. Se administro el Test Cyberbullying. Screening del Acoso entre Iguales (Garaigordobil, 2013). Los resultados informan que en cuanto a bullying, en el ultimo ano el 10,7% habia sufrido de forma severa conductas de bullying (7,3% victimas puras y 3,4% victimas-agresivas); un 7,9% informo haber realizado muy frecuentemente conductas de bullying a otros (4,5% agresores puros); y un 38,8% dijeron que habian visto que unos companeros agredian a otros con frecuencia. En relacion al cyberbullying en el ultimo ano el 10,8% habia sufrido de forma severa conductas de cyberbullying (7,8% cibervictimas puras y 3% cibervictimas-agresivas); un 5,8% informo haber realizado muy frecuentemente conductas de cyberbullying a otros (2,8% agresores puros); y un 35,2% dijeron que habian visto que unos companeros ciberagredian a otros con mucha frecuencia. En bullying, el porcentaje de victimas en ambos sexos es similar pero hay mas agresores varones; las conductas de bullying disminuyen con la edad; y no hay diferencias en funcion al nivel socioeconomicocultural. En cyberbullying, hay mayor porcentaje de cibervictimas mujeres y de ciberagresores varones; aumenta con la edad; y no se observan diferencias en funcion del nivel socio-economico-cultural. El estudio evidencia porcentajes de bullying y cyberbullying dignos de consideracion, enfatizando la necesidad de poner en marcha medidas de prevencion para que el acoso en todas sus modalidades no aparezca, y poner en marcha protocolos de intervencion cuando se detecte.
Hands Free Interaction with Virtual Information in a Real Environment

In augmented reality (AR) systems, real and virtual objects are merged and aligned relative a real environment, and presented in the field of view of a user. AR applications that give hierarchical instructions to users often require some feedback or acknowledgement from the user in order to move to the next step in the instructions. This feedback should be possible to give quickly and without interruption from the ongoing task. Many different types of interaction techniques have been used in the domain of AR; there are numerous examples of systems that use manual input, gestures and/or speech interfaces (Nilsson & Johansson 2006, Billlinghurst et al 2001, Gandy et al 2005 and Henrysson et al 2007). However, there are situations where speech and gesture may not be appropriate. For instance, during surgical procedures in an operating room the surgeon may have difficulties manually interacting with technical devices because of the need to keep her/his hands sterile. Voice interaction with a system may also not be appropriate due to surrounding noise or filtering problems. There is one modality that can overcome the issues of noisy environments, keeping hands sterile and the need to work with both hands while at the same time trying to interact with a computer or an AR system, and that is the visual modality. The aim of this paper is to present an AR system with an integrated gaze tracker, allowing quick feedback from the user to the system, as well as analysis of the users gaze behaviour.
Effectiveness of Phosphorous Fertilizers in Wheat Crop Production in Pakistan

Phosphorus is that element of periodic table, which is extensively found in nature and along with Nitrogen (N) and potassium represents the overall composition of plants and animal life. Phosphorus performed different metabolic activities in plants and is one of the key elements for the maturation of plants and boosting up the larger quantities. As it has a vital role in the metabolism and energy production reaction and can survive the unfavorable environmental effects so cause increase in yield. A research review was carried out on the effectiveness of P fertilizers on wheat crop in Pakistan. Almost all of the researchers in all areas indicated that P fertilizers significantly improved the growth as well as yield parameters of wheat crop. But the optimum rate of P fertilizer at which highest yield recorded was different for each area, soil and environmental condition. Although these findings on P fertilization representing many capable results regarding to yield and yield components of wheat but still further research is strongly recommended to evaluate the dynamics of P in soil as well as the interaction effect of P with other micro and macro nutrients.
Arabic Information Retrieval

Arabic is ranked as the seventh largest language on the Internet but it has also been the fastest growing language in the last decade in terms of users. At this rate of growth, Arabic users should have the fourth largest user population on the Internet by 2020. Given these facts, it is not surprising that Arabic Information Retrieval (IR) has garnered significant attention. The main research interests have focused on retrieval of formal language, mostly in the news domain, with ad hoc retrieval, OCR document retrieval, and cross-language retrieval. The literature on other aspects of retrieval continues to be sparse or non-existent, though some of these aspects have been investigated by industry. Others aspects of Arabic retrieval that have received attention include document image retrieval, speech search, filtering, and social media and web search. However, efforts within different aspects of Arabic retrieval continue to be deficient and severely lacking behind efforts in other languages. Arabic Information Retrieval reviews Arabic IR including the nature of the Arabic language, the techniques used for pre-processing the language, the latest research in Arabic IR in different domains, and the open areas in Arabic IR. It covers general properties of the Arabic language, aspects of Arabic that affect retrieval, Arabic processing necessary for effective Arabic retrieval, Arabic retrieval in public IR evaluations, Arabic IR and NLP resources, and specialized retrieval problems such as Arabic-English CLIR, Arabic Document Image Retrieval, Arabic Social Search, Arabic Web Search, Question Answering, Image retrieval, and Arabic Speech Search. Lastly, it also discusses open IR problems that require further attention.
HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI)

Tremendous efforts have thus been devoted on the establishment of functional MRI informatics systems that recruit a comprehensive collection of statistical/computational approaches for fMRI data analysis. However, the state-of-the-art fMRI informatics systems are especially designed for specific fMRI sessions or studies of which the data size is not really big, and thus has difficulty in handling fMRI 'big data. ' Given the size of fMRI data are growing explosively recently due to the advancement of neuroimaging technologies, an effective and efficient fMRI informatics system which can process and analyze fMRI big data is much needed. To address this challenge, in this work, we introduce our newly developed informatics platform, namely, 'HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI). ' HELPNI implements our recently developed computational framework of sparse representation of whole-brain fMRI signals which is called holistic atlases of functional networks and interactions (HAFNI) for fMRI data analysis. HELPNI provides integrated solutions to archive and process large-scale fMRI data automatically and structurally, to extract and visualize meaningful results information from raw fMRI data, and to share open-access processed and raw data with other collaborators through web. We tested the proposed HELPNI platform using publicly available 1000 Functional Connectomes dataset including over 1200 subjects. We identified consistent and meaningful functional brain networks across individuals and populations based on resting state fMRI (rsfMRI) big data. Using efficient sampling module, the experimental results demonstrate that our HELPNI system has superior performance than other systems for large-scale fMRI data in terms of processing and storing the data and associated results much faster.
Identifying ULF Wave Eigenfrequencies in SuperDARN Backscatter Using a Lomb‐Scargle Cross‐Phase Analysis

The eigenfrequencies of standing Alfvén waves on closed magnetospheric field lines can be estimated using the cross‐phase technique. These eigenfrequencies can be used to monitor the plasma mass density distribution along the field line. So far, this has only been applied to ground‐based magnetometer data. The Super Dual Auroral Radar Network (SuperDARN) radars offer some benefits over magnetometers. They provide greater spatial resolution and coverage, as well as direct sensing above the E region ionosphere, which screens ultralow frequency (ULF) waves from the ground. However, there are significant data quality issues. These include the uncertain origin of radar backscatter, uneven sampling of data due to data gaps, and inaccurate fitting to the autocorrelation functions. Artificial backscatter from an ionospheric heater has been used to remove the uncertainty in backscatter location. We have developed a Lomb‐Scargle cross‐phase analysis for application to discontinuous radar data. The First Principles Fitting Methodology has been used to improve the fitted data products derived from the autocorrelation functions. Using these techniques, we have shown that it is possible to measure eigenfrequencies with SuperDARN data, and we have verified an example using ground‐based magnetometer data. Finally, we have demonstrated that the eigenfrequency signature in this example was caused by a broadband source of energy.
An exploration of challenges associated with machine learning for time series forecasting of COVID-19 community spread using wastewater-based epidemiological data Science of the Total Environment

Explored the challenges associated with using machine learning algorithms for analysis of WBE datasets (cid:129) Evaluated the performance and accuracy of Random Forest algorithm for short- term predictions based on WBE datasets (cid:129) Sampling frequency and training set size wereidenti ﬁ edaskeyfactorscontributing to accuracy. (cid:129) Contribution of catchment population on forecast accuracy was more ambiguous. (cid:129) Determined that the factors governing Random Forest forecast performance are complicated and interrelated ings for the spread of outbreaks. The challenges associated with using machine learning for the analysis of WBE datasets and timeseries forecasting of COVID-19 were explored by running Random Forest (RF) algorithms on WBE datasets across 108 sites in ﬁ ve regions: Scotland, Catalonia, Ohio, the Netherlands, and Switzerland. This method usesmeasurementsofSARS-CoV-2RNAfragmentconcentrationinsamplestakenattheinletsofwastewatertreatment plants,providinginsightintotheprevalenceofinfectioninupstreamwastewatercatchmentpopulations.RF'sforecast-ing performance at each site was quantitatively evaluated by determining mean absolute percentage error (MAPE) values,whichwasusedtohighlightchallengesaffectingfutureimplementationsofRFforWBEforecastingefforts.Per-formance was generally poor using WBE datasets from Catalonia, Scotland, and Ohio with ‘ reasonable ’ or better fore- castsconstituting0%,5%,and0%oftheseregions'forecasts,respectively.RF'sperformancewasmuchstrongerwith WBE data from the Netherlands and Switzerland, which provided 55 % and 45 % ‘ reasonable ’ or better forecasts respectively. Sampling frequency and training set size were identi ﬁ ed as key factors contributing to accuracy, while inclusion of too many unnecessary variables (or e.g., ﬂ ow data) was identi ﬁ ed as a contributing factor to poor performance. The contribution of catchment population on forecast accuracy was more ambiguous. This study determined that the factors governing RF's forecast performance are complicated and interrelated, which presents challenges for furtherworkinthisspace.Asuf ﬁ cientlyaccuratefurtheriterationofthetooldiscussedwithinthisstudywouldprovide signi ﬁ cant but varying value for public health departments for monitoring future, or ongoing outbreaks, assisting the implementation of on-time health response measures.
Comparison of the Odin/OSIRIS stratospheric ozone profiles with coincident POAM III and ozonesonde measurements

We present first statistical comparison results for stratospheric ozone density profiles retrieved from Odin/OSIRIS limb scattered radiance with 1220 coincident POAM III and 205 coincident ozonesonde measurements. Profiles are compared on a monthly basis from November 2001 to October 2002. Most of the time, differences between OSIRIS mean profiles and those measured by POAM III and ozonesondes were 5–7% between 15 km and 32 km, and within 15% above 32 km. In April–July 2002, OSIRIS mean profiles appear shifted downward by ∼1 km, introducing a difference of about 10% with POAM III and about 25% with ozonesonde profiles between 15 km and 32 km. This study demonstrates that outside the April–July 2002 period, the OSIRIS ozone profiles agree well with coincident ozonesonde and POAM III ozone profiles and make a valuable addition to the international ozone database available for research into global ozone change.
Euesperides 2006: Preliminary Report on the Spring 2006 season

Abstract This paper is a preliminary report on the eighth and final fieldwork (Spring 2006) season of the excavations at Euesperides (Benghazi). Work continued in Areas P and Q on the Sidi Abeid mound, in Area R in the lower city and on the processing of finds from the 2006 and previous seasons. In Area P excavations continued below the primary floors of the antepenultimate phase in Room 5a where a series of inter-cutting pits beneath the primary floor provided a section through the stratigraphy to natural. The results of the work showed that occupation in the sixth to fourth centuries BC was less intensive and accumulated at a slower rate than in the Hellenistic period. Three phases of early activity were represented, with the earliest levels dated to the period c. 580–560 BC. A comparable picture emerged in Area R, but in Area Q a second-phase set of buildings laid out in or after the late sixth century BC, with houses flanking the street, persisted until late in the life of the city. Excavations in Area Q Extension revealed a large circular building with an internal floor of terracotta sherds set in cement, tentatively interpreted as part of a set of public baths. A late reuse of the building was indicated by a number of plaster-lined tanks formed over the terracotta floor. The presence of the building was taken to indicate that the building and an associated street, aligned over an in-filled quarry, may have been inter-mural, suggesting that the late city was of greater size than hitherto thought. Selected finewares, coarsewares and amphorae from the excavations are presented, together with preliminary observations, resulting from the environmental sampling of occupation deposits.
SCHNYDER WOODS FOR HIGHER GENUS TRIANGULATED SURFACES 3 Schaeffer

Schnyder woods are a well-known combinatorial structure for plane triangulations, which yields a decomposition into 3 spanning trees. We extend here definitions and algorithms for Schnyder woods to closed orientable surfaces of arbitrary genus. In particular, we describe a method to traverse a triangulation of genus g and compute a so-called g-Schnyder wood on the way. As an application, we give a procedure to encode a triangulation of genus g and n vertices in 4n + O(g log(n)) bits. This matches the worst-case encoding rate of Edgebreaker in positive genus. All the algorithms presented here have execution time O((n + g)g), hence are linear when the genus is fixed. This is the extended and revised journal version of a conference paper with the title “Schnyder woods generalized to higher genus triangulated surfaces”, which appeared in the Proceedings of the ACM Symposium on Computational Geometry 2008 (pages 311-319).