Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentiment Analysis of Twitter by using Apache Flume

Now-a-days social media is playing a key role in all aspects of life. Identifying and classifying views expressed in source text are organized by twitter analysis. Organizations use twitter analysis to understand how the public feels about something at a particular moment in time, and also to track how those opinions change over time. In the form of tweets, status updates and blog posts a huge volume of twitter rich data is being created in social media. User generated data is very useful in knowing the attitude of the crowd. The presence of shortcut words and misspellings makes twitter analysis a bit difficult when compared to general sentiment analysis. The two strategies used for analyzing twitter application from the text are Machine learning approach and Knowledge base approach. By using log analysis we are able to obtain opinions of a particular group or a particular person. Log files from web servers represent a treasure of data that can be used to gain a deep understanding of anything. Here in this paper, we analyze about any type of tweets in twitter on basis of timestamp (like seconds, minutes, hours, days etc.). Standford-corenlp (natural language processing) is used for classifying the tweets in providing twitter application by using Apache flume in Hadoop
Aquatide Activation of SIRT 1 Reduces Cellular Senescence through a SIRT 1-FOXO 1-Autophagy Axis

Autophagy is an evolutionarily conserved intracellular process of delivering cytosolic compartments into the lysosome for degradation (Mizushima et al., 2008). While autophagy process is induced by cellular stresses, such as nutrient starvation, oxidative stress, and pathogenic infection, two main protein kinase complexes, the unc-51-like kinase complex along with mammalian target of rapamycin complex 1; and the class III phosphatidylinositol 3-kinase complex, are responsible for recruitment of proteins required for autophagy in the phagophore assembly site to initiate phagophore formation (Boya et al., 2013; Lapaquette et al., 2015). Phagophore then elongates to form a vesicular structure, termed as autophagosome (Boya et al., 2013; Lapaquette et al., 2015). Subsequently, matured autophagosome fuses with lysosome, leading to the formation of a single membrane autolysosome (Boya et al., 2013; Lapaquette et al., 2015). Physiological
Series Discovery and Ranking of Functional Dependencies

Computing the functional dependencies that hold on a given data set is one of the most important problems in data profiling. Our research advances stateof-the-art in various ways. Utilizing new data structures and original techniques for the dynamic computation of stripped partitions, we devise a new hybridization strategy that outperforms the best algorithms in terms of efficiency, column-, and row-scalability. This is demonstrated on real-world benchmark data. We show that current outputs contain many redundant functional dependencies, but canonical covers greatly reduce output sizes. Smaller representations of outputs are easier to comprehend and use. We propose the number of redundant data values as a natural measure to rank the output of discovery algorithms. Our ranking assesses the relevance of functional dependencies for the given data set.
Sudden Death as Viewed From Autopsy Findings

We examined the rates of sudden death to ordinary deaths of the patients in two hospitals in Obihiro. A total of 130 sudden death cases (89 men and 41 women) out of 1,088 ordinary deaths were listed (11.9%) during the period of two years from 1992 through 1993. We also looked into the cause of sudden death in 86 autopsied cases over a 15-year period from 1985 through 1999 from a pathological stand point. Cardiac diseases underlay 49 cases of sudden death. Myocardial infarction (42 cases), cardiomyopathy (2), sarcoidosis (1), amyloidosis (2) and valvular disease (2) were regarded as the causes of death in the 49 cases. Myocardial infarction occurred more frequently in men than in women (27: 15). Next to cardiac diseases came aortic diseases such as ruptured aortic aneurysm (7 cases) and dissecting aneurysm (6). Cardiac diseases (49 cases) and aortic diseases (13) combined to account for 62 of 86 (72.1%) autopsied cases. Among noncardiovascular diseases, respiratory diseases (18 cases) topped the list, followed by alimentary diseases (3) and cerebral bleeding (2). The major cause of respiratory diseases was pulmonary embolism (16). Pulmonary embolism more often occurred in women than in men (14: 2). There was one case of unidentifiable sudden death, namely Pokkuri disease. A decreased incidence of sudden death on Sunday should be noted. A circadian rhythm was evident. The incidence of sudden death started rising from 6: 00 and peaked at 15: 00. Sudden death occurred during rest (42 cases), during routine daily activity (14), during sleep (11), during bathing (1), during defecation (8), during surgery (2), during physical exercise (6) and during agricultural work (2).
Effect of High-Energy Ball Milling on the Electrical and Piezoelectric Properties of ( K 0 . 5 Na 0 . 5 ) ( Nb 0 . 9 Ta 0 . 1 ) O 3 Lead-Free Piezoceramics

Nanocrystalline powders of the lead-free piezoelectric material, tantalum-substituted potassium sodium niobate (K0.5Na0.5)(Nb0.9Ta0.1)O3 (KNNT), were produced using a Retsch PM100 planetary ball mill by setting the milling time to 15h, 20h, 25h, 30h, 35h and 40h, at a fixed speed of 250rpm. The average particle size of the milled powders was found to decrease from 12nm to 3nm as the milling time increases from 15h to 25h, which is in agreement with the existing theoretical model. An anomalous increase to 98nm and then a drop to 3nm in the particle size were observed as the milling time further increases to 30h and 40h respectively. Various sizes of these starting KNNT powders were used to investigate the effect of milling time on the microstructure, dielectric properties, phase transitions and piezoelectric properties of the resulting KNNT ceramics. The particle size of starting KNNT was somewhat proportional to the grain size. As the milling time increases from 15h to 25h, the resulting ceramics exhibit enhancement in the values of relative density from 94.8% to 95.8%, room temperature dielectric constant (εRT) from 878 to 1213, and piezoelectric charge coefficient (d33) from 108pC/N to 128pC/N. For this range of ceramic samples, grain size refinement suppresses the maximum dielectric constant (εmax), shifts the Curie temperature (Tc) to a lower temperature and the orthorhombic-tetragonal phase transition (Tot) to a higher temperature. Further increase of milling time from 25h to 40h produces a gradual degradation in the values of relative density, εRT, and d33 of the resulting ceramics. Keywords—Ceramics, Dielectric, High-energy milling, Perovskite.
Comparison of Statistical Methods for Genomic Signature Extraction

In recent years microarray technologies have gained a lot of popularity for their ability to quickly measure the expression of thousands of genes and provide valuable information for linking complex diseases such as cancer to their genetic underpinnings. Feature selection methods are used in order to extract small and informative sets of genes that can maximize the performance of classification methods used to map unknown samples into classes of interest, leading to new and efficient methods for prognosis of several diseases, which are personalized to the genome of each specific patient. Moreover, the biological interpretation of these sets of genes, often referred to as “genomic signatures”, can help biologists and physicians better understand the biological processes related to complex diseases, such as cancer and may potentially lead to the discovery of new methods of treatment. Nevertheless, the large number of parameters to be estimated in relation to the small number of available samples gives rise to an “ill posed” problem where the performance assessment of feature selection and classification methods is not stable under slight changes the dataset. In this thesis, a generic evaluation framework named “Stable Bootstrap Validation” (SBV) is presented, that utilizes resampling of the original dataset and an explicit criterion that determines the stability of the observed classification accuracy, as well as the genomic signature. The proposed methodology works in an iterative manner and converges to a stable solution that combines good accuracy with biologically meaningful feature selection. The methodology is orthogonal to the specific feature selection and classification algorithms used. Moreover, methodologies for assessing the statistical significance and consistency of the observed results are also introduced. Some of the most widely used classifiers are compared, based on their average discrimination power and the size of the derived gene signature. According to our proposed model, a unified ‘77 common-gene signature’ was selected, which is closely associated with several aspects of breast tumorigenesis and progression, as well as patient-specific molecular and clinical characteristics.
P 2 . 8 INFLUENCE OF THE AIRFLOW DISTORTION ON AIR-SEA FLUX MEASUREMENTS ABOARD RESEARCH VESSEL : RESULTS OF PHYSICAL SIMULATIONS APPLIED TO THE EQUALANT 99 EXPERIMENT

Turbulent fluxes of momentum, heat and moisture intervene in numerous aspects of meteorology and oceanography (climate studies, weather forecasting, mixed layer modelling .). The exchange estimates between ocean and atmosphere are particularly essential to numerical modelling studies which use turbulent fluxes derived from parameterisations and mean meteorological measurements. In recent years, a main focus has been put on the accuracy of these parameterisations in order to reduce the uncertainties of global models of the coupled ocean-atmosphere system. Since the measurements of turbulent fluxes over the ocean are often performed on huge platforms (research vessels, coastal platforms .) which modify the upstream air, the improvement of flux parameterisation required to address the issue of flow distortion (Edson et al.,1998). For example, Yelland et al. (1998) revealed that for a given wind speed, the corrections of the stream disturbance reduced the drag coefficient by about 6%. The main goal of this study is to present the results of momentum and heat fluxes obtained during the EQUALANT99 experiment aboard the R/V La Thalassa and to apply the correction for airflow distortion to various methods of turbulence flux computation and then observe the correction impact.
Public-private sector segmentation in the labour market in Pakistan

This study investigates public–private sector wage differentials for male and female waged employees in Pakistan. This is done using latest nationally representative data from the Pakistan Living Standards Measurement Survey (PSLM) 2005. We adopt three methodologies to obtain robust estimates of the wage differential and the results reveal that public sector workers enjoy large wage premia. The gross pro-public wage differential is much larger for women than for men. Our findings also show that while private and public sector workers’ differing characteristics ‘explain’ a larger proportion of the private–public wage gap for men, this is not the case for women. 2008 Elsevier Inc. All rights reserved. * Corresponding author at: Department of Economics, Centre for the Study of African Economics, University of Oxford, Manor Road Building, Oxford OX1 3UQ, United Kingdom. Fax: +44 1865 271094. E-mail address: monazza.aslam@economics.ox. ac.uk (M. Aslam). 1 The Exchange rate used everywhere in this study is the historical rate as at January 2005 of 1USD = Rs. 59.57. 2 Wage figures from the Pakistan Living Standards Measurement Survey (2005).
Impact of i human em Einfluss

The radiosensitivity of the early developing human embryo is not well characterized. Radiation protection guidelines in case of an in utero exposure are mainly based on animal experiments and on epidemiological data. The mechanisms behind a radiation response of the embryo especially of high LET radiation is not completely understood. Therefore, there is a need to elucidate the effects of low and high LET ionizing radiation on early embryonic development. To contribute to a better understanding of this topic, H9 human embryonic stem cells were used as an in vitro tool to investigate the early blastocyst-like stage of the human embryonic development. As the latter give rise to an entire functional organism, maintaining their structural and genomic integrity is mandatory to avoid passing DNA damage on to the progeny. In the literature, it is reported that embryonic stem cells indeed exhibit a lower mutation frequency and that they show a higher apoptotic activity upon DNA damage, compared to differentiated somatic cells. A previous study on mouse embryonic stem cells performed at GSI indicates that even though eighth generation daughter cells still harbor chromosomal aberrations after exposure to high LET radiation, they are capable to maintain a pluripotent cell population. This study elucidates the capacity of human embryonic stem cells to efficiently eliminate damaged cells upon ionizing radiation exposure and to proceed normally into endoderm differentiation. Thus, human embryonic stem cells were exposed to 1 and 3 Gy of X-rays, as well as to 1 Gy and 3 Gy of high LET radiation i.e. C, Ca, Ni and Ti ions. Human embryonic stem cells were observed up to 14 days after exposure in pluripotency maintaining culture conditions, and up to 11 days in conditions promoting differentiation into definitive endoderm. Endpoints such as cell cycle block, apoptosis, chromosomal aberrations, and gene expression related to embryonic signaling pathways and pluripotency as well as differentiation were investigated. It was found that isodoses of high LET radiation were more effective than X-rays in inducing apoptosis and chromosomal aberrations in human embryonic stem cells. After a radiation induced G2 block, a fraction of cells undergoes apoptosis. However, few stable chromosomal aberrations are still found in the progeny of exposed human embryonic stem cells. Gene expression studies of embryonic signaling pathways showed a majority of downregulated genes related to WNT, FGF, Hedgehog, TGFβ and Notch signaling pathways. These signaling alterations presumably cause the observed downregulation of core pluripotency markers like OCT4A and NANOG. Consequently, differentiation capability into definitive endoderm was impaired. Together, the results reported in this work might indicate several consequences for the early embryo in case of an in utero exposure, like implantation failure due to cell cycle arrest and apoptosis, or malformations due to alterations in cell signaling and differentiation processes.
A Fragile Link? A New Empirical Analysis of the Relationship between Financial Development and Economic Growth

This article contributes to the literature on the finance–growth link by presenting new findings based on a new, larger dataset that is an improvement on earlier studies due to its greater coverage in terms of time periods and countries, as well as the incorporation of additional control variables such as institutional quality and the investment rate. Our results demonstrate that financial development does not have a statistically significant effect on economic growth, a finding that is robust to different model specification and estimation techniques. This suggests that the finance–growth link is not as strong as portrayed in the literature, being dependent on the sample of countries and time periods considered.
Studying the Relationship among Depression , Anxiety , Stress and Personality Factors in Iranian High School Students :

The objective of this study was to examine stress, anxiety and other personality dimensions inhigh school students’ depressions. This research method was analytic-descriptive , which were assessed in 120 students using understanding mental pressure questionnaire (SPSS) , Zhang anxiety self –assessment scale (SAS), the personality five – factor questionnaire (NEO-PI-R) and Beck depression questionnaire.The results were analyzed by SPSS software.The correlation coefficients showed that there wasa significantcorrelation between depression and anxiety. The regression resultsalso indicated that all Variables werecapable ofpredicting depression.According to the obtained results it could be said that the effects of depression, anxiety, stress and personality factors on students involve family continuously and it has affected parent behaviors . On thy other hand, personality dimensions , stress and anxiety are all factors that play roles in students depression . Therefore variables includedin the vulnerable students should be considered and by mediating them reduce the depression rate in these groups.
Variability of nodulation traits in Andean and Mesoamerican common bean gene pools

The objective of this work was to evaluate the genotypic diversity for nodulation in common bean (Phaseolus vulgaris) genotypes of Andean and Mesoamerican gene pools present in the core collections of Embrapa, in Brazil. Evaluations were carried out in two stages: the first one with 879 genotypes, taking the cultivar 'Ouro Negro' as reference; and the second one with 116 genotypes with greater nodulation, to identify those showing stability in nodulation in the two stages. Rhizobium strains were inoculated in pre-germinated common bean seed. Plants received weekly a nutrient solution without N, and nodulation was evaluated 35 days after planting. The percentage of genotypes that exceeded the reference cultivar was 22% for number of nodules, 46% for nodule dry weight, and 33% for one nodule dry weight. The combined analysis of data from the two evaluation phases showed wide differences among genotypes, and significant interactions between genotypes and stages. By the orthogonal contrasts analysis, the Mesoamerican genotypes showed a greater nodulation than the Andean ones. In both stages, twenty-six more stable genotypes were identified, most of them belonging to the Mesoamerican gene pool. There is a large variability in nodulation traits among the common bean genotypes present in the core germplasm collections of Embrapa, which suggests that there are genotypes with improved nodulation.
Automated Classification of Human Genome Sequences in Patent Documents

Recent changes in gene patent policy has necessitated the analysis of patents that disclose and reference human genome sequences. In this study, our goal is to build an automated classifier that could assign sequences to one of nine predefined categories according to their functional roles in patent claims. By applying mainly natural language processing and supervised learning techniques we build a software system which integrated data processing, training and testing and performance evaluation. We experimented various feature mapping schemes and evaluated their effectiveness with respect to different measurement criteria. Several potential approaches are proposed with up to 79% overall accuracy. Further work could be focused on improving the classification performance and practical utility. Supervisors: Adj. Prof. Hanna Suominen, Dr. Gabriela Ferraro, Prof. Osmat A. Jefferson
Automated Image Processing / Image Understanding Coupled with an Artificial Neural Network Classifier for Quantifying Biological Fouling on Ship Hulls

Use of automated image processing coupled with an artificial neural network based classifier for identifying fouling organisms on ship hulls. Lieberman Stephen H. , He Li-Ming, and Timothy Adam, Space and Naval Warfare Systems Center San Diego, 2361, 53475 Strothe Rd., San Diego, CA 92152 Invasive (or non-native) species have been introduced inadvertently into many marine and fresh water systems via ship movements. The major transport pathways that have been identified include ballast water, tank sediments and ship hull fouling. To date, most monitoring and control programs have focused on ballast water as the dominant pathway for transport of invasive species. However, recent studies suggest that historically, as well as presently, hull fouling may represent an important pathway for transport of invasive species. Most information on invasive species and hull fouling organisms is based on diver inspections of hulls. This method is costly, potentially dangerous, and often subjective. Improved methods are needed to more effectively conduct underwater hull inspections, objectively quantify the abundance and diversity of fouling organisms, and more specifically identify non-indigenous species. In this study we report on the investigation of the use of automated image processing/image-understanding algorithms coupled with artificial neural network based classifiers for identifying fouling organisms on ship hulls from digital images. The methodology is based on a four-step process that includes: 1) image acquisition, 2) image pre-processing, 3) feature extraction, and 4) object classification. Initial results will be presented from studies in which an artificial neural network is used to automatically classify various types of fouling organisms isolated via the standard digital image processing methodologies. Once individual objects are identified in the images, then an array of object properties (e.g., size, shape, color, texture, etc.) is used as an input array to train an artificial neural network to discriminate and thereby identify certain classes of organisms. After the network is trained by example using many images of organisms that have been previously identified, then the trained network is used to automatically classify organisms in new images based on the unique differences in the array of object properties. Preliminary results will be presented for the application of this approach to common hull fouling organisms with special attention to classification and discrimination of target non-indigenous species.
Design of LQG Controller Using Operational Amplifiers for Motion Control Systems

This paper proposes additional steps to the traditional design procedures for continuous control systems using operational amplifiers. Designing an analog Linear Quadratic Gaussian (LQG) controller is selected as a case study. The controller in the s-domain is firstly designed based on the mathematical model of the plant to be controlled, and then simulated and adjusted. Next, the plant and the controller in the s-domain will be converted to equivalent corresponding continuous electronic circuits using operational amplifiers and continued for simulating. The main purpose of these proposed additional steps is to confirm that converting the controller from s-domain to corresponding analog electronic circuits using operational amplifiers is correct or not. After that, the controller will be implemented and applied to the real setup. For a good design, the simulation results of the resulting controlled system in s-domain, also in equivalent analog electronic circuits, and experimental results in the real setup are almost the same.
Distribution of neural-based discrete control algorithms applied to home automation with

Distributed systems have been demonstrated as one of the best options when implementing industrial control systems due their simplicity and power. Following this line, our group has proposed Rule Nets (RN) as a HLP over CAN for the implementation of Distributed Expert Systems (at 6 ICC), obtaining excellent results although RN lack of continuous control capabilities. To provide these new features, in this article, the use of Neural Networks (NN) alongside of RN, as an application level over CAN is proposed, offering an intelligent and hierarchical environment of distributed control, where continuous control loops are being supervised by an expert system. This technique is now being applied in the integral control of an automated house, where NN implement the control loops (heating /cooling, brightness, etc) and advanced features (voice, fingerprints and shape recognition, etc.) and over them RN supervise the operation of the system, under normal operation conditions and exceptional situations.