Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Sentiment Analysis in Twitter Using Multilingual Machine Translated Data

Sentiment analysis is currently a very dynamic field in Computational Linguistics. Research herein has concentrated on the development of methods and resources for different types of texts and various languages. Nonetheless, the implementation of a multilingual system that is able to classify sentiment expressed in various languages has not been approached so far. The main challenge this paper addresses is sentiment analysis from tweets in a multilingual setting. We first build a simple sentiment analysis system for tweets in English. Subsequently, we translate the data from English to four other languages - Italian, Spanish, French and German - using a standard machine translation system. Further on, we manually correct the test data and create Gold Standards for each of the target languages. Finally, we test the performance of the sentiment analysis classifiers for the different languages concerned and show that the joint use of training data from multiple languages (especially those pertaining to the same family of languages) significantly improves the results of the sentiment classification.
Cetuximab-conjugated iron oxide nanoparticles for cancer imaging and therapy

We have developed a theranostic nanoparticle, ie, cet-PEG-dexSPIONs, by conjugation of the anti-epidermal growth factor receptor (EGFR) monoclonal antibody, cetuximab, to dextran-coated superparamagnetic iron oxide nanoparticles (SPIONs) via periodate oxidation. Approximately 31 antibody molecules were conjugated to each nanoparticle. Cet-PEG-dexSPIONs specifically bind to EGFR-expressing tumor cells and enhance image contrast on magnetic resonance imaging. Cet-PEG-dexSPION-treated A431 cells showed significant inhibition of epidermal growth factor-induced EGFR phosphorylation and enhancement of EGFR internalization and degradation. In addition, a significant increase in apoptosis was detected in EGFR-overexpressing cell lines, A431 and 32D/EGFR, after 24 hours of incubation at 37°C with cet-PEG-dexSPIONs compared with cetuximab alone. The antibody-dependent cell-mediated cytotoxicity of cetuximab was observed in cet-PEG-dexSPIONs. The results demonstrated that cet-PEG-dexSPIONs retained the therapeutic effect of cetuximab in addition to having the ability to target and image EGFR-expressing tumors. Cet-PEG-dexSPIONs represent a promising targeted magnetic probe for early detection and treatment of EGFR-expressing tumor cells.
Cardioprotective mIGF-1/SIRT1 signaling induces hypertension, leukocytosis and fear response in mice

Locally acting insulin growth factor isoform (mIGF-1) and the NAD+-dependent protein deacetylase SIRT1 are implicated in life and health span. Heart failure is associated with aging and is a major cause of death. mIGF-1 protects the heart from oxidative stresses via SIRT1. SIRT1 subcellular localization and its genomic regulation by mIGF-1 are unknown. We show here that SIRT1 is located in the nuclei of a significant fraction of cardiomyocytes. Using high throughput sequencing approaches in mIGF-1 transgenic mice, we identified new targets of the mIGF-1/SIRT1 signaling. In addition to its potent cardioprotective properties, cardiac-restricted mIGF-1 transgene induced systemic changes such as high blood pressure, leukocytosis and an enhanced fear response, in a SIRT1-dependent manner. Cardiac mIGF-1/SIRT1 signaling may thus modulate disparate systemic functions.
The transcriptome and miRNome profiling of glioblastoma tissues and peritumoral regions highlights molecular pathways shared by tumors and surrounding areas and reveals differences between short-term and long-term survivors

Glioblastoma multiforme (GBM) is the most common and deadliest primary brain tumor, driving patients to death within 15 months after diagnosis (short term survivors, ST), with the exception of a small fraction of patients (long term survivors, LT) surviving longer than 36 months. Here we present deep sequencing data showing that peritumoral (P) areas differ from healthy white matter, but share with their respective frankly tumoral (C) samples, a number of mRNAs and microRNAs representative of extracellular matrix remodeling, TGFβ and signaling, of the involvement of cell types different from tumor cells but contributing to tumor growth, such as microglia or reactive astrocytes. Moreover, we provide evidence about RNAs differentially expressed in ST vs LT samples, suggesting the contribution of TGF-β signaling in this distinction too. We also show that the edited form of miR-376c-3p is reduced in C vs P samples and in ST tumors compared to LT ones. As a whole, our study provides new insights into the still puzzling distinction between ST and LT tumors, and sheds new light onto that “grey” zone represented by the area surrounding the tumor, which we show to be characterized by the expression of several molecules shared with the proper tumor mass.
A Novel Approach of Full Adder and ALU Design in Quantum Dot Cellular Automata

Quantum dot Cellular Automata (QCA) is a promising technology and can emerge alternative to the existing CMOS based technology. This paper presents a novel reduced design of a full adder both in size and delay. Next a reduced area multilayered Arithmetic Logic Unit (ALU) is presented with significantly less delay. The designs have been verified and simulated using the QCA Designer tool. Keywords—QCA, NNI( Nand Nor Inverter), ALU, Adder
Feature selection with PSO and kernel methods for hyperspectral classification

Hyperspectral image data has great potential to identify and classify the chemical composition of materials remotely. Factors limiting the use of hyperspectral sensors in practical land-based applications, such as robotics and mining, are the complexity and cost of data acquisition, and the processing time required for the subsequent analysis. This is mainly due to the high dimensional and high volume nature of hyperspectral image data. In this paper, we propose to combine a feature selection method, based on particle swarm optimization (PSO), with a kernel method, support vector machines (SVM), to reduce the dimensionality of hyperspectral data for classification. We evaluate several different kernels, including some optimized for hyperspectral analysis. In particular, a recent kernel called observation angle dependent (OAD) kernel, originally designed for Gaussian Process regression, was extended for SVM classification. The SVM with the optimized kernel was then applied to induce the feature selection of a binary version of PSO. We validate the method using hyperspectral data sets acquired of rock samples from Western Australia. The empirical results demonstrate that our method is able to efficiently reduce the number of features while keeping, or even improving, the performance of the SVM classifier.
How Can Peers Assist Each Other in Large-Scale P2P-VoD Systems

A new genre of P2P systems, P2P Video-on-Demand(P2P-VoD), has not only received substantial recent research attention, but also been implemented and deployed with success in large-scale real-world streaming systems, such as PPLive. The essential characterization of P2P-VoD systems is to take full advantage of peer upload bandwidth contribution with a cache on each peer. Meanwhile, the asynchronous playback of each peer dilutes the peers' ability of assisting each other. How can peers assist each other in large-scale P2P-VoD systems? In this paper, we seek to develop a tractable analytical model and present a simple close-form expression of the average peer contribution, to help us form an in-depth understanding of peer contribution in large-scale P2P-VoD systems. Our analytical results are cross-validated by our extensive simulation studies in large-scale scenario.
Three axis Attitude Determination and Control System for a Picosatellite: Design and Implementation

The design and implementation of the Attitude Determination and Control System (ADCS) for a Norwegian pico-satellite is presented. The satellite, named nCube, is based on the CubeSat concept. This means that its size is restricted to a cube measuring 10 cm on all sides and that its total mass is restricted to 1k g. Meeting these restrictions represents the main technical challenge of the work. The complete cube includes the payload, ADCS with actuators and sensors, deployable antennas, communication systems, on board data handling (OBDH) and power system. Miniaturization is a key approach in order to meet the tight mass budget. The Determination part of the ADCS is solved by integrating measurements from a three-axis magnetometer with current measurements from the solar panels in a Kalman filter. The solar panes are used as crude sun sensors. The Control part is solved by using a combination of magnetic coils and gravity boom. The control system operates in one of two modes: 1) Detumbling and 2) Stabilization. The control laws are derived using Lyapunov theory, and stringent stability proofs are given. The gravity boom is realized using measurement tape. Simulations of both detumbling, boom deployment and stabilization are presented.
Computational time quantification of the single diode PV models

A range of photovoltaic (PV) models of different accuracy and complexity are available in the literature. The proper PV model for a particular study is selected based on the desired accuracy and computational time. Although the accuracy of the single diode models is well studied, there is still no available quantification for the computational time needed to simulate a certain PV model. This paper studies the computational time of the single diode models and derives empirical formulas quantifying the computational time needed to model PV arrays. This will enable users to calculate the expected simulation time for running their simulation. The results of this paper will help PV researchers and designers select the suitable PV model for simulating a specific PV system.
Theory of transmission through disordered superlattices

We derive a theory for transmission through disordered finite superlattices in which the interface roughness scattering is treated by disorder averaging. This procedure permits efficient calculation of the transmission thr ough samples with large cross-sections. These calculations can be performed utilizing either the Keldysh or the Landauer-B\"uttiker transmission formalisms, both of which yield identical equations. For energies close to the lowest miniband, we demonstrate the accuracy of the computationally efficient Wannier-function approximation. Our calculations indicate that the transmission is strongly affected by interface roughness and that information about scale and size of the imperfections can be obtained from transmission data.
Identifying diverse usage behaviors of smartphone apps

Smartphone users are increasingly shifting to using apps as "gateways" to Internet services rather than traditional web browsers. App marketplaces for iOS, Android, and Windows Phone platforms have made it attractive for developers to deploy apps and easy for users to discover and start using many network-enabled apps quickly. For example, it was recently reported that the iOS AppStore has more than 350K apps and more than 10 billion downloads. Furthermore, the appearance of tablets and mobile devices with other form factors, which also use these marketplaces, has increased the diversity in apps and their user population. Despite the increasing importance of apps as gateways to network services, we have a much sparser understanding of how, where, and when they are used compared to traditional web services, particularly at scale. This paper takes a first step in addressing this knowledge gap by presenting results on app usage at a national level using anonymized network measurements from a tier-1 cellular carrier in the U.S. We identify traffic from distinct marketplace apps based on HTTP signatures and present aggregate results on their spatial and temporal prevalence, locality, and correlation.
Subdural haematoma: presentation and diagnosis on medical wards

The twenty-two adult patients with subacute and chronic subdural haematoma seen in Leicester during the last 7 years have been reviewed. The clinical manifestations and results of investigations are described. The diagnostic difficulties which may confront physicians are discussed, with special reference to cases with no history of head injury masquerading as strokes. Stress is laid on the points which help with the differentiation.
NCBO Annotator: Semantic Annotation of Biomedical Data

The National Center for Biomedical Ontology Annotator is an ontology-based web service for annotation of textual biomedical data with biomedical ontology concepts. The biomedical community can use the Annotator service to tag datasets automatically with concepts from more than 200 ontologies coming from the two most important set of biomedical ontology & terminology repositories: the UMLS Metathesaurus and NCBO BioPortal. Through annotation (or tagging) of datasets with ontology concepts, unstructured free-text data becomes structured and standardized. Such annotations contribute to create a biomedical semantic web that facilitates translational scientific discoveries by integrating annotated data.
Cross-national Invariance of Dimensions of Parental Rearing Behaviour

A psychometric study on Swedish and Dutch samples used the EMBU, a self-report instrument designed to assess memories of parents' rearing behaviour. Of the four primary factors identified previously with Dutch individuals (Rejection, Emotional Warmth, Over-protection, and Favouring Subject), the first three were retrieved in a similar form in the two Swedish groups (depressives and healthy, non-patients). Examination of the metric equivalence of the scales and the strength of the factors for each group indicated that comparisons of patterns and levels between groups from the respective countries on the three factors showing cross-national constancy would be warranted. Scale-level factor analyses of these dimensions produced identical two-factor compositions (CARE and PROTECTION) across national groups which further supported this conclusion.
The neonatal "sepsis work-up": personal reflections on the development of an evidence-based approach toward newborn infections in a managed care organization.

"Rule out sepsis" may be the most common discharge diagnosis among infants admitted to the neonatal intensive care unit. Although the frequency of sepsis, meningitis, and other confirmed bacterial infections has remained constant (between 1 and 5/1000 live births) for many years, the number of infants evaluated and treated is much higher. Each year in the United States, as many as 600 000 infants experience at least one evaluation for suspected bacterial infection during the birth hospitalization. The number treated is estimated at 130 000 to 400 000 per year. Despite massive overtreatment, delayed diagnosis still occurs. The Kaiser Permanente Medical Care Program (KPMCP) considers developing and implementing an evidence-based approach to "rule out sepsis," a research and operational priority. To achieve these goals, it is essential to consider two key aspects of the problem. First, it is important to adopt a phenomenologic approach that takes clinicians' personal experience into account. This must include reflection on those aspects of experience often considered "irrational" or "subjective. " Second, incorporation of a phenomenologic approach needs to be tempered with sound epidemiologic methods. If one considers these two aspects-physician experience and sound epidemiology-it is clear that much of the existing literature on "rule out sepsis" is of limited utility. Consequently, the KPMCP has conducted its own studies. These are aimed at characterizing the "sepsis work-up," developing electronic datasets that would permit clinicians to simulate various strategies, and developing techniques for ongoing electronic monitoring. This article summarizes the approach taken by the KPMCP Division of Research. It describes the results of a pilot study as well as the development and use of a dedicated neonatology outcomes database, the Kaiser Permanente Neonatal Minimum Data Set (NMDS). The NMDS database includes the Score for Neonatal Acute Physiology and permits ongoing monitoring of sepsis "work-ups" as well as confirmed cases of neonatal infection. The article also describes how the experience from the pilot as well as the NMDS was incorporated in the design of a much larger study on "rule out sepsis. " Finally, the article describes some important theoretic issues affecting decision rule development and the use of computer simulations in neonatology. These issues are 1) how one handles possible overanalysis of a dataset; 2) how one handles data points that are unstable (eg, the absolute neutrophil count, which can vary considerably depending on age and sampling conditions); and 3) the limitations of decision rules based on computer simulations.
Developmental changes in calcium currents of rabbit ventricular cells.

We investigated the postnatal development of L-type Ca2+ current (ICa) in enzymatically isolated adult (AD) and newborn (NB) (1-3-day-old) rabbit ventricular cells using the whole-cell, patch-clamp method. ICa was recorded with Cs(+)-rich pipettes and a Na(+)- and K(+)-free bath solution at 36 degrees C to eliminate other currents. ICa density (obtained by normalizing ICa to the cell capacitance) was significantly higher in AD cells than in NB cells at potential levels between 0 and +50 mV with 1.8 mM Ca2+ as the charge carrier. There was no shift in the current-voltage relation between AD and NB cells. The maximum ICa density was 9.9 +/- 2.0 pA/pF at 14 +/- 5 mV in AD cells (n = 11) compared with 5.6 +/- 2.0 pA/pF at 13 +/- 5 mV in NB cells (n = 7) (mean +/- SD). Time to half inactivation (T 1/2) showed a nearly U-shaped relation to membrane potentials from -10 to +30 mV with the shortest T 1/2 at the potential giving the maximum ICa density in both groups. T 1/2 at 0 and +10 mV was slightly but significantly longer in NB cells (16.8 +/- 4.6 and 13.5 +/- 2.4 msec, respectively) than in AD cells (12.6 +/- 3.0 and 10.6 +/0 1.5 msec). (ABSTRACT TRUNCATED AT 250 WORDS)
Resampling Feature and Blend Regions in Polygonal Meshes for Surface Anti‐Aliasing

Efficient surface reconstruction and reverse engineering techniques are usually based on a polygonal mesh representation of the geometry: the resulting models emerge from piecewise linear interpolation of a set of sample points. The quality of the reconstruction not only depends on the number and density of the sample points but also on their alignment to sharp and rounded features of the original geometry. Bad alignment can lead to severe alias artifacts. In this paper we present a sampling pattern for feature and blend regions which minimizes these alias errors. We show how to improve the quality of a given polygonal mesh model by resampling its feature and blend regions within an interactive framework. We further demonstrate sophisticated modeling operations that can be implemented based on this resampling technique.
Identification of sense selection in regular polysemy using shallow features

The following work describes a method to automatically classify the sense selection of the complex type Location/Organization –which depends on regular polysemy– using shallow features, as well as a way to increase the volume of sense-selection gold standards by using monosemous data as filler. The classifier results show that grammatical features are the most relevant cues for the identification of sense selection in this instance of regular polysemy.
Structure of YidB protein from Shigella flexneri shows a new fold with homeodomain motif

The crystal structure of an uncharacterized conserved protein S4005, coded by yidB gene of Shigella flexneri (gi:30043267),1 has been determined by single wavelength anomalous diffraction (SAD) method and refined to 1.45 A. The YidB structure is the first representative of COG3753 and Pfam06078 medium size families of bacterial proteins of unknown function (Fig. 1). The yidB gene of S. flexneri, as well as yidB gene of Escherichia coli, is located between yidA and gyrB genes which are involved in DNA processing. Biochemical function of the yidA product is unknown, but it is predicted to have hydrolase/phosphotase activity.2,3 The other neighbor, gyrB, codes subunit B of DNA gyrase type II topoisomerase which controls DNA supercoiling and DNA-relaxing.4 It is often found that genes in bacteria are clustered according to their products functions.5 Thus, it is possible that the YidB protein can have functions associated with DNA. YidB is found in number of pathogenic species including Escherichia, Bordetella, Burkholderia, and Shigella species (Fig. 1). Fig. 1 Multiple sequence alignment of YidB protein from Shigella flexneri (S4005 protein, gi:30043267) and its homologs gi|75177733| (Shigella boydii), gi|67662828| (Burkholderia cenocepacia), gi|67534931| (B. vietnamiensis), gi|74019150| (B. mallei), gi|75258238| . Here we report the crystal structure of YidB protein at 1.45 A resolution. The structure represents a new protein fold and shows distant structural similarity to eukaryotic homeodomain proteins.
Compressive sensing measurement matrix construction based on improved size compatible array LDPC code

ISC-array LDPC code matrix is evolved from SC-array LDPC code matrix to improve compressive sensing performance for large-size sparse signal. When q is a prime number, no repetitive row occurs in the shift index of SC-array LDPC code matrix, ISC-array LDPC code matrix performs comparably with SC-array LDPC code matrix. When q is a non-prime number, some repetitive rows will appear in the shift index of SC-array LDPC code matrix, which results in more 4-cycles and decreases the compressive sensing performance. ISC-array LDPC code matrix outperforms SC-array LDPC code matrix by effectively reducing or even eliminating the repetitive rows according to their distribution rule, 4-cycles are removed to the maximum extent. ISC-array LDPC code matrix qualifies for compressive sensing because of satisfying RIP well. It also has good quasi-cyclic structure and supports arbitrary code lengths. The simulations verify that the optimised ISC-array LDPC code matrix is advantageous in the image reconstruction quality, the robustness to noise performance and the algorithm complexity.
Hematological and some biochemical alterations in sheep experimentally infected with Clostridium perfringens type D infection.

The study was designed to determine the hematological and biochemical changes in sheep following the experimental Clostridium perfringens type D infection. Mean leukocyte count was significantly higher (p < 0.05) between control and infected groups at 10 hours (11.2±0.3 vs 19.7±3.5), 20 hours (10.6±0.3 vs 16.9±0.2) and then started to decrease in infected group. A statistically significant increase (p < 0.05) was observed between the means within the infected for PCV at 30 hours. Mean blood glucose (74±6.7 vs 141±13.2), urea (26.3±3.5 vs 92.3±6.7) and serum creatinine 1.6±0.2 vs 7.5±1.4) levels were elevated significantly at 30 hours in group of experimentally infected animals as compared to control groups. The results of our study demonstrated that hematological values fluctuated after post experimental infection but almost remained within the normal range however, blood glucose, urea and serum creatinine levels increased significantly as the disease progressed and could be diagnostic under field conditions in animals suspected for type D enterotoxaemia.