Miracle-dz/UniFAR-FTUs huggingface dataset:
miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades

microRNAs (miRNAs) are a large class of small non-coding RNAs which post-transcriptionally regulate the expression of a large fraction of all animal genes and are important in a wide range of biological processes. Recent advances in high-throughput sequencing allow miRNA detection at unprecedented sensitivity, but the computational task of accurately identifying the miRNAs in the background of sequenced RNAs remains challenging. For this purpose, we have designed miRDeep2, a substantially improved algorithm which identifies canonical and non-canonical miRNAs such as those derived from transposable elements and informs on high-confidence candidates that are detected in multiple independent samples. Analyzing data from seven animal species representing the major animal clades, miRDeep2 identified miRNAs with an accuracy of 98.6–99.9% and reported hundreds of novel miRNAs. To test the accuracy of miRDeep2, we knocked down the miRNA biogenesis pathway in a human cell line and sequenced small RNAs before and after. The vast majority of the >100 novel miRNAs expressed in this cell line were indeed specifically downregulated, validating most miRDeep2 predictions. Last, a new miRNA expression profiling routine, low time and memory usage and user-friendly interactive graphic output can make miRDeep2 useful to a wide range of researchers.
Cloning and expression of medaka cholesterol side chain cleavage cytochrome P450 during gonadal development

Cholesterol side chain cleavage cytochrome P450 (P450scc, Cyp11a) is responsible for the first step in steroidogenesis, catalyzing the conversion of cholesterol to prognenolone. To investigate the differentiation of steroid‐producing cells and the function of sex steroids during gonadal differentiation in the teleost fish, medaka (Oryzias latipes), we isolated the full length cDNA of medaka P450scc and analyzed the expression pattern of P450scc mRNA during gonadal development using in situ hybridization. At hatching, and just after the initiation of morphological sex differentiation, we did not detect any P450scc expression in both sexes. In male gonads, expression of P450scc was detected in the interstitial somatic cells 15 days after hatching following the formation of the seminiferous tubule precursor, and was maintained in the interstitial somatic cells throughout testicular development. In the female gonad, expression of P450scc was initially detected in interstitial somatic cells 5 days after hatching. Subsequently, the expression of P450scc was continuously detected in the interstitial somatic cells of the developing ovary. This expression pattern of P450scc differed from that of female specific steroidogenic enzyme P450arom. Both P450scc and P450arom expressing cells, only P450scc expressing cells, and only P450arom expressing cells were observed. Our results suggest that expression of steroidogenic enzymes is regulated by various mechanisms during ovarian development.
SWASH: A Naive Bayes Classifier for Tweet Sentiment Identification

This paper describes a sentiment classification system designed for SemEval-2015, Task 10, Subtask B. The system employs a constrained, supervised text categorization approach. Firstly, since thorough preprocessing of tweet data was shown to be effective in previous SemEval sentiment classification tasks, various preprocessessing steps were introduced to enhance the quality of lexical information. Secondly, a Naive Bayes classifier is used to detect tweet sentiment. The classifier is trained only on the training data provided by the task organizers. The system makes use of external human-generated lists of positive and negative words at several steps throughout classification. The system produced an overall F-score of 59.26 on the official test set.
Comparison of two analyzers for measurement of plasma total carbon dioxide concentration in horses.

OBJECTIVE To determine the degree of agreement between 2 analyzers for measurement of total CO₂ concentration (ctCO₂) in equine plasma. ANIMALS 6 healthy untrained horses, 6 trained Standardbreds undergoing a simulated race protocol, and 135 trained Standardbreds at a racetrack. PROCEDURES Jugular venous blood samples were obtained from all horses. Two analyzers (commonly used analyzer A and less expensive analyzer B) were used to measure plasma ctCO₂ in each sample. Validation of both analyzers was conducted in accordance with guidelines established by the Clinical and Laboratory Standards Institute and involved characterization of linearity, total analytic error, and bias estimation. RESULTS Total analytic error (instrument SD) was 0.58 mmol/L (coefficient of variation, 1.6%) and 0.49 mmol/L (coefficient of variation, 1.4%) for analyzers A and B, respectively, when measuring an aqueous standard containing 36.0 mmol of CO₂/L. A 1 g/L decrease in plasma protein concentration corresponded to an increase in ctCO₂ measured with analyzer B of 0.065 mmol/L. A difference plot indicated that analyzer B produced values 2.7% higher than analyzer A for 103 samples from the 6 trained and exercised Standardbreds (mean plasma protein concentration, 67 g/L). CONCLUSIONS AND CLINICAL RELEVANCE Analyzer B provided adequate precision and linearity for measurement of ctCO₂ from 5 to 40 mmol/L and was therefore suitable for measuring ctCO₂ in equine plasma, provided allowances are made for changes in plasma protein concentration.
Feature extraction for analysis of ECG signals

The automated diagnostic systems employing diverse and composite features for electrocardiogram (ECG) signals were analyzed and their accuracies were determined. Because of the importance of making the right decision, classification procedures classifying the ECG signals with high accuracy were investigated. The classification accuracies of mixture of experts (ME) trained on composite features and modified mixture of experts (MME) trained on diverse features were compared. The inputs of these automated diagnostic systems were composed of diverse or composite features (power levels of the power spectral density estimates obtained by the eigenvector methods) and were chosen according to the network structures. The conclusions of this study demonstrated that the MME trained on diverse features achieved accuracy rates which were higher than that of the ME trained on composite features.
Gender, Self-Care and Functional Status Among Older Persons with Coronary Heart Disease: A National Perspective

ABSTRACT The risk and burdens of cardiovascular diseases rise in late life and shift from men to women at age 65. This study uses baseline data from the National Survey of Self-Care and Aging to assess the association of self-care and functional status of older men and women with coronary heart disease (CHD). We first compare men and women with and without CHD, then base subsequent analyses on 597 persons with CHD. Three types of self-care (behavior changes, environmental adaptations, medical equipment use) were examined, and functional status was measured as difficulty with basic, mobility, and instrumental ADLs. Regardless of gender, persons with CHD had more functional impairment and used more self-care than those without the disease. Women were more impaired and engaged in more self-care than men. Equipment use was associated with higher functioning for men and women. Behavioral changes were significant only for men, as were advanced age, non-white ethnicity, more depressive symptoms, and low physical activity for women. Education, intervention, and supportive care for older adults with CHD should consider the role of specific types of self-care in disease management and prevention of decline as well as gender differences in use of various self-care strategies.
Why neutral-grounding resistors need continuous monitoring

A resistance-grounded power system has a critical element that is often ignored-the neutral-grounding resistor. A resistance-grounded power system should have itpsilas neutral-grounding resistor continuously monitored. During a single-phase-to-ground fault, current flows from the transformer or generator winding through the faulted-phase conductor to the fault and to ground, returning to the source winding through the ground-return path and the neutral-grounding resistor. When a neutral-grounding resistor fails, the failure mode is usually open circuit leaving the ground-return path open. Current-sensing ground-fault protection, which is the type most commonly employed in a resistance-grounded system, will not operate with an open resistor, and the advantages of resistance grounding are unknowingly lost. Inadvertent operation with an ungrounded system and inoperative ground-fault protection can be avoided by using a continuous neutral-grounding-resistor monitor. This paper reviews the benefits of resistance grounding, compares continuous resistor monitoring with planned-maintenance testing and inspection, and defines the characteristics required of a neutral-grounding-resistor-monitor. Three case studies are presented that show the need for continuous monitoring of the neutral-grounding resistor.
Performance analysis of adaptive step-size least mean modulus-Newton algorithm

This paper first reviews least mean modulus-Newton (LMM-Newton) algorithm for complex-domain adaptive filters. The LMM-Newton algorithm is effective in making the convergence of an adaptive filter with a highly correlated input as fast as that for the LMM algorithm with a White & Gaussian filter input. However, the filter convergence for the LMM-Newton algorithm is still much slower than for the LMS algorithm. Then, the paper introduces a generalized error modulus (“p-modulus”) and proposes a new adaptive step-size (ASS) control algorithm to be combined with the LMM-Newton algorithm to further improve the convergence speed. Analysis of the ASS-LMM-Newton algorithm is developed for calculating transient and steady-state behavior. Through experiment with simulations and theoretical calculations of filter convergence, we find that the filter convergence is almost the same for any value of p of “p-modulus. ” We demonstrate effectiveness of the proposed ASS-LMM-Newton algorithm, while preserving the robustness of the LMM algorithm against impulsive observation noise. Good agreement between simulated and theoretical convergence validates the analysis.
RSA algorithm optimization on assembler of TI TMS320C54x signal processors

Possible optimization techniques for RSA algorithm realization on assembler of Texas Instruments TMS320C54x family of signal processors are considered. Obtained results justify the use of the proposed optimization methods and also show that the TMS320C54x family of signal processors is suitable for the RSA algorithm realization. Therefore, they are proposed for realization of some coprocessor module in computer networks with “client-server” architecture requiring some public-key cryptographic applications.
Pharmaceutical particulate carriers: Lipid - based carriers -

Drug delivery research areas is continuously broaden and modified as a results of the realization of many factors (such as poor drug solubility and/or absorption, rapid metabolism, high fluctuation in the drug plasma level and variability) which play major role in adversely affecting in vivo results, in conventional drug delivery system. Lipids are one of the basic building blocks of biological membranes. Nanoscale-based delivery strategies are beginning to make a significant impact on global pharmaceutical planning and marketing. Among the approaches for exploiting nanotechnology developments in medicine, various nanoparticulates offer some unique advantages as pharmaceutical carriers in delivery systems and image enhancement agents. The review illustrates the various classes of particulate lipid-based carriers among them; lipoproteins, lipid nanoparticles either; solid lipid nanoparticles, nanostructured lipid carriers, or lipid drug conjugates, lipid nanocapsules, and liposomes. Lipid-based particulate carriers’ applications in various areas were also addressed.
Circulation and phylogenetic relationship of chicken and turkey-origin astroviruses detected in domestic ducks (Anas platyrhynchos domesticus)

The natural occurrence of chicken and turkey-origin astroviruses in domestic ducks (Anas platyrhynchos domesticus) is described. Twenty-two duck flocks were covered by this research. The liver, spleen, kidney and intestines were sampled and tested by reverse-transcription polymerase chain reaction for the presence of avian nephritis virus (ANV), chicken astrovirus (CAstV), turkey astrovirus (TAstV)-1, TAstV-2 and duck astrovirus. The astrovirus infection was confirmed in multiple organ samples from 59.1% of tested flocks. CAstV was detected in one flock, TAstV-2 in three flocks and ANV in 10 flocks. The molecular and phylogenetic analysis of the small open reading frame (ORF) 1b fragment (130 nucleotides) of all chicken and turkey-origin astroviruses detected in ducks showed that ANV-sequence group was more distant from CastV, TAstV-1 and TAstV-2 sequences, which formed a separate, more related group. ANV sequences were divided into three subgroups, suggesting that several types of ANV were circulating in Croatian duck flocks. The comparison of the partial ORF 1b (254 nucleotides) duck ANV sequences with 21 ANVs detected in various avian species (chickens, turkeys, geese, guinea fowl and pigeons) revealed they shared the higher nucleotide (95.6 to 97.2%) and amino acid (98.8 to 100%) identity with two ANV-2-like sequences from chickens (GA-SEP-A451-05 and GA-CK-SEP ANV-364-2005). Phylogenetic neighbour-joining tree analysis based on the same nucleotide alignment, and performed using the Jukes-Cantor method, clustered the compared sequences into three groups. All analysed duck ANV sequences showed a close phylogenetic relationship with chicken-origin ANVs. Additional work is required to determine the significance and pathogenicity of chicken and turkey-origin astroviruses in domestic ducks.
Coordinated Upregulation of Mitochondrial Biogenesis and Autophagy in Breast Cancer Cells: The Role of Dynamin Related Protein-1 and Implication for Breast Cancer Treatment

Overactive mitochondrial fission was shown to promote cell transformation and tumor growth. It remains elusive how mitochondrial quality is regulated in such conditions. Here, we show that upregulation of mitochondrial fission protein, dynamin related protein-1 (Drp1), was accompanied with increased mitochondrial biogenesis markers (PGC1α, NRF1, and Tfam) in breast cancer cells. However, mitochondrial number was reduced, which was associated with lower mitochondrial oxidative capacity in breast cancer cells. This contrast might be owing to enhanced mitochondrial turnover through autophagy, because an increased population of autophagic vacuoles engulfing mitochondria was observed in the cancer cells. Consistently, BNIP3 (a mitochondrial autophagy marker) and autophagic flux were significantly upregulated, indicative of augmented mitochondrial autophagy (mitophagy). The upregulation of Drp1 and BNIP3 was also observed in vivo (human breast carcinomas). Importantly, inhibition of Drp1 significantly suppressed mitochondrial autophagy, metabolic reprogramming, and cancer cell viability. Together, this study reveals coordinated increase of mitochondrial biogenesis and mitophagy in which Drp1 plays a central role regulating breast cancer cell metabolism and survival. Given the emerging evidence of PGC1α contributing to tumor growth, it will be of critical importance to target both mitochondrial biogenesis and mitophagy for effective cancer therapeutics.
Observation of Polycrystalline Solar Cell Using a Laser-SQUID Microscope

Laser-SQUID microscopy is a technique for nondestructive inspection of the electrical properties of semiconductors. In laser-SQUID microscopy, a photocurrent is induced by a laser with an energy larger than the band gap of the semiconductor sample. The magnetic field induced by this photocurrent is detected by a SQUID. In our experiment the laser was focused on the surface of the sample, and a high-temperature superconducting SQUID was positioned behind the sample to detect the magnetic field from the photocurrent. The sample was raster scanned while the relative position of the SQUID and laser spot was fixed. The sample used was a commercially available polycrystalline silicon solar cell containing a p-n junction. It had several line electrodes and a transport electrode layer on the surface, and the reverse side was covered with a metal electrode. We studied a piece of this polycrystalline solar cell using a 1065 nm laser. Magnetic field induced by the laser was observed successfully. The produced image shows the inhomogeneity of the solar cell.
Learning Spatial Interest Regions from Videos to Inform Action Recognition in Still Images

Common approaches to human action recognition from im- ages rely on local descriptors for classication. Typically, these descrip- tors are computed in the vicinity of key points which either result from running a key point detector or from dense or random sampling of pixel coordinates. Such key points are not a-priori related to human activi- ties and thus of limited information with regard to action recognition. In this paper, we propose to identify action-specic key points in images using information available from videos. Our approach does not require manual segmentation or templates but applies non-negative matrix fac- torization to optical ow elds extracted from videos. The resulting basis ows are found to to be indicative of action specic image regions and therefore allow for an informed sampling of key points. We also present a generative model that allows for characterizing joint distributions of regions of interest and a human actions. In practical experiments, we determine correspondences between regions of interest that were auto- matically learned from videos and manually annotated locations of hu- man body parts available from independent benchmark image data sets. We observe high correlations between learned interest regions and body parts most relevant for dierent actions.
Repetition rate and wavelength tunable all-optically mode-locked fiber ring laser based on a reflective semiconductor optical amplifier

A repetition rate and wavelength tunable fiber ring laser that utilizes a reflective semiconductor optical amplifier as both a gain and mode-locking element is presented. 10.3 ps pulses at 10 GHz repetition rate are obtained across a 30 nm tuning range covering the entire C-band. The repetition rate is tunable up to 30 GHz via rational harmonic mode-locking.
6-Azido- and 6-aminoflavins as active-site probes of flavin enzymes.

6-Azidoflavins have been bound to the apoproteins of five representative flavoproteins and their properties, before and after light irradiation, compared with those of the same proteins containing the appropriate 6-aminoflavin. In the dark the 6-azidoflavoproteins are quite stable, except for L-lactate oxidase, where spontaneous conversion to the 6-amino-FMN enzyme occurs slowly at pH 7. 6-Azido-FMN Old Yellow Enzyme is converted to the 6-amino-FMN enzyme by aerobic turnover with NADPH, and 6-azido-FAD D-amino acid oxidase is converted to the 6-amino-FAD enzyme by treatment with D-alanine. Light irradiation of 6-azidoriboflavin bound to riboflavin-binding protein does not result in any covalent fixation of the flavin to the protein. Light irradiation of 6-azido-FMN flavodoxin gives only a small amount of covalent linkage. In contrast, 6-azido-FMN Old Yellow Enzyme undergoes a very facile light-induced change, in which approximately 50% of the flavin is attached in a stable covalent linkage to the protein. The resulting flavoprotein form has lost the ability to bind phenols, a distinctive characteristic of the native enzyme; it does, however, bind NADPH, but the latter cannot reduce the covalently bound flavin. 6-Azido-FAD D-amino acid oxidase also undergoes a facile light modification, in which almost quantitative fixation of the flavin to the protein takes place. The resulting flavoprotein cannot bind benzoate, an active-site ligand for the native enzyme, nor is it reduced anaerobically by D-alanine. The covalent linkage is fairly labile and is destroyed on denaturation of the protein. (ABSTRACT TRUNCATED AT 250 WORDS)
Cell assemblies in neuronal recordings : identification and study through the inference of functional network models and statistical physics techniques

This thesis illustrates a research on cell assemblies, groups of closely connected, synchronously activating neurons, which are thought to be the units of memory. After a review of the main experimental and theoretical advances in this field, and of the techniques of statistical physics and inference for the study of interacting neurons, a new method to unveil cell assemblies from neuronal data is illustrated and applied to multi-electrode recordings in the prefrontal cortex of rats during performance of a task and during the preceding and following sleep epochs. The method is based on the inference of an Ising network of effective interactions between the neurons and on the simulation of the inferred model in the presence of a global uniform drive: as the drive increases, configurations of high activity (cell assemblies) are unveiled, which activate in the data on time scales of tens of ms, in the presence of transient stimuli. The assemblies are robust with respect to noise. Comparisonof the interaction networks and of the results of the simulations across the three experimental phases reveals empirical rules for the modification of cell assemblies. The inferred model is also exploited to estimate the reactivation (replay) of the cell assemblies during sleep, important for memory consolidation. Inference and sampling of a generalized linear model show that there is not a specific order of activation of the neurons in the groups. It is finally discussed an application of descriptive statistics to the study of synaptic plasticity of neurons in vitro in an optogenetic framework.
The Weltmodell: A Data-Driven Commonsense Knowledge Base

We present the Weltmodell, a commonsense knowledge base that was automatically generated from aggregated dependency parse fragments gathered from over 3.5 million English language books. We leverage the magnitude and diversity of this dataset to arrive at close to ten million distinct N-ary commonsense facts using techniques from open-domain Information Extraction (IE). Furthermore, we compute a range of measures of association and distributional similarity on this data. We present the results of our efforts using a browsable web demonstrator and publicly release all generated data for use and discussion by the research community. In this paper, we give an overview of our knowledge acquisition method and representation model, and present our web demonstrator.