Miracle-dz/UniFAR-FTUs huggingface dataset:
Erythropoietin attenuates hyperoxia-induced lung injury by upregulating epidermal growth factor-like domain 7 in newborn rats

The aim of the present study was to observe the effects of recombinant human erythropoietin (rhEPO) on the expression of epidermal growth factor-like domain 7 (EGFL7) and cell apoptosis in lung tissue following hyperoxic lung injury in newborn rats. The 96 Sprague-Dawley newborn rats were randomly divided into 4 groups (n=24) as follows: Room air-exposed control group, room air-exposed rhEPO-treated group, hyperoxia-exposed group and the hyperoxia-exposed rhEPO-treated group. Pups (n=8) from each group were sacrificed on postnatal days 3, 7 and 14. The pulmonary morphometric and microvessel density changes were observed. In addition, the mRNA and protein expression levels of EGFL7, B-cell lymphoma 2 (Bcl-2) and Bcl-2-like protein 4 (Bax) in lung tissue samples were measured. The rats in the hyperoxia-exposed group exhibited alveolar and pulmonary vascular dysplasia, as well as low mRNA and protein expression levels of EGFL7 and Bcl-2, in addition to high level of Bax in the lung tissue samples when compared with the room air-exposed control group (P<0.05). However, in the hyperoxia-exposed rhEPO-treated group the lung histopathology was improved, and the protein and mRNA expression levels of EGFL7 and Bcl-2 were increased compared with the hyperoxia-exposed group (P<0.05). Furthermore, the expression level of Bax was lower than that of the hyperoxia-exposed group (P<0.05). The present study demonstrated that rhEPO promotes alveolar development and increases pulmonary vascular density by upregulating the expression level of EGFL7 in hyperoxia-induced lung injury of newborn rats.
Antioxidant and Antibacterial Potential of Silver Nanoparticles: Biogenic Synthesis Utilizing Apple Extract

The advancement of the biological production of nanoparticles using herbal extracts performs a significant role in nanotechnology discipline as it is green and does not engage harsh chemicals. The objective of the present investigation was to extract flavonoids in the mode of apple extract and synthesize its silver nanoparticles and ultimately nanoparticles loading into hydrogels. The presence of flavonoids in apple extract was characterized by preliminary testing like dil. ammonia test and confirmatory test by magnesium ribbon test. The synthesized silver nanoparticles were characterized using UV spectroscopy, particle size and surface morphology, and zeta potential. Silver nanoparticles loaded hydrogels were evaluated for physical appearance, pH, viscosity, spreadability, porosity, in vitro release, ex vivo permeation, and antibacterial (E. coli and S. aureus) and antioxidant studies (DPPH radical scavenging assay). Well dispersed silver nanoparticles below were observed in scanning electron microscope image. Hydrogels displayed in vitro release of 98.01% ± 0.37% up to 24 h and ex vivo permeation of 98.81 ± 0.24% up to 24 h. Hydrogel effectively inhibited the growth of both microorganism indicating good antibacterial properties. The value of percent radical inhibition was 75.16% ± 0.04 revealing its high antioxidant properties. As an outcome, it can be concluded that antioxidant and antiageing traits of flavonoids in apple extract plus biocidal feature of silver nanoparticles can be synergistically and successfully utilized in the form of hydrogel.
Stationary Ballistic 'V' States for Preferred Motions of Many Particles

We use the discrete kinetic theory with the free-orientation parameter being fixed ($\pi/4$) to derive the macroscopic velocity field for many particles flowing through a microdomain. Our results resemble qualitatively other hydrodynamical solutions. The V-shaped velocity field changes as the dominant physical parameter (Knudsen number) varies. We also briefly discuss the possible mechanism due to the entropy production along the boundaries.
Temporal Code-Driven Stimulation: Definition and Application to Electric Fish Signaling

Closed-loop activity-dependent stimulation is a powerful methodology to assess information processing in biological systems. In this context, the development of novel protocols, their implementation in bioinformatics toolboxes and their application to different description levels open up a wide range of possibilities in the study of biological systems. We developed a methodology for studying biological signals representing them as temporal sequences of binary events. A specific sequence of these events (code) is chosen to deliver a predefined stimulation in a closed-loop manner. The response to this code-driven stimulation can be used to characterize the system. This methodology was implemented in a real time toolbox and tested in the context of electric fish signaling. We show that while there are codes that evoke a response that cannot be distinguished from a control recording without stimulation, other codes evoke a characteristic distinct response. We also compare the code-driven response to open-loop stimulation. The discussed experiments validate the proposed methodology and the software toolbox.
The Asian Currency Crisis

In a fascinating account of the financial disaster which engulfed Southeast and East Asia in 1997, Gerald Tan explains the causes, events, reactions to, and effects of, the Asian currency crisis. Starting with the crash of the Thai Baht, Professor Tan traces the chain of events and details the economic, social and political consequences in all the countries involved. The responses of the major economic institutions like the World Bank and the IMF are described. He also includes a chapter on the Asian economic miracle in the years before the crash, and asks whether that sort of growth was sustainable anyway. The final chapters deal with the lessons to be learnt and the possible paths to recovery. This is essential reading for anyone in the fields of finance, economics or politics, and it is also interesting and accessible to the lay-reader.
Analysis of Neural Oscillations on Drosophila's Subesophageal Ganglion Based on Approximate Entropy

The suboesophageal ganglion (SOG), which connects to both central and peripheral nerves, is the primary taste-processing center in the Drosophila’s brain. The neural oscillation in this center may be of great research value yet it is rarely reported. This work aims to determine the amount of unique information contained within oscillations of the SOG and describe the variability of these patterns. The approximate entropy (ApEn) values of the spontaneous membrane potential (sMP) of SOG neurons were calculated in this paper. The arithmetic mean (MA), standard deviation (SDA) and the coefficient of variation (CVA) of ApEn were proposed as the three statistical indicators to describe the irregularity and complexity of oscillations. The hierarchical clustering method was used to classify them. As a result, the oscillations in SOG were divided into five categories, including: (1) Continuous spike pattern; (2) Mixed oscillation pattern; (3) Spikelet pattern; (4) Busting pattern and (5) Sparse spike pattern. Steady oscillation state has a low level of irregularity, and vice versa. The dopamine stimulation can distinctly cut down the complexity of the mixed oscillation pattern. The current study provides a quantitative method and some critera on mining the information carried in neural oscillations.
Textual risk mining for maritime situational awareness

In this paper, we propose an auxiliary Machine Learning (ML) and Natural Language Processing (NLP) integrated system for maritime situational awareness (MSA) operations. We bring into account a new and influential asset - human intuition and perception - to the existing semi-automated decision support systems that mostly rely on numerical data collected by electronic sensors or cameras located either directly on the vessels or in the maritime command-and-control centers. For our project, we gathered weekly textual reports spanning twelve months from the United States Worldwide Threats to Shipping Reports repository that belongs to the National Geospatial-Intelligence Agency (NGA), We considered the maritime incident reports written by human operators as a valuable and accessible unstructured textual input source in which a span of text1 is called “risk” if it expresses one of the following kinds of vessel incidents: fired, robbed, boarded, hijacked, attacked, chased, approached, kidnapped, boarding attempted, suspiciously approached or clashed with. Our approach benefits from probability distributions of some useful features annotated based on a list of lexicons that contain expressions denoting vessel types, risks types, risk associates, maritime geographical locations, dates and times. These distributions are captured and used to anchor the span of “risks” as they are described in the textual reports. After some preprocessing steps that include tokenization, named entity extraction and part-of-speech tagging, the textual risk mining system applies a variety of sequence classification algorithms, e.g., Conditional Random Fields, Conditional Markov Models and Hidden Markov Models in order to compare the risk classification performance. Empirical results show that our NLP/ML-based system can extract variable-length risk spans from the textual reports with about 90% correctness.
An Analysis of Different Variations of Ant Colony Optimization to the Minimum Weight Vertex Cover Problem

Ant colony optimization (ACO) has previously been applied to the Minimum Weight Vertex Cover Problem with very good results. The performance of the ACO algorithm can be improved with the use of different variations of the basic Ant Colony System algorithm, like the use of Elitism, Rank based approach and the MinMax system. In this paper, we have made an analysis of effectiveness of these variations applied to the Minimum Weight Vertex Covering Problem for different problem cases. This analysis is done by the observation of several properties of acquired solutions by these algorithms like best found solution, average solution quality, dispersion and distribution of solutions. Key-Words: Ant Colony, Minimum Weight Vertex Cover, Optimization Problems, Population Based Algorithms
BASAL THYROID FUNCTIONS IN FIRST EPISODE DEPRESSIVE ILLNESS : A CONTROLLED STUDY

Significant but subtle abnormalities in the thyroid functions in depressive patients, have been reported. Basal thyroid functions of 33 drug naive depressive patients having first episode of illness were compared with 31 healthy matched controls. The mean value of total thyroxin (T3) was significantly higher in depressives. Total triiodothyronine (T3) was lower in depressive patients but the difference was not significant. The mean value of thyroid stimulating hormone (TSH) was comparable in the two groups No significant difference was found with respect to total T4 and total T3 when depressive patients with various subtypes of depression were compared. But depressive patients with psychotic features had significantly higher mean value of TSH as compared to those without them. The findings are discussed in relation to the available literature.
Event-Based Clustering for Reducing Labeling Costs of Event-related Microposts

Automatically identifying the event type of event-related information in the sheer amount of social media data makes machine learning inevitable. However, this is highly dependent on (1) the number of correctly labeled instances and (2) labeling costs. Active learning has been proposed to reduce the number of instances to label. Albeit the thematic dimension is already used, other metadata such as spatial and temporal information that is helpful for achieving a more fine-grained clustering is currently not taken into account. In this paper, we present a novel event-based clustering strategy that makes use of temporal, spatial, and thematic metadata to determine instances to label. An evaluation on incident-related tweets shows that our selection strategy for active learning outperforms current state-of-the-art approaches even with few labeled instances.
Argumentation and the decision making process

Following your need to always fulfil the inspiration to obtain everybody is now simple. Connecting to the internet is one of the short cuts to do. There are so many sources that offer and connect us to other world condition. As one of the products to see in internet, this website becomes a very available place to look for countless argumentation and the decision making process sources. Yeah, sources about the books from countries in the world are provided.
IARG-AnCora: Annotating the AnCora corpus with implicit arguments

IARG-AnCora is an ongoing project which aim is to annotate the implicit arguments of deverbal nominalizations in AnCora corpus. This corpus will be the basis for systems of automatic semantic role labeling based on machine learning techniques. Semantic analyzers are essential components in the current applications of language technologies, in which it is important to obtain a deeper understanding of the text to make inferences on the highest level in order to obtain qualitative improvements in the results.
Sorting on the labour market: A literature overview and theoretical framework

In the literature there are basically two main approaches that explain the positive link between the level of education and wages: the human-capital theory and the signalling/screening (collectively known as sorting) theory. We highlight the similarity and differences between these theories and present a general theoretical model of screening with productivity-enhancing effects of education from which we derive four empirically testable hypothesis.
Energy-Efficient Monitoring of Mobile Objects with Uncertainty-Aware Tolerances

In location-based services, continuous queries are often employed to monitor the locations of mobile objects that are determined by sensing devices like GPS receivers. Due to limited battery resources, it is important for these objects to acquire and report location data only if necessary. We study how these energy- consuming operations can be reduced with a controlled impact on query accuracy of continuous range queries (CRQs). Specifically, we develop uncertainty- aware tolerances, which are user-defined error bounds that provide correctness guarantees, with consideration of different sources of data uncertainty: sensing uncertainty, sampling uncertainty, and communication delay. Novel algorithms are developed to control carefully when an object should acquire and update a location, while satisfying these tolerances. Extensive simulations validate the effectiveness of our methods.
Survey on Fault Operation on Multilevel Inverters

This paper is related to faults that can appear in multilevel (ML) inverters, which have a high number of components. This is a subject of increasing importance in high-power inverters. First, methods to identify a fault are classified and briefly described for each topology. In addition, a number of strategies and hardware modifications that allow for operation in faulty conditions are also presented. As a result of the analyzed works, it can be concluded that ML inverters can significantly increase their availability and are able to operate even with some faulty components.
RESEARCH NOTES AND COMMENTARIES DOES INTERFIRM MODULARITY COMPLEMENT IGNORANCE? A FIELD STUDY OF SOFTWARE OUTSOURCING ALLIANCES

Knowledge-intensive outsourcing alliances present outsourcers with a tension between simultaneously sharing enough private knowledge to accomplish alliance goals and safeguarding such knowledge against misappropriation. This study explores the perspective that increasing interfirm modularity lowers the need for interfirm knowledge sharing. Put another way, modularity complements outsourcee ignorance. Analyses of data on 209 alliances between U.S. firms and software services firms in Russia, Ireland, and India provide strong support for this idea. Our theoretical elaboration and empirical testing of the complementarities between modularity and outsourcee ignorance has significant implications for strategy theory, which are also discussed. Copyright  2008 John Wiley & Sons, Ltd.
Circular processing of the hue variable - a particular trait of colour image processing

Novel tools for colour image processing are presented. Unlike many magnitudes dealt with in engineering, the hue variable of a colour image is circular and requires a special treatment. Special techniques have been advanced in statistics for the analysis of data from angular variables; likewise in image processing for the processing of the hue variable. We give a definition of the median and of the range of angular data and apply their running versions on images to smooth them and to detect hue edges. We also give definitions of hue morphology; one based on the topological concept of lifting and on grey level morphology; another definition is wholly given in a circular context.
Epithelial-Mesenchymal Transition Phenotype Is Associated with Clinicopathological Factors That Indicate Aggressive Biological Behavior and Poor Clinical Outcomes in Invasive Breast Cancer

Purpose Cancer tissue may display a wide spectrum of expression phenotypes of epithelial-mesenchymal transition (EMT)-related proteins. The purpose of this study was to investigate the clinical significance of EMT phenotypes in breast cancer. Methods We evaluated the expression pattern of the EMT-related proteins E-cadherin and fibronectin in samples from 1,495 patients with invasive breast carcinoma (IBC) on tissue microarrays using immunohistochemistry to investigate the clinical significance of EMT phenotypes in IBC. EMT phenotypes were divided into complete type (E-cadherin-negative/fibronectin-positive), incomplete type (hybrid type, E-cadherinpositive/fibronectin-positive; null type, E-cadherin-negative/fibronectin-negative), and wild-type (E-cadherin-positive/fibronectin-negative). We analyzed the correlation of EMT phenotype with clinicopathological factors and patient survival. Results Loss of E-cadherin was observed in 302 patients (20.2%), and fibronectin was expressed in the cancer cells of 354 patients (23.7%). In total, 64 (4.3%), 290 (19.4%), 238 (15.9%), and 903 (60.4%) samples were categorized as complete, hybrid, null, and wild-type, respectively. The complete EMT phenotype exhibited significant associations with young age (p=0.017), advanced pT (p<0.001) and pN (p<0.001) stages, higher histological grade (p<0.001), lymphovascular invasion (p<0.001), and triple negativity (p<0.001). Patients with complete and hybrid EMT phenotypes had poorer overall survival (OS) and disease-free survival (DFS) than those with the wild-type phenotype (OS, p=0.001; DFS, p<0.001). In multivariate analysis, the hybrid EMT phenotype was an independent prognostic factor for DFS in patients with IBC (p=0.032). Conclusion EMT phenotypes exhibited significant associations with clinicopathological factors indicating aggressive biologic behavior and poor outcome in patients with IBC.
EUS-Guided Biliary Drainage

The echoendoscopic biliary drainage is an option to treat obstructive jaundices when ERCP drainage fails. These procedures compose alternative methods to the side of surgery and percutaneous transhepatic biliary drainage, and it was only possible by the continuous development and improvement of echoendoscopes and accessories. The development of linear setorial array echoendoscopes in early 1990 brought a new approach to diagnostic and therapeutic dimenion on echoendoscopy capabilities, opening the possibility to perform punction over direct ultrasonographic view. Despite of the high success rate and low morbidity of biliary drainage obtained by ERCP, difficulty could be found at the presence of stent tumor ingrown, tumor gut compression, periampulary diverticula, and anatomic variation. The echoendoscopic technique starts performing punction and contrast of the left biliary tree. When performed from gastric wall, the access is made through hepatic segment III. From duodenum, direct common bile duct punction. Dilatation is required before stent introduction, and a plastic or metallic stent is introduced. This phrase should be replaced by: diathermic dilatation of the puncturing tract is required using a 6F cystostome. The technical success of hepaticogastrostomy is near 98%, and complications are present in 36%: pneumoperitoneum, choleperitoneum, infection, and stent disfunction. To prevent bile leakage, we have used the 2 stent techniques, the first stent introduced was a long uncovered metallic stent (8 or 10 cm), and inside this first stent a second fully covered stent of 6 cm was delivered to bridge the bile duct and the stomach. Choledochoduodenostomy overall success rate is 92% and described complications include, in frequency order, pneumoperitoneum and focal bile peritonitis, present in 19%. By the last 10 years, the technique was especially performed in reference centers, by ERCP experienced groups, and this seems to be a general guideline to safer procedure execution.
Vision Based Navigation System of Intelligent Vehicles: A Robust Object Tracking Approach

Object tracking using vision technology is one of the important and complex functions in computer vision. It should become more challenge in case of there are partial occlusions and significant clutter. A mean shift procedure embedded approach for vehicle and pedestrian tracking under real road scenes is presents. A combined hue and saturation of HSI color model and local orientation information are extracted and constructed to represent the target features since it is more robust to illumination than only RGB color space. The mean shift procedure is employed to fast searching the mode of the potential object in a neighborhood of current video sequence.Meanwhile, a global motion compensation is considered for improve the robust and real-time of the tracking procedure.Some examples are investigated and used to evaluate the proposed approach. Experimental results demonstrate that the proposed approach is robust and validate in complicated real scenes.
Categorizing Host-Dependent RNA Viruses by Principal Component Analysis of Their Codon Usage Preferences

Viruses have to exploit host transcription and translation mechanisms to replicate in a hostile host cellular environment, and therefore, it is likely that the infected host may impose pressure on viral evolution. In this study, we investigated differences in codon usage preferences among the highly mutable single strain RNA viruses which infect vertebrate or invertebrate hosts, respectively. We incorporate principal component analysis (PCA) and k-mean methods to clustering viruses infected with different type of hosts. The relative synonymous codon usage (RSCU) indices of all genes in 32 RNA viruses were calculated, and the correlation of the RSCU indices among different viruses was analyzed by the PCA. Our results show a positive correlation in codon usage preferences among viruses that target the same host category. Results of k-means clustering analysis further confirmed the statistical significance of this study, demonstrating that viruses infecting vertebrate hosts have different codon usage preferences to those of invertebrate viruses. Based on the analysis of the effective number of codons (ENC) in relation to the GC-content at the synonymous third codon position (GC3s), we further identified that mutational pressure was the dominant evolution driving force in making the different codon usage preferences. This study suggests a new and effective way to characterize host-dependent RNA viruses based on the codon usage pattern.