Miracle-dz/UniFAR-FTUs huggingface dataset:
A high-performance Z-source inverter with low capacitor voltage stress and small inductance

A novel high-performance Z-source inverter is proposed in this paper. It can obtain the same voltage gain with low Z-source network capacitor voltage stress than conventional one and has inherent limitation to inrush-current at startup. Moreover, it can work in a very wide range load even with small inductance of the Z-source network inductor. Therefore, compared with the conventional Z-source inverters, the proposed converter not only has lower cost but also has smaller weight and size. The operating principle and parameters design of the proposed converter are analyzed. Simulation and experimental results are presented to verify the validity of the proposed high-performance Z-source inverter.
PEMODELAN INDEKS HARGA SAHAM GABUNGAN (IHSG) MENGGUNAKAN MULTIVARIATE ADAPTIVE REGRESSION SPLINES (MARS)

Composite Stock Price Index (CSPI) is a historical information about the movement of joint-stock until a certain date. CSPI is often used by inventors to see a representation of the overall stock price, it can analyze the possibility of increase or decrease in stock price. Following old examination, some economy macro variables affecting CSPI is inflation, interest rate,and exchange rate the Rupiah againts the u.s.dollar. MARS method is particularly suitable to analyze a CSPI because many variables that affected. Furthermore, in the real world is very difficult to find a spesific data pattern. The analysis is MARS analysis. The purpose is an obtained a MARS model to be used to analyze the CSPI movement’s. Selection MARS model can be used CV method. The MARS model is an obtained from combination of BF, MI, dan MO. In this case, happens the best models with BF=9, MI=2, dan MO=1. Accuracy for MARS model can see MAPE values is 14,32588% it means the model can be used. Keyword: CSPI, economy macro, MARS, CV, MAPE.
Surgical site infections: epidemiology and prevention.

BACKGROUND The overall incidence of surgical site infection (SSI) has been estimated to be 2.8% in the United States, according to the U.S. Centers for Disease Control and Prevention, although the data may underrepresent the true incidence of such infections owing to inherent problems with voluntary self-reporting by surgeons of infections that occur in the ambulatory surgical setting. This review analyzes the reasons why patients are at risk and what can be done to minimize the risk. METHODS Review of the pertinent English-language literature. RESULTS Factors that contribute to the development of SSI include those that arise from the patient's health status, those that relate to the physical environment where surgical care is provided, and those that result from clinical interventions that increase the patient's inherent risk. Careful patient selection and preparation, including the judicious use of antibiotic prophylaxis, can decrease the overall risk of infection, especially following clean-contaminated and contaminated operations. However, antibiotics are not a substitute for attention to detail and meticulous surgical technique, and can increase the risk of nosocomial infection following injudicious use (that is, overuse). CONCLUSION Most SSIs can be attributed to risk factors inherent to the patient, rather than to inherently flawed surgical care. Nonetheless, the surgeon can minimize the risk to the patient through careful patient selection and preparation, attention to technical details and awareness of the operating room environment, and the selective use of short-duration, narrow-spectrum antibiotic prophylaxis for appropriate patients.
Artificial neural networks for automatic ECG analysis

The analysis of ECGs can benefit from the wide availability of computing technology. This paper presents some results achieved by carrying out the classification tasks of equipment integrating the most common features of the ECG analysis: arrhythmia, myocardial ischemia, chronic alterations. Several ANN architectures are implemented, tested, and compared with competing alternatives. The approach, structure, and learning algorithm of ANNs are designed according to the features of each particular classification task. The trade-off between the time consuming training of ANNs and their performance is also explored. Data pre- and post-processing efforts for system performance are critically tested. The crucial role of these efforts for the reduction of input space dimensions, for a more significant description of the input features, and for improving new or ambiguous event processing is also documented. Finally, algorithm assessment is done on data coming from available ECG databases.
TRIASSIC TO TERTIARY STRATIGRAPHY NEAR CERRO DE PASCO, PERU

Near Cerro de Pasco, Peru, thrust faulting and close folding bring an eastern facies of lower Mesozoic limestones, 9500 feet thick, close to beds on the west oe the same age and one quarter as thick. The strata are Upper Triassic and may extend into the lower Liassic. Fossils are abundant but conclusive only as to the oldest beds, of late Triassic age. Original difference in thickness of the two facies is due to abnormal accumulation in a narrow north-trending negative zone east of Cerro de Pasco, with rapidly diminishing thickness and time continuity to the west. Tertiary strata, which have been confused with the Triassic in recent works, accumulated in low-level intermontane basins on folded and faulted Mesozoic and Paleozoic formations. Strong deformation at the end of the Cretaceous was followed, after the accumulation of Tertiary continental deposits, by thrust faulting and isoclinal folding in the early Tertiary. One member of the Tertiary sequence is a fanglomerate, study of which suggests a short period of movement between the two major ones. Minor warping is indicated toward the close of the Permian and Jurassic periods. Intrusive and extrusive igneous activity apparently closely followed early Tertiary deformation.
Measuring the health of antivirus ecosystems

The number and variety of computer threats has fueled a digital arms race, resulting in a complex software ecosystem around malware and antivirus (anti-malware) products. While there has been significant past work in benchmarking antivirus (AV) products against each other, how healthy is the overall AV software ecosystem? Using data collected from Microsoft Windows Malicious Software Removal Tool (MSRT) running on more than one billion machines, we develop ecosystem health measures based upon infection rates, product diversity, market dominance, and activity status. Our study shows that while a diverse group of products is used and the vast majority of them are running properly, there is also significant churn in product usage which may indicate dissatisfaction with current products. While further work is needed to better understand these patterns, this study shows the potential power of an ecosystem health-based approach to studying AV performance in practice.
Social Capital and Disaster Recovery: Evidence from Sichuan Earthquake in 2008

Social capital helps reduce adverse shocks by facilitating access to transfers. This study examines how various measures of social capital are associated with disaster recovery from 2008 Sichuan earthquake. We find that households having a larger Spring Festival network in 2008 do better in housing reconstruction. A larger network significantly increases the amount of government aid received for housing reconstruction. With regards to how Spring Festival network channels more government aid to the household, the results show that a larger network increases the number of people showing up to offer monetary and material support, which is linked to more government aid received. This suggests that Spring Festival network members assist the quake-affected households to apply for and obtain government aid. As for other measures of social capital, connections with government officials and communist party membership do not significantly contribute to disaster recovery. Human capital, measured by the years of schooling of household head, is also not positively correlated with housing reconstruction.
Molecular Mode of Action and Role of TP53 in the Sensitivity to the Novel Epothilone Sagopilone (ZK-EPO) in A549 Non-Small Cell Lung Cancer Cells

Sagopilone, an optimized fully synthetic epothilone, is a microtubule-stabilizing compound that has shown high in vitro and in vivo activity against a broad range of human tumor models. We analyzed the differential mechanism of action of sagopilone in non-small cell lung cancer cell lines in vitro. Sagopilone inhibited proliferation of non-small cell lung cancer cell lines at lower nanomolar concentration. The treatment with sagopilone caused strong disturbances of cellular cytoskeletal organization. Two concentration-dependent phenotypes were observed. At 2.5 nM sagopilone or 4 nM paclitaxel an aneuploid phenotype occur whereas a mitotic arrest phenotype was induced by 40 nM sagopilone or paclitaxel. Interestingly, treatment with 2.5 nM of sagopilone effectively inhibited cell proliferation, but - compared to high concentrations (40 nM) - only marginally induced apoptosis. Treatment with a high versus a low concentration of sagopilone or paclitaxel regulates a non-overlapping set of genes, indicating that both phenotypes substantially differ from each other. Genes involved in G2/M phase transition and the spindle assembly checkpoint, like Cyclin B1 and BUBR1 were upregulated by treatment with 40 nM sagopilone. Unexpectedly, also genes involved in DNA damage response were upregulated under that treatment. In contrast, treatment of A549 cells with a low concentration of sagopilone revealed an upregulation of direct transcriptional target genes of TP53, like CDKN1A, MDM2, GADD45A, FAS. Knockdown of TP53, which inhibited the transcriptional induction of TP53 target genes, led to a significant increase in apoptosis induction in A549 cells when treated with a low concentration of sagopilone. The results indicate that activation of TP53 and its downstream effectors like CDKN1A by low concentrations of sagopilone is responsible for the relative apoptosis resistance of A549 cells and might represent a mechanism of resistance to sagopilone.
Subtype distribution of Hepatitis C virus in Jiangsu, China

Hepatitis C virus (HCV) genotype distribution varied by regions and transmission modes. In this study, we investigated HCV genotype distribution in five cities of Jiangsu, China, all of which are located in the Yangtze River Delta Region. A total of 363 samples were collected during 2011–2012. C/E2 and NS5B fragments of HCV were amplified using a multiple RT‐nested PCR strategy and subjected to sequencing. Phylogenetic analysis was performed for HCV genotyping. Among 106 PCR positive cases, HCV subtypes 1a (0.9%), 1b (61.3%), 2a (15.1%), 3a (4.7%), 3b (9.4%), 6a (6.6%), and 6n (1.9%) were detected. Together with our previous data, we found that HCV subtypes were more among injection drug users (IDUs) (nine) than among general population (GP) (six), and the most common subtype among GP was 1b (73.9%), followed by 2a (14.5%), while the top four common subtypes among IDUs were 3a, 1b, 3b, and 6a, with similar prevalence rates (24.4%, 22.7%, 20.9%, and 17.4%, respectively). There were nine HCV subtypes prevalent among IDUs in Jiangsu, more than those in Xinjiang, Hubei, Yunnan, Guangxi, Guangdong, and Hong Kong. The top four common subtypes among IDUs in Jiangsu covered all the two most common HCV subtypes (except 6n subtype) observed in six targeted provinces/region. These results suggested that Jiangsu may be an important gathering place for various HCV subtypes and the gathering may be involved in the large scale of population migration from other regions of China to Eastern China. J. Med. Virol. 88:498–505, 2016. © 2015 Wiley Periodicals, Inc.
A Daphnia Parasite (Caullerya mesnili) Constitutes a New Member of the Ichthyosporea, a Group of Protists near the Animal–Fungi Divergence

ABSTRACT. Caullerya mesnili is a protozoan endoparasite in the gut epithelium of Daphnia, which causes regular epidemics in lakes throughout Europe. Its classification has remained unchanged for over a century, leaving it placed with the Haplosporidia, despite speculation that this position is incorrect. The difficulty in classifying C. mesnili stems from its few known morphological and ecological characteristics, as well as a lack of genetic markers. Here we sequenced the nuclear small subunit (SSU) and internal transcribed spacer rDNA regions of C. mesnili samples from 10 locations. Based on sequence similarities, we suggest the re‐classification of C. mesnili to the Ichthyosporea, a class of protists near the animal–fungi divergence. We report average intragenomic variation of 0.75% and 2.27% in the SSU and internal transcribed spacer regions, respectively. From electron micrographs and light microscopy of histological sections we determined that C. mesnili spores grow within the intestinal epithelium where they establish themselves intercellularly. In addition, we confirmed previous accounts regarding the high virulence of this parasite. Caullerya mesnili reduces host lifespan, the number of clutches, and the total number of offspring. This high selection pressure placed on hosts supports the importance of C. mesnili as a model parasite for the study of host–parasite biology in permanent lakes.
Chondrules born in plasma? Simulation of gas–grain interaction using plasma arcs with applications to chondrule and cosmic spherule formation

We are investigating chondrule formation by nebular shock waves, using hot plasma as an analog of the heated gas produced by a shock wave as it passes through the protoplanetary environment. Precursor material (mainly silicates, plus metal, and sulfide) was dropped through the plasma in a basic experimental set‐up designed to simulate gas–grain collisions in an unconstrained spatial environment (i.e., no interaction with furnace walls during formation). These experiments were undertaken in air (at atmospheric pressure), to act as a “proof‐of‐principle”—could chondrules, or chondrule‐analog objects (CAO), be formed by gas–grain interaction initiated by shock fronts? Our results showed that if accelerating material through a fixed plasma field is a valid simulation of a supersonic shock wave traveling through a cloud of gas and dust, then CAO certainly could be formed by this process. Melting of and mixing between starting materials occurred, indicating temperatures of at least 1266 °C (the olivine‐feldspar eutectic). The production of CAO with mixed mineralogy from monomineralic starting materials also shows that collisions between particles are an important mechanism within the chondrule formation process, such that dust aggregates are not necessarily required as chondrule precursors. Not surprisingly, there were significant differences between the synthetic CAO and natural chondrules, presumably mainly because of the oxidizing conditions of the experiment. Results also show similarity to features of micrometeorites like cosmic spherules, particularly the dendritic pattern of iron oxide crystallites produced on micrometeorites by oxidation during atmospheric entry and the formation of vesicles by evaporation of sulfides.
OpenBliSSART: Design and evaluation of a research toolkit for Blind Source Separation in Audio Recognition Tasks

We describe and evaluate our toolkit openBliSSART (open-source Blind Source Separation for Audio Recognition Tasks), which is the C++ framework and toolbox that we have successfully used in a multiplicity of research on blind audio source separation and feature extraction. To our knowledge, it provides the first open-source implementation of a widely applicable algorithmic framework based on non-negative matrix factorization (NMF), including several preprocessing, factorization, and signal reconstruction algorithms for monaural signals. Apart from blind source separation using supervised and unsupervised NMF, we show how the framework is useful for the increasingly popular audio feature extraction methods by NMF. Furthermore, we point out a numerical optimization for NMF, and show that NMF source separation in real-time on a desktop PC is feasible with our implementation. We conclude with an evaluation of our toolkit on supervised speaker separation, demonstrating how our algorithmic framework allows to tune the real-time factors to the desired perceptual quality.
Chiral separation with ligand‐exchange micellar electrokinetic chromatography using a D‐penicillamine‐copper(II) ternary complex as chiral selector

D‐Penicillamine is demonstrated for the first time as a chiral ligand for the enantioseparation of dansyl amino acids based on ligand‐exchange micellar electrokinetic chromatography (LE‐MEKC). Copper(II) was used as the central ion in the ternary complex. The effect of surfactant on the resolution was significant. A concentration of 20 mM sodium dodecyl sulfate (SDS) was shown to be necessary for the separation. Other important parameters, such as the concentration ratio of D‐penicillamine (D‐PEN) to Cu2+, the kind of metal central ion, the type and pH value of buffer, were also investigated. N‐Acetyl‐D‐penicillamine and L‐valine (Val), with similar structure to D‐penicillamine, were applied as their copper(II) complexes as chiral selector and the chiral recognition mechanism is briefly discussed. Under optimum experimental conditions, i.e., 20 mM NH4OAc, pH 6.5, a 2:1 concentration ratio of D‐penicillamine to Cu(II), 4 mM CuSO4 and 8 mM D‐penicillamine, the chiral separation of eight pairs of different dansyl amino acid enantiomers was accomplished with resolution ranging from 1.1 to 5.9. When L‐PEN was used instead of D‐PEN, reversal of the migration order was observed.
Implications of maximum daily precipitation on streamflow of a watershed: a case study in Zacatecas, Mexico

ABSTRACT In this article, we present the results of the analysis of a flood event that occurred on 18 July 2008 in the town of Tlaltenango, Zacatecas, Mexico. The flood was caused by a storm that reached an accumulated precipitation of 145 mm/day. The event was caused by the passage of hurricane Fausto that produced an intensification of moisture transport to the mainland channelled by topography. The storm event was simulated using the Mesoscale Model version 5 (MM5). The hydrologic model Hydrologic Engineering Center (HEC)-1 was then employed to determine the run-off hydrographs and streamflows. Finally, the Hydrologic Engineering Centers River Analysis System (HEC-RAS) model predicted water levels by integrating information about channel geometry and characteristics such as roughness. The numerical results show that the map of the flooded area as simulated by the HEC-RAS model matches the observed inundation extent for this event well. The calculated values for water levels were quite similar to those directly recorded by civil protection authorities in the urban area. Despite the recent history of recurring flood events, plans and strategies have not been implemented to reduce flooding.
Tree-ring width and density data around the Northern Hemisphere: Part 1, local and regional climate signals

A detailed description is presented of the statistical patterns of climate forcing of tree growth (annual maximum latewood density and ring-width time series), across a network of 387 specially selected conifer sites that circle the extra-tropical Northern Hemisphere. The in‘ uence of summer temperature dominates growth. A mean April–September response is optimum for describing the major forcing signal over the whole densito-metric network, though a shorter June–July season is more relevant in central and eastern Siberia. The ring- width chronologies also have a shorter optimum (June–August) seasonal signal, but this is much weaker than the density signal. The association between tree-ring density and precipitation variability (as measured by partial correlations to account for the correlation between temperature and precipitation) is considerably weaker than with temperature. The ring-width response to precipitation is dominated by ‘noise’ and local site in‘ uences, though a negative response to winter precipitation in northern Siberia is consistent with the suggestion of an in‘ uence of delayed snowmelt. Average correlations with winter temperatures are small for all regions and correlations with annual temperatures are positive only because of the strong link with summer temperatures. Reconstructions of summer temperature based on composite regional density chronologies for nine areas are presented. Five regions (northwestern North America, NWNA; eastern and central Canada, ECCA; northern Europe, NEUR; northern Siberia, NSIB; and eastern Siberia, ESIB) constitute an arbitrary ‘northern’ division of the network, while the four other regions (western North America, WNA; southern Europe, SEUR; central Asia, CAS; and the Tibetan Plateau, TIBP) make up the ‘southern’ part. We also present two larger composite regional reconstructions comprising the data from the five higher-latitude (HILAT) and four lower-latitude (LOLAT) areas respectively; and a single series made up of data from all regions (ALL), which is highly correlated with Northern Hemisphere mean summer temperature. We calculate time-dependent uncertainty ranges for each of these reconstructions, though they are not intended to represent long timescales of tempera ture variability (>100 years) because the technique used to assemble the site chronologies precludes this. Finally, we examine in more detail the reduced sensitivity in the tree-growth data to decadal-timescale summer-temperature trends during the last 50 years, identified in earlier published work.
Compressive Sensing Image Restoration Using Adaptive Curvelet Thresholding and Nonlocal Sparse Regularization

Compressive sensing (CS) is a recently emerging technique and an extensively studied problem in signal and image processing, which suggests a new framework for the simultaneous sampling and compression of sparse or compressible signals at a rate significantly below the Nyquist rate. Maybe, designing an effective regularization term reflecting the image sparse prior information plays a critical role in CS image restoration. Recently, both local smoothness and nonlocal self-similarity have led to superior sparsity prior for CS image restoration. In this paper, first, an adaptive curvelet thresholding criterion is developed, trying to adaptively remove the perturbations appeared in recovered images during CS recovery process, imposing sparsity. Furthermore, a new sparsity measure called joint adaptive sparsity regularization (JASR) is established, which enforces both local sparsity and nonlocal 3-D sparsity in transform domain, simultaneously. Then, a novel technique for high-fidelity CS image recovery via JASR is proposed-CS-JASR. To efficiently solve the proposed corresponding optimization problem, we employ the split Bregman iterations. Extensive experimental results are reported to attest the adequacy and effectiveness of the proposed method comparing with the current state-of-the-art methods in CS image restoration.
Distributed simulation of coloring graph vertices

The problem of coloring graph vertices, known to be NP-complete, is discussed. The authors present an alternative solution to this problem as a distributed simulation which uses a parallel randomized heuristic algorithm for making local decisions to color graph vertices. The algorithm is based on an inter-particle system from statistical mechanics. Since the algorithm works locally, it is likely to be highly parallel. The simulation of a coloring process on n vertices of a graph can be seen as a set of n distributed processes running in parallel. The simulation algorithm is implemented in Occam 2 language and runs on a transputer system. <<ETX>>