Miracle-dz/UniFAR-FTUs huggingface dataset:
MyETL: a flexible and efficient data quality profiling framework

Data quality is very important in data centric environments. The data quality profiling task is to filter out data records which violate domain semantic rules. The data quality profiling framework is expected to be flexible to represent complex domain semantics and efficient to tackle large amount of data records. We propose a data quality profiling framework, named MyETL, which is conceived from ETL paradigm to fulfil these requirements. A directed acyclic graph is employed to represent domain semantic rules in design phase. Then the graph is optimized by a topology optimization procedure. At last, the graph is mapped to threads and memory objects and scheduled to execution. As implemented based on OSGi framework, MyETL is constructed by bundles and can be extended for convenient.
Methods and apparatus for comprehensive characterization of performance attributes and damage thresholds of ultrafast laser optics

Abstract. It is presently well understood that the operational performance limits of optics are determined by three fundamental attributes: the initiation of laser-induced damage, the growth of damage sites, and the transient (nondamaging) modification of optical parameters. The comprehensive characterization of the performance limitations of ultrafast optics requires consideration of all three fundamental attributes. The vast majority of the literature to date, however, has focused primarily on damage-initiation and testing systems that are largely focused on determining the damage-initiation threshold under single- and multipulse excitation. We discuss a testing apparatus that was designed to offer the capability to adequately characterize all three of these performances attributes under femtosecond, near-infrared laser irradiation. Key aspects of the methodology are discussed; these include high-dynamic-range energy control, variable beam size, wavelength tunability, B-integral management, and functional performance characterization to explore the true operational limits of the components. Example results for a metal-dielectric mirror demonstrate the test station’s operation.
Remaining life prediction of turbofan engine based on multi-path feature fusion

A multi-path feature fusion network model and data augmentation algorithm are proposed based on the limitations of the remaining useful life prediction method of a single network model and the problem of small sample size. Firstly, the sample size of data set is expanded through data augmentation, so as to improve the accuracy of prediction. Secondly, two different paths are selected to extract features: the first path inputs the data into the cascade structure of 1- Dimensional Convolutional Neural Network and Gated Recurrent Unit, and extracts spatial and temporal features respectively; the second path inputs the data directly into the Long Short Term Memory to obtain the complete temporal features. Finally, the output features of the two paths are fused, and the result input into the full connection layer for RUL prediction. The proposition is evaluated on the publicly available health monitoring dataset C-MAPSS of aircraft turbofan engines provided by NASA. The results show that compared with the single network model, the proposed method can effectively improve the remaining useful life prediction accuracy of such equipment, and has practical application value.
A numerical study of the genesis of extratropical convective mesovortices

Abstract The purpose of this study is to understand the genesis of extratropical convective mesovortices and the large-scale environmental features that influence the vortex formation. A hypothesis is proposed that mesovortices form in the stratiform rain regions of mesoscale convective systems (MCSs) due to the reduction of static stability that reduces the effective local Rossby radius in such regions. A conceptual model of the mesoscale convective cyclogenesis is introduced, which describes the three stages of the mesovortex formation. A modified version of the Pennsylvania State University/National Center for Atmospheric Research three-dimensional hydrostatic mesoscale model is used to simulate mesovortex genesis in analytically generated pre-MCS large-scale environments. The model simultaneously incorporates parameterized convection and a grid-resolvable convective scheme containing the effects of hydrostatic water loading, condensation (evaporation), freezing (melting), and sublimation. A control si.
Dynamics, Thermodynamics and Extratropical Interactions of Tropical Intraseasonal Oscillations in a Simple Nonlinear Model.

Abstract This study examines two possible mechanisms responsible for the selection of the preferred period of the Madden and Julian (40–50 day) oscillation. A global two-level nonlinear model with a positive-only CISK-type cumulus heating parameterization is used to simulate the oscillation, which appears when the SST exceeds a critical value for instability of CISK type. Longitudinal variations of tropical SST are imposed so that a stable and an unstable region coexist. When the cold SST sector is sufficiently stable, the CISK wave propagates efficiently through the stable region in the form of a damped moisture-modified Kelvin wave, and reemerges in the unstable region where its amplitude grows. When the SST in the stable sector is set closer to the instability threshold, the moist Kelvin wave slows down and decays before reentering the unstable region, but the CISK perturbation periodically regenerates over the warm waters in response to a local buildup of instability. This last experiment implies a ne.
Comparative assessment of the bactericidal effect of nanoparticles of copper oxide, silver, and chitosan-silver against E. coli infection in broilers Nanotechnology as a tool to fight E. coli infection in broilers

Escherichia coli infection is considered one of the most economically important multi-systemic diseases in poultry farms. Several nanoparticles such as silver, chitosan and copper oxide are known to be highly toxic to several microbes. However, there are no data concerning their success against in vivo experimental E. coli infection in broilers. So that, this study was designed to investigate the bactericidal effect of low doses of CuO-NPs (5mg/kg bwt), Ag-NPs (0.5mg/kg bwt) and Ch-Ag NPs (0.5mg/kg bwt) against E. coli experimental infection in broilers. One hundred chicks were divided in to 5 groups as the following: (1) control; (2) E. coli (4x108 CFU\ml) challenged; (3) E. coli +CuO-NPs; (4) E. coli +Ag-NPs; (5) E. coli +Ch-Ag NPs. The challenged untreated group, not NPs treated groups, recorded the lowest weight gain as well as the highest bacterial count and lesion score in all examined organs. The highest liver content of silver was observed in Ag-NPs treated group compared with the Ch-Ag NPs treated group. Our results concluded that Ch-Ag NPs not only had the best antibacterial effects but also act as a growth promoter in broilers without leaving any residues in edible organs. We recommend using Ch-Ag NPs in broiler farms instead of antibiotics or probiotics.
Homological invariants associated to semi-dualizing bimodules

Cohen-Macaulay dimension for modules over a commutative ring has been defined by A. A. Gerko. That is a homological invariant sharing many properties with projective dimension and Gorenstein dimension. The main purpose of this paper is to extend the notion of Cohen-Macaulay dimension for modules over commutative noetherian local rings to that for bounded complexes over non-commutative noetherian rings.
A R EVIEW ON W IRELESS P OWER T RANSFER IN F REE SPACE AND CONDUCTING LOSSY MEDIA

Recently, the interest in wireless power transfer (WPT) has significantly increased due to its attractive applications. The power transfer efficiency and communication range of most of the existing WPT systems are still limited, which is due to many technical challenges and regulation limitations. This requires more research and technical efforts to overcome the current limitations and make WPT systems much more efficient and widely used. This paper aims at reviewing recent advances and research progress in the area of WPT for the purposes of addressing current challenges and future research directions. To obtain these purposes, an introduction to WPT is provided. Also, main research themes of WPT in free space and lossy media are discussed. Additionally, the benefits of using split ring resonators WPT in conducting lossy media are investigated. This will be very helpful to boost WPT in lossy media and inspire more optimized structures for further improvement.
Environmental Impact of Recent Volcanic Eruption from Mt. Mayon over South-East Asia

Volcanoes are the mountains that erupt metallic compounds in the form of Lava, dust and gases vulnerable to the environment. These erupted gases affect the physical and chemical characteristics of Aerosol particles present in the atmosphere by absorbing the incoming radiation from the sun. This process has a huge contribution towards instability of the Heat budget of the Earth and leads to global warming and climate change. Compounds of sulfur e.g. (H2S, C2S, SO4) erupted from a volcano have severe effect on climate by scattering the incoming sunlight back to the space and leads to increased cooling rate of the earth surface. In this paper; short term and immediate effects of volcanic eruption from Mayon volcano have been discussed. The recent eruption of Mt. Mayon at Albay, Philippines on 29th Jan 2018 affected huge vegetation and environmental impacts of this eruption are found up to Brunei and Sarawak province of Malaysia. The study revealed that outbound airmass patternss from Mt. Mayon had Southwest direction that carried Sulfur dioxide and ash plumes till Malaysia. The case study shows huge vegetation loss and sudden rise in SO2 concentration over Sarawak from 1st Feb 2018 to 4th Feb 2018.
Supporting Complex Query Time Enrichment For Analytics

Several application domains require data to be enriched prior to its use. Data enrichment is often performed using expensive machine learning models to interpret low-level data ( e . g ., models for face detection) into semantically meaningful observation. Col-lecting and enriching data offline before loading it to a database is infeasible if one desires online analysis on data as it arrives. Enriching data on the fly at insertion could result in redundant work (if applications require only a fraction of the data to be enriched) and could result in a bottleneck (if enrichment functions are expensive). Any scalable solution requires enrichment during query processing. This paper explores two different architectures for integrating enrichment into query processing – a loosely coupled approach wherein enrichment is performed outside of the DBMS and a tightly coupled approach wherein it is performed within the DBMS. The paper addresses the challenges of increased query latency due to query time enrichment.
An Adaptive Large Neighborhood Search Algorithm for the Multi-mode RCPSP

We present an Adaptive Large Neighborhood Search (ALNS) algorithm for the Multimode Resource-Constrained Project Scheduling Problem (MRCPSP). We incorporate techniques for deriving additional precedence relations and propose a new method, so-called mode-diminution, for removing modes during execution. These techniques make use of bound arguments, and we propose and experiment with three new bounds for the MRCPSP, in addition to bounds found in the literature. We propose a simple technique, so-called opportunistic mode-ﬂipping, which can be applied whenever a schedule is generated, and which signiﬁcantly improves the results of the algorithm. Computational experiments are performed on a set of standard benchmark instances from the PSPLIB, and a comparison is made with other algorithms found in the literature. The experiments show that the algorithm is competitive, but can not beat the best algorithms. Even so, some of the elements of the algorithm perform well, that is the bound arguments, the mode-removal procedure, and in particular opportunistic mode-ﬂipping, and these elements may perhaps be used to improve the results of other algorithms for this problem. We present an Adaptive Large Neighborhood Search algorithm for the Multi-mode Resource-Con-strained Project Scheduling Problem (MRCPSP). We incorporate techniques for deriving additional precedence relations and propose a new method, so-called mode-diminution, for removing modes during execution. These techniques make use of bound arguments, and we propose and experiment with three new bounds for the MRCPSP, in addition to bounds found in the literature. We propose a simple technique, so-called opportunistic mode-flipping, which can be applied whenever a schedule is generated,and which significantly improves the results of the algorithm. Computational experiments are performed on a set of standard benchmark instances from the PSPLIB, and a comparison is made with other algorithms found in the literature. The experiments show that the algorithm is competitive, but can not beat the best algorithms. Even so, some of the elements of the algorithm perform well, that is the bound arguments, the mode-removal procedure, and in particular opportunistic mode-flipping, and these elements may perhaps be used to improve the results of other algorithms for this problem.
Rigorous results for a population model with selection II: genealogy of the population

We consider a model of a population of fixed size $N$ undergoing selection. Each individual acquires beneficial mutations at rate $\mu_N$, and each beneficial mutation increases the individual's fitness by $s_N$. Each individual dies at rate one, and when a death occurs, an individual is chosen with probability proportional to the individual's fitness to give birth. Under certain conditions on the parameters $\mu_N$ and $s_N$, we show that the genealogy of the population can be described by the Bolthausen-Sznitman coalescent. This result confirms predictions of Desai, Walczak, and Fisher (2013), and Neher and Hallatschek (2013).
Multifractal Analysis of Unvoiced Speech Signals

In this thesis, we analyze the complexity involved in the production of unvoiced speech signals with measures from nonlinear dynamics and chaos theory. Previous research successfully characterized some speech signals as chaotic. However, in this dissertation, we use multifractal measures to postulate the presence of various fractal regimes present in the attractors of unvoiced speech signals. We extend prior work which used only correlation dimension D2 and Lyapunov Exponents to analyze some speech sounds. We capture the chaotic properties of unvoiced speech signals in the embedded vector space more succinctly by not only estimating the correlation dimension D2 , but by also estimating the generalized dimension Dq· The (nonconstant) generalized dimensions were estimated from phase space reconstructed vectors of single scalar variable realization of unvoiced speech signals. The largest of those dimensions is an indicator of the minimum dimension required in the phase space of any realistic dynamical model of speech signals. Results of the generalized dimension estimation support the hypothesis that unvoiced speech signals indeed have multifractal measures. The multifractal analysis also reveals that unvoiced speech signals exhibit low-dimensional chaos as well as "soft" turbulence. This is in contrast to the opinion that unvoiced speech signals are generated from what is technically known as "hard" turbulent flow, in which the dimension of a dynamical model is very high. Unvoiced speech signals may actually be generated from "soft" turbulent flow. In this dissertation, we also explore the relationship between the estimated generalized dimensions Dq and the singularity spectrum f(a). Existing algorithms for accurately estimating the resulting singularity spectrum f(a) from the samples of generalized dimensions Dq of a multifractal chaotic time series use either (a) linear
A genetically encoded photo-proximity labeling approach for mapping protein territories

Studying dynamic biological processes requires approaches compatible with the lifetimes of the biochemical transactions under investigation, which can be very short. We describe a genetically encoded system that allows protein interactomes to be captured using visible light. Our approach involves fusing an engineered flavoprotein to a protein of interest. Brief excitation of the fusion protein leads to local generation of reactive radical species within cell-permeable probes. When combined with quantitative proteomics, the system generates ‘snapshots’ of protein interactions with high temporal resolution. The intrinsic fluorescence of the fusion domain permits correlated imaging and proteomics analyses, a capability that is exploited in several contexts, including defining the protein clients of the major vault protein (MVP). The technology should be broadly useful in the biomedical area.
High intraspecific growth variability despite strong evolutionary heritage in a neotropical forest

Individual tree growth is a key determinant of species performance and a driver of forest dynamics and composition. Previous studies on tree growth unravelled the variation in species growth as a function of demographic trade-offs that are partially predicted using functional traits. They have explored the environmental determinants of species growth potential and the variation of intraspecific growth over space and time due to environment and biotic factors. However, variation in individual growth within species remains underexplored for a whole community and the relative role of species’ evolutionary heritage and of local environments remains unquantified. Here, based on 36 years of diameter records for thousands of mapped individuals belonging to 138 species, we assessed individual tree growth potential in a local neotropical forest community in the Amazon basin. We further related variation in individual growth potential with taxonomic levels, local topography, and neighbourhood crowding, before exploring species growth potential link to functional traits and distribution along the phylogeny. We found that most of the variation in growth potential was individual, and that taxonomic structure explained a third of the observed variation. Species growth potential was phylogenetically conserved with positive conservatism up to the genus level in the vast majority of species. Functional traits of roots, wood and leaves together predicted species growth potential. Phylogeny suggested joint selection of species’ growth strategies and associated functional traits during convergent evolutions. Finally, neighbourhood crowding had a significant effect on individual growth potential, although much of this inter-individual variation remains largely unexplained and the underlying ecological and evolutionary factors are still little explored. The high intraspecific variation observed could allow individuals in these hyperdiverse ecosystems to respond to the variable light and competitive conditions offered by successional niches during forest gap dynamics.
Endothelial Dnmt3a controls placenta vascularization and function to support fetal growth

The fetoplacental capillary network is of vital importance for proper nourishment during early development. Inadequate maternal-fetal circulation has emerged as one of the main pathophysiological features of placental insufficiency. Meta-analysis of human placental endothelial cells (EC) revealed that downregulation of the de novo DNA methyltransferase 3A (DNMT3A) is associated with preeclampsia. However, mechanistic insights into functional consequences of altered DNA methylation patterns during placental vascular development remain elusive. Here, we investigated the role of Dnmt3a in the vasculature during murine placenta development. Spatial and temporal expression analyses revealed an induction of Dnmt3a in the mature labyrinth layer. The global and endothelium-specific loss (ECKO) of Dnmt3a resulted in reduced placental vascularization and fetal growth restriction. EC deleted for Dnmt3a demonstrated extensive loss of DNA methylation, particularly close to angiogenesis related genes. Loss of DNA methylation decreased the angiogenic capacity of EC in vitro and in vivo. Collectively, these data identify DNMT3A as the main DNA methyltransferase in the human and murine placental vasculature and characterize its importance for physiological endothelial function. The Dnmt3a-dependent regulation of genes related to placenta insufficiency validates Dnmt3a ECKO mice as an epigenetically driven mouse model of placenta insufficiency with potential translational relevance.
Efficient Base-Catalyzed Kemp Elimination in an Engineered Ancestral Enzyme

The routine generation of enzymes with completely new active sites is one of the major unsolved problems in protein engineering. Advances in this field have been so far modest, perhaps due, at least in part, to the widespread use of modern natural proteins as scaffolds for de novo engineering. Most modern proteins are highly evolved and specialized, and, consequently, difficult to repurpose for completely new functionalities. Conceivably, resurrected ancestral proteins with the biophysical properties that promote evolvability, such as high stability and conformational diversity, could provide better scaffolds for de novo enzyme generation. Kemp elimination, a non-natural reaction that provides a simple model of proton abstraction from carbon, has been extensively used as a benchmark in de novo enzyme engineering. Here, we present an engineered ancestral β-lactamase with a new active site capable of efficiently catalysing the Kemp elimination. Our Kemp eliminase is the outcome of a minimalist design based on a single function-generating mutation followed by sharply-focused, low-throughput library screening. Yet, its catalytic parameters (kcat/KM=2·105 M−1s−1, kcat=635 s−1) compare favourably with the average modern natural enzyme and with the best proton-abstraction de novo Kemp eliminases reported in the literature. General implications of our results for de novo enzyme engineering are discussed.
The impact of primary colonizers on the community composition of river biofilm

As a strategy for minimizing microbial infections in fish hatcheries, we have investigated how putatively probiotic bacterial populations influence biofilm formation on the surface of eggs. All surfaces that are exposed to the aquatic milieu develop a microbial community through the selective assembly of microbial populations into a surface-adhering biofilm. In the investigations reported herein, we describe laboratory experiments designed to determine how initial colonization of a surface by nonpathogenic isolates from sturgeon eggs influence the subsequent assembly of populations into the existing biofilm from a pelagic river community. All eight of the tested strains altered the assembly of river biofilm in a strain-specific manner. Previously formed isolate biofilm was challenged with natural river populations and after 24 hours, two strains and two isolate combinations proved highly resistant to invasion, comprising at least 80% of the biofilm community, four isolates were intermediate in resistance with at least 45% of the biofilm community and two isolates were reduced to 4% of the biofilm community. Founding biofilms of Serratia sp, and combinations of Brevundimonas sp. -Hydrogenophaga sp. and Brevundimonas sp. -Acidovorax sp. specifically blocked populations of Aeromonas and Flavobacterium, potential fish pathogens, from colonizing the biofilm. In addition, all isolate biofilms were effective at blocking invading populations of Arcobacter. Several strains, notably Deinococcus sp. , recruited specific river populations into the biofilm. The experiments suggest that relatively simple measures can be used to control the assembly of biofilm on the eggs surface and perhaps offer protection from pathogens. In addition, the methodology provides a relatively rapid way to detect potentially strong ecological interactions between bacterial populations in the formation of biofilms.