Miracle-dz/UniFAR-FTUs huggingface dataset:
A Course in Distribution Theory And Applications

Preface / Test Functions and Distributions / Convergence of Distributions / Differentiation of Distributions / Convolution of Distributions / Tempered Distributions and Fourier Transforms / Sobolev Spaces / Weak Solutions / Distributions on Locally Convex Spaces / Distributions on Manifolds / Bibliography / Index.
Floral Volatile Organic Compounds and a List of Pollinators of Fallopia baldschuanica (Polygonaceae)

Simple Summary Fallopia baldschuanica (Polygonaceae) is an Asian plant growing wild in parts of Europe and North and Central America as an introduced taxon. Although F. baldschuanica is considered a potentially invasive alien plant species, little is known about its pollination biology in climatic conditions in Europe. In this study, we identified the volatile organic compounds emitted from F. baldschuanica flowers, from which some are important insect attractants. We also described the pollinator populations of this plant. We confirm that the chemical composition of floral aroma in F. baldschuanica attracts a large group of potential pollinators, which in addition to the intensive growth of the plant is a feature enabling the species to rapidly expand. Abstract Fallopia baldschuanica (Polygonaceae) is an Asian plant growing wild in parts of Europe and North and Central America as an introduced taxon, in many countries it is considered a potentially invasive species. This article presents the list of 18 volatile organic compounds (VOCs) emitted by the flowers of F. baldchuanica and identified by headspace gas chromatography/mass spectrometry (HS-GC/MS) analyzes, and a list of flower-visiting and pollinating insects that have been observed in the city center of Wrocław (SW Poland). β-ocimene, heptanal, nonanal, α-pinene, 3-thujene, and limonene, were detected as the floral scent’s most important aroma compounds. F. baldschuanica also produces the aphid alarm pheromones, i.e., β-farnesene and limonene, that repels aphids. Additionally, the pollinators of F. baldschuanica were indicated, based on two years of observations in five sites in the urban area. It was found, that the pollinators of this plant with the highest species stability are: Diptera from families Syrphidae (Chrysotoxum bicinctum, Eristalis pertinax, Eupeodes corollae, Episyrphus balteatus, Eristalis tenax, Syrphus ribesii, Eristalis intricaria), Muscidae (Musca domestica), Sarcophagidae (Sarcophaga spp.), Calliphoridae (Lucilia sericata, Lucilia caesar), Hymenoptera from families Vespidae (Vespula vulgaris), and Apidae (Apis sp., Bombus sp.). The key role of VOCs in adaptation to plant expansion is discussed.
Deep Learning Based 3D Point Clouds Recognition for Robotic Manufacturing

The present work aims to develop a light-weight deep learning algorithm for 3D vision based on point cloud perception. We first analyzed the current 3D vision models for object classification and pose estimation purposes, and proposed that the global features extracted by PointNet was able to facilitate performing both classification and pose estimation tasks by visualizing the activations of a trained PointNet model. Then, the customized point cloud datasets were produced for both training and testing through Blensor. With our datasets, the performance of our proposed algorithm was evaluated. The predicted results of our model were also compared with those predicted by the framework of [4], which generally showed similar performance but with slightly lower accuracy. Nevertheless, our framework is considered to have a much better efficiency than that of [5], due to simpler structure of our framework that avoid repetitive work of feature extraction that experienced by using the framework of [5].
APPLICATIONS OF NEUTRON ACTIVATION SPECTROSCOPY

Since the discovery in 1932, neutrons became a basis of many methods used not only in research, but also in industry and engineering. Among others, the exceptional role in the modern nuclear engineering is played by the neutron activation spectroscopy, based on the interaction of neutron flux with atomic nuclei. In this article we shortly describe application of this method in medicine and detection of hazardous substances.
On the use of seminumerical simulations in predicting the 21-cm signal from the epoch of reionization

We present a detailed comparison of three different simulations of the epoch of reionization (EoR). The radiative transfer simulation (C-2-RAY) among them is our benchmark. Radiative transfer codes can produce realistic results, but are computationally expensive. We compare it with two seminumerical techniques: one using the same haloes as C-2-RAY as its sources (Sem-Num), and one using a conditional Press-Schechter scheme (CPS+GS). These are vastly more computationally efficient than C-2-RAY, but use more simplistic physical assumptions. We evaluate these simulations in terms of their ability to reproduce the history and morphology of reionization. We find that both Sem-Num and CPS+GS can produce an ionization history and morphology that is very close to C-2-RAY, with Sem-Num performing slightly better compared to CPS+GS. We also study different redshift-space observables of the 21-cm signal from EoR: the variance, power spectrum and its various angular multipole moments. We find that both seminumerical models perform reasonably well in predicting these observables at length scales relevant for present and future experiments. However, Sem-Num performs slightly better than CPS+GS in producing the reionization history, which is necessary for interpreting the future observations. The CPS+GS scheme, however, has the advantage that it is not restricted by the mass resolution of the dark matter density field.
Measurement of Slips at Contact Interfaces Using a Self-Powered Sensor Based on Triboelectric Nanogenerators

The accumulation of tangential small slips at contact interfaces may occur in mechanical assemblies when subjected to cyclic loadings, and cause failure of parts. However, the slip is difficult to measure directly. In this paper, a self-powered displacement sensor based on triboelectric nanogenerator (TENG) is fabricated, which is used to measure the microslip of the specimen in the designed test bench. When the specimen slips under the cyclic tangential load with a frequency of 10 Hz, the resulted average slip displacement of the specimen under a single load cycle is 9.01 μm, which is measured by the Keithley DAQ 6510 multimeter (Tektronix, Shanghai, China). This value is close to that measured by the Keithley 6514 electrometer. In addition, adding a BaTiO3 thin film with a thickness of 100 nm between the Kapton triboelectric layer and the Cu electrode, the output voltage of the sensor is increased by 51.5%. Thus, the sensitivity of the self-powered sensor is improved effectively.
Dynamo in the Intra-Cluster Medium: Simulation of CGL-MHD Turbulent Dynamo

Abstract The standard magnetohydrodynamic (MHD) description of the plasma in the hot, magnetized gas of the intra-cluster (ICM) medium is not adequate because it is weakly collisional. In such collisionless magnetized gas, the microscopic velocity distribution of the particles is not isotropic, giving rise to kinetic effects on the dynamical scales. These kinetic effects could be important in understanding the turbulence as well as the amplification and maintenance of the magnetic fields in the ICM. It is possible to formulate fluid models for collisonless or weakly collisional gas by introducing modifications in the MHD equations. These models are often referred as kinetic MHD (KMHD). Using a KMHD model based on the CGL-closure, which allows the adiabatic evolution of the two components of the pressure tensor (the parallel and perpendicular components with respect to the local magnetic field), we performed 3D numerical simulations of forced turbulence in order to study the amplification of an initially weak seed magnetic field. We found that the growth rate of the magnetic energy is comparable to that of the ordinary MHD turbulent dynamo, but the magnetic energy saturates in a level smaller than that of the MHD case. We also found that a necessary condition for the dynamo to operate is to impose constraints on the anisotropy of the pressure.
A 3-D Printed Helix for Traveling-Wave Tubes

In this work, a 3-D printed copper helix for a traveling-wave tube (TWT) is reported. The fabricated helix was designed to be used in a TWT operating at millimeter-wave frequencies (60–80 GHz). The helix was realized with an additive micromanufacturing technique (<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>AM). Measurements were also performed to estimate the losses of the printed material and evaluate the RF performance of deposited copper. Simulations showed that a TWT based on the 3-D printed helix can have a gain of about 30 dB at 66 GHz and a 1-dB bandwidth of about 5 GHz. The estimated losses from RF measurements reveal an RF copper conductivity of about <inline-formula> <tex-math notation="LaTeX">$2\times 10^{{7}}$ </tex-math></inline-formula> S/m, measured in air without any surface cleaning steps, which is a very good value and comparable to bulk copper conductivity in the millimeter-wave range.
ArcGIS story maps in improving teachers’ Geography awareness

The purpose of this study is to examine the use of story maps in increasing sustainable Geography awareness among Geography teachers. The advent of story maps has altered the current Geography education in the digital era. ArcGIS story maps are a type of user-friendly geospatial technology renewal. This story map is believed capable of helping students learn Geography more independently, transforming Geography education. This belief should be reinforced by implementing story maps on their own Geography teachers, who have low Geography literacy rates in general. This action research involved 67 Geography teachers who were members of the East Java Geography Teacher Working Group, with various backgrounds, ages, and teaching experiences. Learning is implemented using blended learning and the in-on-in model. With blended project-based learning, this research was conducted to solve problems related to high school teachers' low Geography awareness. To identify the effects of the treatment, the obtained data were analyzed using a different test with paired t-test. The findings showed that story maps could increase long-term geographic awareness, illustrated by the obtained significant level of more than 0.05. This success is influenced by teachers' knowledge and experience with geospatial technology, as well as their age. Although the ability to create story projects is limited, the use of story maps provides a meaningful experience for teachers to think, reason, and act geographically.
Characterization of Primordial Perturbations by Observations

We constrain cosmological models where the primordial perturbations have an adiabatic and a (possibly correlated) cold dark matter (CDI), neutrino density (NDI) or neutrino velocity (NVI) isocurvature component. We use both a phenomenological approach, where the power spectra of primordial perturbations are parametrized with two amplitudes at two different scales, and a slow-roll two-field inflation approach where inflation slow-roll parameters are used as primary parameters, determining the spectral indices and the ratio of tensor perturbations to scalar perturbations. We use WMAP 7year and 9-year data combined with other CMB data and Planck 2013 CMB temperature anisotropy data. Bayesian methods indicate no preference for any of the isocurvature modes: the CMB data set tight upper bounds on any non-adiabatic contribution to the observed CMB temperature variance. We show that allowing for a primordial tensor contribution has a negligible effect on the determination of the non-adiabatic contribution and vice versa, as long as the tensor spectral index obeys the first inflationary consistency relation. On large scales, the WMAP CMB data seem to constrain isocurvature tighter than the Planck data. This is due to the lack of power at low multipoles, ` ∼ 2.40, in the Planck data compared to the prediction of the best-fitting adiabatic ΛCDM model. Hence the Planck data prefer a power-reducing mechanism, which the mixed adiabatic and isocurvature models with negative correlation or full anticorrelation can offer. With WMAP 9-year data we find that in the NDI and NVI cases larger isocurvature fractions are allowed than in the corresponding models with CDI. For uncorrelated perturbations, the upper limit to the primordial NDI (NVI) fraction is 24% (20%) at k = 0.002Mpc−1 and 28% (16%) at k = 0.01Mpc−1. For maximally correlated (anticorrelated) perturbations, the upper limit to the NDI fraction is 3.0% (0.9%). The non-adiabatic contribution to the CMB temperature variance can be 10% (–13%) for the NDI (NVI) modes. For Planck data the non-adiabatic contribution to the temperature variance can be up to 7%, 9%, 5% in the CDI, NDI, NVI models. The Planck data constrain the primordial CDI fraction in specific curvaton and axion scenarios to 0.25% and 3.9%, respectively. All bounds above are at 95% CL. With the WMAP data, relaxing the pure adiabaticity assumption leads to large shifts of the preferred values of standard cosmological parameters and broadening of their posterior probability distributions. In contrast, as the Planck data determines the acoustic peak structure precisely up to the sixth acoustic peak, allowing for a mixture of the primordial adiabatic and an isocurvature mode does not significantly affect the determination of standard cosmological parameters.
COVID-GWAB: A Web-Based Prediction of COVID-19 Host Genes via Network Boosting of Genome-Wide Association Data

Host genetics affect both the susceptibility and response to viral infection. Searching for host genes that contribute to COVID-19, the Host Genetics Initiative (HGI) was formed to investigate the genetic factors involved in COVID-19 via genome-wide association studies (GWAS). The GWAS suffer from limited statistical power and in general, only a few genes can pass the conventional significance thresholds. This statistical limitation may be overcome by boosting weak association signals through integrating independent functional information such as molecular interactions. Additionally, the boosted results can be evaluated by various independent data for further connections to COVID-19. We present COVID-GWAB, a web-based tool to boost original GWAS signals from COVID-19 patients by taking the signals of the interactome neighbors. COVID-GWAB takes summary statistics from the COVID-19 HGI or user input data and reprioritizes candidate host genes for COVID-19 using HumanNet, a co-functional human gene network. The current version of COVID-GWAB provides the pre-processed data of releases 5, 6, and 7 of the HGI. Additionally, COVID-GWAB provides web interfaces for a summary of augmented GWAS signals, prediction evaluations by appearance frequency in COVID-19 literature, single-cell transcriptome data, and associated pathways. The web server also enables browsing the candidate gene networks.
Structure formation in monolayers composed of hard bent-core molecules

ABSTRACT We investigate the role of excluded volume interactions instabilising different structures in monolayers filled with bent-shaped molecules using the Onsager type of density functional theory supplemented by constant-pressure Monte-Carlo simulations. We study influence of molecular features, like the apex angle, thickness of the arm and the type of the arm edges on the stability of layered structures. For simple molecular shapes taken the observed phases are dominated by the lamellar antiferroelectric type as observed experimentally, but a considerable sensitivity of the ordering to details of the molecular shape is found for order parameters and wave vectors of the structures. Interestingly, for large opening angles and not too thick molecules, a window of stable nematic splay-bend phase is shown to exist. GRAPHICAL ABSTRACT
Physiological and Transcriptomic Analysis of Arabidopsis thaliana Responses to Ailanthone, a Potential Bio-Herbicide

Many plants naturally synthesize and secrete secondary metabolites that exert an allelopathic effect, offering compelling alternatives to chemical herbicides. These natural herbicides are highly important for sustainable agricultural practices. Ailanthone is the chemical responsible for the herbicidal effect of Ailanthus altissima, or “tree of heaven”. The molecular studies involving ailanthone’s effect on plant growth are limited. In the current study, we combined whole-transcriptome and physiology analysis of three Arabidopsis thaliana ecotypes treated with ailanthone to identify the effect of this allelopathic chemical on genes and plant growth. Our physiology results showed 50% reduced root growth, high proline accumulation, and high reactive-oxygen-species accumulation in response to ailanthone stress. Deep transcriptome analysis revealed 528, 473, and 482 statistically significant differentially expressed genes for Col-0, Cvi-0, and U112-3 under ailanthone stress, including 131 genes shared among the three accessions. The common genes included 82 upregulated and 42 downregulated genes and varied in expression at least twofold. The study also revealed that 34 of the 131 genes had a similar expression pattern when Arabidopsis seedlings were subjected to other herbicides. Differentially expressed genes significantly induced in response to ailanthone included DTXL1, DTX1, ABCC3, NDB4, UGT74E2, and AZI1. Pathways of stress, development and hormone metabolism were significantly altered under ailanthone stress. These results suggest that ailanthone triggers a significant stress response in multiple pathways similar to other herbicides.
Fault Diagnosis of Rotating Machinery Under Multiple Operating Conditions Generalization: A Representation Gradient Muting Paradigm

Fault diagnosis of rotating machinery under fixed operating conditions has been developed considerably. However, the designed model suffers from a performance loss due to the internal covariance shift caused by the changes in operating conditions. How to mine the essential characteristics of faults by multiple related domains and then generalize well to unseen operating conditions is of great significance for the fault diagnosis of rotating machinery. To this end, we present a generic representation gradient muting paradigm (RGMP) to enhance the generalization ability of the diagnostic model. We first develop a deep convolutional network with skip connection and batch normalization. Then, RGMP guides the network to purposely discard a small number of dominant features activated by the training samples and forces the network to learn the remaining label-related representations. RGMP facilitates the network to activate more broad perceptual fields for out-of-domain samples without prior knowledge of the unseen conditions. Finally, the fine-tuned representations are fed into the classification layer, and the network parameters are optimized by backpropagation. Experiments on gear and high-speed train bearing verify the effectiveness of the proposed model under unseen operating conditions.
ANALYSIS OF TWO SMALL MAGELLANIC CLOUD H ii REGIONS CONSIDERING THERMAL INHOMOGENEITIES: IMPLICATIONS FOR THE DETERMINATIONS OF EXTRAGALACTIC CHEMICAL ABUNDANCES

We present long-slit spectrophotometry considering the presence of thermal inhomogeneities (t2) of two H ii regions in the Small Magellanic Cloud (SMC): NGC 456 and NGC 460. Physical conditions and chemical abundances were determined for three positions in NGC 456 and one position in NGC 460, first under the assumption of uniform temperature and then allowing for the possibility of thermal inhomogeneities. We determined t2 values based on three different methods: (1) by comparing the temperature derived using oxygen forbidden lines with the temperature derived using helium recombination lines (RLs), (2) by comparing the abundances derived from oxygen forbidden lines with those derived from oxygen RLs, and (3) by comparing the abundances derived from ultraviolet carbon forbidden lines with those derived from optical carbon RLs. The first two methods averaged t2 = 0.067 ± 0.013 for NGC 456 and t2 = 0.036 ± 0.027 for NGC 460. These values of t2 imply that when gaseous abundances are determined with collisionally excited lines they are underestimated by a factor of nearly two. From these objects and others in the literature, we find that in order to account for thermal inhomogeneities and dust depletion, the O/H ratio in low-metallicity H ii regions should be corrected by 0.25–0.45 dex depending on the thermal structure of the nebula or by 0.35 dex if such information is not available.
Antioxidants from Hyeronima macrocarpa Berries Loaded on Nanocellulose: Thermal and Antioxidant Stability

This study investigated the effect of different storage temperatures (35–55 °C) on the bioactive substances and antioxidant properties of Hyeronima macrocarpa berries loaded on nanocellulose. NC was extracted from banana pseudo-stems and presented an interesting surface and porosity properties. The acidified ethanol extract showed better anthocyanin extraction (1317 mg C3G eq./100 g FW) and was used for the preparation of the powdered product, which presented an intense and uniform magenta color, with CIELAB parameters of L* = 59.16, a* = 35.61, and b* = 7.08. The powder exhibited significant stability at storage temperatures of 35 and 45 °C, in which there was no significant loss of anthocyanins or a decrease in antioxidant capacity. In addition, the color was stable for up to 4 months without adding any preservative agent. The anthocyanin-rich extract of H. macrocarpa reached an estimated shelf-life of 315 days (stored at 35 °C), as a result of the impregnation process between the extract and NC, with the ability to protect the bioactives from degradation, due to NC surface properties.
Implications of lepton flavor violation on long baseline neutrino oscillation experiments

Non-standard neutrino interactions (NSIs), the sub-leading effects in the flavour transitions of neutrinos, play a crucial role in the determination of the various unknowns in neutrino oscillations, such as neutrino mass hierarchy, Dirac CP violating phase and the octant of atmospheric mixing angle. In this work, we focus on the possible implications of lepton flavour violating (LFV) NSIs, which generally affect the neutrino propagation, on the determination of the these unknown oscillation parameters. We study the effect of these NSIs on the physics potential of the currently running and upcoming long-baseline experiments, i.e., T2K, NO$\nu$A and DUNE. We also check the allowed oscillation parameter space in presence of LFV NSIs.
Computed-torque method for the control of a 2 DOF orthosis actuated through pneumatic artificial muscles: a specific case for the rehabilitation of the lower limb

In this paper we give a new control model based on the so called computed-torque method for the control of a 2 degrees of freedom orthosis for the rehabilitation of the lower limb, the AIRGAIT exoskeleton's leg orthosis. The actuation of the AIRGAIT is made through self-made pneumatic muscles. For this reason this work starts with the static and dynamic characterization of our pneumatic muscles. The followed approach is based on the analytical description of the system. For this, we describe the pneumatic muscles behaviour with an easy-invertible polynomial fit function in order to model its non-linear trend. We give a geometrical model of the mechanical system to compute the length between the attachments of the pneumatic muscles to the structure for every angles assumed by the two joints. We evaluate through Newton-Euler equation the couples at the joints for each values of the angles. At last we show some validation tests in order to characterize the functioning of the proposed control model on the actuation of the orthosis.