Miracle-dz/UniFAR-FTUs huggingface dataset:
Rhizosphere Protists Change Metabolite Profiles in Zea mays

Plant growth and productivity depend on the interactions of the plant with the associated rhizosphere microbes. Rhizosphere protists play a significant role in this respect: considerable efforts have been made in the past to reveal the impact of protist-bacteria interactions on the remobilization of essential nutrients for plant uptake, or the grazing induced changes on plant-growth promoting bacteria and the root-architecture. However, the metabolic responses of plants to the presence of protists or to protist-bacteria interactions in the rhizosphere have not yet been analyzed. Here we studied in controlled laboratory experiments the impact of bacterivorous protists in the rhizosphere on maize plant growth parameters and the bacterial community composition. Beyond that we investigated the induction of plant biochemical responses by separately analyzing above- and below-ground metabolite profiles of maize plants incubated either with a soil bacterial inoculum or with a mixture of soil bacteria and bacterivorous protists. Significantly distinct leaf and root metabolite profiles were obtained from plants which grew in the presence of protists. These profiles showed decreased levels of a considerable number of metabolites typical for the plant stress reaction, such as polyols, a number of carbohydrates and metabolites connected to phenolic metabolism. We assume that this decrease in plant stress is connected to the grazing induced shifts in rhizosphere bacterial communities as shown by distinct T-RFLP community profiles. Protist grazing had a clear effect on the overall bacterial community composition, richness and evenness in our microcosms. Given the competition of plant resource allocation to either defense or growth, we propose that a reduction in plant stress levels caused directly or indirectly by protists may be an additional reason for corresponding positive effects on plant growth.
Method for the calibration of atomic force microscope cantilevers

The determination of the spring constants of atomic force microscope (AFM) cantilevers is of fundamental importance to users of the AFM. In this paper, a fast and nondestructive method for the evaluation of the spring constant which relies solely on the determination of the unloaded resonant frequency of the cantilever, a knowledge of its density or mass, and its dimensions is proposed. This is in contrast to the method of Cleveland et al. [Rev. Sci. Instrum. 64, 403 (1993)], which requires the attachment of masses to the cantilever in the determination of the spring constant. A number of factors which can influence the resonant frequency are examined, in particular (i) gold coating, which can result in a dramatic variation in the resonant frequency, for which a theoretical account is presented and (ii) air damping which, it is found, leads to a shift of -4% in the resonant frequency down on its value in a vacuum. Furthermore, the point of load on the cantilever is found to be extremely important, since a small variation in the load point can lead to a dramatic variation in the spring constant. Theoretical results that account for this variation, which, it is believed will be of great practical value to the users of the AFM, are given. © 1995 American Institute of Physics.
Approximate Discrete-Time Modeling of DC–DC Converters With Consideration of the Effects of Pulse Width Modulation

For dc–dc converters with pulsating output current, such as boost and buck–boost converters, the use of leading-edge or trailing-edge pulse width modulation (PWM) can result in distinctly different behavior. This phenomenon is not readily captured by the usual averaged model but can be predicted with a discrete-time model. However, the discrete-time model, which tracks the dynamics of state variables over a switching period, is usually more complex and less convenient to apply for the design of the feedback control. Based on the low-pass characteristics of dc–dc converters, an approximate discrete-time model is proposed in this paper, and upon transforming to the s-domain, the model results in transfer functions that can be conveniently used for deriving practical closed-loop parameters. With the proposed model, the loop gain, the input and output impedances are derived and analyzed. The effects of applying different types of PWM on the stability of a single dc–dc converter and a system of cascaded dc–dc converters are discussed. Finally, prototypes of a buck converter, a boost converter, and a cascaded system of buck and boost converters are constructed to verify the effectiveness of the approximate discrete-time model.
The Sectional Stratospheric Sulfate Aerosol module (S3A-v1) within the LMDZ general circulation model: description and evaluation against stratospheric aerosol observations

Stratospheric aerosols play an important role in the climate system by affecting the Earth's radiative budget as well as atmospheric chemistry, and the capabilities to simulate them interactively within global models are continuously improving. It is important to represent accurately both aerosol microphysical and atmospheric dynamical processes because together they affect the size distribution and the residence time of the aerosol particles in the stratosphere. The newly developed LMDZ-S3A model presented in this article uses a sectional approach for sulfate particles in the stratosphere and includes the relevant microphysical processes. It allows full interaction between aerosol radiative effects (e.g. radiative heating) and atmospheric dynamics, including e.g. an internally generated quasi-biennial oscillation (QBO) in the stratosphere. Sulfur chemistry is semi-prescribed via climatological lifetimes. LMDZ-S3A reasonably reproduces aerosol observations in periods of low (background) and high (volcanic) stratospheric sulfate loading, but tends to overestimate the number of small particles and to underestimate the number of large particles. Thus, it may serve as a tool to study the climate impacts of volcanic eruptions, as well as the deliberate anthropogenic injection of aerosols into the stratosphere, which has been proposed as a method of geoengineering to abate global warming.
Netrin-4 Expression and Regulation by Hypoxia in Human Placenta

Netrin-4 is a well-known actor involved in axonal guidance. Recently we have reported the cellular localization of netrin-4 in human placenta. Furthermore we demonstrated its role in placental angiogenesis. Here we determined netrin-4 mRNA expression in first trimester placenta. First, we showed an increase in netrin-4 mRNA expression at 11-13 weeks of gestation (wg), suggesting a negative regulation of netrin-4 expression by hypoxia. In fact, the human placenta undergoes a transition from a low oxygenated to a highly oxygenated environment during the first trimester of pregnancy. This physiological switch in oxygen tension is a prerequisite for proper placental development and involves the hypoxia-inducible factor (HIF-1), a protein that is up-regulated under hypoxic conditions. Then, we used the trophoblast cell line BeWo to test this hypothesis. BeWo cells cultured under hypoxic conditions exhibited decreased levels of netrin-4 mRNA expression. Using siRNA strategy, hypoxia-inducible factor 1α (HIF-1α) knock-down induced a significant increase in netrin-4 mRNA expression. Altogether these results indicate that netrin-4 expression in the trophoblast cells is regulated by hypoxia via the HIF-1 pathway.
Monitoring Advanced Metering Infrastructures with Amilyzer

Advanced metering infrastructures (AMIs) enable two-way communications between smart meters and utility control centers. They are a key component of the smart grid initiative as they encompass a large number of devices and technologies and provide important applications that improve energy consumption and grid reliability. They could also attract diverse cyber-physical threats, and thus they require efficient monitoring solutions to ensure the detection of known and unknown abnormal activities. This paper presents Amilyzer, a specification-based intrusion detection system (IDS) that leverages tight control over authorized AMI protocol operations to provide a practical network situational awareness solution for AMI operators.
Identifying Movements in Noisy Crowd Analytics Data

Privacy-preserved tracking of WiFi-enabled devices such as smartphones offers a highly scalable solution for large-scale crowd movement studies. However, extracting knowledge out of pedestrian-tracking data acquired this way is not simple. This is, generally, due to the inherent inaccuracy of the measurement technique. Segmenting an individual's trajectory data into periods of stops and moves is a fundamental step in analyzing crowds' movement. Such distinctions allow us to answer advanced questions regarding visited locations or even social behavior. Algorithms previously designed for distinguishing movements from stay periods, assume datasets are gathered using GPS, which offers precise positioning. WiFi tracking, however, does not offer such precision. The location of devices can at best be reduced to a large area around the WiFi scanner. In this paper, we study a set of established algorithms for detecting periods of stops and moves from GPS-based datasets and their applicability to WiFi-based data. Consequently, we propose possible improvements to such algorithms considering the inherent characteristics of WiFi tracking data.
Photovoltaic plant cloud shadowing and energy drops in Northern Europe

In this paper the effect of shadowing due to clouds on the energy production of a photovoltaic power plant installed in northern latitudes in Finland is analyzed. Numerical techniques, which can be also implemented on an embedded system because of their low computational and memory requirements, have been used for having an efficient processing of millions of experimental current vs. voltage curves acquired on the photovoltaic plant. The analysis allows to affirm that, at high latitudes, clouds can have a significant instantaneous effect on the power produced by the plant, but the time duration of the power drop is so short that the energy production is only marginally affected. This result is in full agreement with other studies appeared in the recent literature and suggests that, in such contexts, control electronics producers should avoid to implement related maximum power point tracking techniques for facing mismatched conditions, since their effect on energy production appears to be negligible.
Avatar Self-Identification, Self-Esteem, and Perceived Social Capital in the Real World: A Study of World of Warcraft Players and their Avatars

v CHAPTER ONE: INTRODUCTION 1 CHAPTER TWO: BACKGROUND 3 World of Warcraft 3 Computer-Mediated Communication 5 Gaming Motivations 7 Avatars 8 Avatar Self-Identification 13 Social Capital 16 Self-Esteem 20 CHAPTER THREE: REVIEW OF LITERATURE 22 CHAPTER FOUR: SOCIAL IDENTITY THEORY 27 CHAPTER FIVE: PRESENT STUDY 29 Method 32 CHAPTER SIX: RESULTS 37 CHAPTER SEVEN: DISCUSSION 43 CHAPTER EIGHT: CONCLUSION 46
Waste collection vehicle routing problem benchmark datasets and case studies: A review

Waste collection vehicle routing problem (WCVRP) is one of the most studied areas and has received high interest from the modern society today.This corresponds to the cost efficiency, population growth, and environmental concerns.The growth of the WCVRP awareness is the result of continuous supports from government and private organizations.This paper reviews severa established benchmark datasets and successful real-life case studies. Respectively billions of dollars have been saved from the operational costs.The current trend for benchmark datasets presented and case studies are accordingly grouped by countries and continents, thus revealing the need for WCVRP. Investigation on objectives, constraints and algorithms are also discussed. Results showed the increased interest of researchers in using benchmark datasets as well as the case studies and some of the constraints that should be considered in WCVRP.It also suggested that environmental or quality of service issues can be integrated into the common objectives of minimizing cost and distance travelled.Methods used in WCVRP are exact methods and approximate methods.Results showed that approximate methods have the capability in providing good results for large-scale data. Conclusively, this study analyzes the gap and provides recommendations for researches.
Interactive Editing of Upholstered Furniture

Fast visualization of industrial parts for rapid prototyping is nowadays eased by the fact that CAD construction data is readily available in most cases. Upholstery constitutes an important exception as its shape is not given a priori but the result of complex physical interactions between hard bodies, soft cushioning and elastic sheets. In this paper we propose an interactive visualization and editing method for upholstery that infers physically plausible surfaces from a sewing pattern. Our method supports fast design decisions by allowing easy and intuitive modifications of the inferred surface at any time. We also propose a reconstruction method for point clouds that is specifically targeted at upholstery. We argue that the sewing pattern encodes important information about shape and material deformations of the final surface and consequently use it as a prior in our reconstruction algorithm. The practicability of our method is demonstrated on two real world data sets.
SAR Image Land Cover Datasets for Classification Benchmarking of Temporal Changes

The increased availability of high-resolution synthetic aperture radar (SAR) satellite images has led to new civil applications of these data. Among them is the systematic classification of land cover types based on the patterns of settlements or agriculture recorded by SAR imagers, in particular the identification and quantification of temporal changes. A systematic (re)classification shall allow the assignment of continuously updated semantic content labels to local image patches. This necessitates a careful selection of well-defined and discernible categories being contained in the image data that have to be trained and validated. These steps are well-established for optical images, while the peculiar imaging characteristics of SAR sensors often prevent a comparable approach. Especially, the vast range of SAR imaging parameters and the diversity of local targets impact the image product characteristics and need special care. In the following, we present guidelines and practical examples of how to obtain reliable image patch classification results for time series data with a limited number of given training data. We demonstrate that one can avoid the generation of simulated training data if we decompose the classification task into physically meaningful subsets of characteristic target properties and important imaging parameters. Then, the results obtained during training can serve as benchmarking figures for subsequent image classification. This holds for typical remote sensing examples such as coastal monitoring or the characterization of urban areas where we want to understand the transitions between individual land cover categories. For this purpose, a representative dataset can be obtained from the authors. A final proof of our concept is the comparison of classification results of selected target areas obtained by rather different SAR instruments. Despite the instrumental differences, the final results are surprisingly similar.
Microplastic lens array fabricated by a hot intrusion process

A microplastic lens array has been successfully constructed on top of a 500-/spl mu/m-thick PC (Polycarbonate film) by using a micro hot intrusion process. A single-layer LIGA process is used to fabricate the high-aspect-ratio nickel mold insert that has circular hole patterns of 80 /spl mu/m in diameter and 200 /spl mu/m in depth. Under the hot intrusion process, plastic material can be intruded into these circular-shape holes and stopped at desired depth under elevated temperature and pressure to fabricate microlenses. By adjusting the embossing load, temperature and time, the curvature and height of the lens are controllable when the same mold insert is used. The optical properties of these microlenses have been characterized and the average radius of curvature is found as 41.4 /spl mu/m with a standard deviation of 1.05 /spl mu/m. Experimental characterization and theoretical model are conducted and developed for the micro-intrusion process in terms of the radius of curvature and height of the lenses and they correspond well with experimental data within 5% of variations. The focusing capability of the lenses is demonstrated by comparing the images of laser light with and without using the lenses. When the projection screen is placed 200 /spl mu/m away from the lens, the full-width at half-maximum (FWHM) for the lens is 110 /spl mu/m while the original FWHM of the optical fiber is 300 /spl mu/m.
The m6A Reader ECT2 Controls Trichome Morphology by Affecting mRNA Stability in Arabidopsis[OPEN]

The YTH-domain family protein ECT2 is a reader of the epitranscriptomic mark m6A that affects trichome morphology and functions in mRNA stability and 3′ UTR processing in Arabidopsis. The epitranscriptomic mark N6-methyladenosine (m6A) can be written, read, and erased via the action of a complex network of proteins. m6A binding proteins read m6A marks and transduce their downstream regulatory effects by altering RNA metabolic processes. The characterization of m6A readers is an essential prerequisite for understanding the roles of m6A in plants, but the identities of m6A readers have been unclear. Here, we characterized the YTH-domain family protein ECT2 as an Arabidopsis thaliana m6A reader whose m6A binding function is required for normal trichome morphology. We developed the formaldehyde cross-linking and immunoprecipitation method to identify ECT2-RNA interaction sites at the transcriptome-wide level. This analysis demonstrated that ECT2 binding sites are strongly enriched in the 3′ untranslated regions (3′ UTRs) of target genes and led to the identification of a plant-specific m6A motif. Sequencing analysis suggested that ECT2 plays dual roles in regulating 3′ UTR processing in the nucleus and facilitating mRNA stability in the cytoplasm. Disruption of ECT2 accelerated the degradation of three ECT2 binding transcripts related to trichome morphogenesis, thereby affecting trichome branching. The results shed light on the underlying mechanisms of the roles of m6A in RNA metabolism, as well as plant development and physiology.
IN VIVO EVALUATION OF GENOTOXICTY OF Acorus calamus MEDIATED SILVER NANOPARTICLES

Metal nanomaterials are found to have a potential application in catalysis, photonics, optics and biomedicine. Silver nanoparticles have gained immense interest and have been exploited over the years to expand their applications. Green synthesis is one of the recently developed methods for synthesizing silver nanoparticles using different organisms such as plant, bacteria and fungi. The present study is aimed to synthesize and characterize the silver nanoparticles using Acorus calamus plant extract and to check their genotoxicity using Drosophila as the model organism. Acorus calamus green silver nanoparticles were synthesized and characterized using High-Resolution Scanning Electron Microscopy (HRSEM) and ultraviolet and visible (UV-VIS) spectrum. The in vivo toxicity of the synthesised green silver nanoparticles was tested on flies. Three defined concentrations of the NPs(10mg/L, 50mg/L and 100mg/L) was chosen; and the flies were exposed to food mixed with the above defined concentrations for 24 hours along with a negative control. Post 24 hours, phenotypic changes in the flies were observed under the stereo zoom microscope and documented. Also, the DNA from flies (post exposure) was isolated using phenol chloroform method and subjected to DNA fragmentation assay. Marked phenotypic changes in terms of discoloration were observed. DNA fragmentation assay revealed distinct shearing in all three concentrations on comparison with the control. Novelty of this present study is that the evaluation of green nanoparticles with Drosophila as the model organism.
Poly (3, 3'”-dialkylquaterthiophene) based organic thin film transistor under green light illumination

The bottom gate top contact organic thin film transistors (OTFTs) have been fabricated on silicon substrate using poly (3, 3'”-dialkylquaterthiophene) (PQT-12) polymer by floating film transfer method (FTM) and illuminated from the top with different wavelength and intensity of the visible light. The performance parameters of OTFT such as field effect mobility, threshold voltage, subthreshold swing, and on/off current ratio have been found as 7.8×10<sup>−2</sup> cm<sup>2</sup>/Vs, −8.1 V, −11.3 V/dec, and 4.1×10<sup>2</sup>, respectively under dark conditions. The maximum drain current in the OTFT is observed for 540 nm of light. The drain current is found to increase with the increase in incident light intensity and found a maximum responsivity of 7.4 A/W at 50 μW/cm<sup>2</sup>.
Stochastic Shortest Paths and Weight-Bounded Properties in Markov Decision Processes

The paper deals with finite-state Markov decision processes (MDPs) with integer weights assigned to each state-action pair. New algorithms are presented to classify end components according to their limiting behavior with respect to the accumulated weights. These algorithms are used to provide solutions for two types of fundamental problems for integer-weighted MDPs. First, a polynomial-time algorithm for the classical stochastic shortest path problem is presented, generalizing known results for special classes of weighted MDPs. Second, qualitative probability constraints for weight-bounded (repeated) reachability conditions are addressed. Among others, it is shown that the problem to decide whether a disjunction of weight-bounded reachability conditions holds almost surely under some scheduler belongs to NP ∩ coNP, is solvable in pseudo-polynomial time and is at least as hard as solving two-player mean-payoff games, while the corresponding problem for universal quantification over schedulers is solvable in polynomial time.
Convex Hybrid Restoration and Segmentation Model for Color Images

Image restoration and segmentation are important areas in digital image processing and computer vision. In this paper, a new convex hybrid model is proposed for joint restoration and segmentation during the post-processing of colour images. The proposed Convex Hybrid model is compared with the existing state of the art variational models such as Cai model, Chan-Vese Vector-Valued (CV-VV) model and Local Chan-Vese (LCV) model using noises such as Salt & Pepper and Gaussian. Additional four experiments were performed with increasing combination of noises such as Salt & Pepper, Gaussian, Speckle and Poisson to thoroughly verify the performance of Convex Hybrid Model. The results revealed that the Convex Hybrid model comparatively outperformed qualitatively and has successfully removed the noises and segment the required object properly. The Convex Hybrid model used the colour Tele Vision (TV) as a regularizer for denoising of the corrupt image. The Convex Hybrid Model is convex and can get global minima. The PDEs obtained from the minimisation of the Convex Hybrid Model are numerically solved by using explicit scheme.