Miracle-dz/UniFAR-FTUs huggingface dataset:
Mineral status of kiwiberry

Kiwiberry [Actinidia arguta (Siebold et Zucc.) Planch. ex Miq. ] is – just like the green (Actinidia chinensis var. deliciosa) and yellow (A. chinensis var. chinensis) kiwifruit – a fast-growing, deciduous climbing plant that requires adequate fertilizer management for optimum orchard production. However, compared with kiwifruit, very little is known about the fertilization needs of this crop. Since kiwiberry is gaining importance worldwide, a project was started at four mature orchards in Belgium and the Netherlands with a focus on the mineral status of kiwiberry plants. During two growing seasons, visual deficiency symptoms were recorded and the mineral composition of the first basal leaves on fruiting canes was monitored for three cultivars, ‘Geneva’, ‘Weiki’ and ‘Issai’. We then assessed how these data correlated with each other and whether they were related to soil parameters. Additionally, the mineral composition of the fruits was determined and linked to fruit quality, which was evaluated by storage tests. Sufficiency ranges were set up for kiwiberry leaf composition based on hundreds of foliar analyses for three different timeframes during the growing season: pre-flowering, from flowering until 50 days after full flowering, and from 50 days after full flowering until harvest. The data showed that, in comparison with green and yellow kiwifruit, kiwiberry has a tendency to have higher B, higher Cl, and lower Zn levels in its leaves. Moreover, kiwiberry appeared to be very sensitive to Mn deficiency. Clear varietal differences were observed in the leaves for Mg and P. Sufficiency ranges are important to evaluate foliar analyses and, by consequence, the mineral status of kiwiberry orchards. Although the mineral fruit composition at harvest varied significantly depending on the location, Ca consistently played a key role in the storability of the berries. However, besides Ca, the ratios with, inter alia, K, Mg and N were also important.
Engaging the Wisdom of Crowds : Structural Analysis of Dynamic User Contributions in Online Communities

This paper studies the design of motivating mechanisms under dynamic user contributions in online communities. We characterize individual-level dynamics in a hidden Markov model with two latent motivation states (high vs. low), and examine the influence of different mechanisms with a structural model. From Bayesian estimation on user-level panel data, our results show that reputational motivations are important to transfer users to the high motivation state. For example, if a user were to earn one more accepted answer, the probability that the user stays in the high motivation state would increase by 4.9%. Further, we find that the same motivating mechanisms may work differently in the two motivation states. Surprisingly, badges may suffer the “moral licensing” effect when a user is already highly motivated, even though they help transfer low-motivation users to the high-motivation state. In addition, highly motivated users are more responsive to community size and the demand for knowledge. Design simulations on our structural model provide insights into the consequences of changing specific motivating mechanisms. Our findings offer guidance to platform designers on how to motivate community contributions and build sustainable online communities.
Future and experimental therapeutic strategies for allergic rhinitis and asthma

The rapid progress in our understanding of basic immunology has recently enabled the identifcation of many possible therapeutic targets for the treatment of respiratory allergy and allergic inflammation. As a result, new approaches have been proposed and tested in rhinitis and asthma, including new drugs and mediator antagonists, monoclonal antibodies and immunosuppressant agents. Only a small number of these approaches have become a reality, however, all of them have provided us with the opportunity to improve our knowledge in the field. We will review herein some of the experimental approaches used in humans in relation to the pathogenic aspects of allergic inflammation.
Predictive Data Mining in Nutrition Therapy

The assessment and measurement of health status in communities throughput the world is a massive information technology challenge. Data mining, plays a vital role in health care industry since it really has the potential to generate a knowledge-rich environment that reduces medical errors, decreases costs by increasing efficiency, improves the quality of clinical decisions and significantly enhances patient's outcomes and quality of life. This study falls within the context of nutrition evaluation and its main goal is to apply classification algorithms in order to predict if a patient needs to be followed by a nutrition specialist. One of the tools resorted in this study was the Waikato Environment for Knowledge Analysis (Weka in advance) Workbench since it allows to quickly try out and compare different machine learning solutions. The tasks involved in the development of this project included data preparation, data preprocessing, data transformation and cleaning, application of several classifiers and its respective evaluation through performance measures that include the confusion matrix, accuracy, error rate, and others. The accomplished results showed to be quite optimistic presenting promising values of performance measures. specifically an accuracy around 91 %.
Hysteresis Losses in the Output Capacitance of Wide Bandgap and Superjunction Transistors

This paper deals with switching losses in modern power semiconductors due to a hysteresis in their output capacitance. A modified Sawyer-Tower circuit is presented, which is able to characterize this effect under large signal excitation. Three semiconductor types are analyzed: a Si superjunction MOSFET, a SiC MOSFET and a GaN HEMT. It is revealed that the output capacitance of these devices shows a hysteretic behavior which results in unavoidable losses even under zero voltage turn-on transitions. These losses become a major issue when pushing switching frequencies of power electronics into the megahertz range.
Switched-Boost-Modified Z-Source Inverter Topologies With Improved Voltage Gain Capability

This paper presents three-phase switched-boost-modified Z-source inverter (ZSI) topologies with improved boost capabilities. In the proposed ZSIs, the voltage gain is increased significantly by adding one auxiliary switch and one diode without using additional passive components. The concept is applied to traditional ZSI, discontinuous input current quasi-ZSI (DC-qZSI), and continuous input current qZSI (CC-qZSI) resulting into three new inverter topologies: switched-boost ZSI, DC-qZSI, and CC-qZSI. Anatomization of operating principle, steady-state analysis, voltage gain, voltage stress, current stress, stored energy analysis, power loss, total harmonic distortion, and efficiency analysis are carried out to highlight the advantages of the proposed inverters as compared to the conventional ZSIs. Finally, the operation of the proposed CC-qZSI is validated through simulation and experimental results.
Implementation and Performance Analysis of Probabilistic Cognitive Relaying Communication Demo

Cognitive Relaying is the concept where secondary users (SUs) help primary users (PUs) by relaying its traffic. This paper aims to propose the possibility of studying and comparing the performance of cognitive relaying using an experimental framework developed with USRP2. Probabilistic Relaying and Scheduling is practically implemented and its effect on adjusting the delay and throughput of PU and SU are investigated. Step by Step implementation of a cooperative protocol, where SU helps the PU by relaying its data or its own data based on an adjustable scheduling probability. Adjustable admission control is also introduced in the protocol so that PU data that can be relayed will be introduced in the queue of the SU with certain probability. The effect of varying both these probabilities, service and admission is studied in the setup. Finally, the practical results are verified with the simulation and theoretical results, and a conclusion is drawn from the results of the combined effects of probability of relaying and scheduling on the performance of the PU and SU in a cognitive relay environment. Keywords—Cognitive relaying; GNU radio; probabilistic relaying; USRP2
An ecosystem model-based estimate of changes in water availability differs from water proxies that are commonly used in species distribution models

To assess whether the water availability measures commonly used in species distribution models might be misleading because they do not account for the hydrological effects of changes in vegetation structure and functioning. Europe. We compared different methods for estimating water availability in species distribution models with the soil water content predicted by a process-based ecosystem model. The latter also accounted for the hydrological effects of dynamic changes in vegetation structure and functioning, including potential physiological effects of increasing CO2. All proxies showed similar patterns of water availability across Europe for current climate, but when projected into the future, the changes in the simpler water availability measures showed no correlation with those projected by the more complex ecosystem model, even if CO2 effects were switched off. Results from species distribution modelling studies concerning future changes in species ranges and biodiversity should be interpreted with caution, and more process-based representations of the water balance of terrestrial ecosystems should be considered within these models. (Less)
Image-Sensor-Based Fast Industrial-Robot Positioning System for Assembly Implementation

In this paper, an innovative image-technique-based fast industrial-robot positioning system for assembly implementation is presented. Two laser projectors, that is, a laser pointer and a line laser, and an image sensor are used to construct the innovative system to scan and obtain a 3D point cloud model of the object to be assembled. The system is then integrated with a 6-axis industrial robot to define the insertion position in a semi-autonomous manner. This system can save up to 80% of the manual teaching time for defining robot insertion positions by using a teach pendant. The whole system has been tested on four insertion tasks that require high precision. The results of experiments confirm the effectiveness and efficiency of the system for high-precision tasks. This innovative system can be used in many industrial-robot-based automated assembly tasks.
Grid-tied Modular and Scalable Photovoltaic Distributed Maximum Power Point Tracking System with Storage at Module Level Using Non-Isolated Three-Port Converters

In this manuscript a new modular PV and storage system for grid-tied applications is presented. Each module comprises a PV panel, a small battery pack and a power converter. The system is able to perform distributed MPPT at panel level with enlarged operating conditions thanks to the added storage. Different strategies to enlarge the MPPT capability are presented along with simulations that show their effectiveness.
Soluble dietary fibers from Trigonella foenum graecum Linn. seed and their structures

Soluble dietary fibers of Trigonella foenum graecum Linn. seed were isolated and fractionatedinto neutral and acidic parts. Structures of both the fractions were determined by sugar analysis andhigh resolution 2D NMR spectroscopic studies including total correlation (TOCSY) spectroscopy.Main chain of the neutral SDF fraction was found to be a galactomannan composed of mannoseand galactose (~1 : 1.5 ratio) having 1,3-α linkages between each other. Terminal mannose residuewas linked to galactose residue of the main chain at its 4 position by α-linkage. The acidic SDF wasa rhamnogalacturonan, in the main chain, galacturonic acids and rhamnose had 1,4-α- and 1,2-β-linkeages, respectively. Terminal β-galactose and β-glucuronic acid were linked to α-galacturonicacid of the main chain at its 3-position DOI: http://dx.doi. org/10.3329/jbas.v38i1. 20201 Journal of Bangladesh Academy of Sciences, Vol. 38, No. 1, 19-26, 2014
Automatic Short Answer Scoring based on Paragraph Embeddings

Automatic scoring systems for students’ short answers can eliminate from instructors the burden of grading large number of test questions and facilitate performing even more assessments during lectures especially when number of students is large. This paper presents a supervised learning approach for short answer automatic scoring based on paragraph embeddings. We review significant deep learning based models for generating paragraph embeddings and present a detailed empirical study of how the choice of paragraph embedding model influences accuracy in the task of automatic scoring.
Juvenile Lake Sturgeon Go To School: Life-Skills Training for Hatchery Fish

AbstractHatchery supplementation of declining fish populations is commonly employed to try to increase year-class strength. However, the success of such programs is often hampered from low postrelease survival as a result of the failure of hatchery fish to appropriately recognize predation threats. Not surprisingly, there has been considerable effort to train prey to recognize predators prior to release. The objective of our current work was to characterize the antipredator response of hatchery-reared, predator-naive young-of-the-year Lake Sturgeon Acipenser fulvescens (an endangered species) to alarm cues from injured conspecifics and test whether these alarm cues could be used to train sturgeon to recognize unknown predators. We found that skin-derived alarm cues elicited an antipredator response without learning and that learning required cues coming from whole-body grinds, presumably because they represent a much more reliable indicator of risk. When the experiment was repeated with older sturgeon fro.
Isolated FET pulse driver increases power rate and duty cycle

In power converters, pulse-drive circuits transmit the pulses a controller generates to the power transistor. Driver circuits must both transmit the controller’s switching on/off signals with galvanic isolation and provide energy to turn the switch on and off and to maintain the required on or off state. The required energy increases with the power transistor’s input capacitance, which also increases with the power that the transistor module manages. Thus, when the circuit requires high power, designers typically parallel the power transistors, increasing the input capacitance. When you need to operate IGBT (insulated-gate-bipolar-transistor) modules in parallel, it is best to share the gate drive because using different driver circuits introduces additional variation in turn-on and -off times and creates a possible imbalance between each power module. The basis of the circuit in Figure 1 is an earlier Design Idea (Reference 1). The operation of the circuits is basically the same as the one in the previous Design Idea, but this one can drive MOS-
Pricing S&P 500 Index Options: A Conditional Semi‐Nonparametric Approach

We price S&P 500 index options under the assumption that the conditional risk‐neutral density function of the index follows a Semi‐Nonparametric (SNP) process with GARCH variance. The model is estimated combining a set of option contracts written on the index and the daily index return time series in the period 1996–2011. The in‐sample and out‐sample performance of the model is compared with several benchmark models, beating most of them. We conclude that a pricing model dealing simultaneously with non‐normalities and time‐varying volatility helps to mitigate the observed S&P 500 index option biases. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:217–239, 2016
Steigerung der Arbeitsgenauigkeit bei der Fräsbearbeitung metallischer Werkstoffe mit Industrierobotern

Hinsichtlich der Investitions- und Betriebskosten stellt der Einsatz von Sechs-Achs-Knickarmrobotern als Fuhrungskinematik fur Zerspanaufgaben ein enormes Potenzial dar. Dieses kann allerdings bislang aufgrund der geringen erzielbaren Arbeitsgenauigkeit kaum genutzt werden. Mithilfe der in dieser Arbeit entwickelten Methodik sind eine deutliche Reduktion der statischen Fraserabdrangung sowie eine Erhohung der Prozessstabilitat moglich, wodurch die Grundlage zur Erweiterung des Einsatzfeldes von Frasrobotern geschaffen wurde.
On the Local Hessian in Back-propagation

Back-propagation (BP) is the foundation for successfully training deep neural networks. However, BP sometimes has difficulties in propagating a learning signal deep enough effectively, e.g., the vanishing gradient phenomenon. Meanwhile, BP often works well when combining with ``designing tricks'' like orthogonal initialization, batch normalization and skip connection. There is no clear understanding on what is essential to the efficiency of BP. In this paper, we take one step towards clarifying this problem. We view BP as a solution of back-matching propagation which minimizes a sequence of back-matching losses each corresponding to one block of the network. We study the Hessian of the local back-matching loss (local Hessian) and connect it to the efficiency of BP. It turns out that those designing tricks facilitate BP by improving the spectrum of local Hessian. In addition, we can utilize the local Hessian to balance the training pace of each block and design new training algorithms. Based on a scalar approximation of local Hessian, we propose a scale-amended SGD algorithm. We apply it to train neural networks with batch normalization, and achieve favorable results over vanilla SGD. This corroborates the importance of local Hessian from another side.
Hole mobility enhancement and p -doping in monolayer WSe2 by gold decoration

Tungsten diselenide (WSe2) is an attractive transition metal dichalcogenide material, since its Fermi energy close to the mid gap makes it an excellent candidate for realizing p–n junction devices and complementary digital logic applications. Doping is one of the most important technologies for controlling the Fermi energy in semiconductors, including 2D materials. Here we present a simple, stable and controllable p-doping technique on a WSe2 monolayer, where a more p-typed WSe2 field effect transistor is realized by electron transfer from the WSe2 to the gold (Au) decorated on the WSe2 surfaces. Related changes in Raman spectroscopy are also reported. The p-doping caused by Au on WSe2 monolayers lowers the channel resistance by orders of magnitude. The effective hole mobility is ∼100 (cm2/Vs) and the near ideal subthreshold swing of ∼60 mV/decade and high on/off current ratio of >106 are observed. The Au deposited on the WSe2 also serves as a protection layer to prevent a reaction between the WSe2 and the environment, making the doping stable and promising for future scalable fabrication.
Local Interaction Simulation Approach for Efficient Modeling of Linear and Nonlinear Ultrasonic Guided Wave Active Sensing of Complex Structures

This paper presents the local interaction simulation approach (LISA) for efficient modeling of linear and nonlinear ultrasonic guided wave active sensing of complex structures. Three major modeling challenges are considered: material anisotropy with damping effects, nonlinear interactions between guided waves and structural damage, as well as geometric complexity of waveguides. To demonstrate LISA’s prowess in addressing such challenges, carefully designed numerical case studies are presented. First, guided wave propagation and attenuation in carbon fiber composite panels are simulated. The numerical results are compared with experimental measurements obtained from scanning laser Doppler vibrometry (SLDV) to illustrate LISA’s capability in modeling damped wave propagation in anisotropic medium. Second, nonlinear interactions between guided waves and structural damage are modeled by integrating contact dynamics into the LISA formulations. Comparison with commercial finite element software reveals that LISA can accurately simulate nonlinear ultrasonics but with much higher efficiency. Finally, guided wave propagation in geometrically complex waveguides is studied. The numerical example of multimodal guided wave propagation in a rail track structure with a fatigue crack is presented, demonstrating LISA’s versatility to model complex waveguides and arbitrary damage profiles. This paper serves as a comprehensive, systematic showcase of LISA’s superb capability for efficient modeling of transient dynamic guided wave phenomena in structural health monitoring (SHM). [DOI: 10.1115/1.4037545]
Isolation, Optimization, and Molecular Characterization of a Lipase Producing Bacterium from Oil Contaminated Soils

Lipases have many applications in biotechnology, thanks to their ability of acylglycerides hydrolysis. They alsp possess the unique feature of acting at the lipid-water interface, which distinguishes them from esterases. Commercially useful lipases are produced by microorganisms with the extracellular lipase being produced by many bacteria including Pseudomonas. The greatest production of lipase takes place under optimum conditions such as appropriate temperature, suitable carbon, nitrogen sources, etc. This study tries to collect lipase-producing bacteria from the soil of oil-extraction factories and identify isolated bacteria, while creating optimum conditions for lipase production by bacteria. Having collected three soil samples from an oil extraction factory, lipase-producing bacteria have been identified, based on biochemical and morphological tests. Finally the optimal conditions for lipase production as well as molecular analysis has been evaluated. During the study, among the different bacteria, the strain to produce highest lipase has been selected. It has been found out that the optimal conditions for lipase production by this strain is as follows: 48 hours of incubation; incubation temperature of 37 °C; pH of 7; agitation speed of 150 rpm; peptone extract as the nitrogen source; and olive oil as a carbon source. A lipase-producing bacterium has been identified based on morphological, physiological, and biochemical characteristics as well as 16S rRNA analysis, identified as Pseudomonas spp.
The Prediction Factors of Pre-XDR and XDR-TB among MDR-TB Patients in Northern Thailand

Background: Molecular diagnosis based on the detection of mutations conferring genetic drug resistance is useful for early diagnosis and treatment of Pre-XDR and XDR-TB patients. However, the study of mutation as a marker to predict Pre-XDR and XDR-TB is rare. Methods: Thirty-four Mycobacterium tuberculosis (MTB) isolates from MDR, Pre-XDR and XDR-TB patients in the upper north of Thailand, who had been identified for drug susceptibility using the indirect agar proportion method from 2005-2012, were examined for genetic site mutations of katG, inhA, and ahpC for isoniazid (INH) drug resistance, rpoB for rifampicin (RIF) drug resistance, gyrA for ofloxacin (OFX), and rrs for kanamycin (KAN). Associations between resistant genes and Pre-XDR and XDR-TB in the MDR patients were performed using exact probability tests. Univariable logistic regression was used to quantify the strength of association between the gene mutation with Mycobacterium tuberculosis and the prevalence of Pre-XDR and XDR-TB in the MDR patients. Results: The mutations in the region of the rpoB gene at codon 445 (C445T) in the Pre-XDR or XDR-TB patients were significantly 20.6 times more prevalent among the MDR-TB patients. The inhA gene mutation at codon 114 (T114G) was also significantly 8.1 times more prevalent. Conclusion: The findings can be used to predict the odds of Pre-XDR and XDR-TB in MDR-TB patients, as a guide for prevention and treatments.