Miracle-dz/UniFAR-FTUs huggingface dataset:
RNA Interference: An Eco-Friendly Tool for Plant Disease Management

Efficient control of plant pathogens affecting economically important crop species represents one of the major challenges for sustainable agriculture production. Though plant breeding has been the classical means of manipulating the plant genome to develop resistant cultivar for controlling plants diseases, the advent of genetic engineering provides an entirely new approach. Currently, the area planted with crops genetically modified for resistant to disease is less compared with that of crops for tolerance to herbicide, or resistant to insects. Numerous strategies are being pursued to render plants resistant to fungi, bacteria, viruses and nematodes. Recently, RNA interference (RNAi) technology has emerged to be a promising therapeutic weapon to mitigate the inherent risks like use of specific transgenes, marker genes or gene control sequences associated with development of traditional transgenics as disease-resistant transgenic plants can be produced within a regulatory framework. The advantage of RNAi as a novel gene therapy against fungal, viral and bacterial infection in plants lies in the fact that it regulates gene expression via mRNA degradation, translation repression and chromatin remodeling through small non-coding RNAs. Mechanistically, the silencing processes are guided by processing products of the dsRNA trigger, which are known as small interfering RNAs (siRNAs) and microRNAs (miRNAs). The application of tissue-specific or inducible gene silencing, with the use of appropriate promoters to silence several genes simultaneously should enhance researchers’ ability to protect crops against destructive pathogens. This review updates the current state on the use of RNAi, molecular principles underlying the biology of this phenomenon, development of RNAi technologies in relation to plants and discusses strategies and applications of this technology in plant disease management to save the green world from pathogenic intruders in eco-friendly manner.
Multi-Label Truth Inference for Crowdsourcing Using Mixture Models

When acquiring labels from crowdsourcing platforms, a task may be designed to include multiple labels and the values of each label may belong to a set of various distinct options, which is the so-called multi-class multi-label annotation. To improve the quality of labels, requesters usually let one task be independently completed by a group of heterogeneous crowdsourced workers. Then, the true values of the multiple labels of each task are inferred from these repeated noisy labels. In this paper, we propose two novel probabilistic models MCMLI and MCMLD to address the multi-class multi-label inference problem in crowdsourcing. MCMLI assumes that the labels of each task are mutually independent and MCMLD utilizes a mixture of multiple independently multinoulli distributions to capture the correlation among the labels. Both models can jointly infer multiple true labels of each instance as well as estimate the reliability of crowdsourced workers modeled by a set of confusion matrices with an expectation–maximization algorithm. Experiments with three typical crowdsourcing scenarios and a real-world dataset show that our proposed models significantly outperform existing competitive alternatives. When the labels are strongly correlated, MCMLD substantially outperforms MCMLI. Furthermore, our models can be easily simplified to the one-coin models, which show more advantageous when errors are uniformly distributed, or labels are sparse.
Local T 2 Control Charts for Process Control in Local Structure and Abnormal Distribution Data

Purpose: A Control chart is one of the important statistical process control tools that can improve processes by reducing variability and defects. Methods: In the present study, we propose the local multivariate control chart that can efficiently detect abnormal observations by considering the local pattern of the in-control observations. Results: A simulation study has been conducted to examine the property of the proposed control chart and compare it with existing multivariate control charts. Conclusion: The results demonstrate the usefulness and effectiveness of the proposed control chart.
MINING ALGORITHM DISCOTEX ( DISCOVERY FROM TEXT EXTRACTION ) WITH INFORMATION EXTRACTION 1

Text mining concerns looking for patterns in unstructured text. The related task of Information Extraction (IE) is about locating specific items in natural-language documents. This paper presents a framework for text mining, called DISCOTEX (Discovery from Text EXtraction), using a learned information extraction system to transform text into more structured data which is then mined for interesting relationships. The initial version of DISCOTEX integrates an IE module acquired by an IE learning system, and a standard rule induction module. In addition, rules mined from a database extracted from a corpus of texts are used to predict additional information to extract from future documents, thereby improving the recall of the underlying extraction system. Encouraging results are presented on applying these techniques to a corpus of computer job announcement postings from an Internet newsgroup.
NIST Big Data Interoperability Framework: Volume 7, Standards Roadmap

While opportunities exist with Big Data, the data can overwhelm traditional technical approaches. To advance progress in Big Data, the NIST Big Data Public Working Group (NBD-PWG) is working to develop consensus on important, fundamental concepts related to Big Data. The results are reported in the NIST Big Data Interoperability Framework (BDIF) series of volumes. This volume, Volume 7, contains summaries of the work presented in the other six volumes, an investigation of standards related to Big Data, and an inspection of gaps in those standards.
Measurements of water vapor D/H ratios from Mauna Kea, Hawaii, and implications for subtropical humidity dynamics

Water vapor D/H ratios were measured from samples collected on Mauna Kea, Hawaii, in July 2006, and provide new constraints on the processes that control subtropical humidity. D/H ratios ranged from −88‰ at sea level to −321‰ on the summit of Mauna Kea, with sharply decreased D/H ratios above the trade inversion. A simple Rayleigh distillation model underpredicts the observed clear‐sky D/H ratios by as much as 160‰ at the summit. A model that accounts for large‐scale condensation, fractionation, mixing, and transport of water vapor, but ignores more detailed microphysical processes, is able to reproduce the first‐order characteristics of the clear‐sky free troposphere relative humidity and D/H ratios. These results are consistent with remote sensing studies of subtropical D/H ratios and suggest that subtropical clear‐sky water vapor isotopologues may be relatively insensitive to microphysical processes.
The markers of wellbeing: A basis for a theory-neutral approach

Programmes for measuring national wellbeing are challenged by the fact that there are a number of competing theories of what wellbeing consists in, and there is no prospect that the debate between them will be resolved. Although different theories disagree about what constitutes wellbeing, I argue that there is substantial common ground on what I call the 'markers' of wellbeing: things that are either constitutive, productive or indicative of wellbeing. Whatever stands in one of these relations to wellbeing is potentially relevant to its measurement. Something that is constitutive of wellbeing according to one theory will often be productive or indicative of wellbeing according to another and thus, despite their differences, both theories may acknowledge it as a marker of wellbeing. This paper considers which markers of wellbeing are sufficiently widely shared between different mainstream theories that they could form the basis of a theory-neutral approach to the measurement of wellbeing for the purposes of public policy. The paper defines what would count as a marker of wellbeing in this context; sets out criteria that candidate markers would need to meet; and proposes a list of nine markers that I argue are consistent with a wide range of mainstream theories and with widely-held folk assumptions about wellbeing.
Development of e-Handout materials physics based android for improvement learning outcomes senior high school student

This study aims to develop a product of teaching materials e-Handout based physics android equipped audio visual for improve learning outcomes high school students of class XI semester I. Research conducted in Media Development Laboratory Department of Physics State University of Jakarta. This research uses Research and Development (R & D) method with Dick & Carey model modified by Atwi Suparman into Instructional Development Model (MPI). Product feasibility test is done to material expert and media expert, obtained by percentage of material expert 81,67% with excellent interpretation and media expert 93,13% with very good interpretation. The product test was conducted to physics teacher and 32 students, got percentage by physics teacher 89,48% and by 87,37% for all components with 86,88% for content fulfilment component, 88,75% For component of presentation, 87,88% for easy to see component, 86,75% for interesting component, 87,19% for useful and useful component, 87,50% for well-structured component and 86,67% for effective and efficient component The effectiveness test using the gain test obtained a result of 0.65, which indicates an increase in knowledge with moderate interpretation. Based on the results of validation and testing, the development of e-physics-based android-based e-physics teaching materials equipped with audio visual for high school students of class XI semester I can be categorized as appropriate for use as companion teaching materials and can improvement learning outcomes students.
Power system support functions provided by smart inverters—A review

Renewable energy is seen as a viable alternative to traditional energy sources, and distributed generation (DG) based on renewable energy sources has experienced rapid growth worldwide. High penetration of renewable energy based DG systems makes the grid more vulnerable, and stricter standards have been issued for grid interconnection of DG systems. DG systems are expected to be controllable with high flexibility and reliability. Provision of grid support functions and ancillary services, such as reactive power control, fault ride-through and harmonic compensation, is the key to attaining higher utilization of DG. Such functionalities are implemented in new generation smart inverters, which can contribute to the reduced cost of energy and need for additional system resources. The state-of-the-art power system support functions are summarized in this paper for the purpose of enhancing operation in low-voltage networks. Experimental results are given to better understand the implementation of the functions.
Macroalgae and Eelgrass Mapping in Great Bay Estuary Using AISA Hyperspectral Imagery.

Results Increases in nitrogen concentration and declining eelgrass beds in Great Bay Estuary have been observed in the last decades. These two parameters are clear indicators of the impending eutrophication for New Hampshire’s estuaries. The NH Department of Environmental Services (DES) in collaboration with the Piscataqua Region Estuaries Partnership adopted the assumption that eelgrass survival can be used as the target for establishing numeric water quality criteria for nutrients in NH’s estuaries. One of the hypotheses put forward regarding eelgrass decline is that an eutrophication response to nutrient increases in the Great Bay Estuary has been the proliferation of nuisance macroalgae, which has reduced eelgrass area in Great Bay Estuary. To determine the extent of this effect, mapping of eelgrass and nuisance macroalgae beds using hyperspectral imagery was suggested. A hyperspectral image was made by SpecTIR in August 2007 using an AISA Eagle sensor. The collected dataset was then used to map eelgrass and nuisance macroalgae throughout the Great Bay Estuary. Here we outline the procedure for mapping the macroalgae and eelgrass beds. Hyperspectral imagery was effective where known spectral signatures could be easily identified. Comprehensive eelgrass and macroalgae maps of the estuary could only be produced by combining hyperspectral imagery with ground-truth information and expert opinion. Macroalgae was predominantly located in areas where eelgrass formerly existed. Macroalgae mats have now replaced nearly 9% of the area formerly occupied by eelgrass in Great Bay. Results Flow Chart of the Mapping Procedure SHOALS-3000 Survey dates: 9.30. 05 10.1. 05 Spot Spacing: 4 m X 4 m Coverage: 100% End-members Water attenuation * Each laser measurement is color coded to a flight line.
Fabrication and evaluation of multiple pDNA-hydroxyapatite particles for transfection to HEK 293 cells

Aim: This study aimed to assess multiple marker-loaded plasmid DNA (pDNA)-calcium phosphate (CaP) particles (pDNA-CaP) to allow multiple tumor drug delivery for therapy. Despite its widespread use as an in vitro pDNA-CaP transfection, little attention has been paid to multiple delivery systems. Methods: We optimized Ca:P ion ratios by varying ion concentrations in simulated body fluid solutions to induce sufficient protein expression. We examined the effect of the multiple marker-loaded pDNA-hydroxyapatite (HA) particles, including three markers of pDNA on the transfection to human embryonic kidney (HEK293) cells. Results: The presence of three proteins inside the cells demonstrated successful transfection of multiple pDNAs when using the multiple plasmid-loaded (3-pDNA-HA) particles having 2.4 μm in size. Conclusion: The 3-pDNA-HA showed effective transfection for HEK293 cells in comparison to 3 different single-pDNAHA.
Speed traffic sign detection on the CARLA simulator using YOLO

Research on the self-driving and on the autonomous vehicles field is constantly increasing. The administrations are putting all their efforts to raise awareness among drivers about the responsibility that driving a vehicle implies. By their side, researchers are working hard to make vehicles as safe as possible in order to decrease the number of fatal accidents in our roads. Around 30% of these accidents have a key factor: speeding. Since some decades ago until our days, speeding has become a widely investigated topic by the large automotive companies. The European Union (EU) has recently announced new measures that will be taken in 2022 aiming to reduce car accidents. The most relevant one, is the measure that forces new vehicles manufactured at that year to have an intelligent speed assistance device integrated to make the driver aware when exceeding the speed limit of the road. Unfortunately, the oldest cars will remain without that system. The aim of this project is to contribute to this research by integrating into a realistic driving simulator a system able to detect and recognise the speed traffic signs of the road, taking decisions that help the user make the driving process easier and safer. The simulator used in this study is the CAR Learning to Act (CARLA), an open-source simulator for autonomous research that mainly consists of two modules: the CARLA Simulator and the CARLA Python API module. To detect its road signs, a cutting-edge object-detection algorithm is used: the You Only Look Once (Yolo) algorithm. Instead of using a sliding window over several locations within an image, Yolo sees the entire image during the training and testing phases encoding contextual information about the object classes as well as their appearances. This characteristic allows it to be extremely fast while an image is being evaluated. Identifying the speed traffic signs of a road can have a wide range of utilities. In this project, two applications are exposed: a warning application, to notify the user that the vehicle speed has overtaken the maximum allowed speed of that road, and a control application, to reduce the vehicle speed if it exceeds the road speed limit. Results show that the detection procedure is achieved satisfactorily with a precision metric value of 0.92. Moreover, the system is tested both on the CPU and on the GPU, making it reproducible in most of the environments. Running it on the CPU takes a total time of 130 ms, while running it on the GPU, 8 ms are needed to evaluate the current CARLA scene and determine whether it exists or not any speed traffic sign.
ull-field refractive index measurement with simultaneous hase-shift interferometry

Using the phenomenon of total internal reflection and a beam splitting device, a technique of simultaneous phase-shift interferometry is proposed for measuring the full-field refractive index. Because this method applies a beam splitting device that mimics the characteristics of beam splitting and phase modulation, four interferemetric images of various phase distributions can be simultaneously captured. ull-field refractive index imultaneous phase-shift interferometry otal internal reflection Therefore, this setup can avoid errors caused by non-simultaneous capturing of images and offers the benefits of high stability, ease of operation, and real-time measurement. Furthermore, using the phenomenon of total internal reflection, the phase difference between pand s-polarized light varies considerably with the refractive index of a tested specimen. This can substantially increase the measurement resolution. The feasibility of this method is verified using an experiment, and the measurement resolution can be higher than 3.65 × 10−4 RIU. © 2014 Elsevier GmbH. All rights reserved.
Mapping the Publishing Challenges for an Open Access University Press

Managing a New University Press (NUP) is often a one-person operation and, with limits on time and resources, efficiency and effectiveness are key to having a successful production process and providing a high level of author, editor and reader services. This article looks at the challenges faced by open access (OA) university presses throughout the publishing journey and considers ways in which these challenges can be addressed. In particular, the article focuses on six key stages throughout the lifecycle of an open access publication: commissioning; review; production; discoverability; marketing; analytics. Approached from the point of view of the University of Huddersfield Press, this article also draws on discussions and experiences of other NUPs from community-led forums and events. By highlighting the issues faced, and the potential solutions to them, this research recognises the need for a tailored and formalised production workflow within NUPs and also provides guidance how to begin implementing possible solutions.
The Home Team Advantage Gives Football Referees Something to Ruminate about

Observation suggests that referees significantly contribute to the home team advantage in football. The atmosphere created by the home team fans is thought to be the major contributing factor, but the extent of this influence is dependent on the referee. The Decision-Specific Reinvestment Scale was developed to identify those individuals susceptible to disrupted decision making under pressure as a result of their tendency to over-involve consciousness in decision making (Decision Reinvestment) or as a result of their tendency to ruminate upon poor decisions made in the past (Decision Rumination). We asked qualified referees to make a series of video-based decisions to examine whether the home team advantage effect was associated with a high or low tendency for Decision Reinvestment or Decision Rumination. We showed that referees categorized as high Decision Ruminators disproportionately made decisions in favour of the home team. The tendency to ruminate upon poor decisions may help explain some of the variance in the home team advantage effect shown by different referees. We conclude that aspects of personality should be considered in the development of training programs designed to improve and standardise football refereeing.
Coupled-Fed Antenna with Parasitic Ground Structure for Octa-band WWAN/LTE Narrow-Frame Mobile Phone

In this work, an octa-band narrow-frame mobile phone antenna with the size of 80×7×5.5 mm3 is proposed and studied. The designed antenna adopts coupled-fed technology, which is mainly composed of an F-shaped feeding strip, a coupled bending shorted strip, an upright copper plate and a parasitic ground structure. By introducing the F-shaped feeding strip, the coupled bending shorted strip and the upright copper plate, the working frequency of the antenna can cover the lower band (LTE700/GSM850/GSM900) and part of the upper band. Then, with further use of the parasitic ground structure, the upper band (DCS1800/PCS1900/UMTS2100/LTE2300/LTE2500) can be successfully covered in the proposed antenna. Moreover, in this antenna the non-ground portion height is only 7 mm, showing a fully coverage of 2G/3G/4G operating bands without any matching circuit, and great potential for applications in mobile wireless communication systems. In addition, a prototype of the proposed antenna is fabricated and characterized. From the experimental results, the measured -6 dB impedance bandwidths of the antenna at the lower and upper bands are 305 MHz (660-965 MHz) and 1290 MHz (1630-2920 MHz), respectively. Meanwhile, this antenna shows good radiation characteristics in the operating bands.
Comparison of the Sensitivity of Yes/No and Forced Choice Associative Recognition

Yes-no (YN) and forced choice (FC) associative recognition tasks were compared across three experiments to test the varying effects of familiarity. Schliewinsky and Hockley (2016) previously found a discrimination advantage for FC tasks over YN tasks when word pairs were familiarized. The present research is a continuation to further explore the effects of increased familiarity. Experiment 1 manipulated the familiarity of individual items in the word pairs. No discrimination advantage for the FC condition over the YN condition was found when only item familiarity was increased, emphasizing the importance of associative information for accurate associative recognition. There was, though, a significant effect of item familiarity in the FC task but not for YN responses. Experiment 2 manipulated the familiarity of word pairs and compared simultaneous and sequential FC test procedures. Presentation format did not affect FC associative recognition performance. Due to shortcomings of Experiment 3, the significant discrimination advantage found for FC tasks over YN tasks was not replicated in a withinsubjects design. Trends of the data suggest that this advantage does exist. This study provides evidence for reliance of familiarity-based recognition decisions in FC associative recognition tasks and recall-based recollection in YN associative recognition tasks. Researchers cannot assume models like signal detection theory can account for the equal sensitivity of FC and YN procedures for complex tasks such as associative recognition.