Miracle-dz/UniFAR-FTUs huggingface dataset:
An atypical Phytophthora sojae RxLR effector manipulates host vesicle trafficking to promote infection

In plants, the apoplast is a critical battlefield for plant-microbe interactions. Plants secrete defense-related proteins into the apoplast to ward off the invasion of pathogens. How microbial pathogens overcome plant apoplastic immunity remains largely unknown. In this study, we reported that an atypical RxLR effector PsAvh181 secreted by Phytophthora sojae, inhibits the secretion of plant defense-related apoplastic proteins. PsAvh181 localizes to plant plasma membrane and essential for P. sojae infection. By co-immunoprecipitation assay followed by liquid chromatography-tandem mass spectrometry analyses, we identified the soybean GmSNAP-1 as a candidate host target of PsAvh181. GmSNAP-1 encodes a soluble N-ethylmaleimide-sensitive factor (NSF) attachment protein, which associates with GmNSF of the SNARE complex functioning in vesicle trafficking. PsAvh181 binds to GmSNAP-1 in vivo and in vitro. PsAvh181 interferes with the interaction between GmSNAP-1 and GmNSF, and blocks the secretion of apoplastic defense-related proteins, such as pathogenesis-related protein PR-1 and apoplastic proteases. Taken together, these data show that an atypical P. sojae RxLR effector suppresses host apoplastic immunity by manipulating the host SNARE complex to interfere with host vesicle trafficking pathway.
Long‐term single‐column model intercomparison of diurnal cycle of precipitation over midlatitude and tropical land

General Circulation Models (GCMs) have for decades exhibited difficulties in modelling the diurnal cycle of precipitation (DCP). This issue can be related to inappropriate representation of the processes controlling sub‐diurnal phenomena like convection. In this study, 11 single‐column versions of GCMs are used to investigate the interactions between convection and environmental conditions, processes that control nocturnal convections, and the transition from shallow to deep convection on a diurnal time‐scale. Long‐term simulations are performed over two continental land sites: the Southern Great Plains (SGP) in the USA for 12 summer months from 2004 to 2015 and the Manacapuru site at the central Amazon (MAO) in Brazil for two full years from 2014 to 2015. The analysis is done on two regimes: afternoon convective regime and nocturnal precipitation regime. Most models produce afternoon precipitation too early, likely due to the missing transition of shallow‐to‐deep convection in these models. At SGP, the unified convection schemes better simulate the onset time of precipitation. At MAO, models produce the heating peak in a much lower level compared with observation, indicating too shallow convection in the models. For nocturnal precipitation, models that produce most of nocturnal precipitation all allow convection to be triggered above the boundary layer. This indicates the importance of model capability to detect elevated convection for simulating nocturnal precipitation. Sensitivity studies indicate that (a) nudging environmental variables towards observations has a minor impact on DCP, (b) unified treatment of shallow and deep convection and the capability to capture mid‐level convection can help models better capture DCP, and (c) the interactions of the atmosphere with other components in the climate system (e.g. land) are also important for DCP simulations in coupled models. These results provide long‐term statistical insights on which physical processes are essential in climate models to simulate DCP.
A Lego-Based Soccer-Playing Robot Competition For Teaching Design

Course Objectives in the ME382 Instrumentation Laboratory at Norwich University include 1.Design of systems involving both computer hardware and software. 2.Use of modern computer tools for data acquisition and control. By having the students use a Lego Mindstorms robot kit and Robolab graphical programming software as a rapid prototyping tool combination a beginning at achieving both outcomes can be efficiently accomplished. The problem to be solved during the first six laboratory sessions is to design, build, test and compete with a robot that plays soccer. This competition is patterned after the International RoboCup Junior competition. The kit has the necessary components to allow the students to be creative in their mechanical designs. Since the RoboLab software is realized as a National Instruments LabView Virtual Instrument, this experience naturally gives students the background to design their own custom data acquisition virtual instruments later in the semester using the National Instruments computer-based data acquisition equipment. The spirit of competition heightens the motivation for the engineering lessons. The Australian competition winner (2000) was used as a case study. Mechatronics is stressed from the beginning. The students model their robot dynamics and use a digital video camera to measure critical performance criteria. They redesign the suggested software to achieve a superior ball handling performance. Thrashing behavior detection is discussed and designed into the software to help the autonomous robots recover when they get stuck or grapple with another robot. Players used the touch sensor to communicate pre-kickoff information such as which goal to shoot toward. The software design needed to allow for timely attention to the sensors as well as resolve conflicts when two or more sensors were demanding a response at the same time. The most successful designs used a subsumption software architecture. The students genuinely enjoyed the competition while learning integrated hardware and software design strategies. Their later experience with LabView writing their own stripchart Virtual Instrument proceeded naturally from their RoboLab experience and they have the confidence to be able to realize custom industrial automation solutions in the future.
A Strategic Marketing Framework for Emerging Out of the Climate Change Social Trap: The Case of the Fashion Industry

Climate change mitigation is arguably the most significant challenge of the twenty-first century. On the foundations of research on social traps by economists and behavioral scientists, this research: (1) conceptualizes the climate change social trap as the behavior of entities (firms, individuals, or social groups) favoring short-term positive consequences over long-term negative consequences of climate change for society; (2) provides a brief overview of the impact of the fashion industry on climate change; (3) develops a summary overview of research on social traps and taxonomies of solutions for social traps; (4) discusses, in detail, a strategic marketing framework built on a taxonomy developed in macromarketing; and (5) using the framework, evaluates 130 leading companies in the fashion industry with reference to their strategic marketing efforts to draw insights for emerging out of the climate change social trap. We conclude with a discussion of the implications of this research for marketing theory and practice in helping firms emerge out of social traps in general, and the climate change social trap in particular.
LFT modeling and mu-analysis of Darwin type spacecraft

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
A Novel Low-Cost Product Data Management System

AbstractMany small and medium size companies have multiple products with a complex supply chain. To these companies, managing their product data is vital and yet may be headache because of the complexity of the product, the manufacturing processes and the supply chain. There exist some commercial Product Data Management (PDM) software systems. However, these PDM systems are expensive. Moreover, they are difficult to use. This paper presents a novel low cost product data management system. This system is developed based on Microsoft Foxpro® but can simply run in the MS Windows® environment. It integrates the design (CAD files), the supply chain (MS Excel® files), the production schedule (MS Project® files), and the database (MS Foxpro®). Moreover, it can be expanded to include other information, such as manufacturing simulation. Its Graphic User Interface (GUI) makes the system easy to use and to maintain. A practical demonstration example on mechanical watch movement is included.
Beach fecal coliforms

A combination of the STORM runoff model and a two-dimensional dynamic lake type model successfully reproduced the fecal coliform levels of an urban beach on a lake in the Ottawa River. The elevated fecal coliform levels were associated with rainfall events and runoff from two large catchments upstream of the beach. Due to prevailing conditions in the lake the second largest summer storm did not produce elevated fecal coliform levels while the third and fourth largest storms did. The models predicted these events.The STORM model was calibrated on a subcatehment and supplied the runoff flow volumes and pollution levels to the dynamic lake model. The other input data for the lake model were supplied by field measurements.The models were used to assess the effectiveness of management options to improve the water quality on the beach. The most cost-effective option was identified by the model predictions. Key words: beach fecal coliform predictions, stormwater beach fecal coliforms, storm, runoff, modelling.
Evolving Prioritization for Software Product Management

The quality of a product is commonly defined by its ability to satisfy stakeholder needs and expectations. Therefore, it is important to find, select, and plan the content of a software product to maximize the value for internal and external stakeholders. This process is traditionally referred to as requirements engineering in the software industry, while it is often referred to as product management in industries with a larger market focus. As an increasing number of software products are delivered to a market instead of single customers, the need for product management in software companies is increasing. As a side effect, the need for mechanisms supporting decisions regarding the content of software products also increases. While decision-support within requirements engineering and product management is a broad area, requirements prioritization together with release planning and negotiation are considered as some of the most important decision activities. This is particularly true because these activities support decisions regarding the content of products, and are hence drivers for quality. At the same time, requirements prioritization is seen as an integral and important component in both requirements negotiation (with single customers) and release planning (with markets) in incremental software development. This makes requirements prioritization a key component in software engineering decision support, in particular as input to more sophisticated approaches for release planning and negotiation, where decisions about what and when to develop are made. This thesis primarily focuses on evolving the current body of knowledge in relation to release planning in general and requirements prioritization in particular. The research is carried out by performing qualitative and quantitative studies in industrial and academic environments with an empirical focus. Each of the presented studies has its own focus and scope while together contributing to the research area. Together they answer questions about why and how requirements prioritization should be conducted, as well as what aspects should be taken into account when making decisions about the content of products. The primary objective of the thesis is to give guidelines on how to evolve requirements prioritization to better facilitate decisions regarding the content of software products. This is accomplished by giving suggestions on how to perform research to evolve the area, by evaluating current approaches and suggest ways on how these can be improved, and by giving directions on how to align and focus future research to be more successful in development of decision-support approaches. This means that the thesis solves problems with requirements prioritization today, and gives directions and support on how to evolve the area in a successful way.
Analysis of Grade Difference of TPACK Among Teacher-Oriented Students of Mathematics in Qinghai-Tibet Plateau Area

TPACK is the basis of effective teaching in today's era, and it is also the key content of teachers' professional development. The mastery of TPACK of the teacher-oriented students of mathematics in local colleges and universities directly affects the quality of mathematics teaching in the region in the future. The mastery of TPACK is affected by many factors such as educators' own psychological or external conditions. This study takes into account the factors affecting the mastery of TPACK, designs the teacher-oriented students of mathematics TPACK questionnaire, and conducts a full sample survey of the teacher-oriented students of mathematics in Qinghai-Tibet plateau area. The results show significant grade differences in CK, PK, PCK, TCK, TPK and TPCK of the teacher-oriented mathematics students in the Qinghai-Tibet plateau area. Furthermore, the influence intensity of each factor on TPACK of the teacher-oriented students of mathematics in different grades is different.
Dual naming as a mechanism to recognize multiple identities; Casablanca or Ad-Dār al-Bayḍā

Abstract. The primary aim of place names is to provide clear direction and reference in order to distinguish geographical entities. The Moroccan linguistic situation allows for a bilingual presentation of place names, with an Arabized version and a French counterpart that differs phonetically. On the other hand, Casablanca has dual naming, a colonial name, and an Arabic variant, which is not simply a translation that happened as a result of Arabization policies introduced after the country's independence. This study relies mainly on questionnaires, in addition to interviews, in an attempt to address the following aspects: The attitude towards the standardization of only one variant, variants and the city's cultural heritage and significance, standardization of only one variant and the accurate representation of the place, dual naming as a reminder of the multiple place histories vs. dual naming as a mere case of the language difference, and Moroccans and the etymology of the variants. The findings indicate that Casablanca shifts from a mere marker of the colonial period to an active maker of the city's heritage. Its meaning is disconnected from its historical anchorage and converted into an instrument of identity and means of historical memory. Moreover, the choice of one variant is perceived as a loss of toponymic identity, which will serve as a hindrance against the population and their relation to their past.
Timing-Error-Tolerant Network-on-Chip

With technology scaling, the wire delay as a fraction of the total delay is increasing, and the communication architec- tureisbecomingamajorbottleneckforsystemperformanceinsys- tems on chip (SoCs). A communication-centric design paradigm, networks on chip (NoCs), has been proposed recently to address the communication issues of SoCs. As the geometries of devices approach the physical limits of operation, NoCs will be susceptible to various noise sources such as crosstalk, coupling noise, process variations, etc. Designing systems under such uncertain conditions become a challenge, as it is harder to predict the timing behavior of the system. The use of conservative design methodologies that consider all possible delay variations due to the noise sources, tar- getingsafesystemoperationunderallconditionswillresultinpoor system performance. An aggressive design approach that provides resilience against such timing errors is required for maximizing system performance. In this paper, we present T-error, which is a timing-error-tolerant aggressive design method to design the individual components of the NoC (such as switches, links, and network interfaces), so that the communication subsystem can be clockedatamuchhigherfrequencythanatraditionalconservative design (up to 1.5! increase in frequency). The NoC is designed to tolerate timing errors that arise from overclocking without sub- stantially affecting the latency for communication. We also present a way to dynamically configure the NoC between the overclocked mode and the normal mode, where the frequency of operation is lower than or equal to the traditional design's frequency, so that the error recovery penalty is completely hidden under normal operation. Experiments on several benchmark applications show large performance improvement (up to 33% reduction in average packet latency) for the proposed system when compared to tradi- tional systems. Index Terms—Aggressive design, networks on chip (NoCs), systems on chip (SoCs), timing errors.
Quantifying Decoherence via Increases in Classicality

As a direct consequence of the interplay between the superposition principle of quantum mechanics and the dynamics of open systems, decoherence is a recurring theme in both foundational and experimental exploration of the quantum realm. Decoherence is intimately related to information leakage of open systems and is usually formulated in the setup of “system + environment” as information acquisition of the environment (observer) from the system. As such, it has been mainly characterized via correlations (e.g., quantum mutual information, discord, and entanglement). Decoherence combined with redundant proliferation of the system information to multiple fragments of environment yields the scenario of quantum Darwinism, which is now a widely recognized framework for addressing the quantum-to-classical transition: the emergence of the apparent classical reality from the enigmatic quantum substrate. Despite the half-century development of the notion of decoherence, there are still many aspects awaiting investigations. In this work, we introduce two quantifiers of classicality via the Jordan product and uncertainty, respectively, and then employ them to quantify decoherence from an information-theoretic perspective. As a comparison, we also study the influence of the system on the environment.
Pest Detection in Plants Using Convolutional Neural Network

Abstract: Agriculture or farming is an imperative occupation since the historical backdrop of humanity is kept up. Artificial Intelligence is leading to a revolution in the agricultural practices. This revolution has safeguarded the crops from being affected by distinct factors like climate changes, porosity of the soil, availability of water, etc. The other factors that affect agriculture includes the increase in population, changes in the economy, issues related to food security, etc. Artificial Intelligence finds a lot of applications in the agricultural sector also which includes crop monitoring, soil management, pest detection, weed management and a lot more. Significant problems for sustainable farming include detection of illness and healthy monitoring of plants. Therefore, plant disease must automatically be detected with higher precision by means of image processing technology at an early stage. It consists of image capturing, preprocessing images, image segmentation, extraction of features and disease classification. The digital image processing method is one of those strong techniques used far earlier than human eyes could see to identify the tough symptoms. Considering different climatic situations in various regions of the world that impact local weather conditions. These climate changes affect crop yield directly. There is a great demand for such a platform in the world of today which would enable the farmer market his farm products. We have proposed in this study a system where farmers can sell their products directly to customers without the intervention of distributors and traders. The predictive analytics system is necessary for the farmer to get the maximum yield which benefit the farmer. This may be done if the environment, market conditions and knowledge of the timely planning of farms are known properly. Keywords: Pest Detection, Artificial Intelligence, Agriculture, Image processing, Convolutional Neural Networks
Backwater calculations for the St. Lawrence Seaway with the first computer in Canada

As the oldest branch of engineering, it is fitting that civil engineering was the first in Canada to make use of modern computing techniques. In the early 1950s, serious planning was underway regarding the St. Lawrence Seaway and Power Project, but before construction could begin, a lengthy series of backwater calculations was required to predict upriver changes to the water profile. It was estimated that these calculations would have taken 20 person-years to complete by hand, but in 1952 and 1953 Ontario Hydro was able to make use of the first electronic computer in Canada – the Ferut at the University of Toronto – to complete in about eight months. These were the first major calculations carried out on any electronic computer in Canada, and helped prove that an all-Canadian navigation route was possible.
Evolving Pre-Trained CNN using Two-Layers Optimizer for Road Damage Detection from Drone Images

There are numerous pre-trained Convolutional Neural Networks (CNN) introduced in the literature, such as AlexNet, VGG-19, and ResNet. These pre-trained CNN models could be reused and applied to tackle different image recognition problems. Unfortunately, these pre-trained CNN models are complex and have a large number of convolutional filters. To tackle such a complexity challenge, this research aims to evolve a pre-trained VGG-19 using an efficient two-layers optimizer. The proposed optimizer performs filters selection of the last layers of VGG-19 guided by the accuracy of the linear SVM classifier. The proposed approach has three main advantages. Firstly, it adopts a powerful two-layers optimizer that works with a micro swarm population. Secondly, it automatically evolves a lightweight deep model which uses a small number of VGG-19 convolutional filters. Thirdly, It applies the developed model for real-world road damage detection from drone-based images. To evaluate the effectiveness of the proposed approach, a total of 529 images were captured by using a drone-based camera for various road damages. Reported results indicated that the proposed model achieved 96.4% F1-score accuracy with a reduction of VGG-19 filter up to 52%. In addition, the proposed two-layers optimizer was able to outperform several related optimizers such as AOA (Arithmetic Optimization Algorithm), Wild Geese Algorithm (WGO), Particle Swarm Optimization (PSO), Comprehensive Learning Particle Swarm Optimization (CLPSO), and Reinforcement Learning-based Memetic Particle Swarm Optimization (RLMPSO).
A Survey on Protocols, Platforms and Simulation Tools for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are becoming very common technology which combine sensing, processing, and wireless multi-hop networking. This paper provides a wide review of the present state about WSNs at the time of its writing. Following a top- down approach, WSNs concept, definition and applications is provided. Furthermore, an overview of WSNs constrains and judgment metrics such as lifetime and latency is given. Then, the communication protocol stack for WSNs is described, and protocols developed for each layer are discussed. Finally, this paper provides review and comparisons of current simulation programs All of these features make the paper valuable for an extensive variety of possible readers, researchers in WSNs, students stating research in WSNs, specialists wanting to offer WSN solutions, and WSN application designers.