Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling invasive plant spread: the role of plant-environment interactions and model structure.

Alien plants invade many ecosystems worldwide and often have substantial negative effects on ecosystem structure and functioning. Our ability to quantitatively predict these impacts is, in part, limited by the absence of suitable plant-spread models and by inadequate parameter estimates for such models. This paper explores the effects of model, plant, and environmental attributes on predicted rates and patterns of spread of alien pine trees (Pinus spp.) in South African fynbos (a mediterranean-type shrubland). A factorial experimental design was used to: (1) compare the predictions of a simple reaction-diffusion model and a spatially explicit, individual-based simulation model; (2) investigate the sensitivity of predicted rates and patterns of spread to parameter values; and (3) quantify the effects of the simulation model's spatial grain on its predictions. The results show that the spatial simulation model places greater emphasis on interactions among ecological processes than does the reaction-diffusion model. This ensures that the predictions of the two models differ substantially for some factor combinations. The most important factor in the model is dispersal ability. Fire frequency, fecundity, and age of reproductive maturity are less important, while adult mortality has little effect on the model's predictions. The simulation model's predictions are sensitive to the model's spatial grain. This suggests that simulation models that use matrices as a spatial framework should ensure that the spatial grain of the model is compatible with the spatial processes being modeled. We conclude that parameter estimation and model development must be integrated pro- cedures. This will ensure that the model's structure is compatible with the biological pro- cesses being modeled. Failure to do so may result in spurious predictions.
NUTXO: A Potent Transaction Tracing System using Centralized Block chain Model

: Currency refers to money in any form when in actual use or circulation as a medium of exchange, especially circulating banknotes and coins. Currency is a very important asset to a country. The existing system has some major flaws when it comes to tracking the amount being transferred between several parties. Such details can easily be tampered by a corrupt party in order to gain an unfair advantage. In our proposed system, each serialized currency note can be tracked end-to-end by introducing blockchain. Changes are updated by a trusted centralized party such as the RBI that issues the notes in India. Using blockchain improves privacy as the hash values are updated only by the aforementioned party and any other changes can easily be tracked down to the source which is the underlying principle of a blockchain .
Distribution System Reliability Assessment for Improved Feeder Configurations

This Paper enlightens the significance of the reliability evaluation for an electrical power distribution network using the analytical technique FMEA. The power distribution system is subject to interruptions frequently as a lot of devices are responsible for its effective operation. All the possible failures of each component are considered and the reliability is evaluated in terms of system reliability indices like SAIFI, SAIDI, ENS, and ASAI. FMEA method observes the failure modes of a procedure and reduces it by ranking over its impacts. In this paper, RBTS bus2 distribution network is used for the analysis. The influences of various feeder reconfigurations are considered and the system reliability indices are obtained. The obtained results show that the reliability of the distribution system is enriched with various feeder reconfigurations. Reliability Evaluation helps to design the future Distribution system and its expansion.
IoT in Connected Cars: Challenges and Chances

With pursuits to furnish secure and satisfied driving, various advanced driver assistance system (ADAS) has been developed over the preceding decades. They offer a broad range of offerings such as anti-lock braking systems (ABS), lane keeping assist (LKA), blind spot facts gadget (BLIS), cruise control (CC), adaptive cruise manage (ACC), etc. Modern vehicles are outfitted with part of sensors device like radar, ultrasonic, photography camera, light detection and ranging (LIDAR), etc., and Global Navigation Satellite System (GNSS) receivers such as a Global Positioning System (GPS) receiver, to support the operation of ADAS. Connecting these systems and competencies to manipulate the actuators of the vehicles, evolves toward automatic using systems, the place vehicles are in a position to navigate themselves besides a human driver concerned. Furthermore, trends in wireless communication allow motors to be connected, both vehicle device -to-vehicle device (V2V) and vehicle unit -to- infrastructure part (V2I). The connections furnish records about the surroundings beyond the vary of sensors. For instance, being aware that the car in front of the previous vehicle is braking at its most power, approves the ego vehicle to begin braking early to avoid or mitigate a severe rear-end collision. Consequently, two linked and automated using standards have been added in the context of cooperative wise transport device (C-ITS). C-ITS includes facts and verbal exchange applied sciences into the transport systems. C-ITS strives for safer, greater efficient, and extra sustainable transport systems. Being related will increase the consciousness of cars about their surroundings. To acquire the dreams and decorate transport systems, interplay and cooperation between actors are key factors. To enable this, dependable communication is required, due to the fact that vehicles riding in automated mode can totally alternate facts with each different via wireless communication. Ultimately, those key elements and reliability extend the complexity of the system, which desires to be tested and evaluated.
Dependent-test-aware regression testing techniques

Developers typically rely on regression testing techniques to ensure that their changes do not break existing functionality. Unfortunately, these techniques suffer from flaky tests, which can both pass and fail when run multiple times on the same version of code and tests. One prominent type of flaky tests is order-dependent (OD) tests, which are tests that pass when run in one order but fail when run in another order. Although OD tests may cause flaky-test failures, OD tests can help developers run their tests faster by allowing them to share resources. We propose to make regression testing techniques dependent-test-aware to reduce flaky-test failures. To understand the necessity of dependent-test-aware regression testing techniques, we conduct the first study on the impact of OD tests on three regression testing techniques: test prioritization, test selection, and test parallelization. In particular, we implement 4 test prioritization, 6 test selection, and 2 test parallelization algorithms, and we evaluate them on 11 Java modules with OD tests. When we run the orders produced by the traditional, dependent-test-unaware regression testing algorithms, 82% of human-written test suites and 100% of automatically-generated test suites with OD tests have at least one flaky-test failure. We develop a general approach for enhancing regression testing algorithms to make them dependent-test-aware, and apply our approach to 12 algorithms. Compared to traditional, unenhanced regression testing algorithms, the enhanced algorithms use provided test dependencies to produce orders with different permutations or extra tests. Our evaluation shows that, in comparison to the orders produced by unenhanced algorithms, the orders produced by enhanced algorithms (1) have overall 80% fewer flaky-test failures due to OD tests, and (2) may add extra tests but run only 1% slower on average. Our results suggest that enhancing regression testing algorithms to be dependent-test-aware can substantially reduce flaky-test failures with only a minor slowdown to run the tests.
Simutrace: A Toolkit for Full System Memory Tracing

The ongoing increase in software and hardware complexity poses a challenge for researchers, system architects and software developers who need to understand a system’s runtime behavior. Traces of executed code paths and memory references as well as interesting events for example in the area of resource management are frequently used to support development and debugging as they provide a valuable insight into the execution. Memory traces place an extraordinary demand on the tracing components due to the fact that the rate at which the processor accesses main memory is inherently higher than the rate of function calls, MPI messages or other system events. While many tracing frameworks for memory traces have been proposed in the past, a major limitation of these frameworks is their restriction to track only selected processes and their inability to monitor privileged system components. Proﬁles generated with these tools therefore do not encompass memory references performed by the operating system (OS), system daemons or (kernel-mode) drivers. In this white paper, we present Simu-trace , a tracing framework for eﬃcient full system memory tracing. Simutrace captures memory accesses at the hardware level, using functional full system simulation for holistic memory traces. Simutrace incorporates an aggressive but fast compressor, making full length, no-loss memory traces of long-running workloads possible.
Avaliação in vitro da atividade fungitóxica de extratos de condimentos na inibição de fungos isolados de pães artesanais

Objetivou-se, na presente pesquisa, avaliar a atividade antifungica in vitro de alho, gengibre, oregano, cravo, canela e tomilho sobre a inibicao e o desenvolvimento de Aspergillus ochraceus, Penicillium roqueforti, Rhizopus stolonifer, desenvolvidos em paes artesanais. Para cada planta foram preparados extratos alcolicos (EA10%, EA20% e EA25%), extrato aquoso (EAQ10%), extrator alcoolico puro (EAP) e testemunha sem extrato e alcool. Para alho, gengibre, oregano incluiu-se o extrato alcoolico da planta fresca (EAF 10%). Os experimentos foram instalados no Laboratorio de Fitopatologia do EcoCentro/EPAMIG, Lavras, MG e no Laboratorio de Fitopatologia do Incaper/CRDS-CS, em Domingos Martins, ES. Os tratamentos foram aplicados sobre os fungos inoculados em placas de petri, em meio BDA. Calcularam-se medias do Indice de Velocidade de Crescimento Micelial (IVCM) e esporulacao. Os EA de plantas desidratadas a 10%, 20% e 25% inibiram totalmente o crescimento micelial dos fungos estudados, com excecao do EA 25% de alho sobre o Penicillium roqueforti e o EA 25% de gengibre sobre o desenvolvimento do Aspergillus ochraceus que nao se diferenciaram da testemunha. O EA de alho teve um efeito nao inibitorio sobre P. roqueforti. Os EA, EAF e EAP apresentaram menor esporulacao em relacao a testemunha, exceto com gengibre e cravo sobre a esporulacao do R. stolonifer e o EAQ apresentou um efeito semelhante ao da testemunha.
An Investigation of the Competitive Anxiety Experiences of Adolescent Figure Skaters

Based on the three-factor hierarchical model of competitive anxiety (Jones, Mullen, & Hardy, 2019), the present study explored the relationship between competitive anxiety and performance among a sample of adolescent figure skaters. Participants included 47 figure skating athletes between the ages of 13 – 17 who were participating in a United States Figure Skating Association (USFSA) sanctioned test session. Analyses revealed that the three higher order factors of the Three Factor Anxiety Inventory (TFAI; Jones et al., 2019) along with years of testing experience, test attempt number and months training for a test were not related and therefore were unable to predict figure skaters’ objective performance scores. Recommendations are provided for the future use of the TFAI with adolescent and child populations. INDEX WORDS: Athlete, Sport performance, Perceived control, Three factor hierarchical model, Regulatory dimension AN INVESTIGATION OF THE COMPETITIVE ANXIETY EXPERIENCES OF ADOLESCENT FIGURE SKATERS
Simple and Effective Retrieve-Edit-Rerank Text Generation

Retrieve-and-edit seq2seq methods typically retrieve an output from the training set and learn a model to edit it to produce the final output. We propose to extend this framework with a simple and effective post-generation ranking approach. Our framework (i) retrieves several potentially relevant outputs for each input, (ii) edits each candidate independently, and (iii) re-ranks the edited candidates to select the final output. We use a standard editing model with simple task-specific re-ranking approaches, and we show empirically that this approach outperforms existing, significantly more complex methodologies. Experiments on two machine translation (MT) datasets show new state-of-art results. We also achieve near state-of-art performance on the Gigaword summarization dataset, where our analyses show that there is significant room for performance improvement with better candidate output selection in future work.
Correlation of ADC values measured using 3T diffusion-weighted MRI and SUVs from fluorodeoxyglucose PET/CT in head and neck squamous cell carcinomas

Head and neck carcinomas account for over 6% of all malignant tumors in adults worldwide. Over 90% of malignant head and neck tumors are squamous cell carcinomas. According to the guidelines of American Joint Committee on Cancer, the tumor node metastasis staging of head and neck cancer requires histopathological diagnosis and additional imaging (1). Fluorodeoxyglucose (FDG) positron emission tomography/ computed tomography (PET/CT) and diffusion weighted magnetic resonance imaging (DW MRI) are increasingly recognized as important for assessing tumor malignancy in oncology.
Upwind flight of tsetse (Glossina spp.) in response to natural and synthetic host odour in the field

Abstract. In Zimbabwe, studies were made of the flight responses of tsetse (Glossina spp.) to synthetic and natural ox odour using arrangements of electric nets.Tsetse flying away from a target showed a significant upwind bias when a blend of carbon dioxide (2/1 min), acetone (500 mg/h), octenol (0.4 mg/h), 4‐methylphenol (0.8 mg/h) and 3‐n‐propylphenol (0.1 ma) was dispensed 15 m upwind, with c. 35% flying upwind.Without carbon dioxide this percentage was significantly reduced to 15% which was not significantly different from that with no odour (8%). This pattern was not altered by reducing the doses of acetone, octenol and phenols by 10–100 times, to levels comparable to those produced by an ox.With natural ox odour or a synthetic equivalent of ox odour dispensed from a ventilated pit 8 m upwind of the target, c. 28% flew upwind.This was reduced significantly to 15% if carbon dioxide was removed.In studies using a 17 m line of nets arranged orthogonally across the prevailing wind line, c. 50% of the catch was caught on the downwind side in the absence of odour.This increased significantly to c.60% when acetone, octenol and phenols were dispensed 15 m upwind, with or without carbon dioxide.With a shorter line (9 m) or an incomplete one (16.5 m long with 5 times 1.5 m wide gaps along its length) there was no change in the proportion caught downwind.For all three lines, dispensing odour upwind increased the catch 2–5 times on both the up‐and downwind sides of the nets.It is concluded that a stronger upwind response to host odour is elicited when carbon dioxide is present.It is suggested that in nature upwind flight is very imprecisely orientated, with tsetse making flights up and down an odour plume ‘searching’ for a host.
Whole-genomeampli¢cation (WGA)ofmarinephotosynthetic eukaryotepopulations

Metagenomics approaches have been developing rapidly in marine sciences. However, the application of these approaches to marine eukaryotes, and in particular to the smallest ones, is challenging because marine microbial communities are dominated by prokaryotes. One way to circumvent this problem is to separate eukaryotic cells using techniques such as single-cell pipetting or flow cytometry sorting. However, the number of cells that can be recovered by such techniques remains low and genetic material needs to be amplified before metagenomic sequencing can be undertaken. In this methodological study, we tested the application of whole-genome amplification (WGA) to photosynthetic eukaryotes. We performed various optimization steps both on a mixture of known microalgal strains and on natural photosynthetic eukaryote populations sorted by flow cytometry. rRNA genes were used as markers for assessing the efficiency of different protocols. Our data indicate that WGA is suitable for the amplification of photosynthetic eukaryote genomes, but that biases are induced, reducing the diversity of the initial population. Nonetheless, this approach appears to be suitable for obtaining metagenomics data on microbial eukaryotic communities.
DECODING THE BIBLE

Biblical studies run along two parallel tracks nowadays. One is the extensive archaeological investigation, in particular on the Israeli soil, which provides novel, often surprising data, many of them supporting, or at least elucidating biblical narratives. The other consists of the analytical studies of the Scriptures, exegesis in the strict sense. In a sense, both approaches have many common features. As we know, biblical text is anything but clear and finding out the proper meaning and historical facts resembles much archaeological excavations. We present some of the relevant new discoveries, which shed new light on the biblical message. In particular, we argue that the Holy Scriptures narrative appears much less unique and original in view of the mythological folklore and historical records of the surrounding people and nations. We devote particular attention to the Hellenistic religious tradition and emphasize the similarities and differences between these two religious paradigms.
Production of chemical defenses in relation to plant growth rate

The growth-rate hypothesis outlined by Coley et al. is based on a model which predicts that investment of resources in anti-herbivore defenses by plants should increase as intrinsic growth rate decreases. This prediction is based on a model which assumes α > β (α = constant relating defense investment to reduction in growth, β = constant determining defense effectiveness). Under conditions in which β > α, the model predicts either no investment in anti-herbivore defenses for plants with relatively high intrinsic growth rates or a maximum investment in anti-herbivore defenses for plants with relatively low intrinsic growth rates. Conditions in which β > α are realistic for both immobile and mobile defenses
Organisational Citizenship Behaviour: Exploring member attitudes to BVD control schemes in the UK

Bovine Viral Diarrhoea is a viral disease of cattle with large impacts on herd productivity and reproduction (Houe, 1999). The disease in endemic in the UK and estimates of the overall cost i.e. control and prevention ranges from £25-60 million per annum (Bennet, 2003). In a study in Scotland, benefits to eradicating the disease at the national level were found to be £47 million in „discounted economic gain‟ (Weldegebriel et al., 2009). Thus, at the macro-level, eradication of BVD appears to be sensible and economically prudent.
Classification of Intrusion using Artificial Neural Network with GWO

In the present milieu of connected world, where security is the major concern, Intrusion Detection System is the prominent area of research to deal with various types of attacks in network. Intrusion detection systems (IDS) finds the dynamic and malicious traffic of network, in accordance to the aspect of network. Various form of IDS has been developed working on distinctive approaches. One popular approach is machine learning in which various algorithms like ANN, SVM etc. have been used. But the most prominent method used is ANN. The performance of the ANN can significantly be improved by combining it with different metaheuristic algorithms. In present work, GWO is used to optimize ANN. For this KDD-99 data-set is used to classify various types of attacks i.e. denial of service (DOS), normal and other form of attack. The present paper provides detailed analysis of the performance of Artificial Neural Network and optimized Artificial Neural Network with GA, PSO and GWO. The research shows that ANN with GWO outperform as compared to others (ANN, ANN with PSO and ANN with GA).
Analyzing the Behavior of Reactive Protocols in Wireless Sensor Networks Using TCP Mode of Connection

: Wireless sensor networks are getting famous day by day in the current days of research and applications. These networks are becoming important in day to day communications. In these networks, all the nodes in the network will act as a router and sends the data collecting from other nodes to further other nodes inthe networks. These networks may be the same or the other network.In general several types of nodes and the other protocols are available in the networks.Someprotocols are hugely used while some other protocols are used very less in real time applications. These protocols are used based onvarious scenarios.The performance of the networks and the protocols used in the networks might be changed from time to time based on various parameters. Some of the important performance metrics of these networks and protocols are like network topology, a number of nodes in the network, seed time, speed time and pause time. Some of the protocols that were discussed in the current are DSR, DSDV and AODV. The different connection types that were considered here are Constant bit rate and TCP. The performance of the currently considered protocols are analyzed by using various performance metrics like end to end delay, losses in packet ratio and packet delivery ratio. The simulator NS2.35 was used in the current work to analyze the performance of these protocols.
Near-Real-Time Bio-Optical Water Quality Assessment Using Landsat OLI and Sentinel MSI for Case II Waters

Inland freshwater reservoirs are important resources serving both the natural and human ecosystems. Knowledge of the state of these resources is therefore important. However, the conventional assessment and monitoring systems are expensive and time consuming creating a need for new innovative methods of monitoring their state. Studies have been conducted to assess the viability of other methods of water quality assessment for accurate and more reliable data. This study tries to assess the viability of remote sensing as a water quality assessment tool. Two sensors are assessed namely Landsat OLI mounted on the Landsat 8 satellite and ESA Multispectral Instrument (MSI) mounted on Sentinel 2A satellite. Chebara Dam in Elgeyo Marakwet was chosen for the study. The Water quality parameters assessed were Turbidity, Suspended Particulate Matter and Chlorophyll-a. For the case study, new empirical regression equations were developed to relate the water quality parameters to the reflectances from OLI and MSI. The equations developed were tested and validated using different error estimators. The accuracy of the equations showed that remote sensing has the potential for use as a monitoring tool for inland water bodies.