Miracle-dz/UniFAR-FTUs huggingface dataset:
Several methods to detect the inheritance and resistance to the diamondback moth in transgenic Chinese cabbage.

A positive selection system was developed for Agrobacterium-mediated trasnsformation of using hypocotyl segments of aseptic seedlings of chinese cabbage as explants, regenerated plants with kanamycin resistance were obtained. The transformed plants with CryIA(c) (Bt) gene were confirmed by Southern blotting analysis, indicating the integration of the transgene into the cabbage genome. Majority of the transgenic plants had only a single copy of the inserted CryIA(c) gene. Leaf section bioassays showed that resistance against larvae of diamondback moth in CryIA(c) transgenic cabbage was significantly enhanced. The inheritance patterns of the transgene in T1 offspring of transgenic cabbage were investigated using PCR analysis and kanamycin resistance test on young seedling leaves.
Multi-Purpose Oriented Real-World Underwater Image Enhancement

Images captured underwater usually suffer from weak illumination, color cast, fuzz and noise, which severely degrade the visibility. Numerous methods have been proposed to improve the quality of underwater images, but rarely of them can give a comprehensive consideration to all these problems, which makes them hard to adapt for various and complex real-world underwater scenes. Herein, a novel multi-purpose oriented approach for real-world underwater image enhancement is proposed. To manipulate different information on the corresponding layers, we firstly decompose the input image into illumination layer and reflectance layer. Subsequently, compensation of the brightness is carried out on the illumination layer, while color correction and contrast enhancement are implemented on the reflectance layer through a multi-scale processing strategy. Benefiting from this strategy, the proposed approach is provided with high control flexibility, which can significantly improve the visibility of underwater images while efficiently suppress the amplification of noise. Both qualitative and quantitative evaluations demonstrate that the proposed method has superior robustness, accuracy and effectiveness for complex marine circumstance.
A New LLSC Series Quasi-Resonant Converter With Narrow Switching Frequency Variation

In this paper, the FHA model including the stray capacitance is analysed. The causes of the voltage gain distortion are studied. Limiting the working frequency is an effective method to solve the voltage gain distortion problem. A new type of the LLSC converter is proposed in the paper. It can regulate the voltage at a constant frequency. At the same time, the soft switch can be realized if the parameter design is reasonable. The proposed converter can overcome the voltage gain distortion problem and obtain the high efficiency at the light load condition. Some mathematical analyses are used to prove that the proposed converter can avoid the voltage gain distortion problems. The simulation and experimental results based on a 200W LLSC converter prototype confirm the correctness of the topology.
System-Level Conducted EMI Model for SiC Powertrain of Electric Vehicles

This paper investigates the system-level conducted EMI model for SiC powertrain of electric vehicles. Firstly, a conducted EMI model for the whole powertrain is presented, which includes battery, inverter, PMSM, AC cables and DC cables. Then, a conducted emission test platform for EV powertrain is built to verify the system-level EMI model. Finally, impact of system layout on EMI noise, including AC cable length, grounding schemes of AC and DC cable shielding layers, PWM schemes, and auxiliary power supply are investigated according to both proposed system-level EMI model and experiment test results.
Impedance-Based Interaction Analysis for AC/DC and DC/DC Converters in Telecom Power System

The power system for fifth generation of mobile networks (5G) requires a high level of reliability to be able to support critical internet of things. It has been reported that the interaction between power converters in a power-electronic-based power system can cause system performance degradation or even instability. This paper analyzes the interaction of AC/DC and DC/DC converters at -48VDC interface in a telecom power system based on a source-load impedance model and measured impedances. The study shows that impedance mismatch of the AC/DC and DC/DC converters in a telecom power system can introduce current ringing when working with step load. Impedance shaping is a good solution to minimize the ringing. By defining and modifying critical parameters that have the largest impact on the impedance characteristics of AC/DC and DC/DC converters, the impedance mismatch could be fixed, thus the ringing is limited.
Regulating Transformer Rectifier Unit (R-TRU) for More Electric Aircraft (MEA)

Regulating Transformer Rectifier Units (R-TRU) are increasingly being utilized in more electric aircraft architectures to increase power system efficiency, reduce system weight, improve power quality and reduce electrical stresses on aircraft electronics. This paper describes an R-TRU electrical architecture which consists of a three-phase Power Factor Corrected (PFC) power converter followed by a resonant mode DC/DC converter with a continuous power capability of 7kW, or 250A at 28VDC. With the selected electrical architecture, efficiency is maximized, weight is minimized, and inherent control redundancy reduces the probability of a fault that can damage load electronics.
Gamification in STEM programming courses: State of the art

Computer programming courses are an essential facet of STEM education, confronted by many pressing challenges. Higher education (HE) students struggle to master programming principles resulting in unsatisfactory pass rates, student retention and low levels of student engagement. Gamification in programming courses has been recognized as a prospective technique that could improve student participation as well as impact learning in a positive way. There is currently a shortage of review studies published in the last two years (2018-2019) that focus specifically on the gamification of programming courses in HE. The aim of this paper is to bridge this gap and to provide a comprehensive review of literature concerning studies that focused on the usage of gamification systems in the teaching of programming courses in HE from 2014 until 2019. Results indicate that the most popular gamification elements that were used in the reviewed studies were leaderboards, followed by points, badges and levels. Additionally, in terms of the tools or instruments that were used to implement gamification solutions, it was discovered that the development of a new gamification platform and the usage of existing gamification tools were the most wide-spread method for gamification implementation. Lastly, from the studies that were reviewed, it was evident that gamification of HE programming courses had a very positive impact on student engagement, student programming knowledge and student motivation. This review paper fills a void in existing literature and could therefore serve as a valuable resource for academe that consider gamifying HE programming courses.
A Novel APWM Control Scheme for GaN Based Full-Bridge CLLC Resonant Converter with Improved Light-Load Efficiency

CLLC resonant converter normally faces light-load problems of unsatisfying voltage regulation and efficiency. This paper presents a novel asymmetric pulse width modulation (APWM) control scheme to improve the voltage regulation ability and efficiency of full-bridge CLLC resonant converter. In this control scheme, the proposed APWM method is utilized to reach the desired voltage gain lower than unity at resonant frequency with soft switching of all switches in light-load conditions, and the pulse frequency modulation (PFM) is combined to realize the voltage gain higher than unity. In comparison with traditional PFM, the proposed control scheme effectively regulates the output voltage and achieves satisfactory efficiency over entire load conditions. This control scheme is verified by experiments on a 21.5V/380V and 200W GaN based full bridge CLLC converter prototype, proving desirable voltage gain and favorable efficiency from light-load to full-load conditions.
A New Method to Assess Competition in Coffee Clonal Trials with Single‐Tree Plots in Côte d'Ivoire

A new method is proposed for the assessment of competition in clonal trials with completely randomized single-tree plots, without needing to choose a covariable a priori linked to competition. This method is applied to a coffee clonal trial planted in a completely randomized single-tree plot design located in Cote d'lvoire. Microenvironmental effects were first taken into account using the conventional Papadakis method. The competition effect (C k ) of each clone (k) was then estimated as the influence of its presence on the residual value, after removal of the clonal effect, of its neighbors. Residuals were thus modeled as a linear regression of the neighboring clones' C value. Competition effects were shown this way to explain 4% of the residual yield in young trees and 10% in adult trees. Several clones had C values significantly different from 0. Some were identified as aggressive for their neighbors (C 0). Architecture and vigor variables that were likely to be related to the C value of clones were then sought. For young trees, vigor, estimated by stem diameter, was best correlated to competition effects: vigorous clones were more aggressive than others. When trees became adult, the length of the orthotropic internodes (L ort ) was the trait that most effectively explained (42%) the competition effect of clones: the shorter the internodes, the less aggressive was the clone. In the future, L ort may thus be used in a selection index to prevent from selecting aggressive coffee clones that would undergo their own aggressiveness when grown alone in plantations.
Cost Minimizing Local Anisotropic Quad Mesh Refinement

Quad meshes as a surface representation have many conceptual advantages over triangle meshes. Their edges can naturally be aligned to principal curvatures of the underlying surface and they have the flexibility to create strongly anisotropic cells without causing excessively small inner angles. While in recent years a lot of progress has been made towards generating high quality uniform quad meshes for arbitrary shapes, their adaptive and anisotropic refinement remains difficult since a single edge split might propagate across the entire surface in order to maintain consistency. In this paper we present a novel refinement technique which finds the optimal trade‐off between number of resulting elements and inserted singularities according to a user prescribed weighting. Our algorithm takes as input a quad mesh with those edges tagged that are prescribed to be refined. It then formulates a binary optimization problem that minimizes the number of additional edges which need to be split in order to maintain consistency. Valence 3 and 5 singularities have to be introduced in the transition region between refined and unrefined regions of the mesh. The optimization hence computes the optimal trade‐off and places singularities strategically in order to minimize the number of consistency splits — or avoids singularities where this causes only a small number of additional splits. When applying the refinement scheme iteratively, we extend our binary optimization formulation such that previous splits can be undone if this prevents degenerate cells with small inner angles that otherwise might occur in anisotropic regions or in the vicinity of singularities. We demonstrate on a number of challenging examples that the algorithm performs well in practice.
Genetic diversity and geographical distribution of strains of mycobacterium tuberculosis complex in Ethiopia: Review

In Ethiopia, tuberculosis (TB) is one of the major infectious diseases with wide spread geographic distribution and endemic nature, which has been well documented both in human and livestock of the country. TB in livestock has an important economic and public health significance although the actual prevalence of animal tuberculosis at the national level is yet unknown. Identification of the etiology of tuberculosis in human and different species of livestock has a paramount significance in order to understand the transmission pattern, the pathogenesis, and control of the diseases. So far, detection of animal TB in Ethiopia has been carried out most commonly on the basis of tuberculin skin testing, abattoir meat inspection and very rarely on bacteriological techniques. These diagnostic methods can not differentiate the specific species of Mycobacterium tuberculosis complex or other species /strains of Mycobacterium, hence utilization of advanced molecular techniques to characterize and genotype the causative agents is important. Genotyping of Mycobaterium species allows understanding the genetic diversity, transmission dynamics and evolutionary/phylogenic relationships of the isolates in different hosts of animal and human. The aim of this paper is, therefore, to review molecular genetic diversity and distribution of mycobacterial infection due to M.tuberculosis complex (mainly M.bovis, M.tuberculosis) and non-tuberculous mycobacterium in Ethiopia in addition to highlighting the zoonotic significance of mycobacterial species originated from livestock and to show the feasible prevention and control options of tuberculosis in cattle and other animals.
Efficient Energy Modeling in Wireless Sensor Networks

WSN consists of a number of sensor nodes, each node assigned with the task of sending the sensed information from surroundings to a central base station. In this type of network setup, sensor nodes are generally energy deficient when compared to the base station which is all powerful. Hence it is essential to look into the pattern of energy consumption and protocols adopted by various nodes, so as to increase the lifetime of the network. In this paper, we present a multi-hop ad hoc routing protocol which is all energy aware, hence it reduces the overall energy consumption in the network, thus increasing the life time of nodes in network. This protocol is an event-driven and location based and designed by assuming a stationary configuration of nodes. In this setup we assume that the sensor nodes are distributed uniformly in a rectangular grid, with base station at one of the corners of grid. Then we give a modeling for energy consumed by each node, assuming that an event happens at one node in the grid. By taking into consideration, a uniform distribution of events all across the grid, we give a formulation for expected energy consumed by a node. Based on the formulation, we realized that there was uneven distribution in the pattern of energy consumed by the nodes that are present at boundaries of the grid, and hence we give a small modification to the proposed protocol which makes the energy consumption pattern uniform, across all the nodes in network.
Programmatic Large Precision Optics Manufacturing

We have derived a set of vector polynomials, orthogonal in the rectangular domain, that can ! t the gradient and curl of surface or wavefront data, called G [1] and C [2] polynomials respectively. Both sets are obtained from the 2D Chebyshev polynomials of the ! rst kind, a scalar basis set also orthogonal in the rectangular domain. The combined set of G and C polynomials can ! t any vector data across rectangular apertures with ease and high accuracy. Generating a very large number of terms is e"cient and makes it ideal for high-resolution or freeform surfaces, gives good reconstruction accuracy when the measured surface has blockers or markers on it (such as ! ducials or scratches), and allows it to perform complex systematic error analysis and corrections for metrology systems [1, 2]. 2.2 Dynamic Con! guration Optical System Design
Depth Distribution of the carotenoid pigments and lipids of some oceanic animals. 2. Decapod Crustaceans

Summary Analysis of the carotenoid pigments of decapod crustaceans has indicated that the visible differences in the appearance of species from different depth horizons are largely due to the disposition of pigments and not to differences in total amount of pigment relative to body size. Species from the upper mesopelagic zone have relatively few large chromatophores, and their chitin is either unpigmented or feebly pigmented. Species from deeper zones have very many small chromatophores and chitin heavily pigmented by unesterified astaxanthin. The major carotenoid pigments of almost all species are astaxanthin and its esters. Lipid analyses have shown that several species of Caridea have very high levels of lipid in the body, and that in many deep-water species wax esters comprise a large proportion of the total lipid. Specific patterns of distribution of the various lipid classes are found in different tissues, with wax esters particularly dominating the hepatopancreas lipids of deep-living species. The patterns of pigment and lipid distribution are discussed in relation to the depth distribution, light environment, and metabolic requirements of the different species.
South Africa: An Important Soybean Producer in Sub-Saharan Africa and the Quest for Managing Nematode Pests of the Crop

With an increase in the global population, a protein-rich crop like soybean can help manage food insecurity in sub-Saharan Africa (SSA). The expansion of soybean production in recent years lead to increased land requirements for growing the crop and the increased risk of exposing this valuable crop to various pests and diseases. Of these pests, plant-parasitic nematodes (PPN), especially Meloidogyne and Pratylenchus spp. , are of great concern. The increase in the population densities of these nematodes can cause significant damage to soybean. Furthermore, the use of crop rotation and cultivars (cvs.) with genetic resistance traits might not be effective for Meloidogyne and Pratylenchus control. This review builds on a previous study and focuses on the current nematode threat facing local soybean production, while probing into possible biological control options that still need to be studied in more detail. As soybean is produced on a global scale, the information generated by local and international researchers is needed. This will address the problem of the current global food demand, which is a matter of pressing importance for developing countries, such as those in sub-Saharan Africa.
Influence of different plantain cropping systems on physical properties of soil and plantain bunch yield

Information on the effects of soil physical properties on plantain yield is rare. A factorial trial was conducted in three southern Cameroonian villages comparing four cropping systems comprising: two planted legumes, (1) Flemingia macrophylla and (2) Pueraria phaseoloides; a crop, (3) hot pepper; and (4) natural regrowth, all planted to plantain established in old forest versus young bush fallow. Initially, bush fallow had significantly higher sand content, mean weight diameter (MWD) and proportion of macroaggregates, but lower clay content and lower proportions of mesoaggregates and microaggregates than forest soil. Between 2002 and 2006, clay and silt content, MWD, geometric mean diameter and the proportion of macroaggregates increased, whereas sand content, bulk density, and the proportions of mesoaggregates and microaggregates decreased in all villages, fallows and cropping systems. Changes in aggregate stability parameters were greater in forest than in bush fallow at Ngoumou and Mfou, and greater in the F. macrophylla and natural regrowth systems than in the pepper and Pueraria systems. In Ngoumou and Nkometou, available water capacity increased. Plantain fresh-bunch yield was unaffected by village, fallow and cropping systems, and was not correlated with soil physical properties or their changes.
A Multivariate Method for Normalization in Affymetrix Oligonucleotide Microarray Experiments

Affymetrix high-density oligonucleotide microarray makes it pos- sible to simultaneously measure, and thus compare the expression profiles of hundreds of thousands of genes in living cells. Genes differentially ex- pressed in different conditions are very important to both basic and medical research. However, before detecting these differentially expressed genes from a vast number of candidates, it is necessary to normalize the microarray data due to the significant variation caused by non-biological factors. During the last few years, normalization methods based on probe level or probeset level intensities were proposed in the literature. These methods were motivated by different purposes. In this paper, we propose a multivariate normaliza- tion method, based on partial least squares regression, aiming to equalize the central tendency, reduce and equalize the variation of the probe level intensities in any probeset across the replicated arrays. By so doing, we hope that one can precisely estimate the gene expression indexes.
Machine learning for sequential interactive models

Recently, a new family of algorithms called Sequential Prediction Models has emerged in Machine Learning. The motivation behind their development is that, while there is a plethora of standard algorithmic solutions for supervised and unsupervised training, most of the methods learn a monolithic predictor function, that is each test instance is processed in a single-step, atomic process. In contrast, some recent studies have proposed a different paradigm in which prediction is reformulated as a sequential decision process, and for which learning the predictor function corresponds to solving a dynamic control problem. Both the motivations and applications of these studies are quite diverse. Unrolling monolithic functions into a sequence of decisions and controlling when the final prediction is made is obviously beneficial to learn "budgeted predictors", so some of the approaches are motivated by either fast prediction or by keeping the number of costly feature evaluations low [1, 9]. Typical applications of these techniques are real-time object detection or web page ranking, trigger design in high-energy physics, or resource-bounded information extraction [7]. Despite the promising applications and diverse algorithmic solutions, sequential prediction still remains a young and unexplored field with numerous unanswered theoretical and algorithmic questions. A very interesting point is that sequential learning models can naturally take into account an explicit interaction with an expert, at two different levels :
Ecological and Evolutionary Consequences of Multispecies Plant-Animal Interactions

▪ Abstract Ecologists and evolutionary biologists are broadly interested in how the interactions among organisms influence their abundance, distribution, phenotypes, and genotypic composition. Recently, we have seen a growing appreciation of how multispecies interactions can act synergistically or antagonistically to alter the ecological and evolutionary outcomes of interactions in ways that differ fundamentally from outcomes predicted by pairwise interactions. Here, we review the evidence for criteria identified to detect community-based, diffuse coevolution. These criteria include (a) the presence of genetic correlations between traits involved in multiple interactions, (b) interactions with one species that alter the likelihood or intensity of interactions with other species, and (c) nonadditive combined effects of multiple interactors. In addition, we review the evidence that multispecies interactions have demographic consequences for populations, as well as evolutionary consequences. Finally, we expl.