Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Variations in CIMMYT and Ethiopian Maize(Zea mays L.) Inbred Lines as Determined by Microsatellite Markers

AbstractMolecular markers are more useful in identifying parental inbred lines crosses ofwhich create genetic variation among progenies in the advanced generation morerealistically than selection based on phenotypic data. In this study, 37 maize inbredlines including 14 of Ethiopian and 23 of CIMMYT origin were studied using 28microsatellite markers. Among the 23 CIMMYT inbred lines, 13 were soil aciditytolerant lines and were recently introduced. The main objective was to identifydistantly related Ethiopian maize inbred lines and soil acidity tolerant inbred linesof CIMMYT origin that could be used in broadening the genetic basis of maize fortolerance to soil acidity. Analysis of molecular variance indicated higher geneticvariability (77%) among the inbred lines indicating ability of the SSR markers indiscriminating the inbred lines. One-hundred and seven alleles were identified inthe inbred lines with average of 3.71 alleles per locus. Expected hetrozygosity (He)and major allele frequency ranged from 0.09 to 0.61 and from 0.34 to 0.95,respectively, indicating higher genetic variability among the inbred lines, whichcould be exploited in breeding program. Polymorphic information content (PIC)generated by each marker ranged from 0.10 (Bnlg 1063) to 0.74 (Umc 2205) with amean of 0.50 indicating their power in discriminating the inbred lines. Nei’s geneticdistance among pairs of the 37 maize inbred lines varied from 0.16 to 0.98. Pairs ofinbred lines of Ethiopian origin had genetic distance that ranged from 0.26 to 0.98and the highest genetic distance was in this population. Pairs of inbred lines ofEthiopian and CIMMYT inbred lines developed for tolerance to soil acidity hadgenetic distance that varied from 0.42 to 0.95 and 41.6 % of the pairs had geneticdistance of more than 0.8 indicating their potential in broadening the genetic basisof maize for developing varieties tolerant to soil acidity. Specifically, 124-b(109)was distantly related with five inbred lines, viz., CML359, CML360, CML361,CML436 and CML438, and F-7215 was also distantly related with CML361 withNei’s genetic distance of more than 0.9. These pairs of inbred lines could beexploited in pedigree breeding through which segregating populations can beselected for desirable traits in combination with tolerance to soil acidity. However,the soil acidity tolerant inbred lines have to be evaluated for adaptation toEthiopian environment before embarking on exploiting their potential in breedingfor tolerance to soil acidity.
Behavioral Conditioning and Techniques for Trapping Barred Owls (Strix Varia)

ABSTRACT Condicionamiento Comportamental y Técnicas para Atrapar a Strix Varia Entrenamos individuos de Strix varia para asociar un silbido o llamado con la provisión de alimento. Esto facilitó enormemente atrapar a las aves, localizar sus nidos y pichones, y reconocer el reemplazo en las parejas reproductivas. Atrapamos 61 lechuzas en un total de 78 veces. Cuarenta y cuatro de las lechuzas habían sido entrenadas antes de su captura. Las trampas bal-chatris (36 capturas) y las redes de niebla colapsables dho-gazas (37 capturas) fueron nuestros métodos preferidos para capturar a las lechuzas. Describimos nuestras técnicas de entrenamiento y de captura como una ayuda para otros estudios sobre S. varia y otras especies de lechuzas, para las cuales sospechamos que éstas técnicas pueden ser aplicables.
Genetic characterization of Callosciurus (Rodentia: Sciuridae) Asiatic squirrels introduced in Argentina

Abstract Squirrels have been traded in the pet market for several decades, and numerous species have established in the wild. The Asiatic species Callosciurus erythraeus and Callosciurus finlaysonii have been introduced into other parts of Asia, in Europe and South America. In this study, (1) we conducted a genetic characterization of C. erythraeus introduced into Argentina and compared them with native and introduced populations in Asia, and (2) we analyzed genetic variation among the four invasion foci in Argentina in order to corroborate that the pathway of invasion was a single introduction event in the country and subsequent translocations. We analyzed mitochondrial (cytochrome b, Cyt b; cytochrome oxidase c subunit I, COI and D-loop) and nuclear (recombination activating gene I, RAGI) DNA markers using the classical method (DNA barcoding gap analysis) and also the Automatic Barcode Gap Discovery method (ABGD). The markers D-loop, COI, and RAG1 indicated that the introduced squirrels from the different invasion foci formed a monophyletic group that, together with only one haplotype for the D-loop and COI markers, supported the hypothesis of one introduction event into Argentina followed by subsequent translocations. Unexpectedly, sequences from squirrels captured in Argentina were more related to C. finlaysonii than to C. erythraeus for D-loop and Cyt b markers. However, intraspecific variation among sequences of C. erythraeus belonging to different subspecies or collected in different regions was large and comparable with the distance to the sequences from Argentina. The ABGD method also indicated large genetic variability within C. erythraeus and close proximity between squirrels from Argentina and C. finlaysonii. The complex taxonomy of Callosciurus, as occurs with the sister species C. erythraeus and C. finlaysonii, requires a thorough systematic revision. A simultaneous analysis of diagnostic morphological characters and genetic markers is needed and will provide new insight regarding the worldwide invasion of Asiatic squirrels.
Pathogenic and genetic variability among Colletotrichum gloeosporioides isolates from different yam hosts in the agroecological zones in Nigeria

Anthracnose, caused by Colletotrichum gloeosporioides Penz. , is the most severe foliar disease of water yam (Dioscorea alata) worldwide. Population genetic analyses can yield useful insights into the evolutionary potential of C. gloeosporioides and thus lead to the development of appropriate disease management strategies. The genetic structure of C. gloeosporioides populations from yam and non-yam hosts in three agroecological zones of Nigeria was investigated. Microsatellite-primed polymerase chain reaction (MP-PCR), virulence phenotyping using five putative D. alata differentials, cross-inoculation tests, and the presence/absence of a Glomerella teleomorph in yam fields were used to infer the evolutionary potential of C. gloeosporioides on yam. We observed high genotypic diversity (GD = 0.99 to 1.00) for populations from all hosts and agroecological zones, with multiple pathogen genotypes in individual anthracnose lesions. Genetic differentiation was low among pathogen populations from different hosts (G[subscript ST] = 0.10, [theta] = 0.034), and agroecological zones (G[subscript ST] = 0.04, [theta] = 0.018), indicating limited host differentiation and significant gene flow. No evidence was found for the existence of C. gloeosporioides f. sp. alatae reported in previous studies. The fungus was recovered from several non-yam host species commonly found in yam fields but non-yam isolates caused only mild to moderate symptoms on yam. Eighteen C. gloeosporioides virulence phenotypes were identified among 217 isolates but there was a weak correlation (r = 0.02, P = 0.40) between virulence phenotype and MP-PCR haplotype. Consistent with the above findings, we observed for the first time the Glomerella teleomorph on anthracnose-infected yam plants in Nigeria, indicating that sexual recombination might play an important role in anthracnose epidemics on yam. The implications of these findings for C. gloeosporioides evolutionary potential and anthracnose resistance breeding are discussed.
Construction of Super NLPDE’s Traveling Waves Solutions of Super KdV Equation with Emphasis to Applications

Construction of super NLPDE’s is performed to the aim of finding novel dynamic evolution equations that describe highly dispersive nonlinear systems. It is found that a coupled NLPDE generates a super NLPDE. Which may reveal novel nonlinear phenomena and provide an interpretation of the phenomena complexity. Attention is focused to find the super formulation of the nonlinear, coupled nonlinear Schrodinger (NLS, CNLS), Davey-Stwartson (generalized Zakharov), Higg’s, and coupled KdV equations. The CNLS equation may help to control the propagation of soliton (pulse) waves in fiber optics. These equations are currently used in engineering such as the management of the concept of soliton in the development of modern technology via the study of Bose-Einstein condensate phenomena. Further, to test the behavior and study the characteristics of the propagation of laser pulse and high-power fiber laser applications. Here, the extended unified method is used to find the solutions of the traveling wave to the super KdV equation. These solutions show solitary, soliton with double kinks waves and lumps. We think that the novel equations constructed here will open a new trend of research that may lead new phenomena in the applied sciences.
Differential Pulse Polarography Method for the Determination of Trace Fe, Ni, Pb, Zn, Se and Cu in Black Tea Leaves

In this work a new and simple polarographic method has been established for the determination of trace elements present in tea. After digestion with acids, tea samples were analyzed using various electrolytes such as acetate and ammonia at different pH values in the presence or absence of EDTA. Thus, it was possible tochoosethe best medium for the determination of6 trace elements in one tea sample. Polarographic peaks of copper and iron could be separated in HAc at about pH =7 in the presence of EDTA and their quantities were determined. Ni and Zn peaks could be separated and determined in ammonia buffer at about pH= 10. Lead could be determined at pH= 2HAc electrolyte. Selenite, was determined from its hydrogen catalytic peak in KCl, pH= 2 medium in the presence of Mo (VI). The LOD was found as 2.4x10 for instead of (S/N=3). The trace element ranges in black tea were found as, Fe 35 μg/g, Cu 45 μg/g, Ni 19 μg/g, Zn 22 μg/g, Pb 28 μg/g and Se 77 μg/g.
Mapping tree species in temperate deciduous woodland using time‐series multi‐spectral data

Questions: What is the optimum combination of image dates across a growing season for tree species differentiation in multi-spectral data and how does species composition affect overstorey canopy density? Location: Monks Wood, Cambridgeshire, eastern England, UK. Methods: Six overstorey tree species were mapped using five Airborne Thematic Mapper images acquired across the 2003 growing season (17 March, 30 May, 16 July, 23 September, 27 October). After image pre-processing, supervised maximum likelihood classification was performed on the images and on all two-, three-, four- and five-date combinations. Relationships between tree species composition and canopy density were assessed using regression analyses. Results: The image with the greatest tree species discrimination was acquired on 27/10 when the overstorey species were in different stages of leaf tinting and fall. In this image, tree species were mapped with an overall classification accuracy (OCA) of 71% (kappa 0.63). A similar OCA was achieved from the other four images combined (OCA 72%, kappa 0.64). The highest classification accuracy was achieved by combining three images: 17 March, 16 July, 27 October. This achieved an OCA of 84% (kappa 0.79), increasing to 88% (kappa 0.85) after a post-classification clump and sieve procedure. Canopy height and percentage cover of oak explained 72% of variance in canopy density. Conclusions: The ability to discriminate and map temperate deciduous tree species in airborne multi-spectral imagery is increased using time-series data. An autumn image supplemented with an image from both the green-up and full-leaf phases was optimum. The derived tree species map provides a more powerful ecological tool for determining woodland structural/compositional relationships than field-based measures.
FBG-Based Respiration Rate Sensing With Arduino Interface

Psychophysiological measurement can be very crucial in critical conditions faced in aviation, military, hospitals, etc. Respiration rate is one of the primary parameters to determine the psychophysiological condition of a person. An effective respiration rate measurement system is developed using Fiber Bragg Grating (FBG), and a comparison of its response with an electronic sensor is carried out in this paper. An edge filter detection technique is employed to interrogate the optical sensing data. Arduino Uno is used for acquiring data from both electronic and optical sensors simultaneously. Both the electronic and optical sensors are fitted inside the same PVC mask, and their responses are compared. The experiment is carried out on five subjects, and every time it is found, that optical sensor is much more reliable and responsive. Optical sensor has better rise and decay constants for instantaneous temperature sensing making it a superior candidate to diagnose various respiration abnormalities. Respiration rate calculation is also carried out during coughing and headshaking. In the events of coughing, response of the optical sensor is much more prominent as compared to the electronic sensor. However, respiration rate calculation remains unaffected and reliable.
A Novel Primary-Side Regulation Control Scheme for CCM and DCM LLC LED Driver Based on “Magnetizing Current Cancellation Method”

In this article, the primary-side regulation (PSR) technique to achieve accurate output current in an LLC resonant converter has been studied. A novel PSR control scheme for an LLC light-emitting diode (LED) driver based on the “magnetizing current cancellation method” is proposed. The proposed “magnetizing current cancellation method” can effectively eliminate the effect of magnetizing current in the sampled primary resonant current under both the continuous conduction mode and the discontinuous conduction mode. Thus, the accurate output current can be estimated on the primary side of the LLC resonant converter. The magnetizing current cancellation method for the LLC LED driver with symmetric primary resonant current and asymmetric primary resonant current has been analyzed in detail. Some design considerations have also been presented. Then, an LLC PSR control circuit has been designed based on the theoretical analysis. Finally, a 48-to-78-V/1.3-A laboratory prototype for the LED driver has been built up, and experimental results show that good output current regulation has been obtained.
Effect of a Course on Educational Tools on Students’ Attitude and Digital Literacy Skills

This paper aimed at evaluating the effect of a course on educational tools on the participants’ digital literacy and collecting information on their attitude toward these tools and their pedagogical use as the result of attendance in this course. There were 15 participants in this study who attended the one-month course in one of the charity summer schools in Bam, Iran. The content of the course included topics like tagging, cyber threats, presentation tools, back up, creating video clips and so forth. Analysis of the results showed that there was a significant difference in digital literacy scores and attitudes of students between pre and posttests. A review of the participants’ projects and activities in Edublogs demonstrated that the participants were able to easily adapt technologies in creating different artifacts. The findings of this study provide insight to educators in their task of increasing digital literacy in not only society but also among students.
Doing more with less: similarity neural nets and metrics for small class imbalanced data sets

The focus of this article is deep learning on small, class imbalanced data sets in support of explosive hazard detection (EHD) and automatic target recognition (ATR). To this end, we explore artificial neural networks that are driven by similarity versus classification or regression. Similarity can be emphasized via network design, e.g., siamese networks, and/or underlying metric, e.g., contrastive or triple loss. The general goal of a similarity neural network (SNN) is discriminative training via focusing on similarity between tuples of like (and unlike) inputs. As such, SNNs have the potential to learn improved solutions on small data; aka do more with less". Herein, we explore different avenues and we show that SNNs are essentially neural feature extractors followed by k-nearest neighbor classification. Instead of experimenting on a government data set that cannot be shared, we instead focus on benchmark community data sets for sake of reproducible research. Preliminary findings are encouraging as they suggest that SNNs have great potential for tasks like EHD and ATR.
Generating Anthropomorphic Phantoms Using Fully Unsupervised Deformable Image Registration with Convolutional Neural Networks.

PURPOSE Computerized phantoms have been widely used in nuclear medicine imaging for imaging system optimization and validation. Although the existing computerized phantoms can model anatomical variations through organ and phantom scaling, they do not provide a way to fully reproduce the anatomical variations and details seen in humans. In this work, we present a novel registration-based method for creating highly anatomically detailed computerized phantoms. We experimentally show substantially improved image similarity of the generated phantom to a patient image. METHODS We propose a deep-learning-based unsupervised registration method to generate a highly anatomically detailed computerized phantom by warping an XCAT phantom to a patient CT scan. We implemented and evaluated the proposed method using the NURBS-based XCAT phantom and a publicly available low-dose CT dataset from TCIA. A rigorous tradeoff analysis between image similarity and deformation regularization was conducted to select the loss function and regularization term for the proposed method. A novel SSIM-based unsupervised objective function was proposed. Finally, ablation studies were conducted to evaluate the performance of the proposed method (using the optimal regularization and loss function) and the current state-of-the-art unsupervised registration methods. RESULTS The proposed method outperformed the state-of-the-art registration methods, such as SyN and VoxelMorph, by more than 8%, measured by the SSIM and less than 30%, by the MSE. The phantom generated by the proposed method was highly detailed and was almost identical in appearance to a patient image. CONCLUSIONS A deep-learning-based unsupervised registration method was developed to create anthropomorphic phantoms with anatomies labels that can be used as the basis for modeling organ properties. Experimental results demonstrate the effectiveness of the proposed method. The resulting anthropomorphic phantom is highly realistic. Combined with realistic simulations of the image formation process, the generated phantoms could serve in many applications of medical imaging research.
Potential of Pressure Sensor Based Mass Estimation Methods for Electric Buses

One approach to improve the economic efficiency of trolleybuses in the so-called BOB Project in the German town of Solingen is to use them as mobile energy storages in a smart grid. To achieve this, reliable information on available energy is essential, which in turn needs to be derived from a precise range calculator. As shown in this article, vehicle mass is a strong influencing factor, especially in urban traffic. Depending on passenger volume, the total mass and range of the bus varies by about 30 percent. The currently available mass on the bus fluctuates by more than 2 tons for constant payloads, and there is no proven solution for a more accurate mass estimation for buses in public passenger transportation. Therefore, this article presents a viable methodology to detect changes in payload, using high precision pressure sensors on the bus’s tires and air suspensions. These mass inducted pressure changes are extracted from the measurement data, using a filter to be later converted back into the corresponding masses. As the article will show, both approaches have their respective advantages and disadvantages, but have high potential and should therefore be investigated further.
Measles Virus Activates NF-κB and STAT Transcription Factors and Production of IFN-α/β and IL-6 in the Human Lung Epithelial Cell Line A549

Abstract Epithelial cells of the respiratory tract are the primary targets of measles virus (MV) infection. In this work we have studied the effect of MV infection on the activation of transcription factors nuclear factor (NF)-κB and signal transducer and activator of transcription (STAT) and the production of cytokines in the lung epithelial A549 cell line. NF-κB and STAT activation were induced by MV in A549 cells as analyzed by electrophoretic mobility shift assay. NF-κB activation was rapid and it was not inhibited by the protein synthesis inhibitor cycloheximide, suggesting that MV directly activates NF-κB. In contrast, Stat1, Stat3, and interferon-stimulated gene factor 3 (ISGF3) DNA binding was induced by MV infection with delayed kinetics compared to NF-κB activation. MV infection also resulted in an efficient interferon (IFN)-α/β and interleukin-6 production. Cycloheximide and neutralizing anti-IFN-α/β antibodies inhibited MV-induced activation of Stat1, Stat3, and ISGF3 DNA binding in A549 cells. In conclusion, the results suggest that MV infection activates transcription factors involved in the initiation of innate immune responses in epithelial cells by two different mechanisms: directly by leading to NF-κB activation and indirectly via IFN-α/β leading to STAT activation.