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Fig. 2 in Morphology of the female reproductive system and physiological age-grading of Megamelus scutellaris (Hemiptera: Delphacidae), a biological control agent of water hyacinth

Fig. 2. Photomicrographs of the female reproductive system of Megamelus scutellaris showing a) distal portion of the ovary showing the distal lateral oviduct (lop), common oviduct (co), bursa copulatrix (b), and spermatheca/spermathecal gland (spt and sptg, respectively), and b) close-up of ovariole morphology (b) showing the anterior lateral oviduct (loa), germarium (g), vitellarium (v), and terminal filament (tf).

Fig. 1 in Morphology of the female reproductive system and physiological age-grading of Megamelus scutellaris (Hemiptera: Delphacidae), a biological control agent of water hyacinth

Fig. 1. Photomicrograph of the female reproductive system of Megamelus scutellaris showing ovaries (ov), common oviduct (c), anterior and posterior portions of the lateral oviduct (loa and lop, respectively), and overall structure of a follicle including the germinal vesicle (gv) and oocyte with yolk (oy).

Fig. 3 in Morphology of the female reproductive system and physiological age-grading of Megamelus scutellaris (Hemiptera: Delphacidae), a biological control agent of water hyacinth

Fig. 3. Photomicrographs of the female reproductive system of Megamelus scutellaris showing a) close-up of the distal portion of an ovariole showing the anterior lateral oviduct (loa), follicular epithelium (fe), ovariole sheath (os), germinal vesicle (gv), oocyte with yolk (oy), and collar (c), and b) distal portion of an ovariole showing a newly ovulated egg (e) into the anterior lateral oviduct (loa), ovary (ov), ovariole (lov), and the collar (c).

Fig. 5. The 3 in Morphology of the female reproductive system and physiological age-grading of Megamelus scutellaris (Hemiptera: Delphacidae), a biological control agent of water hyacinth

Fig. 5. The 3 nulliparous stages of Megamelus scutellaris. a) N1—Note the lack of differentiation in the vitellarium (v) and large size of the germarium (g) in comparison to the vitellarium. b) N2—In this stage the ovarioles are fully differentiated, no fully mature follicles, and no follicular relics. c and d) N3—In this stage the ovarioles are fully differentiated, no follicular relics are present, and at least 2 follicles are mature and ready to be ovulated as indicated by darkening of the interior of the oocyte by yolk deposition.

opencc-by-4.0Jul 2018View details →

The CAPA Apple Quality Grading Multi-Spectral Image Database

The CAPA Apple Quality Grading Multi-Spectral Image Database consists of multispectral (450nm, 500nm, 750nm, and 800nm) images of health and defected apples of bi-color, manual segmentations of defected regions, and expert evaluations of the apples into 4 quality categories. The defect types consist of bruise, rot, flesh damage, frost damage, russet, etc.  The database can be used for academic or research purposes with the aim of computer vision based apple quality inspection. The CAPA Apple Quality Grading Multi-Spectral Image Database is a propriety of ULG (Gembloux Agro-Bio Tech) - Belgium, and cannot be used without the consent of the ULG (Gembloux Agro-Bio Tech), Belgium.  For consent, contact Devrim Unay, İzmir University of Economics, Turkey: unaydevrim@gmail.com OR Marie-France Destain, Gembloux Agro-Bio Tech, Belgium: mfdestain@ulg.ac.be In disseminating results using this database,  1. the author should indicate in the manuscript that it was acquired by ULG (Gembloux Agro-Bio Tech), Belgium. 2. cite the following article Kleynen, O., Leemans, V., & Destain, M.-F. (2005). Development of a multi-spectral vision system for the detection of defects on apples. Journal of Food Engineering, 69(1), 41-49. Relevant publications: Kleynen et al., 2003 O. Kleynen, V. Leemans and M.F. Destain, Selection of the most efficient wavelength bands for ‘Jonagold’ apple sorting. Postharv. Biol. Technol.,  30  (2003), pp. 221–232. Leemans and Destain, 2004 V. Leemans and M.F. Destain, A real-time grading method of apples based on features extracted from defects. J. Food Eng.,  61  (2004), pp. 83–89. Leemans et al., 2002 V. Leemans, H. Magein and M.F. Destain, On-line fruit grading according to their external quality using machine vision. Biosyst. Eng.,  83  (2002), pp. 397–404. Unay and Gosselin, 2006 D. Unay and B. Gosselin, Automatic defect detection of ‘Jonagold’ apples on multi-spectral images: A comparative study. Postharv. Biol. Technol.,  42  (2006), pp. 271–279. Unay and Gosselin, 2007 D. Unay and B. Gosselin, Stem and calyx recognition on ‘Jonagold’ apples by pattern recognition. J. Food Eng.,  78  (2007), pp. 597–605. Unay et al., 2011 Unay, D., Gosselin, B., Kleynen, O, Leemans, V., Destain, M.-F., Debeir, O, “Automatic Grading of Bi-Colored Apples by Multispectral Machine Vision”, Computers and Electronics in Agriculture, 75(1), 204-212, 2011.

opencc-by-4.0Dec 2008View details →

Text-fig. 1. D&E tree of Endress and Doyle (2009), from the combined morphological and molecular analysis of Doyle and Endress (2000), with modifications based on more recent data, showing the inferred evolution of the reticulum grading character (39). Boxes under names of taxa indicate their character state; shading of branches indicates their reconstructed state based on parsimony optimization with MacClade (Maddison and Maddison 2003). Nymph = Nymphaeales, Aust = Austrobaileyales, Chlor = Chloranthaceae, Piper = Piperales, Ca = Canellales, Magnol = Magnoliales. in Early Cretaceous Monocots: A Phylogenetic Evaluation

Text-fig. 1. D&E tree of Endress and Doyle (2009), from the combined morphological and molecular analysis of Doyle and Endress (2000), with modifications based on more recent data, showing the inferred evolution of the reticulum grading character (39). Boxes under names of taxa indicate their character state; shading of branches indicates their reconstructed state based on parsimony optimization with MacClade (Maddison and Maddison 2003). Nymph = Nymphaeales, Aust = Austrobaileyales, Chlor = Chloranthaceae, Piper = Piperales, Ca = Canellales, Magnol = Magnoliales.

opencc-by-4.0Oct 2024View details →

Raw data used in the manuscript titled "Metabolomic Analysis of Histological Composition Variability of High-Grade Serous Ovarian Cancer Using 1H HR MAS NMR Spectroscopy "

The folder contains raw data used in the manuscript titled "Metabolomic Analysis of Histological Composition Variability of High-Grade Serous Ovarian Cancer Using 1H HR MAS NMR Spectroscopy ".    Raw data measured on Bruker Avance III 400 MHz NMR spectrometer: - 1D 1H HR MAS NMR spectra (path: Patient_code – Sample_code/500/fid) - 2D 1H-1H J-resolved HR MAS NMR spectra (path: Patient_code – Sample_code/600/ser).   Metadata is included in Metadata.xlsx file. Each sample is described with the following parameters: - patient code (after anonymization), - sample code (the label l or r denotes the left or right ovary in patients from whom samples were obtained bilaterally), - sample weight, - clinic-pathological parameters (such as: age, BMI, menopausal status, diagnosis, FIGO stage), - percentage tissue content obtained from histopathological analysis after HR MAS NMR studies (cancer cells, epithelial compartment within benign tumors, necrosis, inflammation, fibrosis, calcification, normal ovary, vessels, fatty tissue).   Some samples were considered representative of particular tissue components: - cancer (HGSOC) compartment, - fibrotic stroma within malignant  (HGSOC) tumors, - fibrotic stroma within benign tumors, - normal ovary tissue (the samples collected from the control group), - normal ovary tissue (the samples collected from the cancer patients), - necrosis, - non-tumoral fibrous tissue / fibrous tumor capsule (obtained from the patients with benign non-neoplastic lesions) - corpus albicans The assignment of the samples to these categories is indicated in the column Tissue components.   The samples classified as outliers in PCA model 1 are indicated in the column Outliers. The samples included in multivariate models are indicted in the columns: PCA 2, PCA 3, PCA 4, PCA 5, PCA 5a, PCA 6, OPLS-DA 1, OPLS-DA 2, OPLS-DA 3, OPLS-DA 4, OPLS-DA 5, OPLS-DA 6 and OPLSR.

opencc-by-4.0Nov 2024View details →

Mechanical Simulation Analysis of skeleton gyroid structure (standard, double and graded)_Spoke11_WP4_Task4.1_MOST

These data provide a foundation for understanding how each skeletal configuration handles stress, with practical implications for applications requiring tailored energy absorption and strength properties in lattice structures.

opencc-by-4.0Nov 2024View details →

3D Printing Simulation Analysis of skeleton gyroid structure (standard, double and graded)_Spoke11_WP4_Task4.1_MOST

These findings provide a comprehensive understanding of the challenges and considerations in 3D printing complex lattice structures, emphasizing the importance of residual stress management, thermal stability, and print direction alignment for optimal mechanical performance.

opencc-by-4.0Jul 2021View details →

The effect of the graded bilayer design on the strain depth profiles and microstructure of CuW nano-multilayers

In this document we share: -the XRD in-plane scans acquired on Cu/W multilayers at different incidence angle, -the in-situ stress curvature data acquired during multilayer growth, -the in plane d-spacing derived at different incidence angle, used for the simulation of the strain gradient.

opencc-by-4.0Aug 2021View details →

Poster session grading

Grades given by teachers and peers in poster session organized in 4 consecutive years (2017-2020). The data is anonymized, after origins were infered from the names with Namsor and ethnea.

opencc-by-4.0Dec 2020View details →

Text-fig. 6. Scanning electron micrographs of multicarpellate and apocarpous floral structures from the Early Cretaceous Puddledock locality, Virginia, USA (a, b: PP43701, Puddledock sample 001; c: PP43000x, Puddledock sample 073). a) Anacostia? sp., strongly compressed, elongated receptacle with spirally arranged carpels (red dots; not all shown); note larger size compared to the other floral structures; b) Numerous Anacostia type pollen grains in proximal view from the base of floral structure in (a); note graded reticulum over the proximal pole of the pollen grains; c) Elongated receptacle with numerous carpels in a spiral arrangement, possibly representing an earlier developmental stage of Anacostia? sp. Scale bars = 1 mm (a, c), 10 µm (b). in Multiparted, Apocarpous Flowers From The Early Cretaceous Of Eastern North America And Portugal

Text-fig. 6. Scanning electron micrographs of multicarpellate and apocarpous floral structures from the Early Cretaceous Puddledock locality, Virginia, USA (a, b: PP43701, Puddledock sample 001; c: PP43000x, Puddledock sample 073). a) Anacostia? sp., strongly compressed, elongated receptacle with spirally arranged carpels (red dots; not all shown); note larger size compared to the other floral structures; b) Numerous Anacostia type pollen grains in proximal view from the base of floral structure in (a); note graded reticulum over the proximal pole of the pollen grains; c) Elongated receptacle with numerous carpels in a spiral arrangement, possibly representing an earlier developmental stage of Anacostia? sp. Scale bars = 1 mm (a, c), 10 µm (b).

opencc-by-4.0Nov 2019View details →

Text-fig. 44. Scanning electron microscope (SEM) images of monocolpate pollen of Juhaszia portugallica gen. et sp. nov. from a fragment of a pollen sac (a–e) and stamen fragment and pollen of Dictyozonia pusilla gen. et sp. nov. (f–k); Torres Vedras locality, Portugal. a) Holotype; fragment of pollen sac that yielded the pollen in (b–e); b) Proximal surface of pollen grain showing reticulate sculpture in the equatorial regions grading into more a continuous foveolate tectum at the proximal pole; c) Reticulum on the proximal surface showing smooth muri delimiting large and small luminae. Muri supported by numerous short columellae that are only loosely attached to the smooth surface of the foot layer; d) Distal surface of pollen grain showing the long colpus and reticulate sculpture with a distinctive pattern of large and small luminae; e) Pollen grain from which the reticulum has become in The Early Cretaceous Mesofossil Flora Of Torres Vedras (Ne Of Forte Da Forca), Portugal: A Palaeofloristic Analysis Of An Early Angiosperm Community

Text-fig. 44. Scanning electron microscope (SEM) images of monocolpate pollen of Juhaszia portugallica gen. et sp. nov. from a fragment of a pollen sac (a–e) and stamen fragment and pollen of Dictyozonia pusilla gen. et sp. nov. (f–k); Torres Vedras locality, Portugal. a) Holotype; fragment of pollen sac that yielded the pollen in (b–e); b) Proximal surface of pollen grain showing reticulate sculpture in the equatorial regions grading into more a continuous foveolate tectum at the proximal pole; c) Reticulum on the proximal surface showing smooth muri delimiting large and small luminae. Muri supported by numerous short columellae that are only loosely attached to the smooth surface of the foot layer; d) Distal surface of pollen grain showing the long colpus and reticulate sculpture with a distinctive pattern of large and small luminae; e) Pollen grain from which the reticulum has become

Literature on effectiveness of digital learning environments for math in grades 4-10

This table contains metadata on 139 papers which were included in a literature research regarding the effectiveness of digital learning environment for math in grades 4-10. The literature research had three branches: 1) meta-studies on digital learning environments for math in grades 4-10 (13), 2) effectiveness studies regarding popular digital math learning environments (87), and 3) other effectiveness studies for digital learning environments for math in grades 4-10 (identified via a SCOPUS search, 39). The results of each paper are sorted according to their relevance for four core system properties of digital learning environments, namely A) domain modelling/completeness of curriculum coverage, B) user interface/intelligent interaction tools, C) inner loop/micro-adaptivity, that is, strategies to support students in completing single learning tasks, and D) outer loop/macro-adaptivity, that is, strategies to support students in selecting the next learning task. Additionally, we considered E) the integration of the system with in-class teaching. Conflict of interest statement: The study was financed by bettermarks. bettermarks did not influence the text of the publication or the content of this data set. DE: Diese Tabelle enthält Metadaten für 139 wissenschaftliche Artikel, die im Rahmen der Literaturstude "Was wirkt? Eine Literaturstudie zur Wirksamkeit von Systemeigenschaften in Mathematik-Lernumgebungen" (DELFI, 2023) berücksichtigt wurden. Die Studie befasst sich mit der Effektivität von digitalen Mathematik-Lernumgebungen für die Mittelstufe. Die Suche gliederte sich in drei Zweige, nämlich 1) Metastudien über digitale Mathematik-Lernumgebungen in der Mittelstufe (13), 2) Lernwirksamkeitsstudien zu einzelnen, bekannten Lernumgebungen (87), 3) Weitere, einzelne Lernwirksamkeitsstudien zu digitalen Mathematik-Lernumgebungen in der Mittelstufe (über eine SCOPUS-Recherche, 39). Die Ergebnisse der Artikel wurden gegliedert nach vier zentralen Systemeigenschaften digitaler Mathematik-Lernumgebungen, nämlich A) Vollständigkeit der Lerninhalte (bzw. Domänen-Modellierung), B) Intelligente Interaktionswerkzeuge (bzw. user interface), C) Mikro-Adaptivität (bzw. die Unterstützung der Lernenden bei der Bearbeitung einzelner Lernaufgaben) und D) Makro-Adaptivität (bzw. die Unterstützung der Lernenden bei der Auswahl der nächsten Lernaufgabe). Zusätzlich wurde E) die Einbindung im Klassenverbund mit einbezogen. Interessenkonflikt-Angabe: Diese Studie wurde von bettermarks finanziert. Bettermarks hat den Text der Publikation oder den Inhalt dieser Tabelle nicht beeinflusst.

FIG. 54 in Cranial And Postcranial Morphology Of The Insectivoran-Grade Mammals Hsiangolestes And Naranius (Mammalia, Eutheria) With Analyses Of Their Phylogenetic Relationships

FIG. 54. Drawing of anterior part of skull of?Didymoconidae: A. dorsal, B. ventral, and C. left lateral views (based on IVPP V7441).

FIG. 51 in Cranial And Postcranial Morphology Of The Insectivoran-Grade Mammals Hsiangolestes And Naranius (Mammalia, Eutheria) With Analyses Of Their Phylogenetic Relationships

FIG. 51. Drawing of temporal region of skull of Naranius hengdongensis, sp. n. (based on IVPP V 5353).

FIG. 47 in Cranial And Postcranial Morphology Of The Insectivoran-Grade Mammals Hsiangolestes And Naranius (Mammalia, Eutheria) With Analyses Of Their Phylogenetic Relationships

FIG. 47. Skull and lower jaw of Naranius hengdongensis, sp. n., IVPP V5352: A. right lateral, B. left lateral, C. dorsal, and D. right dorsal-lateral views.

FIG. 44 in Cranial And Postcranial Morphology Of The Insectivoran-Grade Mammals Hsiangolestes And Naranius (Mammalia, Eutheria) With Analyses Of Their Phylogenetic Relationships

FIG. 44. Anterior part of skull of Naranius hengdongensis, sp. n., IVPP V7440: A. right lateral, B. left lateral, and C. dorsal views.

FIG. 38. Hsiangolestes youngi, IVPP V5797 in Cranial And Postcranial Morphology Of The Insectivoran-Grade Mammals Hsiangolestes And Naranius (Mammalia, Eutheria) With Analyses Of Their Phylogenetic Relationships

FIG. 38. Hsiangolestes youngi, IVPP V5797, skull and postcranial bones: A. ventral and B. dorsal views of skull, showing preservation before preparation.

FIG. 53 in Cranial And Postcranial Morphology Of The Insectivoran-Grade Mammals Hsiangolestes And Naranius (Mammalia, Eutheria) With Analyses Of Their Phylogenetic Relationships

FIG. 53. Anterior part of skull of?Didymoconidae, IVPP V7441: A. ventral, B. dorsal, and C. left lateral views.