Morphometric Descriptors Research Articles

Simple methodology to score micropattern quality and effectiveness.

Micropatterns (MPs) are widely used as a powerful tool to control cell morphology and phenotype. However, methods for determining the effectiveness of how well cells are controlled by the shape of MPs have been inconsistently used and studies rarely report on this topic, indicating lack of standardization. We introduce an evaluation score that quantitatively assesses the MP fabrication quality and effectiveness, which can be broadly used in conjunction with all currently available MP design types. This score uses four simple and quick steps: (i) scoring MP and (ii) background fabrication quality, (iii) defining the type(s) of MP of interest, and (iv) assigning so-called efficiency descriptors describing cell behavior. These steps are based on visual inspection and quick categorization of various aspects of MP fabrication quality and cell behaviour, presented in illustrations and microscopy image examples intended to serve as a reference "atlas". To illustrate the advantage of using this score, we determined differences in cell morphology and F-actin intensity between scored vs. non-scored cells. These measurements, which could be different in other studies, were chosen because both are understood as markers of cell phenotype and function. We combined intensity-calibrated immunofluorescence microscopy and image-based single cell protein analysis. Importantly, significant differences in cell morphology and cytoskeletal protein content between scored vs. non-scored cells were noted: the unconditional inclusion of all experimental read-outs (i.e., all MP data regardless of MP quality and effectiveness) into the final results significantly misjudged the experimental readouts vs. only including experimental read-outs of quality-controlled and effective MPs, identified by scoring. Specifically, non-scoring underestimated the F-actin intensity per cell and quantitative cellular morphometric descriptors circularity and solidity and overestimated aspect ratio. Scoring improved the precision of cellular readouts, advocating the use of a MP quality and efficiency score as a quantitative decision-supporting tool in deciding whether or not particular MPs should be used for experiments, saving time and money. This simple scoring methodology can be used for improving MP fabrication, comparing results across studies, benefiting basic science studies and potential future clinical use of MPs by introducing standardization.

The Effect of Irrigation on the Vineyard Canopy and Individual Leaf Morphology Evaluated with Proximal Sensing, Colorimetry, and Traditional Morphometry

The high number of grapevine (Vitis vinifera L.) cultivars grown world-wide are described and identified according to detailed morphological and morphometric descriptor lists. The grapevine leaf is of utmost importance in characterization, despite its traits being very sensitive to environmental factors. In this study, the effect of irrigation/drought stress on the individual leaf morphology and morphometry of the ‘Hárslevelű’ grapevine (Vitis vinifera L.) cultivar was examined. To verify the effect of the applied irrigation methods (drip and subsoil irrigation) on the plant’s water status, water potential measurements were carried out during the 2022 season. The effect of the applied treatments on the vegetative growth was evaluated according to point quadrat and a multichannel LiDAR analysis in order to describe the width of the canopy area, row volume, and area coverage index. The individual leaf morphology was assessed via traditional morphometry and colorimetry. Our results showed that rainfed plants had a significantly lower stem ψ compared to the drip- and subsoil-irrigated plants at all examined dates. The point quadrat results indicate that the leaf layer number was significantly (p < 0.05) influenced by the position, while the treatment showed no effect on the leaf layer number. The leaf colorimetry showed a difference among the samples, as significant alterations were found in 28 out of the 32 examined color properties. Within the traditional morphometric analysis, 54 traits were evaluated, and 14 of the traits were significantly altered due to the different water management systems.

Machine learning aided single cell image analysis improves understanding of morphometric heterogeneity of human mesenchymal stem cells

The multipotent stem cells of our body have been largely harnessed in biotherapeutics. However, as they are derived from multiple anatomical sources, from different tissues, human mesenchymal stem cells (hMSCs) are a heterogeneous population showing ambiguity in their in vitro behavior. Intra-clonal population heterogeneity has also been identified and pre-clinical mechanistic studies suggest that these cumulatively depreciate the therapeutic effects of hMSC transplantation. Although various biomarkers identify these specific stem cell populations, recent artificial intelligence-based methods have capitalized on the cellular morphologies of hMSCs, opening a new approach to understand their attributes. A robust and rapid platform is required to accommodate and eliminate the heterogeneity observed in the cell population, to standardize the quality of hMSC therapeutics globally.Here, we report our primary findings of morphological heterogeneity observed within and across two sources of hMSCs namely, stem cells from human exfoliated deciduous teeth (SHEDs) and human Wharton jelly mesenchymal stem cells (hWJ MSCs), using real-time single-cell images generated on immunophenotyping by imaging flow cytometry (IFC). We used the ImageJ software for identification and comparison between the two types of hMSCs using statistically significant morphometric descriptors that are biologically relevant. To expand on these insights, we have further applied deep learning methods and successfully report the development of a Convolutional Neural Network-based image classifier. In our research, we introduced a machine learning methodology to streamline the entire procedure, utilizing convolutional neural networks and transfer learning for binary classification, achieving an accuracy rate of 97.54%. We have also critically discussed the challenges, comparisons between solutions and future directions of machine learning in hMSC classification in biotherapeutics.

Microstructural Changes in Vanilla planifolia Beans after Using High-Hydrostatic-Pressure Treatment in the Curing Process.

During vanilla bean curing, the cell arrangement derived from the killing technique applied to start bean ripening is essential to obtain the characteristic aroma and flavor of vanilla. Hence, killing is an important step to release the enzymes and compounds required for vanillin production. In this work, high hydrostatic pressure (HHP) at 100-400 MPa for 5 min, using water at 7 °C as the pressure-transmitting medium, was applied as the killing method, and its effect on the microstructural changes in vanilla beans during different curing cycles (C0-C20) was evaluated and compared with that observed after scalding by using water at 100 °C for 8 s. Microstructural changes in the cross-sectioned beans were analyzed using a stereomicroscope (SM), confocal laser scanning microscopy (CLSM), and environmental scanning electron microscopy (ESEM). The vanilla beans were cross-sectioned and three main sectors were analyzed: the total, annular, and core. The morphometric descriptors, namely, area, Feret's diameter, and circularity, were quantified via digital image analysis (DIA), from which a shrinkage ratio was calculated. The results show that the total area in the beans presented a maximum decrease in the C16 of curing. The core area was most affected by the HHP treatment, mainly at 400 MPa, rather than scalding. CSLM observations revealed the autofluorescence of the compounds inside the beans. In conclusion, the use of microscopy techniques and DIA allowed us to determine the microstructural changes in the HHP-treated pods, which were found to be more numerous than those found in the scalded beans.

Characterization and differentiation of forest species by seed image analysis: a new methodological approach

Biometric seed analysis can be used to characterize and differentiate forest species. However, forest species are generally studied using manual methods such as measurements with a digital caliper, which provides a limited amount of information on plant morphological characteristics, whereas agronomic species are analyzed using expensive and often inaccessible equipment. Thus, the objective of the present study was to demonstrate that seed image analysis and processing tools can help characterize and differentiate Brazilian forest species. For this purpose, the seeds of 155 forest species belonging to 42 families were photographed and analyzed to extract data on their morphometric descriptors using a new methodological approach. A total of 18 characteristics were assessed, namely eight dimensions, four shape characteristics, and six color characteristics. A set of approximately 1.827 million data was extracted from 101,521 seed images. Digital image processing efficiently characterized the studied seeds and the obtained characteristics allowed us to differentiate between species, including those belonging to the same botanical family and genus. Therefore, seed image analysis using the proposed methodology can be used to characterize, differentiate, and automatedly identify forest species in Brazil.

Morphometric properties, scaling laws and hydrologic response of the Greater Paris combined sewer system

AbstractMorphometric properties of channel networks are useful tools to classify catchments and calculate their hydrological response. Scaling laws have been established for Optimal Channel Networks (OCNs), which are defined based on a generative geomorphological mechanism of minimizing the total energy dissipation. However, sewer networks obey engineering efficiency rules and are conceived based on local optimizations, both in time and space, for minimal costs. Not all the scaling laws have been verified for artificial sewer networks found in urban areas. This raises questions regarding the applicability of OCN scaling laws to sewer networks and their potential impact on the shape of the Geomorphological Instantaneous Unit Hydrograph (GIUH). Hence, this work aims to study the morphometric properties of the Greater Paris combined sewer system through a case study on twelve nested subcatchments. A two‐step methodology is used. First, the morphometric properties are analysed using the reference Horton‐Strahler, Rodríguez‐Iturbe and Moussa‐Bocquillon scaling laws. The results show that Horton‐Strahler's laws of bifurcation are verified while the length and area laws are not always verified. Rodriguez‐Iturbe and Moussa‐Bocquillon laws are verified with slightly different values of the descriptors in comparison to OCNs. Second, these morphometric properties are used to calculate four GIUHs: the reference Width Function (GWF), the Nash unit hydrograph (GN) using Horton‐Strahler ratios, the Nash Unit Hydrograph equivalent (GNe) using Moussa‐Bocquillon descriptors, and the Hayami function (GH) solution of the diffusive wave equation. We identified four catchments for which the scaling laws are verified and therefore all GIUHs are similar while for four other catchments the scaling laws are not verified and strongly impact the GIUHs. These morphometric descriptors and the GIUHs can be considered as ‘hydrological signatures’ of Combined Sewer Systems (CSSs) and are useful for the comparison and classification of hydrological responses.

Automated extraction of seed morphological traits from images

Abstract The description of biological objects, such as seeds, mainly relies on manual measurements of few characteristics, and on visual classification of structures, both of which can be subjective, error prone and time‐consuming. Image analysis tools offer means to address these shortcomings, but we currently lack a method capable of automatically handling seeds from different taxa with varying morphological attributes and obtaining interpretable results. Here, we provide a simple image acquisition and processing protocol and introduce Traitor, an open‐source software available as a command‐line interface (CLI), which automates the extraction of seed morphological traits from images. The workflow for trait extraction consists of scanning seeds against a high‐contrast background, correcting image colours, and analysing images with the software. Traitor is capable of processing hundreds of images of varied taxa simultaneously with just three commands, and without a need for training, manual fine‐tuning or thresholding. The software automatically detects each object in the image and extracts size measurements, traditional morphometric descriptors widely used by scientists and practitioners, standardised shape coordinates, and colorimetric measurements. The method was tested on a dataset comprising of 91,667 images of seeds from 1228 taxa. Traitor's extracted average length and width values closely matched the average manual measurements obtained from the same collection (concordance correlation coefficient of 0.98). Further, we used a large image dataset to demonstrate how Traitor's output can be used to obtain representative seed colours for taxa, determine the phylogenetic signal of seed colour, and build objective classification categories for shape with high levels of visual interpretability. Our approach increases productivity and allows for large‐scale analyses that would otherwise be unfeasible. Traitor enables the acquisition of data that are readily comparable across different taxa, opening new avenues to explore functional relevance of morphological traits and to advance on new tools for seed identification.

Intra-specific correlations between fatty acids and morphological traits are consistent across fish species

We explored intraspecific relationships between biochemical and morphometric traits among sixteen fish species from the Canadian waters of the Laurentian Great Lakes. We focused on hypotheses linking two morphometric descriptors (fish length and condition factor, CF, the latter derived from species-specific allometric-growth equations) to lipid content and polyunsaturated fatty acid (PUFA) composition of dorsal muscle tissue. Each population from each of the lakes was assumed to display different relationships. All correlations were better represented by linear than non-linear relationships. Interspecific and among lakes differences accounted for most of the registered variability of fatty acid (FA) composition. Once these two covariates were parsed out, there was a discernible intraspecific coupling between fish length, CF, and fish biochemical traits, including positive correlations with muscle lipid and PUFA composition. The sign of the correlations was consistent among different populations, aligned with the theoretical expectations, and with interspecific trait correlations. However, for some species, correlations could be positive in one lake but negative in another, suggesting that local environmental variations could affect biochemical rates. We also found three trends associated with the rate at which different fatty acids accumulate in fish muscle tissue that are potentially related to food availability. These relationships between CF and FA composition provide a promising starting point to establish efficient, cost-effective, field-based estimates of essential FA descriptors. In this vein, we present a user-friendly application for the estimation of lipid content and PUFA composition, based solely on weight and length, that any angler and/or citizen-science participant can easily obtain.

Blondes do it better? A comparative study on the morphometry and life-history traits of commercially important skates blonde ray Raja brachyura, thornback ray Raja clavata, and spotted ray Raja montagui, with management implications

Due to data limitation and challenges with species-specific reporting, the management of European skate fisheries currently lacks measures tailored to individual species. Given these caveats, detailed information about skate stocks at the species level is warranted. The morphometry and life-history parameters were determined for samples of 170 individuals (58 Raja brachyura, 92 R. clavata, 20 R. montagui) collected by observers in commercial fisheries, and two bottom trawl surveys (December 2020 – August 2021) in the Southern North Sea and Eastern English Channel. A combination of three morphometric measurements were considered and proven successful (3.846% misclassification, N = 78) in species discrimination for easily confusable species R. brachyura and R. montagui. Through the application of these morphometric descriptors in electronic catch monitoring via Artificial Intelligence (AI), the misidentification of easily confusable species may be reduced in future catch reporting from surveys, fisheries-dependent data, and market sampling. Additionally, the morphometric differences between species may have implications for species’ catchability, and gear modification to avoid bycatch of skates under the European Landing Obligation (LO). The length-weight relationships indicated a faster rate of increase in body mass per unit of size for R. montagui. Life-history trait parameter estimates were obtained for R. clavata and R. brachyura. Age was determined through digital processing of images from visually enhanced whole vertebral centra (0.01% crystal violet staining). Age reading precision was low (CV > 45%, PA < 60%). The von Bertalanffy and logistic growth models provided more accurate fits for the length-at-age data than the Gompertz model. Macroscopic maturity assessment revealed that male R. montagui matured at the smallest size (Lm = 57.5 cm), while female R. brachyura matured at the largest size (Lm = 87.6 cm). Maturity ogives were fitted for males (L50 = 65.4 cm) and females (L50 = 84.1) of R. clavata and females of R. brachyura (L50 = 82.7 cm), with statistically significant intersexual differences for R. clavata. The Legal Minimum Landing Size (LMLS) measures of smaller sizes may not offer adequate protection (to immature specimens) of the skate species in the present study, that mature at larger sizes. The life-history trait parameters for growth and maturity are discussed in relation to published results of earlier studies, and no major changes in the life-history parameter traits were observed in recent years. The interspecific differences in the morphometries and life-history traits of R. brachyura, R. clavata, and R. montagui highlight the need for species-specific data collection and management considerations of skate stocks in the Northeast Atlantic Region at the local and EU level.

Sexual dimorphism of ducks (Cairina moschata, Linnaeus 1758) reared in the southern forest of Côte d’Ivoire

Sexual dimorphism was studied on 213 ducks including 92 males and 121 females of the species Cairina moschata in the southern forest of Côte d'Ivoire. Measurements were made using a tape measure and weighing with an electronic scale. A step-wise discriminant analysis made it possible to examine 21 morphometric descriptors. All linear measures except beak and head with were significantly higher in males than in females. 18 of these 21 parameters are statistically significant with the Mann-Whitney U test. Of these 18 significant descriptors, nine are strongly correlated positively for the first two and the fourth axis while it is negatively for the third factorial axis. The projection of the individuals in the plane of the principal component analysis shows a separation of the batches so that along axis 1 the male individuals gather towards the negative coordinates and the female individuals towards the positive coordinates. The values ​​recorded with the discriminant factor analysis confirm to 92.49% the membership of the specimens to the different defined groups. This analysis proposes a reclassification of two females in the group of males and of 14 males among the females.

Distinct Stocks of the Redtail Scad Decapterus kurroides Bleeker, 1855 (Perciformes: Carangidae) from the Northern Sulu and Southern Sibuyan Seas, Philippines Revealed from Otolith Morphometry and Shape Analysis

A recent study was performed to assess the morphometric variation of otoliths of the Decapterus kurroides collected in the northern Sulu and southern Sibuyan seas in delineating fish stocks. Seven of the otolith morphometric descriptors (otolith length, OL; otolith height, OH; otolith weight OW; otolith area, OA; otolith perimeter, OP; ellipticity, EL; and aspect ratio, AR) demonstrated a significant positive correlation with fish length and six (rectangularity, RE; squareness, SQ; roundness, RO; circularity, CI; compactness, CO; and form factor, FF) demonstrated a significant negative correlation. In terms of intraspecific comparisons, almost all the otolith morphometric descriptors were significantly different between the two sites (except RE and OH). Further, principal component (PC) analysis showed that direct otolith morphometric descriptors such as OL, OH, OW, OA, and OP explained 61.71% of the differences (PC1). In contrast, derived otolith descriptors such as EL, AR, and CO explained 22.00% of the variations (PC2) for a total of 83.71% explained variations with the eight otolith morphometric descriptors. Statistics reveal that D. kurroides from the Sibuyan Sea have significantly larger, heavier, and more elliptical otoliths than those from the Sulu Sea. Results suggested that the D. kurroides from Sulu and Sibuyan seas are two different phenotypic stocks. Further studies such as otolith microchemistry, genetics, other life history-based studies, and present exploitation levels should be carried out to supplement the results of this study to fully establish the D. kurroides stock structures within Philippine waters.

Urban form and COVID-19 cases and deaths in Greater London: An urban morphometric approach.

The COVID-19 pandemic generated a considerable debate in relation to urban density. This is an old debate, originated in mid 19th century’s England with the emergence of public health and urban planning disciplines. While popularly linked, evidence suggests that such relationship cannot be generally assumed. Furthermore, urban density has been investigated in a spatially coarse manner (predominantly at city level) and never contextualised with other descriptors of urban form. In this work, we explore COVID-19 and urban form in Greater London, relating a comprehensive set of morphometric descriptors (including built-up density) to COVID-19 deaths and cases, while controlling for socioeconomic, ethnicity, age and co-morbidity. We describe urban form at individual building level and then aggregate information for official neighbourhoods, allowing for a detailed intra-urban representation. Results show that: (i) control variables significantly explain more variance of both COVID-19 cases and deaths than the morphometric descriptors; (ii) of what the latter can explain, built-up density is indeed the most associated, though inversely. The typical London neighbourhood with high levels of COVID-19 infections and deaths resembles a suburb, featuring a low-density urban fabric dotted by larger free-standing buildings and framed by a poorly inter-connected street network.

Block copolymer nanopatterns affect cell spreading: Stem versus cancer bone cells

Bone healing after a tumor removal can be promoted by biomaterials that enhance the bone regeneration and prevent the tumor relapse. Herein, we obtained several nanopatterns by self-assembly of polystyrene-block-poly-(2-vinylpyridine) (PS-b-P2VP) with different molecular weights and investigated the adhesion and morphology of human bone marrow mesenchymal stem cells (BMMSC) and osteosarcoma cell line (SaOS-2) on these patterns aiming to identify topography and chemistry that promote bone healing. We analyzed > 2000 cells per experimental condition using imaging software and different morphometric descriptors, namely area, perimeter, aspect ratio, circularity, surface/area, and fractal dimension of cellular contour (FDC). The obtained data were used as inputs for principal component analysis, which showed distinct response of BMMSC and SaOS-2 to the surface topography and chemistry. Among the studied substrates, micellar nanopatterns assembled from the copolymer with high molecular weight promote the adhesion and spreading of BMMSC and have an opposite effect on SaOS-2. This nanopattern is thus beneficial for bone regeneration after injury or pathology, e.g. bone fracture or tumor removal.

Model-based plant phenomics on morphological traits using morphometric descriptors.

The morphological traits of plants contribute to many important functional features such as radiation interception, lodging tolerance, gas exchange efficiency, spatial competition between individuals and/or species, and disease resistance. Although the importance of plant phenotyping techniques is increasing with advances in molecular breeding strategies, there are barriers to its advancement, including the gap between measured data and phenotypic values, low quantitativity, and low throughput caused by the lack of models for representing morphological traits. In this review, we introduce morphological descriptors that can be used for phenotyping plant morphological traits. Geometric morphometric approaches pave the way to a general-purpose method applicable to single units. Hierarchical structures composed of an indefinite number of multiple elements, which is often observed in plants, can be quantified in terms of their multi-scale topological characteristics using topological data analysis. Theoretical morphological models capture specific anatomical structures, if recognized. These morphological descriptors provide us with the advantages of model-based plant phenotyping, including robust quantification of limited datasets. Moreover, we discuss the future possibilities that a system of model-based measurement and model refinement would solve the lack of morphological models and the difficulties in scaling out the phenotyping processes.

Morphoagronomic and molecular characterization of Euterpe oleracea accessions from eastern Brazilian Amazon

Açaí (Euterpe oleracea Mart.) - a common tropical palm has high social, economic, and environmental importance in the Amazon region. In the light of increasing exploration to obtain the fruit and heart of this palms, comprehensive studies are warranted for conservation and genetic improvement. Here, we characterized açaí accessions using phenological, morphological, and agronomic descriptors and random amplified polymorphic DNA (RAPD) molecular markers for joint selection of accessions with greater productivity. Hundred accessions were analyzed using 18 morphoagronomic descriptors and 13 RAPD markers. The spathe and inflorescence emission phases during flowering and fruiting showed seasonality. Based on the coefficient of variation and mean squared error, the accessions exhibited high variability in the tested morphoagronomic descriptors and were distributed into seven groups. Fruit, seed, and pulp weights were important descriptors for the distinction of accessions and identification of those with greater productivity. The accessions presented &gt;85% similarity, and 85 accessions, distributed in nine subgroups, could not be differentiated using RAPD markers. There was no correlation between grouping based on morphometric descriptors and RAPD markers. Panicle weight was 3.9-9.0 kg in 15 accessions and 100-fruit pulp weight was 35-50 g in six accessions. Therefore, accessions with high productivity could be selected.

Guidelines for a Morphometric Analysis of Prokaryotic and Eukaryotic Cells by Scanning Electron Microscopy.

The invention of a scanning electron microscopy (SEM) pushed the imaging methods and allowed for the observation of cell details with a high resolution. Currently, SEM appears as an extremely useful tool to analyse the morphology of biological samples. The aim of this paper is to provide a set of guidelines for using SEM to analyse morphology of prokaryotic and eukaryotic cells, taking as model cases Escherichia coli bacteria and B-35 rat neuroblastoma cells. Herein, we discuss the necessity of a careful sample preparation and provide an optimised protocol that allows to observe the details of cell ultrastructure (≥ 50 nm) with a minimum processing effort. Highlighting the versatility of morphometric descriptors, we present the most informative parameters and couple them with molecular processes. In this way, we indicate the wide range of information that can be collected through SEM imaging of biological materials that makes SEM a convenient screening method to detect cell pathology.

A morphometric approach to track opium poppy domestication

Opium poppy (Papaver somniferum L. subsp. somniferum) was likely domesticated in the Western Mediterranean, where its putative wild ancestor is indigenous, and then spread to central and northern Europe. While opium poppy seeds are regularly identified in archaeobotanical studies, the absence of morphological criteria to distinguish the seeds of wild and domestic forms prevents the documentation of their respective historical and geographical occurrences and of the process of opium domestication as a whole. To fill this gap and better understand the status of this crop in the Neolithic, we combined seed outline analyses, namely elliptic Fourier transforms, with other morphometric descriptors to describe and identify Papaver setigerum, Papaver somniferum and other Papaver taxa. The combination of all measured parameters gives the most precise predictions for the identification of all seven taxa. We finally provide a case study on a Neolithic assemblage from a pile-dwelling site in Switzerland (Zurich-Parkhaus Opéra, ca. 3170 BC). Our results indicate the presence of mixed populations of domestic and wild seeds belonging to the P. somniferum group, suggesting that the plant was already in the process of domestication at the end of 4th millennium BC. Altogether, these results pave the way to understand the geography and history of the poppy domestication and its spread into Europe.

Biphasic Calcium Phosphate Biomaterials: Stem Cell-Derived Osteoinduction or In Vivo Osteoconduction? Novel Insights in Maxillary Sinus Augmentation by Advanced Imaging.

Maxillary sinus augmentation is often necessary prior to implantology procedure, in particular in cases of atrophic posterior maxilla. In this context, bone substitute biomaterials made of biphasic calcium phosphates, produced by three-dimensional additive manufacturing were shown to be highly biocompatible with an efficient osteoconductivity, especially when combined with cell-based tissue engineering. Thus, in the present research, osteoinduction and osteoconduction properties of biphasic calcium-phosphate constructs made by direct rapid prototyping and engineered with ovine-derived amniotic epithelial cells or amniotic fluid cells were evaluated. More in details, this preclinical study was performed using adult sheep targeted to receive scaffold alone (CTR), oAFSMC, or oAEC engineered constructs. The grafted sinuses were explanted at 90 days and a cross-linked experimental approach based on Synchrotron Radiation microCT and histology analysis was performed on the complete set of samples. The study, performed taking into account the distance from native surrounding bone, demonstrated that no significant differences occurred in bone regeneration between oAEC-, oAFMSC-cultured, and Ctr samples and that there was a predominant action of the osteoconduction versus the stem cells osteo-induction. Indeed, it was proven that the newly formed bone amount and distribution decreased from the side of contact scaffold/native bone toward the bulk of the scaffold itself, with almost constant values of morphometric descriptors in volumes more than 1 mm from the border.

Urban morphology parameterization for assessing the effects of housing blocks layouts on air temperature in the Euro-Mediterranean context

Urban environment characteristics directly affect local microclimate and, in turn, changes in local microclimate affect the urban environmental conditions, often resulting in negative consequences on human health and comfort. The study of these interactions is largely supported by scientific literature, but there is a general lack concerning the urban forms influence on outdoor thermal comfort in Euro-Mediterranean cities.In this study, the topic is addressed by investigating performances and characteristics of typical Euro-Mediterranean housing blocks to highlight their effects on local microclimate. Its relevance is related to the need for supporting the assessment of microclimate conditions and outdoor thermal comfort, providing an effective tool that can steer future adaptation policies and design processes.In this perspective, a parametric study is performed by investigating different housing blocks through some morphometric descriptors (density, land-use, canyon geometry descriptors), commonly used in urban and environmental planning. Seven typologies (detached, attached, linear, U-shaped, block with courtyard, block with multiple courtyards, tower) are modelled with the Computational Fluid Dynamic (CFD) ENVI-met v4.4 model, considering three configurations of surface cover and wind direction. For each combination, air temperature at pedestrian level (TA,1.6m) and descriptors are compared to highlight the microclimate performances of urban forms.The results show a close relationship between density, geometry and TA,1.6m distribution, highlighting the perimeter type (which includes three block types: U-shaped, block with courtyard, block with multiple courtyards) as the optimal configuration. Moreover, in some cases, a reduced amount of vegetation can lead to a significant reduction in air temperature, with economic benefits in terms of cost reductions for implementation, management and maintenance.

English

The development of drainage basins to raise aquifer potentiality is considering the major target in Qena-Safaga-Bir Queh (central Eastern Desert). It is attributed to drought, scarce groundwater resource, expansion of agriculture, growth population, infrastructures, and civilization. Geological, hydrogeological, and morphometric information is used to prepare the drainage development plan and strategy. The morphometric parameters were used to evaluate the hydraulic conductivity of the surficial lithology. The aquifer recharge rate was established according to permeability ranking of the surface geology. DEM, ETM+8, geologic map, and SPSS were used to characterize the hydrological parameters and delineate the watershed. Ten drainage basins were extracted and characterize for the morphometric analysis. The digital geological distribution, of each basin, was determined from geological and remote sensing data. The morphometric parameters (drainage density, constant channel maintenance, length of overland flow, drainage frequency, and drainage texture ratio) indicate the basins related to medium surface rock permeability (weight score 7-12). Multivariate statistical techniques were investigated using 17 morphometric descriptors (variables). The dendrogram analysis (R-mode) was divided into two cluster, which was subdivided into four groups. BirQueh basin is independent basin due to highest drainage area and perimeter. There is great hydrological similarity between sub basin 9 and 10 (wadi Qena). Wadi Safaga is hydrologically similar to sub basin 3, followed by sub basin 4. The principle component analysis contains four factors and represented by 74% of the total variance in the data. It identifies the promising areas in local scale, so that development and agriculture are easier. Key words: Drainage basins, morphometric parameters, SPSS, central Eastern desert.