Identifying Handsaw Tooth Shape Based on the Micro- and Macroscopic Analysis of the Kerf Floor Contour

Skeletal trauma analysis is a major facet of forensic anthropology casework and can entail interpretation of sharp force saw trauma. Hand-powered saws are commonly used in cases of dismemberment and analysis requires differentiating class characteristics. Features of the kerf walls and floor provide information utilized in identifying set, shape, size, power, and direction of sawing motion of the tool. The focus of this study is to examine validity and reliability of determining tooth shape class characteristic (rip versus crosscut) from features of the kerf floor. Two crosscut and three rip handsaws, ranging from 6 to 16 teeth per inch, were used to make 30 incomplete cuts per saw for a total of 150 cuts. Each kerf floor was analyzed macroscopically and microscopically using a digital microscope at 30 × magnification by three observers of different experience levels (expert, experienced, and novice). Profile shapes were classified as U-shaped/concave (rip) or W-shaped/convex (crosscut) by each observer for all 150 cuts. Reliability tests using Cohen’s kappa ranged from substantial in the two less experienced observers to almost perfect in pairwise comparisons with the expert. Microscopic classification accuracy was 94.0% (423/450) for all three observers and macroscopic examination increased accuracy to 99.8% (449/450). Saw wear and tooth size were not a significant determiner in correct identification of saw tooth type. Overall, tooth shape can be reliably and accurately determined from incomplete cuts.

SCANNING ELECTRON MICROSCOPY STUDIES ON PLECTRANTHUS- AN IMPORTANT BEE FORAGE PLANT OF HIMACHAL PRADESH, INDIA

The present investigations were conducted on two important nectar and pollen yielding plants viz. Plecranthus coesta and Plecranthus rugosus from different agro-climatic zones of Himachal Pradesh. The bee forage plants were collected, identified, classified and diffentiating characters of two species were noted. Apart from this, pollen grains of P. coesta and P. rugosus were also studied using light and scanning electron microscope. The pollen grains were observed in terms of aggregation, shape, shape class, size, aperture, polarity, symmetry, surface pattern/exine complexity. Both P. coesta and P. rugosus had solitary medium sized, hexacolpate, isopolar and radially symmetric grains. However, the pollen grain of two species varies in shape and exine complexity. P. coesta pollens were round/ circular and were prolate, whereas in P. rugosus pollens were round/oval and subprolate-prolate. Variation was also found in the exine complexity of the two species. Exine was tectate, tectum was nearly reticulate / scabrate in P. coesta. But in P. rugosus and exine was either tectate or semitectate, tectum was reticulate, microreticulate.

Floral Complexity Traits as Predictors of Plant-Bee Interactions in a Mediterranean Pollination Web

Despite intensive research, predicting pairwise species associations in pollination networks remains a challenge. The morphological fit between flowers and pollinators acts as a filter that allows only some species within the network to interact. Previous studies emphasized the depth of floral tubes as a key shape trait that explains the composition of their animal visitors. Yet, additional shape-related parameters, related to the handling difficulty of flowers, may be important as well. We analyzed a dataset of 2288 visits by six bee genera to 53 flowering species in a Mediterranean plant community. We characterized the plant species by five discrete shape parameters, which potentially affect their accessibility to insects: floral shape class, tube depth, symmetry, corolla segmentation and type of reproductive unit. We then trained a random forest machine-learning model to predict visitor identities, based on the shape traits. The model’s predictor variables also included the Julian date on which each bee visit was observed and the year of observation, as proxies for within- and between-season variation in flower and bee abundance. The model attained a classification accuracy of 0.86 (AUC = 0.96). Using only shape parameters as predictors reduced its classification accuracy to 0.76 (AUC = 0.86), while using only the date and year variables resulted in a prediction accuracy of 0.69 (AUC = 0.80). Among the shape-related variables considered, flower shape class was the most important predictor of visitor identity in a logistic regression model. Our study demonstrates the power of machine-learning algorithms for understanding pollination interactions in a species-rich plant community, based on multiple features of flower morphology.

Evolution of Angiosperm Pollen: 8. Lamiids

Lamiids, a clade composed of approximately 15% of all flowering plants, contains more than 50,000 species dispersed across 49 families and eight orders (APG IV, 2016). This paper is the eighth in a series that analyzes pollen characters across angiosperms. We reconstructed a maximum likelihood tree based on the most recent phylogenetic studies for the Lamiids, comprising 150 terminal genera (including six outgroups) and covering all eight orders and 49 families within the clade. To illustrate pollen diversity across the Lamiids, pollen grains from 22 species (22 genera in 14 families) were imaged under light, scanning, and transmission electron microscopy. Eighteen pollen characters that were documented from previous publications, websites, and our new observations were coded and optimized onto the reconstructed phylogenetic tree using Fitch parsimony, maximum likelihood, and hierarchical Bayesian analysis. Pollen morphology of the Lamiids is highly diverse, particularly in shape class, pollen size, aperture number, endoaperture shape, supratectal element shape, and tectum sculpture. In addition, some genera show relatively high infrageneric pollen variation within the Lamiids: i.e., Coffea L., Jacquemontia Choisy, Justicia L., Pedicularis L., Psychotria L. nom. cons., Sesamum L., Stachytarpheta Vahl, and Veronica L. The plesiomorphic states for 16 pollen characters were inferred unambiguously, and 10 of them displayed consistent plesiomorphic states under all optimization methods. Seventy-one lineages at or above the family level are characterized by pollen character state transitions. We identified diagnostic character states for monophyletic clades and explored palynological evidence to shed light on unresolved relationships. For example, palynological evidence supports the monophyly of Garryales and Metteniusaceae, and sister relationships between Icacinaceae and Oncothecaceae, as well as between Vahliales and Solanales. The evolutionary patterns of pollen morphology found in this study reconfirm several previously postulated evolutionary trends, which include an increase in aperture number, a transition from equatorially arranged apertures to globally distributed ones, and an increase in exine ornamentation complexity. Furthermore, there is a significant correlation between pollen characters and a number of ecological factors, e.g., pollen size and pollination type, pollen ornamentation and pollination type, and shape class and plant growth form. Our results provide insight into the ecological, environmental, and evolutionary mechanisms driving pollen character state changes in the Lamiids.

Klassifizierung von Schmiedeteilen mittels KNN/AI enables automated recognition and classification of geometrically complex forged parts

Im Beitrag wird eine Methode auf Basis Künstlicher Neuronaler Netze vorgestellt, die es erlaubt, schmiedetechnisch hergestellte Bauteile automatisiert zur Einordnung in Formenklassen zu klassifizieren. Dadurch ist es möglich, direkt aus der CAD-Datei des Schmiedeteils eine Formenklasse und für die Auslegung des Prozesses relevante Charakteristika zu ermitteln, die in einem übergeordneten Ziel dazu genutzt werden, eine automatisierte Stadienplanung durchzuführen.   This paper presents a method for the automated classification of forged parts for classification into the Spies order of shapes by artificial neural networks. The aim is to develop a recognition program within the framework of automated forging sequence planning, which can directly identify a shape class from the CAD file of the forged part and characteristics of the forged part relevant for the design of the process.

Adaptation decorrelates shape representations

Perception and neural responses are modulated by sensory history. Visual adaptation, an example of such an effect, has been hypothesized to improve stimulus discrimination by decorrelating responses across a set of neural units. While a central theoretical model, behavioral and neural evidence for this theory is limited and inconclusive. Here, we use a parametric 3D shape-space to test whether adaptation decorrelates shape representations in humans. In a behavioral experiment with 20 subjects, we find that adaptation to a shape class improves discrimination of subsequently presented stimuli with similar features. In a BOLD fMRI experiment with 10 subjects we observe that adaptation to a shape class decorrelates the multivariate representations of subsequently presented stimuli with similar features in object-selective cortex. These results support the long-standing proposal that adaptation improves perceptual discrimination and decorrelates neural representations, offering insights into potential underlying mechanisms.

How Parties Shape Class Politics: Explaining the Decline of the Class Basis of Party Support

Why has the association between class and party declined over time? Contrary to conventional wisdom that emphasizes the fracturing of social structures and blurring of class boundaries in post-industrial society, it is argued here that class divisions in party preferences are conditioned by the changing shape of the class structure and the effect of parties’ strategic ideological responses to this transformation on the choices facing voters. This thesis is tested using British survey data from 1959 to 2006. We demonstrate that increasing class heterogeneity does not account for the decline of the class–party association, which occurs primarily as a result of ideological convergence between the main parties resulting from New Labour's shift to the centre.