Odontogenesis is a complex process regulated by both genetic and molecular controls. The development of a tooth in the embryo stage is controlled by a series of signals which occur between tooth-forming epithelium and neural crest-derived ectomesenchyme. Though many genes are involved in tooth formation involving major signalling molecules, the bone morphogenetic protein and fibroblast growth factor are the most important ones involved in odontogenesis. Supernumerary tooth occurs because of imbalance in the expression of the signalling pathways and their inhibitors. This review highlights the various signalling molecules that play a role in odontogenesis in order to provide a better understanding on of the molecular mechanisms involved in the formation of supernumerary tooth in humans.
Compelling facial expression recognition (FER) processes have been utilized in very successful fields like computer vision, robotics, artificial intelligence, and dynamic texture recognition. However, the FER's critical problem with traditional local binary pattern (LBP) is the loss of neighboring pixels related to different scales that can affect the texture of facial images. To overcome such limitations, this study describes a new extended LBP method to extract feature vectors from images, detecting each image from facial expressions. The proposed method is based on the bitwise AND operation of two rotational kernels applied on LBP(8,1) and LBP(8,2) and utilizes two accessible datasets. Firstly, the facial parts are detected and the essential components of a face are observed, such as eyes, nose, and lips. The portion of the face is then cropped to reduce the dimensions and an unsharp masking kernel is applied to sharpen the image. The filtered images then go through the feature extraction method and wait for the classification process. Four machine learning classifiers were used to verify the proposed method. This study shows that the proposed multi-scale featured local binary pattern (MSFLBP), together with Support Vector Machine (SVM), outperformed the recent LBP-based state-of-the-art approaches resulting in an accuracy of 99.12% for the Extended Cohn-Kanade (CK+) dataset and 89.08% for the Karolinska Directed Emotional Faces (KDEF) dataset.
Among the various types of decorative materials used in Bangladeshi dwellings, the marble/marble stone is one of the most common ones that used largely for enhancing the beauty and/or aristocracy of the dwelling environment. In this study, the most commonly used, six types of marble stones, have been analyzed for retrospective accident dosimetry. With the interest of characterizing several key thermoluminescence properties to examine their potentiality for dosimetry, annealing - irradiation - readout steps have been done chronologically which comprises the analysis of glow curves, relative sensitivity, dose dependence, repeatability and fading. Considering the various TL parameters, marble 'Carrara' imported from Italy present relatively better capability for reconstruction of radiation dose in the dose range of 10-50 Gy. From fading result, it is clear that for reconstruction of absorbed dose up to four weeks of post exposure, the marble 'Carrara' is found to be the most reliable media among the studied marble types. The Zeff values for the various marble samples are found to be in the range of 13.65-19.12, comparing favorably in replace of TLD-200 (Zeff = 16.3) which can be used for low-level environmental radiation dosimetry. Present work constitutes the first study to investigate the potentials of marble stone for reconstruction of absorbed dose in the range of 10-50 Gy dose.
Sign Language Recognition is a breakthrough for communication among deaf-mute society and has been a critical research topic for years. Although some of the previous studies have successfully recognized sign language, it requires many costly instruments including sensors, devices, and high-end processing power. However, such drawbacks can be easily overcome by employing artificial intelligence-based techniques. Since, in this modern era of advanced mobile technology, using a camera to take video or images is much easier, this study demonstrates a cost-effective technique to detect American Sign Language (ASL) using an image dataset. Here, "Finger Spelling, A" dataset has been used, with 24 letters (except j and z as they contain motion). The main reason for using this dataset is that these images have a complex background with different environments and scene colors. Two layers of image processing have been used: in the first layer, images are processed as a whole for training, and in the second layer, the hand landmarks are extracted. A multi-headed convolutional neural network (CNN) model has been proposed and tested with 30% of the dataset to train these two layers. To avoid the overfitting problem, data augmentation and dynamic learning rate reduction have been used. With the proposed model, 98.981% test accuracy has been achieved. It is expected that this study may help to develop an efficient human-machine communication system for a deaf-mute society.
The title CuII macrocyclic complex salt tetra-hydrate, [Cu(C22H46N6O2)](C2H3O2)2·4H2O, sees the metal atom located on a centre of inversion and coordinated within a 4 + 2 (N4O2) tetra-gonally distorted coordination geometry; the N atoms are derived from the macrocycle and the O atoms from weakly associated [3.2048 (15) Å] acetate anions. Further stability to the three-ion aggregate is provided by intra-molecular amine-N-H⋯O(carboxyl-ate) hydrogen bonds. Hydrogen bonding is also prominent in the mol-ecular packing with amide-N-H⋯O(amide) inter-actions, leading to eight-membered {⋯HNCO}2 synthons, amide-N-H⋯O(water), water-O-H⋯O(carboxyl-ate) and water-O-H⋯O(water) hydrogen bonds featuring within the three-dimensional architecture. The calculated Hirshfeld surfaces for the individual components of the asymmetric unit differentiate the water mol-ecules owing to their distinctive supra-molecular association. For each of the anion and cation, H⋯H contacts predominate (50.7 and 65.2%, respectively) followed by H⋯O/O⋯H contacts (44.5 and 29.9%, respectively).