Here we determined the structure of a cold active family IV esterase (EstN7) cloned from Bacillus cohnii strain N1. EstN7 is a dimer with a classical α/β hydrolase fold. It has an acidic surface that is thought to play a role in cold-adaption by retaining solvation under changed water solvent entropy at lower temperatures. The conformation of the functionally important cap region is significantly different to EstN7's closest relatives, forming a bridge-like structure with reduced helical content providing greater access to the active site through more than one substrate access tunnel. However, dynamics do not appear to play a major role in cold adaption. Molecular dyn

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Maintaining the quality of apricot fruits during storage is not an easy task due to the changes in their physical and chemical properties, so it is necessary to use less expensive, easy to apply, environmentally friendly, and safer preservatives to maintain the nutritional value of apricot. The damage to some fruits during storage can be a source of infection, which leads to the damage of healthy fruits more quickly, which requires building an intelligent model to detect damaged fruits. The aim of the research is to study the effect of immersing apricots in lemon juice once and sugar-water solution again on the quality properties of apricots, including sweetness, color, hardness, and water content. On the other hand, the YOLOv7 algorithm wa

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

Background: Periodontitis is an inflammatory disease that affects the supporting tissues of the teeth; Smoking is an important risk factor for periodontitis induces alveolar bone loss and cause an imbalance between bone resorption and bone deposition. The purpose of this study is to detect and compare the presence of incipient periodontitis among young smokers and non-smokers by measuring the distance between cement-enamel junction and alveolar crest (CEJ-Ac) using Cone Beam Computed Tomography (CBCT). Material and methods: The total sample composed of fifty two participants, thirty one smokers and twenty one non-smokers (age range 14-22 years). Periodontal parameters: plaque index (PLI), gingival index (GI) were recorded for all teeth exc

A procedure for the mutual derivatization and determination of thymol and Dapsone was developed and validated in this study. Dapsone was used as the derivatizing agent for the determination of thymol, and thymol was used as the derivatizing agent for the determination of Dapsone. An optimization study was performed for the derivatization reaction; i.e., the diazonium coupling reaction. Linear regression calibration plots for thymol and Dapsone in the direct reaction were constructed at 460 nm, within the concentration range of 0.3-7 μg ml-1 for thymol and 0.3-4 μg ml-1 for Dapsone, with limits of detection 0.086 and 0.053 μg ml-1, respectively. Corresponding plots for the cloud point extraction of thymol and Dapsone were constructed

Basically, media studies focused on the important role of the blogs in boosting the democratic process in the Arab States. Blogs also worked on creating an alternative media for the public that maintained freedom of expression. However, media studies ignored the status of the blogs in the social and cultural fields.
The current study tries to tackle the socio-cultural dimensions of the blogs by means of showing how the blogs construct the self. The researcher is going to conduct interviews with the bloggers. He will also carry out a semiotic analysis that may reveal the strategies used by the bloggers. Besides, he tries to identify the realistic and traditional frames in which the social relationships are buil

This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that