In recent decades, global obesity has increased significantly, causing a major health problem with associated complications and major socioeconomic issues. The central nervous system (CNS), particularly the hypothalamus, regulates food intake through sensing the metabolic signals of peripheral organs and modulating feeding behaviors. The hypothalamus interacts with other brain regions such as the brain stem to perform these vital functions. The gut plays a crucial role in controlling food consumption and energy homeostasis. The gut releases orexigenic and anorexigenic hormones that interact directly with the CNS or indirectly through vagal afferent neurons. Gastrointestinal peptides (GIP) including cholecystokinin, peptide YY, Nesfatin-1, glucagon-like peptide 1, and oxyntomodulin send satiety signals to the brain and ghrelin transmit hunger signals to the brain. The GIP is essential for the control of food consumption; thus, explain the link between the gastrointestinal tract (GIT) and the brain is important for managing obesity and its associated diseases. This review aimed to explain the role of gut peptides in satiety and hunger control.
In this research, the results of the Integral breadth method were used to analyze the X-ray lines to determine the crystallite size and lattice strain of the zirconium oxide nanoparticles and the value of the crystal size was equal to (8.2nm) and the lattice strain (0.001955), and then the results were compared with three other methods, which are the Scherer and Scherer dynamical diffraction theory and two formulas of the Scherer and Wilson method.the results were as followsScherer crystallite size(7.4nm)and lattice strain(0.011968),Schererdynamic method crystallite size(7.5 nm),Scherrer and Wilson methodcrystallite size( 8.5nm) and lattice strain( 0.001919).And using another formula for Schearer and Wilson methodwe obtain the size of the c
... Show MoreWe found that 4,5- diphenyl- 3(2- propynyl) thio- 1??-triazole [1? forms a complex with Pd (11) ion of ratio 1:1 which absorbs light in CH2CI2 at 400 nm, and 4,5- diphenyl- 3(2- propenyl) thio- 1,2,4- triazole [II] forms complexes with Pd (II) ion of ratio 1:1 which absorbs light at 390 nm, and of ratio 2:1 which absorbs light at 435 nm. On the other hand, we found that the new derivative 4- phenyl- 5( p- amino phenyl) -3- mercapto- 1,2,4- triazole ?111? forms complexes with Cu (II) ion of the ratio 1:1 which absorbs light at 380 nm, with Ni (II) ion of the ratio 3:1 which absorbs light at 358 nm; and with Co (11) ion of the ratio 3.2:1 which absorbs light at 588 nm. The ratio of the complexes were determined by measuring the electronic spe
... Show MoreIn this paper, an adaptive active disturbance rejection control is newly designed for precise angular steering position tracking of the uncertain and nonlinear SBW system with time delay communications. The proposed adaptive active disturbance rejection control comprises the following two elements: (1) An adaptive extended state observer and (2) an adaptive state error feedback controller. The adaptive extended state observer with adaptive gains is employed for estimating the unmeasured velocity, acceleration, and compound disturbance which consists of system parameter uncertainties, nonlinearities, exterior disturbances, and time delay in which the observer gains are dynamically adjusted based on the estimation error to enhance est
... Show MoreThis research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
The aesthetic and technical expertise help in producing the artistic work and achieving results in aesthetic formulations that reflect the aesthetic and expressive dimensions and the reflective dimensions of the pottery, surpassing its traditions, asserting its active presence in life, cherishing it even when it breaks or get damaged by employing techniques that are originated from the Japanese environment.
The research problem is to study how ( Kintsugi) technique and similar techniques are used to create new rebirths of pottery piec
... Show MoreKE Sharquie, AA Noaimi, HA Al-Mudaris, Journal of Cosmetics, Dermatological Sciences and Applications, 2012 - Cited by 6
In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
... Show MoreThis research aims to develop new spectrophotometric analytical method to determine drug compound Salbutamol by reaction it with ferric chloride in presence potassium ferricyanide in acid median to formation of Prussian blue complex to determine it by uv-vis spectrophotmetric at wavelengths rang(700-750)nm . Study the optimal experimental condition for determination drug and found the follows: 1- Volume of(10M) H2SO4 to determine of drug is 1.5 ml . 2- Volume and concentration of K3Fe(CN)6 is 1.5 ml ,0.2% . 3- Volume and concentration of FeCl3 is 2.5ml , 0.2%. 4- Temperature has been found 80 . 5- Reaction time is 15 minute . 6- Order of addition is (drug + K3Fe(CN)6+ FeCl3 + acid) . Concentration rang (0.025-5 ppm) , limit detecti
... Show MoreCorrect grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
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