Effect of Licorice Extract and Prebiotic on Laying Hen Performance and Egg Quality in the Pre and Early Laying Periods

This study was conducted to investigate the effect of licorice (Glycyrrhizaglabra) extract, Active-mos®prebiotic, and flavomycin antibiotic on performance, egg quality, and body mass status in the pre and early laying periods. A total of 180 Leghorn pullets (Hy-line W-36), were assigned into 6 treatments (5 cages/treatment, 6 pullets/cage) in a completely randomized design. The experimental treatments included control (feed additive-free- diet), and control supplemented by licorice extract (5 and 10 g/kg of diet; as LIEX5 and LIEX10, respectively), flavomycin antibiotic (400 and 650 mg/kg of diet; as FL400 and FL650, respectively), and Active-mos®prebiotic (1 kg/ton of diet; as ACPR). Birds were raised in a cage-layer facility. Body weight, feed intake, and feed conversion ratio were determined weekly. Body mass index was recorded before and after using the treatments. Also, the growth, egg quality, egg cholesterol, serum cholesterol, and triglyceride were tested. During weeks 18 to 19 of age, birds received control, FL650, and ACPR treatments showed greater feed intake compared to LIEX10. The body weight of birds that received FL400 diet was greater than LIEX5 and ACPR treatments at weeks 17 to 19 of age. All treatments, except for ACPR, decreased serum cholesterol compared with the control treatment (P < 0.05). No significant effect on feed conversion ratio, egg production, and body mass index was observed by treatments throughout the study (17-25 wk). Furthermore, there was no significant effect of treatments on the eggs' internal and external quality status, egg cholesterol, and serum triglyceride by treatments. However, more research is needed on the use of licorice extract and prebiotics as antibiotic alternatives and their effects on the body mass index in laying hens during pre- and early-laying periods

Application of artificial intelligence in cognitive load analysis using functional near-infrared spectroscopy:A systematic review

Cognitive load theory suggests that overloading of working memory may negatively affect the performance of human in cognitively demanding tasks. Evaluation of cognitive load is a difficult task; it is often assessed through feedback and evaluation from experts. Cognitive load classification based on Functional Near-InfraRed Spectroscopy (fNIRS) is now one of the key research areas in recent years, due to its resistance of artefacts, cost-effectiveness, and portability. To make fNIRS more practical in various applications, it is necessary to develop robust algorithms that can automatically classify fNIRS signals and less reliant on trained signals. Many of the analytical tools used in cognitive sciences have used Deep Learning (DL) modalities to uncover relevant information for mental workload classification. This review investigates the research questions on the design and overall effectiveness of DL as well as its key characteristics. We have identified 45 studies published between 2011 and 2023, that specifically proposed Machine Learning (ML) models for classifying cognitive load using data obtained from fNIRS devices. Those studies were analyzed based on type of feature selection methods, input, and DL model architectures. Most of the existing cognitive load studies are based on ML algorithms, which follow signal filtration and hand-crafted features. It is observed that hybrid DL architectures that integrate convolution and LSTM operators performed significantly better in comparison with other models. However, DL models especially hybrid models have not been extensively investigated for the classification of cognitive load captured by fNIRS devices. The current trends and challenges are highlighted to provide directions for the development of DL models pertaining to fNIRS research

Adaptive Washout Filter Based on Fuzzy Logic for a Motion Simulation Platform With Consideration of Joints Limitations

Motion simulation platforms (MSPs) are widely used to generate driving/flying motion sensations for the users. The MSPs have a restricted workspace area due to the dynamical and physical restrictions of the Motion Platforms active joints as well as the physical limitations of its passive joints. The motion cueing algorithm (MCA) is the reproduction of the motion signal including linear accelerations and angular velocities. It aims to simultaneously respect the MSP's workspace limitations and make the same motion feeling for the user as a real vehicle. The Classical washout filter (WF) is a well-known type of MCA. The classical WF is easy to set-up, offers a low computational burden and high functionality but has some major drawbacks such as fixed WF parameters tuned according to worst-case scenarios and no consideration of the human vestibular system. As a result, adaptive WFs were developed to consider the human vestibular system and enhance the efficiency of the method using time-varying filters. The existing adaptive WFs only cogitate the boundaries of the end-effector in the Cartesian coordinate space as a substitute for the active and passive joints limitations, which is MSP's main limiting factor. This conservative assumption reduces the available workspace area of the MSP and increases the motion sensation error for the MSPs user. In this study, a fuzzy logic-based WF is developed, to consider the dynamical and physical boundaries of the active joints as well as the physical boundaries of the passive joints. A genetic algorithm is used to select the membership functions values of the active and passive joints boundaries. The model is designed using MATLAB /Simulink and the outcomes demonstrate the efficiency of the proposed method versus existing adaptive WFs

CoV-TI-Net: Transferred Initialization with Modified End Layer for COVID-19 Diagnosis

This paper proposes transferred initialization with modified fully connected layers for COVID-19 diagnosis. Convolutional neural networks (CNN) achieved a remarkable result in image classification. However, training a high-performing model is a very complicated and time-consuming process because of the complexity of image recognition applications. On the other hand, transfer learning is a relatively new learning method that has been employed in many sectors to achieve good performance with fewer computations. In this research, the PyTorch pre-trained models (VGG19\_bn and WideResNet -101) are applied in the MNIST dataset for the first time as initialization and with modified fully connected layers. The employed PyTorch pre-trained models were previously trained in ImageNet. The proposed model is developed and verified in the Kaggle notebook, and it reached the outstanding accuracy of 99.77% without taking a huge computational time during the training process of the network. We also applied the same methodology to the SIIM-FISABIO-RSNA COVID-19 Detection dataset and achieved 80.01% accuracy. In contrast, the previous methods need a huge compactional time during the training process to reach a high-performing model. Codes are available at the following link: github.com/dipuk0506/SpinalNe

Online) An Open Access

ABSTRACT The Aim of This Study Was to Investigate the Effects of Plyometric Exercises on Physical Fitness and Motor Skills Indicators in FiroozAbad City. Subjects were a group of 20 people of handball players city of FiroozAbad formed. The plyometric exercises to train three days per week for eight weeks, and they did. Participants were pre-and post-tests. Plyometric exercises independent variables and change some parameters of physical fitness and fitness-related variables were investigated. The two methods for analyzing data and descriptive statistics, inferential statistics, paired T alpha level was α= 5% .The results showed that plyometric exercises on, muscular strength and, agility and power and has a positive effect. Also plyometric exercise on triple shooting and 3 steps shooting have a positive effect, and shooting on the move with negative effect. As regards to this matter that most of the handball techniques need to jump, sudden shifts explosive movements in hands and legs implementation of plyometric exercises on handball athletes can effects on some fitness factors like power agility and muscle power on the other hand because implementation most sport technique need fitness factors so we can conclude that plyometric exercise can effect on some motion skills of handball. Keywords: Plyometric Exercise, Fitness, Physical Fitness, Motor Skills, Handball INTRODUCTION Physical Education and Sports Science is one of the spheres of human sciences, which is of utmost value in the current era. One of the most important goals of physical education and sport sciences is physical health and nurturing, and the appropriate physical health itself includes vast domains and dimensions. Marinating an appropriate body health is one of these domains, which has an important and determinant role in our daily actions, activities, and sport skills. In sports, athletes usually break their preceding records and achieve new ones. Male and female athletes, around the globe and in all sports, try to achieve better results than before, which these improvements are usually due to the athlete&apos;s increased physical, mental, and technical fitness. This increased fitness in its own turn is due to the coaches and athletes&apos; heightened understanding from their exercises and results. Theoretical exercise is the collectio n of all sport related material from scientific or social sources. These data, alongside the experience and knowledge the trainer has from the athlete, is used to present an effective exercise program. Discovering appropriate methods in order to improve the motor and physical factors has been one of the most important goals pursued by sports scientists, and among them, analyzing exercise methods and their effects has been of utmost importance. Amongst these factors affecting the physical fitness, we could point out the explosive power and potency. Over the past few years, various methods have been used by different researchers and trainers in order to improve this power and potency (Alijani, 2005). One of the effective exercise methods in order to improve the physical fitness is plyometric exercises. These exercises are used in order to improve the athletes&apos; speed and explosive power. Plyometric exercises include some of the prevalent sport moves such as jumping, skipping, and throwing. Plyometric exercises are a series of eccentric contractions which are promptly followed by introvert contractions, which are also known as the stretch-shortening cycle. These types of contractions have a significant effect over the muscular attitude, including the lower limb muscles. These exercises could be performed with the least amount of equipment or even none at all. The most important feature of said exercises, are the improvement of the athlete&apos;s skill pattern (Alijani, 2005)